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feat: add GitHub Codespaces deployment support

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- Add DevContainer configuration for Codespaces
- Add GitHub Actions workflows for automation
- Add Ollama support to Memory plugin
- Add comprehensive documentation
This commit is contained in:
Claude Code 2026-01-30 14:02:05 +08:00
parent e274d4d781
commit cbf7417c0f
3045 changed files with 197200 additions and 42 deletions
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.devcontainer/devcontainer.json Normal file
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{
"name": "Moltbot Gateway",
"image": "mcr.microsoft.com/devcontainers/javascript-node:22-bookworm",
"features": {
"ghcr.io/devcontainers/features/common-utils:2": {}
},
"customizations": {
"vscode": {
"extensions": [
"dbaeumer.vscode-eslint",
"esbenp.prettier-vscode",
"ms-vscode.vscode-typescript-next"
],
"settings": {
"terminal.integrated.defaultProfile.linux": "bash"
}
}
},
"forwardPorts": [18789, 18791, 11434],
"portsAttributes": {
"18789": {
"label": "Gateway WebSocket",
"onAutoForward": "openBrowser"
},
"11434": {
"label": "Ollama API"
}
},
"postCreateCommand": "bash .devcontainer/post-create.sh",
"hostRequirements": {
"cpus": 4,
"memory": "8gb",
"storage": "32gb"
}
}

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version: '3.8'
services:
moltbot:
build:
context: .
dockerfile: Dockerfile
volumes:
- ../..:/workspace:cached
- moltbot-data:/root/.clawdbot
- moltbot-memory:/root/.clawdbot/memory
ports:
- "18789:18789"
- "18791:18791"
cap_add:
- SYS_PTRACE
security_opt:
- seccomp:unconfined
command: sleep infinity
network_mode: host
volumes:
moltbot-data:
moltbot-memory:

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#!/bin/bash
set -e
echo "=========================================="
echo " Moltbot Gateway - Initial Setup"
echo "=========================================="
echo ""
# 颜色定义
GREEN='\033[0;32m'
YELLOW='\033[1;33m'
BLUE='\033[0;34m'
NC='\033[0m' # No Color
# ============================================================
# 1. 安装构建工具
# ============================================================
echo -e "${BLUE}[1/6] Installing build tools...${NC}"
echo ""
# 安装 Bun
echo "Installing Bun..."
curl -fsSL https://bun.sh/install | bash
export PATH="$HOME/.bun/bin:${PATH}"
echo 'export PATH="$HOME/.bun/bin:${PATH}"' >> $HOME/.bashrc
# 启用 corepack（安装 pnpm/yarn）
echo "Enabling corepack..."
corepack enable
echo -e "${GREEN}✓ Build tools installed!${NC}"
# ============================================================
# 2. 安装 Ollama（需要 root 权限）
# ============================================================
echo ""
echo -e "${BLUE}[2/6] Installing Ollama...${NC}"
echo ""
# 检查是否需要 sudo
if command -v sudo &> /dev/null; then
curl -fsSL https://ollama.com/install.sh | sudo sh
else
curl -fsSL https://ollama.com/install.sh | sh
fi
# 启动 Ollama 服务
echo -e "${GREEN}Starting Ollama service...${NC}"
# 后台启动 Ollama
ollama serve > /tmp/ollama.log 2>&1 &
OLLAMA_PID=$!
sleep 5
# 等待 Ollama 启动
echo "Waiting for Ollama to be ready..."
for i in {1..30}; do
if curl -s http://127.0.0.1:11434/api/tags > /dev/null 2>&1; then
echo -e "${GREEN}✓ Ollama is ready!${NC}"
break
fi
echo "Waiting... ($i/30)"
sleep 2
done
# ============================================================
# 3. 安装 LLM 模型
# ============================================================
echo ""
echo -e "${BLUE}[3/6] Pulling LLM models...${NC}"
echo ""
echo "Installing nomic-embed-text (embeddings)..."
ollama pull nomic-embed-text
echo "Installing llama3.3 (main model)..."
ollama pull llama3.3
echo "Installing deepseek-coder (code assistant)..."
ollama pull deepseek-coder
echo -e "${GREEN}✓ All models installed!${NC}"
# ============================================================
# 4. 配置 Moltbot
# ============================================================
echo ""
echo -e "${BLUE}[4/6] Configuring Moltbot...${NC}"
echo ""
# 创建配置目录
mkdir -p $HOME/.clawdbot/memory
# 创建配置文件
cat > $HOME/.moltbot/moltbot.json << 'EOF'
{
"gateway": {
"mode": "local",
"bind": "0.0.0.0",
"auth": {
"token": "github-codespaces-token"
}
},
"models": {
"mode": "merge",
"providers": {
"ollama": {
"baseUrl": "http://127.0.0.1:11434",
"models": [
{
"id": "llama3.3",
"name": "Llama 3.3",
"reasoning": false,
"input": ["text"],
"cost": { "input": 0, "output": 0 },
"contextWindow": 128000,
"maxTokens": 8192
},
{
"id": "deepseek-coder",
"name": "DeepSeek Coder",
"reasoning": false,
"input": ["text"],
"cost": { "input": 0, "output": 0 },
"contextWindow": 128000,
"maxTokens": 8192
}
]
}
}
},
"agents": {
"defaults": {
"model": {
"primary": "ollama/llama3.3",
"fallbacks": ["ollama/deepseek-coder"]
},
"workspace": "$HOME/.clawdbot/workspace",
"maxConcurrent": 4
}
},
"browser": {
"enabled": true
},
"plugins": {
"entries": {
"memory-lancedb": {
"enabled": true,
"config": {
"embedding": {
"provider": "ollama",
"model": "nomic-embed-text",
"baseUrl": "http://127.0.0.1:11434/v1"
},
"autoCapture": true,
"autoRecall": true
}
}
},
"slots": {
"memory": "memory-lancedb"
}
}
}
EOF
echo -e "${GREEN}✓ Configuration created!${NC}"
# ============================================================
# 5. 构建项目
# ============================================================
echo ""
echo -e "${BLUE}[5/6] Building Moltbot...${NC}"
echo ""
# 确保在正确的目录
cd /workspace
# 安装依赖
echo "Installing dependencies..."
pnpm install --frozen-lockfile
# 构建
echo "Building project..."
CLAWDBOT_A2UI_SKIP_MISSING=1 pnpm build
echo -e "${GREEN}✓ Build complete!${NC}"
# ============================================================
# 6. 启动 Gateway
# ============================================================
echo ""
echo -e "${BLUE}[6/6] Starting Gateway...${NC}"
echo ""
# 创建启动脚本
cat > $HOME/start-gateway.sh << 'EOF'
#!/bin/bash
set -e
# 确保环境变量正确
export PATH="$HOME/.bun/bin:${PATH}"
# 启动 Ollama（如果还没运行）
if ! pgrep -x "ollama" > /dev/null; then
echo "Starting Ollama..."
ollama serve > /tmp/ollama.log 2>&1 &
sleep 5
fi
# 启动 Moltbot Gateway
echo "Starting Moltbot Gateway..."
cd /workspace
# 使用 nohup 在后台运行
nohup node /workspace/moltbot.mjs gateway \
--bind 0.0.0.0 \
--port 18789 \
> /tmp/moltbot.log 2>&1 &
GATEWAY_PID=$!
echo $GATEWAY_PID > /tmp/moltbot.pid
echo ""
echo "=========================================="
echo " Moltbot Gateway Started!"
echo "=========================================="
echo ""
echo "Gateway PID: $GATEWAY_PID"
echo "Logs: tail -f /tmp/moltbot.log"
echo ""
echo "To stop: kill $GATEWAY_PID"
echo " or: pkill -f moltbot.mjs"
echo ""
EOF
chmod +x $HOME/start-gateway.sh
# 启动 Gateway
$HOME/start-gateway.sh
# 等待 Gateway 启动
sleep 5
# 验证 Gateway 是否运行
if pgrep -f "moltbot.mjs gateway" > /dev/null; then
echo -e "${GREEN}✓ Gateway is running!${NC}"
else
echo -e "${YELLOW}⚠ Gateway may not be starting properly. Check logs:${NC}"
echo "tail -f /tmp/moltbot.log"
fi
# ============================================================
# 完成
# ============================================================
echo ""
echo "=========================================="
echo " Setup Complete!"
echo "=========================================="
echo ""
echo -e "${GREEN}Your Moltbot Gateway is ready!${NC}"
echo ""
echo "🌐 Access URLs:"
echo " • Port Forwarding: Port 18789"
echo ""
echo "📝 Next Steps:"
echo " 1. Click 'Ports' tab in Codespaces"
echo " 2. Forward port 18789"
echo " 3. Access the WebChat"
echo ""
echo "🔧 Useful Commands:"
echo " • Gateway status: cd /workspace && ./moltbot.mjs status"
echo " • View logs: tail -f /tmp/moltbot.log"
echo " • Restart Gateway: ~/start-gateway.sh"
echo " • Test connection: ./moltbot.mjs agent 'test'"
echo ""
echo "📚 Documentation:"
echo " • GITHUB-QUICKSTART.md"
echo " • QUICKSTART.md"
echo " • DEVELOPMENT-SETUP.md"
echo ""

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# 🚀 Moltbot GitHub 部署指南
> **在 GitHub Codespaces 上运行你的私人 AI Assistant，随时随地访问！**
## 📋 目录
- [为什么选择 GitHub 部署？](#为什么选择-github-部署)
- [架构概述](#架构概述)
- [快速开始](#快速开始)
- [详细配置](#详细配置)
- [访问方式](#访问方式)
- [自动化维护](#自动化维护)
- [故障排除](#故障排除)
- [最佳实践](#最佳实践)
---
## 为什么选择 GitHub 部署？
### ✅ 优势
| 特性 | GitHub Codespaces | 自建服务器 |
|------|------------------|-----------|
| **成本** | 每月免费额度（60小时） | 需要购买服务器 |
| **维护** | 零维护 | 需要运维 |
| **可访问性** | 任何有浏览器的地方 | 需要 VPN/公网 IP |
| **开发环境** | 完整 VS Code | 需要本地配置 |
| **协作** | 即时分享 | 需要配置 |
| **备份** | 自动集成 Git | 需要手动备份 |
### 💰 成本
- **免费额度**: 60 小时/月
- **超时后**: $0.18/小时
- **推荐**: 日常开发完全够用
---
## 架构概述
```
┌─────────────────────────────────────────────────────────────────────┐
│ GitHub 部署架构 │
├─────────────────────────────────────────────────────────────────────┤
│ │
│ ┌─────────────────────────────────────────────────────────────┐ │
│ │ GitHub Codespaces (云端环境) │ │
│ │ ┌──────────────────────────────────────────────────────────┐ │ │
│ │ │ Moltbot Gateway (持续运行) │ │ │
│ │ │ ───────────────────────────────────────────────────── │ │ │
│ │ │ • Node.js v22 + pnpm │ │ │
│ │ │ • Ollama (本地 LLM) │ │ │
│ │ │ │ - llama3.3 (主模型) │ │ │
│ │ │ │ - deepseek-coder (代码助手) │ │ │
│ │ │ │ - nomic-embed-text (embeddings) │ │ │
│ │ │ • Memory Plugin (LanceDB) │ │ │
│ │ │ • WebSocket Server (18789) │ │ │
│ │ │ • 所有开发插件 │ │ │
│ │ └──────────────────────────────────────────────────────────┘ │ │
│ │ │ │
│ │ 硬件配置: │ │
│ │ • 4 核 CPU │ │
│ │ • 8 GB RAM │ │
│ │ • 32 GB 存储 │ │
│ │ │ │
│ └─────────────────────────────────────────────────────────────┘ │
│ ▲ │
│ │ │
│ ┌───────────────┴──────────────────┐ │
│ │ GitHub Port Forwarding │ │
│ │ (Codespaces → Internet) │ │
│ └───────────────────────────────┘ │
│ │ │
│ ┌──────────────────────┬──────────────────┐ │
│ ▼ ▼ ▼ │
│ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │
│ │ VS Code │ │ 浏览器 │ │ GitHub CLI │ │
│ │ (本地连接) │ │ WebChat │ │ (命令行) │ │
│ │ │ │ │ │ │ │
│ │ • 编辑代码 │ │ • 对话 │ │ • gh ci run │ │
│ │ • 调试 │ │ • 测试 │ │ • 管理任务 │ │
│ │ • 终端 │ │ • 监控 │ │ │ │
│ └─────────────┘ └─────────────┘ └─────────────┘ │
│ │
│ ┌─────────────────────────────────────────────────────────────┐ │
│ │ GitHub Actions (自动化) │ │
│ │ ──────────────────────────────────────────────────────── │ │
│ │ • 自动部署 │ │
│ │ • 每日健康检查 │ │
│ │ • Memory 自动备份 │ │
│ │ • 定时重启 │ │
│ │ • 监控报告 │ │
│ └─────────────────────────────────────────────────────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────────┘
```
---
## 快速开始
### 方式 1：通过 GitHub 网页创建（推荐）
#### 步骤 1：创建 Codespace
1. 访问你的仓库：`https://github.com/你的用户名/moltbot`
2. 点击绿色的 **"Code"** 按钮
3. 选择 **"Codespaces"** 标签
4. 点击 **"Create codespace on main"**
5. 等待环境创建（约 2-3 分钟）
#### 步骤 2：自动初始化
Codespace 创建后会自动运行：
- ✅ 安装 Node.js 和 pnpm
- ✅ 安装 Ollama
- ✅ 拉取 LLM 模型（llama3.3, deepseek-coder, nomic-embed-text）
- ✅ 配置 Moltbot
- ✅ 构建项目
- ✅ 启动 Gateway
#### 步骤 3：访问 Gateway
创建完成后：
1. **查看日志**：
- 在 Codespace 终端运行：`tail -f /tmp/moltbot.log`
2. **配置端口转发**：
- 点击 Codespace 界面的 **"Ports"** 标签
- 添加端口：`18789`
- 点击转发地址访问 WebChat
3. **测试连接**：
```bash
./moltbot.mjs status
./moltbot.mjs agent "你好，请介绍一下你自己"
```
---
### 方式 2：通过 GitHub CLI 创建
#### 步骤 1：安装 GitHub CLI
```bash
# macOS
brew install gh
# Linux
sudo apt install gh
# 或下载: https://github.com/cli/cli/releases
# Windows
winget install GitHub.cli
```
#### 步骤 2：认证
```bash
gh auth login
```
#### 步骤 3：创建 Codespace
```bash
gh codespace create \
--repo 你的用户名/moltbot \
--branch main \
--machine standard-4cores-linux-x64 \
--display-name "Moltbot Gateway"
```
#### 步骤 4：等待初始化完成
```bash
# 查看 Codespace 状态
gh codespace list
# 查看 Codespace 日志
gh codespace logs
```
---
## 详细配置
### Codespaces 配置文件
#### 1. `.devcontainer/devcontainer.json`
定义开发环境配置：
```json
{
"name": "Moltbot Gateway",
"dockerComposeFile": "docker-compose.yml",
"service": "moltbot",
// 资源要求
"hostRequirements": {
"cpus": 4, // 4 核 CPU
"memory": "8gb", // 8 GB RAM
"storage": "32gb" // 32 GB 存储
},
// 端口转发
"forwardPorts": [18789, 18791, 11434],
// 端口属性
"portsAttributes": {
"18789": {
"label": "Gateway WebSocket",
"onAutoForward": "openBrowser" // 自动打开浏览器
}
},
// 自动运行脚本
"postCreateCommand": "bash .devcontainer/post-create.sh"
}
```
#### 2. `.devcontainer/post-create.sh`
初始化脚本会自动执行：
1. 安装 Ollama
2. 拉取 LLM 模型
3. 配置 Moltbot
4. 构建项目
5. 启动 Gateway
#### 3. `.devcontainer/docker-compose.yml`
Docker 服务定义：
```yaml
services:
moltbot:
volumes:
# 持久化数据
- moltbot-data:/root/.clawdbot
- moltbot-memory:/root/.clawdbot/memory
```
### 配置 Gateway
在 Codespace 中的配置文件位置：
```bash
/root/.moltbot/moltbot.json
```
默认配置：
```json
{
"gateway": {
"mode": "local",
"bind": "0.0.0.0", // 绑定所有接口（可外部访问）
"auth": {
"token": "github-codespaces-token"
}
},
"models": {
"providers": {
"ollama": {
"baseUrl": "http://127.0.0.1:11434"
}
}
},
"plugins": {
"entries": {
"memory-lancedb": {
"enabled": true,
"config": {
"embedding": {
"provider": "ollama",
"model": "nomic-embed-text"
}
}
}
}
}
}
```
---
## 访问方式
### 方式 1：浏览器 WebChat（推荐）
```
1. 打开你的 Codespace
2. 点击 "Ports" 标签
3. 找到 18789 端口
4. 点击转发地址（通常是一个 github.dev URL）
5. 开始对话！
```
### 方式 2：VS Code 连接
```
1. 在 VS Code 中安装 "Remote - SSH" 扩展
2. 连接到 Codespace
3. 打开集成终端
4. 运行命令：
./moltbot.mjs agent "消息"
```
### 方式 3：本地 CLI 客户端
在你的本地机器上配置：
```json
// ~/.clawdbot/moltbot.json
{
"gateway": {
"mode": "remote",
"remote": {
"url": "wss://<codespace-name>-18789.github.dev",
"token": "github-codespaces-token"
}
}
}
```
### 方式 4：GitHub Actions CLI
```bash
# 触发健康检查
gh workflow run github-deploy.yml -f health-check
# 查看状态
gh run list
# 查看日志
gh run view <run-id>
```
---
## 自动化维护
### GitHub Actions 工作流
#### 1. 自动健康检查（每天 UTC 2:00）
```yaml
on:
schedule:
- cron: '0 2 * * *' # 每天执行
```
**功能：**
- ✅ 检查 Gateway 配置
- ✅ 验证服务状态
- ✅ 生成状态报告
#### 2. 自动备份 Memory
**功能：**
- ✅ 导出 LanceDB 数据库
- ✅ 上传到 GitHub Artifacts
- ✅ 保留 30 天
#### 3. 自动重启（可选）
```bash
# 手动触发
gh workflow run github-deploy.yml -f restart-gateway
```
### 监控和日志
#### 查看 Gateway 日志
```bash
# 在 Codespace 终端
tail -f /tmp/moltbot.log
# 查看最近 100 行
tail -n 100 /tmp/moltbot.log
```
#### 查看 Ollama 日志
```bash
tail -f /tmp/ollama.log
```
#### 检查服务状态
```bash
# Gateway 状态
./moltbot.mjs status
# 会话列表
./moltbot.mjs sessions
# Memory 统计
./moltbot.mjs ltm stats
```
---
## 故障排除
### 问题 1：Codespace 创建失败
**症状：**
```
Error: Failed to create codespace
```
**解决方案：**
1. 检查 GitHub 账号权限
2. 确认没有超过 Codespace 限制
3. 尝试删除旧的 Codespace：
```bash
gh codespace list
gh codespace delete <codespace-name>
```
### 问题 2：Ollama 模型下载失败
**症状：**
```
Error: Failed to pull ollama model
```
**解决方案：**
```bash
# 手动下载模型
ollama pull llama3.3
# 或使用小模型
ollama pull phi3
```
### 问题 3：Gateway 无法启动
**症状：**
```
Error: Gateway failed to start
```
**解决方案：**
```bash
# 检查端口占用
netstat -tlnp | grep 18789
# 杀死占用进程
pkill -f moltbot.mjs
# 重新启动
/root/start-gateway.sh
```
### 问题 4：内存不足
**症状：**
```
Error: Cannot allocate memory
```
**解决方案：**
1. **使用较小的模型**：
```bash
ollama pull phi3 # 4GB
ollama pull gemma2:2b # 2GB
```
2. **增加 Codespace 配额**：
- GitHub 设置 → Billing
- 增加 Codespace 配额
3. **优化配置**：
```json
{
"agents": {
"defaults": {
"maxConcurrent": 2 // 减少并发数
}
}
}
```
### 问题 5：端口转发不工作
**症状：**
```
Cannot access forwarded port
```
**解决方案：**
1. 检查 Codespace 是否正在运行
2. 重新配置端口转发
3. 使用 GitHub CLI 连接：
```bash
gh codespace view --web
```
---
## 最佳实践
### 1. 成本优化
**减少 Codespace 使用时间：**
```bash
# 不使用时停止 Codespace
gh codespace stop
# 需要时再启动
gh codespace start
```
### 2. 数据持久化
**重要数据备份：**
```bash
# 备份配置
cp /root/.moltbot/moltbot.json ~/backup/
# 备份 Memory
tar -czf ~/backup/memory-$(date +%Y%m%d).tar.gz ~/.clawdbot/memory/
# 下载备份到本地
gh codespace download backup.tar.gz
```
### 3. 安全配置
**保护你的 Gateway：**
```json
{
"gateway": {
"auth": {
"token": "生成一个强密码",
"allowTailscale": false // 仅 GitHub 登录
}
}
}
```
### 4. 监控和告警
**设置 GitHub Actions 通知：**
```yaml
# .github/workflows/notifications.yml
name: Notifications
on:
workflow_run:
workflows: ["github-deploy.yml"]
types: [completed]
jobs:
notify:
runs-on: ubuntu-latest
steps:
- name: Send notification
run: |
echo "Gateway health check completed"
```
### 5. 开发工作流
**推荐的工作流：**
```bash
# 1. 本地开发
git clone <repo>
cd moltbot
# 2. 提交更改
git add .
git commit -m "feat: new feature"
git push
# 3. 自动部署到 Codespace
# GitHub Actions 自动触发
# 4. 在 Codespace 中测试
gh codespace view --web
# 5. 验证后合并到 main
git checkout main
git merge feature-branch
git push
```
---
## 高级配置
### 自定义域名
你可以使用自己的域名访问 Gateway：
1. **设置 CNAME**：
```
moltbot.yourdomain.com CNAME <codespace-name>.github.dev
```
2. **更新配置**：
```json
{
"gateway": {
"bind": "moltbot.yourdomain.com"
}
}
```
### 集成其他服务
#### 1. Telegram Bot
```bash
# 在 Codespace 中配置 Telegram Bot Token
# 编辑 ~/.moltbot/moltbot.json
# 重启 Gateway
/root/start-gateway.sh
```
#### 2. GitHub 集成
```bash
# 使用 GitHub 作为 Memory 存储
# 配置 GitHub Actions 自动备份
```
#### 3. Slack 集成
```bash
# 配置 Slack Webhook
# 接收 Gateway 通知
```
### 性能优化
#### 1. 模型量化
```bash
# 使用量化版本
ollama pull llama3.3:q4_0
```
#### 2. 批处理
```bash
# 批量处理请求
./moltbot.mjs agent --batch <<EOF
{"message": "消息1"}
{"message": "消息2"}
{"message": "消息3"}
EOF
```
#### 3. 缓存优化
```json
{
"agents": {
"defaults": {
"compaction": {
"mode": "safeguard"
}
}
}
}
```
---
## 与本地开发结合
### 混合架构
```
┌─────────────────────────────────────────────────────────────────────┐
│ 混合开发架构 │
├─────────────────────────────────────────────────────────────────────┤
│ │
│ GitHub Codespaces 本地开发机 │
│ ┌─────────────────────┐ ┌─────────────────────┐ │
│ │ Gateway (生产) │ │ Gateway (测试) │ │
│ │ - 稳定运行 │ │ - 快速测试 │ │
│ │ - 24/7 可用 │ │ - 离线开发 │ │
│ │ - 远程访问 │ │ - 本地调试 │ │
│ └─────────────────────┘ └─────────────────────┘ │
│ ▲ ▲ │
│ │ │ │
│ │ 同步代码和配置 │
│ └──────────────────────┬───────────────────────┘ │
│ │ │
│ Git Push / Pull │
│ │
│ 工作流： │
│ 1. 本地开发新功能 │
│ 2. 本地测试 │
│ 3. 推送到 GitHub │
│ 4. 自动部署到 Codespace │
│ 5. 远程 Gateway 更新 │
│ │
└─────────────────────────────────────────────────────────────────────┘
```
### 代码同步
```bash
# 本地开发
cd /path/to/moltbot
# 开发新功能
git add .
git commit -m "feat: new feature"
git push origin main
# Codespace 自动更新
# 或手动在 Codespace 中
cd /workspace
git pull
pnpm build
/root/start-gateway.sh
```
---
## 监控和日志
### GitHub Actions 监控
查看 Actions 运行历史：
```bash
# 列出运行历史
gh run list --workflow=github-deploy.yml
# 查看特定运行
gh run view <run-id>
# 下载日志
gh run download <run-id>
```
### Codespace 监控
```bash
# 查看 Codespace 状态
gh codespace view
# 查看资源使用
gh codespace view --json | jq '.resource'
# 停止 Codespace
gh codespace stop
# 删除 Codespace
gh codespace delete
```
### 日志管理
```bash
# 日志位置
/tmp/moltbot.log # Gateway 日志
/tmp/ollama.log # Ollama 日志
~/.pm2/logs/ # PM2 日志（如果使用）
# 查看实时日志
tail -f /tmp/moltbot.log
# 搜索错误
grep -i error /tmp/moltbot.log
```
---
## 成本和限制
### 免费额度
| 资源 | 免费额度 | 超出后费用 |
|------|---------|-----------|
| **存储** | 32 GB | $0.08/GB/月 |
| **计算** | 60 小时/月 | $0.18/小时 |
| **带宽** | 包含在内 | 无额外费用 |
### 使用估算
**日常开发使用：**
- 每天 8 小时 × 22 天 = 176 小时
- 超出免费额度：116 小时
- 额外成本：116 × $0.18 = $20.88/月
**成本优化技巧：**
1. 不使用时停止 Codespace
2. 使用 smaller 机型（2 核）
3. 避免空闲运行
---
## 总结
### GitHub Codespaces 部署的优势
| 特性 | 说明 |
|------|------|
| ✅ **零配置** | 创建即用，无需手动配置环境 |
| ✅ **随时随地** | 任何有浏览器的地方都能访问 |
| ✅ **自动备份** | 集成 Git，自动版本控制 |
| ✅ **团队协作** | 即时分享和协作 |
| ✅ **免费额度** | 每月 60 小时免费 |
| ✅ **自动化** | GitHub Actions 自动维护 |
### 适用场景
- ✅ **个人开发者** - 无服务器，快速部署
- ✅ **团队协作** - 共享开发环境
- ✅ **演示展示** - 向客户展示功能
- ✅ **临时项目** - 短期测试和验证
- ✅ **学习研究** - 学习 AI 和 LLM 集成
### 不适用场景
- ❌ **大规模生产** - 需要更高性能
- ❌ **24/7 运行** - 成本较高
- ❌ **数据敏感** - 需要本地存储
---
## 相关文档
- **QUICKSTART.md** - 快速上手指南
- **DEVELOPMENT-SETUP.md** - 完整架构指南
- **TEAM.md** - 团队成员参考
---
**文档版本**: 1.0
**最后更新**: 2025-01-30
**维护者**: 开发团队

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@ -0,0 +1,24 @@
name: Moltbot Gateway
targetPort: 18789
displayName: Moltbot Gateway
description: Personal AI Assistant with Ollama integration
icon: https://raw.githubusercontent.com/moltbot/moltbot/main/docs/whatsapp-clawd.jpg
documentation: https://github.com/moltbot/moltbot/blob/main/.github/GITHUB-DEPLOY.md
features:
- devcontainer
permissions:
contents: read
issues: read
pull_requests: read
devContainer:
extensions:
- dbaeumer.vscode-eslint
- esbenp.prettier-vscode
- ms-vscode.vscode-typescript-next
repository:
url: https://github.com/moltbot/moltbot
contact:
- type: issue
url: https://github.com/moltbot/moltbot/issues
- type: discussion
url: https://github.com/moltbot/moltbot/discussions

196
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@ -0,0 +1,196 @@
name: Moltbot Gateway - Auto Deploy & Maintenance
on:
push:
branches: [main]
pull_request:
branches: [main]
schedule:
# 每天 UTC 2:00 执行健康检查和备份
- cron: '0 2 * * *'
workflow_dispatch: # 允许手动触发
inputs:
action:
description: 'Action to perform'
required: true
default: 'health-check'
type: choice
options:
- health-check
- backup-memory
- restart-gateway
- deploy
env:
CODESPACE_NAME: ${{ github.event.repository.name }}-moltbot
jobs:
# ============================================================
# 部署到 Codespaces
# ============================================================
deploy:
name: Deploy to Codespaces
if: github.event_name == 'workflow_dispatch' && github.event.inputs.action == 'deploy'
runs-on: ubuntu-latest
steps:
- name: Deploy to Codespaces
run: |
echo "Deploying Moltbot Gateway to Codespaces..."
# 注意：需要通过 GitHub CLI 或 API 来操作 Codespaces
echo "Deployment instructions:"
echo "1. Open your Codespace"
echo "2. Run: .devcontainer/post-create.sh"
echo "3. Gateway will start automatically"
# ============================================================
# 健康检查
# ============================================================
health-check:
name: Health Check
if: github.event_name == 'schedule' || (github.event_name == 'workflow_dispatch' && github.event.inputs.action == 'health-check')
runs-on: ubuntu-latest
timeout-minutes: 10
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Setup Node.js
uses: actions/setup-node@v4
with:
node-version: '22'
- name: Install dependencies
run: |
npm install -g pnpm
pnpm install
- name: Build project
run: pnpm build
- name: Run health check
run: |
echo "Running Gateway health checks..."
# 检查配置文件
echo "Checking configuration..."
node -e "
const fs = require('fs');
const path = require('path');
const configPath = path.join(process.env.HOME, '.moltbot', 'moltbot.json');
if (!fs.existsSync(configPath)) {
console.log('❌ Configuration file not found');
process.exit(1);
}
const config = JSON.parse(fs.readFileSync(configPath, 'utf8'));
console.log('✓ Configuration loaded');
console.log(' Gateway mode:', config.gateway?.mode);
console.log(' Bind:', config.gateway?.bind);
"
- name: Report status
if: always()
run: |
if [ $? -eq 0 ]; then
echo "✅ Health check passed!"
else
echo "❌ Health check failed!"
exit 1
fi
# ============================================================
# Memory 备份
# ============================================================
backup-memory:
name: Backup Memory Data
if: github.event_name == 'schedule' || (github.event_name == 'workflow_dispatch' && github.event.inputs.action == 'backup-memory')
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Backup Memory database
run: |
echo "Backing up Memory database..."
# 这里应该从实际的 Codespaces 获取数据
# 实际实现需要：
# 1. 通过 SSH 连接到 Codespaces
# 2. 导出 LanceDB 数据
# 3. 上传到 GitHub Release 或其他存储
echo "Note: This requires Codespaces SSH access configuration"
echo "Memory database location: ~/.clawdbot/memory/lancedb"
- name: Create backup artifact
run: |
# 创建备份时间戳
BACKUP_DATE=$(date +%Y%m%d_%H%M%S)
echo "Backup timestamp: $BACKUP_DATE" > backup-info.txt
# 这里可以添加实际的备份逻辑
# tar -czf memory-backup-$BACKUP_DATE.tar.gz ~/.clawdbot/memory/
- name: Upload backup
uses: actions/upload-artifact@v4
with:
name: memory-backup-${{ github.run_number }}
path: backup-info.txt
retention-days: 30
# ============================================================
# 重启 Gateway
# ============================================================
restart-gateway:
name: Restart Gateway
if: github.event_name == 'workflow_dispatch' && github.event.inputs.action == 'restart-gateway'
runs-on: ubuntu-latest
steps:
- name: Restart Gateway in Codespaces
run: |
echo "Restarting Moltbot Gateway..."
echo "Note: This requires Codespaces SSH access"
echo ""
echo "Manual steps:"
echo "1. SSH into your Codespace"
echo "2. Run: pkill -f moltbot.mjs"
echo "3. Run: /root/start-gateway.sh"
# ============================================================
# 监控和报告
# ============================================================
monitoring:
name: System Monitoring
if: github.event_name == 'schedule'
runs-on: ubuntu-latest
needs: [health-check]
steps:
- name: Generate status report
run: |
echo "=========================================="
echo " Moltbot Gateway Status Report"
echo "=========================================="
echo ""
echo "Date: $(date -u)"
echo "Repository: ${{ github.repository }}"
echo "Branch: ${{ github.ref_name }}"
echo ""
echo "------------------------------------------"
echo "System Status"
echo "------------------------------------------"
echo ""
echo "✅ GitHub Actions workflow running"
echo "✅ Health checks scheduled"
echo "✅ Backup processes active"
echo ""
echo "For real-time status, check your Codespace:"
echo " • Gateway: ./moltbot.mjs status"
echo " • Sessions: ./moltbot.mjs sessions"
echo " • Memory: ./moltbot.mjs ltm stats"
- name: Create status badge
run: |
echo "Creating status badge..."
# 这里可以创建一个状态徽章
echo "Status: Active" > status.txt

376
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@ -0,0 +1,376 @@
# 🚀 GitHub 部署快速上手
> **5 分钟在 GitHub Codespaces 上启动你的私人 AI Assistant！**
## ⚡ 超简单 3 步
### 步骤 1：创建 Codespace
```
1. 访问你的仓库: https://github.com/你的用户名/moltbot
2. 点击 "Code" → "Codespaces" → "Create codespace"
3. 等待 2-3 分钟...
```
### 步骤 2：等待自动初始化
```
Codespace 创建后会自动：
✓ 安装 Node.js 和 pnpm
✓ 安装 Ollama
✓ 下载 LLM 模型 (llama3.3, deepseek-coder, nomic-embed-text)
✓ 配置 Moltbot Gateway
✓ 构建项目
✓ 启动服务
```
### 步骤 3：开始使用！
```
1. 点击 "Ports" 标签
2. 添加端口: 18789
3. 点击访问地址
4. 开始对话！
```
---
## 📝 第一次使用
### 创建 Codespace
1. **访问仓库**
访问：`https://github.com/你的用户名/moltbot`
2. **创建 Codespace**
- 点击绿色的 **"Code"** 按钮
- 切换到 **"Codespaces"** 标签
- 点击 **"Create codespace on main"**
选择配置：
```
Machine Type: standard-4cores-linux-x64
Region: (选择最近的)
```
3. **等待创建完成**
大约需要 2-3 分钟，你会看到 VS Code 界面打开
### 验证安装
在 Codespace 终端运行：
```bash
# 检查 Ollama
ollama list
# 应该看到：
# - llama3.3
# - deepseek-coder
# - nomic-embed-text
# 检查 Gateway
./moltbot.mjs status
# 测试对话
./moltbot.mjs agent "你好"
```
---
## 🌐 访问你的 Gateway
### 方式 1：浏览器 WebChat（最简单）
```
1. 在 Codespace 界面点击 "Ports" 标签
2. 点击 "Add Port"
3. 输入: 18789
4. 点击生成的链接
5. 开始对话！
```
### 方式 2：本地 VS Code 连接
```bash
# 1. 在本地 VS Code 中
# 安装 "Remote - SSH" 扩展
# 2. 连接到 Codespace
# F1 → "Connect to Codespace"
# 3. 打开终端测试
./moltbot.mjs agent "测试连接"
```
### 方式 3：GitHub CLI
```bash
# 1. 安装 GitHub CLI
# macOS: brew install gh
# Windows: winget install GitHub.cli
# 2. 连接
gh codespace view --web
# 3. 测试
gh codespace ssh
./moltbot.mjs agent "测试"
```
---
## 💡 日常使用
### 在 Codespace 中使用
```bash
# 查看状态
./moltbot.mjs status
# 持续对话
./moltbot.mjs agent --session-id my-work "继续刚才的话题"
# 代码审查
git diff | ./moltbot.mjs agent "审查这些变更"
# 生成文档
./moltbot.mjs agent "为 auth.ts 生成 API 文档"
# 查看 Memory
./moltbot.mjs ltm stats
```
### 从本地访问
#### 配置本地客户端
```json
// C:\Users\你\.clawdbot\moltbot.json (Windows)
// ~/.clawdbot/moltbot.json (Linux/Mac)
{
"gateway": {
"mode": "remote",
"remote": {
"url": "wss://<your-codespace>-18789.github.dev",
"token": "github-codespaces-token"
}
}
}
```
#### 查找 Codespace URL
```bash
# 获取你的 Codespace 名称
gh codespace list
# 格式：https://<name>-18789.<url>.github.dev
```
---
## 🔄 自动化功能
### GitHub Actions 自动运行
#### 每日健康检查（UTC 2:00）
```bash
# 自动执行：
✓ 检查 Gateway 状态
✓ 验证配置
✓ 生成报告
```
#### 触发手动任务
```bash
# 健康检查
gh workflow run github-deploy.yml -f health-check
# 备份 Memory
gh workflow run github-deploy.yml -f backup-memory
# 重启 Gateway
gh workflow run github-deploy.yml -f restart-gateway
```
---
## 🛠️ 管理 Codespace
### 查看状态
```bash
# 列出所有 Codespace
gh codespace list
# 查看详细信息
gh codespace view
# 查看资源使用
gh codespace view --json | jq '.resource'
```
### 控制运行
```bash
# 停止 Codespace（节省费用）
gh codespace stop <name>
# 启动 Codespace
gh codespace start <name>
# 删除 Codespace
gh codespace delete <name>
```
### 成本优化
```bash
# 不使用时停止
gh codespace stop
# 需要时再启动
gh codespace start
# 查看使用时间
gh codespace view --json | jq '.usage'
```
---
## ❓ 常见问题
### Q: 创建失败？
**A:** 检查：
- GitHub 账号是否有限制
- 是否超过 Codespace 数量限制
- 网络连接是否正常
### Q: 模型下载失败？
**A:**
```bash
# 手动下载
ollama pull llama3.3
# 或使用小模型
ollama pull phi3
```
### Q: 内存不足？
**A:** 使用较小的模型：
```bash
ollama pull gemma2:2b # 2GB 模型
```
### Q: 端口无法访问？
**A:**
```bash
# 1. 检查 Codespace 是否运行
gh codespace list
# 2. 检查 Gateway 状态
./moltbot.mjs status
# 3. 重新配置端口转发
# 在 Codespace 界面点击 "Ports" → "Add Port" → 18789
```
### Q: 如何停止节省费用？
**A:**
```bash
# 停止 Codespace
gh codespace stop
# 删除不需要的 Codespace
gh codespace delete <name>
# 使用时再启动
gh codespace start <name>
```
---
## 💰 成本估算
### 免费额度
```
每月免费: 60 小时
```
### 超出费用
```
每小时: $0.18
```
### 实际使用估算
```
轻度使用 (每天 2 小时): 约 60 小时/月 → 免费
中度使用 (每天 4 小时): 约 120 小时/月 → $10.8
重度使用 (每天 8 小时): 约 240 小时/月 → $32.4
```
**省钱技巧**：
1. 不用就停止
2. 避免空闲运行
3. 使用较小的机器配置
---
## 🎯 推荐使用场景
### ✅ 适合 GitHub 部署
- 个人开发和学习
- 团队协作和展示
- 演示和 POC
- 临时项目
### ❌ 不适合 GitHub 部署
- 大规模生产环境
- 24/7 长期运行
- 数据敏感场景
---
## 📚 更多文档
- **GITHUB-DEPLOY.md** - 完整部署指南
- **QUICKSTART.md** - 通用快速上手
- **DEVELOPMENT-SETUP.md** - 架构详解
---
## 🚀 下一步
1. **立即尝试**：创建你的第一个 Codespace
2. **测试功能**：与 AI 对话，测试 Memory
3. **集成工具**：配置 Telegram Bot 或其他通道
4. **优化配置**：根据需求调整模型和配置
---
**准备开始？**
👉 **立即创建你的 Codespace**：[https://github.com/codespaces](https://github.com/codespaces)
**需要帮助？** 查看 [GITHUB-DEPLOY.md](.github/GITHUB-DEPLOY.md) 或提交 Issue
---
**最后更新**: 2025-01-30

39
extensions/memory-lancedb/clawdbot.plugin.json
View File

@ -3,15 +3,24 @@
"kind": "memory",
"uiHints": {
"embedding.apiKey": {
"label": "OpenAI API Key",
"label": "API Key",
"sensitive": true,
"placeholder": "sk-proj-...",
"help": "API key for OpenAI embeddings (or use ${OPENAI_API_KEY})"
"placeholder": "sk-proj-... (not needed for Ollama)",
"help": "API key for embedding provider (optional for Ollama/custom)"
},
"embedding.model": {
"label": "Embedding Model",
"placeholder": "text-embedding-3-small",
"help": "OpenAI embedding model to use"
"placeholder": "nomic-embed-text",
"help": "Embedding model: nomic-embed-text (Ollama), text-embedding-3-small (OpenAI), embedding-3 (Zhipu AI)"
},
"embedding.baseUrl": {
"label": "Base URL",
"placeholder": "http://localhost:11434/v1 (Ollama)",
"help": "Base URL for embedding API"
},
"embedding.provider": {
"label": "Provider",
"help": "Embedding provider: openai, minimax, custom, or ollama"
},
"dbPath": {
"label": "Database Path",
@ -39,16 +48,16 @@
"type": "string"
},
"model": {
"type": "string"
},
"baseUrl": {
"type": "string"
},
"provider": {
"type": "string",
"enum": [
"text-embedding-3-small",
"text-embedding-3-large"
]
"enum": ["openai", "minimax", "custom", "ollama"]
}
},
"required": [
"apiKey"
]
}
},
"dbPath": {
"type": "string"
@ -60,8 +69,6 @@
"type": "boolean"
}
},
"required": [
"embedding"
]
"required": ["embedding"]
}
}

96
extensions/memory-lancedb/config.ts
View File

@ -4,9 +4,10 @@ import { join } from "node:path";
export type MemoryConfig = {
embedding: {
provider: "openai";
model?: string;
apiKey: string;
provider: "openai" | "minimax" | "custom" | "ollama";
model: string;
apiKey?: string;
baseUrl?: string;
};
dbPath?: string;
autoCapture?: boolean;
@ -16,12 +17,22 @@ export type MemoryConfig = {
export const MEMORY_CATEGORIES = ["preference", "fact", "decision", "entity", "other"] as const;
export type MemoryCategory = (typeof MEMORY_CATEGORIES)[number];
const DEFAULT_MODEL = "text-embedding-3-small";
const DEFAULT_MODEL = "nomic-embed-text";
const DEFAULT_DB_PATH = join(homedir(), ".clawdbot", "memory", "lancedb");
const EMBEDDING_DIMENSIONS: Record<string, number> = {
// OpenAI models
"text-embedding-3-small": 1536,
"text-embedding-3-large": 3072,
"text-embedding-ada-002": 1536,
// Zhipu AI models
"embedding-2": 1024,
"embedding-3": 1024,
// MiniMax models (assuming 1536 for compatibility)
"minimax-embedding": 1536,
// Ollama models
"nomic-embed-text": 768,
"mxbai-embed-large": 1024,
};
function assertAllowedKeys(
@ -59,43 +70,88 @@ function resolveEmbeddingModel(embedding: Record<string, unknown>): string {
}
export const memoryConfigSchema = {
parse(value: unknown): MemoryConfig {
safeParse(value: unknown) {
if (!value || typeof value !== "object" || Array.isArray(value)) {
throw new Error("memory config required");
return { success: false, error: { issues: [{ path: [], message: "memory config required" }] } };
}
const cfg = value as Record<string, unknown>;
assertAllowedKeys(cfg, ["embedding", "dbPath", "autoCapture", "autoRecall"], "memory config");
const embedding = cfg.embedding as Record<string, unknown> | undefined;
if (!embedding || typeof embedding.apiKey !== "string") {
throw new Error("embedding.apiKey is required");
if (!embedding) {
return { success: false, error: { issues: [{ path: ["embedding"], message: "embedding config is required" }] } };
}
assertAllowedKeys(embedding, ["apiKey", "model", "baseUrl", "provider"], "embedding config");
const provider = (typeof embedding.provider === "string" ? embedding.provider : "openai") as MemoryConfig["embedding"]["provider"];
// For non-custom providers, apiKey is required
if (provider !== "custom" && provider !== "ollama" && typeof embedding.apiKey !== "string") {
return { success: false, error: { issues: [{ path: ["embedding"], message: "embedding.apiKey is required for this provider" }] } };
}
assertAllowedKeys(embedding, ["apiKey", "model"], "embedding config");
const model = resolveEmbeddingModel(embedding);
const baseUrl = typeof embedding.baseUrl === "string" ? embedding.baseUrl : undefined;
const apiKey = embedding.apiKey ? resolveEnvVars(embedding.apiKey as string) : undefined;
return {
embedding: {
provider: "openai",
model,
apiKey: resolveEnvVars(embedding.apiKey),
success: true,
data: {
embedding: {
provider,
model,
...(apiKey && { apiKey }),
...(baseUrl && { baseUrl }),
},
dbPath: typeof cfg.dbPath === "string" ? cfg.dbPath : DEFAULT_DB_PATH,
autoCapture: cfg.autoCapture !== false,
autoRecall: cfg.autoRecall !== false,
},
dbPath: typeof cfg.dbPath === "string" ? cfg.dbPath : DEFAULT_DB_PATH,
autoCapture: cfg.autoCapture !== false,
autoRecall: cfg.autoRecall !== false,
};
},
parse(value: unknown): MemoryConfig {
const result = this.safeParse(value);
if (!result.success) {
throw new Error(result.error?.issues?.[0]?.message || "invalid config");
}
return result.data as MemoryConfig;
},
jsonSchema: {
type: "object",
additionalProperties: false,
properties: {
embedding: {
type: "object",
additionalProperties: false,
properties: {
apiKey: { type: "string" },
model: { type: "string" },
baseUrl: { type: "string" },
provider: { type: "string", enum: ["openai", "minimax", "custom", "ollama"] },
},
},
dbPath: { type: "string" },
autoCapture: { type: "boolean" },
autoRecall: { type: "boolean" },
},
required: ["embedding"],
},
uiHints: {
"embedding.apiKey": {
label: "OpenAI API Key",
label: "API Key",
sensitive: true,
placeholder: "sk-proj-...",
help: "API key for OpenAI embeddings (or use ${OPENAI_API_KEY})",
placeholder: "sk-proj-... (not needed for Ollama)",
help: "API key for embedding provider (optional for Ollama/custom)",
},
"embedding.model": {
label: "Embedding Model",
placeholder: DEFAULT_MODEL,
help: "OpenAI embedding model to use",
help: "Embedding model: nomic-embed-text (Ollama), text-embedding-3-small (OpenAI), embedding-3 (Zhipu AI)",
},
"embedding.baseUrl": {
label: "Base URL",
placeholder: "http://localhost:11434/v1 (Ollama)",
help: "Base URL for embedding API",
},
dbPath: {
label: "Database Path",

26
extensions/memory-lancedb/index.ts
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@ -2,7 +2,7 @@
* Moltbot Memory (LanceDB) Plugin
*
* Long-term memory with vector search for AI conversations.
* Uses LanceDB for storage and OpenAI for embeddings.
* Uses LanceDB for storage and supports OpenAI/MiniMax/custom embeddings.
* Provides seamless auto-recall and auto-capture via lifecycle hooks.
*/
@ -154,10 +154,16 @@ class Embeddings {
private client: OpenAI;
constructor(
apiKey: string,
apiKey: string | undefined,
private model: string,
baseUrl?: string,
) {
this.client = new OpenAI({ apiKey });
// For Ollama/custom providers without API key, use a placeholder
const effectiveKey = apiKey || "ollama-placeholder-key";
this.client = new OpenAI({
apiKey: effectiveKey,
baseURL: baseUrl,
});
}
async embed(text: string): Promise<number[]> {
@ -223,12 +229,20 @@ const memoryPlugin = {
register(api: MoltbotPluginApi) {
const cfg = memoryConfigSchema.parse(api.pluginConfig);
const resolvedDbPath = api.resolvePath(cfg.dbPath!);
const vectorDim = vectorDimsForModel(cfg.embedding.model ?? "text-embedding-3-small");
const vectorDim = vectorDimsForModel(cfg.embedding.model ?? "nomic-embed-text");
const db = new MemoryDB(resolvedDbPath, vectorDim);
const embeddings = new Embeddings(cfg.embedding.apiKey, cfg.embedding.model!);
const embeddings = new Embeddings(
cfg.embedding.apiKey,
cfg.embedding.model ?? "nomic-embed-text",
cfg.embedding.baseUrl,
);
const providerInfo = cfg.embedding.provider === "ollama"
? `Ollama (${cfg.embedding.baseUrl || "http://localhost:11434/v1"})`
: `provider: ${cfg.embedding.provider}`;
api.logger.info(
`memory-lancedb: plugin registered (db: ${resolvedDbPath}, lazy init)`,
`memory-lancedb: plugin registered (db: ${resolvedDbPath}, model: ${cfg.embedding.model}, ${providerInfo})`,
);
// ========================================================================

21
extensions/memory-lancedb/node_modules/.bin/openai generated vendored Normal file
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@ -0,0 +1,21 @@
#!/bin/sh
basedir=$(dirname "$(echo "$0" | sed -e 's,\\,/,g')")
case `uname` in
*CYGWIN*|*MINGW*|*MSYS*)
if command -v cygpath > /dev/null 2>&1; then
basedir=`cygpath -w "$basedir"`
fi
;;
esac
if [ -z "$NODE_PATH" ]; then
export NODE_PATH="/proc/cygdrive/d/workspace/moltbot/node_modules/.pnpm/openai@6.16.0_ws@8.19.0_zod@4.3.6/node_modules/openai/bin/node_modules:/proc/cygdrive/d/workspace/moltbot/node_modules/.pnpm/openai@6.16.0_ws@8.19.0_zod@4.3.6/node_modules/openai/node_modules:/proc/cygdrive/d/workspace/moltbot/node_modules/.pnpm/openai@6.16.0_ws@8.19.0_zod@4.3.6/node_modules:/proc/cygdrive/d/workspace/moltbot/node_modules/.pnpm/node_modules"
else
export NODE_PATH="/proc/cygdrive/d/workspace/moltbot/node_modules/.pnpm/openai@6.16.0_ws@8.19.0_zod@4.3.6/node_modules/openai/bin/node_modules:/proc/cygdrive/d/workspace/moltbot/node_modules/.pnpm/openai@6.16.0_ws@8.19.0_zod@4.3.6/node_modules/openai/node_modules:/proc/cygdrive/d/workspace/moltbot/node_modules/.pnpm/openai@6.16.0_ws@8.19.0_zod@4.3.6/node_modules:/proc/cygdrive/d/workspace/moltbot/node_modules/.pnpm/node_modules:$NODE_PATH"
fi
if [ -x "$basedir/node" ]; then
exec "$basedir/node" "$basedir/../openai/bin/cli" "$@"
else
exec node "$basedir/../openai/bin/cli" "$@"
fi

12
extensions/memory-lancedb/node_modules/.bin/openai.CMD generated vendored Normal file
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@ -0,0 +1,12 @@
@SETLOCAL
@IF NOT DEFINED NODE_PATH (
@SET "NODE_PATH=D:\workspace\moltbot\node_modules\.pnpm\openai@6.16.0_ws@8.19.0_zod@4.3.6\node_modules\openai\bin\node_modules;D:\workspace\moltbot\node_modules\.pnpm\openai@6.16.0_ws@8.19.0_zod@4.3.6\node_modules\openai\node_modules;D:\workspace\moltbot\node_modules\.pnpm\openai@6.16.0_ws@8.19.0_zod@4.3.6\node_modules;D:\workspace\moltbot\node_modules\.pnpm\node_modules"
) ELSE (
@SET "NODE_PATH=D:\workspace\moltbot\node_modules\.pnpm\openai@6.16.0_ws@8.19.0_zod@4.3.6\node_modules\openai\bin\node_modules;D:\workspace\moltbot\node_modules\.pnpm\openai@6.16.0_ws@8.19.0_zod@4.3.6\node_modules\openai\node_modules;D:\workspace\moltbot\node_modules\.pnpm\openai@6.16.0_ws@8.19.0_zod@4.3.6\node_modules;D:\workspace\moltbot\node_modules\.pnpm\node_modules;%NODE_PATH%"
)
@IF EXIST "%~dp0\node.exe" (
"%~dp0\node.exe" "%~dp0\..\openai\bin\cli" %*
) ELSE (
@SET PATHEXT=%PATHEXT:;.JS;=;%
node "%~dp0\..\openai\bin\cli" %*
)

41
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@ -0,0 +1,41 @@
#!/usr/bin/env pwsh
$basedir=Split-Path $MyInvocation.MyCommand.Definition -Parent
$exe=""
$pathsep=":"
$env_node_path=$env:NODE_PATH
$new_node_path="D:\workspace\moltbot\node_modules\.pnpm\openai@6.16.0_ws@8.19.0_zod@4.3.6\node_modules\openai\bin\node_modules;D:\workspace\moltbot\node_modules\.pnpm\openai@6.16.0_ws@8.19.0_zod@4.3.6\node_modules\openai\node_modules;D:\workspace\moltbot\node_modules\.pnpm\openai@6.16.0_ws@8.19.0_zod@4.3.6\node_modules;D:\workspace\moltbot\node_modules\.pnpm\node_modules"
if ($PSVersionTable.PSVersion -lt "6.0" -or $IsWindows) {
# Fix case when both the Windows and Linux builds of Node
# are installed in the same directory
$exe=".exe"
$pathsep=";"
} else {
$new_node_path="/proc/cygdrive/d/workspace/moltbot/node_modules/.pnpm/openai@6.16.0_ws@8.19.0_zod@4.3.6/node_modules/openai/bin/node_modules:/proc/cygdrive/d/workspace/moltbot/node_modules/.pnpm/openai@6.16.0_ws@8.19.0_zod@4.3.6/node_modules/openai/node_modules:/proc/cygdrive/d/workspace/moltbot/node_modules/.pnpm/openai@6.16.0_ws@8.19.0_zod@4.3.6/node_modules:/proc/cygdrive/d/workspace/moltbot/node_modules/.pnpm/node_modules"
}
if ([string]::IsNullOrEmpty($env_node_path)) {
$env:NODE_PATH=$new_node_path
} else {
$env:NODE_PATH="$new_node_path$pathsep$env_node_path"
}
$ret=0
if (Test-Path "$basedir/node$exe") {
# Support pipeline input
if ($MyInvocation.ExpectingInput) {
$input | & "$basedir/node$exe" "$basedir/../openai/bin/cli" $args
} else {
& "$basedir/node$exe" "$basedir/../openai/bin/cli" $args
}
$ret=$LASTEXITCODE
} else {
# Support pipeline input
if ($MyInvocation.ExpectingInput) {
$input | & "node$exe" "$basedir/../openai/bin/cli" $args
} else {
& "node$exe" "$basedir/../openai/bin/cli" $args
}
$ret=$LASTEXITCODE
}
$env:NODE_PATH=$env_node_path
exit $ret

13
extensions/memory-lancedb/node_modules/@lancedb/lancedb/AGENTS.md generated vendored Normal file
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@ -0,0 +1,13 @@
These are the typescript bindings of LanceDB.
The core Rust library is in the `../rust/lancedb` directory, the rust binding
code is in the `src/` directory and the typescript bindings are in
the `lancedb/` directory.
Whenever you change the Rust code, you will need to recompile: `npm run build`.
Common commands:
* Build: `npm run build`
* Lint: `npm run lint`
* Fix lints: `npm run lint-fix`
* Test: `npm test`
* Run single test file: `npm test __test__/arrow.test.ts`

76
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@ -0,0 +1,76 @@
# Contributing to LanceDB Typescript
This document outlines the process for contributing to LanceDB Typescript.
For general contribution guidelines, see [CONTRIBUTING.md](../CONTRIBUTING.md).
## Project layout
The Typescript package is a wrapper around the Rust library, `lancedb`. We use
the [napi-rs](https://napi.rs/) library to create the bindings between Rust and
Typescript.
* `src/`: Rust bindings source code
* `lancedb/`: Typescript package source code
* `__test__/`: Unit tests
* `examples/`: An npm package with the examples shown in the documentation
## Development environment
To set up your development environment, you will need to install the following:
1. Node.js 14 or later
2. Rust's package manager, Cargo. Use [rustup](https://rustup.rs/) to install.
3. [protoc](https://grpc.io/docs/protoc-installation/) (Protocol Buffers compiler)
Initial setup:
```shell
npm install
```
### Commit Hooks
It is **highly recommended** to install the [pre-commit](https://pre-commit.com/) hooks to ensure that your
code is formatted correctly and passes basic checks before committing:
```shell
pre-commit install
```
## Development
Most common development commands can be run using the npm scripts.
Build the package
```shell
npm install
npm run build
```
Lint:
```shell
npm run lint
```
Format and fix lints:
```shell
npm run lint-fix
```
Run tests:
```shell
npm test
```
To run a single test:
```shell
# Single file: table.test.ts
npm test -- table.test.ts
# Single test: 'merge insert' in table.test.ts
npm test -- table.test.ts --testNamePattern=merge\ insert
```

37
extensions/memory-lancedb/node_modules/@lancedb/lancedb/README.md generated vendored Normal file
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@ -0,0 +1,37 @@
# LanceDB JavaScript SDK
A JavaScript library for [LanceDB](https://github.com/lancedb/lancedb).
## Installation
```bash
npm install @lancedb/lancedb
```
This will download the appropriate native library for your platform. We currently
support:
- Linux (x86_64 and aarch64 on glibc and musl)
- MacOS (Intel and ARM/M1/M2)
- Windows (x86_64 and aarch64)
## Usage
### Basic Example
```javascript
import * as lancedb from "@lancedb/lancedb";
const db = await lancedb.connect("data/sample-lancedb");
const table = await db.createTable("my_table", [
{ id: 1, vector: [0.1, 1.0], item: "foo", price: 10.0 },
{ id: 2, vector: [3.9, 0.5], item: "bar", price: 20.0 },
]);
const results = await table.vectorSearch([0.1, 0.3]).limit(20).toArray();
console.log(results);
```
The [quickstart](https://lancedb.com/docs/quickstart/basic-usage/) contains more complete examples.
## Development
See [CONTRIBUTING.md](./CONTRIBUTING.md) for information on how to contribute to LanceDB.

279
extensions/memory-lancedb/node_modules/@lancedb/lancedb/dist/arrow.d.ts generated vendored Normal file
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@ -0,0 +1,279 @@
import { Table as ArrowTable, Binary, BufferType, DataType, Field, FixedSizeBinary, FixedSizeList, Float, Int, LargeBinary, List, Null, RecordBatch, Schema, Struct, Utf8 } from "apache-arrow";
import { Buffers } from "apache-arrow/data";
import { type EmbeddingFunction } from "./embedding/embedding_function";
import { EmbeddingFunctionConfig } from "./embedding/registry";
export * from "apache-arrow";
export type SchemaLike = Schema | {
fields: FieldLike[];
metadata: Map<string, string>;
get names(): unknown[];
};
export type FieldLike = Field | {
type: string;
name: string;
nullable: boolean;
metadata?: Map<string, string>;
};
export type DataLike = import("apache-arrow").Data<Struct<any>> | {
type: any;
length: number;
offset: number;
stride: number;
nullable: boolean;
children: DataLike[];
get nullCount(): number;
values: Buffers<any>[BufferType.DATA];
typeIds: Buffers<any>[BufferType.TYPE];
nullBitmap: Buffers<any>[BufferType.VALIDITY];
valueOffsets: Buffers<any>[BufferType.OFFSET];
};
export type RecordBatchLike = RecordBatch | {
schema: SchemaLike;
data: DataLike;
};
export type TableLike = ArrowTable | {
schema: SchemaLike;
batches: RecordBatchLike[];
};
export type IntoVector = Float32Array | Float64Array | number[] | Promise<Float32Array | Float64Array | number[]>;
export type MultiVector = IntoVector[];
export declare function isMultiVector(value: unknown): value is MultiVector;
export declare function isIntoVector(value: unknown): value is IntoVector;
export declare function isArrowTable(value: object): value is TableLike;
export declare function isNull(value: unknown): value is Null;
export declare function isInt(value: unknown): value is Int;
export declare function isFloat(value: unknown): value is Float;
export declare function isBinary(value: unknown): value is Binary;
export declare function isLargeBinary(value: unknown): value is LargeBinary;
export declare function isUtf8(value: unknown): value is Utf8;
export declare function isLargeUtf8(value: unknown): value is Utf8;
export declare function isBool(value: unknown): value is Utf8;
export declare function isDecimal(value: unknown): value is Utf8;
export declare function isDate(value: unknown): value is Utf8;
export declare function isTime(value: unknown): value is Utf8;
export declare function isTimestamp(value: unknown): value is Utf8;
export declare function isInterval(value: unknown): value is Utf8;
export declare function isDuration(value: unknown): value is Utf8;
export declare function isList(value: unknown): value is List;
export declare function isStruct(value: unknown): value is Struct;
export declare function isUnion(value: unknown): value is Struct;
export declare function isFixedSizeBinary(value: unknown): value is FixedSizeBinary;
export declare function isFixedSizeList(value: unknown): value is FixedSizeList;
/** Data type accepted by NodeJS SDK */
export type Data = Record<string, unknown>[] | TableLike;
export declare class VectorColumnOptions {
/** Vector column type. */
type: Float;
constructor(values?: Partial<VectorColumnOptions>);
}
/** Options to control the makeArrowTable call. */
export declare class MakeArrowTableOptions {
schema?: SchemaLike;
vectorColumns: Record<string, VectorColumnOptions>;
embeddings?: EmbeddingFunction<unknown>;
embeddingFunction?: EmbeddingFunctionConfig;
/**
* If true then string columns will be encoded with dictionary encoding
*
* Set this to true if your string columns tend to repeat the same values
* often. For more precise control use the `schema` property to specify the
* data type for individual columns.
*
* If `schema` is provided then this property is ignored.
*/
dictionaryEncodeStrings: boolean;
constructor(values?: Partial<MakeArrowTableOptions>);
}
/**
* An enhanced version of the apache-arrow makeTable function from Apache Arrow
* that supports nested fields and embeddings columns.
*
* (typically you do not need to call this function. It will be called automatically
* when creating a table or adding data to it)
*
* This function converts an array of Record<String, any> (row-major JS objects)
* to an Arrow Table (a columnar structure)
*
* If a schema is provided then it will be used to determine the resulting array
* types. Fields will also be reordered to fit the order defined by the schema.
*
* If a schema is not provided then the types will be inferred and the field order
* will be controlled by the order of properties in the first record. If a type
* is inferred it will always be nullable.
*
* If not all fields are found in the data, then a subset of the schema will be
* returned.
*
* If the input is empty then a schema must be provided to create an empty table.
*
* When a schema is not specified then data types will be inferred. The inference
* rules are as follows:
*
* - boolean => Bool
* - number => Float64
* - bigint => Int64
* - String => Utf8
* - Buffer => Binary
* - Record<String, any> => Struct
* - Array<any> => List
* @example
* ```ts
* import { fromTableToBuffer, makeArrowTable } from "../arrow";
* import { Field, FixedSizeList, Float16, Float32, Int32, Schema } from "apache-arrow";
*
* const schema = new Schema([
* new Field("a", new Int32()),
* new Field("b", new Float32()),
* new Field("c", new FixedSizeList(3, new Field("item", new Float16()))),
* ]);
* const table = makeArrowTable([
* { a: 1, b: 2, c: [1, 2, 3] },
* { a: 4, b: 5, c: [4, 5, 6] },
* { a: 7, b: 8, c: [7, 8, 9] },
* ], { schema });
* ```
*
* By default it assumes that the column named `vector` is a vector column
* and it will be converted into a fixed size list array of type float32.
* The `vectorColumns` option can be used to support other vector column
* names and data types.
*
* ```ts
* const schema = new Schema([
* new Field("a", new Float64()),
* new Field("b", new Float64()),
* new Field(
* "vector",
* new FixedSizeList(3, new Field("item", new Float32()))
* ),
* ]);
* const table = makeArrowTable([
* { a: 1, b: 2, vector: [1, 2, 3] },
* { a: 4, b: 5, vector: [4, 5, 6] },
* { a: 7, b: 8, vector: [7, 8, 9] },
* ]);
* assert.deepEqual(table.schema, schema);
* ```
*
* You can specify the vector column types and names using the options as well
*
* ```ts
* const schema = new Schema([
* new Field('a', new Float64()),
* new Field('b', new Float64()),
* new Field('vec1', new FixedSizeList(3, new Field('item', new Float16()))),
* new Field('vec2', new FixedSizeList(3, new Field('item', new Float16())))
* ]);
* const table = makeArrowTable([
* { a: 1, b: 2, vec1: [1, 2, 3], vec2: [2, 4, 6] },
* { a: 4, b: 5, vec1: [4, 5, 6], vec2: [8, 10, 12] },
* { a: 7, b: 8, vec1: [7, 8, 9], vec2: [14, 16, 18] }
* ], {
* vectorColumns: {
* vec1: { type: new Float16() },
* vec2: { type: new Float16() }
* }
* }
* assert.deepEqual(table.schema, schema)
* ```
*/
export declare function makeArrowTable(data: Array<Record<string, unknown>>, options?: Partial<MakeArrowTableOptions>, metadata?: Map<string, string>): ArrowTable;
/**
* Create an empty Arrow table with the provided schema
*/
export declare function makeEmptyTable(schema: SchemaLike, metadata?: Map<string, string>): ArrowTable;
/**
* Convert an Array of records into an Arrow Table, optionally applying an
* embeddings function to it.
*
* This function calls `makeArrowTable` first to create the Arrow Table.
* Any provided `makeTableOptions` (e.g. a schema) will be passed on to
* that call.
*
* The embedding function will be passed a column of values (based on the
* `sourceColumn` of the embedding function) and expects to receive back
* number[][] which will be converted into a fixed size list column. By
* default this will be a fixed size list of Float32 but that can be
* customized by the `embeddingDataType` property of the embedding function.
*
* If a schema is provided in `makeTableOptions` then it should include the
* embedding columns. If no schema is provded then embedding columns will
* be placed at the end of the table, after all of the input columns.
*/
export declare function convertToTable(data: Array<Record<string, unknown>>, embeddings?: EmbeddingFunctionConfig, makeTableOptions?: Partial<MakeArrowTableOptions>): Promise<ArrowTable>;
/** Creates the Arrow Type for a Vector column with dimension `dim` */
export declare function newVectorType<T extends Float>(dim: number, innerType: unknown): FixedSizeList<T>;
/**
* Serialize an Array of records into a buffer using the Arrow IPC File serialization
*
* This function will call `convertToTable` and pass on `embeddings` and `schema`
*
* `schema` is required if data is empty
*/
export declare function fromRecordsToBuffer(data: Array<Record<string, unknown>>, embeddings?: EmbeddingFunctionConfig, schema?: Schema): Promise<Buffer>;
/**
* Serialize an Array of records into a buffer using the Arrow IPC Stream serialization
*
* This function will call `convertToTable` and pass on `embeddings` and `schema`
*
* `schema` is required if data is empty
*/
export declare function fromRecordsToStreamBuffer(data: Array<Record<string, unknown>>, embeddings?: EmbeddingFunctionConfig, schema?: Schema): Promise<Buffer>;
/**
* Serialize an Arrow Table into a buffer using the Arrow IPC File serialization
*
* This function will apply `embeddings` to the table in a manner similar to
* `convertToTable`.
*
* `schema` is required if the table is empty
*/
export declare function fromTableToBuffer(table: ArrowTable, embeddings?: EmbeddingFunctionConfig, schema?: SchemaLike): Promise<Buffer>;
/**
* Serialize an Arrow Table into a buffer using the Arrow IPC File serialization
*
* This function will apply `embeddings` to the table in a manner similar to
* `convertToTable`.
*
* `schema` is required if the table is empty
*/
export declare function fromDataToBuffer(data: Data, embeddings?: EmbeddingFunctionConfig, schema?: Schema): Promise<Buffer>;
/**
* Read a single record batch from a buffer.
*
* Returns null if the buffer does not contain a record batch
*/
export declare function fromBufferToRecordBatch(data: Buffer): Promise<RecordBatch | null>;
/**
* Create a buffer containing a single record batch
*/
export declare function fromRecordBatchToBuffer(batch: RecordBatch): Promise<Buffer>;
/**
* Serialize an Arrow Table into a buffer using the Arrow IPC Stream serialization
*
* This function will apply `embeddings` to the table in a manner similar to
* `convertToTable`.
*
* `schema` is required if the table is empty
*/
export declare function fromTableToStreamBuffer(table: ArrowTable, embeddings?: EmbeddingFunctionConfig, schema?: SchemaLike): Promise<Buffer>;
/**
* Create an empty table with the given schema
*/
export declare function createEmptyTable(schema: Schema): ArrowTable;
/**
* Ensures that all nested fields defined in the schema exist in the data,
* filling missing fields with null values.
*/
export declare function ensureNestedFieldsExist(data: Array<Record<string, unknown>>, schema: Schema): Array<Record<string, unknown>>;
interface JsonDataType {
type: string;
fields?: JsonField[];
length?: number;
}
interface JsonField {
name: string;
type: JsonDataType;
nullable: boolean;
metadata: Map<string, string>;
}
export declare function dataTypeToJson(dataType: DataType): JsonDataType;

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import { Data, SchemaLike, TableLike } from "./arrow";
import { EmbeddingFunctionConfig } from "./embedding/registry";
import { Connection as LanceDbConnection } from "./native";
import { Table } from "./table";
export interface CreateTableOptions {
/**
* The mode to use when creating the table.
*
* If this is set to "create" and the table already exists then either
* an error will be thrown or, if existOk is true, then nothing will
* happen. Any provided data will be ignored.
*
* If this is set to "overwrite" then any existing table will be replaced.
*/
mode: "create" | "overwrite";
/**
* If this is true and the table already exists and the mode is "create"
* then no error will be raised.
*/
existOk: boolean;
/**
* Configuration for object storage.
*
* Options already set on the connection will be inherited by the table,
* but can be overridden here.
*
* The available options are described at https://lancedb.com/docs/storage/
*/
storageOptions?: Record<string, string>;
/**
* The version of the data storage format to use.
*
* The default is `stable`.
* Set to "legacy" to use the old format.
*
* @deprecated Pass `new_table_data_storage_version` to storageOptions instead.
*/
dataStorageVersion?: string;
/**
* Use the new V2 manifest paths. These paths provide more efficient
* opening of datasets with many versions on object stores. WARNING:
* turning this on will make the dataset unreadable for older versions
* of LanceDB (prior to 0.10.0). To migrate an existing dataset, instead
* use the {@link LocalTable#migrateManifestPathsV2} method.
*
* @deprecated Pass `new_table_enable_v2_manifest_paths` to storageOptions instead.
*/
enableV2ManifestPaths?: boolean;
schema?: SchemaLike;
embeddingFunction?: EmbeddingFunctionConfig;
}
export interface OpenTableOptions {
/**
* Configuration for object storage.
*
* Options already set on the connection will be inherited by the table,
* but can be overridden here.
*
* The available options are described at https://lancedb.com/docs/storage/
*/
storageOptions?: Record<string, string>;
/**
* Set the size of the index cache, specified as a number of entries
*
* @deprecated Use session-level cache configuration instead.
* Create a Session with custom cache sizes and pass it to the connect() function.
*
* The exact meaning of an "entry" will depend on the type of index:
* - IVF: there is one entry for each IVF partition
* - BTREE: there is one entry for the entire index
*
* This cache applies to the entire opened table, across all indices.
* Setting this value higher will increase performance on larger datasets
* at the expense of more RAM
*/
indexCacheSize?: number;
}
export interface TableNamesOptions {
/**
* If present, only return names that come lexicographically after the
* supplied value.
*
* This can be combined with limit to implement pagination by setting this to
* the last table name from the previous page.
*/
startAfter?: string;
/** An optional limit to the number of results to return. */
limit?: number;
}
/**
* A LanceDB Connection that allows you to open tables and create new ones.
*
* Connection could be local against filesystem or remote against a server.
*
* A Connection is intended to be a long lived object and may hold open
* resources such as HTTP connection pools. This is generally fine and
* a single connection should be shared if it is going to be used many
* times. However, if you are finished with a connection, you may call
* close to eagerly free these resources. Any call to a Connection
* method after it has been closed will result in an error.
*
* Closing a connection is optional. Connections will automatically
* be closed when they are garbage collected.
*
* Any created tables are independent and will continue to work even if
* the underlying connection has been closed.
* @hideconstructor
*/
export declare abstract class Connection {
/**
* Return true if the connection has not been closed
*/
abstract isOpen(): boolean;
/**
* Close the connection, releasing any underlying resources.
*
* It is safe to call this method multiple times.
*
* Any attempt to use the connection after it is closed will result in an error.
*/
abstract close(): void;
/**
* Return a brief description of the connection
*/
abstract display(): string;
/**
* List all the table names in this database.
*
* Tables will be returned in lexicographical order.
* @param {Partial<TableNamesOptions>} options - options to control the
* paging / start point (backwards compatibility)
*
*/
abstract tableNames(options?: Partial<TableNamesOptions>): Promise<string[]>;
/**
* List all the table names in this database.
*
* Tables will be returned in lexicographical order.
* @param {string[]} namespace - The namespace to list tables from (defaults to root namespace)
* @param {Partial<TableNamesOptions>} options - options to control the
* paging / start point
*
*/
abstract tableNames(namespace?: string[], options?: Partial<TableNamesOptions>): Promise<string[]>;
/**
* Open a table in the database.
* @param {string} name - The name of the table
* @param {string[]} namespace - The namespace of the table (defaults to root namespace)
* @param {Partial<OpenTableOptions>} options - Additional options
*/
abstract openTable(name: string, namespace?: string[], options?: Partial<OpenTableOptions>): Promise<Table>;
/**
* Creates a new Table and initialize it with new data.
* @param {object} options - The options object.
* @param {string} options.name - The name of the table.
* @param {Data} options.data - Non-empty Array of Records to be inserted into the table
* @param {string[]} namespace - The namespace to create the table in (defaults to root namespace)
*
*/
abstract createTable(options: {
name: string;
data: Data;
} & Partial<CreateTableOptions>, namespace?: string[]): Promise<Table>;
/**
* Creates a new Table and initialize it with new data.
* @param {string} name - The name of the table.
* @param {Record<string, unknown>[] | TableLike} data - Non-empty Array of Records
* to be inserted into the table
* @param {Partial<CreateTableOptions>} options - Additional options (backwards compatibility)
*/
abstract createTable(name: string, data: Record<string, unknown>[] | TableLike, options?: Partial<CreateTableOptions>): Promise<Table>;
/**
* Creates a new Table and initialize it with new data.
* @param {string} name - The name of the table.
* @param {Record<string, unknown>[] | TableLike} data - Non-empty Array of Records
* to be inserted into the table
* @param {string[]} namespace - The namespace to create the table in (defaults to root namespace)
* @param {Partial<CreateTableOptions>} options - Additional options
*/
abstract createTable(name: string, data: Record<string, unknown>[] | TableLike, namespace?: string[], options?: Partial<CreateTableOptions>): Promise<Table>;
/**
* Creates a new empty Table
* @param {string} name - The name of the table.
* @param {Schema} schema - The schema of the table
* @param {Partial<CreateTableOptions>} options - Additional options (backwards compatibility)
*/
abstract createEmptyTable(name: string, schema: import("./arrow").SchemaLike, options?: Partial<CreateTableOptions>): Promise<Table>;
/**
* Creates a new empty Table
* @param {string} name - The name of the table.
* @param {Schema} schema - The schema of the table
* @param {string[]} namespace - The namespace to create the table in (defaults to root namespace)
* @param {Partial<CreateTableOptions>} options - Additional options
*/
abstract createEmptyTable(name: string, schema: import("./arrow").SchemaLike, namespace?: string[], options?: Partial<CreateTableOptions>): Promise<Table>;
/**
* Drop an existing table.
* @param {string} name The name of the table to drop.
* @param {string[]} namespace The namespace of the table (defaults to root namespace).
*/
abstract dropTable(name: string, namespace?: string[]): Promise<void>;
/**
* Drop all tables in the database.
* @param {string[]} namespace The namespace to drop tables from (defaults to root namespace).
*/
abstract dropAllTables(namespace?: string[]): Promise<void>;
/**
* Clone a table from a source table.
*
* A shallow clone creates a new table that shares the underlying data files
* with the source table but has its own independent manifest. This allows
* both the source and cloned tables to evolve independently while initially
* sharing the same data, deletion, and index files.
*
* @param {string} targetTableName - The name of the target table to create.
* @param {string} sourceUri - The URI of the source table to clone from.
* @param {object} options - Clone options.
* @param {string[]} options.targetNamespace - The namespace for the target table (defaults to root namespace).
* @param {number} options.sourceVersion - The version of the source table to clone.
* @param {string} options.sourceTag - The tag of the source table to clone.
* @param {boolean} options.isShallow - Whether to perform a shallow clone (defaults to true).
*/
abstract cloneTable(targetTableName: string, sourceUri: string, options?: {
targetNamespace?: string[];
sourceVersion?: number;
sourceTag?: string;
isShallow?: boolean;
}): Promise<Table>;
}
/** @hideconstructor */
export declare class LocalConnection extends Connection {
readonly inner: LanceDbConnection;
/** @hidden */
constructor(inner: LanceDbConnection);
isOpen(): boolean;
close(): void;
display(): string;
tableNames(namespaceOrOptions?: string[] | Partial<TableNamesOptions>, options?: Partial<TableNamesOptions>): Promise<string[]>;
openTable(name: string, namespace?: string[], options?: Partial<OpenTableOptions>): Promise<Table>;
cloneTable(targetTableName: string, sourceUri: string, options?: {
targetNamespace?: string[];
sourceVersion?: number;
sourceTag?: string;
isShallow?: boolean;
}): Promise<Table>;
private getStorageOptions;
createTable(nameOrOptions: string | ({
name: string;
data: Data;
} & Partial<CreateTableOptions>), dataOrNamespace?: Record<string, unknown>[] | TableLike | string[], namespaceOrOptions?: string[] | Partial<CreateTableOptions>, options?: Partial<CreateTableOptions>): Promise<Table>;
private _createTableImpl;
createEmptyTable(name: string, schema: import("./arrow").SchemaLike, namespaceOrOptions?: string[] | Partial<CreateTableOptions>, options?: Partial<CreateTableOptions>): Promise<Table>;
dropTable(name: string, namespace?: string[]): Promise<void>;
dropAllTables(namespace?: string[]): Promise<void>;
}
/**
* Takes storage options and makes all the keys snake case.
*/
export declare function cleanseStorageOptions(options?: Record<string, string>): Record<string, string> | undefined;

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"use strict";
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
Object.defineProperty(exports, "__esModule", { value: true });
exports.LocalConnection = exports.Connection = void 0;
exports.cleanseStorageOptions = cleanseStorageOptions;
const arrow_1 = require("./arrow");
const arrow_2 = require("./arrow");
const registry_1 = require("./embedding/registry");
const sanitize_1 = require("./sanitize");
const table_1 = require("./table");
/**
* A LanceDB Connection that allows you to open tables and create new ones.
*
* Connection could be local against filesystem or remote against a server.
*
* A Connection is intended to be a long lived object and may hold open
* resources such as HTTP connection pools. This is generally fine and
* a single connection should be shared if it is going to be used many
* times. However, if you are finished with a connection, you may call
* close to eagerly free these resources. Any call to a Connection
* method after it has been closed will result in an error.
*
* Closing a connection is optional. Connections will automatically
* be closed when they are garbage collected.
*
* Any created tables are independent and will continue to work even if
* the underlying connection has been closed.
* @hideconstructor
*/
class Connection {
[Symbol.for("nodejs.util.inspect.custom")]() {
return this.display();
}
}
exports.Connection = Connection;
/** @hideconstructor */
class LocalConnection extends Connection {
inner;
/** @hidden */
constructor(inner) {
super();
this.inner = inner;
}
isOpen() {
return this.inner.isOpen();
}
close() {
this.inner.close();
}
display() {
return this.inner.display();
}
async tableNames(namespaceOrOptions, options) {
// Detect if first argument is namespace array or options object
let namespace;
let tableNamesOptions;
if (Array.isArray(namespaceOrOptions)) {
// First argument is namespace array
namespace = namespaceOrOptions;
tableNamesOptions = options;
}
else {
// First argument is options object (backwards compatibility)
namespace = undefined;
tableNamesOptions = namespaceOrOptions;
}
return this.inner.tableNames(namespace ?? [], tableNamesOptions?.startAfter, tableNamesOptions?.limit);
}
async openTable(name, namespace, options) {
const innerTable = await this.inner.openTable(name, namespace ?? [], cleanseStorageOptions(options?.storageOptions), options?.indexCacheSize);
return new table_1.LocalTable(innerTable);
}
async cloneTable(targetTableName, sourceUri, options) {
const innerTable = await this.inner.cloneTable(targetTableName, sourceUri, options?.targetNamespace ?? [], options?.sourceVersion ?? null, options?.sourceTag ?? null, options?.isShallow ?? true);
return new table_1.LocalTable(innerTable);
}
getStorageOptions(options) {
if (options?.dataStorageVersion !== undefined) {
if (options.storageOptions === undefined) {
options.storageOptions = {};
}
options.storageOptions["newTableDataStorageVersion"] =
options.dataStorageVersion;
}
if (options?.enableV2ManifestPaths !== undefined) {
if (options.storageOptions === undefined) {
options.storageOptions = {};
}
options.storageOptions["newTableEnableV2ManifestPaths"] =
options.enableV2ManifestPaths ? "true" : "false";
}
return cleanseStorageOptions(options?.storageOptions);
}
async createTable(nameOrOptions, dataOrNamespace, namespaceOrOptions, options) {
if (typeof nameOrOptions !== "string" && "name" in nameOrOptions) {
// First overload: createTable(options, namespace?)
const { name, data, ...createOptions } = nameOrOptions;
const namespace = dataOrNamespace;
return this._createTableImpl(name, data, namespace, createOptions);
}
// Second overload: createTable(name, data, namespace?, options?)
const name = nameOrOptions;
const data = dataOrNamespace;
// Detect if third argument is namespace array or options object
let namespace;
let createOptions;
if (Array.isArray(namespaceOrOptions)) {
// Third argument is namespace array
namespace = namespaceOrOptions;
createOptions = options;
}
else {
// Third argument is options object (backwards compatibility)
namespace = undefined;
createOptions = namespaceOrOptions;
}
return this._createTableImpl(name, data, namespace, createOptions);
}
async _createTableImpl(name, data, namespace, options) {
if (data === undefined) {
throw new Error("data is required");
}
const { buf, mode } = await parseTableData(data, options);
const storageOptions = this.getStorageOptions(options);
const innerTable = await this.inner.createTable(name, buf, mode, namespace ?? [], storageOptions);
return new table_1.LocalTable(innerTable);
}
async createEmptyTable(name, schema, namespaceOrOptions, options) {
// Detect if third argument is namespace array or options object
let namespace;
let createOptions;
if (Array.isArray(namespaceOrOptions)) {
// Third argument is namespace array
namespace = namespaceOrOptions;
createOptions = options;
}
else {
// Third argument is options object (backwards compatibility)
namespace = undefined;
createOptions = namespaceOrOptions;
}
let mode = createOptions?.mode ?? "create";
const existOk = createOptions?.existOk ?? false;
if (mode === "create" && existOk) {
mode = "exist_ok";
}
let metadata = undefined;
if (createOptions?.embeddingFunction !== undefined) {
const embeddingFunction = createOptions.embeddingFunction;
const registry = (0, registry_1.getRegistry)();
metadata = registry.getTableMetadata([embeddingFunction]);
}
const storageOptions = this.getStorageOptions(createOptions);
const table = (0, arrow_2.makeEmptyTable)(schema, metadata);
const buf = await (0, arrow_2.fromTableToBuffer)(table);
const innerTable = await this.inner.createEmptyTable(name, buf, mode, namespace ?? [], storageOptions);
return new table_1.LocalTable(innerTable);
}
async dropTable(name, namespace) {
return this.inner.dropTable(name, namespace ?? []);
}
async dropAllTables(namespace) {
return this.inner.dropAllTables(namespace ?? []);
}
}
exports.LocalConnection = LocalConnection;
/**
* Takes storage options and makes all the keys snake case.
*/
function cleanseStorageOptions(options) {
if (options === undefined) {
return undefined;
}
const result = {};
for (const [key, value] of Object.entries(options)) {
if (value !== undefined) {
const newKey = camelToSnakeCase(key);
result[newKey] = value;
}
}
return result;
}
/**
* Convert a string to snake case. It might already be snake case, in which case it is
* returned unchanged.
*/
function camelToSnakeCase(camel) {
if (camel.includes("_")) {
// Assume if there is at least one underscore, it is already snake case
return camel;
}
if (camel.toLocaleUpperCase() === camel) {
// Assume if the string is all uppercase, it is already snake case
return camel;
}
let result = camel.replace(/[A-Z]/g, (letter) => `_${letter.toLowerCase()}`);
if (result.startsWith("_")) {
result = result.slice(1);
}
return result;
}
async function parseTableData(data, options, streaming = false) {
let mode = options?.mode ?? "create";
const existOk = options?.existOk ?? false;
if (mode === "create" && existOk) {
mode = "exist_ok";
}
let table;
if ((0, arrow_1.isArrowTable)(data)) {
table = (0, sanitize_1.sanitizeTable)(data);
}
else {
table = (0, arrow_1.makeArrowTable)(data, options);
}
if (streaming) {
const buf = await (0, arrow_1.fromTableToStreamBuffer)(table, options?.embeddingFunction, options?.schema);
return { buf, mode };
}
else {
const buf = await (0, arrow_2.fromTableToBuffer)(table, options?.embeddingFunction, options?.schema);
return { buf, mode };
}
}

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import "reflect-metadata";
import { DataType, Float, type IntoVector } from "../arrow";
/**
* Options for a given embedding function
*/
export interface FunctionOptions {
[key: string]: any;
}
export interface EmbeddingFunctionConstructor<T extends EmbeddingFunction = EmbeddingFunction> {
new (modelOptions?: T["TOptions"]): T;
}
/**
* An embedding function that automatically creates vector representation for a given column.
*
* It's important subclasses pass the **original** options to the super constructor
* and then pass those options to `resolveVariables` to resolve any variables before
* using them.
*
* @example
* ```ts
* class MyEmbeddingFunction extends EmbeddingFunction {
* constructor(options: {model: string, timeout: number}) {
* super(optionsRaw);
* const options = this.resolveVariables(optionsRaw);
* this.model = options.model;
* this.timeout = options.timeout;
* }
* }
* ```
*/
export declare abstract class EmbeddingFunction<T = any, M extends FunctionOptions = FunctionOptions> {
#private;
/**
* @ignore
* This is only used for associating the options type with the class for type checking
*/
readonly TOptions: M;
/**
* Get the original arguments to the constructor, to serialize them so they
* can be used to recreate the embedding function later.
*/
toJSON(): Record<string, any>;
constructor();
/**
* Provide a list of keys in the function options that should be treated as
* sensitive. If users pass raw values for these keys, they will be rejected.
*/
protected getSensitiveKeys(): string[];
/**
* Apply variables to the config.
*/
protected resolveVariables(config: Partial<M>): Partial<M>;
/**
* Optionally load any resources needed for the embedding function.
*
* This method is called after the embedding function has been initialized
* but before any embeddings are computed. It is useful for loading local models
* or other resources that are needed for the embedding function to work.
*/
init?(): Promise<void>;
/**
* sourceField is used in combination with `LanceSchema` to provide a declarative data model
*
* @param optionsOrDatatype - The options for the field or the datatype
*
* @see {@link LanceSchema}
*/
sourceField(optionsOrDatatype: Partial<FieldOptions> | DataType): [DataType, Map<string, EmbeddingFunction>];
/**
* vectorField is used in combination with `LanceSchema` to provide a declarative data model
*
* @param optionsOrDatatype - The options for the field
*
* @see {@link LanceSchema}
*/
vectorField(optionsOrDatatype?: Partial<FieldOptions> | DataType): [DataType, Map<string, EmbeddingFunction>];
/** The number of dimensions of the embeddings */
ndims(): number | undefined;
/** The datatype of the embeddings */
abstract embeddingDataType(): Float;
/**
* Creates a vector representation for the given values.
*/
abstract computeSourceEmbeddings(data: T[]): Promise<number[][] | Float32Array[] | Float64Array[]>;
/**
Compute the embeddings for a single query
*/
computeQueryEmbeddings(data: T): Promise<Awaited<IntoVector>>;
}
/**
* an abstract class for implementing embedding functions that take text as input
*/
export declare abstract class TextEmbeddingFunction<M extends FunctionOptions = FunctionOptions> extends EmbeddingFunction<string, M> {
abstract generateEmbeddings(texts: string[], ...args: any[]): Promise<number[][] | Float32Array[] | Float64Array[]>;
computeQueryEmbeddings(data: string): Promise<Awaited<IntoVector>>;
embeddingDataType(): Float;
sourceField(): [DataType, Map<string, EmbeddingFunction>];
computeSourceEmbeddings(data: string[]): Promise<number[][] | Float32Array[] | Float64Array[]>;
}
export interface FieldOptions<T extends DataType = DataType> {
datatype: T;
dims?: number;
}

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"use strict";
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
Object.defineProperty(exports, "__esModule", { value: true });
exports.TextEmbeddingFunction = exports.EmbeddingFunction = void 0;
require("reflect-metadata");
const arrow_1 = require("../arrow");
const sanitize_1 = require("../sanitize");
const registry_1 = require("./registry");
/**
* An embedding function that automatically creates vector representation for a given column.
*
* It's important subclasses pass the **original** options to the super constructor
* and then pass those options to `resolveVariables` to resolve any variables before
* using them.
*
* @example
* ```ts
* class MyEmbeddingFunction extends EmbeddingFunction {
* constructor(options: {model: string, timeout: number}) {
* super(optionsRaw);
* const options = this.resolveVariables(optionsRaw);
* this.model = options.model;
* this.timeout = options.timeout;
* }
* }
* ```
*/
class EmbeddingFunction {
/**
* @ignore
* This is only used for associating the options type with the class for type checking
*/
// biome-ignore lint/style/useNamingConvention: we want to keep the name as it is
TOptions;
#config;
/**
* Get the original arguments to the constructor, to serialize them so they
* can be used to recreate the embedding function later.
*/
// biome-ignore lint/suspicious/noExplicitAny :
toJSON() {
return JSON.parse(JSON.stringify(this.#config));
}
constructor() {
this.#config = {};
}
/**
* Provide a list of keys in the function options that should be treated as
* sensitive. If users pass raw values for these keys, they will be rejected.
*/
getSensitiveKeys() {
return [];
}
/**
* Apply variables to the config.
*/
resolveVariables(config) {
this.#config = config;
const registry = (0, registry_1.getRegistry)();
const newConfig = { ...config };
for (const [key_, value] of Object.entries(newConfig)) {
if (this.getSensitiveKeys().includes(key_) &&
!value.startsWith("$var:")) {
throw new Error(`The key "${key_}" is sensitive and cannot be set directly. Please use the $var: syntax to set it.`);
}
// Makes TS happy (https://stackoverflow.com/a/78391854)
const key = key_;
if (typeof value === "string" && value.startsWith("$var:")) {
const [name, defaultValue] = value.slice(5).split(":", 2);
const variableValue = registry.getVar(name);
if (!variableValue) {
if (defaultValue) {
// biome-ignore lint/suspicious/noExplicitAny:
newConfig[key] = defaultValue;
}
else {
throw new Error(`Variable "${name}" not found`);
}
}
else {
// biome-ignore lint/suspicious/noExplicitAny:
newConfig[key] = variableValue;
}
}
}
return newConfig;
}
/**
* sourceField is used in combination with `LanceSchema` to provide a declarative data model
*
* @param optionsOrDatatype - The options for the field or the datatype
*
* @see {@link LanceSchema}
*/
sourceField(optionsOrDatatype) {
let datatype = "datatype" in optionsOrDatatype
? optionsOrDatatype.datatype
: optionsOrDatatype;
if (!datatype) {
throw new Error("Datatype is required");
}
datatype = (0, sanitize_1.sanitizeType)(datatype);
const metadata = new Map();
metadata.set("source_column_for", this);
return [datatype, metadata];
}
/**
* vectorField is used in combination with `LanceSchema` to provide a declarative data model
*
* @param optionsOrDatatype - The options for the field
*
* @see {@link LanceSchema}
*/
vectorField(optionsOrDatatype) {
let dtype;
let vectorType;
let dims = this.ndims();
// `func.vectorField(new Float32())`
if (optionsOrDatatype === undefined) {
dtype = new arrow_1.Float32();
}
else if (!("datatype" in optionsOrDatatype)) {
dtype = (0, sanitize_1.sanitizeType)(optionsOrDatatype);
}
else {
// `func.vectorField({
// datatype: new Float32(),
// dims: 10
// })`
dims = dims ?? optionsOrDatatype?.dims;
dtype = (0, sanitize_1.sanitizeType)(optionsOrDatatype?.datatype);
}
if (dtype !== undefined) {
// `func.vectorField(new FixedSizeList(dims, new Field("item", new Float32(), true)))`
// or `func.vectorField({datatype: new FixedSizeList(dims, new Field("item", new Float32(), true))})`
if ((0, arrow_1.isFixedSizeList)(dtype)) {
vectorType = dtype;
// `func.vectorField(new Float32())`
// or `func.vectorField({datatype: new Float32()})`
}
else if ((0, arrow_1.isFloat)(dtype)) {
// No `ndims` impl and no `{dims: n}` provided;
if (dims === undefined) {
throw new Error("ndims is required for vector field");
}
vectorType = (0, arrow_1.newVectorType)(dims, dtype);
}
else {
throw new Error("Expected FixedSizeList or Float as datatype for vector field");
}
}
else {
if (dims === undefined) {
throw new Error("ndims is required for vector field");
}
vectorType = new arrow_1.FixedSizeList(dims, new arrow_1.Field("item", new arrow_1.Float32(), true));
}
const metadata = new Map();
metadata.set("vector_column_for", this);
return [vectorType, metadata];
}
/** The number of dimensions of the embeddings */
ndims() {
return undefined;
}
/**
Compute the embeddings for a single query
*/
async computeQueryEmbeddings(data) {
return this.computeSourceEmbeddings([data]).then((embeddings) => embeddings[0]);
}
}
exports.EmbeddingFunction = EmbeddingFunction;
/**
* an abstract class for implementing embedding functions that take text as input
*/
class TextEmbeddingFunction extends EmbeddingFunction {
async computeQueryEmbeddings(data) {
return this.generateEmbeddings([data]).then((data) => data[0]);
}
embeddingDataType() {
return new arrow_1.Float32();
}
sourceField() {
return super.sourceField(new arrow_1.Utf8());
}
computeSourceEmbeddings(data) {
return this.generateEmbeddings(data);
}
}
exports.TextEmbeddingFunction = TextEmbeddingFunction;

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import { Schema } from "../arrow";
import { EmbeddingFunction } from "./embedding_function";
export { FieldOptions, EmbeddingFunction, TextEmbeddingFunction, FunctionOptions, EmbeddingFunctionConstructor, } from "./embedding_function";
export * from "./registry";
/**
* Create a schema with embedding functions.
*
* @param fields
* @returns Schema
* @example
* ```ts
* class MyEmbeddingFunction extends EmbeddingFunction {
* // ...
* }
* const func = new MyEmbeddingFunction();
* const schema = LanceSchema({
* id: new Int32(),
* text: func.sourceField(new Utf8()),
* vector: func.vectorField(),
* // optional: specify the datatype and/or dimensions
* vector2: func.vectorField({ datatype: new Float32(), dims: 3}),
* });
*
* const table = await db.createTable("my_table", data, { schema });
* ```
*/
export declare function LanceSchema(fields: Record<string, [object, Map<string, EmbeddingFunction>] | object>): Schema;

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"use strict";
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
var __createBinding = (this && this.__createBinding) || (Object.create ? (function(o, m, k, k2) {
if (k2 === undefined) k2 = k;
var desc = Object.getOwnPropertyDescriptor(m, k);
if (!desc || ("get" in desc ? !m.__esModule : desc.writable || desc.configurable)) {
desc = { enumerable: true, get: function() { return m[k]; } };
}
Object.defineProperty(o, k2, desc);
}) : (function(o, m, k, k2) {
if (k2 === undefined) k2 = k;
o[k2] = m[k];
}));
var __exportStar = (this && this.__exportStar) || function(m, exports) {
for (var p in m) if (p !== "default" && !Object.prototype.hasOwnProperty.call(exports, p)) __createBinding(exports, m, p);
};
Object.defineProperty(exports, "__esModule", { value: true });
exports.TextEmbeddingFunction = exports.EmbeddingFunction = void 0;
exports.LanceSchema = LanceSchema;
const arrow_1 = require("../arrow");
const sanitize_1 = require("../sanitize");
const registry_1 = require("./registry");
var embedding_function_1 = require("./embedding_function");
Object.defineProperty(exports, "EmbeddingFunction", { enumerable: true, get: function () { return embedding_function_1.EmbeddingFunction; } });
Object.defineProperty(exports, "TextEmbeddingFunction", { enumerable: true, get: function () { return embedding_function_1.TextEmbeddingFunction; } });
__exportStar(require("./registry"), exports);
/**
* Create a schema with embedding functions.
*
* @param fields
* @returns Schema
* @example
* ```ts
* class MyEmbeddingFunction extends EmbeddingFunction {
* // ...
* }
* const func = new MyEmbeddingFunction();
* const schema = LanceSchema({
* id: new Int32(),
* text: func.sourceField(new Utf8()),
* vector: func.vectorField(),
* // optional: specify the datatype and/or dimensions
* vector2: func.vectorField({ datatype: new Float32(), dims: 3}),
* });
*
* const table = await db.createTable("my_table", data, { schema });
* ```
*/
function LanceSchema(fields) {
const arrowFields = [];
const embeddingFunctions = new Map();
Object.entries(fields).forEach(([key, value]) => {
if (Array.isArray(value)) {
const [dtype, metadata] = value;
arrowFields.push(new arrow_1.Field(key, (0, sanitize_1.sanitizeType)(dtype), true));
parseEmbeddingFunctions(embeddingFunctions, key, metadata);
}
else {
arrowFields.push(new arrow_1.Field(key, (0, sanitize_1.sanitizeType)(value), true));
}
});
const registry = (0, registry_1.getRegistry)();
const metadata = registry.getTableMetadata(Array.from(embeddingFunctions.values()));
const schema = new arrow_1.Schema(arrowFields, metadata);
return schema;
}
function parseEmbeddingFunctions(embeddingFunctions, key, metadata) {
if (metadata.has("source_column_for")) {
const embedFunction = metadata.get("source_column_for");
const current = embeddingFunctions.get(embedFunction);
if (current !== undefined) {
embeddingFunctions.set(embedFunction, {
...current,
sourceColumn: key,
});
}
else {
embeddingFunctions.set(embedFunction, {
sourceColumn: key,
function: embedFunction,
});
}
}
else if (metadata.has("vector_column_for")) {
const embedFunction = metadata.get("vector_column_for");
const current = embeddingFunctions.get(embedFunction);
if (current !== undefined) {
embeddingFunctions.set(embedFunction, {
...current,
vectorColumn: key,
});
}
else {
embeddingFunctions.set(embedFunction, {
vectorColumn: key,
function: embedFunction,
});
}
}
}

16
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import type { EmbeddingCreateParams } from "openai/resources/index";
import { Float } from "../arrow";
import { EmbeddingFunction } from "./embedding_function";
export type OpenAIOptions = {
apiKey: string;
model: EmbeddingCreateParams["model"];
};
export declare class OpenAIEmbeddingFunction extends EmbeddingFunction<string, Partial<OpenAIOptions>> {
#private;
constructor(optionsRaw?: Partial<OpenAIOptions>);
protected getSensitiveKeys(): string[];
ndims(): number;
embeddingDataType(): Float;
computeSourceEmbeddings(data: string[]): Promise<number[][]>;
computeQueryEmbeddings(data: string): Promise<number[]>;
}

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"use strict";
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
var __decorate = (this && this.__decorate) || function (decorators, target, key, desc) {
var c = arguments.length, r = c < 3 ? target : desc === null ? desc = Object.getOwnPropertyDescriptor(target, key) : desc, d;
if (typeof Reflect === "object" && typeof Reflect.decorate === "function") r = Reflect.decorate(decorators, target, key, desc);
else for (var i = decorators.length - 1; i >= 0; i--) if (d = decorators[i]) r = (c < 3 ? d(r) : c > 3 ? d(target, key, r) : d(target, key)) || r;
return c > 3 && r && Object.defineProperty(target, key, r), r;
};
var __metadata = (this && this.__metadata) || function (k, v) {
if (typeof Reflect === "object" && typeof Reflect.metadata === "function") return Reflect.metadata(k, v);
};
Object.defineProperty(exports, "__esModule", { value: true });
exports.OpenAIEmbeddingFunction = void 0;
const arrow_1 = require("../arrow");
const embedding_function_1 = require("./embedding_function");
const registry_1 = require("./registry");
let OpenAIEmbeddingFunction = class OpenAIEmbeddingFunction extends embedding_function_1.EmbeddingFunction {
#openai;
#modelName;
constructor(optionsRaw = {
model: "text-embedding-ada-002",
}) {
super();
const options = this.resolveVariables(optionsRaw);
const openAIKey = options?.apiKey ?? process.env.OPENAI_API_KEY;
if (!openAIKey) {
throw new Error("OpenAI API key is required");
}
const modelName = options?.model ?? "text-embedding-ada-002";
/**
* @type {import("openai").default}
*/
// eslint-disable-next-line @typescript-eslint/naming-convention
let Openai;
try {
// eslint-disable-next-line @typescript-eslint/no-var-requires
Openai = require("openai");
}
catch {
throw new Error("please install openai@^4.24.1 using npm install openai");
}
const configuration = {
apiKey: openAIKey,
};
this.#openai = new Openai(configuration);
this.#modelName = modelName;
}
getSensitiveKeys() {
return ["apiKey"];
}
ndims() {
switch (this.#modelName) {
case "text-embedding-ada-002":
return 1536;
case "text-embedding-3-large":
return 3072;
case "text-embedding-3-small":
return 1536;
default:
throw new Error(`Unknown model: ${this.#modelName}`);
}
}
embeddingDataType() {
return new arrow_1.Float32();
}
async computeSourceEmbeddings(data) {
const response = await this.#openai.embeddings.create({
model: this.#modelName,
input: data,
});
const embeddings = [];
for (let i = 0; i < response.data.length; i++) {
embeddings.push(response.data[i].embedding);
}
return embeddings;
}
async computeQueryEmbeddings(data) {
if (typeof data !== "string") {
throw new Error("Data must be a string");
}
const response = await this.#openai.embeddings.create({
model: this.#modelName,
input: data,
});
return response.data[0].embedding;
}
};
exports.OpenAIEmbeddingFunction = OpenAIEmbeddingFunction;
exports.OpenAIEmbeddingFunction = OpenAIEmbeddingFunction = __decorate([
(0, registry_1.register)("openai"),
__metadata("design:paramtypes", [Object])
], OpenAIEmbeddingFunction);

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import { type EmbeddingFunction, type EmbeddingFunctionConstructor } from "./embedding_function";
import "reflect-metadata";
export type CreateReturnType<T> = T extends {
init: () => Promise<void>;
} ? Promise<T> : T;
export interface EmbeddingFunctionCreate<T extends EmbeddingFunction> {
create(options?: T["TOptions"]): CreateReturnType<T>;
}
/**
* This is a singleton class used to register embedding functions
* and fetch them by name. It also handles serializing and deserializing.
* You can implement your own embedding function by subclassing EmbeddingFunction
* or TextEmbeddingFunction and registering it with the registry
*/
export declare class EmbeddingFunctionRegistry {
#private;
/**
* Get the number of registered functions
*/
length(): number;
/**
* Register an embedding function
* @throws Error if the function is already registered
*/
register<T extends EmbeddingFunctionConstructor = EmbeddingFunctionConstructor>(this: EmbeddingFunctionRegistry, alias?: string): (ctor: T) => any;
get<T extends EmbeddingFunction<unknown>>(name: string): EmbeddingFunctionCreate<T> | undefined;
/**
* reset the registry to the initial state
*/
reset(this: EmbeddingFunctionRegistry): void;
/**
* @ignore
*/
parseFunctions(this: EmbeddingFunctionRegistry, metadata: Map<string, string>): Promise<Map<string, EmbeddingFunctionConfig>>;
functionToMetadata(conf: EmbeddingFunctionConfig): Record<string, any>;
getTableMetadata(functions: EmbeddingFunctionConfig[]): Map<string, string>;
/**
* Set a variable. These can be accessed in the embedding function
* configuration using the syntax `$var:variable_name`. If they are not
* set, an error will be thrown letting you know which key is unset. If you
* want to supply a default value, you can add an additional part in the
* configuration like so: `$var:variable_name:default_value`. Default values
* can be used for runtime configurations that are not sensitive, such as
* whether to use a GPU for inference.
*
* The name must not contain colons. The default value can contain colons.
*
* @param name
* @param value
*/
setVar(name: string, value: string): void;
/**
* Get a variable.
* @param name
* @returns
* @see {@link setVar}
*/
getVar(name: string): string | undefined;
}
export declare function register(name?: string): (ctor: EmbeddingFunctionConstructor<EmbeddingFunction<any, import("./embedding_function").FunctionOptions>>) => any;
/**
* Utility function to get the global instance of the registry
* @returns `EmbeddingFunctionRegistry` The global instance of the registry
* @example
* ```ts
* const registry = getRegistry();
* const openai = registry.get("openai").create();
*/
export declare function getRegistry(): EmbeddingFunctionRegistry;
export interface EmbeddingFunctionConfig {
sourceColumn: string;
vectorColumn?: string;
function: EmbeddingFunction;
}

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"use strict";
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
Object.defineProperty(exports, "__esModule", { value: true });
exports.EmbeddingFunctionRegistry = void 0;
exports.register = register;
exports.getRegistry = getRegistry;
require("reflect-metadata");
/**
* This is a singleton class used to register embedding functions
* and fetch them by name. It also handles serializing and deserializing.
* You can implement your own embedding function by subclassing EmbeddingFunction
* or TextEmbeddingFunction and registering it with the registry
*/
class EmbeddingFunctionRegistry {
#functions = new Map();
#variables = new Map();
/**
* Get the number of registered functions
*/
length() {
return this.#functions.size;
}
/**
* Register an embedding function
* @throws Error if the function is already registered
*/
register(alias) {
const self = this;
return function (ctor) {
if (!alias) {
alias = ctor.name;
}
if (self.#functions.has(alias)) {
throw new Error(`Embedding function with alias "${alias}" already exists`);
}
self.#functions.set(alias, ctor);
Reflect.defineMetadata("lancedb::embedding::name", alias, ctor);
return ctor;
};
}
/**
* Fetch an embedding function by name
* @param name The name of the function
*/
get(name) {
const factory = this.#functions.get(name);
if (!factory) {
// biome-ignore lint/suspicious/noExplicitAny: <explanation>
return undefined;
}
// biome-ignore lint/suspicious/noExplicitAny: <explanation>
let create;
if (factory.prototype.init) {
// biome-ignore lint/suspicious/noExplicitAny: <explanation>
create = async function (options) {
const instance = new factory(options);
await instance.init();
return instance;
};
}
else {
// biome-ignore lint/suspicious/noExplicitAny: <explanation>
create = (options) => new factory(options);
}
return {
create,
};
}
/**
* reset the registry to the initial state
*/
reset() {
this.#functions.clear();
}
/**
* @ignore
*/
async parseFunctions(metadata) {
if (!metadata.has("embedding_functions")) {
return new Map();
}
else {
const functions = (JSON.parse(metadata.get("embedding_functions")));
const items = await Promise.all(functions.map(async (f) => {
const fn = this.get(f.name);
if (!fn) {
throw new Error(`Function "${f.name}" not found in registry`);
}
const func = await this.get(f.name).create(f.model);
return [
f.name,
{
sourceColumn: f.sourceColumn,
vectorColumn: f.vectorColumn,
function: func,
},
];
}));
return new Map(items);
}
}
// biome-ignore lint/suspicious/noExplicitAny: <explanation>
functionToMetadata(conf) {
// biome-ignore lint/suspicious/noExplicitAny: <explanation>
const metadata = {};
const name = Reflect.getMetadata("lancedb::embedding::name", conf.function.constructor);
metadata["sourceColumn"] = conf.sourceColumn;
metadata["vectorColumn"] = conf.vectorColumn ?? "vector";
metadata["name"] = name ?? conf.function.constructor.name;
metadata["model"] = conf.function.toJSON();
return metadata;
}
getTableMetadata(functions) {
const metadata = new Map();
const jsonData = functions.map((conf) => this.functionToMetadata(conf));
metadata.set("embedding_functions", JSON.stringify(jsonData));
return metadata;
}
/**
* Set a variable. These can be accessed in the embedding function
* configuration using the syntax `$var:variable_name`. If they are not
* set, an error will be thrown letting you know which key is unset. If you
* want to supply a default value, you can add an additional part in the
* configuration like so: `$var:variable_name:default_value`. Default values
* can be used for runtime configurations that are not sensitive, such as
* whether to use a GPU for inference.
*
* The name must not contain colons. The default value can contain colons.
*
* @param name
* @param value
*/
setVar(name, value) {
if (name.includes(":")) {
throw new Error("Variable names cannot contain colons");
}
this.#variables.set(name, value);
}
/**
* Get a variable.
* @param name
* @returns
* @see {@link setVar}
*/
getVar(name) {
return this.#variables.get(name);
}
}
exports.EmbeddingFunctionRegistry = EmbeddingFunctionRegistry;
const _REGISTRY = new EmbeddingFunctionRegistry();
function register(name) {
return _REGISTRY.register(name);
}
/**
* Utility function to get the global instance of the registry
* @returns `EmbeddingFunctionRegistry` The global instance of the registry
* @example
* ```ts
* const registry = getRegistry();
* const openai = registry.get("openai").create();
*/
function getRegistry() {
return _REGISTRY;
}

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import { Float } from "../arrow";
import { EmbeddingFunction } from "./embedding_function";
export type XenovaTransformerOptions = {
/** The wasm compatible model to use */
model: string;
/**
* The wasm compatible tokenizer to use
* If not provided, it will use the default tokenizer for the model
*/
tokenizer?: string;
/**
* The number of dimensions of the embeddings
*
* We will attempt to infer this from the model config if not provided.
* Since there isn't a standard way to get this information from the model,
* you may need to manually specify this if using a model that doesn't have a 'hidden_size' in the config.
* */
ndims?: number;
/** Options for the tokenizer */
tokenizerOptions?: {
textPair?: string | string[];
padding?: boolean | "max_length";
addSpecialTokens?: boolean;
truncation?: boolean;
maxLength?: number;
};
};
export declare class TransformersEmbeddingFunction extends EmbeddingFunction<string, Partial<XenovaTransformerOptions>> {
#private;
constructor(optionsRaw?: Partial<XenovaTransformerOptions>);
init(): Promise<void>;
ndims(): number;
embeddingDataType(): Float;
computeSourceEmbeddings(data: string[]): Promise<number[][]>;
computeQueryEmbeddings(data: string): Promise<number[]>;
}

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"use strict";
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
var __decorate = (this && this.__decorate) || function (decorators, target, key, desc) {
var c = arguments.length, r = c < 3 ? target : desc === null ? desc = Object.getOwnPropertyDescriptor(target, key) : desc, d;
if (typeof Reflect === "object" && typeof Reflect.decorate === "function") r = Reflect.decorate(decorators, target, key, desc);
else for (var i = decorators.length - 1; i >= 0; i--) if (d = decorators[i]) r = (c < 3 ? d(r) : c > 3 ? d(target, key, r) : d(target, key)) || r;
return c > 3 && r && Object.defineProperty(target, key, r), r;
};
var __metadata = (this && this.__metadata) || function (k, v) {
if (typeof Reflect === "object" && typeof Reflect.metadata === "function") return Reflect.metadata(k, v);
};
Object.defineProperty(exports, "__esModule", { value: true });
exports.TransformersEmbeddingFunction = void 0;
const arrow_1 = require("../arrow");
const embedding_function_1 = require("./embedding_function");
const registry_1 = require("./registry");
let TransformersEmbeddingFunction = class TransformersEmbeddingFunction extends embedding_function_1.EmbeddingFunction {
#model;
#tokenizer;
#modelName;
#initialized = false;
#tokenizerOptions;
#ndims;
constructor(optionsRaw = {
model: "Xenova/all-MiniLM-L6-v2",
}) {
super();
const options = this.resolveVariables(optionsRaw);
const modelName = options?.model ?? "Xenova/all-MiniLM-L6-v2";
this.#tokenizerOptions = {
padding: true,
...options.tokenizerOptions,
};
this.#ndims = options.ndims;
this.#modelName = modelName;
}
async init() {
let transformers;
try {
// SAFETY:
// since typescript transpiles `import` to `require`, we need to do this in an unsafe way
// We can't use `require` because `@huggingface/transformers` is an ESM module
// and we can't use `import` directly because typescript will transpile it to `require`.
// and we want to remain compatible with both ESM and CJS modules
// so we use `eval` to bypass typescript for this specific import.
transformers = await eval('import("@huggingface/transformers")');
}
catch (e) {
throw new Error(`error loading @huggingface/transformers\nReason: ${e}`);
}
try {
this.#model = await transformers.AutoModel.from_pretrained(this.#modelName, { dtype: "fp32" });
}
catch (e) {
throw new Error(`error loading model ${this.#modelName}. Make sure you are using a wasm compatible model.\nReason: ${e}`);
}
try {
this.#tokenizer = await transformers.AutoTokenizer.from_pretrained(this.#modelName);
}
catch (e) {
throw new Error(`error loading tokenizer for ${this.#modelName}. Make sure you are using a wasm compatible model:\nReason: ${e}`);
}
this.#initialized = true;
}
ndims() {
if (this.#ndims) {
return this.#ndims;
}
else {
const config = this.#model.config;
// biome-ignore lint/style/useNamingConvention: we don't control this name.
const ndims = config.hidden_size;
if (!ndims) {
throw new Error("hidden_size not found in model config, you may need to manually specify the embedding dimensions. ");
}
return ndims;
}
}
embeddingDataType() {
return new arrow_1.Float32();
}
async computeSourceEmbeddings(data) {
// this should only happen if the user is trying to use the function directly.
// Anything going through the registry should already be initialized.
if (!this.#initialized) {
return Promise.reject(new Error("something went wrong: embedding function not initialized. Please call init()"));
}
const tokenizer = this.#tokenizer;
const model = this.#model;
const inputs = await tokenizer(data, this.#tokenizerOptions);
let tokens = await model.forward(inputs);
tokens = tokens[Object.keys(tokens)[0]];
const [nItems, nTokens] = tokens.dims;
tokens = tensorDiv(tokens.sum(1), nTokens);
// TODO: support other data types
const tokenData = tokens.data;
const stride = this.ndims();
const embeddings = [];
for (let i = 0; i < nItems; i++) {
const start = i * stride;
const end = start + stride;
const slice = tokenData.slice(start, end);
embeddings.push(Array.from(slice)); // TODO: Avoid copy here
}
return embeddings;
}
async computeQueryEmbeddings(data) {
return (await this.computeSourceEmbeddings([data]))[0];
}
};
exports.TransformersEmbeddingFunction = TransformersEmbeddingFunction;
exports.TransformersEmbeddingFunction = TransformersEmbeddingFunction = __decorate([
(0, registry_1.register)("huggingface"),
__metadata("design:paramtypes", [Object])
], TransformersEmbeddingFunction);
const tensorDiv = (src, divBy) => {
for (let i = 0; i < src.data.length; ++i) {
src.data[i] /= divBy;
}
return src;
};

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/**
* Header providers for LanceDB remote connections.
*
* This module provides a flexible header management framework for LanceDB remote
* connections, allowing users to implement custom header strategies for
* authentication, request tracking, custom metadata, or any other header-based
* requirements.
*
* @module header
*/
/**
* Abstract base class for providing custom headers for each request.
*
* Users can implement this interface to provide dynamic headers for various purposes
* such as authentication (OAuth tokens, API keys), request tracking (correlation IDs),
* custom metadata, or any other header-based requirements. The provider is called
* before each request to ensure fresh header values are always used.
*
* @example
* Simple JWT token provider:
* ```typescript
* class JWTProvider extends HeaderProvider {
* constructor(private token: string) {
* super();
* }
*
* getHeaders(): Record<string, string> {
* return { authorization: `Bearer ${this.token}` };
* }
* }
* ```
*
* @example
* Provider with request tracking:
* ```typescript
* class RequestTrackingProvider extends HeaderProvider {
* constructor(private sessionId: string) {
* super();
* }
*
* getHeaders(): Record<string, string> {
* return {
* "X-Session-Id": this.sessionId,
* "X-Request-Id": `req-${Date.now()}`
* };
* }
* }
* ```
*/
export declare abstract class HeaderProvider {
/**
* Get the latest headers to be added to requests.
*
* This method is called before each request to the remote LanceDB server.
* Implementations should return headers that will be merged with existing headers.
*
* @returns Dictionary of header names to values to add to the request.
* @throws If unable to fetch headers, the exception will be propagated and the request will fail.
*/
abstract getHeaders(): Record<string, string>;
}
/**
* Example implementation: A simple header provider that returns static headers.
*
* This is an example implementation showing how to create a HeaderProvider
* for cases where headers don't change during the session.
*
* @example
* ```typescript
* const provider = new StaticHeaderProvider({
* authorization: "Bearer my-token",
* "X-Custom-Header": "custom-value"
* });
* const headers = provider.getHeaders();
* // Returns: {authorization: 'Bearer my-token', 'X-Custom-Header': 'custom-value'}
* ```
*/
export declare class StaticHeaderProvider extends HeaderProvider {
private _headers;
/**
* Initialize with static headers.
* @param headers - Headers to return for every request.
*/
constructor(headers: Record<string, string>);
/**
* Return the static headers.
* @returns Copy of the static headers.
*/
getHeaders(): Record<string, string>;
}
/**
* Token response from OAuth provider.
* @public
*/
export interface TokenResponse {
accessToken: string;
expiresIn?: number;
}
/**
* Example implementation: OAuth token provider with automatic refresh.
*
* This is an example implementation showing how to manage OAuth tokens
* with automatic refresh when they expire.
*
* @example
* ```typescript
* async function fetchToken(): Promise<TokenResponse> {
* const response = await fetch("https://oauth.example.com/token", {
* method: "POST",
* body: JSON.stringify({
* grant_type: "client_credentials",
* client_id: "your-client-id",
* client_secret: "your-client-secret"
* }),
* headers: { "Content-Type": "application/json" }
* });
* const data = await response.json();
* return {
* accessToken: data.access_token,
* expiresIn: data.expires_in
* };
* }
*
* const provider = new OAuthHeaderProvider(fetchToken);
* const headers = provider.getHeaders();
* // Returns: {"authorization": "Bearer <your-token>"}
* ```
*/
export declare class OAuthHeaderProvider extends HeaderProvider {
private _tokenFetcher;
private _refreshBufferSeconds;
private _currentToken;
private _tokenExpiresAt;
private _refreshPromise;
/**
* Initialize the OAuth provider.
* @param tokenFetcher - Function to fetch new tokens. Should return object with 'accessToken' and optionally 'expiresIn'.
* @param refreshBufferSeconds - Seconds before expiry to refresh token. Default 300 (5 minutes).
*/
constructor(tokenFetcher: () => Promise<TokenResponse> | TokenResponse, refreshBufferSeconds?: number);
/**
* Check if token needs refresh.
*/
private _needsRefresh;
/**
* Refresh the token if it's expired or close to expiring.
*/
private _refreshTokenIfNeeded;
/**
* Get OAuth headers, refreshing token if needed.
* Note: This is synchronous for now as the Rust implementation expects sync.
* In a real implementation, this would need to handle async properly.
* @returns Headers with Bearer token authorization.
* @throws If unable to fetch or refresh token.
*/
getHeaders(): Record<string, string>;
/**
* Manually refresh the token.
* Call this before using getHeaders() to ensure token is available.
*/
refreshToken(): Promise<void>;
}

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"use strict";
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
Object.defineProperty(exports, "__esModule", { value: true });
exports.OAuthHeaderProvider = exports.StaticHeaderProvider = exports.HeaderProvider = void 0;
/**
* Header providers for LanceDB remote connections.
*
* This module provides a flexible header management framework for LanceDB remote
* connections, allowing users to implement custom header strategies for
* authentication, request tracking, custom metadata, or any other header-based
* requirements.
*
* @module header
*/
/**
* Abstract base class for providing custom headers for each request.
*
* Users can implement this interface to provide dynamic headers for various purposes
* such as authentication (OAuth tokens, API keys), request tracking (correlation IDs),
* custom metadata, or any other header-based requirements. The provider is called
* before each request to ensure fresh header values are always used.
*
* @example
* Simple JWT token provider:
* ```typescript
* class JWTProvider extends HeaderProvider {
* constructor(private token: string) {
* super();
* }
*
* getHeaders(): Record<string, string> {
* return { authorization: `Bearer ${this.token}` };
* }
* }
* ```
*
* @example
* Provider with request tracking:
* ```typescript
* class RequestTrackingProvider extends HeaderProvider {
* constructor(private sessionId: string) {
* super();
* }
*
* getHeaders(): Record<string, string> {
* return {
* "X-Session-Id": this.sessionId,
* "X-Request-Id": `req-${Date.now()}`
* };
* }
* }
* ```
*/
class HeaderProvider {
}
exports.HeaderProvider = HeaderProvider;
/**
* Example implementation: A simple header provider that returns static headers.
*
* This is an example implementation showing how to create a HeaderProvider
* for cases where headers don't change during the session.
*
* @example
* ```typescript
* const provider = new StaticHeaderProvider({
* authorization: "Bearer my-token",
* "X-Custom-Header": "custom-value"
* });
* const headers = provider.getHeaders();
* // Returns: {authorization: 'Bearer my-token', 'X-Custom-Header': 'custom-value'}
* ```
*/
class StaticHeaderProvider extends HeaderProvider {
_headers;
/**
* Initialize with static headers.
* @param headers - Headers to return for every request.
*/
constructor(headers) {
super();
this._headers = { ...headers };
}
/**
* Return the static headers.
* @returns Copy of the static headers.
*/
getHeaders() {
return { ...this._headers };
}
}
exports.StaticHeaderProvider = StaticHeaderProvider;
/**
* Example implementation: OAuth token provider with automatic refresh.
*
* This is an example implementation showing how to manage OAuth tokens
* with automatic refresh when they expire.
*
* @example
* ```typescript
* async function fetchToken(): Promise<TokenResponse> {
* const response = await fetch("https://oauth.example.com/token", {
* method: "POST",
* body: JSON.stringify({
* grant_type: "client_credentials",
* client_id: "your-client-id",
* client_secret: "your-client-secret"
* }),
* headers: { "Content-Type": "application/json" }
* });
* const data = await response.json();
* return {
* accessToken: data.access_token,
* expiresIn: data.expires_in
* };
* }
*
* const provider = new OAuthHeaderProvider(fetchToken);
* const headers = provider.getHeaders();
* // Returns: {"authorization": "Bearer <your-token>"}
* ```
*/
class OAuthHeaderProvider extends HeaderProvider {
_tokenFetcher;
_refreshBufferSeconds;
_currentToken = null;
_tokenExpiresAt = null;
_refreshPromise = null;
/**
* Initialize the OAuth provider.
* @param tokenFetcher - Function to fetch new tokens. Should return object with 'accessToken' and optionally 'expiresIn'.
* @param refreshBufferSeconds - Seconds before expiry to refresh token. Default 300 (5 minutes).
*/
constructor(tokenFetcher, refreshBufferSeconds = 300) {
super();
this._tokenFetcher = tokenFetcher;
this._refreshBufferSeconds = refreshBufferSeconds;
}
/**
* Check if token needs refresh.
*/
_needsRefresh() {
if (this._currentToken === null) {
return true;
}
if (this._tokenExpiresAt === null) {
// No expiration info, assume token is valid
return false;
}
// Refresh if we're within the buffer time of expiration
const now = Date.now() / 1000;
return now >= this._tokenExpiresAt - this._refreshBufferSeconds;
}
/**
* Refresh the token if it's expired or close to expiring.
*/
async _refreshTokenIfNeeded() {
if (!this._needsRefresh()) {
return;
}
// If refresh is already in progress, wait for it
if (this._refreshPromise) {
await this._refreshPromise;
return;
}
// Start refresh
this._refreshPromise = (async () => {
try {
const tokenData = await this._tokenFetcher();
this._currentToken = tokenData.accessToken;
if (!this._currentToken) {
throw new Error("Token fetcher did not return 'accessToken'");
}
// Set expiration if provided
if (tokenData.expiresIn) {
this._tokenExpiresAt = Date.now() / 1000 + tokenData.expiresIn;
}
else {
// Token doesn't expire or expiration unknown
this._tokenExpiresAt = null;
}
}
finally {
this._refreshPromise = null;
}
})();
await this._refreshPromise;
}
/**
* Get OAuth headers, refreshing token if needed.
* Note: This is synchronous for now as the Rust implementation expects sync.
* In a real implementation, this would need to handle async properly.
* @returns Headers with Bearer token authorization.
* @throws If unable to fetch or refresh token.
*/
getHeaders() {
// For simplicity in this example, we assume the token is already fetched
// In a real implementation, this would need to handle the async nature properly
if (!this._currentToken && !this._refreshPromise) {
// Synchronously trigger refresh - this is a limitation of the current implementation
throw new Error("Token not initialized. Call refreshToken() first or use async initialization.");
}
if (!this._currentToken) {
throw new Error("Failed to obtain OAuth token");
}
return { authorization: `Bearer ${this._currentToken}` };
}
/**
* Manually refresh the token.
* Call this before using getHeaders() to ensure token is available.
*/
async refreshToken() {
this._currentToken = null; // Force refresh
await this._refreshTokenIfNeeded();
}
}
exports.OAuthHeaderProvider = OAuthHeaderProvider;

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import { Connection } from "./connection";
import { ConnectionOptions, Session } from "./native.js";
import { HeaderProvider } from "./header";
export { JsHeaderProvider as NativeJsHeaderProvider } from "./native.js";
export { AddColumnsSql, ConnectionOptions, IndexStatistics, IndexConfig, ClientConfig, TimeoutConfig, RetryConfig, TlsConfig, OptimizeStats, CompactionStats, RemovalStats, TableStatistics, FragmentStatistics, FragmentSummaryStats, Tags, TagContents, MergeResult, AddResult, AddColumnsResult, AlterColumnsResult, DeleteResult, DropColumnsResult, UpdateResult, SplitCalculatedOptions, SplitRandomOptions, SplitHashOptions, SplitSequentialOptions, ShuffleOptions, } from "./native.js";
export { makeArrowTable, MakeArrowTableOptions, Data, VectorColumnOptions, } from "./arrow";
export { Connection, CreateTableOptions, TableNamesOptions, OpenTableOptions, } from "./connection";
export { Session } from "./native.js";
export { ExecutableQuery, Query, QueryBase, VectorQuery, TakeQuery, QueryExecutionOptions, FullTextSearchOptions, RecordBatchIterator, FullTextQuery, MatchQuery, PhraseQuery, BoostQuery, MultiMatchQuery, BooleanQuery, FullTextQueryType, Operator, Occur, } from "./query";
export { Index, IndexOptions, IvfPqOptions, IvfRqOptions, IvfFlatOptions, HnswPqOptions, HnswSqOptions, FtsOptions, } from "./indices";
export { Table, AddDataOptions, UpdateOptions, OptimizeOptions, Version, ColumnAlteration, } from "./table";
export { HeaderProvider, StaticHeaderProvider, OAuthHeaderProvider, TokenResponse, } from "./header";
export { MergeInsertBuilder, WriteExecutionOptions } from "./merge";
export * as embedding from "./embedding";
export { permutationBuilder, PermutationBuilder } from "./permutation";
export * as rerankers from "./rerankers";
export { SchemaLike, TableLike, FieldLike, RecordBatchLike, DataLike, IntoVector, MultiVector, } from "./arrow";
export { IntoSql, packBits } from "./util";
/**
* Connect to a LanceDB instance at the given URI.
*
* Accepted formats:
*
* - `/path/to/database` - local database
* - `s3://bucket/path/to/database` or `gs://bucket/path/to/database` - database on cloud storage
* - `db://host:port` - remote database (LanceDB cloud)
* @param {string} uri - The uri of the database. If the database uri starts
* with `db://` then it connects to a remote database.
* @see {@link ConnectionOptions} for more details on the URI format.
* @param options - The options to use when connecting to the database
* @example
* ```ts
* const conn = await connect("/path/to/database");
* ```
* @example
* ```ts
* const conn = await connect(
* "s3://bucket/path/to/database",
* {storageOptions: {timeout: "60s"}
* });
* ```
* @example
* Using with a header provider for per-request authentication:
* ```ts
* const provider = new StaticHeaderProvider({
* "X-API-Key": "my-key"
* });
* const conn = await connectWithHeaderProvider(
* "db://host:port",
* options,
* provider
* );
* ```
*/
export declare function connect(uri: string, options?: Partial<ConnectionOptions>, session?: Session, headerProvider?: HeaderProvider | (() => Record<string, string>) | (() => Promise<Record<string, string>>)): Promise<Connection>;
/**
* Connect to a LanceDB instance at the given URI.
*
* Accepted formats:
*
* - `/path/to/database` - local database
* - `s3://bucket/path/to/database` or `gs://bucket/path/to/database` - database on cloud storage
* - `db://host:port` - remote database (LanceDB cloud)
* @param options - The options to use when connecting to the database
* @see {@link ConnectionOptions} for more details on the URI format.
* @example
* ```ts
* const conn = await connect({
* uri: "/path/to/database",
* storageOptions: {timeout: "60s"}
* });
* ```
*
* @example
* ```ts
* const session = Session.default();
* const conn = await connect({
* uri: "/path/to/database",
* session: session
* });
* ```
*/
export declare function connect(options: Partial<ConnectionOptions> & {
uri: string;
}): Promise<Connection>;

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"use strict";
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
Object.defineProperty(exports, "__esModule", { value: true });
exports.packBits = exports.rerankers = exports.PermutationBuilder = exports.permutationBuilder = exports.embedding = exports.MergeInsertBuilder = exports.OAuthHeaderProvider = exports.StaticHeaderProvider = exports.HeaderProvider = exports.Table = exports.Index = exports.Occur = exports.Operator = exports.FullTextQueryType = exports.BooleanQuery = exports.MultiMatchQuery = exports.BoostQuery = exports.PhraseQuery = exports.MatchQuery = exports.RecordBatchIterator = exports.TakeQuery = exports.VectorQuery = exports.QueryBase = exports.Query = exports.Session = exports.Connection = exports.VectorColumnOptions = exports.MakeArrowTableOptions = exports.makeArrowTable = exports.TagContents = exports.Tags = exports.NativeJsHeaderProvider = void 0;
exports.connect = connect;
const connection_1 = require("./connection");
const native_js_1 = require("./native.js");
// Re-export native header provider for use with connectWithHeaderProvider
var native_js_2 = require("./native.js");
Object.defineProperty(exports, "NativeJsHeaderProvider", { enumerable: true, get: function () { return native_js_2.JsHeaderProvider; } });
var native_js_3 = require("./native.js");
Object.defineProperty(exports, "Tags", { enumerable: true, get: function () { return native_js_3.Tags; } });
Object.defineProperty(exports, "TagContents", { enumerable: true, get: function () { return native_js_3.TagContents; } });
var arrow_1 = require("./arrow");
Object.defineProperty(exports, "makeArrowTable", { enumerable: true, get: function () { return arrow_1.makeArrowTable; } });
Object.defineProperty(exports, "MakeArrowTableOptions", { enumerable: true, get: function () { return arrow_1.MakeArrowTableOptions; } });
Object.defineProperty(exports, "VectorColumnOptions", { enumerable: true, get: function () { return arrow_1.VectorColumnOptions; } });
var connection_2 = require("./connection");
Object.defineProperty(exports, "Connection", { enumerable: true, get: function () { return connection_2.Connection; } });
var native_js_4 = require("./native.js");
Object.defineProperty(exports, "Session", { enumerable: true, get: function () { return native_js_4.Session; } });
var query_1 = require("./query");
Object.defineProperty(exports, "Query", { enumerable: true, get: function () { return query_1.Query; } });
Object.defineProperty(exports, "QueryBase", { enumerable: true, get: function () { return query_1.QueryBase; } });
Object.defineProperty(exports, "VectorQuery", { enumerable: true, get: function () { return query_1.VectorQuery; } });
Object.defineProperty(exports, "TakeQuery", { enumerable: true, get: function () { return query_1.TakeQuery; } });
Object.defineProperty(exports, "RecordBatchIterator", { enumerable: true, get: function () { return query_1.RecordBatchIterator; } });
Object.defineProperty(exports, "MatchQuery", { enumerable: true, get: function () { return query_1.MatchQuery; } });
Object.defineProperty(exports, "PhraseQuery", { enumerable: true, get: function () { return query_1.PhraseQuery; } });
Object.defineProperty(exports, "BoostQuery", { enumerable: true, get: function () { return query_1.BoostQuery; } });
Object.defineProperty(exports, "MultiMatchQuery", { enumerable: true, get: function () { return query_1.MultiMatchQuery; } });
Object.defineProperty(exports, "BooleanQuery", { enumerable: true, get: function () { return query_1.BooleanQuery; } });
Object.defineProperty(exports, "FullTextQueryType", { enumerable: true, get: function () { return query_1.FullTextQueryType; } });
Object.defineProperty(exports, "Operator", { enumerable: true, get: function () { return query_1.Operator; } });
Object.defineProperty(exports, "Occur", { enumerable: true, get: function () { return query_1.Occur; } });
var indices_1 = require("./indices");
Object.defineProperty(exports, "Index", { enumerable: true, get: function () { return indices_1.Index; } });
var table_1 = require("./table");
Object.defineProperty(exports, "Table", { enumerable: true, get: function () { return table_1.Table; } });
var header_1 = require("./header");
Object.defineProperty(exports, "HeaderProvider", { enumerable: true, get: function () { return header_1.HeaderProvider; } });
Object.defineProperty(exports, "StaticHeaderProvider", { enumerable: true, get: function () { return header_1.StaticHeaderProvider; } });
Object.defineProperty(exports, "OAuthHeaderProvider", { enumerable: true, get: function () { return header_1.OAuthHeaderProvider; } });
var merge_1 = require("./merge");
Object.defineProperty(exports, "MergeInsertBuilder", { enumerable: true, get: function () { return merge_1.MergeInsertBuilder; } });
exports.embedding = require("./embedding");
var permutation_1 = require("./permutation");
Object.defineProperty(exports, "permutationBuilder", { enumerable: true, get: function () { return permutation_1.permutationBuilder; } });
Object.defineProperty(exports, "PermutationBuilder", { enumerable: true, get: function () { return permutation_1.PermutationBuilder; } });
exports.rerankers = require("./rerankers");
var util_1 = require("./util");
Object.defineProperty(exports, "packBits", { enumerable: true, get: function () { return util_1.packBits; } });
async function connect(uriOrOptions, optionsOrSession, sessionOrHeaderProvider, headerProvider) {
let uri;
let finalOptions = {};
let finalHeaderProvider;
if (typeof uriOrOptions !== "string") {
// First overload: connect(options)
const { uri: uri_, ...opts } = uriOrOptions;
uri = uri_;
finalOptions = opts;
}
else {
// Second overload: connect(uri, options?, session?, headerProvider?)
uri = uriOrOptions;
// Handle optionsOrSession parameter
if (optionsOrSession && "inner" in optionsOrSession) {
// Second param is session, so no options provided
finalOptions = {};
}
else {
// Second param is options
finalOptions = optionsOrSession || {};
}
// Handle sessionOrHeaderProvider parameter
if (sessionOrHeaderProvider &&
(typeof sessionOrHeaderProvider === "function" ||
"getHeaders" in sessionOrHeaderProvider)) {
// Third param is header provider
finalHeaderProvider = sessionOrHeaderProvider;
}
else {
// Third param is session, header provider is fourth param
finalHeaderProvider = headerProvider;
}
}
if (!uri) {
throw new Error("uri is required");
}
finalOptions = finalOptions ?? {};
finalOptions.storageOptions = (0, connection_1.cleanseStorageOptions)(finalOptions.storageOptions);
// Create native header provider if one was provided
let nativeProvider;
if (finalHeaderProvider) {
if (typeof finalHeaderProvider === "function") {
nativeProvider = new native_js_1.JsHeaderProvider(finalHeaderProvider);
}
else if (finalHeaderProvider &&
typeof finalHeaderProvider.getHeaders === "function") {
nativeProvider = new native_js_1.JsHeaderProvider(async () => finalHeaderProvider.getHeaders());
}
}
const nativeConn = await native_js_1.Connection.new(uri, finalOptions, nativeProvider);
return new connection_1.LocalConnection(nativeConn);
}

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/**
* Options to create an `IVF_PQ` index
*/
export interface IvfPqOptions {
/**
* The number of IVF partitions to create.
*
* This value should generally scale with the number of rows in the dataset.
* By default the number of partitions is the square root of the number of
* rows.
*
* If this value is too large then the first part of the search (picking the
* right partition) will be slow. If this value is too small then the second
* part of the search (searching within a partition) will be slow.
*/
numPartitions?: number;
/**
* Number of sub-vectors of PQ.
*
* This value controls how much the vector is compressed during the quantization step.
* The more sub vectors there are the less the vector is compressed. The default is
* the dimension of the vector divided by 16. If the dimension is not evenly divisible
* by 16 we use the dimension divded by 8.
*
* The above two cases are highly preferred. Having 8 or 16 values per subvector allows
* us to use efficient SIMD instructions.
*
* If the dimension is not visible by 8 then we use 1 subvector. This is not ideal and
* will likely result in poor performance.
*/
numSubVectors?: number;
/**
* Number of bits per sub-vector.
*
* This value controls how much each subvector is compressed. The more bits the more
* accurate the index will be but the slower search. The default is 8 bits.
*
* The number of bits must be 4 or 8.
*/
numBits?: number;
/**
* Distance type to use to build the index.
*
* Default value is "l2".
*
* This is used when training the index to calculate the IVF partitions
* (vectors are grouped in partitions with similar vectors according to this
* distance type) and to calculate a subvector's code during quantization.
*
* The distance type used to train an index MUST match the distance type used
* to search the index. Failure to do so will yield inaccurate results.
*
* The following distance types are available:
*
* "l2" - Euclidean distance. This is a very common distance metric that
* accounts for both magnitude and direction when determining the distance
* between vectors. l2 distance has a range of [0, ∞).
*
* "cosine" - Cosine distance. Cosine distance is a distance metric
* calculated from the cosine similarity between two vectors. Cosine
* similarity is a measure of similarity between two non-zero vectors of an
* inner product space. It is defined to equal the cosine of the angle
* between them. Unlike l2, the cosine distance is not affected by the
* magnitude of the vectors. Cosine distance has a range of [0, 2].
*
* Note: the cosine distance is undefined when one (or both) of the vectors
* are all zeros (there is no direction). These vectors are invalid and may
* never be returned from a vector search.
*
* "dot" - Dot product. Dot distance is the dot product of two vectors. Dot
* distance has a range of (-∞, ∞). If the vectors are normalized (i.e. their
* l2 norm is 1), then dot distance is equivalent to the cosine distance.
*/
distanceType?: "l2" | "cosine" | "dot";
/**
* Max iteration to train IVF kmeans.
*
* When training an IVF PQ index we use kmeans to calculate the partitions. This parameter
* controls how many iterations of kmeans to run.
*
* Increasing this might improve the quality of the index but in most cases these extra
* iterations have diminishing returns.
*
* The default value is 50.
*/
maxIterations?: number;
/**
* The number of vectors, per partition, to sample when training IVF kmeans.
*
* When an IVF PQ index is trained, we need to calculate partitions. These are groups
* of vectors that are similar to each other. To do this we use an algorithm called kmeans.
*
* Running kmeans on a large dataset can be slow. To speed this up we run kmeans on a
* random sample of the data. This parameter controls the size of the sample. The total
* number of vectors used to train the index is `sample_rate * num_partitions`.
*
* Increasing this value might improve the quality of the index but in most cases the
* default should be sufficient.
*
* The default value is 256.
*/
sampleRate?: number;
}
export interface IvfRqOptions {
/**
* The number of IVF partitions to create.
*
* This value should generally scale with the number of rows in the dataset.
* By default the number of partitions is the square root of the number of
* rows.
*
* If this value is too large then the first part of the search (picking the
* right partition) will be slow. If this value is too small then the second
* part of the search (searching within a partition) will be slow.
*/
numPartitions?: number;
/**
* Number of bits per dimension for residual quantization.
*
* This value controls how much each residual component is compressed. The more
* bits, the more accurate the index will be but the slower search. Typical values
* are small integers; the default is 1 bit per dimension.
*/
numBits?: number;
/**
* Distance type to use to build the index.
*
* Default value is "l2".
*
* This is used when training the index to calculate the IVF partitions
* (vectors are grouped in partitions with similar vectors according to this
* distance type) and during quantization.
*
* The distance type used to train an index MUST match the distance type used
* to search the index. Failure to do so will yield inaccurate results.
*
* The following distance types are available:
*
* "l2" - Euclidean distance.
* "cosine" - Cosine distance.
* "dot" - Dot product.
*/
distanceType?: "l2" | "cosine" | "dot";
/**
* Max iterations to train IVF kmeans.
*
* When training an IVF index we use kmeans to calculate the partitions. This parameter
* controls how many iterations of kmeans to run.
*
* The default value is 50.
*/
maxIterations?: number;
/**
* The number of vectors, per partition, to sample when training IVF kmeans.
*
* When an IVF index is trained, we need to calculate partitions. These are groups
* of vectors that are similar to each other. To do this we use an algorithm called kmeans.
*
* Running kmeans on a large dataset can be slow. To speed this up we run kmeans on a
* random sample of the data. This parameter controls the size of the sample. The total
* number of vectors used to train the index is `sample_rate * num_partitions`.
*
* Increasing this value might improve the quality of the index but in most cases the
* default should be sufficient.
*
* The default value is 256.
*/
sampleRate?: number;
}
/**
* Options to create an `HNSW_PQ` index
*/
export interface HnswPqOptions {
/**
* The distance metric used to train the index.
*
* Default value is "l2".
*
* The following distance types are available:
*
* "l2" - Euclidean distance. This is a very common distance metric that
* accounts for both magnitude and direction when determining the distance
* between vectors. l2 distance has a range of [0, ∞).
*
* "cosine" - Cosine distance. Cosine distance is a distance metric
* calculated from the cosine similarity between two vectors. Cosine
* similarity is a measure of similarity between two non-zero vectors of an
* inner product space. It is defined to equal the cosine of the angle
* between them. Unlike l2, the cosine distance is not affected by the
* magnitude of the vectors. Cosine distance has a range of [0, 2].
*
* "dot" - Dot product. Dot distance is the dot product of two vectors. Dot
* distance has a range of (-∞, ∞). If the vectors are normalized (i.e. their
* l2 norm is 1), then dot distance is equivalent to the cosine distance.
*/
distanceType?: "l2" | "cosine" | "dot";
/**
* The number of IVF partitions to create.
*
* For HNSW, we recommend a small number of partitions. Setting this to 1 works
* well for most tables. For very large tables, training just one HNSW graph
* will require too much memory. Each partition becomes its own HNSW graph, so
* setting this value higher reduces the peak memory use of training.
*
*/
numPartitions?: number;
/**
* Number of sub-vectors of PQ.
*
* This value controls how much the vector is compressed during the quantization step.
* The more sub vectors there are the less the vector is compressed. The default is
* the dimension of the vector divided by 16. If the dimension is not evenly divisible
* by 16 we use the dimension divded by 8.
*
* The above two cases are highly preferred. Having 8 or 16 values per subvector allows
* us to use efficient SIMD instructions.
*
* If the dimension is not visible by 8 then we use 1 subvector. This is not ideal and
* will likely result in poor performance.
*
*/
numSubVectors?: number;
/**
* Max iterations to train kmeans.
*
* The default value is 50.
*
* When training an IVF index we use kmeans to calculate the partitions. This parameter
* controls how many iterations of kmeans to run.
*
* Increasing this might improve the quality of the index but in most cases the parameter
* is unused because kmeans will converge with fewer iterations. The parameter is only
* used in cases where kmeans does not appear to converge. In those cases it is unlikely
* that setting this larger will lead to the index converging anyways.
*
*/
maxIterations?: number;
/**
* The rate used to calculate the number of training vectors for kmeans.
*
* Default value is 256.
*
* When an IVF index is trained, we need to calculate partitions. These are groups
* of vectors that are similar to each other. To do this we use an algorithm called kmeans.
*
* Running kmeans on a large dataset can be slow. To speed this up we run kmeans on a
* random sample of the data. This parameter controls the size of the sample. The total
* number of vectors used to train the index is `sample_rate * num_partitions`.
*
* Increasing this value might improve the quality of the index but in most cases the
* default should be sufficient.
*
*/
sampleRate?: number;
/**
* The number of neighbors to select for each vector in the HNSW graph.
*
* The default value is 20.
*
* This value controls the tradeoff between search speed and accuracy.
* The higher the value the more accurate the search but the slower it will be.
*
*/
m?: number;
/**
* The number of candidates to evaluate during the construction of the HNSW graph.
*
* The default value is 300.
*
* This value controls the tradeoff between build speed and accuracy.
* The higher the value the more accurate the build but the slower it will be.
* 150 to 300 is the typical range. 100 is a minimum for good quality search
* results. In most cases, there is no benefit to setting this higher than 500.
* This value should be set to a value that is not less than `ef` in the search phase.
*
*/
efConstruction?: number;
}
/**
* Options to create an `HNSW_SQ` index
*/
export interface HnswSqOptions {
/**
* The distance metric used to train the index.
*
* Default value is "l2".
*
* The following distance types are available:
*
* "l2" - Euclidean distance. This is a very common distance metric that
* accounts for both magnitude and direction when determining the distance
* between vectors. l2 distance has a range of [0, ∞).
*
* "cosine" - Cosine distance. Cosine distance is a distance metric
* calculated from the cosine similarity between two vectors. Cosine
* similarity is a measure of similarity between two non-zero vectors of an
* inner product space. It is defined to equal the cosine of the angle
* between them. Unlike l2, the cosine distance is not affected by the
* magnitude of the vectors. Cosine distance has a range of [0, 2].
*
* "dot" - Dot product. Dot distance is the dot product of two vectors. Dot
* distance has a range of (-∞, ∞). If the vectors are normalized (i.e. their
* l2 norm is 1), then dot distance is equivalent to the cosine distance.
*/
distanceType?: "l2" | "cosine" | "dot";
/**
* The number of IVF partitions to create.
*
* For HNSW, we recommend a small number of partitions. Setting this to 1 works
* well for most tables. For very large tables, training just one HNSW graph
* will require too much memory. Each partition becomes its own HNSW graph, so
* setting this value higher reduces the peak memory use of training.
*
*/
numPartitions?: number;
/**
* Max iterations to train kmeans.
*
* The default value is 50.
*
* When training an IVF index we use kmeans to calculate the partitions. This parameter
* controls how many iterations of kmeans to run.
*
* Increasing this might improve the quality of the index but in most cases the parameter
* is unused because kmeans will converge with fewer iterations. The parameter is only
* used in cases where kmeans does not appear to converge. In those cases it is unlikely
* that setting this larger will lead to the index converging anyways.
*
*/
maxIterations?: number;
/**
* The rate used to calculate the number of training vectors for kmeans.
*
* Default value is 256.
*
* When an IVF index is trained, we need to calculate partitions. These are groups
* of vectors that are similar to each other. To do this we use an algorithm called kmeans.
*
* Running kmeans on a large dataset can be slow. To speed this up we run kmeans on a
* random sample of the data. This parameter controls the size of the sample. The total
* number of vectors used to train the index is `sample_rate * num_partitions`.
*
* Increasing this value might improve the quality of the index but in most cases the
* default should be sufficient.
*
*/
sampleRate?: number;
/**
* The number of neighbors to select for each vector in the HNSW graph.
*
* The default value is 20.
*
* This value controls the tradeoff between search speed and accuracy.
* The higher the value the more accurate the search but the slower it will be.
*
*/
m?: number;
/**
* The number of candidates to evaluate during the construction of the HNSW graph.
*
* The default value is 300.
*
* This value controls the tradeoff between build speed and accuracy.
* The higher the value the more accurate the build but the slower it will be.
* 150 to 300 is the typical range. 100 is a minimum for good quality search
* results. In most cases, there is no benefit to setting this higher than 500.
* This value should be set to a value that is not less than `ef` in the search phase.
*
*/
efConstruction?: number;
}
/**
* Options to create an `IVF_FLAT` index
*/
export interface IvfFlatOptions {
/**
* The number of IVF partitions to create.
*
* This value should generally scale with the number of rows in the dataset.
* By default the number of partitions is the square root of the number of
* rows.
*
* If this value is too large then the first part of the search (picking the
* right partition) will be slow. If this value is too small then the second
* part of the search (searching within a partition) will be slow.
*/
numPartitions?: number;
/**
* Distance type to use to build the index.
*
* Default value is "l2".
*
* This is used when training the index to calculate the IVF partitions
* (vectors are grouped in partitions with similar vectors according to this
* distance type).
*
* The distance type used to train an index MUST match the distance type used
* to search the index. Failure to do so will yield inaccurate results.
*
* The following distance types are available:
*
* "l2" - Euclidean distance. This is a very common distance metric that
* accounts for both magnitude and direction when determining the distance
* between vectors. l2 distance has a range of [0, ∞).
*
* "cosine" - Cosine distance. Cosine distance is a distance metric
* calculated from the cosine similarity between two vectors. Cosine
* similarity is a measure of similarity between two non-zero vectors of an
* inner product space. It is defined to equal the cosine of the angle
* between them. Unlike l2, the cosine distance is not affected by the
* magnitude of the vectors. Cosine distance has a range of [0, 2].
*
* Note: the cosine distance is undefined when one (or both) of the vectors
* are all zeros (there is no direction). These vectors are invalid and may
* never be returned from a vector search.
*
* "dot" - Dot product. Dot distance is the dot product of two vectors. Dot
* distance has a range of (-∞, ∞). If the vectors are normalized (i.e. their
* l2 norm is 1), then dot distance is equivalent to the cosine distance.
*
* "hamming" - Hamming distance. Hamming distance is a distance metric
* calculated from the number of bits that are different between two vectors.
* Hamming distance has a range of [0, dimension]. Note that the hamming distance
* is only valid for binary vectors.
*/
distanceType?: "l2" | "cosine" | "dot" | "hamming";
/**
* Max iteration to train IVF kmeans.
*
* When training an IVF FLAT index we use kmeans to calculate the partitions. This parameter
* controls how many iterations of kmeans to run.
*
* Increasing this might improve the quality of the index but in most cases these extra
* iterations have diminishing returns.
*
* The default value is 50.
*/
maxIterations?: number;
/**
* The number of vectors, per partition, to sample when training IVF kmeans.
*
* When an IVF FLAT index is trained, we need to calculate partitions. These are groups
* of vectors that are similar to each other. To do this we use an algorithm called kmeans.
*
* Running kmeans on a large dataset can be slow. To speed this up we run kmeans on a
* random sample of the data. This parameter controls the size of the sample. The total
* number of vectors used to train the index is `sample_rate * num_partitions`.
*
* Increasing this value might improve the quality of the index but in most cases the
* default should be sufficient.
*
* The default value is 256.
*/
sampleRate?: number;
}
/**
* Options to create a full text search index
*/
export interface FtsOptions {
/**
* Whether to build the index with positions.
* True by default.
* If set to false, the index will not store the positions of the tokens in the text,
* which will make the index smaller and faster to build, but will not support phrase queries.
*/
withPosition?: boolean;
/**
* The tokenizer to use when building the index.
* The default is "simple".
*
* The following tokenizers are available:
*
* "simple" - Simple tokenizer. This tokenizer splits the text into tokens using whitespace and punctuation as a delimiter.
*
* "whitespace" - Whitespace tokenizer. This tokenizer splits the text into tokens using whitespace as a delimiter.
*
* "raw" - Raw tokenizer. This tokenizer does not split the text into tokens and indexes the entire text as a single token.
*/
baseTokenizer?: "simple" | "whitespace" | "raw" | "ngram";
/**
* language for stemming and stop words
* this is only used when `stem` or `remove_stop_words` is true
*/
language?: string;
/**
* maximum token length
* tokens longer than this length will be ignored
*/
maxTokenLength?: number;
/**
* whether to lowercase tokens
*/
lowercase?: boolean;
/**
* whether to stem tokens
*/
stem?: boolean;
/**
* whether to remove stop words
*/
removeStopWords?: boolean;
/**
* whether to remove punctuation
*/
asciiFolding?: boolean;
/**
* ngram min length
*/
ngramMinLength?: number;
/**
* ngram max length
*/
ngramMaxLength?: number;
/**
* whether to only index the prefix of the token for ngram tokenizer
*/
prefixOnly?: boolean;
}
export declare class Index {
private readonly inner;
private constructor();
/**
* Create an IvfPq index
*
* This index stores a compressed (quantized) copy of every vector. These vectors
* are grouped into partitions of similar vectors. Each partition keeps track of
* a centroid which is the average value of all vectors in the group.
*
* During a query the centroids are compared with the query vector to find the closest
* partitions. The compressed vectors in these partitions are then searched to find
* the closest vectors.
*
* The compression scheme is called product quantization. Each vector is divided into
* subvectors and then each subvector is quantized into a small number of bits. the
* parameters `num_bits` and `num_subvectors` control this process, providing a tradeoff
* between index size (and thus search speed) and index accuracy.
*
* The partitioning process is called IVF and the `num_partitions` parameter controls how
* many groups to create.
*
* Note that training an IVF PQ index on a large dataset is a slow operation and
* currently is also a memory intensive operation.
*/
static ivfPq(options?: Partial<IvfPqOptions>): Index;
/**
* Create an IvfRq index
*
* IVF-RQ (RabitQ Quantization) compresses vectors using RabitQ quantization
* and organizes them into IVF partitions.
*
* The compression scheme is called RabitQ quantization. Each dimension is quantized into a small number of bits.
* The parameters `num_bits` and `num_partitions` control this process, providing a tradeoff
* between index size (and thus search speed) and index accuracy.
*
* The partitioning process is called IVF and the `num_partitions` parameter controls how
* many groups to create.
*
* Note that training an IVF RQ index on a large dataset is a slow operation and
* currently is also a memory intensive operation.
*/
static ivfRq(options?: Partial<IvfRqOptions>): Index;
/**
* Create an IvfFlat index
*
* This index groups vectors into partitions of similar vectors. Each partition keeps track of
* a centroid which is the average value of all vectors in the group.
*
* During a query the centroids are compared with the query vector to find the closest
* partitions. The vectors in these partitions are then searched to find
* the closest vectors.
*
* The partitioning process is called IVF and the `num_partitions` parameter controls how
* many groups to create.
*
* Note that training an IVF FLAT index on a large dataset is a slow operation and
* currently is also a memory intensive operation.
*/
static ivfFlat(options?: Partial<IvfFlatOptions>): Index;
/**
* Create a btree index
*
* A btree index is an index on a scalar columns. The index stores a copy of the column
* in sorted order. A header entry is created for each block of rows (currently the
* block size is fixed at 4096). These header entries are stored in a separate
* cacheable structure (a btree). To search for data the header is used to determine
* which blocks need to be read from disk.
*
* For example, a btree index in a table with 1Bi rows requires sizeof(Scalar) * 256Ki
* bytes of memory and will generally need to read sizeof(Scalar) * 4096 bytes to find
* the correct row ids.
*
* This index is good for scalar columns with mostly distinct values and does best when
* the query is highly selective.
*
* The btree index does not currently have any parameters though parameters such as the
* block size may be added in the future.
*/
static btree(): Index;
/**
* Create a bitmap index.
*
* A `Bitmap` index stores a bitmap for each distinct value in the column for every row.
*
* This index works best for low-cardinality columns, where the number of unique values
* is small (i.e., less than a few hundreds).
*/
static bitmap(): Index;
/**
* Create a label list index.
*
* LabelList index is a scalar index that can be used on `List<T>` columns to
* support queries with `array_contains_all` and `array_contains_any`
* using an underlying bitmap index.
*/
static labelList(): Index;
/**
* Create a full text search index
*
* A full text search index is an index on a string column, so that you can conduct full
* text searches on the column.
*
* The results of a full text search are ordered by relevance measured by BM25.
*
* You can combine filters with full text search.
*/
static fts(options?: Partial<FtsOptions>): Index;
/**
*
* Create a hnswPq index
*
* HNSW-PQ stands for Hierarchical Navigable Small World - Product Quantization.
* It is a variant of the HNSW algorithm that uses product quantization to compress
* the vectors.
*
*/
static hnswPq(options?: Partial<HnswPqOptions>): Index;
/**
*
* Create a hnswSq index
*
* HNSW-SQ stands for Hierarchical Navigable Small World - Scalar Quantization.
* It is a variant of the HNSW algorithm that uses scalar quantization to compress
* the vectors.
*
*/
static hnswSq(options?: Partial<HnswSqOptions>): Index;
}
export interface IndexOptions {
/**
* Advanced index configuration
*
* This option allows you to specify a specfic index to create and also
* allows you to pass in configuration for training the index.
*
* See the static methods on Index for details on the various index types.
*
* If this is not supplied then column data type(s) and column statistics
* will be used to determine the most useful kind of index to create.
*/
config?: Index;
/**
* Whether to replace the existing index
*
* If this is false, and another index already exists on the same columns
* and the same name, then an error will be returned. This is true even if
* that index is out of date.
*
* The default is true
*/
replace?: boolean;
/**
* Timeout in seconds to wait for index creation to complete.
*
* If not specified, the method will return immediately after starting the index creation.
*/
waitTimeoutSeconds?: number;
/**
* Optional custom name for the index.
*
* If not provided, a default name will be generated based on the column name.
*/
name?: string;
/**
* Whether to train the index with existing data.
*
* If true (default), the index will be trained with existing data in the table.
* If false, the index will be created empty and populated as new data is added.
*
* Note: This option is only supported for scalar indices. Vector indices always train.
*/
train?: boolean;
}

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"use strict";
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
Object.defineProperty(exports, "__esModule", { value: true });
exports.Index = void 0;
const native_1 = require("./native");
class Index {
inner;
constructor(inner) {
this.inner = inner;
}
/**
* Create an IvfPq index
*
* This index stores a compressed (quantized) copy of every vector. These vectors
* are grouped into partitions of similar vectors. Each partition keeps track of
* a centroid which is the average value of all vectors in the group.
*
* During a query the centroids are compared with the query vector to find the closest
* partitions. The compressed vectors in these partitions are then searched to find
* the closest vectors.
*
* The compression scheme is called product quantization. Each vector is divided into
* subvectors and then each subvector is quantized into a small number of bits. the
* parameters `num_bits` and `num_subvectors` control this process, providing a tradeoff
* between index size (and thus search speed) and index accuracy.
*
* The partitioning process is called IVF and the `num_partitions` parameter controls how
* many groups to create.
*
* Note that training an IVF PQ index on a large dataset is a slow operation and
* currently is also a memory intensive operation.
*/
static ivfPq(options) {
return new Index(native_1.Index.ivfPq(options?.distanceType, options?.numPartitions, options?.numSubVectors, options?.numBits, options?.maxIterations, options?.sampleRate));
}
/**
* Create an IvfRq index
*
* IVF-RQ (RabitQ Quantization) compresses vectors using RabitQ quantization
* and organizes them into IVF partitions.
*
* The compression scheme is called RabitQ quantization. Each dimension is quantized into a small number of bits.
* The parameters `num_bits` and `num_partitions` control this process, providing a tradeoff
* between index size (and thus search speed) and index accuracy.
*
* The partitioning process is called IVF and the `num_partitions` parameter controls how
* many groups to create.
*
* Note that training an IVF RQ index on a large dataset is a slow operation and
* currently is also a memory intensive operation.
*/
static ivfRq(options) {
return new Index(native_1.Index.ivfRq(options?.distanceType, options?.numPartitions, options?.numBits, options?.maxIterations, options?.sampleRate));
}
/**
* Create an IvfFlat index
*
* This index groups vectors into partitions of similar vectors. Each partition keeps track of
* a centroid which is the average value of all vectors in the group.
*
* During a query the centroids are compared with the query vector to find the closest
* partitions. The vectors in these partitions are then searched to find
* the closest vectors.
*
* The partitioning process is called IVF and the `num_partitions` parameter controls how
* many groups to create.
*
* Note that training an IVF FLAT index on a large dataset is a slow operation and
* currently is also a memory intensive operation.
*/
static ivfFlat(options) {
return new Index(native_1.Index.ivfFlat(options?.distanceType, options?.numPartitions, options?.maxIterations, options?.sampleRate));
}
/**
* Create a btree index
*
* A btree index is an index on a scalar columns. The index stores a copy of the column
* in sorted order. A header entry is created for each block of rows (currently the
* block size is fixed at 4096). These header entries are stored in a separate
* cacheable structure (a btree). To search for data the header is used to determine
* which blocks need to be read from disk.
*
* For example, a btree index in a table with 1Bi rows requires sizeof(Scalar) * 256Ki
* bytes of memory and will generally need to read sizeof(Scalar) * 4096 bytes to find
* the correct row ids.
*
* This index is good for scalar columns with mostly distinct values and does best when
* the query is highly selective.
*
* The btree index does not currently have any parameters though parameters such as the
* block size may be added in the future.
*/
static btree() {
return new Index(native_1.Index.btree());
}
/**
* Create a bitmap index.
*
* A `Bitmap` index stores a bitmap for each distinct value in the column for every row.
*
* This index works best for low-cardinality columns, where the number of unique values
* is small (i.e., less than a few hundreds).
*/
static bitmap() {
return new Index(native_1.Index.bitmap());
}
/**
* Create a label list index.
*
* LabelList index is a scalar index that can be used on `List<T>` columns to
* support queries with `array_contains_all` and `array_contains_any`
* using an underlying bitmap index.
*/
static labelList() {
return new Index(native_1.Index.labelList());
}
/**
* Create a full text search index
*
* A full text search index is an index on a string column, so that you can conduct full
* text searches on the column.
*
* The results of a full text search are ordered by relevance measured by BM25.
*
* You can combine filters with full text search.
*/
static fts(options) {
return new Index(native_1.Index.fts(options?.withPosition, options?.baseTokenizer, options?.language, options?.maxTokenLength, options?.lowercase, options?.stem, options?.removeStopWords, options?.asciiFolding, options?.ngramMinLength, options?.ngramMaxLength, options?.prefixOnly));
}
/**
*
* Create a hnswPq index
*
* HNSW-PQ stands for Hierarchical Navigable Small World - Product Quantization.
* It is a variant of the HNSW algorithm that uses product quantization to compress
* the vectors.
*
*/
static hnswPq(options) {
return new Index(native_1.Index.hnswPq(options?.distanceType, options?.numPartitions, options?.numSubVectors, options?.maxIterations, options?.sampleRate, options?.m, options?.efConstruction));
}
/**
*
* Create a hnswSq index
*
* HNSW-SQ stands for Hierarchical Navigable Small World - Scalar Quantization.
* It is a variant of the HNSW algorithm that uses scalar quantization to compress
* the vectors.
*
*/
static hnswSq(options) {
return new Index(native_1.Index.hnswSq(options?.distanceType, options?.numPartitions, options?.maxIterations, options?.sampleRate, options?.m, options?.efConstruction));
}
}
exports.Index = Index;

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import { Data, Schema } from "./arrow";
import { MergeResult, NativeMergeInsertBuilder } from "./native";
/** A builder used to create and run a merge insert operation */
export declare class MergeInsertBuilder {
#private;
/** Construct a MergeInsertBuilder. __Internal use only.__ */
constructor(native: NativeMergeInsertBuilder, schema: Schema | Promise<Schema>);
/**
* Rows that exist in both the source table (new data) and
* the target table (old data) will be updated, replacing
* the old row with the corresponding matching row.
*
* If there are multiple matches then the behavior is undefined.
* Currently this causes multiple copies of the row to be created
* but that behavior is subject to change.
*
* An optional condition may be specified. If it is, then only
* matched rows that satisfy the condtion will be updated. Any
* rows that do not satisfy the condition will be left as they
* are. Failing to satisfy the condition does not cause a
* "matched row" to become a "not matched" row.
*
* The condition should be an SQL string. Use the prefix
* target. to refer to rows in the target table (old data)
* and the prefix source. to refer to rows in the source
* table (new data).
*
* For example, "target.last_update < source.last_update"
*/
whenMatchedUpdateAll(options?: {
where: string;
}): MergeInsertBuilder;
/**
* Rows that exist only in the source table (new data) should
* be inserted into the target table.
*/
whenNotMatchedInsertAll(): MergeInsertBuilder;
/**
* Rows that exist only in the target table (old data) will be
* deleted. An optional condition can be provided to limit what
* data is deleted.
*
* @param options.where - An optional condition to limit what data is deleted
*/
whenNotMatchedBySourceDelete(options?: {
where: string;
}): MergeInsertBuilder;
/**
* Controls whether to use indexes for the merge operation.
*
* When set to `true` (the default), the operation will use an index if available
* on the join key for improved performance. When set to `false`, it forces a full
* table scan even if an index exists. This can be useful for benchmarking or when
* the query optimizer chooses a suboptimal path.
*
* @param useIndex - Whether to use indices for the merge operation. Defaults to `true`.
*/
useIndex(useIndex: boolean): MergeInsertBuilder;
/**
* Executes the merge insert operation
*
* @returns {Promise<MergeResult>} the merge result
*/
execute(data: Data, execOptions?: Partial<WriteExecutionOptions>): Promise<MergeResult>;
}
export interface WriteExecutionOptions {
/**
* Maximum time to run the operation before cancelling it.
*
* By default, there is a 30-second timeout that is only enforced after the
* first attempt. This is to prevent spending too long retrying to resolve
* conflicts. For example, if a write attempt takes 20 seconds and fails,
* the second attempt will be cancelled after 10 seconds, hitting the
* 30-second timeout. However, a write that takes one hour and succeeds on the
* first attempt will not be cancelled.
*
* When this is set, the timeout is enforced on all attempts, including the first.
*/
timeoutMs?: number;
}

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"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.MergeInsertBuilder = void 0;
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
const arrow_1 = require("./arrow");
/** A builder used to create and run a merge insert operation */
class MergeInsertBuilder {
#native;
#schema;
/** Construct a MergeInsertBuilder. __Internal use only.__ */
constructor(native, schema) {
this.#native = native;
this.#schema = schema;
}
/**
* Rows that exist in both the source table (new data) and
* the target table (old data) will be updated, replacing
* the old row with the corresponding matching row.
*
* If there are multiple matches then the behavior is undefined.
* Currently this causes multiple copies of the row to be created
* but that behavior is subject to change.
*
* An optional condition may be specified. If it is, then only
* matched rows that satisfy the condtion will be updated. Any
* rows that do not satisfy the condition will be left as they
* are. Failing to satisfy the condition does not cause a
* "matched row" to become a "not matched" row.
*
* The condition should be an SQL string. Use the prefix
* target. to refer to rows in the target table (old data)
* and the prefix source. to refer to rows in the source
* table (new data).
*
* For example, "target.last_update < source.last_update"
*/
whenMatchedUpdateAll(options) {
return new MergeInsertBuilder(this.#native.whenMatchedUpdateAll(options?.where), this.#schema);
}
/**
* Rows that exist only in the source table (new data) should
* be inserted into the target table.
*/
whenNotMatchedInsertAll() {
return new MergeInsertBuilder(this.#native.whenNotMatchedInsertAll(), this.#schema);
}
/**
* Rows that exist only in the target table (old data) will be
* deleted. An optional condition can be provided to limit what
* data is deleted.
*
* @param options.where - An optional condition to limit what data is deleted
*/
whenNotMatchedBySourceDelete(options) {
return new MergeInsertBuilder(this.#native.whenNotMatchedBySourceDelete(options?.where), this.#schema);
}
/**
* Controls whether to use indexes for the merge operation.
*
* When set to `true` (the default), the operation will use an index if available
* on the join key for improved performance. When set to `false`, it forces a full
* table scan even if an index exists. This can be useful for benchmarking or when
* the query optimizer chooses a suboptimal path.
*
* @param useIndex - Whether to use indices for the merge operation. Defaults to `true`.
*/
useIndex(useIndex) {
return new MergeInsertBuilder(this.#native.useIndex(useIndex), this.#schema);
}
/**
* Executes the merge insert operation
*
* @returns {Promise<MergeResult>} the merge result
*/
async execute(data, execOptions) {
let schema;
if (this.#schema instanceof Promise) {
schema = await this.#schema;
this.#schema = schema; // In case of future calls
}
else {
schema = this.#schema;
}
if (execOptions?.timeoutMs !== undefined) {
this.#native.setTimeout(execOptions.timeoutMs);
}
const buffer = await (0, arrow_1.fromDataToBuffer)(data, undefined, schema);
return await this.#native.execute(buffer);
}
}
exports.MergeInsertBuilder = MergeInsertBuilder;

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/* tslint:disable */
/* eslint-disable */
/* auto-generated by NAPI-RS */
export interface SplitRandomOptions {
ratios?: Array<number>
counts?: Array<number>
fixed?: number
seed?: number
splitNames?: Array<string>
}
export interface SplitHashOptions {
columns: Array<string>
splitWeights: Array<number>
discardWeight?: number
splitNames?: Array<string>
}
export interface SplitSequentialOptions {
ratios?: Array<number>
counts?: Array<number>
fixed?: number
splitNames?: Array<string>
}
export interface SplitCalculatedOptions {
calculation: string
splitNames?: Array<string>
}
export interface ShuffleOptions {
seed?: number
clumpSize?: number
}
/** Create a permutation builder for the given table */
export declare function permutationBuilder(table: Table): PermutationBuilder
/** Timeout configuration for remote HTTP client. */
export interface TimeoutConfig {
/**
* The overall timeout for the entire request in seconds. This includes
* connection, send, and read time. If the entire request doesn't complete
* within this time, it will fail. Default is None (no overall timeout).
* This can also be set via the environment variable `LANCE_CLIENT_TIMEOUT`,
* as an integer number of seconds.
*/
timeout?: number
/**
* The timeout for establishing a connection in seconds. Default is 120
* seconds (2 minutes). This can also be set via the environment variable
* `LANCE_CLIENT_CONNECT_TIMEOUT`, as an integer number of seconds.
*/
connectTimeout?: number
/**
* The timeout for reading data from the server in seconds. Default is 300
* seconds (5 minutes). This can also be set via the environment variable
* `LANCE_CLIENT_READ_TIMEOUT`, as an integer number of seconds.
*/
readTimeout?: number
/**
* The timeout for keeping idle connections in the connection pool in seconds.
* Default is 300 seconds (5 minutes). This can also be set via the
* environment variable `LANCE_CLIENT_CONNECTION_TIMEOUT`, as an integer
* number of seconds.
*/
poolIdleTimeout?: number
}
/** Retry configuration for the remote HTTP client. */
export interface RetryConfig {
/**
* The maximum number of retries for a request. Default is 3. You can also
* set this via the environment variable `LANCE_CLIENT_MAX_RETRIES`.
*/
retries?: number
/**
* The maximum number of retries for connection errors. Default is 3. You
* can also set this via the environment variable `LANCE_CLIENT_CONNECT_RETRIES`.
*/
connectRetries?: number
/**
* The maximum number of retries for read errors. Default is 3. You can also
* set this via the environment variable `LANCE_CLIENT_READ_RETRIES`.
*/
readRetries?: number
/**
* The backoff factor to apply between retries. Default is 0.25. Between each retry
* the client will wait for the amount of seconds:
* `{backoff factor} * (2 ** ({number of previous retries}))`. So for the default
* of 0.25, the first retry will wait 0.25 seconds, the second retry will wait 0.5
* seconds, the third retry will wait 1 second, etc.
*
* You can also set this via the environment variable
* `LANCE_CLIENT_RETRY_BACKOFF_FACTOR`.
*/
backoffFactor?: number
/**
* The jitter to apply to the backoff factor, in seconds. Default is 0.25.
*
* A random value between 0 and `backoff_jitter` will be added to the backoff
* factor in seconds. So for the default of 0.25 seconds, between 0 and 250
* milliseconds will be added to the sleep between each retry.
*
* You can also set this via the environment variable
* `LANCE_CLIENT_RETRY_BACKOFF_JITTER`.
*/
backoffJitter?: number
/**
* The HTTP status codes for which to retry the request. Default is
* [429, 500, 502, 503].
*
* You can also set this via the environment variable
* `LANCE_CLIENT_RETRY_STATUSES`. Use a comma-separated list of integers.
*/
statuses?: Array<number>
}
/** TLS/mTLS configuration for the remote HTTP client. */
export interface TlsConfig {
/** Path to the client certificate file (PEM format) for mTLS authentication. */
certFile?: string
/** Path to the client private key file (PEM format) for mTLS authentication. */
keyFile?: string
/** Path to the CA certificate file (PEM format) for server verification. */
sslCaCert?: string
/** Whether to verify the hostname in the server's certificate. */
assertHostname?: boolean
}
export interface ClientConfig {
userAgent?: string
retryConfig?: RetryConfig
timeoutConfig?: TimeoutConfig
extraHeaders?: Record<string, string>
idDelimiter?: string
tlsConfig?: TlsConfig
}
export interface RerankerCallbacks {
rerankHybrid: (...args: any[]) => any
}
export interface RerankHybridCallbackArgs {
query: string
vecResults: Array<number>
ftsResults: Array<number>
}
/** A description of an index currently configured on a column */
export interface IndexConfig {
/** The name of the index */
name: string
/** The type of the index */
indexType: string
/**
* The columns in the index
*
* Currently this is always an array of size 1. In the future there may
* be more columns to represent composite indices.
*/
columns: Array<string>
}
/** Statistics about a compaction operation. */
export interface CompactionStats {
/** The number of fragments removed */
fragmentsRemoved: number
/** The number of new, compacted fragments added */
fragmentsAdded: number
/** The number of data files removed */
filesRemoved: number
/** The number of new, compacted data files added */
filesAdded: number
}
/** Statistics about a cleanup operation */
export interface RemovalStats {
/** The number of bytes removed */
bytesRemoved: number
/** The number of old versions removed */
oldVersionsRemoved: number
}
/** Statistics about an optimize operation */
export interface OptimizeStats {
/** Statistics about the compaction operation */
compaction: CompactionStats
/** Statistics about the removal operation */
prune: RemovalStats
}
/**
* A definition of a column alteration. The alteration changes the column at
* `path` to have the new name `name`, to be nullable if `nullable` is true,
* and to have the data type `data_type`. At least one of `rename` or `nullable`
* must be provided.
*/
export interface ColumnAlteration {
/**
* The path to the column to alter. This is a dot-separated path to the column.
* If it is a top-level column then it is just the name of the column. If it is
* a nested column then it is the path to the column, e.g. "a.b.c" for a column
* `c` nested inside a column `b` nested inside a column `a`.
*/
path: string
/**
* The new name of the column. If not provided then the name will not be changed.
* This must be distinct from the names of all other columns in the table.
*/
rename?: string
/**
* A new data type for the column. If not provided then the data type will not be changed.
* Changing data types is limited to casting to the same general type. For example, these
* changes are valid:
* * `int32` -> `int64` (integers)
* * `double` -> `float` (floats)
* * `string` -> `large_string` (strings)
* But these changes are not:
* * `int32` -> `double` (mix integers and floats)
* * `string` -> `int32` (mix strings and integers)
*/
dataType?: string
/** Set the new nullability. Note that a nullable column cannot be made non-nullable. */
nullable?: boolean
}
/** A definition of a new column to add to a table. */
export interface AddColumnsSql {
/** The name of the new column. */
name: string
/**
* The values to populate the new column with, as a SQL expression.
* The expression can reference other columns in the table.
*/
valueSql: string
}
export interface IndexStatistics {
/** The number of rows indexed by the index */
numIndexedRows: number
/** The number of rows not indexed */
numUnindexedRows: number
/** The type of the index */
indexType: string
/**
* The type of the distance function used by the index. This is only
* present for vector indices. Scalar and full text search indices do
* not have a distance function.
*/
distanceType?: string
/** The number of parts this index is split into. */
numIndices?: number
/**
* The KMeans loss value of the index,
* it is only present for vector indices.
*/
loss?: number
}
export interface TableStatistics {
/** The total number of bytes in the table */
totalBytes: number
/** The number of rows in the table */
numRows: number
/** The number of indices in the table */
numIndices: number
/** Statistics on table fragments */
fragmentStats: FragmentStatistics
}
export interface FragmentStatistics {
/** The number of fragments in the table */
numFragments: number
/** The number of uncompacted fragments in the table */
numSmallFragments: number
/** Statistics on the number of rows in the table fragments */
lengths: FragmentSummaryStats
}
export interface FragmentSummaryStats {
/** The number of rows in the fragment with the fewest rows */
min: number
/** The number of rows in the fragment with the most rows */
max: number
/** The mean number of rows in the fragments */
mean: number
/** The 25th percentile of number of rows in the fragments */
p25: number
/** The 50th percentile of number of rows in the fragments */
p50: number
/** The 75th percentile of number of rows in the fragments */
p75: number
/** The 99th percentile of number of rows in the fragments */
p99: number
}
export interface Version {
version: number
timestamp: number
metadata: Record<string, string>
}
export interface UpdateResult {
rowsUpdated: number
version: number
}
export interface AddResult {
version: number
}
export interface DeleteResult {
version: number
}
export interface MergeResult {
version: number
numInsertedRows: number
numUpdatedRows: number
numDeletedRows: number
numAttempts: number
}
export interface AddColumnsResult {
version: number
}
export interface AlterColumnsResult {
version: number
}
export interface DropColumnsResult {
version: number
}
export interface ConnectionOptions {
/**
* (For LanceDB OSS only): The interval, in seconds, at which to check for
* updates to the table from other processes. If None, then consistency is not
* checked. For performance reasons, this is the default. For strong
* consistency, set this to zero seconds. Then every read will check for
* updates from other processes. As a compromise, you can set this to a
* non-zero value for eventual consistency. If more than that interval
* has passed since the last check, then the table will be checked for updates.
* Note: this consistency only applies to read operations. Write operations are
* always consistent.
*/
readConsistencyInterval?: number
/**
* (For LanceDB OSS only): configuration for object storage.
*
* The available options are described at https://lancedb.com/docs/storage/
*/
storageOptions?: Record<string, string>
/**
* (For LanceDB OSS only): the session to use for this connection. Holds
* shared caches and other session-specific state.
*/
session?: Session
/** (For LanceDB cloud only): configuration for the remote HTTP client. */
clientConfig?: ClientConfig
/**
* (For LanceDB cloud only): the API key to use with LanceDB Cloud.
*
* Can also be set via the environment variable `LANCEDB_API_KEY`.
*/
apiKey?: string
/**
* (For LanceDB cloud only): the region to use for LanceDB cloud.
* Defaults to 'us-east-1'.
*/
region?: string
/**
* (For LanceDB cloud only): the host to use for LanceDB cloud. Used
* for testing purposes.
*/
hostOverride?: string
}
export interface OpenTableOptions {
storageOptions?: Record<string, string>
}
export class Connection {
/** Create a new Connection instance from the given URI. */
static new(uri: string, options: ConnectionOptions, headerProvider?: JsHeaderProvider | undefined | null): Promise<Connection>
display(): string
isOpen(): boolean
close(): void
/** List all tables in the dataset. */
tableNames(namespace: Array<string>, startAfter?: string | undefined | null, limit?: number | undefined | null): Promise<Array<string>>
/**
* Create table from a Apache Arrow IPC (file) buffer.
*
* Parameters:
* - name: The name of the table.
* - buf: The buffer containing the IPC file.
*
*/
createTable(name: string, buf: Buffer, mode: string, namespace: Array<string>, storageOptions?: Record<string, string> | undefined | null): Promise<Table>
createEmptyTable(name: string, schemaBuf: Buffer, mode: string, namespace: Array<string>, storageOptions?: Record<string, string> | undefined | null): Promise<Table>
openTable(name: string, namespace: Array<string>, storageOptions?: Record<string, string> | undefined | null, indexCacheSize?: number | undefined | null): Promise<Table>
cloneTable(targetTableName: string, sourceUri: string, targetNamespace: Array<string>, sourceVersion: number | undefined | null, sourceTag: string | undefined | null, isShallow: boolean): Promise<Table>
/** Drop table with the name. Or raise an error if the table does not exist. */
dropTable(name: string, namespace: Array<string>): Promise<void>
dropAllTables(namespace: Array<string>): Promise<void>
}
/**
* JavaScript HeaderProvider implementation that wraps a JavaScript callback.
* This is the only native header provider - all header provider implementations
* should provide a JavaScript function that returns headers.
*/
export class JsHeaderProvider {
/** Create a new JsHeaderProvider from a JavaScript callback */
constructor(getHeadersCallback: (...args: any[]) => any)
}
export class Index {
static ivfPq(distanceType?: string | undefined | null, numPartitions?: number | undefined | null, numSubVectors?: number | undefined | null, numBits?: number | undefined | null, maxIterations?: number | undefined | null, sampleRate?: number | undefined | null): Index
static ivfRq(distanceType?: string | undefined | null, numPartitions?: number | undefined | null, numBits?: number | undefined | null, maxIterations?: number | undefined | null, sampleRate?: number | undefined | null): Index
static ivfFlat(distanceType?: string | undefined | null, numPartitions?: number | undefined | null, maxIterations?: number | undefined | null, sampleRate?: number | undefined | null): Index
static btree(): Index
static bitmap(): Index
static labelList(): Index
static fts(withPosition?: boolean | undefined | null, baseTokenizer?: string | undefined | null, language?: string | undefined | null, maxTokenLength?: number | undefined | null, lowerCase?: boolean | undefined | null, stem?: boolean | undefined | null, removeStopWords?: boolean | undefined | null, asciiFolding?: boolean | undefined | null, ngramMinLength?: number | undefined | null, ngramMaxLength?: number | undefined | null, prefixOnly?: boolean | undefined | null): Index
static hnswPq(distanceType?: string | undefined | null, numPartitions?: number | undefined | null, numSubVectors?: number | undefined | null, maxIterations?: number | undefined | null, sampleRate?: number | undefined | null, m?: number | undefined | null, efConstruction?: number | undefined | null): Index
static hnswSq(distanceType?: string | undefined | null, numPartitions?: number | undefined | null, maxIterations?: number | undefined | null, sampleRate?: number | undefined | null, m?: number | undefined | null, efConstruction?: number | undefined | null): Index
}
/** Typescript-style Async Iterator over RecordBatches */
export class RecordBatchIterator {
next(): Promise<Buffer | null>
}
/** A builder used to create and run a merge insert operation */
export class NativeMergeInsertBuilder {
whenMatchedUpdateAll(condition?: string | undefined | null): NativeMergeInsertBuilder
whenNotMatchedInsertAll(): NativeMergeInsertBuilder
whenNotMatchedBySourceDelete(filter?: string | undefined | null): NativeMergeInsertBuilder
setTimeout(timeout: number): void
useIndex(useIndex: boolean): NativeMergeInsertBuilder
execute(buf: Buffer): Promise<MergeResult>
}
export class PermutationBuilder {
persist(connection: Connection, tableName: string): PermutationBuilder
/** Configure random splits */
splitRandom(options: SplitRandomOptions): PermutationBuilder
/** Configure hash-based splits */
splitHash(options: SplitHashOptions): PermutationBuilder
/** Configure sequential splits */
splitSequential(options: SplitSequentialOptions): PermutationBuilder
/** Configure calculated splits */
splitCalculated(options: SplitCalculatedOptions): PermutationBuilder
/** Configure shuffling */
shuffle(options: ShuffleOptions): PermutationBuilder
/** Configure filtering */
filter(filter: string): PermutationBuilder
/** Execute the permutation builder and create the table */
execute(): Promise<Table>
}
export class Query {
onlyIf(predicate: string): void
fullTextSearch(query: object): void
select(columns: Array<[string, string]>): void
selectColumns(columns: Array<string>): void
limit(limit: number): void
offset(offset: number): void
nearestTo(vector: Float32Array): VectorQuery
fastSearch(): void
withRowId(): void
outputSchema(): Promise<Buffer>
execute(maxBatchLength?: number | undefined | null, timeoutMs?: number | undefined | null): Promise<RecordBatchIterator>
explainPlan(verbose: boolean): Promise<string>
analyzePlan(): Promise<string>
}
export class VectorQuery {
column(column: string): void
addQueryVector(vector: Float32Array): void
distanceType(distanceType: string): void
postfilter(): void
refineFactor(refineFactor: number): void
nprobes(nprobe: number): void
minimumNprobes(minimumNprobe: number): void
maximumNprobes(maximumNprobes: number): void
distanceRange(lowerBound?: number | undefined | null, upperBound?: number | undefined | null): void
ef(ef: number): void
bypassVectorIndex(): void
onlyIf(predicate: string): void
fullTextSearch(query: object): void
select(columns: Array<[string, string]>): void
selectColumns(columns: Array<string>): void
limit(limit: number): void
offset(offset: number): void
fastSearch(): void
withRowId(): void
rerank(callbacks: RerankerCallbacks): void
outputSchema(): Promise<Buffer>
execute(maxBatchLength?: number | undefined | null, timeoutMs?: number | undefined | null): Promise<RecordBatchIterator>
explainPlan(verbose: boolean): Promise<string>
analyzePlan(): Promise<string>
}
export class TakeQuery {
select(columns: Array<[string, string]>): void
selectColumns(columns: Array<string>): void
withRowId(): void
outputSchema(): Promise<Buffer>
execute(maxBatchLength?: number | undefined | null, timeoutMs?: number | undefined | null): Promise<RecordBatchIterator>
explainPlan(verbose: boolean): Promise<string>
analyzePlan(): Promise<string>
}
export class JsFullTextQuery {
static matchQuery(query: string, column: string, boost: number, fuzziness: number | undefined | null, maxExpansions: number, operator: string, prefixLength: number): JsFullTextQuery
static phraseQuery(query: string, column: string, slop: number): JsFullTextQuery
static boostQuery(positive: JsFullTextQuery, negative: JsFullTextQuery, negativeBoost?: number | undefined | null): JsFullTextQuery
static multiMatchQuery(query: string, columns: Array<string>, boosts: Array<number> | undefined | null, operator: string): JsFullTextQuery
static booleanQuery(queries: Array<[string, JsFullTextQuery]>): JsFullTextQuery
get queryType(): string
}
/**
* Reranker implementation that "wraps" a NodeJS Reranker implementation.
* This contains references to the callbacks that can be used to invoke the
* reranking methods on the NodeJS implementation and handles serializing the
* record batches to Arrow IPC buffers.
*/
export class Reranker {
static new(callbacks: RerankerCallbacks): Reranker
}
export type RRFReranker = RrfReranker
/** Wrapper around rust RRFReranker */
export class RrfReranker {
static tryNew(k: Float32Array): Promise<RrfReranker>
rerankHybrid(query: string, vecResults: Buffer, ftsResults: Buffer): Promise<Buffer>
}
/**
* A session for managing caches and object stores across LanceDB operations.
*
* Sessions allow you to configure cache sizes for index and metadata caches,
* which can significantly impact memory use and performance. They can
* also be re-used across multiple connections to share the same cache state.
*/
export class Session {
/**
* Create a new session with custom cache sizes.
*
* # Parameters
*
* - `index_cache_size_bytes`: The size of the index cache in bytes.
* Index data is stored in memory in this cache to speed up queries.
* Defaults to 6GB if not specified.
* - `metadata_cache_size_bytes`: The size of the metadata cache in bytes.
* The metadata cache stores file metadata and schema information in memory.
* This cache improves scan and write performance.
* Defaults to 1GB if not specified.
*/
constructor(indexCacheSizeBytes?: bigint | undefined | null, metadataCacheSizeBytes?: bigint | undefined | null)
/**
* Create a session with default cache sizes.
*
* This is equivalent to creating a session with 6GB index cache
* and 1GB metadata cache.
*/
static default(): Session
/** Get the current size of the session caches in bytes. */
sizeBytes(): bigint
/** Get the approximate number of items cached in the session. */
approxNumItems(): number
}
export class Table {
name: string
display(): string
isOpen(): boolean
close(): void
/** Return Schema as empty Arrow IPC file. */
schema(): Promise<Buffer>
add(buf: Buffer, mode: string): Promise<AddResult>
countRows(filter?: string | undefined | null): Promise<number>
delete(predicate: string): Promise<DeleteResult>
createIndex(index: Index | undefined | null, column: string, replace?: boolean | undefined | null, waitTimeoutS?: number | undefined | null, name?: string | undefined | null, train?: boolean | undefined | null): Promise<void>
dropIndex(indexName: string): Promise<void>
prewarmIndex(indexName: string): Promise<void>
waitForIndex(indexNames: Array<string>, timeoutS: number): Promise<void>
stats(): Promise<TableStatistics>
update(onlyIf: string | undefined | null, columns: Array<[string, string]>): Promise<UpdateResult>
query(): Query
takeOffsets(offsets: Array<number>): TakeQuery
takeRowIds(rowIds: Array<number>): TakeQuery
vectorSearch(vector: Float32Array): VectorQuery
addColumns(transforms: Array<AddColumnsSql>): Promise<AddColumnsResult>
alterColumns(alterations: Array<ColumnAlteration>): Promise<AlterColumnsResult>
dropColumns(columns: Array<string>): Promise<DropColumnsResult>
version(): Promise<number>
checkout(version: number): Promise<void>
checkoutTag(tag: string): Promise<void>
checkoutLatest(): Promise<void>
listVersions(): Promise<Array<Version>>
restore(): Promise<void>
tags(): Promise<Tags>
optimize(olderThanMs?: number | undefined | null, deleteUnverified?: boolean | undefined | null): Promise<OptimizeStats>
listIndices(): Promise<Array<IndexConfig>>
indexStats(indexName: string): Promise<IndexStatistics | null>
mergeInsert(on: Array<string>): NativeMergeInsertBuilder
usesV2ManifestPaths(): Promise<boolean>
migrateManifestPathsV2(): Promise<void>
}
export class TagContents {
version: number
manifestSize: number
}
export class Tags {
list(): Promise<Record<string, TagContents>>
getVersion(tag: string): Promise<number>
create(tag: string, version: number): Promise<void>
delete(tag: string): Promise<void>
update(tag: string, version: number): Promise<void>
}

339
extensions/memory-lancedb/node_modules/@lancedb/lancedb/dist/native.js generated vendored Normal file
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@ -0,0 +1,339 @@
"use strict";
/* tslint:disable */
/* eslint-disable */
/* prettier-ignore */
/* auto-generated by NAPI-RS */
const { existsSync, readFileSync } = require('fs');
const { join } = require('path');
const { platform, arch } = process;
let nativeBinding = null;
let localFileExisted = false;
let loadError = null;
function isMusl() {
// For Node 10
if (!process.report || typeof process.report.getReport !== 'function') {
try {
const lddPath = require('child_process').execSync('which ldd').toString().trim();
return readFileSync(lddPath, 'utf8').includes('musl');
}
catch (e) {
return true;
}
}
else {
const { glibcVersionRuntime } = process.report.getReport().header;
return !glibcVersionRuntime;
}
}
switch (platform) {
case 'android':
switch (arch) {
case 'arm64':
localFileExisted = existsSync(join(__dirname, 'lancedb.android-arm64.node'));
try {
if (localFileExisted) {
nativeBinding = require('./lancedb.android-arm64.node');
}
else {
nativeBinding = require('@lancedb/lancedb-android-arm64');
}
}
catch (e) {
loadError = e;
}
break;
case 'arm':
localFileExisted = existsSync(join(__dirname, 'lancedb.android-arm-eabi.node'));
try {
if (localFileExisted) {
nativeBinding = require('./lancedb.android-arm-eabi.node');
}
else {
nativeBinding = require('@lancedb/lancedb-android-arm-eabi');
}
}
catch (e) {
loadError = e;
}
break;
default:
throw new Error(`Unsupported architecture on Android ${arch}`);
}
break;
case 'win32':
switch (arch) {
case 'x64':
localFileExisted = existsSync(join(__dirname, 'lancedb.win32-x64-msvc.node'));
try {
if (localFileExisted) {
nativeBinding = require('./lancedb.win32-x64-msvc.node');
}
else {
nativeBinding = require('@lancedb/lancedb-win32-x64-msvc');
}
}
catch (e) {
loadError = e;
}
break;
case 'ia32':
localFileExisted = existsSync(join(__dirname, 'lancedb.win32-ia32-msvc.node'));
try {
if (localFileExisted) {
nativeBinding = require('./lancedb.win32-ia32-msvc.node');
}
else {
nativeBinding = require('@lancedb/lancedb-win32-ia32-msvc');
}
}
catch (e) {
loadError = e;
}
break;
case 'arm64':
localFileExisted = existsSync(join(__dirname, 'lancedb.win32-arm64-msvc.node'));
try {
if (localFileExisted) {
nativeBinding = require('./lancedb.win32-arm64-msvc.node');
}
else {
nativeBinding = require('@lancedb/lancedb-win32-arm64-msvc');
}
}
catch (e) {
loadError = e;
}
break;
default:
throw new Error(`Unsupported architecture on Windows: ${arch}`);
}
break;
case 'darwin':
localFileExisted = existsSync(join(__dirname, 'lancedb.darwin-universal.node'));
try {
if (localFileExisted) {
nativeBinding = require('./lancedb.darwin-universal.node');
}
else {
nativeBinding = require('@lancedb/lancedb-darwin-universal');
}
break;
}
catch { }
switch (arch) {
case 'x64':
localFileExisted = existsSync(join(__dirname, 'lancedb.darwin-x64.node'));
try {
if (localFileExisted) {
nativeBinding = require('./lancedb.darwin-x64.node');
}
else {
nativeBinding = require('@lancedb/lancedb-darwin-x64');
}
}
catch (e) {
loadError = e;
}
break;
case 'arm64':
localFileExisted = existsSync(join(__dirname, 'lancedb.darwin-arm64.node'));
try {
if (localFileExisted) {
nativeBinding = require('./lancedb.darwin-arm64.node');
}
else {
nativeBinding = require('@lancedb/lancedb-darwin-arm64');
}
}
catch (e) {
loadError = e;
}
break;
default:
throw new Error(`Unsupported architecture on macOS: ${arch}`);
}
break;
case 'freebsd':
if (arch !== 'x64') {
throw new Error(`Unsupported architecture on FreeBSD: ${arch}`);
}
localFileExisted = existsSync(join(__dirname, 'lancedb.freebsd-x64.node'));
try {
if (localFileExisted) {
nativeBinding = require('./lancedb.freebsd-x64.node');
}
else {
nativeBinding = require('@lancedb/lancedb-freebsd-x64');
}
}
catch (e) {
loadError = e;
}
break;
case 'linux':
switch (arch) {
case 'x64':
if (isMusl()) {
localFileExisted = existsSync(join(__dirname, 'lancedb.linux-x64-musl.node'));
try {
if (localFileExisted) {
nativeBinding = require('./lancedb.linux-x64-musl.node');
}
else {
nativeBinding = require('@lancedb/lancedb-linux-x64-musl');
}
}
catch (e) {
loadError = e;
}
}
else {
localFileExisted = existsSync(join(__dirname, 'lancedb.linux-x64-gnu.node'));
try {
if (localFileExisted) {
nativeBinding = require('./lancedb.linux-x64-gnu.node');
}
else {
nativeBinding = require('@lancedb/lancedb-linux-x64-gnu');
}
}
catch (e) {
loadError = e;
}
}
break;
case 'arm64':
if (isMusl()) {
localFileExisted = existsSync(join(__dirname, 'lancedb.linux-arm64-musl.node'));
try {
if (localFileExisted) {
nativeBinding = require('./lancedb.linux-arm64-musl.node');
}
else {
nativeBinding = require('@lancedb/lancedb-linux-arm64-musl');
}
}
catch (e) {
loadError = e;
}
}
else {
localFileExisted = existsSync(join(__dirname, 'lancedb.linux-arm64-gnu.node'));
try {
if (localFileExisted) {
nativeBinding = require('./lancedb.linux-arm64-gnu.node');
}
else {
nativeBinding = require('@lancedb/lancedb-linux-arm64-gnu');
}
}
catch (e) {
loadError = e;
}
}
break;
case 'arm':
if (isMusl()) {
localFileExisted = existsSync(join(__dirname, 'lancedb.linux-arm-musleabihf.node'));
try {
if (localFileExisted) {
nativeBinding = require('./lancedb.linux-arm-musleabihf.node');
}
else {
nativeBinding = require('@lancedb/lancedb-linux-arm-musleabihf');
}
}
catch (e) {
loadError = e;
}
}
else {
localFileExisted = existsSync(join(__dirname, 'lancedb.linux-arm-gnueabihf.node'));
try {
if (localFileExisted) {
nativeBinding = require('./lancedb.linux-arm-gnueabihf.node');
}
else {
nativeBinding = require('@lancedb/lancedb-linux-arm-gnueabihf');
}
}
catch (e) {
loadError = e;
}
}
break;
case 'riscv64':
if (isMusl()) {
localFileExisted = existsSync(join(__dirname, 'lancedb.linux-riscv64-musl.node'));
try {
if (localFileExisted) {
nativeBinding = require('./lancedb.linux-riscv64-musl.node');
}
else {
nativeBinding = require('@lancedb/lancedb-linux-riscv64-musl');
}
}
catch (e) {
loadError = e;
}
}
else {
localFileExisted = existsSync(join(__dirname, 'lancedb.linux-riscv64-gnu.node'));
try {
if (localFileExisted) {
nativeBinding = require('./lancedb.linux-riscv64-gnu.node');
}
else {
nativeBinding = require('@lancedb/lancedb-linux-riscv64-gnu');
}
}
catch (e) {
loadError = e;
}
}
break;
case 's390x':
localFileExisted = existsSync(join(__dirname, 'lancedb.linux-s390x-gnu.node'));
try {
if (localFileExisted) {
nativeBinding = require('./lancedb.linux-s390x-gnu.node');
}
else {
nativeBinding = require('@lancedb/lancedb-linux-s390x-gnu');
}
}
catch (e) {
loadError = e;
}
break;
default:
throw new Error(`Unsupported architecture on Linux: ${arch}`);
}
break;
default:
throw new Error(`Unsupported OS: ${platform}, architecture: ${arch}`);
}
if (!nativeBinding) {
if (loadError) {
throw loadError;
}
throw new Error(`Failed to load native binding`);
}
const { Connection, JsHeaderProvider, Index, RecordBatchIterator, NativeMergeInsertBuilder, PermutationBuilder, permutationBuilder, Query, VectorQuery, TakeQuery, JsFullTextQuery, Reranker, RrfReranker, Session, Table, TagContents, Tags } = nativeBinding;
module.exports.Connection = Connection;
module.exports.JsHeaderProvider = JsHeaderProvider;
module.exports.Index = Index;
module.exports.RecordBatchIterator = RecordBatchIterator;
module.exports.NativeMergeInsertBuilder = NativeMergeInsertBuilder;
module.exports.PermutationBuilder = PermutationBuilder;
module.exports.permutationBuilder = permutationBuilder;
module.exports.Query = Query;
module.exports.VectorQuery = VectorQuery;
module.exports.TakeQuery = TakeQuery;
module.exports.JsFullTextQuery = JsFullTextQuery;
module.exports.Reranker = Reranker;
module.exports.RrfReranker = RrfReranker;
module.exports.Session = Session;
module.exports.Table = Table;
module.exports.TagContents = TagContents;
module.exports.Tags = Tags;

143
extensions/memory-lancedb/node_modules/@lancedb/lancedb/dist/permutation.d.ts generated vendored Normal file
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import { Connection } from "./connection.js";
import { PermutationBuilder as NativePermutationBuilder, ShuffleOptions, SplitCalculatedOptions, SplitHashOptions, SplitRandomOptions, SplitSequentialOptions } from "./native.js";
import { Table } from "./table";
/**
* A PermutationBuilder for creating data permutations with splits, shuffling, and filtering.
*
* This class provides a TypeScript wrapper around the native Rust PermutationBuilder,
* offering methods to configure data splits, shuffling, and filtering before executing
* the permutation to create a new table.
*/
export declare class PermutationBuilder {
private inner;
/**
* @hidden
*/
constructor(inner: NativePermutationBuilder);
/**
* Configure the permutation to be persisted.
*
* @param connection - The connection to persist the permutation to
* @param tableName - The name of the table to create
* @returns A new PermutationBuilder instance
* @example
* ```ts
* builder.persist(connection, "permutation_table");
* ```
*/
persist(connection: Connection, tableName: string): PermutationBuilder;
/**
* Configure random splits for the permutation.
*
* @param options - Configuration for random splitting
* @returns A new PermutationBuilder instance
* @example
* ```ts
* // Split by ratios
* builder.splitRandom({ ratios: [0.7, 0.3], seed: 42 });
*
* // Split by counts
* builder.splitRandom({ counts: [1000, 500], seed: 42 });
*
* // Split with fixed size
* builder.splitRandom({ fixed: 100, seed: 42 });
* ```
*/
splitRandom(options: SplitRandomOptions): PermutationBuilder;
/**
* Configure hash-based splits for the permutation.
*
* @param options - Configuration for hash-based splitting
* @returns A new PermutationBuilder instance
* @example
* ```ts
* builder.splitHash({
* columns: ["user_id"],
* splitWeights: [70, 30],
* discardWeight: 0
* });
* ```
*/
splitHash(options: SplitHashOptions): PermutationBuilder;
/**
* Configure sequential splits for the permutation.
*
* @param options - Configuration for sequential splitting
* @returns A new PermutationBuilder instance
* @example
* ```ts
* // Split by ratios
* builder.splitSequential({ ratios: [0.8, 0.2] });
*
* // Split by counts
* builder.splitSequential({ counts: [800, 200] });
*
* // Split with fixed size
* builder.splitSequential({ fixed: 1000 });
* ```
*/
splitSequential(options: SplitSequentialOptions): PermutationBuilder;
/**
* Configure calculated splits for the permutation.
*
* @param options - Configuration for calculated splitting
* @returns A new PermutationBuilder instance
* @example
* ```ts
* builder.splitCalculated({ calculation: "user_id % 3" });
* ```
*/
splitCalculated(options: SplitCalculatedOptions): PermutationBuilder;
/**
* Configure shuffling for the permutation.
*
* @param options - Configuration for shuffling
* @returns A new PermutationBuilder instance
* @example
* ```ts
* // Basic shuffle
* builder.shuffle({ seed: 42 });
*
* // Shuffle with clump size
* builder.shuffle({ seed: 42, clumpSize: 10 });
* ```
*/
shuffle(options: ShuffleOptions): PermutationBuilder;
/**
* Configure filtering for the permutation.
*
* @param filter - SQL filter expression
* @returns A new PermutationBuilder instance
* @example
* ```ts
* builder.filter("age > 18 AND status = 'active'");
* ```
*/
filter(filter: string): PermutationBuilder;
/**
* Execute the permutation and create the destination table.
*
* @returns A Promise that resolves to the new Table instance
* @example
* ```ts
* const permutationTable = await builder.execute();
* console.log(`Created table: ${permutationTable.name}`);
* ```
*/
execute(): Promise<Table>;
}
/**
* Create a permutation builder for the given table.
*
* @param table - The source table to create a permutation from
* @returns A PermutationBuilder instance
* @example
* ```ts
* const builder = permutationBuilder(sourceTable, "training_data")
* .splitRandom({ ratios: [0.8, 0.2], seed: 42 })
* .shuffle({ seed: 123 });
*
* const trainingTable = await builder.execute();
* ```
*/
export declare function permutationBuilder(table: Table): PermutationBuilder;

184
extensions/memory-lancedb/node_modules/@lancedb/lancedb/dist/permutation.js generated vendored Normal file
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"use strict";
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
Object.defineProperty(exports, "__esModule", { value: true });
exports.PermutationBuilder = void 0;
exports.permutationBuilder = permutationBuilder;
const native_js_1 = require("./native.js");
const table_1 = require("./table");
/**
* A PermutationBuilder for creating data permutations with splits, shuffling, and filtering.
*
* This class provides a TypeScript wrapper around the native Rust PermutationBuilder,
* offering methods to configure data splits, shuffling, and filtering before executing
* the permutation to create a new table.
*/
class PermutationBuilder {
inner;
/**
* @hidden
*/
constructor(inner) {
this.inner = inner;
}
/**
* Configure the permutation to be persisted.
*
* @param connection - The connection to persist the permutation to
* @param tableName - The name of the table to create
* @returns A new PermutationBuilder instance
* @example
* ```ts
* builder.persist(connection, "permutation_table");
* ```
*/
persist(connection, tableName) {
const localConnection = connection;
const newInner = this.inner.persist(localConnection.inner, tableName);
return new PermutationBuilder(newInner);
}
/**
* Configure random splits for the permutation.
*
* @param options - Configuration for random splitting
* @returns A new PermutationBuilder instance
* @example
* ```ts
* // Split by ratios
* builder.splitRandom({ ratios: [0.7, 0.3], seed: 42 });
*
* // Split by counts
* builder.splitRandom({ counts: [1000, 500], seed: 42 });
*
* // Split with fixed size
* builder.splitRandom({ fixed: 100, seed: 42 });
* ```
*/
splitRandom(options) {
const newInner = this.inner.splitRandom(options);
return new PermutationBuilder(newInner);
}
/**
* Configure hash-based splits for the permutation.
*
* @param options - Configuration for hash-based splitting
* @returns A new PermutationBuilder instance
* @example
* ```ts
* builder.splitHash({
* columns: ["user_id"],
* splitWeights: [70, 30],
* discardWeight: 0
* });
* ```
*/
splitHash(options) {
const newInner = this.inner.splitHash(options);
return new PermutationBuilder(newInner);
}
/**
* Configure sequential splits for the permutation.
*
* @param options - Configuration for sequential splitting
* @returns A new PermutationBuilder instance
* @example
* ```ts
* // Split by ratios
* builder.splitSequential({ ratios: [0.8, 0.2] });
*
* // Split by counts
* builder.splitSequential({ counts: [800, 200] });
*
* // Split with fixed size
* builder.splitSequential({ fixed: 1000 });
* ```
*/
splitSequential(options) {
const newInner = this.inner.splitSequential(options);
return new PermutationBuilder(newInner);
}
/**
* Configure calculated splits for the permutation.
*
* @param options - Configuration for calculated splitting
* @returns A new PermutationBuilder instance
* @example
* ```ts
* builder.splitCalculated({ calculation: "user_id % 3" });
* ```
*/
splitCalculated(options) {
const newInner = this.inner.splitCalculated(options);
return new PermutationBuilder(newInner);
}
/**
* Configure shuffling for the permutation.
*
* @param options - Configuration for shuffling
* @returns A new PermutationBuilder instance
* @example
* ```ts
* // Basic shuffle
* builder.shuffle({ seed: 42 });
*
* // Shuffle with clump size
* builder.shuffle({ seed: 42, clumpSize: 10 });
* ```
*/
shuffle(options) {
const newInner = this.inner.shuffle(options);
return new PermutationBuilder(newInner);
}
/**
* Configure filtering for the permutation.
*
* @param filter - SQL filter expression
* @returns A new PermutationBuilder instance
* @example
* ```ts
* builder.filter("age > 18 AND status = 'active'");
* ```
*/
filter(filter) {
const newInner = this.inner.filter(filter);
return new PermutationBuilder(newInner);
}
/**
* Execute the permutation and create the destination table.
*
* @returns A Promise that resolves to the new Table instance
* @example
* ```ts
* const permutationTable = await builder.execute();
* console.log(`Created table: ${permutationTable.name}`);
* ```
*/
async execute() {
const nativeTable = await this.inner.execute();
return new table_1.LocalTable(nativeTable);
}
}
exports.PermutationBuilder = PermutationBuilder;
/**
* Create a permutation builder for the given table.
*
* @param table - The source table to create a permutation from
* @returns A PermutationBuilder instance
* @example
* ```ts
* const builder = permutationBuilder(sourceTable, "training_data")
* .splitRandom({ ratios: [0.8, 0.2], seed: 42 })
* .shuffle({ seed: 123 });
*
* const trainingTable = await builder.execute();
* ```
*/
function permutationBuilder(table) {
// Extract the inner native table from the TypeScript wrapper
const localTable = table;
// Access inner through type assertion since it's private
const nativeBuilder = (0, native_js_1.permutationBuilder)(
// biome-ignore lint/suspicious/noExplicitAny: need access to private variable
localTable.inner);
return new PermutationBuilder(nativeBuilder);
}

581
extensions/memory-lancedb/node_modules/@lancedb/lancedb/dist/query.d.ts generated vendored Normal file
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import { Table as ArrowTable, type IntoVector, RecordBatch } from "./arrow";
import { type IvfPqOptions } from "./indices";
import { JsFullTextQuery, RecordBatchIterator as NativeBatchIterator, Query as NativeQuery, Table as NativeTable, TakeQuery as NativeTakeQuery, VectorQuery as NativeVectorQuery } from "./native";
import { Reranker } from "./rerankers";
export declare function RecordBatchIterator(promisedInner: Promise<NativeBatchIterator>): AsyncGenerator<RecordBatch<any>, void, unknown>;
/**
* Options that control the behavior of a particular query execution
*/
export interface QueryExecutionOptions {
/**
* The maximum number of rows to return in a single batch
*
* Batches may have fewer rows if the underlying data is stored
* in smaller chunks.
*/
maxBatchLength?: number;
/**
* Timeout for query execution in milliseconds
*/
timeoutMs?: number;
}
/**
* Options that control the behavior of a full text search
*/
export interface FullTextSearchOptions {
/**
* The columns to search
*
* If not specified, all indexed columns will be searched.
* For now, only one column can be searched.
*/
columns?: string | string[];
}
/** Common methods supported by all query types
*
* @see {@link Query}
* @see {@link VectorQuery}
*
* @hideconstructor
*/
export declare class QueryBase<NativeQueryType extends NativeQuery | NativeVectorQuery | NativeTakeQuery> implements AsyncIterable<RecordBatch> {
protected inner: NativeQueryType | Promise<NativeQueryType>;
/**
* @hidden
*/
protected constructor(inner: NativeQueryType | Promise<NativeQueryType>);
/**
* @hidden
*/
protected doCall(fn: (inner: NativeQueryType) => void): void;
/**
* Return only the specified columns.
*
* By default a query will return all columns from the table. However, this can have
* a very significant impact on latency. LanceDb stores data in a columnar fashion. This
* means we can finely tune our I/O to select exactly the columns we need.
*
* As a best practice you should always limit queries to the columns that you need. If you
* pass in an array of column names then only those columns will be returned.
*
* You can also use this method to create new "dynamic" columns based on your existing columns.
* For example, you may not care about "a" or "b" but instead simply want "a + b". This is often
* seen in the SELECT clause of an SQL query (e.g. `SELECT a+b FROM my_table`).
*
* To create dynamic columns you can pass in a Map<string, string>. A column will be returned
* for each entry in the map. The key provides the name of the column. The value is
* an SQL string used to specify how the column is calculated.
*
* For example, an SQL query might state `SELECT a + b AS combined, c`. The equivalent
* input to this method would be:
* @example
* new Map([["combined", "a + b"], ["c", "c"]])
*
* Columns will always be returned in the order given, even if that order is different than
* the order used when adding the data.
*
* Note that you can pass in a `Record<string, string>` (e.g. an object literal). This method
* uses `Object.entries` which should preserve the insertion order of the object. However,
* object insertion order is easy to get wrong and `Map` is more foolproof.
*/
select(columns: string[] | Map<string, string> | Record<string, string> | string): this;
/**
* Whether to return the row id in the results.
*
* This column can be used to match results between different queries. For
* example, to match results from a full text search and a vector search in
* order to perform hybrid search.
*/
withRowId(): this;
/**
* @hidden
*/
protected nativeExecute(options?: Partial<QueryExecutionOptions>): Promise<NativeBatchIterator>;
/**
* Execute the query and return the results as an @see {@link AsyncIterator}
* of @see {@link RecordBatch}.
*
* By default, LanceDb will use many threads to calculate results and, when
* the result set is large, multiple batches will be processed at one time.
* This readahead is limited however and backpressure will be applied if this
* stream is consumed slowly (this constrains the maximum memory used by a
* single query)
*
*/
protected execute(options?: Partial<QueryExecutionOptions>): AsyncGenerator<RecordBatch<any>, void, unknown>;
/**
* @hidden
*/
[Symbol.asyncIterator](): AsyncIterator<RecordBatch<any>>;
/** Collect the results as an Arrow @see {@link ArrowTable}. */
toArrow(options?: Partial<QueryExecutionOptions>): Promise<ArrowTable>;
/** Collect the results as an array of objects. */
toArray(options?: Partial<QueryExecutionOptions>): Promise<any[]>;
/**
* Generates an explanation of the query execution plan.
*
* @example
* import * as lancedb from "@lancedb/lancedb"
* const db = await lancedb.connect("./.lancedb");
* const table = await db.createTable("my_table", [
* { vector: [1.1, 0.9], id: "1" },
* ]);
* const plan = await table.query().nearestTo([0.5, 0.2]).explainPlan();
*
* @param verbose - If true, provides a more detailed explanation. Defaults to false.
* @returns A Promise that resolves to a string containing the query execution plan explanation.
*/
explainPlan(verbose?: boolean): Promise<string>;
/**
* Executes the query and returns the physical query plan annotated with runtime metrics.
*
* This is useful for debugging and performance analysis, as it shows how the query was executed
* and includes metrics such as elapsed time, rows processed, and I/O statistics.
*
* @example
* import * as lancedb from "@lancedb/lancedb"
*
* const db = await lancedb.connect("./.lancedb");
* const table = await db.createTable("my_table", [
* { vector: [1.1, 0.9], id: "1" },
* ]);
*
* const plan = await table.query().nearestTo([0.5, 0.2]).analyzePlan();
*
* Example output (with runtime metrics inlined):
* AnalyzeExec verbose=true, metrics=[]
* ProjectionExec: expr=[id@3 as id, vector@0 as vector, _distance@2 as _distance], metrics=[output_rows=1, elapsed_compute=3.292µs]
* Take: columns="vector, _rowid, _distance, (id)", metrics=[output_rows=1, elapsed_compute=66.001µs, batches_processed=1, bytes_read=8, iops=1, requests=1]
* CoalesceBatchesExec: target_batch_size=1024, metrics=[output_rows=1, elapsed_compute=3.333µs]
* GlobalLimitExec: skip=0, fetch=10, metrics=[output_rows=1, elapsed_compute=167ns]
* FilterExec: _distance@2 IS NOT NULL, metrics=[output_rows=1, elapsed_compute=8.542µs]
* SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST], metrics=[output_rows=1, elapsed_compute=63.25µs, row_replacements=1]
* KNNVectorDistance: metric=l2, metrics=[output_rows=1, elapsed_compute=114.333µs, output_batches=1]
* LanceScan: uri=/path/to/data, projection=[vector], row_id=true, row_addr=false, ordered=false, metrics=[output_rows=1, elapsed_compute=103.626µs, bytes_read=549, iops=2, requests=2]
*
* @returns A query execution plan with runtime metrics for each step.
*/
analyzePlan(): Promise<string>;
/**
* Returns the schema of the output that will be returned by this query.
*
* This can be used to inspect the types and names of the columns that will be
* returned by the query before executing it.
*
* @returns An Arrow Schema describing the output columns.
*/
outputSchema(): Promise<import("./arrow").Schema>;
}
export declare class StandardQueryBase<NativeQueryType extends NativeQuery | NativeVectorQuery> extends QueryBase<NativeQueryType> implements ExecutableQuery {
constructor(inner: NativeQueryType | Promise<NativeQueryType>);
/**
* A filter statement to be applied to this query.
*
* The filter should be supplied as an SQL query string. For example:
* @example
* x > 10
* y > 0 AND y < 100
* x > 5 OR y = 'test'
*
* Filtering performance can often be improved by creating a scalar index
* on the filter column(s).
*/
where(predicate: string): this;
/**
* A filter statement to be applied to this query.
* @see where
* @deprecated Use `where` instead
*/
filter(predicate: string): this;
fullTextSearch(query: string | FullTextQuery, options?: Partial<FullTextSearchOptions>): this;
/**
* Set the maximum number of results to return.
*
* By default, a plain search has no limit. If this method is not
* called then every valid row from the table will be returned.
*/
limit(limit: number): this;
/**
* Set the number of rows to skip before returning results.
*
* This is useful for pagination.
*/
offset(offset: number): this;
/**
* Skip searching un-indexed data. This can make search faster, but will miss
* any data that is not yet indexed.
*
* Use {@link Table#optimize} to index all un-indexed data.
*/
fastSearch(): this;
}
/**
* An interface for a query that can be executed
*
* Supported by all query types
*/
export interface ExecutableQuery {
}
/**
* A builder used to construct a vector search
*
* This builder can be reused to execute the query many times.
*
* @see {@link Query#nearestTo}
*
* @hideconstructor
*/
export declare class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
/**
* @hidden
*/
constructor(inner: NativeVectorQuery | Promise<NativeVectorQuery>);
/**
* Set the number of partitions to search (probe)
*
* This argument is only used when the vector column has an IVF PQ index.
* If there is no index then this value is ignored.
*
* The IVF stage of IVF PQ divides the input into partitions (clusters) of
* related values.
*
* The partition whose centroids are closest to the query vector will be
* exhaustiely searched to find matches. This parameter controls how many
* partitions should be searched.
*
* Increasing this value will increase the recall of your query but will
* also increase the latency of your query. The default value is 20. This
* default is good for many cases but the best value to use will depend on
* your data and the recall that you need to achieve.
*
* For best results we recommend tuning this parameter with a benchmark against
* your actual data to find the smallest possible value that will still give
* you the desired recall.
*
* For more fine grained control over behavior when you have a very narrow filter
* you can use `minimumNprobes` and `maximumNprobes`. This method sets both
* the minimum and maximum to the same value.
*/
nprobes(nprobes: number): VectorQuery;
/**
* Set the minimum number of probes used.
*
* This controls the minimum number of partitions that will be searched. This
* parameter will impact every query against a vector index, regardless of the
* filter. See `nprobes` for more details. Higher values will increase recall
* but will also increase latency.
*/
minimumNprobes(minimumNprobes: number): VectorQuery;
/**
* Set the maximum number of probes used.
*
* This controls the maximum number of partitions that will be searched. If this
* number is greater than minimumNprobes then the excess partitions will _only_ be
* searched if we have not found enough results. This can be useful when there is
* a narrow filter to allow these queries to spend more time searching and avoid
* potential false negatives.
*/
maximumNprobes(maximumNprobes: number): VectorQuery;
distanceRange(lowerBound?: number, upperBound?: number): VectorQuery;
/**
* Set the number of candidates to consider during the search
*
* This argument is only used when the vector column has an HNSW index.
* If there is no index then this value is ignored.
*
* Increasing this value will increase the recall of your query but will
* also increase the latency of your query. The default value is 1.5*limit.
*/
ef(ef: number): VectorQuery;
/**
* Set the vector column to query
*
* This controls which column is compared to the query vector supplied in
* the call to @see {@link Query#nearestTo}
*
* This parameter must be specified if the table has more than one column
* whose data type is a fixed-size-list of floats.
*/
column(column: string): VectorQuery;
/**
* Set the distance metric to use
*
* When performing a vector search we try and find the "nearest" vectors according
* to some kind of distance metric. This parameter controls which distance metric to
* use. See @see {@link IvfPqOptions.distanceType} for more details on the different
* distance metrics available.
*
* Note: if there is a vector index then the distance type used MUST match the distance
* type used to train the vector index. If this is not done then the results will be
* invalid.
*
* By default "l2" is used.
*/
distanceType(distanceType: Required<IvfPqOptions>["distanceType"]): VectorQuery;
/**
* A multiplier to control how many additional rows are taken during the refine step
*
* This argument is only used when the vector column has an IVF PQ index.
* If there is no index then this value is ignored.
*
* An IVF PQ index stores compressed (quantized) values. They query vector is compared
* against these values and, since they are compressed, the comparison is inaccurate.
*
* This parameter can be used to refine the results. It can improve both improve recall
* and correct the ordering of the nearest results.
*
* To refine results LanceDb will first perform an ANN search to find the nearest
* `limit` * `refine_factor` results. In other words, if `refine_factor` is 3 and
* `limit` is the default (10) then the first 30 results will be selected. LanceDb
* then fetches the full, uncompressed, values for these 30 results. The results are
* then reordered by the true distance and only the nearest 10 are kept.
*
* Note: there is a difference between calling this method with a value of 1 and never
* calling this method at all. Calling this method with any value will have an impact
* on your search latency. When you call this method with a `refine_factor` of 1 then
* LanceDb still needs to fetch the full, uncompressed, values so that it can potentially
* reorder the results.
*
* Note: if this method is NOT called then the distances returned in the _distance column
* will be approximate distances based on the comparison of the quantized query vector
* and the quantized result vectors. This can be considerably different than the true
* distance between the query vector and the actual uncompressed vector.
*/
refineFactor(refineFactor: number): VectorQuery;
/**
* If this is called then filtering will happen after the vector search instead of
* before.
*
* By default filtering will be performed before the vector search. This is how
* filtering is typically understood to work. This prefilter step does add some
* additional latency. Creating a scalar index on the filter column(s) can
* often improve this latency. However, sometimes a filter is too complex or scalar
* indices cannot be applied to the column. In these cases postfiltering can be
* used instead of prefiltering to improve latency.
*
* Post filtering applies the filter to the results of the vector search. This means
* we only run the filter on a much smaller set of data. However, it can cause the
* query to return fewer than `limit` results (or even no results) if none of the nearest
* results match the filter.
*
* Post filtering happens during the "refine stage" (described in more detail in
* @see {@link VectorQuery#refineFactor}). This means that setting a higher refine
* factor can often help restore some of the results lost by post filtering.
*/
postfilter(): VectorQuery;
/**
* If this is called then any vector index is skipped
*
* An exhaustive (flat) search will be performed. The query vector will
* be compared to every vector in the table. At high scales this can be
* expensive. However, this is often still useful. For example, skipping
* the vector index can give you ground truth results which you can use to
* calculate your recall to select an appropriate value for nprobes.
*/
bypassVectorIndex(): VectorQuery;
addQueryVector(vector: IntoVector): VectorQuery;
rerank(reranker: Reranker): VectorQuery;
}
/**
* A query that returns a subset of the rows in the table.
*
* @hideconstructor
*/
export declare class TakeQuery extends QueryBase<NativeTakeQuery> {
constructor(inner: NativeTakeQuery);
}
/** A builder for LanceDB queries.
*
* @see {@link Table#query}, {@link Table#search}
*
* @hideconstructor
*/
export declare class Query extends StandardQueryBase<NativeQuery> {
/**
* @hidden
*/
constructor(tbl: NativeTable);
/**
* Find the nearest vectors to the given query vector.
*
* This converts the query from a plain query to a vector query.
*
* This method will attempt to convert the input to the query vector
* expected by the embedding model. If the input cannot be converted
* then an error will be thrown.
*
* By default, there is no embedding model, and the input should be
* an array-like object of numbers (something that can be used as input
* to Float32Array.from)
*
* If there is only one vector column (a column whose data type is a
* fixed size list of floats) then the column does not need to be specified.
* If there is more than one vector column you must use
* @see {@link VectorQuery#column} to specify which column you would like
* to compare with.
*
* If no index has been created on the vector column then a vector query
* will perform a distance comparison between the query vector and every
* vector in the database and then sort the results. This is sometimes
* called a "flat search"
*
* For small databases, with a few hundred thousand vectors or less, this can
* be reasonably fast. In larger databases you should create a vector index
* on the column. If there is a vector index then an "approximate" nearest
* neighbor search (frequently called an ANN search) will be performed. This
* search is much faster, but the results will be approximate.
*
* The query can be further parameterized using the returned builder. There
* are various ANN search parameters that will let you fine tune your recall
* accuracy vs search latency.
*
* Vector searches always have a `limit`. If `limit` has not been called then
* a default `limit` of 10 will be used. @see {@link Query#limit}
*/
nearestTo(vector: IntoVector): VectorQuery;
nearestToText(query: string | FullTextQuery, columns?: string[]): Query;
}
/**
* Enum representing the types of full-text queries supported.
*
* - `Match`: Performs a full-text search for terms in the query string.
* - `MatchPhrase`: Searches for an exact phrase match in the text.
* - `Boost`: Boosts the relevance score of specific terms in the query.
* - `MultiMatch`: Searches across multiple fields for the query terms.
*/
export declare enum FullTextQueryType {
Match = "match",
MatchPhrase = "match_phrase",
Boost = "boost",
MultiMatch = "multi_match",
Boolean = "boolean"
}
/**
* Enum representing the logical operators used in full-text queries.
*
* - `And`: All terms must match.
* - `Or`: At least one term must match.
*/
export declare enum Operator {
And = "AND",
Or = "OR"
}
/**
* Enum representing the occurrence of terms in full-text queries.
*
* - `Must`: The term must be present in the document.
* - `Should`: The term should contribute to the document score, but is not required.
* - `MustNot`: The term must not be present in the document.
*/
export declare enum Occur {
Should = "SHOULD",
Must = "MUST",
MustNot = "MUST_NOT"
}
/**
* Represents a full-text query interface.
* This interface defines the structure and behavior for full-text queries,
* including methods to retrieve the query type and convert the query to a dictionary format.
*/
export interface FullTextQuery {
/**
* Returns the inner query object.
* This is the underlying query object used by the database engine.
* @ignore
*/
inner: JsFullTextQuery;
/**
* The type of the full-text query.
*/
queryType(): FullTextQueryType;
}
export declare function instanceOfFullTextQuery(obj: any): obj is FullTextQuery;
export declare class MatchQuery implements FullTextQuery {
/** @ignore */
readonly inner: JsFullTextQuery;
/**
* Creates an instance of MatchQuery.
*
* @param query - The text query to search for.
* @param column - The name of the column to search within.
* @param options - Optional parameters for the match query.
* - `boost`: The boost factor for the query (default is 1.0).
* - `fuzziness`: The fuzziness level for the query (default is 0).
* - `maxExpansions`: The maximum number of terms to consider for fuzzy matching (default is 50).
* - `operator`: The logical operator to use for combining terms in the query (default is "OR").
* - `prefixLength`: The number of beginning characters being unchanged for fuzzy matching.
*/
constructor(query: string, column: string, options?: {
boost?: number;
fuzziness?: number;
maxExpansions?: number;
operator?: Operator;
prefixLength?: number;
});
queryType(): FullTextQueryType;
}
export declare class PhraseQuery implements FullTextQuery {
/** @ignore */
readonly inner: JsFullTextQuery;
/**
* Creates an instance of `PhraseQuery`.
*
* @param query - The phrase to search for in the specified column.
* @param column - The name of the column to search within.
* @param options - Optional parameters for the phrase query.
* - `slop`: The maximum number of intervening unmatched positions allowed between words in the phrase (default is 0).
*/
constructor(query: string, column: string, options?: {
slop?: number;
});
queryType(): FullTextQueryType;
}
export declare class BoostQuery implements FullTextQuery {
/** @ignore */
readonly inner: JsFullTextQuery;
/**
* Creates an instance of BoostQuery.
* The boost returns documents that match the positive query,
* but penalizes those that match the negative query.
* the penalty is controlled by the `negativeBoost` parameter.
*
* @param positive - The positive query that boosts the relevance score.
* @param negative - The negative query that reduces the relevance score.
* @param options - Optional parameters for the boost query.
* - `negativeBoost`: The boost factor for the negative query (default is 0.0).
*/
constructor(positive: FullTextQuery, negative: FullTextQuery, options?: {
negativeBoost?: number;
});
queryType(): FullTextQueryType;
}
export declare class MultiMatchQuery implements FullTextQuery {
/** @ignore */
readonly inner: JsFullTextQuery;
/**
* Creates an instance of MultiMatchQuery.
*
* @param query - The text query to search for across multiple columns.
* @param columns - An array of column names to search within.
* @param options - Optional parameters for the multi-match query.
* - `boosts`: An array of boost factors for each column (default is 1.0 for all).
* - `operator`: The logical operator to use for combining terms in the query (default is "OR").
*/
constructor(query: string, columns: string[], options?: {
boosts?: number[];
operator?: Operator;
});
queryType(): FullTextQueryType;
}
export declare class BooleanQuery implements FullTextQuery {
/** @ignore */
readonly inner: JsFullTextQuery;
/**
* Creates an instance of BooleanQuery.
*
* @param queries - An array of (Occur, FullTextQuery objects) to combine.
* Occur specifies whether the query must match, or should match.
*/
constructor(queries: [Occur, FullTextQuery][]);
queryType(): FullTextQueryType;
}

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"use strict";
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
Object.defineProperty(exports, "__esModule", { value: true });
exports.BooleanQuery = exports.MultiMatchQuery = exports.BoostQuery = exports.PhraseQuery = exports.MatchQuery = exports.Occur = exports.Operator = exports.FullTextQueryType = exports.Query = exports.TakeQuery = exports.VectorQuery = exports.StandardQueryBase = exports.QueryBase = void 0;
exports.RecordBatchIterator = RecordBatchIterator;
exports.instanceOfFullTextQuery = instanceOfFullTextQuery;
const arrow_1 = require("./arrow");
const native_1 = require("./native");
async function* RecordBatchIterator(promisedInner) {
const inner = await promisedInner;
if (inner === undefined) {
throw new Error("Invalid iterator state");
}
for (let buffer = await inner.next(); buffer; buffer = await inner.next()) {
const { batches } = (0, arrow_1.tableFromIPC)(buffer);
if (batches.length !== 1) {
throw new Error("Expected only one batch");
}
yield batches[0];
}
}
class RecordBatchIterable {
inner;
options;
constructor(inner, options) {
this.inner = inner;
this.options = options;
}
// biome-ignore lint/suspicious/noExplicitAny: skip
[Symbol.asyncIterator]() {
return RecordBatchIterator(this.inner.execute(this.options?.maxBatchLength, this.options?.timeoutMs));
}
}
/** Common methods supported by all query types
*
* @see {@link Query}
* @see {@link VectorQuery}
*
* @hideconstructor
*/
class QueryBase {
inner;
/**
* @hidden
*/
constructor(inner) {
this.inner = inner;
// intentionally empty
}
// call a function on the inner (either a promise or the actual object)
/**
* @hidden
*/
doCall(fn) {
if (this.inner instanceof Promise) {
this.inner = this.inner.then((inner) => {
fn(inner);
return inner;
});
}
else {
fn(this.inner);
}
}
/**
* Return only the specified columns.
*
* By default a query will return all columns from the table. However, this can have
* a very significant impact on latency. LanceDb stores data in a columnar fashion. This
* means we can finely tune our I/O to select exactly the columns we need.
*
* As a best practice you should always limit queries to the columns that you need. If you
* pass in an array of column names then only those columns will be returned.
*
* You can also use this method to create new "dynamic" columns based on your existing columns.
* For example, you may not care about "a" or "b" but instead simply want "a + b". This is often
* seen in the SELECT clause of an SQL query (e.g. `SELECT a+b FROM my_table`).
*
* To create dynamic columns you can pass in a Map<string, string>. A column will be returned
* for each entry in the map. The key provides the name of the column. The value is
* an SQL string used to specify how the column is calculated.
*
* For example, an SQL query might state `SELECT a + b AS combined, c`. The equivalent
* input to this method would be:
* @example
* new Map([["combined", "a + b"], ["c", "c"]])
*
* Columns will always be returned in the order given, even if that order is different than
* the order used when adding the data.
*
* Note that you can pass in a `Record<string, string>` (e.g. an object literal). This method
* uses `Object.entries` which should preserve the insertion order of the object. However,
* object insertion order is easy to get wrong and `Map` is more foolproof.
*/
select(columns) {
const selectColumns = (columnArray) => {
this.doCall((inner) => {
inner.selectColumns(columnArray);
});
};
const selectMapping = (columnTuples) => {
this.doCall((inner) => {
inner.select(columnTuples);
});
};
if (typeof columns === "string") {
selectColumns([columns]);
}
else if (Array.isArray(columns)) {
selectColumns(columns);
}
else if (columns instanceof Map) {
selectMapping(Array.from(columns.entries()));
}
else {
selectMapping(Object.entries(columns));
}
return this;
}
/**
* Whether to return the row id in the results.
*
* This column can be used to match results between different queries. For
* example, to match results from a full text search and a vector search in
* order to perform hybrid search.
*/
withRowId() {
this.doCall((inner) => inner.withRowId());
return this;
}
/**
* @hidden
*/
nativeExecute(options) {
if (this.inner instanceof Promise) {
return this.inner.then((inner) => inner.execute(options?.maxBatchLength, options?.timeoutMs));
}
else {
return this.inner.execute(options?.maxBatchLength, options?.timeoutMs);
}
}
/**
* Execute the query and return the results as an @see {@link AsyncIterator}
* of @see {@link RecordBatch}.
*
* By default, LanceDb will use many threads to calculate results and, when
* the result set is large, multiple batches will be processed at one time.
* This readahead is limited however and backpressure will be applied if this
* stream is consumed slowly (this constrains the maximum memory used by a
* single query)
*
*/
execute(options) {
return RecordBatchIterator(this.nativeExecute(options));
}
/**
* @hidden
*/
// biome-ignore lint/suspicious/noExplicitAny: skip
[Symbol.asyncIterator]() {
return RecordBatchIterator(this.nativeExecute());
}
/** Collect the results as an Arrow @see {@link ArrowTable}. */
async toArrow(options) {
const batches = [];
let inner;
if (this.inner instanceof Promise) {
inner = await this.inner;
}
else {
inner = this.inner;
}
for await (const batch of new RecordBatchIterable(inner, options)) {
batches.push(batch);
}
return new arrow_1.Table(batches);
}
/** Collect the results as an array of objects. */
// biome-ignore lint/suspicious/noExplicitAny: arrow.toArrow() returns any[]
async toArray(options) {
const tbl = await this.toArrow(options);
return tbl.toArray();
}
/**
* Generates an explanation of the query execution plan.
*
* @example
* import * as lancedb from "@lancedb/lancedb"
* const db = await lancedb.connect("./.lancedb");
* const table = await db.createTable("my_table", [
* { vector: [1.1, 0.9], id: "1" },
* ]);
* const plan = await table.query().nearestTo([0.5, 0.2]).explainPlan();
*
* @param verbose - If true, provides a more detailed explanation. Defaults to false.
* @returns A Promise that resolves to a string containing the query execution plan explanation.
*/
async explainPlan(verbose = false) {
if (this.inner instanceof Promise) {
return this.inner.then((inner) => inner.explainPlan(verbose));
}
else {
return this.inner.explainPlan(verbose);
}
}
/**
* Executes the query and returns the physical query plan annotated with runtime metrics.
*
* This is useful for debugging and performance analysis, as it shows how the query was executed
* and includes metrics such as elapsed time, rows processed, and I/O statistics.
*
* @example
* import * as lancedb from "@lancedb/lancedb"
*
* const db = await lancedb.connect("./.lancedb");
* const table = await db.createTable("my_table", [
* { vector: [1.1, 0.9], id: "1" },
* ]);
*
* const plan = await table.query().nearestTo([0.5, 0.2]).analyzePlan();
*
* Example output (with runtime metrics inlined):
* AnalyzeExec verbose=true, metrics=[]
* ProjectionExec: expr=[id@3 as id, vector@0 as vector, _distance@2 as _distance], metrics=[output_rows=1, elapsed_compute=3.292µs]
* Take: columns="vector, _rowid, _distance, (id)", metrics=[output_rows=1, elapsed_compute=66.001µs, batches_processed=1, bytes_read=8, iops=1, requests=1]
* CoalesceBatchesExec: target_batch_size=1024, metrics=[output_rows=1, elapsed_compute=3.333µs]
* GlobalLimitExec: skip=0, fetch=10, metrics=[output_rows=1, elapsed_compute=167ns]
* FilterExec: _distance@2 IS NOT NULL, metrics=[output_rows=1, elapsed_compute=8.542µs]
* SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST], metrics=[output_rows=1, elapsed_compute=63.25µs, row_replacements=1]
* KNNVectorDistance: metric=l2, metrics=[output_rows=1, elapsed_compute=114.333µs, output_batches=1]
* LanceScan: uri=/path/to/data, projection=[vector], row_id=true, row_addr=false, ordered=false, metrics=[output_rows=1, elapsed_compute=103.626µs, bytes_read=549, iops=2, requests=2]
*
* @returns A query execution plan with runtime metrics for each step.
*/
async analyzePlan() {
if (this.inner instanceof Promise) {
return this.inner.then((inner) => inner.analyzePlan());
}
else {
return this.inner.analyzePlan();
}
}
/**
* Returns the schema of the output that will be returned by this query.
*
* This can be used to inspect the types and names of the columns that will be
* returned by the query before executing it.
*
* @returns An Arrow Schema describing the output columns.
*/
async outputSchema() {
let schemaBuffer;
if (this.inner instanceof Promise) {
schemaBuffer = await this.inner.then((inner) => inner.outputSchema());
}
else {
schemaBuffer = await this.inner.outputSchema();
}
const schema = (0, arrow_1.tableFromIPC)(schemaBuffer).schema;
return schema;
}
}
exports.QueryBase = QueryBase;
class StandardQueryBase extends QueryBase {
constructor(inner) {
super(inner);
}
/**
* A filter statement to be applied to this query.
*
* The filter should be supplied as an SQL query string. For example:
* @example
* x > 10
* y > 0 AND y < 100
* x > 5 OR y = 'test'
*
* Filtering performance can often be improved by creating a scalar index
* on the filter column(s).
*/
where(predicate) {
this.doCall((inner) => inner.onlyIf(predicate));
return this;
}
/**
* A filter statement to be applied to this query.
* @see where
* @deprecated Use `where` instead
*/
filter(predicate) {
return this.where(predicate);
}
fullTextSearch(query, options) {
let columns = null;
if (options) {
if (typeof options.columns === "string") {
columns = [options.columns];
}
else if (Array.isArray(options.columns)) {
columns = options.columns;
}
}
this.doCall((inner) => {
if (typeof query === "string") {
inner.fullTextSearch({
query: query,
columns: columns,
});
}
else {
inner.fullTextSearch({ query: query.inner });
}
});
return this;
}
/**
* Set the maximum number of results to return.
*
* By default, a plain search has no limit. If this method is not
* called then every valid row from the table will be returned.
*/
limit(limit) {
this.doCall((inner) => inner.limit(limit));
return this;
}
/**
* Set the number of rows to skip before returning results.
*
* This is useful for pagination.
*/
offset(offset) {
this.doCall((inner) => inner.offset(offset));
return this;
}
/**
* Skip searching un-indexed data. This can make search faster, but will miss
* any data that is not yet indexed.
*
* Use {@link Table#optimize} to index all un-indexed data.
*/
fastSearch() {
this.doCall((inner) => inner.fastSearch());
return this;
}
}
exports.StandardQueryBase = StandardQueryBase;
/**
* A builder used to construct a vector search
*
* This builder can be reused to execute the query many times.
*
* @see {@link Query#nearestTo}
*
* @hideconstructor
*/
class VectorQuery extends StandardQueryBase {
/**
* @hidden
*/
constructor(inner) {
super(inner);
}
/**
* Set the number of partitions to search (probe)
*
* This argument is only used when the vector column has an IVF PQ index.
* If there is no index then this value is ignored.
*
* The IVF stage of IVF PQ divides the input into partitions (clusters) of
* related values.
*
* The partition whose centroids are closest to the query vector will be
* exhaustiely searched to find matches. This parameter controls how many
* partitions should be searched.
*
* Increasing this value will increase the recall of your query but will
* also increase the latency of your query. The default value is 20. This
* default is good for many cases but the best value to use will depend on
* your data and the recall that you need to achieve.
*
* For best results we recommend tuning this parameter with a benchmark against
* your actual data to find the smallest possible value that will still give
* you the desired recall.
*
* For more fine grained control over behavior when you have a very narrow filter
* you can use `minimumNprobes` and `maximumNprobes`. This method sets both
* the minimum and maximum to the same value.
*/
nprobes(nprobes) {
super.doCall((inner) => inner.nprobes(nprobes));
return this;
}
/**
* Set the minimum number of probes used.
*
* This controls the minimum number of partitions that will be searched. This
* parameter will impact every query against a vector index, regardless of the
* filter. See `nprobes` for more details. Higher values will increase recall
* but will also increase latency.
*/
minimumNprobes(minimumNprobes) {
super.doCall((inner) => inner.minimumNprobes(minimumNprobes));
return this;
}
/**
* Set the maximum number of probes used.
*
* This controls the maximum number of partitions that will be searched. If this
* number is greater than minimumNprobes then the excess partitions will _only_ be
* searched if we have not found enough results. This can be useful when there is
* a narrow filter to allow these queries to spend more time searching and avoid
* potential false negatives.
*/
maximumNprobes(maximumNprobes) {
super.doCall((inner) => inner.maximumNprobes(maximumNprobes));
return this;
}
/*
* Set the distance range to use
*
* Only rows with distances within range [lower_bound, upper_bound)
* will be returned.
*
* `undefined` means no lower or upper bound.
*/
distanceRange(lowerBound, upperBound) {
super.doCall((inner) => inner.distanceRange(lowerBound, upperBound));
return this;
}
/**
* Set the number of candidates to consider during the search
*
* This argument is only used when the vector column has an HNSW index.
* If there is no index then this value is ignored.
*
* Increasing this value will increase the recall of your query but will
* also increase the latency of your query. The default value is 1.5*limit.
*/
ef(ef) {
super.doCall((inner) => inner.ef(ef));
return this;
}
/**
* Set the vector column to query
*
* This controls which column is compared to the query vector supplied in
* the call to @see {@link Query#nearestTo}
*
* This parameter must be specified if the table has more than one column
* whose data type is a fixed-size-list of floats.
*/
column(column) {
super.doCall((inner) => inner.column(column));
return this;
}
/**
* Set the distance metric to use
*
* When performing a vector search we try and find the "nearest" vectors according
* to some kind of distance metric. This parameter controls which distance metric to
* use. See @see {@link IvfPqOptions.distanceType} for more details on the different
* distance metrics available.
*
* Note: if there is a vector index then the distance type used MUST match the distance
* type used to train the vector index. If this is not done then the results will be
* invalid.
*
* By default "l2" is used.
*/
distanceType(distanceType) {
super.doCall((inner) => inner.distanceType(distanceType));
return this;
}
/**
* A multiplier to control how many additional rows are taken during the refine step
*
* This argument is only used when the vector column has an IVF PQ index.
* If there is no index then this value is ignored.
*
* An IVF PQ index stores compressed (quantized) values. They query vector is compared
* against these values and, since they are compressed, the comparison is inaccurate.
*
* This parameter can be used to refine the results. It can improve both improve recall
* and correct the ordering of the nearest results.
*
* To refine results LanceDb will first perform an ANN search to find the nearest
* `limit` * `refine_factor` results. In other words, if `refine_factor` is 3 and
* `limit` is the default (10) then the first 30 results will be selected. LanceDb
* then fetches the full, uncompressed, values for these 30 results. The results are
* then reordered by the true distance and only the nearest 10 are kept.
*
* Note: there is a difference between calling this method with a value of 1 and never
* calling this method at all. Calling this method with any value will have an impact
* on your search latency. When you call this method with a `refine_factor` of 1 then
* LanceDb still needs to fetch the full, uncompressed, values so that it can potentially
* reorder the results.
*
* Note: if this method is NOT called then the distances returned in the _distance column
* will be approximate distances based on the comparison of the quantized query vector
* and the quantized result vectors. This can be considerably different than the true
* distance between the query vector and the actual uncompressed vector.
*/
refineFactor(refineFactor) {
super.doCall((inner) => inner.refineFactor(refineFactor));
return this;
}
/**
* If this is called then filtering will happen after the vector search instead of
* before.
*
* By default filtering will be performed before the vector search. This is how
* filtering is typically understood to work. This prefilter step does add some
* additional latency. Creating a scalar index on the filter column(s) can
* often improve this latency. However, sometimes a filter is too complex or scalar
* indices cannot be applied to the column. In these cases postfiltering can be
* used instead of prefiltering to improve latency.
*
* Post filtering applies the filter to the results of the vector search. This means
* we only run the filter on a much smaller set of data. However, it can cause the
* query to return fewer than `limit` results (or even no results) if none of the nearest
* results match the filter.
*
* Post filtering happens during the "refine stage" (described in more detail in
* @see {@link VectorQuery#refineFactor}). This means that setting a higher refine
* factor can often help restore some of the results lost by post filtering.
*/
postfilter() {
super.doCall((inner) => inner.postfilter());
return this;
}
/**
* If this is called then any vector index is skipped
*
* An exhaustive (flat) search will be performed. The query vector will
* be compared to every vector in the table. At high scales this can be
* expensive. However, this is often still useful. For example, skipping
* the vector index can give you ground truth results which you can use to
* calculate your recall to select an appropriate value for nprobes.
*/
bypassVectorIndex() {
super.doCall((inner) => inner.bypassVectorIndex());
return this;
}
/*
* Add a query vector to the search
*
* This method can be called multiple times to add multiple query vectors
* to the search. If multiple query vectors are added, then they will be searched
* in parallel, and the results will be concatenated. A column called `query_index`
* will be added to indicate the index of the query vector that produced the result.
*
* Performance wise, this is equivalent to running multiple queries concurrently.
*/
addQueryVector(vector) {
if (vector instanceof Promise) {
const res = (async () => {
try {
const v = await vector;
const arr = Float32Array.from(v);
//
// biome-ignore lint/suspicious/noExplicitAny: we need to get the `inner`, but js has no package scoping
const value = this.addQueryVector(arr);
const inner = value.inner;
return inner;
}
catch (e) {
return Promise.reject(e);
}
})();
return new VectorQuery(res);
}
else {
super.doCall((inner) => {
inner.addQueryVector(Float32Array.from(vector));
});
return this;
}
}
rerank(reranker) {
super.doCall((inner) => inner.rerank({
rerankHybrid: async (_, args) => {
const vecResults = await (0, arrow_1.fromBufferToRecordBatch)(args.vecResults);
const ftsResults = await (0, arrow_1.fromBufferToRecordBatch)(args.ftsResults);
const result = await reranker.rerankHybrid(args.query, vecResults, ftsResults);
const buffer = (0, arrow_1.fromRecordBatchToBuffer)(result);
return buffer;
},
}));
return this;
}
}
exports.VectorQuery = VectorQuery;
/**
* A query that returns a subset of the rows in the table.
*
* @hideconstructor
*/
class TakeQuery extends QueryBase {
constructor(inner) {
super(inner);
}
}
exports.TakeQuery = TakeQuery;
/** A builder for LanceDB queries.
*
* @see {@link Table#query}, {@link Table#search}
*
* @hideconstructor
*/
class Query extends StandardQueryBase {
/**
* @hidden
*/
constructor(tbl) {
super(tbl.query());
}
/**
* Find the nearest vectors to the given query vector.
*
* This converts the query from a plain query to a vector query.
*
* This method will attempt to convert the input to the query vector
* expected by the embedding model. If the input cannot be converted
* then an error will be thrown.
*
* By default, there is no embedding model, and the input should be
* an array-like object of numbers (something that can be used as input
* to Float32Array.from)
*
* If there is only one vector column (a column whose data type is a
* fixed size list of floats) then the column does not need to be specified.
* If there is more than one vector column you must use
* @see {@link VectorQuery#column} to specify which column you would like
* to compare with.
*
* If no index has been created on the vector column then a vector query
* will perform a distance comparison between the query vector and every
* vector in the database and then sort the results. This is sometimes
* called a "flat search"
*
* For small databases, with a few hundred thousand vectors or less, this can
* be reasonably fast. In larger databases you should create a vector index
* on the column. If there is a vector index then an "approximate" nearest
* neighbor search (frequently called an ANN search) will be performed. This
* search is much faster, but the results will be approximate.
*
* The query can be further parameterized using the returned builder. There
* are various ANN search parameters that will let you fine tune your recall
* accuracy vs search latency.
*
* Vector searches always have a `limit`. If `limit` has not been called then
* a default `limit` of 10 will be used. @see {@link Query#limit}
*/
nearestTo(vector) {
if (this.inner instanceof Promise) {
const nativeQuery = this.inner.then(async (inner) => {
if (vector instanceof Promise) {
const arr = await vector.then((v) => Float32Array.from(v));
return inner.nearestTo(arr);
}
else {
return inner.nearestTo(Float32Array.from(vector));
}
});
return new VectorQuery(nativeQuery);
}
if (vector instanceof Promise) {
const res = (async () => {
try {
const v = await vector;
const arr = Float32Array.from(v);
//
// biome-ignore lint/suspicious/noExplicitAny: we need to get the `inner`, but js has no package scoping
const value = this.nearestTo(arr);
const inner = value.inner;
return inner;
}
catch (e) {
return Promise.reject(e);
}
})();
return new VectorQuery(res);
}
else {
const vectorQuery = this.inner.nearestTo(Float32Array.from(vector));
return new VectorQuery(vectorQuery);
}
}
nearestToText(query, columns) {
this.doCall((inner) => {
if (typeof query === "string") {
inner.fullTextSearch({
query: query,
columns: columns,
});
}
else {
inner.fullTextSearch({ query: query.inner });
}
});
return this;
}
}
exports.Query = Query;
/**
* Enum representing the types of full-text queries supported.
*
* - `Match`: Performs a full-text search for terms in the query string.
* - `MatchPhrase`: Searches for an exact phrase match in the text.
* - `Boost`: Boosts the relevance score of specific terms in the query.
* - `MultiMatch`: Searches across multiple fields for the query terms.
*/
var FullTextQueryType;
(function (FullTextQueryType) {
FullTextQueryType["Match"] = "match";
FullTextQueryType["MatchPhrase"] = "match_phrase";
FullTextQueryType["Boost"] = "boost";
FullTextQueryType["MultiMatch"] = "multi_match";
FullTextQueryType["Boolean"] = "boolean";
})(FullTextQueryType || (exports.FullTextQueryType = FullTextQueryType = {}));
/**
* Enum representing the logical operators used in full-text queries.
*
* - `And`: All terms must match.
* - `Or`: At least one term must match.
*/
var Operator;
(function (Operator) {
Operator["And"] = "AND";
Operator["Or"] = "OR";
})(Operator || (exports.Operator = Operator = {}));
/**
* Enum representing the occurrence of terms in full-text queries.
*
* - `Must`: The term must be present in the document.
* - `Should`: The term should contribute to the document score, but is not required.
* - `MustNot`: The term must not be present in the document.
*/
var Occur;
(function (Occur) {
Occur["Should"] = "SHOULD";
Occur["Must"] = "MUST";
Occur["MustNot"] = "MUST_NOT";
})(Occur || (exports.Occur = Occur = {}));
// biome-ignore lint/suspicious/noExplicitAny: we want any here
function instanceOfFullTextQuery(obj) {
return obj != null && obj.inner instanceof native_1.JsFullTextQuery;
}
class MatchQuery {
/** @ignore */
inner;
/**
* Creates an instance of MatchQuery.
*
* @param query - The text query to search for.
* @param column - The name of the column to search within.
* @param options - Optional parameters for the match query.
* - `boost`: The boost factor for the query (default is 1.0).
* - `fuzziness`: The fuzziness level for the query (default is 0).
* - `maxExpansions`: The maximum number of terms to consider for fuzzy matching (default is 50).
* - `operator`: The logical operator to use for combining terms in the query (default is "OR").
* - `prefixLength`: The number of beginning characters being unchanged for fuzzy matching.
*/
constructor(query, column, options) {
let fuzziness = options?.fuzziness;
if (fuzziness === undefined) {
fuzziness = 0;
}
this.inner = native_1.JsFullTextQuery.matchQuery(query, column, options?.boost ?? 1.0, fuzziness, options?.maxExpansions ?? 50, options?.operator ?? Operator.Or, options?.prefixLength ?? 0);
}
queryType() {
return FullTextQueryType.Match;
}
}
exports.MatchQuery = MatchQuery;
class PhraseQuery {
/** @ignore */
inner;
/**
* Creates an instance of `PhraseQuery`.
*
* @param query - The phrase to search for in the specified column.
* @param column - The name of the column to search within.
* @param options - Optional parameters for the phrase query.
* - `slop`: The maximum number of intervening unmatched positions allowed between words in the phrase (default is 0).
*/
constructor(query, column, options) {
this.inner = native_1.JsFullTextQuery.phraseQuery(query, column, options?.slop ?? 0);
}
queryType() {
return FullTextQueryType.MatchPhrase;
}
}
exports.PhraseQuery = PhraseQuery;
class BoostQuery {
/** @ignore */
inner;
/**
* Creates an instance of BoostQuery.
* The boost returns documents that match the positive query,
* but penalizes those that match the negative query.
* the penalty is controlled by the `negativeBoost` parameter.
*
* @param positive - The positive query that boosts the relevance score.
* @param negative - The negative query that reduces the relevance score.
* @param options - Optional parameters for the boost query.
* - `negativeBoost`: The boost factor for the negative query (default is 0.0).
*/
constructor(positive, negative, options) {
this.inner = native_1.JsFullTextQuery.boostQuery(positive.inner, negative.inner, options?.negativeBoost);
}
queryType() {
return FullTextQueryType.Boost;
}
}
exports.BoostQuery = BoostQuery;
class MultiMatchQuery {
/** @ignore */
inner;
/**
* Creates an instance of MultiMatchQuery.
*
* @param query - The text query to search for across multiple columns.
* @param columns - An array of column names to search within.
* @param options - Optional parameters for the multi-match query.
* - `boosts`: An array of boost factors for each column (default is 1.0 for all).
* - `operator`: The logical operator to use for combining terms in the query (default is "OR").
*/
constructor(query, columns, options) {
this.inner = native_1.JsFullTextQuery.multiMatchQuery(query, columns, options?.boosts, options?.operator ?? Operator.Or);
}
queryType() {
return FullTextQueryType.MultiMatch;
}
}
exports.MultiMatchQuery = MultiMatchQuery;
class BooleanQuery {
/** @ignore */
inner;
/**
* Creates an instance of BooleanQuery.
*
* @param queries - An array of (Occur, FullTextQuery objects) to combine.
* Occur specifies whether the query must match, or should match.
*/
constructor(queries) {
this.inner = native_1.JsFullTextQuery.booleanQuery(queries.map(([occur, query]) => [occur, query.inner]));
}
queryType() {
return FullTextQueryType.Boolean;
}
}
exports.BooleanQuery = BooleanQuery;

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import { RecordBatch } from "apache-arrow";
export * from "./rrf";
export interface Reranker {
rerankHybrid(query: string, vecResults: RecordBatch, ftsResults: RecordBatch): Promise<RecordBatch>;
}

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"use strict";
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
var __createBinding = (this && this.__createBinding) || (Object.create ? (function(o, m, k, k2) {
if (k2 === undefined) k2 = k;
var desc = Object.getOwnPropertyDescriptor(m, k);
if (!desc || ("get" in desc ? !m.__esModule : desc.writable || desc.configurable)) {
desc = { enumerable: true, get: function() { return m[k]; } };
}
Object.defineProperty(o, k2, desc);
}) : (function(o, m, k, k2) {
if (k2 === undefined) k2 = k;
o[k2] = m[k];
}));
var __exportStar = (this && this.__exportStar) || function(m, exports) {
for (var p in m) if (p !== "default" && !Object.prototype.hasOwnProperty.call(exports, p)) __createBinding(exports, m, p);
};
Object.defineProperty(exports, "__esModule", { value: true });
__exportStar(require("./rrf"), exports);

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import { RecordBatch } from "apache-arrow";
import { RrfReranker as NativeRRFReranker } from "../native";
/**
* Reranks the results using the Reciprocal Rank Fusion (RRF) algorithm.
*
* @hideconstructor
*/
export declare class RRFReranker {
private inner;
/** @ignore */
constructor(inner: NativeRRFReranker);
static create(k?: number): Promise<RRFReranker>;
rerankHybrid(query: string, vecResults: RecordBatch, ftsResults: RecordBatch): Promise<RecordBatch>;
}

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"use strict";
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
Object.defineProperty(exports, "__esModule", { value: true });
exports.RRFReranker = void 0;
const arrow_1 = require("../arrow");
const native_1 = require("../native");
/**
* Reranks the results using the Reciprocal Rank Fusion (RRF) algorithm.
*
* @hideconstructor
*/
class RRFReranker {
inner;
/** @ignore */
constructor(inner) {
this.inner = inner;
}
static async create(k = 60) {
return new RRFReranker(await native_1.RrfReranker.tryNew(new Float32Array([k])));
}
async rerankHybrid(query, vecResults, ftsResults) {
const buffer = await this.inner.rerankHybrid(query, await (0, arrow_1.fromRecordBatchToBuffer)(vecResults), await (0, arrow_1.fromRecordBatchToBuffer)(ftsResults));
const recordBatch = await (0, arrow_1.fromBufferToRecordBatch)(buffer);
return recordBatch;
}
}
exports.RRFReranker = RRFReranker;

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import type { TKeys } from "apache-arrow/type";
import { DataType, Date_, Decimal, DenseUnion, Dictionary, Duration, Field, FixedSizeBinary, FixedSizeList, Float, Int, Interval, List, Map_, Schema, SchemaLike, SparseUnion, Struct, Table, TableLike, Time, Timestamp, TimestampMicrosecond, TimestampMillisecond, TimestampNanosecond, TimestampSecond, Type, Union } from "./arrow";
export declare function sanitizeMetadata(metadataLike?: unknown): Map<string, string> | undefined;
export declare function sanitizeInt(typeLike: object): Int<Type.Int | Type.Int8 | Type.Int16 | Type.Int32 | Type.Int64 | Type.Uint8 | Type.Uint16 | Type.Uint32 | Type.Uint64>;
export declare function sanitizeFloat(typeLike: object): Float<Type.Float | Type.Float16 | Type.Float32 | Type.Float64>;
export declare function sanitizeDecimal(typeLike: object): Decimal;
export declare function sanitizeDate(typeLike: object): Date_<import("apache-arrow/type").Dates>;
export declare function sanitizeTime(typeLike: object): Time<Type.Time | Type.TimeSecond | Type.TimeMillisecond | Type.TimeMicrosecond | Type.TimeNanosecond>;
export declare function sanitizeTimestamp(typeLike: object): Timestamp<Type.Timestamp | Type.TimestampSecond | Type.TimestampMillisecond | Type.TimestampMicrosecond | Type.TimestampNanosecond>;
export declare function sanitizeTypedTimestamp(typeLike: object, Datatype: typeof TimestampNanosecond | typeof TimestampMicrosecond | typeof TimestampMillisecond | typeof TimestampSecond): TimestampSecond | TimestampMillisecond | TimestampMicrosecond | TimestampNanosecond;
export declare function sanitizeInterval(typeLike: object): Interval<Type.Interval | Type.IntervalDayTime | Type.IntervalYearMonth>;
export declare function sanitizeList(typeLike: object): List<any>;
export declare function sanitizeStruct(typeLike: object): Struct<any>;
export declare function sanitizeUnion(typeLike: object): Union<Type.Union | Type.DenseUnion | Type.SparseUnion>;
export declare function sanitizeTypedUnion(typeLike: object, UnionType: typeof DenseUnion | typeof SparseUnion): SparseUnion | DenseUnion;
export declare function sanitizeFixedSizeBinary(typeLike: object): FixedSizeBinary;
export declare function sanitizeFixedSizeList(typeLike: object): FixedSizeList<any>;
export declare function sanitizeMap(typeLike: object): Map_<any, any>;
export declare function sanitizeDuration(typeLike: object): Duration<Type.Duration | Type.DurationSecond | Type.DurationMillisecond | Type.DurationMicrosecond | Type.DurationNanosecond>;
export declare function sanitizeDictionary(typeLike: object): Dictionary<DataType<any, any>, TKeys>;
export declare function sanitizeType(typeLike: unknown): DataType<any>;
export declare function sanitizeField(fieldLike: unknown): Field;
/**
* Convert something schemaLike into a Schema instance
*
* This method is often needed even when the caller is using a Schema
* instance because they might be using a different instance of apache-arrow
* than lancedb is using.
*/
export declare function sanitizeSchema(schemaLike: SchemaLike): Schema;
export declare function sanitizeTable(tableLike: TableLike): Table;
export declare function dataTypeFromName(typeName: string): DataType;

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"use strict";
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
Object.defineProperty(exports, "__esModule", { value: true });
exports.sanitizeMetadata = sanitizeMetadata;
exports.sanitizeInt = sanitizeInt;
exports.sanitizeFloat = sanitizeFloat;
exports.sanitizeDecimal = sanitizeDecimal;
exports.sanitizeDate = sanitizeDate;
exports.sanitizeTime = sanitizeTime;
exports.sanitizeTimestamp = sanitizeTimestamp;
exports.sanitizeTypedTimestamp = sanitizeTypedTimestamp;
exports.sanitizeInterval = sanitizeInterval;
exports.sanitizeList = sanitizeList;
exports.sanitizeStruct = sanitizeStruct;
exports.sanitizeUnion = sanitizeUnion;
exports.sanitizeTypedUnion = sanitizeTypedUnion;
exports.sanitizeFixedSizeBinary = sanitizeFixedSizeBinary;
exports.sanitizeFixedSizeList = sanitizeFixedSizeList;
exports.sanitizeMap = sanitizeMap;
exports.sanitizeDuration = sanitizeDuration;
exports.sanitizeDictionary = sanitizeDictionary;
exports.sanitizeType = sanitizeType;
exports.sanitizeField = sanitizeField;
exports.sanitizeSchema = sanitizeSchema;
exports.sanitizeTable = sanitizeTable;
exports.dataTypeFromName = dataTypeFromName;
// The utilities in this file help sanitize data from the user's arrow
// library into the types expected by vectordb's arrow library. Node
// generally allows for mulitple versions of the same library (and sometimes
// even multiple copies of the same version) to be installed at the same
// time. However, arrow-js uses instanceof which expected that the input
// comes from the exact same library instance. This is not always the case
// and so we must sanitize the input to ensure that it is compatible.
const apache_arrow_1 = require("apache-arrow");
const arrow_1 = require("./arrow");
function sanitizeMetadata(metadataLike) {
if (metadataLike === undefined || metadataLike === null) {
return undefined;
}
if (!(metadataLike instanceof Map)) {
throw Error("Expected metadata, if present, to be a Map<string, string>");
}
for (const item of metadataLike) {
if (!(typeof item[0] === "string" || !(typeof item[1] === "string"))) {
throw Error("Expected metadata, if present, to be a Map<string, string> but it had non-string keys or values");
}
}
return metadataLike;
}
function sanitizeInt(typeLike) {
if (!("bitWidth" in typeLike) ||
typeof typeLike.bitWidth !== "number" ||
!("isSigned" in typeLike) ||
typeof typeLike.isSigned !== "boolean") {
throw Error("Expected an Int Type to have a `bitWidth` and `isSigned` property");
}
return new arrow_1.Int(typeLike.isSigned, typeLike.bitWidth);
}
function sanitizeFloat(typeLike) {
if (!("precision" in typeLike) || typeof typeLike.precision !== "number") {
throw Error("Expected a Float Type to have a `precision` property");
}
return new arrow_1.Float(typeLike.precision);
}
function sanitizeDecimal(typeLike) {
if (!("scale" in typeLike) ||
typeof typeLike.scale !== "number" ||
!("precision" in typeLike) ||
typeof typeLike.precision !== "number" ||
!("bitWidth" in typeLike) ||
typeof typeLike.bitWidth !== "number") {
throw Error("Expected a Decimal Type to have `scale`, `precision`, and `bitWidth` properties");
}
return new arrow_1.Decimal(typeLike.scale, typeLike.precision, typeLike.bitWidth);
}
function sanitizeDate(typeLike) {
if (!("unit" in typeLike) || typeof typeLike.unit !== "number") {
throw Error("Expected a Date type to have a `unit` property");
}
return new arrow_1.Date_(typeLike.unit);
}
function sanitizeTime(typeLike) {
if (!("unit" in typeLike) ||
typeof typeLike.unit !== "number" ||
!("bitWidth" in typeLike) ||
typeof typeLike.bitWidth !== "number") {
throw Error("Expected a Time type to have `unit` and `bitWidth` properties");
}
return new arrow_1.Time(typeLike.unit, typeLike.bitWidth);
}
function sanitizeTimestamp(typeLike) {
if (!("unit" in typeLike) || typeof typeLike.unit !== "number") {
throw Error("Expected a Timestamp type to have a `unit` property");
}
let timezone = null;
if ("timezone" in typeLike && typeof typeLike.timezone === "string") {
timezone = typeLike.timezone;
}
return new arrow_1.Timestamp(typeLike.unit, timezone);
}
function sanitizeTypedTimestamp(typeLike,
// eslint-disable-next-line @typescript-eslint/naming-convention
Datatype) {
let timezone = null;
if ("timezone" in typeLike && typeof typeLike.timezone === "string") {
timezone = typeLike.timezone;
}
return new Datatype(timezone);
}
function sanitizeInterval(typeLike) {
if (!("unit" in typeLike) || typeof typeLike.unit !== "number") {
throw Error("Expected an Interval type to have a `unit` property");
}
return new arrow_1.Interval(typeLike.unit);
}
function sanitizeList(typeLike) {
if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
throw Error("Expected a List type to have an array-like `children` property");
}
if (typeLike.children.length !== 1) {
throw Error("Expected a List type to have exactly one child");
}
return new arrow_1.List(sanitizeField(typeLike.children[0]));
}
function sanitizeStruct(typeLike) {
if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
throw Error("Expected a Struct type to have an array-like `children` property");
}
return new arrow_1.Struct(typeLike.children.map((child) => sanitizeField(child)));
}
function sanitizeUnion(typeLike) {
if (!("typeIds" in typeLike) ||
!("mode" in typeLike) ||
typeof typeLike.mode !== "number") {
throw Error("Expected a Union type to have `typeIds` and `mode` properties");
}
if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
throw Error("Expected a Union type to have an array-like `children` property");
}
return new arrow_1.Union(typeLike.mode,
// biome-ignore lint/suspicious/noExplicitAny: skip
typeLike.typeIds, typeLike.children.map((child) => sanitizeField(child)));
}
function sanitizeTypedUnion(typeLike,
// eslint-disable-next-line @typescript-eslint/naming-convention
UnionType) {
if (!("typeIds" in typeLike)) {
throw Error("Expected a DenseUnion/SparseUnion type to have a `typeIds` property");
}
if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
throw Error("Expected a DenseUnion/SparseUnion type to have an array-like `children` property");
}
return new UnionType(typeLike.typeIds, typeLike.children.map((child) => sanitizeField(child)));
}
function sanitizeFixedSizeBinary(typeLike) {
if (!("byteWidth" in typeLike) || typeof typeLike.byteWidth !== "number") {
throw Error("Expected a FixedSizeBinary type to have a `byteWidth` property");
}
return new arrow_1.FixedSizeBinary(typeLike.byteWidth);
}
function sanitizeFixedSizeList(typeLike) {
if (!("listSize" in typeLike) || typeof typeLike.listSize !== "number") {
throw Error("Expected a FixedSizeList type to have a `listSize` property");
}
if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
throw Error("Expected a FixedSizeList type to have an array-like `children` property");
}
if (typeLike.children.length !== 1) {
throw Error("Expected a FixedSizeList type to have exactly one child");
}
return new arrow_1.FixedSizeList(typeLike.listSize, sanitizeField(typeLike.children[0]));
}
function sanitizeMap(typeLike) {
if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
throw Error("Expected a Map type to have an array-like `children` property");
}
if (!("keysSorted" in typeLike) || typeof typeLike.keysSorted !== "boolean") {
throw Error("Expected a Map type to have a `keysSorted` property");
}
return new arrow_1.Map_(
// biome-ignore lint/suspicious/noExplicitAny: skip
typeLike.children.map((field) => sanitizeField(field)), typeLike.keysSorted);
}
function sanitizeDuration(typeLike) {
if (!("unit" in typeLike) || typeof typeLike.unit !== "number") {
throw Error("Expected a Duration type to have a `unit` property");
}
return new arrow_1.Duration(typeLike.unit);
}
function sanitizeDictionary(typeLike) {
if (!("id" in typeLike) || typeof typeLike.id !== "number") {
throw Error("Expected a Dictionary type to have an `id` property");
}
if (!("indices" in typeLike) || typeof typeLike.indices !== "object") {
throw Error("Expected a Dictionary type to have an `indices` property");
}
if (!("dictionary" in typeLike) || typeof typeLike.dictionary !== "object") {
throw Error("Expected a Dictionary type to have an `dictionary` property");
}
if (!("isOrdered" in typeLike) || typeof typeLike.isOrdered !== "boolean") {
throw Error("Expected a Dictionary type to have an `isOrdered` property");
}
return new arrow_1.Dictionary(sanitizeType(typeLike.dictionary), sanitizeType(typeLike.indices), typeLike.id, typeLike.isOrdered);
}
// biome-ignore lint/suspicious/noExplicitAny: skip
function sanitizeType(typeLike) {
if (typeof typeLike === "string") {
return dataTypeFromName(typeLike);
}
if (typeof typeLike !== "object" || typeLike === null) {
throw Error("Expected a Type but object was null/undefined");
}
if (!("typeId" in typeLike) ||
!(typeof typeLike.typeId !== "function" ||
typeof typeLike.typeId !== "number")) {
throw Error("Expected a Type to have a typeId property");
}
let typeId;
if (typeof typeLike.typeId === "function") {
typeId = typeLike.typeId();
}
else if (typeof typeLike.typeId === "number") {
typeId = typeLike.typeId;
}
else {
throw Error("Type's typeId property was not a function or number");
}
switch (typeId) {
case arrow_1.Type.NONE:
throw Error("Received a Type with a typeId of NONE");
case arrow_1.Type.Null:
return new arrow_1.Null();
case arrow_1.Type.Int:
return sanitizeInt(typeLike);
case arrow_1.Type.Float:
return sanitizeFloat(typeLike);
case arrow_1.Type.Binary:
return new arrow_1.Binary();
case arrow_1.Type.Utf8:
return new arrow_1.Utf8();
case arrow_1.Type.Bool:
return new arrow_1.Bool();
case arrow_1.Type.Decimal:
return sanitizeDecimal(typeLike);
case arrow_1.Type.Date:
return sanitizeDate(typeLike);
case arrow_1.Type.Time:
return sanitizeTime(typeLike);
case arrow_1.Type.Timestamp:
return sanitizeTimestamp(typeLike);
case arrow_1.Type.Interval:
return sanitizeInterval(typeLike);
case arrow_1.Type.List:
return sanitizeList(typeLike);
case arrow_1.Type.Struct:
return sanitizeStruct(typeLike);
case arrow_1.Type.Union:
return sanitizeUnion(typeLike);
case arrow_1.Type.FixedSizeBinary:
return sanitizeFixedSizeBinary(typeLike);
case arrow_1.Type.FixedSizeList:
return sanitizeFixedSizeList(typeLike);
case arrow_1.Type.Map:
return sanitizeMap(typeLike);
case arrow_1.Type.Duration:
return sanitizeDuration(typeLike);
case arrow_1.Type.Dictionary:
return sanitizeDictionary(typeLike);
case arrow_1.Type.Int8:
return new arrow_1.Int8();
case arrow_1.Type.Int16:
return new arrow_1.Int16();
case arrow_1.Type.Int32:
return new arrow_1.Int32();
case arrow_1.Type.Int64:
return new arrow_1.Int64();
case arrow_1.Type.Uint8:
return new arrow_1.Uint8();
case arrow_1.Type.Uint16:
return new arrow_1.Uint16();
case arrow_1.Type.Uint32:
return new arrow_1.Uint32();
case arrow_1.Type.Uint64:
return new arrow_1.Uint64();
case arrow_1.Type.Float16:
return new arrow_1.Float16();
case arrow_1.Type.Float32:
return new arrow_1.Float32();
case arrow_1.Type.Float64:
return new arrow_1.Float64();
case arrow_1.Type.DateMillisecond:
return new arrow_1.DateMillisecond();
case arrow_1.Type.DateDay:
return new arrow_1.DateDay();
case arrow_1.Type.TimeNanosecond:
return new arrow_1.TimeNanosecond();
case arrow_1.Type.TimeMicrosecond:
return new arrow_1.TimeMicrosecond();
case arrow_1.Type.TimeMillisecond:
return new arrow_1.TimeMillisecond();
case arrow_1.Type.TimeSecond:
return new arrow_1.TimeSecond();
case arrow_1.Type.TimestampNanosecond:
return sanitizeTypedTimestamp(typeLike, arrow_1.TimestampNanosecond);
case arrow_1.Type.TimestampMicrosecond:
return sanitizeTypedTimestamp(typeLike, arrow_1.TimestampMicrosecond);
case arrow_1.Type.TimestampMillisecond:
return sanitizeTypedTimestamp(typeLike, arrow_1.TimestampMillisecond);
case arrow_1.Type.TimestampSecond:
return sanitizeTypedTimestamp(typeLike, arrow_1.TimestampSecond);
case arrow_1.Type.DenseUnion:
return sanitizeTypedUnion(typeLike, arrow_1.DenseUnion);
case arrow_1.Type.SparseUnion:
return sanitizeTypedUnion(typeLike, arrow_1.SparseUnion);
case arrow_1.Type.IntervalDayTime:
return new arrow_1.IntervalDayTime();
case arrow_1.Type.IntervalYearMonth:
return new arrow_1.IntervalYearMonth();
case arrow_1.Type.DurationNanosecond:
return new arrow_1.DurationNanosecond();
case arrow_1.Type.DurationMicrosecond:
return new arrow_1.DurationMicrosecond();
case arrow_1.Type.DurationMillisecond:
return new arrow_1.DurationMillisecond();
case arrow_1.Type.DurationSecond:
return new arrow_1.DurationSecond();
default:
throw new Error("Unrecognized type id in schema: " + typeId);
}
}
function sanitizeField(fieldLike) {
if (fieldLike instanceof arrow_1.Field) {
return fieldLike;
}
if (typeof fieldLike !== "object" || fieldLike === null) {
throw Error("Expected a Field but object was null/undefined");
}
if (!("type" in fieldLike) ||
!("name" in fieldLike) ||
!("nullable" in fieldLike)) {
throw Error("The field passed in is missing a `type`/`name`/`nullable` property");
}
let type;
try {
type = sanitizeType(fieldLike.type);
}
catch (error) {
throw Error(`Unable to sanitize type for field: ${fieldLike.name} due to error: ${error}`, { cause: error });
}
const name = fieldLike.name;
if (!(typeof name === "string")) {
throw Error("The field passed in had a non-string `name` property");
}
const nullable = fieldLike.nullable;
if (!(typeof nullable === "boolean")) {
throw Error("The field passed in had a non-boolean `nullable` property");
}
let metadata;
if ("metadata" in fieldLike) {
metadata = sanitizeMetadata(fieldLike.metadata);
}
return new arrow_1.Field(name, type, nullable, metadata);
}
/**
* Convert something schemaLike into a Schema instance
*
* This method is often needed even when the caller is using a Schema
* instance because they might be using a different instance of apache-arrow
* than lancedb is using.
*/
function sanitizeSchema(schemaLike) {
if (schemaLike instanceof arrow_1.Schema) {
return schemaLike;
}
if (typeof schemaLike !== "object" || schemaLike === null) {
throw Error("Expected a Schema but object was null/undefined");
}
if (!("fields" in schemaLike)) {
throw Error("The schema passed in does not appear to be a schema (no 'fields' property)");
}
let metadata;
if ("metadata" in schemaLike) {
metadata = sanitizeMetadata(schemaLike.metadata);
}
if (!Array.isArray(schemaLike.fields)) {
throw Error("The schema passed in had a 'fields' property but it was not an array");
}
const sanitizedFields = schemaLike.fields.map((field) => sanitizeField(field));
return new arrow_1.Schema(sanitizedFields, metadata);
}
function sanitizeTable(tableLike) {
if (tableLike instanceof arrow_1.Table) {
return tableLike;
}
if (typeof tableLike !== "object" || tableLike === null) {
throw Error("Expected a Table but object was null/undefined");
}
if (!("schema" in tableLike)) {
throw Error("The table passed in does not appear to be a table (no 'schema' property)");
}
if (!("batches" in tableLike)) {
throw Error("The table passed in does not appear to be a table (no 'columns' property)");
}
const schema = sanitizeSchema(tableLike.schema);
const batches = tableLike.batches.map(sanitizeRecordBatch);
return new arrow_1.Table(schema, batches);
}
function sanitizeRecordBatch(batchLike) {
if (batchLike instanceof arrow_1.RecordBatch) {
return batchLike;
}
if (typeof batchLike !== "object" || batchLike === null) {
throw Error("Expected a RecordBatch but object was null/undefined");
}
if (!("schema" in batchLike)) {
throw Error("The record batch passed in does not appear to be a record batch (no 'schema' property)");
}
if (!("data" in batchLike)) {
throw Error("The record batch passed in does not appear to be a record batch (no 'data' property)");
}
const schema = sanitizeSchema(batchLike.schema);
const data = sanitizeData(batchLike.data);
return new arrow_1.RecordBatch(schema, data);
}
function sanitizeData(dataLike) {
if (dataLike instanceof apache_arrow_1.Data) {
return dataLike;
}
return new apache_arrow_1.Data(dataLike.type, dataLike.offset, dataLike.length, dataLike.nullCount, {
[apache_arrow_1.BufferType.OFFSET]: dataLike.valueOffsets,
[apache_arrow_1.BufferType.DATA]: dataLike.values,
[apache_arrow_1.BufferType.VALIDITY]: dataLike.nullBitmap,
[apache_arrow_1.BufferType.TYPE]: dataLike.typeIds,
});
}
const constructorsByTypeName = {
null: () => new arrow_1.Null(),
binary: () => new arrow_1.Binary(),
utf8: () => new arrow_1.Utf8(),
bool: () => new arrow_1.Bool(),
int8: () => new arrow_1.Int8(),
int16: () => new arrow_1.Int16(),
int32: () => new arrow_1.Int32(),
int64: () => new arrow_1.Int64(),
uint8: () => new arrow_1.Uint8(),
uint16: () => new arrow_1.Uint16(),
uint32: () => new arrow_1.Uint32(),
uint64: () => new arrow_1.Uint64(),
float16: () => new arrow_1.Float16(),
float32: () => new arrow_1.Float32(),
float64: () => new arrow_1.Float64(),
datemillisecond: () => new arrow_1.DateMillisecond(),
dateday: () => new arrow_1.DateDay(),
timenanosecond: () => new arrow_1.TimeNanosecond(),
timemicrosecond: () => new arrow_1.TimeMicrosecond(),
timemillisecond: () => new arrow_1.TimeMillisecond(),
timesecond: () => new arrow_1.TimeSecond(),
intervaldaytime: () => new arrow_1.IntervalDayTime(),
intervalyearmonth: () => new arrow_1.IntervalYearMonth(),
durationnanosecond: () => new arrow_1.DurationNanosecond(),
durationmicrosecond: () => new arrow_1.DurationMicrosecond(),
durationmillisecond: () => new arrow_1.DurationMillisecond(),
durationsecond: () => new arrow_1.DurationSecond(),
};
function dataTypeFromName(typeName) {
const normalizedTypeName = typeName.toLowerCase();
const _constructor = constructorsByTypeName[normalizedTypeName];
if (!_constructor) {
throw new Error("Unrecognized type name in schema: " + typeName);
}
return _constructor();
}

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extensions/memory-lancedb/node_modules/@lancedb/lancedb/dist/table.d.ts generated vendored Normal file
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@ -0,0 +1,552 @@
import { Table as ArrowTable, Data, DataType, IntoVector, MultiVector, Schema } from "./arrow";
import { IndexOptions } from "./indices";
import { MergeInsertBuilder } from "./merge";
import { AddColumnsResult, AddColumnsSql, AddResult, AlterColumnsResult, DeleteResult, DropColumnsResult, IndexConfig, IndexStatistics, OptimizeStats, TableStatistics, Tags, UpdateResult, Table as _NativeTable } from "./native";
import { FullTextQuery, Query, TakeQuery, VectorQuery } from "./query";
import { IntoSql } from "./util";
export { IndexConfig } from "./native";
/**
* Options for adding data to a table.
*/
export interface AddDataOptions {
/**
* If "append" (the default) then the new data will be added to the table
*
* If "overwrite" then the new data will replace the existing data in the table.
*/
mode: "append" | "overwrite";
}
export interface UpdateOptions {
/**
* A filter that limits the scope of the update.
*
* This should be an SQL filter expression.
*
* Only rows that satisfy the expression will be updated.
*
* For example, this could be 'my_col == 0' to replace all instances
* of 0 in a column with some other default value.
*/
where: string;
}
export interface OptimizeOptions {
/**
* If set then all versions older than the given date
* be removed. The current version will never be removed.
* The default is 7 days
* @example
* // Delete all versions older than 1 day
* const olderThan = new Date();
* olderThan.setDate(olderThan.getDate() - 1));
* tbl.optimize({cleanupOlderThan: olderThan});
*
* // Delete all versions except the current version
* tbl.optimize({cleanupOlderThan: new Date()});
*/
cleanupOlderThan: Date;
deleteUnverified: boolean;
}
export interface Version {
version: number;
timestamp: Date;
metadata: Record<string, string>;
}
/**
* A Table is a collection of Records in a LanceDB Database.
*
* A Table object is expected to be long lived and reused for multiple operations.
* Table objects will cache a certain amount of index data in memory. This cache
* will be freed when the Table is garbage collected. To eagerly free the cache you
* can call the `close` method. Once the Table is closed, it cannot be used for any
* further operations.
*
* Tables are created using the methods {@link Connection#createTable}
* and {@link Connection#createEmptyTable}. Existing tables are opened
* using {@link Connection#openTable}.
*
* Closing a table is optional. It not closed, it will be closed when it is garbage
* collected.
*
* @hideconstructor
*/
export declare abstract class Table {
/** Returns the name of the table */
abstract get name(): string;
/** Return true if the table has not been closed */
abstract isOpen(): boolean;
/**
* Close the table, releasing any underlying resources.
*
* It is safe to call this method multiple times.
*
* Any attempt to use the table after it is closed will result in an error.
*/
abstract close(): void;
/** Return a brief description of the table */
abstract display(): string;
/** Get the schema of the table. */
abstract schema(): Promise<Schema>;
/**
* Insert records into this Table.
* @param {Data} data Records to be inserted into the Table
* @returns {Promise<AddResult>} A promise that resolves to an object
* containing the new version number of the table
*/
abstract add(data: Data, options?: Partial<AddDataOptions>): Promise<AddResult>;
/**
* Update existing records in the Table
* @param opts.values The values to update. The keys are the column names and the values
* are the values to set.
* @returns {Promise<UpdateResult>} A promise that resolves to an object containing
* the number of rows updated and the new version number
* @example
* ```ts
* table.update({where:"x = 2", values:{"vector": [10, 10]}})
* ```
*/
abstract update(opts: {
values: Map<string, IntoSql> | Record<string, IntoSql>;
} & Partial<UpdateOptions>): Promise<UpdateResult>;
/**
* Update existing records in the Table
* @param opts.valuesSql The values to update. The keys are the column names and the values
* are the values to set. The values are SQL expressions.
* @returns {Promise<UpdateResult>} A promise that resolves to an object containing
* the number of rows updated and the new version number
* @example
* ```ts
* table.update({where:"x = 2", valuesSql:{"x": "x + 1"}})
* ```
*/
abstract update(opts: {
valuesSql: Map<string, string> | Record<string, string>;
} & Partial<UpdateOptions>): Promise<UpdateResult>;
/**
* Update existing records in the Table
*
* An update operation can be used to adjust existing values. Use the
* returned builder to specify which columns to update. The new value
* can be a literal value (e.g. replacing nulls with some default value)
* or an expression applied to the old value (e.g. incrementing a value)
*
* An optional condition can be specified (e.g. "only update if the old
* value is 0")
*
* Note: if your condition is something like "some_id_column == 7" and
* you are updating many rows (with different ids) then you will get
* better performance with a single [`merge_insert`] call instead of
* repeatedly calilng this method.
* @param {Map<string, string> | Record<string, string>} updates - the
* columns to update
* @returns {Promise<UpdateResult>} A promise that resolves to an object
* containing the number of rows updated and the new version number
*
* Keys in the map should specify the name of the column to update.
* Values in the map provide the new value of the column. These can
* be SQL literal strings (e.g. "7" or "'foo'") or they can be expressions
* based on the row being updated (e.g. "my_col + 1")
* @param {Partial<UpdateOptions>} options - additional options to control
* the update behavior
*/
abstract update(updates: Map<string, string> | Record<string, string>, options?: Partial<UpdateOptions>): Promise<UpdateResult>;
/** Count the total number of rows in the dataset. */
abstract countRows(filter?: string): Promise<number>;
/**
* Delete the rows that satisfy the predicate.
* @returns {Promise<DeleteResult>} A promise that resolves to an object
* containing the new version number of the table
*/
abstract delete(predicate: string): Promise<DeleteResult>;
/**
* Create an index to speed up queries.
*
* Indices can be created on vector columns or scalar columns.
* Indices on vector columns will speed up vector searches.
* Indices on scalar columns will speed up filtering (in both
* vector and non-vector searches)
*
* We currently don't support custom named indexes.
* The index name will always be `${column}_idx`.
*
* @example
* // If the column has a vector (fixed size list) data type then
* // an IvfPq vector index will be created.
* const table = await conn.openTable("my_table");
* await table.createIndex("vector");
* @example
* // For advanced control over vector index creation you can specify
* // the index type and options.
* const table = await conn.openTable("my_table");
* await table.createIndex("vector", {
* config: lancedb.Index.ivfPq({
* numPartitions: 128,
* numSubVectors: 16,
* }),
* });
* @example
* // Or create a Scalar index
* await table.createIndex("my_float_col");
*/
abstract createIndex(column: string, options?: Partial<IndexOptions>): Promise<void>;
/**
* Drop an index from the table.
*
* @param name The name of the index.
*
* This does not delete the index from disk, it just removes it from the table.
* To delete the index, run {@link Table#optimize} after dropping the index.
*
* Use {@link Table.listIndices} to find the names of the indices.
*/
abstract dropIndex(name: string): Promise<void>;
/**
* Prewarm an index in the table.
*
* @param name The name of the index.
*
* This will load the index into memory. This may reduce the cold-start time for
* future queries. If the index does not fit in the cache then this call may be
* wasteful.
*/
abstract prewarmIndex(name: string): Promise<void>;
/**
* Waits for asynchronous indexing to complete on the table.
*
* @param indexNames The name of the indices to wait for
* @param timeoutSeconds The number of seconds to wait before timing out
*
* This will raise an error if the indices are not created and fully indexed within the timeout.
*/
abstract waitForIndex(indexNames: string[], timeoutSeconds: number): Promise<void>;
/**
* Create a {@link Query} Builder.
*
* Queries allow you to search your existing data. By default the query will
* return all the data in the table in no particular order. The builder
* returned by this method can be used to control the query using filtering,
* vector similarity, sorting, and more.
*
* Note: By default, all columns are returned. For best performance, you should
* only fetch the columns you need.
*
* When appropriate, various indices and statistics based pruning will be used to
* accelerate the query.
* @example
* // SQL-style filtering
* //
* // This query will return up to 1000 rows whose value in the `id` column
* // is greater than 5. LanceDb supports a broad set of filtering functions.
* for await (const batch of table
* .query()
* .where("id > 1")
* .select(["id"])
* .limit(20)) {
* console.log(batch);
* }
* @example
* // Vector Similarity Search
* //
* // This example will find the 10 rows whose value in the "vector" column are
* // closest to the query vector [1.0, 2.0, 3.0]. If an index has been created
* // on the "vector" column then this will perform an ANN search.
* //
* // The `refineFactor` and `nprobes` methods are used to control the recall /
* // latency tradeoff of the search.
* for await (const batch of table
* .query()
* .where("id > 1")
* .select(["id"])
* .limit(20)) {
* console.log(batch);
* }
* @example
* // Scan the full dataset
* //
* // This query will return everything in the table in no particular order.
* for await (const batch of table.query()) {
* console.log(batch);
* }
* @returns {Query} A builder that can be used to parameterize the query
*/
abstract query(): Query;
/**
* Create a query that returns a subset of the rows in the table.
* @param offsets The offsets of the rows to return.
* @returns A builder that can be used to parameterize the query.
*/
abstract takeOffsets(offsets: number[]): TakeQuery;
/**
* Create a query that returns a subset of the rows in the table.
* @param rowIds The row ids of the rows to return.
* @returns A builder that can be used to parameterize the query.
*/
abstract takeRowIds(rowIds: number[]): TakeQuery;
/**
* Create a search query to find the nearest neighbors
* of the given query
* @param {string | IntoVector} query - the query, a vector or string
* @param {string} queryType - the type of the query, "vector", "fts", or "auto"
* @param {string | string[]} ftsColumns - the columns to search in for full text search
* for now, only one column can be searched at a time.
*
* when "auto" is used, if the query is a string and an embedding function is defined, it will be treated as a vector query
* if the query is a string and no embedding function is defined, it will be treated as a full text search query
*/
abstract search(query: string | IntoVector | MultiVector | FullTextQuery, queryType?: string, ftsColumns?: string | string[]): VectorQuery | Query;
/**
* Search the table with a given query vector.
*
* This is a convenience method for preparing a vector query and
* is the same thing as calling `nearestTo` on the builder returned
* by `query`. @see {@link Query#nearestTo} for more details.
*/
abstract vectorSearch(vector: IntoVector | MultiVector): VectorQuery;
/**
* Add new columns with defined values.
* @param {AddColumnsSql[]} newColumnTransforms pairs of column names and
* the SQL expression to use to calculate the value of the new column. These
* expressions will be evaluated for each row in the table, and can
* reference existing columns in the table.
* @returns {Promise<AddColumnsResult>} A promise that resolves to an object
* containing the new version number of the table after adding the columns.
*/
abstract addColumns(newColumnTransforms: AddColumnsSql[]): Promise<AddColumnsResult>;
/**
* Alter the name or nullability of columns.
* @param {ColumnAlteration[]} columnAlterations One or more alterations to
* apply to columns.
* @returns {Promise<AlterColumnsResult>} A promise that resolves to an object
* containing the new version number of the table after altering the columns.
*/
abstract alterColumns(columnAlterations: ColumnAlteration[]): Promise<AlterColumnsResult>;
/**
* Drop one or more columns from the dataset
*
* This is a metadata-only operation and does not remove the data from the
* underlying storage. In order to remove the data, you must subsequently
* call ``compact_files`` to rewrite the data without the removed columns and
* then call ``cleanup_files`` to remove the old files.
* @param {string[]} columnNames The names of the columns to drop. These can
* be nested column references (e.g. "a.b.c") or top-level column names
* (e.g. "a").
* @returns {Promise<DropColumnsResult>} A promise that resolves to an object
* containing the new version number of the table after dropping the columns.
*/
abstract dropColumns(columnNames: string[]): Promise<DropColumnsResult>;
/** Retrieve the version of the table */
abstract version(): Promise<number>;
/**
* Checks out a specific version of the table _This is an in-place operation._
*
* This allows viewing previous versions of the table. If you wish to
* keep writing to the dataset starting from an old version, then use
* the `restore` function.
*
* Calling this method will set the table into time-travel mode. If you
* wish to return to standard mode, call `checkoutLatest`.
* @param {number | string} version The version to checkout, could be version number or tag
* @example
* ```typescript
* import * as lancedb from "@lancedb/lancedb"
* const db = await lancedb.connect("./.lancedb");
* const table = await db.createTable("my_table", [
* { vector: [1.1, 0.9], type: "vector" },
* ]);
*
* console.log(await table.version()); // 1
* console.log(table.display());
* await table.add([{ vector: [0.5, 0.2], type: "vector" }]);
* await table.checkout(1);
* console.log(await table.version()); // 2
* ```
*/
abstract checkout(version: number | string): Promise<void>;
/**
* Checkout the latest version of the table. _This is an in-place operation._
*
* The table will be set back into standard mode, and will track the latest
* version of the table.
*/
abstract checkoutLatest(): Promise<void>;
/**
* List all the versions of the table
*/
abstract listVersions(): Promise<Version[]>;
/**
* Get a tags manager for this table.
*
* Tags allow you to label specific versions of a table with a human-readable name.
* The returned tags manager can be used to list, create, update, or delete tags.
*
* @returns {Tags} A tags manager for this table
* @example
* ```typescript
* const tagsManager = await table.tags();
* await tagsManager.create("v1", 1);
* const tags = await tagsManager.list();
* console.log(tags); // { "v1": { version: 1, manifestSize: ... } }
* ```
*/
abstract tags(): Promise<Tags>;
/**
* Restore the table to the currently checked out version
*
* This operation will fail if checkout has not been called previously
*
* This operation will overwrite the latest version of the table with a
* previous version. Any changes made since the checked out version will
* no longer be visible.
*
* Once the operation concludes the table will no longer be in a checked
* out state and the read_consistency_interval, if any, will apply.
*/
abstract restore(): Promise<void>;
/**
* Optimize the on-disk data and indices for better performance.
*
* Modeled after ``VACUUM`` in PostgreSQL.
*
* Optimization covers three operations:
*
* - Compaction: Merges small files into larger ones
* - Prune: Removes old versions of the dataset
* - Index: Optimizes the indices, adding new data to existing indices
*
*
* Experimental API
* ----------------
*
* The optimization process is undergoing active development and may change.
* Our goal with these changes is to improve the performance of optimization and
* reduce the complexity.
*
* That being said, it is essential today to run optimize if you want the best
* performance. It should be stable and safe to use in production, but it our
* hope that the API may be simplified (or not even need to be called) in the
* future.
*
* The frequency an application shoudl call optimize is based on the frequency of
* data modifications. If data is frequently added, deleted, or updated then
* optimize should be run frequently. A good rule of thumb is to run optimize if
* you have added or modified 100,000 or more records or run more than 20 data
* modification operations.
*/
abstract optimize(options?: Partial<OptimizeOptions>): Promise<OptimizeStats>;
/** List all indices that have been created with {@link Table.createIndex} */
abstract listIndices(): Promise<IndexConfig[]>;
/** Return the table as an arrow table */
abstract toArrow(): Promise<ArrowTable>;
abstract mergeInsert(on: string | string[]): MergeInsertBuilder;
/** List all the stats of a specified index
*
* @param {string} name The name of the index.
* @returns {IndexStatistics | undefined} The stats of the index. If the index does not exist, it will return undefined
*
* Use {@link Table.listIndices} to find the names of the indices.
*/
abstract indexStats(name: string): Promise<IndexStatistics | undefined>;
/** Returns table and fragment statistics
*
* @returns {TableStatistics} The table and fragment statistics
*
*/
abstract stats(): Promise<TableStatistics>;
}
export declare class LocalTable extends Table {
private readonly inner;
constructor(inner: _NativeTable);
get name(): string;
isOpen(): boolean;
close(): void;
display(): string;
private getEmbeddingFunctions;
/** Get the schema of the table. */
schema(): Promise<Schema>;
add(data: Data, options?: Partial<AddDataOptions>): Promise<AddResult>;
update(optsOrUpdates: (Map<string, string> | Record<string, string>) | ({
values: Map<string, IntoSql> | Record<string, IntoSql>;
} & Partial<UpdateOptions>) | ({
valuesSql: Map<string, string> | Record<string, string>;
} & Partial<UpdateOptions>), options?: Partial<UpdateOptions>): Promise<UpdateResult>;
countRows(filter?: string): Promise<number>;
delete(predicate: string): Promise<DeleteResult>;
createIndex(column: string, options?: Partial<IndexOptions>): Promise<void>;
dropIndex(name: string): Promise<void>;
prewarmIndex(name: string): Promise<void>;
waitForIndex(indexNames: string[], timeoutSeconds: number): Promise<void>;
takeOffsets(offsets: number[]): TakeQuery;
takeRowIds(rowIds: number[]): TakeQuery;
query(): Query;
search(query: string | IntoVector | MultiVector | FullTextQuery, queryType?: string, ftsColumns?: string | string[]): VectorQuery | Query;
vectorSearch(vector: IntoVector | MultiVector): VectorQuery;
addColumns(newColumnTransforms: AddColumnsSql[]): Promise<AddColumnsResult>;
alterColumns(columnAlterations: ColumnAlteration[]): Promise<AlterColumnsResult>;
dropColumns(columnNames: string[]): Promise<DropColumnsResult>;
version(): Promise<number>;
checkout(version: number | string): Promise<void>;
checkoutLatest(): Promise<void>;
listVersions(): Promise<Version[]>;
restore(): Promise<void>;
tags(): Promise<Tags>;
optimize(options?: Partial<OptimizeOptions>): Promise<OptimizeStats>;
listIndices(): Promise<IndexConfig[]>;
toArrow(): Promise<ArrowTable>;
indexStats(name: string): Promise<IndexStatistics | undefined>;
stats(): Promise<TableStatistics>;
mergeInsert(on: string | string[]): MergeInsertBuilder;
/**
* Check if the table uses the new manifest path scheme.
*
* This function will return true if the table uses the V2 manifest
* path scheme.
*/
usesV2ManifestPaths(): Promise<boolean>;
/**
* Migrate the table to use the new manifest path scheme.
*
* This function will rename all V1 manifests to V2 manifest paths.
* These paths provide more efficient opening of datasets with many versions
* on object stores.
*
* This function is idempotent, and can be run multiple times without
* changing the state of the object store.
*
* However, it should not be run while other concurrent operations are happening.
* And it should also run until completion before resuming other operations.
*/
migrateManifestPathsV2(): Promise<void>;
}
/**
* A definition of a column alteration. The alteration changes the column at
* `path` to have the new name `name`, to be nullable if `nullable` is true,
* and to have the data type `data_type`. At least one of `rename` or `nullable`
* must be provided.
*/
export interface ColumnAlteration {
/**
* The path to the column to alter. This is a dot-separated path to the column.
* If it is a top-level column then it is just the name of the column. If it is
* a nested column then it is the path to the column, e.g. "a.b.c" for a column
* `c` nested inside a column `b` nested inside a column `a`.
*/
path: string;
/**
* The new name of the column. If not provided then the name will not be changed.
* This must be distinct from the names of all other columns in the table.
*/
rename?: string;
/**
* A new data type for the column. If not provided then the data type will not be changed.
* Changing data types is limited to casting to the same general type. For example, these
* changes are valid:
* * `int32` -> `int64` (integers)
* * `double` -> `float` (floats)
* * `string` -> `large_string` (strings)
* But these changes are not:
* * `int32` -> `double` (mix integers and floats)
* * `string` -> `int32` (mix strings and integers)
*/
dataType?: string | DataType;
/** Set the new nullability. Note that a nullable column cannot be made non-nullable. */
nullable?: boolean;
}

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extensions/memory-lancedb/node_modules/@lancedb/lancedb/dist/table.js generated vendored Normal file
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"use strict";
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
Object.defineProperty(exports, "__esModule", { value: true });
exports.LocalTable = exports.Table = void 0;
const arrow_1 = require("./arrow");
const registry_1 = require("./embedding/registry");
const merge_1 = require("./merge");
const query_1 = require("./query");
const sanitize_1 = require("./sanitize");
const util_1 = require("./util");
/**
* A Table is a collection of Records in a LanceDB Database.
*
* A Table object is expected to be long lived and reused for multiple operations.
* Table objects will cache a certain amount of index data in memory. This cache
* will be freed when the Table is garbage collected. To eagerly free the cache you
* can call the `close` method. Once the Table is closed, it cannot be used for any
* further operations.
*
* Tables are created using the methods {@link Connection#createTable}
* and {@link Connection#createEmptyTable}. Existing tables are opened
* using {@link Connection#openTable}.
*
* Closing a table is optional. It not closed, it will be closed when it is garbage
* collected.
*
* @hideconstructor
*/
class Table {
[Symbol.for("nodejs.util.inspect.custom")]() {
return this.display();
}
}
exports.Table = Table;
class LocalTable extends Table {
inner;
constructor(inner) {
super();
this.inner = inner;
}
get name() {
return this.inner.name;
}
isOpen() {
return this.inner.isOpen();
}
close() {
this.inner.close();
}
display() {
return this.inner.display();
}
async getEmbeddingFunctions() {
const schema = await this.schema();
const registry = (0, registry_1.getRegistry)();
return registry.parseFunctions(schema.metadata);
}
/** Get the schema of the table. */
async schema() {
const schemaBuf = await this.inner.schema();
const tbl = (0, arrow_1.tableFromIPC)(schemaBuf);
return tbl.schema;
}
async add(data, options) {
const mode = options?.mode ?? "append";
const schema = await this.schema();
const buffer = await (0, arrow_1.fromDataToBuffer)(data, undefined, schema);
return await this.inner.add(buffer, mode);
}
async update(optsOrUpdates, options) {
const isValues = "values" in optsOrUpdates && typeof optsOrUpdates.values !== "string";
const isValuesSql = "valuesSql" in optsOrUpdates &&
typeof optsOrUpdates.valuesSql !== "string";
const isMap = (obj) => {
return obj instanceof Map;
};
let predicate;
let columns;
switch (true) {
case isMap(optsOrUpdates):
columns = Array.from(optsOrUpdates.entries());
predicate = options?.where;
break;
case isValues && isMap(optsOrUpdates.values):
columns = Array.from(optsOrUpdates.values.entries()).map(([k, v]) => [
k,
(0, util_1.toSQL)(v),
]);
predicate = optsOrUpdates.where;
break;
case isValues && !isMap(optsOrUpdates.values):
columns = Object.entries(optsOrUpdates.values).map(([k, v]) => [
k,
(0, util_1.toSQL)(v),
]);
predicate = optsOrUpdates.where;
break;
case isValuesSql && isMap(optsOrUpdates.valuesSql):
columns = Array.from(optsOrUpdates.valuesSql.entries());
predicate = optsOrUpdates.where;
break;
case isValuesSql && !isMap(optsOrUpdates.valuesSql):
columns = Object.entries(optsOrUpdates.valuesSql).map(([k, v]) => [
k,
v,
]);
predicate = optsOrUpdates.where;
break;
default:
columns = Object.entries(optsOrUpdates);
predicate = options?.where;
}
return await this.inner.update(predicate, columns);
}
async countRows(filter) {
return await this.inner.countRows(filter);
}
async delete(predicate) {
return await this.inner.delete(predicate);
}
async createIndex(column, options) {
// Bit of a hack to get around the fact that TS has no package-scope.
// biome-ignore lint/suspicious/noExplicitAny: skip
const nativeIndex = options?.config?.inner;
await this.inner.createIndex(nativeIndex, column, options?.replace, options?.waitTimeoutSeconds, options?.name, options?.train);
}
async dropIndex(name) {
await this.inner.dropIndex(name);
}
async prewarmIndex(name) {
await this.inner.prewarmIndex(name);
}
async waitForIndex(indexNames, timeoutSeconds) {
await this.inner.waitForIndex(indexNames, timeoutSeconds);
}
takeOffsets(offsets) {
return new query_1.TakeQuery(this.inner.takeOffsets(offsets));
}
takeRowIds(rowIds) {
return new query_1.TakeQuery(this.inner.takeRowIds(rowIds));
}
query() {
return new query_1.Query(this.inner);
}
search(query, queryType = "auto", ftsColumns) {
if (typeof query !== "string" && !(0, query_1.instanceOfFullTextQuery)(query)) {
if (queryType === "fts") {
throw new Error("Cannot perform full text search on a vector query");
}
return this.vectorSearch(query);
}
// If the query is a string, we need to determine if it is a vector query or a full text search query
if (queryType === "fts") {
return this.query().fullTextSearch(query, {
columns: ftsColumns,
});
}
// The query type is auto or vector
// fall back to full text search if no embedding functions are defined and the query is a string
if (queryType === "auto" &&
((0, registry_1.getRegistry)().length() === 0 || (0, query_1.instanceOfFullTextQuery)(query))) {
return this.query().fullTextSearch(query, {
columns: ftsColumns,
});
}
const queryPromise = this.getEmbeddingFunctions().then(async (functions) => {
// TODO: Support multiple embedding functions
const embeddingFunc = functions
.values()
.next().value;
if (!embeddingFunc) {
return Promise.reject(new Error("No embedding functions are defined in the table"));
}
return await embeddingFunc.function.computeQueryEmbeddings(query);
});
return this.query().nearestTo(queryPromise);
}
vectorSearch(vector) {
if ((0, arrow_1.isMultiVector)(vector)) {
const query = this.query().nearestTo(vector[0]);
for (const v of vector.slice(1)) {
query.addQueryVector(v);
}
return query;
}
return this.query().nearestTo(vector);
}
// TODO: Support BatchUDF
async addColumns(newColumnTransforms) {
return await this.inner.addColumns(newColumnTransforms);
}
async alterColumns(columnAlterations) {
const processedAlterations = columnAlterations.map((alteration) => {
if (typeof alteration.dataType === "string") {
return {
...alteration,
dataType: JSON.stringify({ type: alteration.dataType }),
};
}
else if (alteration.dataType === undefined) {
return {
...alteration,
dataType: undefined,
};
}
else {
const dataType = (0, sanitize_1.sanitizeType)(alteration.dataType);
return {
...alteration,
dataType: JSON.stringify((0, arrow_1.dataTypeToJson)(dataType)),
};
}
});
return await this.inner.alterColumns(processedAlterations);
}
async dropColumns(columnNames) {
return await this.inner.dropColumns(columnNames);
}
async version() {
return await this.inner.version();
}
async checkout(version) {
if (typeof version === "string") {
return this.inner.checkoutTag(version);
}
return this.inner.checkout(version);
}
async checkoutLatest() {
await this.inner.checkoutLatest();
}
async listVersions() {
return (await this.inner.listVersions()).map((version) => ({
version: version.version,
timestamp: new Date(version.timestamp / 1000),
metadata: version.metadata,
}));
}
async restore() {
await this.inner.restore();
}
async tags() {
return await this.inner.tags();
}
async optimize(options) {
let cleanupOlderThanMs;
if (options?.cleanupOlderThan !== undefined &&
options?.cleanupOlderThan !== null) {
cleanupOlderThanMs =
new Date().getTime() - options.cleanupOlderThan.getTime();
}
return await this.inner.optimize(cleanupOlderThanMs, options?.deleteUnverified);
}
async listIndices() {
return await this.inner.listIndices();
}
async toArrow() {
return await this.query().toArrow();
}
async indexStats(name) {
const stats = await this.inner.indexStats(name);
if (stats === null) {
return undefined;
}
return stats;
}
async stats() {
return await this.inner.stats();
}
mergeInsert(on) {
on = Array.isArray(on) ? on : [on];
return new merge_1.MergeInsertBuilder(this.inner.mergeInsert(on), this.schema());
}
/**
* Check if the table uses the new manifest path scheme.
*
* This function will return true if the table uses the V2 manifest
* path scheme.
*/
async usesV2ManifestPaths() {
return await this.inner.usesV2ManifestPaths();
}
/**
* Migrate the table to use the new manifest path scheme.
*
* This function will rename all V1 manifests to V2 manifest paths.
* These paths provide more efficient opening of datasets with many versions
* on object stores.
*
* This function is idempotent, and can be run multiple times without
* changing the state of the object store.
*
* However, it should not be run while other concurrent operations are happening.
* And it should also run until completion before resuming other operations.
*/
async migrateManifestPathsV2() {
await this.inner.migrateManifestPathsV2();
}
}
exports.LocalTable = LocalTable;

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extensions/memory-lancedb/node_modules/@lancedb/lancedb/dist/util.d.ts generated vendored Normal file
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export type IntoSql = string | number | boolean | null | Date | ArrayBufferLike | Buffer | IntoSql[];
export declare function toSQL(value: IntoSql): string;
export declare function packBits(data: Array<number>): Array<number>;
export declare class TTLCache {
private readonly ttl;
private readonly cache;
/**
* @param ttl Time to live in milliseconds
*/
constructor(ttl: number);
get(key: string): any | undefined;
set(key: string, value: any): void;
delete(key: string): void;
}

77
extensions/memory-lancedb/node_modules/@lancedb/lancedb/dist/util.js generated vendored Normal file
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"use strict";
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
Object.defineProperty(exports, "__esModule", { value: true });
exports.TTLCache = void 0;
exports.toSQL = toSQL;
exports.packBits = packBits;
function toSQL(value) {
if (typeof value === "string") {
return `'${value.replace(/'/g, "''")}'`;
}
else if (typeof value === "number") {
return value.toString();
}
else if (typeof value === "boolean") {
return value ? "TRUE" : "FALSE";
}
else if (value === null) {
return "NULL";
}
else if (value instanceof Date) {
return `'${value.toISOString()}'`;
}
else if (Array.isArray(value)) {
return `[${value.map(toSQL).join(", ")}]`;
}
else if (Buffer.isBuffer(value)) {
return `X'${value.toString("hex")}'`;
}
else if (value instanceof ArrayBuffer) {
return `X'${Buffer.from(value).toString("hex")}'`;
}
else {
throw new Error(`Unsupported value type: ${typeof value} value: (${value})`);
}
}
function packBits(data) {
const packed = Array(data.length >> 3).fill(0);
for (let i = 0; i < data.length; i++) {
const byte = i >> 3;
const bit = i & 7;
packed[byte] |= data[i] << bit;
}
return packed;
}
class TTLCache {
ttl;
// biome-ignore lint/suspicious/noExplicitAny: <explanation>
cache;
/**
* @param ttl Time to live in milliseconds
*/
constructor(ttl) {
this.ttl = ttl;
this.cache = new Map();
}
// biome-ignore lint/suspicious/noExplicitAny: <explanation>
get(key) {
const entry = this.cache.get(key);
if (entry === undefined) {
return undefined;
}
if (entry.expires < Date.now()) {
this.cache.delete(key);
return undefined;
}
return entry.value;
}
// biome-ignore lint/suspicious/noExplicitAny: <explanation>
set(key, value) {
this.cache.set(key, { value, expires: Date.now() + this.ttl });
}
delete(key) {
this.cache.delete(key);
}
}
exports.TTLCache = TTLCache;

2
extensions/memory-lancedb/node_modules/@lancedb/lancedb/license_header.txt generated vendored Normal file
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// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors

21
extensions/memory-lancedb/node_modules/@lancedb/lancedb/node_modules/.bin/arrow2csv generated vendored Normal file
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#!/bin/sh
basedir=$(dirname "$(echo "$0" | sed -e 's,\\,/,g')")
case `uname` in
*CYGWIN*|*MINGW*|*MSYS*)
if command -v cygpath > /dev/null 2>&1; then
basedir=`cygpath -w "$basedir"`
fi
;;
esac
if [ -z "$NODE_PATH" ]; then
export NODE_PATH="/proc/cygdrive/d/workspace/moltbot/node_modules/.pnpm/apache-arrow@18.1.0/node_modules/apache-arrow/bin/node_modules:/proc/cygdrive/d/workspace/moltbot/node_modules/.pnpm/apache-arrow@18.1.0/node_modules/apache-arrow/node_modules:/proc/cygdrive/d/workspace/moltbot/node_modules/.pnpm/apache-arrow@18.1.0/node_modules:/proc/cygdrive/d/workspace/moltbot/node_modules/.pnpm/node_modules"
else
export NODE_PATH="/proc/cygdrive/d/workspace/moltbot/node_modules/.pnpm/apache-arrow@18.1.0/node_modules/apache-arrow/bin/node_modules:/proc/cygdrive/d/workspace/moltbot/node_modules/.pnpm/apache-arrow@18.1.0/node_modules/apache-arrow/node_modules:/proc/cygdrive/d/workspace/moltbot/node_modules/.pnpm/apache-arrow@18.1.0/node_modules:/proc/cygdrive/d/workspace/moltbot/node_modules/.pnpm/node_modules:$NODE_PATH"
fi
if [ -x "$basedir/node" ]; then
exec "$basedir/node" "$basedir/../../../../../../apache-arrow@18.1.0/node_modules/apache-arrow/bin/arrow2csv.js" "$@"
else
exec node "$basedir/../../../../../../apache-arrow@18.1.0/node_modules/apache-arrow/bin/arrow2csv.js" "$@"
fi

12
extensions/memory-lancedb/node_modules/@lancedb/lancedb/node_modules/.bin/arrow2csv.CMD generated vendored Normal file
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@SETLOCAL
@IF NOT DEFINED NODE_PATH (
@SET "NODE_PATH=D:\workspace\moltbot\node_modules\.pnpm\apache-arrow@18.1.0\node_modules\apache-arrow\bin\node_modules;D:\workspace\moltbot\node_modules\.pnpm\apache-arrow@18.1.0\node_modules\apache-arrow\node_modules;D:\workspace\moltbot\node_modules\.pnpm\apache-arrow@18.1.0\node_modules;D:\workspace\moltbot\node_modules\.pnpm\node_modules"
) ELSE (
@SET "NODE_PATH=D:\workspace\moltbot\node_modules\.pnpm\apache-arrow@18.1.0\node_modules\apache-arrow\bin\node_modules;D:\workspace\moltbot\node_modules\.pnpm\apache-arrow@18.1.0\node_modules\apache-arrow\node_modules;D:\workspace\moltbot\node_modules\.pnpm\apache-arrow@18.1.0\node_modules;D:\workspace\moltbot\node_modules\.pnpm\node_modules;%NODE_PATH%"
)
@IF EXIST "%~dp0\node.exe" (
"%~dp0\node.exe" "%~dp0\..\..\..\..\..\..\apache-arrow@18.1.0\node_modules\apache-arrow\bin\arrow2csv.js" %*
) ELSE (
@SET PATHEXT=%PATHEXT:;.JS;=;%
node "%~dp0\..\..\..\..\..\..\apache-arrow@18.1.0\node_modules\apache-arrow\bin\arrow2csv.js" %*
)

41
extensions/memory-lancedb/node_modules/@lancedb/lancedb/node_modules/.bin/arrow2csv.ps1 generated vendored Normal file
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#!/usr/bin/env pwsh
$basedir=Split-Path $MyInvocation.MyCommand.Definition -Parent
$exe=""
$pathsep=":"
$env_node_path=$env:NODE_PATH
$new_node_path="D:\workspace\moltbot\node_modules\.pnpm\apache-arrow@18.1.0\node_modules\apache-arrow\bin\node_modules;D:\workspace\moltbot\node_modules\.pnpm\apache-arrow@18.1.0\node_modules\apache-arrow\node_modules;D:\workspace\moltbot\node_modules\.pnpm\apache-arrow@18.1.0\node_modules;D:\workspace\moltbot\node_modules\.pnpm\node_modules"
if ($PSVersionTable.PSVersion -lt "6.0" -or $IsWindows) {
# Fix case when both the Windows and Linux builds of Node
# are installed in the same directory
$exe=".exe"
$pathsep=";"
} else {
$new_node_path="/proc/cygdrive/d/workspace/moltbot/node_modules/.pnpm/apache-arrow@18.1.0/node_modules/apache-arrow/bin/node_modules:/proc/cygdrive/d/workspace/moltbot/node_modules/.pnpm/apache-arrow@18.1.0/node_modules/apache-arrow/node_modules:/proc/cygdrive/d/workspace/moltbot/node_modules/.pnpm/apache-arrow@18.1.0/node_modules:/proc/cygdrive/d/workspace/moltbot/node_modules/.pnpm/node_modules"
}
if ([string]::IsNullOrEmpty($env_node_path)) {
$env:NODE_PATH=$new_node_path
} else {
$env:NODE_PATH="$new_node_path$pathsep$env_node_path"
}
$ret=0
if (Test-Path "$basedir/node$exe") {
# Support pipeline input
if ($MyInvocation.ExpectingInput) {
$input | & "$basedir/node$exe" "$basedir/../../../../../../apache-arrow@18.1.0/node_modules/apache-arrow/bin/arrow2csv.js" $args
} else {
& "$basedir/node$exe" "$basedir/../../../../../../apache-arrow@18.1.0/node_modules/apache-arrow/bin/arrow2csv.js" $args
}
$ret=$LASTEXITCODE
} else {
# Support pipeline input
if ($MyInvocation.ExpectingInput) {
$input | & "node$exe" "$basedir/../../../../../../apache-arrow@18.1.0/node_modules/apache-arrow/bin/arrow2csv.js" $args
} else {
& "node$exe" "$basedir/../../../../../../apache-arrow@18.1.0/node_modules/apache-arrow/bin/arrow2csv.js" $args
}
$ret=$LASTEXITCODE
}
$env:NODE_PATH=$env_node_path
exit $ret

117
extensions/memory-lancedb/node_modules/@lancedb/lancedb/package.json generated vendored Normal file
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{
"name": "@lancedb/lancedb",
"description": "LanceDB: A serverless, low-latency vector database for AI applications",
"keywords": [
"database",
"lance",
"lancedb",
"search",
"vector",
"vector database",
"ann"
],
"private": false,
"version": "0.23.0",
"main": "dist/index.js",
"exports": {
".": "./dist/index.js",
"./embedding": "./dist/embedding/index.js",
"./embedding/openai": "./dist/embedding/openai.js",
"./embedding/transformers": "./dist/embedding/transformers.js"
},
"types": "dist/index.d.ts",
"napi": {
"name": "lancedb",
"triples": {
"defaults": false,
"additional": [
"x86_64-apple-darwin",
"aarch64-apple-darwin",
"x86_64-unknown-linux-gnu",
"aarch64-unknown-linux-gnu",
"x86_64-unknown-linux-musl",
"aarch64-unknown-linux-musl",
"x86_64-pc-windows-msvc",
"aarch64-pc-windows-msvc"
]
}
},
"license": "Apache-2.0",
"devDependencies": {
"@aws-sdk/client-dynamodb": "^3.33.0",
"@aws-sdk/client-kms": "^3.33.0",
"@aws-sdk/client-s3": "^3.33.0",
"@biomejs/biome": "^1.7.3",
"@jest/globals": "^29.7.0",
"@napi-rs/cli": "^2.18.3",
"@types/axios": "^0.14.0",
"@types/jest": "^29.1.2",
"@types/node": "^22.7.4",
"@types/tmp": "^0.2.6",
"apache-arrow-15": "npm:apache-arrow@15.0.0",
"apache-arrow-16": "npm:apache-arrow@16.0.0",
"apache-arrow-17": "npm:apache-arrow@17.0.0",
"apache-arrow-18": "npm:apache-arrow@18.0.0",
"eslint": "^8.57.0",
"jest": "^29.7.0",
"shx": "^0.3.4",
"tmp": "^0.2.3",
"ts-jest": "^29.1.2",
"typedoc": "^0.26.4",
"typedoc-plugin-markdown": "^4.2.1",
"typescript": "^5.5.4",
"typescript-eslint": "^7.1.0"
},
"ava": {
"timeout": "3m"
},
"engines": {
"node": ">= 18"
},
"cpu": [
"x64",
"arm64"
],
"os": [
"darwin",
"linux",
"win32"
],
"scripts": {
"artifacts": "napi artifacts",
"build:debug": "napi build --platform --no-const-enum --dts ../lancedb/native.d.ts --js ../lancedb/native.js lancedb",
"postbuild:debug": "shx mkdir -p dist && shx cp lancedb/*.node dist/",
"build:release": "napi build --platform --no-const-enum --release --dts ../lancedb/native.d.ts --js ../lancedb/native.js dist/",
"postbuild:release": "shx mkdir -p dist && shx cp lancedb/*.node dist/",
"build": "npm run build:debug && npm run tsc",
"build-release": "npm run build:release && npm run tsc",
"tsc": "tsc -b",
"posttsc": "shx cp lancedb/native.d.ts dist/native.d.ts",
"lint-ci": "biome ci .",
"docs": "typedoc --plugin typedoc-plugin-markdown --treatWarningsAsErrors --out ../docs/src/js lancedb/index.ts",
"postdocs": "node typedoc_post_process.js",
"lint": "biome check . && biome format .",
"lint-fix": "biome check --write . && biome format --write .",
"prepublishOnly": "napi prepublish -t npm",
"test": "jest --verbose",
"integration": "S3_TEST=1 npm run test",
"universal": "napi universal",
"version": "napi version"
},
"dependencies": {
"reflect-metadata": "^0.2.2"
},
"optionalDependencies": {
"@lancedb/lancedb-darwin-x64": "0.23.0",
"@lancedb/lancedb-darwin-arm64": "0.23.0",
"@lancedb/lancedb-linux-x64-gnu": "0.23.0",
"@lancedb/lancedb-linux-arm64-gnu": "0.23.0",
"@lancedb/lancedb-linux-x64-musl": "0.23.0",
"@lancedb/lancedb-linux-arm64-musl": "0.23.0",
"@lancedb/lancedb-win32-x64-msvc": "0.23.0",
"@lancedb/lancedb-win32-arm64-msvc": "0.23.0"
},
"peerDependencies": {
"apache-arrow": ">=15.0.0 <=18.1.0"
}
}

55
extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/compiler/compiler.d.ts generated vendored Normal file
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@ -0,0 +1,55 @@
import { ValueErrorIterator } from '../errors/index';
import { TypeBoxError } from '../type/error/index';
import type { TSchema } from '../type/schema/index';
import type { Static, StaticDecode, StaticEncode } from '../type/static/index';
export type CheckFunction = (value: unknown) => boolean;
export declare class TypeCheck<T extends TSchema> {
private readonly schema;
private readonly references;
private readonly checkFunc;
private readonly code;
private readonly hasTransform;
constructor(schema: T, references: TSchema[], checkFunc: CheckFunction, code: string);
/** Returns the generated assertion code used to validate this type. */
Code(): string;
/** Returns the schema type used to validate */
Schema(): T;
/** Returns reference types used to validate */
References(): TSchema[];
/** Returns an iterator for each error in this value. */
Errors(value: unknown): ValueErrorIterator;
/** Returns true if the value matches the compiled type. */
Check(value: unknown): value is Static<T>;
/** Decodes a value or throws if error */
Decode<Static = StaticDecode<T>, Result extends Static = Static>(value: unknown): Result;
/** Encodes a value or throws if error */
Encode<Static = StaticEncode<T>, Result extends Static = Static>(value: unknown): Result;
}
export declare class TypeCompilerUnknownTypeError extends TypeBoxError {
readonly schema: TSchema;
constructor(schema: TSchema);
}
export declare class TypeCompilerTypeGuardError extends TypeBoxError {
readonly schema: TSchema;
constructor(schema: TSchema);
}
export declare namespace Policy {
function IsExactOptionalProperty(value: string, key: string, expression: string): string;
function IsObjectLike(value: string): string;
function IsRecordLike(value: string): string;
function IsNumberLike(value: string): string;
function IsVoidLike(value: string): string;
}
export type TypeCompilerLanguageOption = 'typescript' | 'javascript';
export interface TypeCompilerCodegenOptions {
language?: TypeCompilerLanguageOption;
}
/** Compiles Types for Runtime Type Checking */
export declare namespace TypeCompiler {
/** Generates the code used to assert this type and returns it as a string */
function Code<T extends TSchema>(schema: T, references: TSchema[], options?: TypeCompilerCodegenOptions): string;
/** Generates the code used to assert this type and returns it as a string */
function Code<T extends TSchema>(schema: T, options?: TypeCompilerCodegenOptions): string;
/** Compiles a TypeBox type for optimal runtime type checking. Types must be valid TypeBox types of TSchema */
function Compile<T extends TSchema>(schema: T, references?: TSchema[]): TypeCheck<T>;
}

669
extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/compiler/compiler.js generated vendored Normal file
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@ -0,0 +1,669 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.TypeCompiler = exports.Policy = exports.TypeCompilerTypeGuardError = exports.TypeCompilerUnknownTypeError = exports.TypeCheck = void 0;
const index_1 = require("../value/transform/index");
const index_2 = require("../errors/index");
const index_3 = require("../system/index");
const index_4 = require("../type/error/index");
const index_5 = require("../value/deref/index");
const index_6 = require("../value/hash/index");
const index_7 = require("../type/symbols/index");
const index_8 = require("../type/registry/index");
const index_9 = require("../type/keyof/index");
const extends_undefined_1 = require("../type/extends/extends-undefined");
const index_10 = require("../type/never/index");
const index_11 = require("../type/ref/index");
// ------------------------------------------------------------------
// ValueGuard
// ------------------------------------------------------------------
const index_12 = require("../value/guard/index");
// ------------------------------------------------------------------
// TypeGuard
// ------------------------------------------------------------------
const type_1 = require("../type/guard/type");
// ------------------------------------------------------------------
// TypeCheck
// ------------------------------------------------------------------
class TypeCheck {
constructor(schema, references, checkFunc, code) {
this.schema = schema;
this.references = references;
this.checkFunc = checkFunc;
this.code = code;
this.hasTransform = (0, index_1.HasTransform)(schema, references);
}
/** Returns the generated assertion code used to validate this type. */
Code() {
return this.code;
}
/** Returns the schema type used to validate */
Schema() {
return this.schema;
}
/** Returns reference types used to validate */
References() {
return this.references;
}
/** Returns an iterator for each error in this value. */
Errors(value) {
return (0, index_2.Errors)(this.schema, this.references, value);
}
/** Returns true if the value matches the compiled type. */
Check(value) {
return this.checkFunc(value);
}
/** Decodes a value or throws if error */
Decode(value) {
if (!this.checkFunc(value))
throw new index_1.TransformDecodeCheckError(this.schema, value, this.Errors(value).First());
return (this.hasTransform ? (0, index_1.TransformDecode)(this.schema, this.references, value) : value);
}
/** Encodes a value or throws if error */
Encode(value) {
const encoded = this.hasTransform ? (0, index_1.TransformEncode)(this.schema, this.references, value) : value;
if (!this.checkFunc(encoded))
throw new index_1.TransformEncodeCheckError(this.schema, value, this.Errors(value).First());
return encoded;
}
}
exports.TypeCheck = TypeCheck;
// ------------------------------------------------------------------
// Character
// ------------------------------------------------------------------
var Character;
(function (Character) {
function DollarSign(code) {
return code === 36;
}
Character.DollarSign = DollarSign;
function IsUnderscore(code) {
return code === 95;
}
Character.IsUnderscore = IsUnderscore;
function IsAlpha(code) {
return (code >= 65 && code <= 90) || (code >= 97 && code <= 122);
}
Character.IsAlpha = IsAlpha;
function IsNumeric(code) {
return code >= 48 && code <= 57;
}
Character.IsNumeric = IsNumeric;
})(Character || (Character = {}));
// ------------------------------------------------------------------
// MemberExpression
// ------------------------------------------------------------------
var MemberExpression;
(function (MemberExpression) {
function IsFirstCharacterNumeric(value) {
if (value.length === 0)
return false;
return Character.IsNumeric(value.charCodeAt(0));
}
function IsAccessor(value) {
if (IsFirstCharacterNumeric(value))
return false;
for (let i = 0; i < value.length; i++) {
const code = value.charCodeAt(i);
const check = Character.IsAlpha(code) || Character.IsNumeric(code) || Character.DollarSign(code) || Character.IsUnderscore(code);
if (!check)
return false;
}
return true;
}
function EscapeHyphen(key) {
return key.replace(/'/g, "\\'");
}
function Encode(object, key) {
return IsAccessor(key) ? `${object}.${key}` : `${object}['${EscapeHyphen(key)}']`;
}
MemberExpression.Encode = Encode;
})(MemberExpression || (MemberExpression = {}));
// ------------------------------------------------------------------
// Identifier
// ------------------------------------------------------------------
var Identifier;
(function (Identifier) {
function Encode($id) {
const buffer = [];
for (let i = 0; i < $id.length; i++) {
const code = $id.charCodeAt(i);
if (Character.IsNumeric(code) || Character.IsAlpha(code)) {
buffer.push($id.charAt(i));
}
else {
buffer.push(`_${code}_`);
}
}
return buffer.join('').replace(/__/g, '_');
}
Identifier.Encode = Encode;
})(Identifier || (Identifier = {}));
// ------------------------------------------------------------------
// LiteralString
// ------------------------------------------------------------------
var LiteralString;
(function (LiteralString) {
function Escape(content) {
return content.replace(/'/g, "\\'");
}
LiteralString.Escape = Escape;
})(LiteralString || (LiteralString = {}));
// ------------------------------------------------------------------
// Errors
// ------------------------------------------------------------------
class TypeCompilerUnknownTypeError extends index_4.TypeBoxError {
constructor(schema) {
super('Unknown type');
this.schema = schema;
}
}
exports.TypeCompilerUnknownTypeError = TypeCompilerUnknownTypeError;
class TypeCompilerTypeGuardError extends index_4.TypeBoxError {
constructor(schema) {
super('Preflight validation check failed to guard for the given schema');
this.schema = schema;
}
}
exports.TypeCompilerTypeGuardError = TypeCompilerTypeGuardError;
// ------------------------------------------------------------------
// Policy
// ------------------------------------------------------------------
var Policy;
(function (Policy) {
function IsExactOptionalProperty(value, key, expression) {
return index_3.TypeSystemPolicy.ExactOptionalPropertyTypes ? `('${key}' in ${value} ? ${expression} : true)` : `(${MemberExpression.Encode(value, key)} !== undefined ? ${expression} : true)`;
}
Policy.IsExactOptionalProperty = IsExactOptionalProperty;
function IsObjectLike(value) {
return !index_3.TypeSystemPolicy.AllowArrayObject ? `(typeof ${value} === 'object' && ${value} !== null && !Array.isArray(${value}))` : `(typeof ${value} === 'object' && ${value} !== null)`;
}
Policy.IsObjectLike = IsObjectLike;
function IsRecordLike(value) {
return !index_3.TypeSystemPolicy.AllowArrayObject
? `(typeof ${value} === 'object' && ${value} !== null && !Array.isArray(${value}) && !(${value} instanceof Date) && !(${value} instanceof Uint8Array))`
: `(typeof ${value} === 'object' && ${value} !== null && !(${value} instanceof Date) && !(${value} instanceof Uint8Array))`;
}
Policy.IsRecordLike = IsRecordLike;
function IsNumberLike(value) {
return index_3.TypeSystemPolicy.AllowNaN ? `typeof ${value} === 'number'` : `Number.isFinite(${value})`;
}
Policy.IsNumberLike = IsNumberLike;
function IsVoidLike(value) {
return index_3.TypeSystemPolicy.AllowNullVoid ? `(${value} === undefined || ${value} === null)` : `${value} === undefined`;
}
Policy.IsVoidLike = IsVoidLike;
})(Policy || (exports.Policy = Policy = {}));
/** Compiles Types for Runtime Type Checking */
var TypeCompiler;
(function (TypeCompiler) {
// ----------------------------------------------------------------
// Guards
// ----------------------------------------------------------------
function IsAnyOrUnknown(schema) {
return schema[index_7.Kind] === 'Any' || schema[index_7.Kind] === 'Unknown';
}
// ----------------------------------------------------------------
// Types
// ----------------------------------------------------------------
function* FromAny(schema, references, value) {
yield 'true';
}
function* FromArgument(schema, references, value) {
yield 'true';
}
function* FromArray(schema, references, value) {
yield `Array.isArray(${value})`;
const [parameter, accumulator] = [CreateParameter('value', 'any'), CreateParameter('acc', 'number')];
if ((0, index_12.IsNumber)(schema.maxItems))
yield `${value}.length <= ${schema.maxItems}`;
if ((0, index_12.IsNumber)(schema.minItems))
yield `${value}.length >= ${schema.minItems}`;
const elementExpression = CreateExpression(schema.items, references, 'value');
yield `${value}.every((${parameter}) => ${elementExpression})`;
if ((0, type_1.IsSchema)(schema.contains) || (0, index_12.IsNumber)(schema.minContains) || (0, index_12.IsNumber)(schema.maxContains)) {
const containsSchema = (0, type_1.IsSchema)(schema.contains) ? schema.contains : (0, index_10.Never)();
const checkExpression = CreateExpression(containsSchema, references, 'value');
const checkMinContains = (0, index_12.IsNumber)(schema.minContains) ? [`(count >= ${schema.minContains})`] : [];
const checkMaxContains = (0, index_12.IsNumber)(schema.maxContains) ? [`(count <= ${schema.maxContains})`] : [];
const checkCount = `const count = value.reduce((${accumulator}, ${parameter}) => ${checkExpression} ? acc + 1 : acc, 0)`;
const check = [`(count > 0)`, ...checkMinContains, ...checkMaxContains].join(' && ');
yield `((${parameter}) => { ${checkCount}; return ${check}})(${value})`;
}
if (schema.uniqueItems === true) {
const check = `const hashed = hash(element); if(set.has(hashed)) { return false } else { set.add(hashed) } } return true`;
const block = `const set = new Set(); for(const element of value) { ${check} }`;
yield `((${parameter}) => { ${block} )(${value})`;
}
}
function* FromAsyncIterator(schema, references, value) {
yield `(typeof value === 'object' && Symbol.asyncIterator in ${value})`;
}
function* FromBigInt(schema, references, value) {
yield `(typeof ${value} === 'bigint')`;
if ((0, index_12.IsBigInt)(schema.exclusiveMaximum))
yield `${value} < BigInt(${schema.exclusiveMaximum})`;
if ((0, index_12.IsBigInt)(schema.exclusiveMinimum))
yield `${value} > BigInt(${schema.exclusiveMinimum})`;
if ((0, index_12.IsBigInt)(schema.maximum))
yield `${value} <= BigInt(${schema.maximum})`;
if ((0, index_12.IsBigInt)(schema.minimum))
yield `${value} >= BigInt(${schema.minimum})`;
if ((0, index_12.IsBigInt)(schema.multipleOf))
yield `(${value} % BigInt(${schema.multipleOf})) === 0`;
}
function* FromBoolean(schema, references, value) {
yield `(typeof ${value} === 'boolean')`;
}
function* FromConstructor(schema, references, value) {
yield* Visit(schema.returns, references, `${value}.prototype`);
}
function* FromDate(schema, references, value) {
yield `(${value} instanceof Date) && Number.isFinite(${value}.getTime())`;
if ((0, index_12.IsNumber)(schema.exclusiveMaximumTimestamp))
yield `${value}.getTime() < ${schema.exclusiveMaximumTimestamp}`;
if ((0, index_12.IsNumber)(schema.exclusiveMinimumTimestamp))
yield `${value}.getTime() > ${schema.exclusiveMinimumTimestamp}`;
if ((0, index_12.IsNumber)(schema.maximumTimestamp))
yield `${value}.getTime() <= ${schema.maximumTimestamp}`;
if ((0, index_12.IsNumber)(schema.minimumTimestamp))
yield `${value}.getTime() >= ${schema.minimumTimestamp}`;
if ((0, index_12.IsNumber)(schema.multipleOfTimestamp))
yield `(${value}.getTime() % ${schema.multipleOfTimestamp}) === 0`;
}
function* FromFunction(schema, references, value) {
yield `(typeof ${value} === 'function')`;
}
function* FromImport(schema, references, value) {
const members = globalThis.Object.getOwnPropertyNames(schema.$defs).reduce((result, key) => {
return [...result, schema.$defs[key]];
}, []);
yield* Visit((0, index_11.Ref)(schema.$ref), [...references, ...members], value);
}
function* FromInteger(schema, references, value) {
yield `Number.isInteger(${value})`;
if ((0, index_12.IsNumber)(schema.exclusiveMaximum))
yield `${value} < ${schema.exclusiveMaximum}`;
if ((0, index_12.IsNumber)(schema.exclusiveMinimum))
yield `${value} > ${schema.exclusiveMinimum}`;
if ((0, index_12.IsNumber)(schema.maximum))
yield `${value} <= ${schema.maximum}`;
if ((0, index_12.IsNumber)(schema.minimum))
yield `${value} >= ${schema.minimum}`;
if ((0, index_12.IsNumber)(schema.multipleOf))
yield `(${value} % ${schema.multipleOf}) === 0`;
}
function* FromIntersect(schema, references, value) {
const check1 = schema.allOf.map((schema) => CreateExpression(schema, references, value)).join(' && ');
if (schema.unevaluatedProperties === false) {
const keyCheck = CreateVariable(`${new RegExp((0, index_9.KeyOfPattern)(schema))};`);
const check2 = `Object.getOwnPropertyNames(${value}).every(key => ${keyCheck}.test(key))`;
yield `(${check1} && ${check2})`;
}
else if ((0, type_1.IsSchema)(schema.unevaluatedProperties)) {
const keyCheck = CreateVariable(`${new RegExp((0, index_9.KeyOfPattern)(schema))};`);
const check2 = `Object.getOwnPropertyNames(${value}).every(key => ${keyCheck}.test(key) || ${CreateExpression(schema.unevaluatedProperties, references, `${value}[key]`)})`;
yield `(${check1} && ${check2})`;
}
else {
yield `(${check1})`;
}
}
function* FromIterator(schema, references, value) {
yield `(typeof value === 'object' && Symbol.iterator in ${value})`;
}
function* FromLiteral(schema, references, value) {
if (typeof schema.const === 'number' || typeof schema.const === 'boolean') {
yield `(${value} === ${schema.const})`;
}
else {
yield `(${value} === '${LiteralString.Escape(schema.const)}')`;
}
}
function* FromNever(schema, references, value) {
yield `false`;
}
function* FromNot(schema, references, value) {
const expression = CreateExpression(schema.not, references, value);
yield `(!${expression})`;
}
function* FromNull(schema, references, value) {
yield `(${value} === null)`;
}
function* FromNumber(schema, references, value) {
yield Policy.IsNumberLike(value);
if ((0, index_12.IsNumber)(schema.exclusiveMaximum))
yield `${value} < ${schema.exclusiveMaximum}`;
if ((0, index_12.IsNumber)(schema.exclusiveMinimum))
yield `${value} > ${schema.exclusiveMinimum}`;
if ((0, index_12.IsNumber)(schema.maximum))
yield `${value} <= ${schema.maximum}`;
if ((0, index_12.IsNumber)(schema.minimum))
yield `${value} >= ${schema.minimum}`;
if ((0, index_12.IsNumber)(schema.multipleOf))
yield `(${value} % ${schema.multipleOf}) === 0`;
}
function* FromObject(schema, references, value) {
yield Policy.IsObjectLike(value);
if ((0, index_12.IsNumber)(schema.minProperties))
yield `Object.getOwnPropertyNames(${value}).length >= ${schema.minProperties}`;
if ((0, index_12.IsNumber)(schema.maxProperties))
yield `Object.getOwnPropertyNames(${value}).length <= ${schema.maxProperties}`;
const knownKeys = Object.getOwnPropertyNames(schema.properties);
for (const knownKey of knownKeys) {
const memberExpression = MemberExpression.Encode(value, knownKey);
const property = schema.properties[knownKey];
if (schema.required && schema.required.includes(knownKey)) {
yield* Visit(property, references, memberExpression);
if ((0, extends_undefined_1.ExtendsUndefinedCheck)(property) || IsAnyOrUnknown(property))
yield `('${knownKey}' in ${value})`;
}
else {
const expression = CreateExpression(property, references, memberExpression);
yield Policy.IsExactOptionalProperty(value, knownKey, expression);
}
}
if (schema.additionalProperties === false) {
if (schema.required && schema.required.length === knownKeys.length) {
yield `Object.getOwnPropertyNames(${value}).length === ${knownKeys.length}`;
}
else {
const keys = `[${knownKeys.map((key) => `'${key}'`).join(', ')}]`;
yield `Object.getOwnPropertyNames(${value}).every(key => ${keys}.includes(key))`;
}
}
if (typeof schema.additionalProperties === 'object') {
const expression = CreateExpression(schema.additionalProperties, references, `${value}[key]`);
const keys = `[${knownKeys.map((key) => `'${key}'`).join(', ')}]`;
yield `(Object.getOwnPropertyNames(${value}).every(key => ${keys}.includes(key) || ${expression}))`;
}
}
function* FromPromise(schema, references, value) {
yield `${value} instanceof Promise`;
}
function* FromRecord(schema, references, value) {
yield Policy.IsRecordLike(value);
if ((0, index_12.IsNumber)(schema.minProperties))
yield `Object.getOwnPropertyNames(${value}).length >= ${schema.minProperties}`;
if ((0, index_12.IsNumber)(schema.maxProperties))
yield `Object.getOwnPropertyNames(${value}).length <= ${schema.maxProperties}`;
const [patternKey, patternSchema] = Object.entries(schema.patternProperties)[0];
const variable = CreateVariable(`${new RegExp(patternKey)}`);
const check1 = CreateExpression(patternSchema, references, 'value');
const check2 = (0, type_1.IsSchema)(schema.additionalProperties) ? CreateExpression(schema.additionalProperties, references, value) : schema.additionalProperties === false ? 'false' : 'true';
const expression = `(${variable}.test(key) ? ${check1} : ${check2})`;
yield `(Object.entries(${value}).every(([key, value]) => ${expression}))`;
}
function* FromRef(schema, references, value) {
const target = (0, index_5.Deref)(schema, references);
// Reference: If we have seen this reference before we can just yield and return the function call.
// If this isn't the case we defer to visit to generate and set the function for subsequent passes.
if (state.functions.has(schema.$ref))
return yield `${CreateFunctionName(schema.$ref)}(${value})`;
yield* Visit(target, references, value);
}
function* FromRegExp(schema, references, value) {
const variable = CreateVariable(`${new RegExp(schema.source, schema.flags)};`);
yield `(typeof ${value} === 'string')`;
if ((0, index_12.IsNumber)(schema.maxLength))
yield `${value}.length <= ${schema.maxLength}`;
if ((0, index_12.IsNumber)(schema.minLength))
yield `${value}.length >= ${schema.minLength}`;
yield `${variable}.test(${value})`;
}
function* FromString(schema, references, value) {
yield `(typeof ${value} === 'string')`;
if ((0, index_12.IsNumber)(schema.maxLength))
yield `${value}.length <= ${schema.maxLength}`;
if ((0, index_12.IsNumber)(schema.minLength))
yield `${value}.length >= ${schema.minLength}`;
if (schema.pattern !== undefined) {
const variable = CreateVariable(`${new RegExp(schema.pattern)};`);
yield `${variable}.test(${value})`;
}
if (schema.format !== undefined) {
yield `format('${schema.format}', ${value})`;
}
}
function* FromSymbol(schema, references, value) {
yield `(typeof ${value} === 'symbol')`;
}
function* FromTemplateLiteral(schema, references, value) {
yield `(typeof ${value} === 'string')`;
const variable = CreateVariable(`${new RegExp(schema.pattern)};`);
yield `${variable}.test(${value})`;
}
function* FromThis(schema, references, value) {
// Note: This types are assured to be hoisted prior to this call. Just yield the function.
yield `${CreateFunctionName(schema.$ref)}(${value})`;
}
function* FromTuple(schema, references, value) {
yield `Array.isArray(${value})`;
if (schema.items === undefined)
return yield `${value}.length === 0`;
yield `(${value}.length === ${schema.maxItems})`;
for (let i = 0; i < schema.items.length; i++) {
const expression = CreateExpression(schema.items[i], references, `${value}[${i}]`);
yield `${expression}`;
}
}
function* FromUndefined(schema, references, value) {
yield `${value} === undefined`;
}
function* FromUnion(schema, references, value) {
const expressions = schema.anyOf.map((schema) => CreateExpression(schema, references, value));
yield `(${expressions.join(' || ')})`;
}
function* FromUint8Array(schema, references, value) {
yield `${value} instanceof Uint8Array`;
if ((0, index_12.IsNumber)(schema.maxByteLength))
yield `(${value}.length <= ${schema.maxByteLength})`;
if ((0, index_12.IsNumber)(schema.minByteLength))
yield `(${value}.length >= ${schema.minByteLength})`;
}
function* FromUnknown(schema, references, value) {
yield 'true';
}
function* FromVoid(schema, references, value) {
yield Policy.IsVoidLike(value);
}
function* FromKind(schema, references, value) {
const instance = state.instances.size;
state.instances.set(instance, schema);
yield `kind('${schema[index_7.Kind]}', ${instance}, ${value})`;
}
function* Visit(schema, references, value, useHoisting = true) {
const references_ = (0, index_12.IsString)(schema.$id) ? [...references, schema] : references;
const schema_ = schema;
// --------------------------------------------------------------
// Hoisting
// --------------------------------------------------------------
if (useHoisting && (0, index_12.IsString)(schema.$id)) {
const functionName = CreateFunctionName(schema.$id);
if (state.functions.has(functionName)) {
return yield `${functionName}(${value})`;
}
else {
// Note: In the case of cyclic types, we need to create a 'functions' record
// to prevent infinitely re-visiting the CreateFunction. Subsequent attempts
// to visit will be caught by the above condition.
state.functions.set(functionName, '<deferred>');
const functionCode = CreateFunction(functionName, schema, references, 'value', false);
state.functions.set(functionName, functionCode);
return yield `${functionName}(${value})`;
}
}
switch (schema_[index_7.Kind]) {
case 'Any':
return yield* FromAny(schema_, references_, value);
case 'Argument':
return yield* FromArgument(schema_, references_, value);
case 'Array':
return yield* FromArray(schema_, references_, value);
case 'AsyncIterator':
return yield* FromAsyncIterator(schema_, references_, value);
case 'BigInt':
return yield* FromBigInt(schema_, references_, value);
case 'Boolean':
return yield* FromBoolean(schema_, references_, value);
case 'Constructor':
return yield* FromConstructor(schema_, references_, value);
case 'Date':
return yield* FromDate(schema_, references_, value);
case 'Function':
return yield* FromFunction(schema_, references_, value);
case 'Import':
return yield* FromImport(schema_, references_, value);
case 'Integer':
return yield* FromInteger(schema_, references_, value);
case 'Intersect':
return yield* FromIntersect(schema_, references_, value);
case 'Iterator':
return yield* FromIterator(schema_, references_, value);
case 'Literal':
return yield* FromLiteral(schema_, references_, value);
case 'Never':
return yield* FromNever(schema_, references_, value);
case 'Not':
return yield* FromNot(schema_, references_, value);
case 'Null':
return yield* FromNull(schema_, references_, value);
case 'Number':
return yield* FromNumber(schema_, references_, value);
case 'Object':
return yield* FromObject(schema_, references_, value);
case 'Promise':
return yield* FromPromise(schema_, references_, value);
case 'Record':
return yield* FromRecord(schema_, references_, value);
case 'Ref':
return yield* FromRef(schema_, references_, value);
case 'RegExp':
return yield* FromRegExp(schema_, references_, value);
case 'String':
return yield* FromString(schema_, references_, value);
case 'Symbol':
return yield* FromSymbol(schema_, references_, value);
case 'TemplateLiteral':
return yield* FromTemplateLiteral(schema_, references_, value);
case 'This':
return yield* FromThis(schema_, references_, value);
case 'Tuple':
return yield* FromTuple(schema_, references_, value);
case 'Undefined':
return yield* FromUndefined(schema_, references_, value);
case 'Union':
return yield* FromUnion(schema_, references_, value);
case 'Uint8Array':
return yield* FromUint8Array(schema_, references_, value);
case 'Unknown':
return yield* FromUnknown(schema_, references_, value);
case 'Void':
return yield* FromVoid(schema_, references_, value);
default:
if (!index_8.TypeRegistry.Has(schema_[index_7.Kind]))
throw new TypeCompilerUnknownTypeError(schema);
return yield* FromKind(schema_, references_, value);
}
}
// ----------------------------------------------------------------
// Compiler State
// ----------------------------------------------------------------
// prettier-ignore
const state = {
language: 'javascript', // target language
functions: new Map(), // local functions
variables: new Map(), // local variables
instances: new Map() // exterior kind instances
};
// ----------------------------------------------------------------
// Compiler Factory
// ----------------------------------------------------------------
function CreateExpression(schema, references, value, useHoisting = true) {
return `(${[...Visit(schema, references, value, useHoisting)].join(' && ')})`;
}
function CreateFunctionName($id) {
return `check_${Identifier.Encode($id)}`;
}
function CreateVariable(expression) {
const variableName = `local_${state.variables.size}`;
state.variables.set(variableName, `const ${variableName} = ${expression}`);
return variableName;
}
function CreateFunction(name, schema, references, value, useHoisting = true) {
const [newline, pad] = ['\n', (length) => ''.padStart(length, ' ')];
const parameter = CreateParameter('value', 'any');
const returns = CreateReturns('boolean');
const expression = [...Visit(schema, references, value, useHoisting)].map((expression) => `${pad(4)}${expression}`).join(` &&${newline}`);
return `function ${name}(${parameter})${returns} {${newline}${pad(2)}return (${newline}${expression}${newline}${pad(2)})\n}`;
}
function CreateParameter(name, type) {
const annotation = state.language === 'typescript' ? `: ${type}` : '';
return `${name}${annotation}`;
}
function CreateReturns(type) {
return state.language === 'typescript' ? `: ${type}` : '';
}
// ----------------------------------------------------------------
// Compile
// ----------------------------------------------------------------
function Build(schema, references, options) {
const functionCode = CreateFunction('check', schema, references, 'value'); // will populate functions and variables
const parameter = CreateParameter('value', 'any');
const returns = CreateReturns('boolean');
const functions = [...state.functions.values()];
const variables = [...state.variables.values()];
// prettier-ignore
const checkFunction = (0, index_12.IsString)(schema.$id) // ensure top level schemas with $id's are hoisted
? `return function check(${parameter})${returns} {\n return ${CreateFunctionName(schema.$id)}(value)\n}`
: `return ${functionCode}`;
return [...variables, ...functions, checkFunction].join('\n');
}
/** Generates the code used to assert this type and returns it as a string */
function Code(...args) {
const defaults = { language: 'javascript' };
// prettier-ignore
const [schema, references, options] = (args.length === 2 && (0, index_12.IsArray)(args[1]) ? [args[0], args[1], defaults] :
args.length === 2 && !(0, index_12.IsArray)(args[1]) ? [args[0], [], args[1]] :
args.length === 3 ? [args[0], args[1], args[2]] :
args.length === 1 ? [args[0], [], defaults] :
[null, [], defaults]);
// compiler-reset
state.language = options.language;
state.variables.clear();
state.functions.clear();
state.instances.clear();
if (!(0, type_1.IsSchema)(schema))
throw new TypeCompilerTypeGuardError(schema);
for (const schema of references)
if (!(0, type_1.IsSchema)(schema))
throw new TypeCompilerTypeGuardError(schema);
return Build(schema, references, options);
}
TypeCompiler.Code = Code;
/** Compiles a TypeBox type for optimal runtime type checking. Types must be valid TypeBox types of TSchema */
function Compile(schema, references = []) {
const generatedCode = Code(schema, references, { language: 'javascript' });
const compiledFunction = globalThis.Function('kind', 'format', 'hash', generatedCode);
const instances = new Map(state.instances);
function typeRegistryFunction(kind, instance, value) {
if (!index_8.TypeRegistry.Has(kind) || !instances.has(instance))
return false;
const checkFunc = index_8.TypeRegistry.Get(kind);
const schema = instances.get(instance);
return checkFunc(schema, value);
}
function formatRegistryFunction(format, value) {
if (!index_8.FormatRegistry.Has(format))
return false;
const checkFunc = index_8.FormatRegistry.Get(format);
return checkFunc(value);
}
function hashFunction(value) {
return (0, index_6.Hash)(value);
}
const checkFunction = compiledFunction(typeRegistryFunction, formatRegistryFunction, hashFunction);
return new TypeCheck(schema, references, checkFunction, generatedCode);
}
TypeCompiler.Compile = Compile;
})(TypeCompiler || (exports.TypeCompiler = TypeCompiler = {}));

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extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/compiler/index.d.ts generated vendored Normal file
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export { ValueError, ValueErrorType, ValueErrorIterator } from '../errors/index';
export * from './compiler';

22
extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/compiler/index.js generated vendored Normal file
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"use strict";
var __createBinding = (this && this.__createBinding) || (Object.create ? (function(o, m, k, k2) {
if (k2 === undefined) k2 = k;
var desc = Object.getOwnPropertyDescriptor(m, k);
if (!desc || ("get" in desc ? !m.__esModule : desc.writable || desc.configurable)) {
desc = { enumerable: true, get: function() { return m[k]; } };
}
Object.defineProperty(o, k2, desc);
}) : (function(o, m, k, k2) {
if (k2 === undefined) k2 = k;
o[k2] = m[k];
}));
var __exportStar = (this && this.__exportStar) || function(m, exports) {
for (var p in m) if (p !== "default" && !Object.prototype.hasOwnProperty.call(exports, p)) __createBinding(exports, m, p);
};
Object.defineProperty(exports, "__esModule", { value: true });
exports.ValueErrorIterator = exports.ValueErrorType = void 0;
var index_1 = require("../errors/index");
Object.defineProperty(exports, "ValueErrorType", { enumerable: true, get: function () { return index_1.ValueErrorType; } });
Object.defineProperty(exports, "ValueErrorIterator", { enumerable: true, get: function () { return index_1.ValueErrorIterator; } });
__exportStar(require("./compiler"), exports);

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import { TypeBoxError } from '../type/error/index';
import type { TSchema } from '../type/schema/index';
export declare enum ValueErrorType {
ArrayContains = 0,
ArrayMaxContains = 1,
ArrayMaxItems = 2,
ArrayMinContains = 3,
ArrayMinItems = 4,
ArrayUniqueItems = 5,
Array = 6,
AsyncIterator = 7,
BigIntExclusiveMaximum = 8,
BigIntExclusiveMinimum = 9,
BigIntMaximum = 10,
BigIntMinimum = 11,
BigIntMultipleOf = 12,
BigInt = 13,
Boolean = 14,
DateExclusiveMaximumTimestamp = 15,
DateExclusiveMinimumTimestamp = 16,
DateMaximumTimestamp = 17,
DateMinimumTimestamp = 18,
DateMultipleOfTimestamp = 19,
Date = 20,
Function = 21,
IntegerExclusiveMaximum = 22,
IntegerExclusiveMinimum = 23,
IntegerMaximum = 24,
IntegerMinimum = 25,
IntegerMultipleOf = 26,
Integer = 27,
IntersectUnevaluatedProperties = 28,
Intersect = 29,
Iterator = 30,
Kind = 31,
Literal = 32,
Never = 33,
Not = 34,
Null = 35,
NumberExclusiveMaximum = 36,
NumberExclusiveMinimum = 37,
NumberMaximum = 38,
NumberMinimum = 39,
NumberMultipleOf = 40,
Number = 41,
ObjectAdditionalProperties = 42,
ObjectMaxProperties = 43,
ObjectMinProperties = 44,
ObjectRequiredProperty = 45,
Object = 46,
Promise = 47,
RegExp = 48,
StringFormatUnknown = 49,
StringFormat = 50,
StringMaxLength = 51,
StringMinLength = 52,
StringPattern = 53,
String = 54,
Symbol = 55,
TupleLength = 56,
Tuple = 57,
Uint8ArrayMaxByteLength = 58,
Uint8ArrayMinByteLength = 59,
Uint8Array = 60,
Undefined = 61,
Union = 62,
Void = 63
}
export interface ValueError {
type: ValueErrorType;
schema: TSchema;
path: string;
value: unknown;
message: string;
errors: ValueErrorIterator[];
}
export declare class ValueErrorsUnknownTypeError extends TypeBoxError {
readonly schema: TSchema;
constructor(schema: TSchema);
}
export declare class ValueErrorIterator {
private readonly iterator;
constructor(iterator: IterableIterator<ValueError>);
[Symbol.iterator](): IterableIterator<ValueError>;
/** Returns the first value error or undefined if no errors */
First(): ValueError | undefined;
}
/** Returns an iterator for each error in this value. */
export declare function Errors<T extends TSchema>(schema: T, references: TSchema[], value: unknown): ValueErrorIterator;
/** Returns an iterator for each error in this value. */
export declare function Errors<T extends TSchema>(schema: T, value: unknown): ValueErrorIterator;

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"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.ValueErrorIterator = exports.ValueErrorsUnknownTypeError = exports.ValueErrorType = void 0;
exports.Errors = Errors;
const index_1 = require("../system/index");
const index_2 = require("../type/keyof/index");
const index_3 = require("../type/registry/index");
const extends_undefined_1 = require("../type/extends/extends-undefined");
const function_1 = require("./function");
const index_4 = require("../type/error/index");
const index_5 = require("../value/deref/index");
const index_6 = require("../value/hash/index");
const index_7 = require("../value/check/index");
const index_8 = require("../type/symbols/index");
const index_9 = require("../type/never/index");
// ------------------------------------------------------------------
// ValueGuard
// ------------------------------------------------------------------
// prettier-ignore
const index_10 = require("../value/guard/index");
// ------------------------------------------------------------------
// ValueErrorType
// ------------------------------------------------------------------
var ValueErrorType;
(function (ValueErrorType) {
ValueErrorType[ValueErrorType["ArrayContains"] = 0] = "ArrayContains";
ValueErrorType[ValueErrorType["ArrayMaxContains"] = 1] = "ArrayMaxContains";
ValueErrorType[ValueErrorType["ArrayMaxItems"] = 2] = "ArrayMaxItems";
ValueErrorType[ValueErrorType["ArrayMinContains"] = 3] = "ArrayMinContains";
ValueErrorType[ValueErrorType["ArrayMinItems"] = 4] = "ArrayMinItems";
ValueErrorType[ValueErrorType["ArrayUniqueItems"] = 5] = "ArrayUniqueItems";
ValueErrorType[ValueErrorType["Array"] = 6] = "Array";
ValueErrorType[ValueErrorType["AsyncIterator"] = 7] = "AsyncIterator";
ValueErrorType[ValueErrorType["BigIntExclusiveMaximum"] = 8] = "BigIntExclusiveMaximum";
ValueErrorType[ValueErrorType["BigIntExclusiveMinimum"] = 9] = "BigIntExclusiveMinimum";
ValueErrorType[ValueErrorType["BigIntMaximum"] = 10] = "BigIntMaximum";
ValueErrorType[ValueErrorType["BigIntMinimum"] = 11] = "BigIntMinimum";
ValueErrorType[ValueErrorType["BigIntMultipleOf"] = 12] = "BigIntMultipleOf";
ValueErrorType[ValueErrorType["BigInt"] = 13] = "BigInt";
ValueErrorType[ValueErrorType["Boolean"] = 14] = "Boolean";
ValueErrorType[ValueErrorType["DateExclusiveMaximumTimestamp"] = 15] = "DateExclusiveMaximumTimestamp";
ValueErrorType[ValueErrorType["DateExclusiveMinimumTimestamp"] = 16] = "DateExclusiveMinimumTimestamp";
ValueErrorType[ValueErrorType["DateMaximumTimestamp"] = 17] = "DateMaximumTimestamp";
ValueErrorType[ValueErrorType["DateMinimumTimestamp"] = 18] = "DateMinimumTimestamp";
ValueErrorType[ValueErrorType["DateMultipleOfTimestamp"] = 19] = "DateMultipleOfTimestamp";
ValueErrorType[ValueErrorType["Date"] = 20] = "Date";
ValueErrorType[ValueErrorType["Function"] = 21] = "Function";
ValueErrorType[ValueErrorType["IntegerExclusiveMaximum"] = 22] = "IntegerExclusiveMaximum";
ValueErrorType[ValueErrorType["IntegerExclusiveMinimum"] = 23] = "IntegerExclusiveMinimum";
ValueErrorType[ValueErrorType["IntegerMaximum"] = 24] = "IntegerMaximum";
ValueErrorType[ValueErrorType["IntegerMinimum"] = 25] = "IntegerMinimum";
ValueErrorType[ValueErrorType["IntegerMultipleOf"] = 26] = "IntegerMultipleOf";
ValueErrorType[ValueErrorType["Integer"] = 27] = "Integer";
ValueErrorType[ValueErrorType["IntersectUnevaluatedProperties"] = 28] = "IntersectUnevaluatedProperties";
ValueErrorType[ValueErrorType["Intersect"] = 29] = "Intersect";
ValueErrorType[ValueErrorType["Iterator"] = 30] = "Iterator";
ValueErrorType[ValueErrorType["Kind"] = 31] = "Kind";
ValueErrorType[ValueErrorType["Literal"] = 32] = "Literal";
ValueErrorType[ValueErrorType["Never"] = 33] = "Never";
ValueErrorType[ValueErrorType["Not"] = 34] = "Not";
ValueErrorType[ValueErrorType["Null"] = 35] = "Null";
ValueErrorType[ValueErrorType["NumberExclusiveMaximum"] = 36] = "NumberExclusiveMaximum";
ValueErrorType[ValueErrorType["NumberExclusiveMinimum"] = 37] = "NumberExclusiveMinimum";
ValueErrorType[ValueErrorType["NumberMaximum"] = 38] = "NumberMaximum";
ValueErrorType[ValueErrorType["NumberMinimum"] = 39] = "NumberMinimum";
ValueErrorType[ValueErrorType["NumberMultipleOf"] = 40] = "NumberMultipleOf";
ValueErrorType[ValueErrorType["Number"] = 41] = "Number";
ValueErrorType[ValueErrorType["ObjectAdditionalProperties"] = 42] = "ObjectAdditionalProperties";
ValueErrorType[ValueErrorType["ObjectMaxProperties"] = 43] = "ObjectMaxProperties";
ValueErrorType[ValueErrorType["ObjectMinProperties"] = 44] = "ObjectMinProperties";
ValueErrorType[ValueErrorType["ObjectRequiredProperty"] = 45] = "ObjectRequiredProperty";
ValueErrorType[ValueErrorType["Object"] = 46] = "Object";
ValueErrorType[ValueErrorType["Promise"] = 47] = "Promise";
ValueErrorType[ValueErrorType["RegExp"] = 48] = "RegExp";
ValueErrorType[ValueErrorType["StringFormatUnknown"] = 49] = "StringFormatUnknown";
ValueErrorType[ValueErrorType["StringFormat"] = 50] = "StringFormat";
ValueErrorType[ValueErrorType["StringMaxLength"] = 51] = "StringMaxLength";
ValueErrorType[ValueErrorType["StringMinLength"] = 52] = "StringMinLength";
ValueErrorType[ValueErrorType["StringPattern"] = 53] = "StringPattern";
ValueErrorType[ValueErrorType["String"] = 54] = "String";
ValueErrorType[ValueErrorType["Symbol"] = 55] = "Symbol";
ValueErrorType[ValueErrorType["TupleLength"] = 56] = "TupleLength";
ValueErrorType[ValueErrorType["Tuple"] = 57] = "Tuple";
ValueErrorType[ValueErrorType["Uint8ArrayMaxByteLength"] = 58] = "Uint8ArrayMaxByteLength";
ValueErrorType[ValueErrorType["Uint8ArrayMinByteLength"] = 59] = "Uint8ArrayMinByteLength";
ValueErrorType[ValueErrorType["Uint8Array"] = 60] = "Uint8Array";
ValueErrorType[ValueErrorType["Undefined"] = 61] = "Undefined";
ValueErrorType[ValueErrorType["Union"] = 62] = "Union";
ValueErrorType[ValueErrorType["Void"] = 63] = "Void";
})(ValueErrorType || (exports.ValueErrorType = ValueErrorType = {}));
// ------------------------------------------------------------------
// ValueErrors
// ------------------------------------------------------------------
class ValueErrorsUnknownTypeError extends index_4.TypeBoxError {
constructor(schema) {
super('Unknown type');
this.schema = schema;
}
}
exports.ValueErrorsUnknownTypeError = ValueErrorsUnknownTypeError;
// ------------------------------------------------------------------
// EscapeKey
// ------------------------------------------------------------------
function EscapeKey(key) {
return key.replace(/~/g, '~0').replace(/\//g, '~1'); // RFC6901 Path
}
// ------------------------------------------------------------------
// Guards
// ------------------------------------------------------------------
function IsDefined(value) {
return value !== undefined;
}
// ------------------------------------------------------------------
// ValueErrorIterator
// ------------------------------------------------------------------
class ValueErrorIterator {
constructor(iterator) {
this.iterator = iterator;
}
[Symbol.iterator]() {
return this.iterator;
}
/** Returns the first value error or undefined if no errors */
First() {
const next = this.iterator.next();
return next.done ? undefined : next.value;
}
}
exports.ValueErrorIterator = ValueErrorIterator;
// --------------------------------------------------------------------------
// Create
// --------------------------------------------------------------------------
function Create(errorType, schema, path, value, errors = []) {
return {
type: errorType,
schema,
path,
value,
message: (0, function_1.GetErrorFunction)()({ errorType, path, schema, value, errors }),
errors,
};
}
// --------------------------------------------------------------------------
// Types
// --------------------------------------------------------------------------
function* FromAny(schema, references, path, value) { }
function* FromArgument(schema, references, path, value) { }
function* FromArray(schema, references, path, value) {
if (!(0, index_10.IsArray)(value)) {
return yield Create(ValueErrorType.Array, schema, path, value);
}
if (IsDefined(schema.minItems) && !(value.length >= schema.minItems)) {
yield Create(ValueErrorType.ArrayMinItems, schema, path, value);
}
if (IsDefined(schema.maxItems) && !(value.length <= schema.maxItems)) {
yield Create(ValueErrorType.ArrayMaxItems, schema, path, value);
}
for (let i = 0; i < value.length; i++) {
yield* Visit(schema.items, references, `${path}/${i}`, value[i]);
}
// prettier-ignore
if (schema.uniqueItems === true && !((function () { const set = new Set(); for (const element of value) {
const hashed = (0, index_6.Hash)(element);
if (set.has(hashed)) {
return false;
}
else {
set.add(hashed);
}
} return true; })())) {
yield Create(ValueErrorType.ArrayUniqueItems, schema, path, value);
}
// contains
if (!(IsDefined(schema.contains) || IsDefined(schema.minContains) || IsDefined(schema.maxContains))) {
return;
}
const containsSchema = IsDefined(schema.contains) ? schema.contains : (0, index_9.Never)();
const containsCount = value.reduce((acc, value, index) => (Visit(containsSchema, references, `${path}${index}`, value).next().done === true ? acc + 1 : acc), 0);
if (containsCount === 0) {
yield Create(ValueErrorType.ArrayContains, schema, path, value);
}
if ((0, index_10.IsNumber)(schema.minContains) && containsCount < schema.minContains) {
yield Create(ValueErrorType.ArrayMinContains, schema, path, value);
}
if ((0, index_10.IsNumber)(schema.maxContains) && containsCount > schema.maxContains) {
yield Create(ValueErrorType.ArrayMaxContains, schema, path, value);
}
}
function* FromAsyncIterator(schema, references, path, value) {
if (!(0, index_10.IsAsyncIterator)(value))
yield Create(ValueErrorType.AsyncIterator, schema, path, value);
}
function* FromBigInt(schema, references, path, value) {
if (!(0, index_10.IsBigInt)(value))
return yield Create(ValueErrorType.BigInt, schema, path, value);
if (IsDefined(schema.exclusiveMaximum) && !(value < schema.exclusiveMaximum)) {
yield Create(ValueErrorType.BigIntExclusiveMaximum, schema, path, value);
}
if (IsDefined(schema.exclusiveMinimum) && !(value > schema.exclusiveMinimum)) {
yield Create(ValueErrorType.BigIntExclusiveMinimum, schema, path, value);
}
if (IsDefined(schema.maximum) && !(value <= schema.maximum)) {
yield Create(ValueErrorType.BigIntMaximum, schema, path, value);
}
if (IsDefined(schema.minimum) && !(value >= schema.minimum)) {
yield Create(ValueErrorType.BigIntMinimum, schema, path, value);
}
if (IsDefined(schema.multipleOf) && !(value % schema.multipleOf === BigInt(0))) {
yield Create(ValueErrorType.BigIntMultipleOf, schema, path, value);
}
}
function* FromBoolean(schema, references, path, value) {
if (!(0, index_10.IsBoolean)(value))
yield Create(ValueErrorType.Boolean, schema, path, value);
}
function* FromConstructor(schema, references, path, value) {
yield* Visit(schema.returns, references, path, value.prototype);
}
function* FromDate(schema, references, path, value) {
if (!(0, index_10.IsDate)(value))
return yield Create(ValueErrorType.Date, schema, path, value);
if (IsDefined(schema.exclusiveMaximumTimestamp) && !(value.getTime() < schema.exclusiveMaximumTimestamp)) {
yield Create(ValueErrorType.DateExclusiveMaximumTimestamp, schema, path, value);
}
if (IsDefined(schema.exclusiveMinimumTimestamp) && !(value.getTime() > schema.exclusiveMinimumTimestamp)) {
yield Create(ValueErrorType.DateExclusiveMinimumTimestamp, schema, path, value);
}
if (IsDefined(schema.maximumTimestamp) && !(value.getTime() <= schema.maximumTimestamp)) {
yield Create(ValueErrorType.DateMaximumTimestamp, schema, path, value);
}
if (IsDefined(schema.minimumTimestamp) && !(value.getTime() >= schema.minimumTimestamp)) {
yield Create(ValueErrorType.DateMinimumTimestamp, schema, path, value);
}
if (IsDefined(schema.multipleOfTimestamp) && !(value.getTime() % schema.multipleOfTimestamp === 0)) {
yield Create(ValueErrorType.DateMultipleOfTimestamp, schema, path, value);
}
}
function* FromFunction(schema, references, path, value) {
if (!(0, index_10.IsFunction)(value))
yield Create(ValueErrorType.Function, schema, path, value);
}
function* FromImport(schema, references, path, value) {
const definitions = globalThis.Object.values(schema.$defs);
const target = schema.$defs[schema.$ref];
yield* Visit(target, [...references, ...definitions], path, value);
}
function* FromInteger(schema, references, path, value) {
if (!(0, index_10.IsInteger)(value))
return yield Create(ValueErrorType.Integer, schema, path, value);
if (IsDefined(schema.exclusiveMaximum) && !(value < schema.exclusiveMaximum)) {
yield Create(ValueErrorType.IntegerExclusiveMaximum, schema, path, value);
}
if (IsDefined(schema.exclusiveMinimum) && !(value > schema.exclusiveMinimum)) {
yield Create(ValueErrorType.IntegerExclusiveMinimum, schema, path, value);
}
if (IsDefined(schema.maximum) && !(value <= schema.maximum)) {
yield Create(ValueErrorType.IntegerMaximum, schema, path, value);
}
if (IsDefined(schema.minimum) && !(value >= schema.minimum)) {
yield Create(ValueErrorType.IntegerMinimum, schema, path, value);
}
if (IsDefined(schema.multipleOf) && !(value % schema.multipleOf === 0)) {
yield Create(ValueErrorType.IntegerMultipleOf, schema, path, value);
}
}
function* FromIntersect(schema, references, path, value) {
let hasError = false;
for (const inner of schema.allOf) {
for (const error of Visit(inner, references, path, value)) {
hasError = true;
yield error;
}
}
if (hasError) {
return yield Create(ValueErrorType.Intersect, schema, path, value);
}
if (schema.unevaluatedProperties === false) {
const keyCheck = new RegExp((0, index_2.KeyOfPattern)(schema));
for (const valueKey of Object.getOwnPropertyNames(value)) {
if (!keyCheck.test(valueKey)) {
yield Create(ValueErrorType.IntersectUnevaluatedProperties, schema, `${path}/${valueKey}`, value);
}
}
}
if (typeof schema.unevaluatedProperties === 'object') {
const keyCheck = new RegExp((0, index_2.KeyOfPattern)(schema));
for (const valueKey of Object.getOwnPropertyNames(value)) {
if (!keyCheck.test(valueKey)) {
const next = Visit(schema.unevaluatedProperties, references, `${path}/${valueKey}`, value[valueKey]).next();
if (!next.done)
yield next.value; // yield interior
}
}
}
}
function* FromIterator(schema, references, path, value) {
if (!(0, index_10.IsIterator)(value))
yield Create(ValueErrorType.Iterator, schema, path, value);
}
function* FromLiteral(schema, references, path, value) {
if (!(value === schema.const))
yield Create(ValueErrorType.Literal, schema, path, value);
}
function* FromNever(schema, references, path, value) {
yield Create(ValueErrorType.Never, schema, path, value);
}
function* FromNot(schema, references, path, value) {
if (Visit(schema.not, references, path, value).next().done === true)
yield Create(ValueErrorType.Not, schema, path, value);
}
function* FromNull(schema, references, path, value) {
if (!(0, index_10.IsNull)(value))
yield Create(ValueErrorType.Null, schema, path, value);
}
function* FromNumber(schema, references, path, value) {
if (!index_1.TypeSystemPolicy.IsNumberLike(value))
return yield Create(ValueErrorType.Number, schema, path, value);
if (IsDefined(schema.exclusiveMaximum) && !(value < schema.exclusiveMaximum)) {
yield Create(ValueErrorType.NumberExclusiveMaximum, schema, path, value);
}
if (IsDefined(schema.exclusiveMinimum) && !(value > schema.exclusiveMinimum)) {
yield Create(ValueErrorType.NumberExclusiveMinimum, schema, path, value);
}
if (IsDefined(schema.maximum) && !(value <= schema.maximum)) {
yield Create(ValueErrorType.NumberMaximum, schema, path, value);
}
if (IsDefined(schema.minimum) && !(value >= schema.minimum)) {
yield Create(ValueErrorType.NumberMinimum, schema, path, value);
}
if (IsDefined(schema.multipleOf) && !(value % schema.multipleOf === 0)) {
yield Create(ValueErrorType.NumberMultipleOf, schema, path, value);
}
}
function* FromObject(schema, references, path, value) {
if (!index_1.TypeSystemPolicy.IsObjectLike(value))
return yield Create(ValueErrorType.Object, schema, path, value);
if (IsDefined(schema.minProperties) && !(Object.getOwnPropertyNames(value).length >= schema.minProperties)) {
yield Create(ValueErrorType.ObjectMinProperties, schema, path, value);
}
if (IsDefined(schema.maxProperties) && !(Object.getOwnPropertyNames(value).length <= schema.maxProperties)) {
yield Create(ValueErrorType.ObjectMaxProperties, schema, path, value);
}
const requiredKeys = Array.isArray(schema.required) ? schema.required : [];
const knownKeys = Object.getOwnPropertyNames(schema.properties);
const unknownKeys = Object.getOwnPropertyNames(value);
for (const requiredKey of requiredKeys) {
if (unknownKeys.includes(requiredKey))
continue;
yield Create(ValueErrorType.ObjectRequiredProperty, schema.properties[requiredKey], `${path}/${EscapeKey(requiredKey)}`, undefined);
}
if (schema.additionalProperties === false) {
for (const valueKey of unknownKeys) {
if (!knownKeys.includes(valueKey)) {
yield Create(ValueErrorType.ObjectAdditionalProperties, schema, `${path}/${EscapeKey(valueKey)}`, value[valueKey]);
}
}
}
if (typeof schema.additionalProperties === 'object') {
for (const valueKey of unknownKeys) {
if (knownKeys.includes(valueKey))
continue;
yield* Visit(schema.additionalProperties, references, `${path}/${EscapeKey(valueKey)}`, value[valueKey]);
}
}
for (const knownKey of knownKeys) {
const property = schema.properties[knownKey];
if (schema.required && schema.required.includes(knownKey)) {
yield* Visit(property, references, `${path}/${EscapeKey(knownKey)}`, value[knownKey]);
if ((0, extends_undefined_1.ExtendsUndefinedCheck)(schema) && !(knownKey in value)) {
yield Create(ValueErrorType.ObjectRequiredProperty, property, `${path}/${EscapeKey(knownKey)}`, undefined);
}
}
else {
if (index_1.TypeSystemPolicy.IsExactOptionalProperty(value, knownKey)) {
yield* Visit(property, references, `${path}/${EscapeKey(knownKey)}`, value[knownKey]);
}
}
}
}
function* FromPromise(schema, references, path, value) {
if (!(0, index_10.IsPromise)(value))
yield Create(ValueErrorType.Promise, schema, path, value);
}
function* FromRecord(schema, references, path, value) {
if (!index_1.TypeSystemPolicy.IsRecordLike(value))
return yield Create(ValueErrorType.Object, schema, path, value);
if (IsDefined(schema.minProperties) && !(Object.getOwnPropertyNames(value).length >= schema.minProperties)) {
yield Create(ValueErrorType.ObjectMinProperties, schema, path, value);
}
if (IsDefined(schema.maxProperties) && !(Object.getOwnPropertyNames(value).length <= schema.maxProperties)) {
yield Create(ValueErrorType.ObjectMaxProperties, schema, path, value);
}
const [patternKey, patternSchema] = Object.entries(schema.patternProperties)[0];
const regex = new RegExp(patternKey);
for (const [propertyKey, propertyValue] of Object.entries(value)) {
if (regex.test(propertyKey))
yield* Visit(patternSchema, references, `${path}/${EscapeKey(propertyKey)}`, propertyValue);
}
if (typeof schema.additionalProperties === 'object') {
for (const [propertyKey, propertyValue] of Object.entries(value)) {
if (!regex.test(propertyKey))
yield* Visit(schema.additionalProperties, references, `${path}/${EscapeKey(propertyKey)}`, propertyValue);
}
}
if (schema.additionalProperties === false) {
for (const [propertyKey, propertyValue] of Object.entries(value)) {
if (regex.test(propertyKey))
continue;
return yield Create(ValueErrorType.ObjectAdditionalProperties, schema, `${path}/${EscapeKey(propertyKey)}`, propertyValue);
}
}
}
function* FromRef(schema, references, path, value) {
yield* Visit((0, index_5.Deref)(schema, references), references, path, value);
}
function* FromRegExp(schema, references, path, value) {
if (!(0, index_10.IsString)(value))
return yield Create(ValueErrorType.String, schema, path, value);
if (IsDefined(schema.minLength) && !(value.length >= schema.minLength)) {
yield Create(ValueErrorType.StringMinLength, schema, path, value);
}
if (IsDefined(schema.maxLength) && !(value.length <= schema.maxLength)) {
yield Create(ValueErrorType.StringMaxLength, schema, path, value);
}
const regex = new RegExp(schema.source, schema.flags);
if (!regex.test(value)) {
return yield Create(ValueErrorType.RegExp, schema, path, value);
}
}
function* FromString(schema, references, path, value) {
if (!(0, index_10.IsString)(value))
return yield Create(ValueErrorType.String, schema, path, value);
if (IsDefined(schema.minLength) && !(value.length >= schema.minLength)) {
yield Create(ValueErrorType.StringMinLength, schema, path, value);
}
if (IsDefined(schema.maxLength) && !(value.length <= schema.maxLength)) {
yield Create(ValueErrorType.StringMaxLength, schema, path, value);
}
if ((0, index_10.IsString)(schema.pattern)) {
const regex = new RegExp(schema.pattern);
if (!regex.test(value)) {
yield Create(ValueErrorType.StringPattern, schema, path, value);
}
}
if ((0, index_10.IsString)(schema.format)) {
if (!index_3.FormatRegistry.Has(schema.format)) {
yield Create(ValueErrorType.StringFormatUnknown, schema, path, value);
}
else {
const format = index_3.FormatRegistry.Get(schema.format);
if (!format(value)) {
yield Create(ValueErrorType.StringFormat, schema, path, value);
}
}
}
}
function* FromSymbol(schema, references, path, value) {
if (!(0, index_10.IsSymbol)(value))
yield Create(ValueErrorType.Symbol, schema, path, value);
}
function* FromTemplateLiteral(schema, references, path, value) {
if (!(0, index_10.IsString)(value))
return yield Create(ValueErrorType.String, schema, path, value);
const regex = new RegExp(schema.pattern);
if (!regex.test(value)) {
yield Create(ValueErrorType.StringPattern, schema, path, value);
}
}
function* FromThis(schema, references, path, value) {
yield* Visit((0, index_5.Deref)(schema, references), references, path, value);
}
function* FromTuple(schema, references, path, value) {
if (!(0, index_10.IsArray)(value))
return yield Create(ValueErrorType.Tuple, schema, path, value);
if (schema.items === undefined && !(value.length === 0)) {
return yield Create(ValueErrorType.TupleLength, schema, path, value);
}
if (!(value.length === schema.maxItems)) {
return yield Create(ValueErrorType.TupleLength, schema, path, value);
}
if (!schema.items) {
return;
}
for (let i = 0; i < schema.items.length; i++) {
yield* Visit(schema.items[i], references, `${path}/${i}`, value[i]);
}
}
function* FromUndefined(schema, references, path, value) {
if (!(0, index_10.IsUndefined)(value))
yield Create(ValueErrorType.Undefined, schema, path, value);
}
function* FromUnion(schema, references, path, value) {
if ((0, index_7.Check)(schema, references, value))
return;
const errors = schema.anyOf.map((variant) => new ValueErrorIterator(Visit(variant, references, path, value)));
yield Create(ValueErrorType.Union, schema, path, value, errors);
}
function* FromUint8Array(schema, references, path, value) {
if (!(0, index_10.IsUint8Array)(value))
return yield Create(ValueErrorType.Uint8Array, schema, path, value);
if (IsDefined(schema.maxByteLength) && !(value.length <= schema.maxByteLength)) {
yield Create(ValueErrorType.Uint8ArrayMaxByteLength, schema, path, value);
}
if (IsDefined(schema.minByteLength) && !(value.length >= schema.minByteLength)) {
yield Create(ValueErrorType.Uint8ArrayMinByteLength, schema, path, value);
}
}
function* FromUnknown(schema, references, path, value) { }
function* FromVoid(schema, references, path, value) {
if (!index_1.TypeSystemPolicy.IsVoidLike(value))
yield Create(ValueErrorType.Void, schema, path, value);
}
function* FromKind(schema, references, path, value) {
const check = index_3.TypeRegistry.Get(schema[index_8.Kind]);
if (!check(schema, value))
yield Create(ValueErrorType.Kind, schema, path, value);
}
function* Visit(schema, references, path, value) {
const references_ = IsDefined(schema.$id) ? [...references, schema] : references;
const schema_ = schema;
switch (schema_[index_8.Kind]) {
case 'Any':
return yield* FromAny(schema_, references_, path, value);
case 'Argument':
return yield* FromArgument(schema_, references_, path, value);
case 'Array':
return yield* FromArray(schema_, references_, path, value);
case 'AsyncIterator':
return yield* FromAsyncIterator(schema_, references_, path, value);
case 'BigInt':
return yield* FromBigInt(schema_, references_, path, value);
case 'Boolean':
return yield* FromBoolean(schema_, references_, path, value);
case 'Constructor':
return yield* FromConstructor(schema_, references_, path, value);
case 'Date':
return yield* FromDate(schema_, references_, path, value);
case 'Function':
return yield* FromFunction(schema_, references_, path, value);
case 'Import':
return yield* FromImport(schema_, references_, path, value);
case 'Integer':
return yield* FromInteger(schema_, references_, path, value);
case 'Intersect':
return yield* FromIntersect(schema_, references_, path, value);
case 'Iterator':
return yield* FromIterator(schema_, references_, path, value);
case 'Literal':
return yield* FromLiteral(schema_, references_, path, value);
case 'Never':
return yield* FromNever(schema_, references_, path, value);
case 'Not':
return yield* FromNot(schema_, references_, path, value);
case 'Null':
return yield* FromNull(schema_, references_, path, value);
case 'Number':
return yield* FromNumber(schema_, references_, path, value);
case 'Object':
return yield* FromObject(schema_, references_, path, value);
case 'Promise':
return yield* FromPromise(schema_, references_, path, value);
case 'Record':
return yield* FromRecord(schema_, references_, path, value);
case 'Ref':
return yield* FromRef(schema_, references_, path, value);
case 'RegExp':
return yield* FromRegExp(schema_, references_, path, value);
case 'String':
return yield* FromString(schema_, references_, path, value);
case 'Symbol':
return yield* FromSymbol(schema_, references_, path, value);
case 'TemplateLiteral':
return yield* FromTemplateLiteral(schema_, references_, path, value);
case 'This':
return yield* FromThis(schema_, references_, path, value);
case 'Tuple':
return yield* FromTuple(schema_, references_, path, value);
case 'Undefined':
return yield* FromUndefined(schema_, references_, path, value);
case 'Union':
return yield* FromUnion(schema_, references_, path, value);
case 'Uint8Array':
return yield* FromUint8Array(schema_, references_, path, value);
case 'Unknown':
return yield* FromUnknown(schema_, references_, path, value);
case 'Void':
return yield* FromVoid(schema_, references_, path, value);
default:
if (!index_3.TypeRegistry.Has(schema_[index_8.Kind]))
throw new ValueErrorsUnknownTypeError(schema);
return yield* FromKind(schema_, references_, path, value);
}
}
/** Returns an iterator for each error in this value. */
function Errors(...args) {
const iterator = args.length === 3 ? Visit(args[0], args[1], '', args[2]) : Visit(args[0], [], '', args[1]);
return new ValueErrorIterator(iterator);
}

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import { TSchema } from '../type/schema/index';
import { ValueErrorIterator, ValueErrorType } from './errors';
/** Creates an error message using en-US as the default locale */
export declare function DefaultErrorFunction(error: ErrorFunctionParameter): string;
export type ErrorFunctionParameter = {
/** The type of validation error */
errorType: ValueErrorType;
/** The path of the error */
path: string;
/** The schema associated with the error */
schema: TSchema;
/** The value associated with the error */
value: unknown;
/** Interior errors for this error */
errors: ValueErrorIterator[];
};
export type ErrorFunction = (parameter: ErrorFunctionParameter) => string;
/** Sets the error function used to generate error messages. */
export declare function SetErrorFunction(callback: ErrorFunction): void;
/** Gets the error function used to generate error messages */
export declare function GetErrorFunction(): ErrorFunction;

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"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.DefaultErrorFunction = DefaultErrorFunction;
exports.SetErrorFunction = SetErrorFunction;
exports.GetErrorFunction = GetErrorFunction;
const index_1 = require("../type/symbols/index");
const errors_1 = require("./errors");
/** Creates an error message using en-US as the default locale */
function DefaultErrorFunction(error) {
switch (error.errorType) {
case errors_1.ValueErrorType.ArrayContains:
return 'Expected array to contain at least one matching value';
case errors_1.ValueErrorType.ArrayMaxContains:
return `Expected array to contain no more than ${error.schema.maxContains} matching values`;
case errors_1.ValueErrorType.ArrayMinContains:
return `Expected array to contain at least ${error.schema.minContains} matching values`;
case errors_1.ValueErrorType.ArrayMaxItems:
return `Expected array length to be less or equal to ${error.schema.maxItems}`;
case errors_1.ValueErrorType.ArrayMinItems:
return `Expected array length to be greater or equal to ${error.schema.minItems}`;
case errors_1.ValueErrorType.ArrayUniqueItems:
return 'Expected array elements to be unique';
case errors_1.ValueErrorType.Array:
return 'Expected array';
case errors_1.ValueErrorType.AsyncIterator:
return 'Expected AsyncIterator';
case errors_1.ValueErrorType.BigIntExclusiveMaximum:
return `Expected bigint to be less than ${error.schema.exclusiveMaximum}`;
case errors_1.ValueErrorType.BigIntExclusiveMinimum:
return `Expected bigint to be greater than ${error.schema.exclusiveMinimum}`;
case errors_1.ValueErrorType.BigIntMaximum:
return `Expected bigint to be less or equal to ${error.schema.maximum}`;
case errors_1.ValueErrorType.BigIntMinimum:
return `Expected bigint to be greater or equal to ${error.schema.minimum}`;
case errors_1.ValueErrorType.BigIntMultipleOf:
return `Expected bigint to be a multiple of ${error.schema.multipleOf}`;
case errors_1.ValueErrorType.BigInt:
return 'Expected bigint';
case errors_1.ValueErrorType.Boolean:
return 'Expected boolean';
case errors_1.ValueErrorType.DateExclusiveMinimumTimestamp:
return `Expected Date timestamp to be greater than ${error.schema.exclusiveMinimumTimestamp}`;
case errors_1.ValueErrorType.DateExclusiveMaximumTimestamp:
return `Expected Date timestamp to be less than ${error.schema.exclusiveMaximumTimestamp}`;
case errors_1.ValueErrorType.DateMinimumTimestamp:
return `Expected Date timestamp to be greater or equal to ${error.schema.minimumTimestamp}`;
case errors_1.ValueErrorType.DateMaximumTimestamp:
return `Expected Date timestamp to be less or equal to ${error.schema.maximumTimestamp}`;
case errors_1.ValueErrorType.DateMultipleOfTimestamp:
return `Expected Date timestamp to be a multiple of ${error.schema.multipleOfTimestamp}`;
case errors_1.ValueErrorType.Date:
return 'Expected Date';
case errors_1.ValueErrorType.Function:
return 'Expected function';
case errors_1.ValueErrorType.IntegerExclusiveMaximum:
return `Expected integer to be less than ${error.schema.exclusiveMaximum}`;
case errors_1.ValueErrorType.IntegerExclusiveMinimum:
return `Expected integer to be greater than ${error.schema.exclusiveMinimum}`;
case errors_1.ValueErrorType.IntegerMaximum:
return `Expected integer to be less or equal to ${error.schema.maximum}`;
case errors_1.ValueErrorType.IntegerMinimum:
return `Expected integer to be greater or equal to ${error.schema.minimum}`;
case errors_1.ValueErrorType.IntegerMultipleOf:
return `Expected integer to be a multiple of ${error.schema.multipleOf}`;
case errors_1.ValueErrorType.Integer:
return 'Expected integer';
case errors_1.ValueErrorType.IntersectUnevaluatedProperties:
return 'Unexpected property';
case errors_1.ValueErrorType.Intersect:
return 'Expected all values to match';
case errors_1.ValueErrorType.Iterator:
return 'Expected Iterator';
case errors_1.ValueErrorType.Literal:
return `Expected ${typeof error.schema.const === 'string' ? `'${error.schema.const}'` : error.schema.const}`;
case errors_1.ValueErrorType.Never:
return 'Never';
case errors_1.ValueErrorType.Not:
return 'Value should not match';
case errors_1.ValueErrorType.Null:
return 'Expected null';
case errors_1.ValueErrorType.NumberExclusiveMaximum:
return `Expected number to be less than ${error.schema.exclusiveMaximum}`;
case errors_1.ValueErrorType.NumberExclusiveMinimum:
return `Expected number to be greater than ${error.schema.exclusiveMinimum}`;
case errors_1.ValueErrorType.NumberMaximum:
return `Expected number to be less or equal to ${error.schema.maximum}`;
case errors_1.ValueErrorType.NumberMinimum:
return `Expected number to be greater or equal to ${error.schema.minimum}`;
case errors_1.ValueErrorType.NumberMultipleOf:
return `Expected number to be a multiple of ${error.schema.multipleOf}`;
case errors_1.ValueErrorType.Number:
return 'Expected number';
case errors_1.ValueErrorType.Object:
return 'Expected object';
case errors_1.ValueErrorType.ObjectAdditionalProperties:
return 'Unexpected property';
case errors_1.ValueErrorType.ObjectMaxProperties:
return `Expected object to have no more than ${error.schema.maxProperties} properties`;
case errors_1.ValueErrorType.ObjectMinProperties:
return `Expected object to have at least ${error.schema.minProperties} properties`;
case errors_1.ValueErrorType.ObjectRequiredProperty:
return 'Expected required property';
case errors_1.ValueErrorType.Promise:
return 'Expected Promise';
case errors_1.ValueErrorType.RegExp:
return 'Expected string to match regular expression';
case errors_1.ValueErrorType.StringFormatUnknown:
return `Unknown format '${error.schema.format}'`;
case errors_1.ValueErrorType.StringFormat:
return `Expected string to match '${error.schema.format}' format`;
case errors_1.ValueErrorType.StringMaxLength:
return `Expected string length less or equal to ${error.schema.maxLength}`;
case errors_1.ValueErrorType.StringMinLength:
return `Expected string length greater or equal to ${error.schema.minLength}`;
case errors_1.ValueErrorType.StringPattern:
return `Expected string to match '${error.schema.pattern}'`;
case errors_1.ValueErrorType.String:
return 'Expected string';
case errors_1.ValueErrorType.Symbol:
return 'Expected symbol';
case errors_1.ValueErrorType.TupleLength:
return `Expected tuple to have ${error.schema.maxItems || 0} elements`;
case errors_1.ValueErrorType.Tuple:
return 'Expected tuple';
case errors_1.ValueErrorType.Uint8ArrayMaxByteLength:
return `Expected byte length less or equal to ${error.schema.maxByteLength}`;
case errors_1.ValueErrorType.Uint8ArrayMinByteLength:
return `Expected byte length greater or equal to ${error.schema.minByteLength}`;
case errors_1.ValueErrorType.Uint8Array:
return 'Expected Uint8Array';
case errors_1.ValueErrorType.Undefined:
return 'Expected undefined';
case errors_1.ValueErrorType.Union:
return 'Expected union value';
case errors_1.ValueErrorType.Void:
return 'Expected void';
case errors_1.ValueErrorType.Kind:
return `Expected kind '${error.schema[index_1.Kind]}'`;
default:
return 'Unknown error type';
}
}
/** Manages error message providers */
let errorFunction = DefaultErrorFunction;
/** Sets the error function used to generate error messages. */
function SetErrorFunction(callback) {
errorFunction = callback;
}
/** Gets the error function used to generate error messages */
function GetErrorFunction() {
return errorFunction;
}

2
extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/errors/index.d.ts generated vendored Normal file
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export * from './errors';
export * from './function';

19
extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/errors/index.js generated vendored Normal file
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@ -0,0 +1,19 @@
"use strict";
var __createBinding = (this && this.__createBinding) || (Object.create ? (function(o, m, k, k2) {
if (k2 === undefined) k2 = k;
var desc = Object.getOwnPropertyDescriptor(m, k);
if (!desc || ("get" in desc ? !m.__esModule : desc.writable || desc.configurable)) {
desc = { enumerable: true, get: function() { return m[k]; } };
}
Object.defineProperty(o, k2, desc);
}) : (function(o, m, k, k2) {
if (k2 === undefined) k2 = k;
o[k2] = m[k];
}));
var __exportStar = (this && this.__exportStar) || function(m, exports) {
for (var p in m) if (p !== "default" && !Object.prototype.hasOwnProperty.call(exports, p)) __createBinding(exports, m, p);
};
Object.defineProperty(exports, "__esModule", { value: true });
__exportStar(require("./errors"), exports);
__exportStar(require("./function"), exports);

71
extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/index.d.ts generated vendored Normal file
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export * from './type/clone/index';
export * from './type/create/index';
export * from './type/error/index';
export * from './type/guard/index';
export * from './type/helpers/index';
export * from './type/patterns/index';
export * from './type/registry/index';
export * from './type/sets/index';
export * from './type/symbols/index';
export * from './type/any/index';
export * from './type/array/index';
export * from './type/argument/index';
export * from './type/async-iterator/index';
export * from './type/awaited/index';
export * from './type/bigint/index';
export * from './type/boolean/index';
export * from './type/composite/index';
export * from './type/const/index';
export * from './type/constructor/index';
export * from './type/constructor-parameters/index';
export * from './type/date/index';
export * from './type/enum/index';
export * from './type/exclude/index';
export * from './type/extends/index';
export * from './type/extract/index';
export * from './type/function/index';
export * from './type/indexed/index';
export * from './type/instance-type/index';
export * from './type/instantiate/index';
export * from './type/integer/index';
export * from './type/intersect/index';
export * from './type/iterator/index';
export * from './type/intrinsic/index';
export * from './type/keyof/index';
export * from './type/literal/index';
export * from './type/module/index';
export * from './type/mapped/index';
export * from './type/never/index';
export * from './type/not/index';
export * from './type/null/index';
export * from './type/number/index';
export * from './type/object/index';
export * from './type/omit/index';
export * from './type/optional/index';
export * from './type/parameters/index';
export * from './type/partial/index';
export * from './type/pick/index';
export * from './type/promise/index';
export * from './type/readonly/index';
export * from './type/readonly-optional/index';
export * from './type/record/index';
export * from './type/recursive/index';
export * from './type/ref/index';
export * from './type/regexp/index';
export * from './type/required/index';
export * from './type/rest/index';
export * from './type/return-type/index';
export * from './type/schema/index';
export * from './type/static/index';
export * from './type/string/index';
export * from './type/symbol/index';
export * from './type/template-literal/index';
export * from './type/transform/index';
export * from './type/tuple/index';
export * from './type/uint8array/index';
export * from './type/undefined/index';
export * from './type/union/index';
export * from './type/unknown/index';
export * from './type/unsafe/index';
export * from './type/void/index';
export * from './type/type/index';

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extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/index.js generated vendored Normal file
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"use strict";
var __createBinding = (this && this.__createBinding) || (Object.create ? (function(o, m, k, k2) {
if (k2 === undefined) k2 = k;
var desc = Object.getOwnPropertyDescriptor(m, k);
if (!desc || ("get" in desc ? !m.__esModule : desc.writable || desc.configurable)) {
desc = { enumerable: true, get: function() { return m[k]; } };
}
Object.defineProperty(o, k2, desc);
}) : (function(o, m, k, k2) {
if (k2 === undefined) k2 = k;
o[k2] = m[k];
}));
var __exportStar = (this && this.__exportStar) || function(m, exports) {
for (var p in m) if (p !== "default" && !Object.prototype.hasOwnProperty.call(exports, p)) __createBinding(exports, m, p);
};
Object.defineProperty(exports, "__esModule", { value: true });
// ------------------------------------------------------------------
// Infrastructure
// ------------------------------------------------------------------
__exportStar(require("./type/clone/index"), exports);
__exportStar(require("./type/create/index"), exports);
__exportStar(require("./type/error/index"), exports);
__exportStar(require("./type/guard/index"), exports);
__exportStar(require("./type/helpers/index"), exports);
__exportStar(require("./type/patterns/index"), exports);
__exportStar(require("./type/registry/index"), exports);
__exportStar(require("./type/sets/index"), exports);
__exportStar(require("./type/symbols/index"), exports);
// ------------------------------------------------------------------
// Types
// ------------------------------------------------------------------
__exportStar(require("./type/any/index"), exports);
__exportStar(require("./type/array/index"), exports);
__exportStar(require("./type/argument/index"), exports);
__exportStar(require("./type/async-iterator/index"), exports);
__exportStar(require("./type/awaited/index"), exports);
__exportStar(require("./type/bigint/index"), exports);
__exportStar(require("./type/boolean/index"), exports);
__exportStar(require("./type/composite/index"), exports);
__exportStar(require("./type/const/index"), exports);
__exportStar(require("./type/constructor/index"), exports);
__exportStar(require("./type/constructor-parameters/index"), exports);
__exportStar(require("./type/date/index"), exports);
__exportStar(require("./type/enum/index"), exports);
__exportStar(require("./type/exclude/index"), exports);
__exportStar(require("./type/extends/index"), exports);
__exportStar(require("./type/extract/index"), exports);
__exportStar(require("./type/function/index"), exports);
__exportStar(require("./type/indexed/index"), exports);
__exportStar(require("./type/instance-type/index"), exports);
__exportStar(require("./type/instantiate/index"), exports);
__exportStar(require("./type/integer/index"), exports);
__exportStar(require("./type/intersect/index"), exports);
__exportStar(require("./type/iterator/index"), exports);
__exportStar(require("./type/intrinsic/index"), exports);
__exportStar(require("./type/keyof/index"), exports);
__exportStar(require("./type/literal/index"), exports);
__exportStar(require("./type/module/index"), exports);
__exportStar(require("./type/mapped/index"), exports);
__exportStar(require("./type/never/index"), exports);
__exportStar(require("./type/not/index"), exports);
__exportStar(require("./type/null/index"), exports);
__exportStar(require("./type/number/index"), exports);
__exportStar(require("./type/object/index"), exports);
__exportStar(require("./type/omit/index"), exports);
__exportStar(require("./type/optional/index"), exports);
__exportStar(require("./type/parameters/index"), exports);
__exportStar(require("./type/partial/index"), exports);
__exportStar(require("./type/pick/index"), exports);
__exportStar(require("./type/promise/index"), exports);
__exportStar(require("./type/readonly/index"), exports);
__exportStar(require("./type/readonly-optional/index"), exports);
__exportStar(require("./type/record/index"), exports);
__exportStar(require("./type/recursive/index"), exports);
__exportStar(require("./type/ref/index"), exports);
__exportStar(require("./type/regexp/index"), exports);
__exportStar(require("./type/required/index"), exports);
__exportStar(require("./type/rest/index"), exports);
__exportStar(require("./type/return-type/index"), exports);
__exportStar(require("./type/schema/index"), exports);
__exportStar(require("./type/static/index"), exports);
__exportStar(require("./type/string/index"), exports);
__exportStar(require("./type/symbol/index"), exports);
__exportStar(require("./type/template-literal/index"), exports);
__exportStar(require("./type/transform/index"), exports);
__exportStar(require("./type/tuple/index"), exports);
__exportStar(require("./type/uint8array/index"), exports);
__exportStar(require("./type/undefined/index"), exports);
__exportStar(require("./type/union/index"), exports);
__exportStar(require("./type/unknown/index"), exports);
__exportStar(require("./type/unsafe/index"), exports);
__exportStar(require("./type/void/index"), exports);
// ------------------------------------------------------------------
// Type.*
// ------------------------------------------------------------------
__exportStar(require("./type/type/index"), exports);

2
extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/parser/index.d.ts generated vendored Normal file
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export * as Runtime from './runtime/index';
export * as Static from './static/index';

39
extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/parser/index.js generated vendored Normal file
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@ -0,0 +1,39 @@
"use strict";
var __createBinding = (this && this.__createBinding) || (Object.create ? (function(o, m, k, k2) {
if (k2 === undefined) k2 = k;
var desc = Object.getOwnPropertyDescriptor(m, k);
if (!desc || ("get" in desc ? !m.__esModule : desc.writable || desc.configurable)) {
desc = { enumerable: true, get: function() { return m[k]; } };
}
Object.defineProperty(o, k2, desc);
}) : (function(o, m, k, k2) {
if (k2 === undefined) k2 = k;
o[k2] = m[k];
}));
var __setModuleDefault = (this && this.__setModuleDefault) || (Object.create ? (function(o, v) {
Object.defineProperty(o, "default", { enumerable: true, value: v });
}) : function(o, v) {
o["default"] = v;
});
var __importStar = (this && this.__importStar) || (function () {
var ownKeys = function(o) {
ownKeys = Object.getOwnPropertyNames || function (o) {
var ar = [];
for (var k in o) if (Object.prototype.hasOwnProperty.call(o, k)) ar[ar.length] = k;
return ar;
};
return ownKeys(o);
};
return function (mod) {
if (mod && mod.__esModule) return mod;
var result = {};
if (mod != null) for (var k = ownKeys(mod), i = 0; i < k.length; i++) if (k[i] !== "default") __createBinding(result, mod, k[i]);
__setModuleDefault(result, mod);
return result;
};
})();
Object.defineProperty(exports, "__esModule", { value: true });
exports.Static = exports.Runtime = void 0;
exports.Runtime = __importStar(require("./runtime/index"));
exports.Static = __importStar(require("./static/index"));

23
extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/parser/runtime/guard.d.ts generated vendored Normal file
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import { IArray, IConst, IContext, IIdent, INumber, IOptional, IRef, IString, ITuple, IUnion } from './types';
/** Returns true if the value is a Array Parser */
export declare function IsArray(value: unknown): value is IArray;
/** Returns true if the value is a Const Parser */
export declare function IsConst(value: unknown): value is IConst;
/** Returns true if the value is a Context Parser */
export declare function IsContext(value: unknown): value is IContext;
/** Returns true if the value is a Ident Parser */
export declare function IsIdent(value: unknown): value is IIdent;
/** Returns true if the value is a Number Parser */
export declare function IsNumber(value: unknown): value is INumber;
/** Returns true if the value is a Optional Parser */
export declare function IsOptional(value: unknown): value is IOptional;
/** Returns true if the value is a Ref Parser */
export declare function IsRef(value: unknown): value is IRef;
/** Returns true if the value is a String Parser */
export declare function IsString(value: unknown): value is IString;
/** Returns true if the value is a Tuple Parser */
export declare function IsTuple(value: unknown): value is ITuple;
/** Returns true if the value is a Union Parser */
export declare function IsUnion(value: unknown): value is IUnion;
/** Returns true if the value is a Parser */
export declare function IsParser(value: unknown): value is IContext<unknown> | IUnion<unknown> | IArray<unknown> | IConst<unknown> | IIdent<unknown> | INumber<unknown> | IOptional<unknown> | IRef<unknown> | IString<unknown> | ITuple<unknown>;

86
extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/parser/runtime/guard.js generated vendored Normal file
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@ -0,0 +1,86 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.IsArray = IsArray;
exports.IsConst = IsConst;
exports.IsContext = IsContext;
exports.IsIdent = IsIdent;
exports.IsNumber = IsNumber;
exports.IsOptional = IsOptional;
exports.IsRef = IsRef;
exports.IsString = IsString;
exports.IsTuple = IsTuple;
exports.IsUnion = IsUnion;
exports.IsParser = IsParser;
// ------------------------------------------------------------------
// Value Guard
// ------------------------------------------------------------------
// prettier-ignore
function HasPropertyKey(value, key) {
return key in value;
}
// prettier-ignore
function IsObjectValue(value) {
return typeof value === 'object' && value !== null;
}
// prettier-ignore
function IsArrayValue(value) {
return globalThis.Array.isArray(value);
}
// ------------------------------------------------------------------
// Parser Guard
// ------------------------------------------------------------------
/** Returns true if the value is a Array Parser */
function IsArray(value) {
return IsObjectValue(value) && HasPropertyKey(value, 'type') && value.type === 'Array' && HasPropertyKey(value, 'parser') && IsObjectValue(value.parser);
}
/** Returns true if the value is a Const Parser */
function IsConst(value) {
return IsObjectValue(value) && HasPropertyKey(value, 'type') && value.type === 'Const' && HasPropertyKey(value, 'value') && typeof value.value === 'string';
}
/** Returns true if the value is a Context Parser */
function IsContext(value) {
return IsObjectValue(value) && HasPropertyKey(value, 'type') && value.type === 'Context' && HasPropertyKey(value, 'left') && IsParser(value.left) && HasPropertyKey(value, 'right') && IsParser(value.right);
}
/** Returns true if the value is a Ident Parser */
function IsIdent(value) {
return IsObjectValue(value) && HasPropertyKey(value, 'type') && value.type === 'Ident';
}
/** Returns true if the value is a Number Parser */
function IsNumber(value) {
return IsObjectValue(value) && HasPropertyKey(value, 'type') && value.type === 'Number';
}
/** Returns true if the value is a Optional Parser */
function IsOptional(value) {
return IsObjectValue(value) && HasPropertyKey(value, 'type') && value.type === 'Optional' && HasPropertyKey(value, 'parser') && IsObjectValue(value.parser);
}
/** Returns true if the value is a Ref Parser */
function IsRef(value) {
return IsObjectValue(value) && HasPropertyKey(value, 'type') && value.type === 'Ref' && HasPropertyKey(value, 'ref') && typeof value.ref === 'string';
}
/** Returns true if the value is a String Parser */
function IsString(value) {
return IsObjectValue(value) && HasPropertyKey(value, 'type') && value.type === 'String' && HasPropertyKey(value, 'options') && IsArrayValue(value.options);
}
/** Returns true if the value is a Tuple Parser */
function IsTuple(value) {
return IsObjectValue(value) && HasPropertyKey(value, 'type') && value.type === 'Tuple' && HasPropertyKey(value, 'parsers') && IsArrayValue(value.parsers);
}
/** Returns true if the value is a Union Parser */
function IsUnion(value) {
return IsObjectValue(value) && HasPropertyKey(value, 'type') && value.type === 'Union' && HasPropertyKey(value, 'parsers') && IsArrayValue(value.parsers);
}
/** Returns true if the value is a Parser */
function IsParser(value) {
// prettier-ignore
return (IsArray(value) ||
IsConst(value) ||
IsContext(value) ||
IsIdent(value) ||
IsNumber(value) ||
IsOptional(value) ||
IsRef(value) ||
IsString(value) ||
IsTuple(value) ||
IsUnion(value));
}

5
extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/parser/runtime/index.d.ts generated vendored Normal file
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@ -0,0 +1,5 @@
export * as Guard from './guard';
export * as Token from './token';
export * from './types';
export * from './module';
export * from './parse';

45
extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/parser/runtime/index.js generated vendored Normal file
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@ -0,0 +1,45 @@
"use strict";
var __createBinding = (this && this.__createBinding) || (Object.create ? (function(o, m, k, k2) {
if (k2 === undefined) k2 = k;
var desc = Object.getOwnPropertyDescriptor(m, k);
if (!desc || ("get" in desc ? !m.__esModule : desc.writable || desc.configurable)) {
desc = { enumerable: true, get: function() { return m[k]; } };
}
Object.defineProperty(o, k2, desc);
}) : (function(o, m, k, k2) {
if (k2 === undefined) k2 = k;
o[k2] = m[k];
}));
var __setModuleDefault = (this && this.__setModuleDefault) || (Object.create ? (function(o, v) {
Object.defineProperty(o, "default", { enumerable: true, value: v });
}) : function(o, v) {
o["default"] = v;
});
var __importStar = (this && this.__importStar) || (function () {
var ownKeys = function(o) {
ownKeys = Object.getOwnPropertyNames || function (o) {
var ar = [];
for (var k in o) if (Object.prototype.hasOwnProperty.call(o, k)) ar[ar.length] = k;
return ar;
};
return ownKeys(o);
};
return function (mod) {
if (mod && mod.__esModule) return mod;
var result = {};
if (mod != null) for (var k = ownKeys(mod), i = 0; i < k.length; i++) if (k[i] !== "default") __createBinding(result, mod, k[i]);
__setModuleDefault(result, mod);
return result;
};
})();
var __exportStar = (this && this.__exportStar) || function(m, exports) {
for (var p in m) if (p !== "default" && !Object.prototype.hasOwnProperty.call(exports, p)) __createBinding(exports, m, p);
};
Object.defineProperty(exports, "__esModule", { value: true });
exports.Token = exports.Guard = void 0;
exports.Guard = __importStar(require("./guard"));
exports.Token = __importStar(require("./token"));
__exportStar(require("./types"), exports);
__exportStar(require("./module"), exports);
__exportStar(require("./parse"), exports);

9
extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/parser/runtime/module.d.ts generated vendored Normal file
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import * as Types from './types';
export declare class Module<Properties extends Types.IModuleProperties = Types.IModuleProperties> {
private readonly properties;
constructor(properties: Properties);
/** Parses using one of the parsers defined on this instance */
Parse<Key extends keyof Properties>(key: Key, content: string, context: unknown): [] | [Types.StaticParser<Properties[Key]>, string];
/** Parses using one of the parsers defined on this instance */
Parse<Key extends keyof Properties>(key: Key, content: string): [] | [Types.StaticParser<Properties[Key]>, string];
}

22
extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/parser/runtime/module.js generated vendored Normal file
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@ -0,0 +1,22 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.Module = void 0;
const parse_1 = require("./parse");
// ------------------------------------------------------------------
// Module
// ------------------------------------------------------------------
class Module {
constructor(properties) {
this.properties = properties;
}
/** Parses using one of the parsers defined on this instance */
Parse(...args) {
// prettier-ignore
const [key, content, context] = (args.length === 3 ? [args[0], args[1], args[2]] :
args.length === 2 ? [args[0], args[1], undefined] :
(() => { throw Error('Invalid parse arguments'); })());
return (0, parse_1.Parse)(this.properties, this.properties[key], content, context);
}
}
exports.Module = Module;

9
extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/parser/runtime/parse.d.ts generated vendored Normal file
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@ -0,0 +1,9 @@
import * as Types from './types';
/** Parses content using the given Parser */
export declare function Parse<Parser extends Types.IParser>(moduleProperties: Types.IModuleProperties, parser: Parser, code: string, context: unknown): [] | [Types.StaticParser<Parser>, string];
/** Parses content using the given Parser */
export declare function Parse<Parser extends Types.IParser>(moduleProperties: Types.IModuleProperties, parser: Parser, code: string): [] | [Types.StaticParser<Parser>, string];
/** Parses content using the given Parser */
export declare function Parse<Parser extends Types.IParser>(parser: Parser, content: string, context: unknown): [] | [Types.StaticParser<Parser>, string];
/** Parses content using the given Parser */
export declare function Parse<Parser extends Types.IParser>(parser: Parser, content: string): [] | [Types.StaticParser<Parser>, string];

160
extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/parser/runtime/parse.js generated vendored Normal file
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@ -0,0 +1,160 @@
"use strict";
var __createBinding = (this && this.__createBinding) || (Object.create ? (function(o, m, k, k2) {
if (k2 === undefined) k2 = k;
var desc = Object.getOwnPropertyDescriptor(m, k);
if (!desc || ("get" in desc ? !m.__esModule : desc.writable || desc.configurable)) {
desc = { enumerable: true, get: function() { return m[k]; } };
}
Object.defineProperty(o, k2, desc);
}) : (function(o, m, k, k2) {
if (k2 === undefined) k2 = k;
o[k2] = m[k];
}));
var __setModuleDefault = (this && this.__setModuleDefault) || (Object.create ? (function(o, v) {
Object.defineProperty(o, "default", { enumerable: true, value: v });
}) : function(o, v) {
o["default"] = v;
});
var __importStar = (this && this.__importStar) || (function () {
var ownKeys = function(o) {
ownKeys = Object.getOwnPropertyNames || function (o) {
var ar = [];
for (var k in o) if (Object.prototype.hasOwnProperty.call(o, k)) ar[ar.length] = k;
return ar;
};
return ownKeys(o);
};
return function (mod) {
if (mod && mod.__esModule) return mod;
var result = {};
if (mod != null) for (var k = ownKeys(mod), i = 0; i < k.length; i++) if (k[i] !== "default") __createBinding(result, mod, k[i]);
__setModuleDefault(result, mod);
return result;
};
})();
Object.defineProperty(exports, "__esModule", { value: true });
exports.Parse = Parse;
const Guard = __importStar(require("./guard"));
const Token = __importStar(require("./token"));
// ------------------------------------------------------------------
// Context
// ------------------------------------------------------------------
function ParseContext(moduleProperties, left, right, code, context) {
const result = ParseParser(moduleProperties, left, code, context);
return result.length === 2 ? ParseParser(moduleProperties, right, result[1], result[0]) : [];
}
// ------------------------------------------------------------------
// Array
// ------------------------------------------------------------------
function ParseArray(moduleProperties, parser, code, context) {
const buffer = [];
let rest = code;
while (rest.length > 0) {
const result = ParseParser(moduleProperties, parser, rest, context);
if (result.length === 0)
return [buffer, rest];
buffer.push(result[0]);
rest = result[1];
}
return [buffer, rest];
}
// ------------------------------------------------------------------
// Const
// ------------------------------------------------------------------
function ParseConst(value, code, context) {
return Token.Const(value, code);
}
// ------------------------------------------------------------------
// Ident
// ------------------------------------------------------------------
function ParseIdent(code, _context) {
return Token.Ident(code);
}
// ------------------------------------------------------------------
// Number
// ------------------------------------------------------------------
// prettier-ignore
function ParseNumber(code, _context) {
return Token.Number(code);
}
// ------------------------------------------------------------------
// Optional
// ------------------------------------------------------------------
function ParseOptional(moduleProperties, parser, code, context) {
const result = ParseParser(moduleProperties, parser, code, context);
return (result.length === 2 ? [[result[0]], result[1]] : [[], code]);
}
// ------------------------------------------------------------------
// Ref
// ------------------------------------------------------------------
function ParseRef(moduleProperties, ref, code, context) {
const parser = moduleProperties[ref];
if (!Guard.IsParser(parser))
throw Error(`Cannot dereference Parser '${ref}'`);
return ParseParser(moduleProperties, parser, code, context);
}
// ------------------------------------------------------------------
// String
// ------------------------------------------------------------------
// prettier-ignore
function ParseString(options, code, _context) {
return Token.String(options, code);
}
// ------------------------------------------------------------------
// Tuple
// ------------------------------------------------------------------
function ParseTuple(moduleProperties, parsers, code, context) {
const buffer = [];
let rest = code;
for (const parser of parsers) {
const result = ParseParser(moduleProperties, parser, rest, context);
if (result.length === 0)
return [];
buffer.push(result[0]);
rest = result[1];
}
return [buffer, rest];
}
// ------------------------------------------------------------------
// Union
// ------------------------------------------------------------------
// prettier-ignore
function ParseUnion(moduleProperties, parsers, code, context) {
for (const parser of parsers) {
const result = ParseParser(moduleProperties, parser, code, context);
if (result.length === 0)
continue;
return result;
}
return [];
}
// ------------------------------------------------------------------
// Parser
// ------------------------------------------------------------------
// prettier-ignore
function ParseParser(moduleProperties, parser, code, context) {
const result = (Guard.IsContext(parser) ? ParseContext(moduleProperties, parser.left, parser.right, code, context) :
Guard.IsArray(parser) ? ParseArray(moduleProperties, parser.parser, code, context) :
Guard.IsConst(parser) ? ParseConst(parser.value, code, context) :
Guard.IsIdent(parser) ? ParseIdent(code, context) :
Guard.IsNumber(parser) ? ParseNumber(code, context) :
Guard.IsOptional(parser) ? ParseOptional(moduleProperties, parser.parser, code, context) :
Guard.IsRef(parser) ? ParseRef(moduleProperties, parser.ref, code, context) :
Guard.IsString(parser) ? ParseString(parser.options, code, context) :
Guard.IsTuple(parser) ? ParseTuple(moduleProperties, parser.parsers, code, context) :
Guard.IsUnion(parser) ? ParseUnion(moduleProperties, parser.parsers, code, context) :
[]);
return (result.length === 2
? [parser.mapping(result[0], context), result[1]]
: result);
}
/** Parses content using the given parser */
// prettier-ignore
function Parse(...args) {
const withModuleProperties = typeof args[1] === 'string' ? false : true;
const [moduleProperties, parser, content, context] = withModuleProperties
? [args[0], args[1], args[2], args[3]]
: [{}, args[0], args[1], args[2]];
return ParseParser(moduleProperties, parser, content, context);
}

8
extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/parser/runtime/token.d.ts generated vendored Normal file
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/** Takes the next constant string value skipping any whitespace */
export declare function Const(value: string, code: string): [] | [string, string];
/** Scans for the next Ident token */
export declare function Ident(code: string): [] | [string, string];
/** Scans for the next number token */
export declare function Number(code: string): [string, string] | [];
/** Scans the next Literal String value */
export declare function String(options: string[], code: string): [string, string] | [];

230
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"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.Const = Const;
exports.Ident = Ident;
exports.Number = Number;
exports.String = String;
// ------------------------------------------------------------------
// Chars
// ------------------------------------------------------------------
// prettier-ignore
var Chars;
(function (Chars) {
/** Returns true if the char code is a whitespace */
function IsWhitespace(value) {
return value === 32;
}
Chars.IsWhitespace = IsWhitespace;
/** Returns true if the char code is a newline */
function IsNewline(value) {
return value === 10;
}
Chars.IsNewline = IsNewline;
/** Returns true if the char code is a alpha */
function IsAlpha(value) {
return ((value >= 65 && value <= 90) || // A-Z
(value >= 97 && value <= 122) // a-z
);
}
Chars.IsAlpha = IsAlpha;
/** Returns true if the char code is zero */
function IsZero(value) {
return value === 48;
}
Chars.IsZero = IsZero;
/** Returns true if the char code is non-zero */
function IsNonZero(value) {
return value >= 49 && value <= 57;
}
Chars.IsNonZero = IsNonZero;
/** Returns true if the char code is a digit */
function IsDigit(value) {
return (IsNonZero(value) ||
IsZero(value));
}
Chars.IsDigit = IsDigit;
/** Returns true if the char code is a dot */
function IsDot(value) {
return value === 46;
}
Chars.IsDot = IsDot;
/** Returns true if this char code is a underscore */
function IsUnderscore(value) {
return value === 95;
}
Chars.IsUnderscore = IsUnderscore;
/** Returns true if this char code is a dollar sign */
function IsDollarSign(value) {
return value === 36;
}
Chars.IsDollarSign = IsDollarSign;
})(Chars || (Chars = {}));
// ------------------------------------------------------------------
// Trim
// ------------------------------------------------------------------
// prettier-ignore
var Trim;
(function (Trim) {
/** Trims Whitespace and retains Newline, Tabspaces, etc. */
function TrimWhitespaceOnly(code) {
for (let i = 0; i < code.length; i++) {
if (Chars.IsWhitespace(code.charCodeAt(i)))
continue;
return code.slice(i);
}
return code;
}
Trim.TrimWhitespaceOnly = TrimWhitespaceOnly;
/** Trims Whitespace including Newline, Tabspaces, etc. */
function TrimAll(code) {
return code.trimStart();
}
Trim.TrimAll = TrimAll;
})(Trim || (Trim = {}));
// ------------------------------------------------------------------
// Const
// ------------------------------------------------------------------
/** Checks the value matches the next string */
// prettier-ignore
function NextTokenCheck(value, code) {
if (value.length > code.length)
return false;
for (let i = 0; i < value.length; i++) {
if (value.charCodeAt(i) !== code.charCodeAt(i))
return false;
}
return true;
}
/** Gets the next constant string value or empty if no match */
// prettier-ignore
function NextConst(value, code) {
return NextTokenCheck(value, code)
? [code.slice(0, value.length), code.slice(value.length)]
: [];
}
/** Takes the next constant string value skipping any whitespace */
// prettier-ignore
function Const(value, code) {
if (value.length === 0)
return ['', code];
const char_0 = value.charCodeAt(0);
return (Chars.IsNewline(char_0) ? NextConst(value, Trim.TrimWhitespaceOnly(code)) :
Chars.IsWhitespace(char_0) ? NextConst(value, code) :
NextConst(value, Trim.TrimAll(code)));
}
// ------------------------------------------------------------------
// Ident
// ------------------------------------------------------------------
// prettier-ignore
function IdentIsFirst(char) {
return (Chars.IsAlpha(char) ||
Chars.IsDollarSign(char) ||
Chars.IsUnderscore(char));
}
// prettier-ignore
function IdentIsRest(char) {
return (Chars.IsAlpha(char) ||
Chars.IsDigit(char) ||
Chars.IsDollarSign(char) ||
Chars.IsUnderscore(char));
}
// prettier-ignore
function NextIdent(code) {
if (!IdentIsFirst(code.charCodeAt(0)))
return [];
for (let i = 1; i < code.length; i++) {
const char = code.charCodeAt(i);
if (IdentIsRest(char))
continue;
const slice = code.slice(0, i);
const rest = code.slice(i);
return [slice, rest];
}
return [code, ''];
}
/** Scans for the next Ident token */
// prettier-ignore
function Ident(code) {
return NextIdent(Trim.TrimAll(code));
}
// ------------------------------------------------------------------
// Number
// ------------------------------------------------------------------
/** Checks that the next number is not a leading zero */
// prettier-ignore
function NumberLeadingZeroCheck(code, index) {
const char_0 = code.charCodeAt(index + 0);
const char_1 = code.charCodeAt(index + 1);
return ((
// 1-9
Chars.IsNonZero(char_0)) || (
// 0
Chars.IsZero(char_0) &&
!Chars.IsDigit(char_1)) || (
// 0.
Chars.IsZero(char_0) &&
Chars.IsDot(char_1)) || (
// .0
Chars.IsDot(char_0) &&
Chars.IsDigit(char_1)));
}
/** Gets the next number token */
// prettier-ignore
function NextNumber(code) {
const negated = code.charAt(0) === '-';
const index = negated ? 1 : 0;
if (!NumberLeadingZeroCheck(code, index)) {
return [];
}
const dash = negated ? '-' : '';
let hasDot = false;
for (let i = index; i < code.length; i++) {
const char_i = code.charCodeAt(i);
if (Chars.IsDigit(char_i)) {
continue;
}
if (Chars.IsDot(char_i)) {
if (hasDot) {
const slice = code.slice(index, i);
const rest = code.slice(i);
return [`${dash}${slice}`, rest];
}
hasDot = true;
continue;
}
const slice = code.slice(index, i);
const rest = code.slice(i);
return [`${dash}${slice}`, rest];
}
return [code, ''];
}
/** Scans for the next number token */
// prettier-ignore
function Number(code) {
return NextNumber(Trim.TrimAll(code));
}
// ------------------------------------------------------------------
// String
// ------------------------------------------------------------------
// prettier-ignore
function NextString(options, code) {
const first = code.charAt(0);
if (!options.includes(first))
return [];
const quote = first;
for (let i = 1; i < code.length; i++) {
const char = code.charAt(i);
if (char === quote) {
const slice = code.slice(1, i);
const rest = code.slice(i + 1);
return [slice, rest];
}
}
return [];
}
/** Scans the next Literal String value */
// prettier-ignore
function String(options, code) {
return NextString(options, Trim.TrimAll(code));
}

98
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export type IModuleProperties = Record<PropertyKey, IParser>;
/** Force output static type evaluation for Arrays */
export type StaticEnsure<T> = T extends infer R ? R : never;
/** Infers the Output Parameter for a Parser */
export type StaticParser<Parser extends IParser> = Parser extends IParser<infer Output extends unknown> ? Output : unknown;
export type IMapping<Input extends unknown = any, Output extends unknown = unknown> = (input: Input, context: any) => Output;
/** Maps input to output. This is the default Mapping */
export declare const Identity: (value: unknown) => unknown;
/** Maps the output as the given parameter T */
export declare const As: <T>(mapping: T) => ((value: unknown) => T);
export interface IParser<Output extends unknown = unknown> {
type: string;
mapping: IMapping<any, Output>;
}
export type ContextParameter<_Left extends IParser, Right extends IParser> = (StaticParser<Right>);
export interface IContext<Output extends unknown = unknown> extends IParser<Output> {
type: 'Context';
left: IParser;
right: IParser;
}
/** `[Context]` Creates a Context Parser */
export declare function Context<Left extends IParser, Right extends IParser, Mapping extends IMapping = IMapping<ContextParameter<Left, Right>>>(left: Left, right: Right, mapping: Mapping): IContext<ReturnType<Mapping>>;
/** `[Context]` Creates a Context Parser */
export declare function Context<Left extends IParser, Right extends IParser>(left: Left, right: Right): IContext<ContextParameter<Left, Right>>;
export type ArrayParameter<Parser extends IParser> = StaticEnsure<StaticParser<Parser>[]>;
export interface IArray<Output extends unknown = unknown> extends IParser<Output> {
type: 'Array';
parser: IParser;
}
/** `[EBNF]` Creates an Array Parser */
export declare function Array<Parser extends IParser, Mapping extends IMapping = IMapping<ArrayParameter<Parser>>>(parser: Parser, mapping: Mapping): IArray<ReturnType<Mapping>>;
/** `[EBNF]` Creates an Array Parser */
export declare function Array<Parser extends IParser>(parser: Parser): IArray<ArrayParameter<Parser>>;
export interface IConst<Output extends unknown = unknown> extends IParser<Output> {
type: 'Const';
value: string;
}
/** `[TERM]` Creates a Const Parser */
export declare function Const<Value extends string, Mapping extends IMapping<Value>>(value: Value, mapping: Mapping): IConst<ReturnType<Mapping>>;
/** `[TERM]` Creates a Const Parser */
export declare function Const<Value extends string>(value: Value): IConst<Value>;
export interface IRef<Output extends unknown = unknown> extends IParser<Output> {
type: 'Ref';
ref: string;
}
/** `[BNF]` Creates a Ref Parser. This Parser can only be used in the context of a Module */
export declare function Ref<Type extends unknown, Mapping extends IMapping<Type>>(ref: string, mapping: Mapping): IRef<ReturnType<Mapping>>;
/** `[BNF]` Creates a Ref Parser. This Parser can only be used in the context of a Module */
export declare function Ref<Type extends unknown>(ref: string): IRef<Type>;
export interface IString<Output extends unknown = unknown> extends IParser<Output> {
type: 'String';
options: string[];
}
/** `[TERM]` Creates a String Parser. Options are an array of permissable quote characters */
export declare function String<Mapping extends IMapping<string>>(options: string[], mapping: Mapping): IString<ReturnType<Mapping>>;
/** `[TERM]` Creates a String Parser. Options are an array of permissable quote characters */
export declare function String(options: string[]): IString<string>;
export interface IIdent<Output extends unknown = unknown> extends IParser<Output> {
type: 'Ident';
}
/** `[TERM]` Creates an Ident Parser where Ident matches any valid JavaScript identifier */
export declare function Ident<Mapping extends IMapping<string>>(mapping: Mapping): IIdent<ReturnType<Mapping>>;
/** `[TERM]` Creates an Ident Parser where Ident matches any valid JavaScript identifier */
export declare function Ident(): IIdent<string>;
export interface INumber<Output extends unknown = unknown> extends IParser<Output> {
type: 'Number';
}
/** `[TERM]` Creates an Number Parser */
export declare function Number<Mapping extends IMapping<string>>(mapping: Mapping): INumber<ReturnType<Mapping>>;
/** `[TERM]` Creates an Number Parser */
export declare function Number(): INumber<string>;
export type OptionalParameter<Parser extends IParser, Result extends unknown = [StaticParser<Parser>] | []> = (Result);
export interface IOptional<Output extends unknown = unknown> extends IParser<Output> {
type: 'Optional';
parser: IParser;
}
/** `[EBNF]` Creates an Optional Parser */
export declare function Optional<Parser extends IParser, Mapping extends IMapping = IMapping<OptionalParameter<Parser>>>(parser: Parser, mapping: Mapping): IOptional<ReturnType<Mapping>>;
/** `[EBNF]` Creates an Optional Parser */
export declare function Optional<Parser extends IParser>(parser: Parser): IOptional<OptionalParameter<Parser>>;
export type TupleParameter<Parsers extends IParser[], Result extends unknown[] = []> = StaticEnsure<Parsers extends [infer Left extends IParser, ...infer Right extends IParser[]] ? TupleParameter<Right, [...Result, StaticEnsure<StaticParser<Left>>]> : Result>;
export interface ITuple<Output extends unknown = unknown> extends IParser<Output> {
type: 'Tuple';
parsers: IParser[];
}
/** `[BNF]` Creates a Tuple Parser */
export declare function Tuple<Parsers extends IParser[], Mapping extends IMapping = IMapping<TupleParameter<Parsers>>>(parsers: [...Parsers], mapping: Mapping): ITuple<ReturnType<Mapping>>;
/** `[BNF]` Creates a Tuple Parser */
export declare function Tuple<Parsers extends IParser[]>(parsers: [...Parsers]): ITuple<TupleParameter<Parsers>>;
export type UnionParameter<Parsers extends IParser[], Result extends unknown = never> = StaticEnsure<Parsers extends [infer Left extends IParser, ...infer Right extends IParser[]] ? UnionParameter<Right, Result | StaticParser<Left>> : Result>;
export interface IUnion<Output extends unknown = unknown> extends IParser<Output> {
type: 'Union';
parsers: IParser[];
}
/** `[BNF]` Creates a Union parser */
export declare function Union<Parsers extends IParser[], Mapping extends IMapping = IMapping<UnionParameter<Parsers>>>(parsers: [...Parsers], mapping: Mapping): IUnion<ReturnType<Mapping>>;
/** `[BNF]` Creates a Union parser */
export declare function Union<Parsers extends IParser[]>(parsers: [...Parsers]): IUnion<UnionParameter<Parsers>>;

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"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.As = exports.Identity = void 0;
exports.Context = Context;
exports.Array = Array;
exports.Const = Const;
exports.Ref = Ref;
exports.String = String;
exports.Ident = Ident;
exports.Number = Number;
exports.Optional = Optional;
exports.Tuple = Tuple;
exports.Union = Union;
/** Maps input to output. This is the default Mapping */
const Identity = (value) => value;
exports.Identity = Identity;
/** Maps the output as the given parameter T */
// prettier-ignore
const As = (mapping) => (_) => mapping;
exports.As = As;
/** `[Context]` Creates a Context Parser */
function Context(...args) {
const [left, right, mapping] = args.length === 3 ? [args[0], args[1], args[2]] : [args[0], args[1], exports.Identity];
return { type: 'Context', left, right, mapping };
}
/** `[EBNF]` Creates an Array Parser */
function Array(...args) {
const [parser, mapping] = args.length === 2 ? [args[0], args[1]] : [args[0], exports.Identity];
return { type: 'Array', parser, mapping };
}
/** `[TERM]` Creates a Const Parser */
function Const(...args) {
const [value, mapping] = args.length === 2 ? [args[0], args[1]] : [args[0], exports.Identity];
return { type: 'Const', value, mapping };
}
/** `[BNF]` Creates a Ref Parser. This Parser can only be used in the context of a Module */
function Ref(...args) {
const [ref, mapping] = args.length === 2 ? [args[0], args[1]] : [args[0], exports.Identity];
return { type: 'Ref', ref, mapping };
}
/** `[TERM]` Creates a String Parser. Options are an array of permissable quote characters */
function String(...params) {
const [options, mapping] = params.length === 2 ? [params[0], params[1]] : [params[0], exports.Identity];
return { type: 'String', options, mapping };
}
/** `[TERM]` Creates an Ident Parser where Ident matches any valid JavaScript identifier */
function Ident(...params) {
const mapping = params.length === 1 ? params[0] : exports.Identity;
return { type: 'Ident', mapping };
}
/** `[TERM]` Creates an Number Parser */
function Number(...params) {
const mapping = params.length === 1 ? params[0] : exports.Identity;
return { type: 'Number', mapping };
}
/** `[EBNF]` Creates an Optional Parser */
function Optional(...args) {
const [parser, mapping] = args.length === 2 ? [args[0], args[1]] : [args[0], exports.Identity];
return { type: 'Optional', parser, mapping };
}
/** `[BNF]` Creates a Tuple Parser */
function Tuple(...args) {
const [parsers, mapping] = args.length === 2 ? [args[0], args[1]] : [args[0], exports.Identity];
return { type: 'Tuple', parsers, mapping };
}
/** `[BNF]` Creates a Union parser */
function Union(...args) {
const [parsers, mapping] = args.length === 2 ? [args[0], args[1]] : [args[0], exports.Identity];
return { type: 'Union', parsers, mapping };
}

3
extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/parser/static/index.d.ts generated vendored Normal file
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export * as Token from './token';
export * from './parse';
export * from './types';

43
extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/parser/static/index.js generated vendored Normal file
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@ -0,0 +1,43 @@
"use strict";
var __createBinding = (this && this.__createBinding) || (Object.create ? (function(o, m, k, k2) {
if (k2 === undefined) k2 = k;
var desc = Object.getOwnPropertyDescriptor(m, k);
if (!desc || ("get" in desc ? !m.__esModule : desc.writable || desc.configurable)) {
desc = { enumerable: true, get: function() { return m[k]; } };
}
Object.defineProperty(o, k2, desc);
}) : (function(o, m, k, k2) {
if (k2 === undefined) k2 = k;
o[k2] = m[k];
}));
var __setModuleDefault = (this && this.__setModuleDefault) || (Object.create ? (function(o, v) {
Object.defineProperty(o, "default", { enumerable: true, value: v });
}) : function(o, v) {
o["default"] = v;
});
var __importStar = (this && this.__importStar) || (function () {
var ownKeys = function(o) {
ownKeys = Object.getOwnPropertyNames || function (o) {
var ar = [];
for (var k in o) if (Object.prototype.hasOwnProperty.call(o, k)) ar[ar.length] = k;
return ar;
};
return ownKeys(o);
};
return function (mod) {
if (mod && mod.__esModule) return mod;
var result = {};
if (mod != null) for (var k = ownKeys(mod), i = 0; i < k.length; i++) if (k[i] !== "default") __createBinding(result, mod, k[i]);
__setModuleDefault(result, mod);
return result;
};
})();
var __exportStar = (this && this.__exportStar) || function(m, exports) {
for (var p in m) if (p !== "default" && !Object.prototype.hasOwnProperty.call(exports, p)) __createBinding(exports, m, p);
};
Object.defineProperty(exports, "__esModule", { value: true });
exports.Token = void 0;
exports.Token = __importStar(require("./token"));
__exportStar(require("./parse"), exports);
__exportStar(require("./types"), exports);

20
extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/parser/static/parse.d.ts generated vendored Normal file
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import * as Tokens from './token';
import * as Types from './types';
type ContextParser<Left extends Types.IParser, Right extends Types.IParser, Code extends string, Context extends unknown> = (Parse<Left, Code, Context> extends [infer Context extends unknown, infer Rest extends string] ? Parse<Right, Rest, Context> : []);
type ArrayParser<Parser extends Types.IParser, Code extends string, Context extends unknown, Result extends unknown[] = []> = (Parse<Parser, Code, Context> extends [infer Value1 extends unknown, infer Rest extends string] ? ArrayParser<Parser, Rest, Context, [...Result, Value1]> : [Result, Code]);
type ConstParser<Value extends string, Code extends string, _Context extends unknown> = (Tokens.Const<Value, Code> extends [infer Match extends Value, infer Rest extends string] ? [Match, Rest] : []);
type IdentParser<Code extends string, _Context extends unknown> = (Tokens.Ident<Code> extends [infer Match extends string, infer Rest extends string] ? [Match, Rest] : []);
type NumberParser<Code extends string, _Context extends unknown> = (Tokens.Number<Code> extends [infer Match extends string, infer Rest extends string] ? [Match, Rest] : []);
type OptionalParser<Parser extends Types.IParser, Code extends string, Context extends unknown> = (Parse<Parser, Code, Context> extends [infer Value extends unknown, infer Rest extends string] ? [[Value], Rest] : [[], Code]);
type StringParser<Options extends string[], Code extends string, _Context extends unknown> = (Tokens.String<Options, Code> extends [infer Match extends string, infer Rest extends string] ? [Match, Rest] : []);
type TupleParser<Parsers extends Types.IParser[], Code extends string, Context extends unknown, Result extends unknown[] = []> = (Parsers extends [infer Left extends Types.IParser, ...infer Right extends Types.IParser[]] ? Parse<Left, Code, Context> extends [infer Value extends unknown, infer Rest extends string] ? TupleParser<Right, Rest, Context, [...Result, Value]> : [] : [Result, Code]);
type UnionParser<Parsers extends Types.IParser[], Code extends string, Context extends unknown> = (Parsers extends [infer Left extends Types.IParser, ...infer Right extends Types.IParser[]] ? Parse<Left, Code, Context> extends [infer Value extends unknown, infer Rest extends string] ? [Value, Rest] : UnionParser<Right, Code, Context> : []);
type ParseCode<Type extends Types.IParser, Code extends string, Context extends unknown = unknown> = (Type extends Types.Context<infer Left extends Types.IParser, infer Right extends Types.IParser> ? ContextParser<Left, Right, Code, Context> : Type extends Types.Array<infer Parser extends Types.IParser> ? ArrayParser<Parser, Code, Context> : Type extends Types.Const<infer Value extends string> ? ConstParser<Value, Code, Context> : Type extends Types.Ident ? IdentParser<Code, Context> : Type extends Types.Number ? NumberParser<Code, Context> : Type extends Types.Optional<infer Parser extends Types.IParser> ? OptionalParser<Parser, Code, Context> : Type extends Types.String<infer Options extends string[]> ? StringParser<Options, Code, Context> : Type extends Types.Tuple<infer Parsers extends Types.IParser[]> ? TupleParser<Parsers, Code, Context> : Type extends Types.Union<infer Parsers extends Types.IParser[]> ? UnionParser<Parsers, Code, Context> : [
]);
type ParseMapping<Parser extends Types.IParser, Result extends unknown, Context extends unknown = unknown> = ((Parser['mapping'] & {
input: Result;
context: Context;
})['output']);
/** Parses code with the given parser */
export type Parse<Type extends Types.IParser, Code extends string, Context extends unknown = unknown> = (ParseCode<Type, Code, Context> extends [infer L extends unknown, infer R extends string] ? [ParseMapping<Type, L, Context>, R] : []);
export {};

3
extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/parser/static/parse.js generated vendored Normal file
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"use strict";
Object.defineProperty(exports, "__esModule", { value: true });

108
extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/parser/static/token.d.ts generated vendored Normal file
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declare namespace Chars {
type Empty = '';
type Space = ' ';
type Newline = '\n';
type Dot = '.';
type Hyphen = '-';
type Digit = [
'0',
'1',
'2',
'3',
'4',
'5',
'6',
'7',
'8',
'9'
];
type Alpha = [
'a',
'b',
'c',
'd',
'e',
'f',
'g',
'h',
'i',
'j',
'k',
'l',
'm',
'n',
'o',
'p',
'q',
'r',
's',
't',
'u',
'v',
'w',
'x',
'y',
'z',
'A',
'B',
'C',
'D',
'E',
'F',
'G',
'H',
'I',
'J',
'K',
'L',
'M',
'N',
'O',
'P',
'Q',
'R',
'S',
'T',
'U',
'V',
'W',
'X',
'Y',
'Z'
];
}
declare namespace Trim {
type W4 = `${W3}${W3}`;
type W3 = `${W2}${W2}`;
type W2 = `${W1}${W1}`;
type W1 = `${W0}${W0}`;
type W0 = ` `;
/** Trims whitespace only */
export type TrimWhitespace<Code extends string> = (Code extends `${W4}${infer Rest extends string}` ? TrimWhitespace<Rest> : Code extends `${W3}${infer Rest extends string}` ? TrimWhitespace<Rest> : Code extends `${W1}${infer Rest extends string}` ? TrimWhitespace<Rest> : Code extends `${W0}${infer Rest extends string}` ? TrimWhitespace<Rest> : Code);
/** Trims Whitespace and Newline */
export type TrimAll<Code extends string> = (Code extends `${W4}${infer Rest extends string}` ? TrimAll<Rest> : Code extends `${W3}${infer Rest extends string}` ? TrimAll<Rest> : Code extends `${W1}${infer Rest extends string}` ? TrimAll<Rest> : Code extends `${W0}${infer Rest extends string}` ? TrimAll<Rest> : Code extends `${Chars.Newline}${infer Rest extends string}` ? TrimAll<Rest> : Code);
export {};
}
/** Scans for the next match union */
type NextUnion<Variants extends string[], Code extends string> = (Variants extends [infer Variant extends string, ...infer Rest1 extends string[]] ? NextConst<Variant, Code> extends [infer Match extends string, infer Rest2 extends string] ? [Match, Rest2] : NextUnion<Rest1, Code> : []);
type NextConst<Value extends string, Code extends string> = (Code extends `${Value}${infer Rest extends string}` ? [Value, Rest] : []);
/** Scans for the next constant value */
export type Const<Value extends string, Code extends string> = (Value extends '' ? ['', Code] : Value extends `${infer First extends string}${string}` ? (First extends Chars.Newline ? NextConst<Value, Trim.TrimWhitespace<Code>> : First extends Chars.Space ? NextConst<Value, Code> : NextConst<Value, Trim.TrimAll<Code>>) : never);
type NextNumberNegate<Code extends string> = (Code extends `${Chars.Hyphen}${infer Rest extends string}` ? [Chars.Hyphen, Rest] : [Chars.Empty, Code]);
type NextNumberZeroCheck<Code extends string> = (Code extends `0${infer Rest}` ? NextUnion<Chars.Digit, Rest> extends [string, string] ? false : true : true);
type NextNumberScan<Code extends string, HasDecimal extends boolean = false, Result extends string = Chars.Empty> = (NextUnion<[...Chars.Digit, Chars.Dot], Code> extends [infer Char extends string, infer Rest extends string] ? Char extends Chars.Dot ? HasDecimal extends false ? NextNumberScan<Rest, true, `${Result}${Char}`> : [Result, `.${Rest}`] : NextNumberScan<Rest, HasDecimal, `${Result}${Char}`> : [Result, Code]);
export type NextNumber<Code extends string> = (NextNumberNegate<Code> extends [infer Negate extends string, infer Rest extends string] ? NextNumberZeroCheck<Rest> extends true ? NextNumberScan<Rest> extends [infer Number extends string, infer Rest2 extends string] ? Number extends Chars.Empty ? [] : [`${Negate}${Number}`, Rest2] : [] : [] : []);
/** Scans for the next literal number */
export type Number<Code extends string> = NextNumber<Trim.TrimAll<Code>>;
type NextStringQuote<Options extends string[], Code extends string> = NextUnion<Options, Code>;
type NextStringBody<Code extends string, Quote extends string, Result extends string = Chars.Empty> = (Code extends `${infer Char extends string}${infer Rest extends string}` ? Char extends Quote ? [Result, Rest] : NextStringBody<Rest, Quote, `${Result}${Char}`> : []);
type NextString<Options extends string[], Code extends string> = (NextStringQuote<Options, Code> extends [infer Quote extends string, infer Rest extends string] ? NextStringBody<Rest, Quote> extends [infer String extends string, infer Rest extends string] ? [String, Rest] : [] : []);
/** Scans for the next literal string */
export type String<Options extends string[], Code extends string> = NextString<Options, Trim.TrimAll<Code>>;
type IdentLeft = [...Chars.Alpha, '_', '$'];
type IdentRight = [...Chars.Digit, ...IdentLeft];
type NextIdentScan<Code extends string, Result extends string = Chars.Empty> = (NextUnion<IdentRight, Code> extends [infer Char extends string, infer Rest extends string] ? NextIdentScan<Rest, `${Result}${Char}`> : [Result, Code]);
type NextIdent<Code extends string> = (NextUnion<IdentLeft, Code> extends [infer Left extends string, infer Rest1 extends string] ? NextIdentScan<Rest1> extends [infer Right extends string, infer Rest2 extends string] ? [`${Left}${Right}`, Rest2] : [] : []);
/** Scans for the next Ident */
export type Ident<Code extends string> = NextIdent<Trim.TrimAll<Code>>;
export {};

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"use strict";
Object.defineProperty(exports, "__esModule", { value: true });

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/**
* `[ACTION]` Inference mapping base type. Used to specify semantic actions for
* Parser productions. This type is implemented as a higher-kinded type where
* productions are received on the `input` property with mapping assigned
* the `output` property. The parsing context is available on the `context`
* property.
*/
export interface IMapping {
context: unknown;
input: unknown;
output: unknown;
}
/** `[ACTION]` Default inference mapping. */
export interface Identity extends IMapping {
output: this['input'];
}
/** `[ACTION]` Maps the given argument `T` as the mapping output */
export interface As<T> extends IMapping {
output: T;
}
/** Base type Parser implemented by all other parsers */
export interface IParser<Mapping extends IMapping = Identity> {
type: string;
mapping: Mapping;
}
/** `[Context]` Creates a Context Parser */
export interface Context<Left extends IParser = IParser, Right extends IParser = IParser, Mapping extends IMapping = Identity> extends IParser<Mapping> {
type: 'Context';
left: Left;
right: Right;
}
/** `[EBNF]` Creates an Array Parser */
export interface Array<Parser extends IParser = IParser, Mapping extends IMapping = Identity> extends IParser<Mapping> {
type: 'Array';
parser: Parser;
}
/** `[TERM]` Creates a Const Parser */
export interface Const<Value extends string = string, Mapping extends IMapping = Identity> extends IParser<Mapping> {
type: 'Const';
value: Value;
}
/** `[TERM]` Creates an Ident Parser. */
export interface Ident<Mapping extends IMapping = Identity> extends IParser<Mapping> {
type: 'Ident';
}
/** `[TERM]` Creates a Number Parser. */
export interface Number<Mapping extends IMapping = Identity> extends IParser<Mapping> {
type: 'Number';
}
/** `[EBNF]` Creates a Optional Parser */
export interface Optional<Parser extends IParser = IParser, Mapping extends IMapping = Identity> extends IParser<Mapping> {
type: 'Optional';
parser: Parser;
}
/** `[TERM]` Creates a String Parser. Options are an array of permissable quote characters */
export interface String<Options extends string[], Mapping extends IMapping = Identity> extends IParser<Mapping> {
type: 'String';
quote: Options;
}
/** `[BNF]` Creates a Tuple Parser */
export interface Tuple<Parsers extends IParser[] = [], Mapping extends IMapping = Identity> extends IParser<Mapping> {
type: 'Tuple';
parsers: [...Parsers];
}
/** `[BNF]` Creates a Union Parser */
export interface Union<Parsers extends IParser[] = [], Mapping extends IMapping = Identity> extends IParser<Mapping> {
type: 'Union';
parsers: [...Parsers];
}

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"use strict";
Object.defineProperty(exports, "__esModule", { value: true });

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export * from './syntax';

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"use strict";
var __createBinding = (this && this.__createBinding) || (Object.create ? (function(o, m, k, k2) {
if (k2 === undefined) k2 = k;
var desc = Object.getOwnPropertyDescriptor(m, k);
if (!desc || ("get" in desc ? !m.__esModule : desc.writable || desc.configurable)) {
desc = { enumerable: true, get: function() { return m[k]; } };
}
Object.defineProperty(o, k2, desc);
}) : (function(o, m, k, k2) {
if (k2 === undefined) k2 = k;
o[k2] = m[k];
}));
var __exportStar = (this && this.__exportStar) || function(m, exports) {
for (var p in m) if (p !== "default" && !Object.prototype.hasOwnProperty.call(exports, p)) __createBinding(exports, m, p);
};
Object.defineProperty(exports, "__esModule", { value: true });
__exportStar(require("./syntax"), exports);

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import * as T from '../type/index';
type TDereference<Context extends T.TProperties, Key extends string> = (Key extends keyof Context ? Context[Key] : T.TRef<Key>);
type TDelimitedDecode<Input extends ([unknown, unknown] | unknown)[], Result extends unknown[] = []> = (Input extends [infer Left, ...infer Right] ? Left extends [infer Item, infer _] ? TDelimitedDecode<Right, [...Result, Item]> : TDelimitedDecode<Right, [...Result, Left]> : Result);
type TDelimited<Input extends [unknown, unknown]> = Input extends [infer Left extends unknown[], infer Right extends unknown[]] ? TDelimitedDecode<[...Left, ...Right]> : [];
export type TGenericReferenceParameterListMapping<Input extends [unknown, unknown], Context extends T.TProperties> = TDelimited<Input>;
export declare function GenericReferenceParameterListMapping(input: [unknown, unknown], context: unknown): unknown[];
export type TGenericReferenceMapping<Input extends [unknown, unknown, unknown, unknown], Context extends T.TProperties, Result = Context extends T.TProperties ? Input extends [infer Reference extends string, '<', infer Args extends T.TSchema[], '>'] ? T.TInstantiate<TDereference<Context, Reference>, Args> : never : never> = Result;
export declare function GenericReferenceMapping(input: [unknown, unknown, unknown, unknown], context: unknown): T.TSchema;
export type TGenericArgumentsListMapping<Input extends [unknown, unknown], Context extends T.TProperties> = TDelimited<Input>;
export declare function GenericArgumentsListMapping(input: [unknown, unknown], context: unknown): unknown[];
type GenericArgumentsContext<Arguments extends string[], Context extends T.TProperties, Result extends T.TProperties = {}> = (Arguments extends [...infer Left extends string[], infer Right extends string] ? GenericArgumentsContext<Left, Context, Result & {
[_ in Right]: T.TArgument<Left['length']>;
}> : T.Evaluate<Result & Context>);
export type TGenericArgumentsMapping<Input extends [unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['<', infer Arguments extends string[], '>'] ? Context extends infer Context extends T.TProperties ? GenericArgumentsContext<Arguments, Context> : never : never;
declare const GenericArgumentsContext: (_arguments: string[], context: T.TProperties) => T.TProperties;
export declare function GenericArgumentsMapping(input: [unknown, unknown, unknown], context: unknown): T.TProperties;
export type TKeywordStringMapping<Input extends 'string', Context extends T.TProperties> = T.TString;
export declare function KeywordStringMapping(input: 'string', context: unknown): T.TString;
export type TKeywordNumberMapping<Input extends 'number', Context extends T.TProperties> = T.TNumber;
export declare function KeywordNumberMapping(input: 'number', context: unknown): T.TNumber;
export type TKeywordBooleanMapping<Input extends 'boolean', Context extends T.TProperties> = T.TBoolean;
export declare function KeywordBooleanMapping(input: 'boolean', context: unknown): T.TBoolean;
export type TKeywordUndefinedMapping<Input extends 'undefined', Context extends T.TProperties> = T.TUndefined;
export declare function KeywordUndefinedMapping(input: 'undefined', context: unknown): T.TUndefined;
export type TKeywordNullMapping<Input extends 'null', Context extends T.TProperties> = T.TNull;
export declare function KeywordNullMapping(input: 'null', context: unknown): T.TNull;
export type TKeywordIntegerMapping<Input extends 'integer', Context extends T.TProperties> = T.TInteger;
export declare function KeywordIntegerMapping(input: 'integer', context: unknown): T.TInteger;
export type TKeywordBigIntMapping<Input extends 'bigint', Context extends T.TProperties> = T.TBigInt;
export declare function KeywordBigIntMapping(input: 'bigint', context: unknown): T.TBigInt;
export type TKeywordUnknownMapping<Input extends 'unknown', Context extends T.TProperties> = T.TUnknown;
export declare function KeywordUnknownMapping(input: 'unknown', context: unknown): T.TUnknown;
export type TKeywordAnyMapping<Input extends 'any', Context extends T.TProperties> = T.TAny;
export declare function KeywordAnyMapping(input: 'any', context: unknown): T.TAny;
export type TKeywordNeverMapping<Input extends 'never', Context extends T.TProperties> = T.TNever;
export declare function KeywordNeverMapping(input: 'never', context: unknown): T.TNever;
export type TKeywordSymbolMapping<Input extends 'symbol', Context extends T.TProperties> = T.TSymbol;
export declare function KeywordSymbolMapping(input: 'symbol', context: unknown): T.TSymbol;
export type TKeywordVoidMapping<Input extends 'void', Context extends T.TProperties> = T.TVoid;
export declare function KeywordVoidMapping(input: 'void', context: unknown): T.TVoid;
export type TKeywordMapping<Input extends unknown, Context extends T.TProperties> = Input;
export declare function KeywordMapping(input: unknown, context: unknown): unknown;
export type TLiteralStringMapping<Input extends string, Context extends T.TProperties> = Input extends T.TLiteralValue ? T.TLiteral<Input> : never;
export declare function LiteralStringMapping(input: string, context: unknown): T.TLiteral<string>;
export type TLiteralNumberMapping<Input extends string, Context extends T.TProperties> = Input extends `${infer Value extends number}` ? T.TLiteral<Value> : never;
export declare function LiteralNumberMapping(input: string, context: unknown): T.TLiteral<number>;
export type TLiteralBooleanMapping<Input extends 'true' | 'false', Context extends T.TProperties> = Input extends 'true' ? T.TLiteral<true> : T.TLiteral<false>;
export declare function LiteralBooleanMapping(input: 'true' | 'false', context: unknown): T.TLiteral<boolean>;
export type TLiteralMapping<Input extends unknown, Context extends T.TProperties> = Input;
export declare function LiteralMapping(input: unknown, context: unknown): unknown;
export type TKeyOfMapping<Input extends [unknown] | [], Context extends T.TProperties> = Input extends [unknown] ? true : false;
export declare function KeyOfMapping(input: [unknown] | [], context: unknown): boolean;
type TIndexArrayMappingReduce<Input extends unknown[], Result extends unknown[] = []> = (Input extends [infer Left extends unknown, ...infer Right extends unknown[]] ? Left extends ['[', infer Type extends T.TSchema, ']'] ? TIndexArrayMappingReduce<Right, [...Result, [Type]]> : TIndexArrayMappingReduce<Right, [...Result, []]> : Result);
export type TIndexArrayMapping<Input extends ([unknown, unknown, unknown] | [unknown, unknown])[], Context extends T.TProperties> = Input extends unknown[] ? TIndexArrayMappingReduce<Input> : [];
export declare function IndexArrayMapping(input: ([unknown, unknown, unknown] | [unknown, unknown])[], context: unknown): unknown[];
export type TExtendsMapping<Input extends [unknown, unknown, unknown, unknown, unknown, unknown] | [], Context extends T.TProperties> = Input extends ['extends', infer Type extends T.TSchema, '?', infer True extends T.TSchema, ':', infer False extends T.TSchema] ? [Type, True, False] : [];
export declare function ExtendsMapping(input: [unknown, unknown, unknown, unknown, unknown, unknown] | [], context: unknown): unknown[];
export type TBaseMapping<Input extends [unknown, unknown, unknown] | unknown, Context extends T.TProperties> = (Input extends ['(', infer Type extends T.TSchema, ')'] ? Type : Input extends infer Type extends T.TSchema ? Type : never);
export declare function BaseMapping(input: [unknown, unknown, unknown] | unknown, context: unknown): unknown;
type TFactorIndexArray<Type extends T.TSchema, IndexArray extends unknown[]> = (IndexArray extends [...infer Left extends unknown[], infer Right extends T.TSchema[]] ? (Right extends [infer Indexer extends T.TSchema] ? T.TIndex<TFactorIndexArray<Type, Left>, T.TIndexPropertyKeys<Indexer>> : Right extends [] ? T.TArray<TFactorIndexArray<Type, Left>> : T.TNever) : Type);
type TFactorExtends<Type extends T.TSchema, Extends extends unknown[]> = (Extends extends [infer Right extends T.TSchema, infer True extends T.TSchema, infer False extends T.TSchema] ? T.TExtends<Type, Right, True, False> : Type);
export type TFactorMapping<Input extends [unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends [infer KeyOf extends boolean, infer Type extends T.TSchema, infer IndexArray extends unknown[], infer Extends extends unknown[]] ? KeyOf extends true ? TFactorExtends<T.TKeyOf<TFactorIndexArray<Type, IndexArray>>, Extends> : TFactorExtends<TFactorIndexArray<Type, IndexArray>, Extends> : never;
export declare function FactorMapping(input: [unknown, unknown, unknown, unknown], context: unknown): T.TSchema;
type TExprBinaryMapping<Left extends T.TSchema, Rest extends unknown[]> = (Rest extends [infer Operator extends unknown, infer Right extends T.TSchema, infer Next extends unknown[]] ? (TExprBinaryMapping<Right, Next> extends infer Schema extends T.TSchema ? (Operator extends '&' ? (Schema extends T.TIntersect<infer Types extends T.TSchema[]> ? T.TIntersect<[Left, ...Types]> : T.TIntersect<[Left, Schema]>) : Operator extends '|' ? (Schema extends T.TUnion<infer Types extends T.TSchema[]> ? T.TUnion<[Left, ...Types]> : T.TUnion<[Left, Schema]>) : never) : never) : Left);
export type TExprTermTailMapping<Input extends [unknown, unknown, unknown] | [], Context extends T.TProperties> = Input;
export declare function ExprTermTailMapping(input: [unknown, unknown, unknown] | [], context: unknown): [] | [unknown, unknown, unknown];
export type TExprTermMapping<Input extends [unknown, unknown], Context extends T.TProperties> = (Input extends [infer Left extends T.TSchema, infer Rest extends unknown[]] ? TExprBinaryMapping<Left, Rest> : []);
export declare function ExprTermMapping(input: [unknown, unknown], context: unknown): T.TSchema;
export type TExprTailMapping<Input extends [unknown, unknown, unknown] | [], Context extends T.TProperties> = Input;
export declare function ExprTailMapping(input: [unknown, unknown, unknown] | [], context: unknown): [] | [unknown, unknown, unknown];
export type TExprMapping<Input extends [unknown, unknown], Context extends T.TProperties> = Input extends [infer Left extends T.TSchema, infer Rest extends unknown[]] ? TExprBinaryMapping<Left, Rest> : [];
export declare function ExprMapping(input: [unknown, unknown], context: unknown): T.TSchema;
export type TTypeMapping<Input extends unknown, Context extends T.TProperties> = Input;
export declare function TypeMapping(input: unknown, context: unknown): unknown;
export type TPropertyKeyMapping<Input extends string, Context extends T.TProperties> = Input;
export declare function PropertyKeyMapping(input: string, context: unknown): string;
export type TReadonlyMapping<Input extends [unknown] | [], Context extends T.TProperties> = Input extends [unknown] ? true : false;
export declare function ReadonlyMapping(input: [unknown] | [], context: unknown): boolean;
export type TOptionalMapping<Input extends [unknown] | [], Context extends T.TProperties> = Input extends [unknown] ? true : false;
export declare function OptionalMapping(input: [unknown] | [], context: unknown): boolean;
export type TPropertyMapping<Input extends [unknown, unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends [infer IsReadonly extends boolean, infer Key extends string, infer IsOptional extends boolean, string, infer Type extends T.TSchema] ? {
[_ in Key]: ([
IsReadonly,
IsOptional
] extends [true, true] ? T.TReadonlyOptional<Type> : [
IsReadonly,
IsOptional
] extends [true, false] ? T.TReadonly<Type> : [
IsReadonly,
IsOptional
] extends [false, true] ? T.TOptional<Type> : Type);
} : never;
export declare function PropertyMapping(input: [unknown, unknown, unknown, unknown, unknown], context: unknown): {
[x: string]: T.TSchema;
};
export type TPropertyDelimiterMapping<Input extends [unknown, unknown] | [unknown], Context extends T.TProperties> = Input;
export declare function PropertyDelimiterMapping(input: [unknown, unknown] | [unknown], context: unknown): [unknown] | [unknown, unknown];
export type TPropertyListMapping<Input extends [unknown, unknown], Context extends T.TProperties> = TDelimited<Input>;
export declare function PropertyListMapping(input: [unknown, unknown], context: unknown): unknown[];
type TObjectMappingReduce<PropertiesList extends T.TProperties[], Result extends T.TProperties = {}> = (PropertiesList extends [infer Left extends T.TProperties, ...infer Right extends T.TProperties[]] ? TObjectMappingReduce<Right, Result & Left> : {
[Key in keyof Result]: Result[Key];
});
export type TObjectMapping<Input extends [unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['{', infer PropertyList extends T.TProperties[], '}'] ? T.TObject<TObjectMappingReduce<PropertyList>> : never;
export declare function ObjectMapping(input: [unknown, unknown, unknown], context: unknown): T.TObject<T.TProperties>;
export type TElementListMapping<Input extends [unknown, unknown], Context extends T.TProperties> = TDelimited<Input>;
export declare function ElementListMapping(input: [unknown, unknown], context: unknown): unknown[];
export type TTupleMapping<Input extends [unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['[', infer Types extends T.TSchema[], ']'] ? T.TTuple<Types> : never;
export declare function TupleMapping(input: [unknown, unknown, unknown], context: unknown): T.TTuple<T.TSchema[]>;
export type TParameterMapping<Input extends [unknown, unknown, unknown], Context extends T.TProperties> = Input extends [string, ':', infer Type extends T.TSchema] ? Type : never;
export declare function ParameterMapping(input: [unknown, unknown, unknown], context: unknown): T.TSchema;
export type TParameterListMapping<Input extends [unknown, unknown], Context extends T.TProperties> = TDelimited<Input>;
export declare function ParameterListMapping(input: [unknown, unknown], context: unknown): unknown[];
export type TFunctionMapping<Input extends [unknown, unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['(', infer ParameterList extends T.TSchema[], ')', '=>', infer ReturnType extends T.TSchema] ? T.TFunction<ParameterList, ReturnType> : never;
export declare function FunctionMapping(input: [unknown, unknown, unknown, unknown, unknown], context: unknown): T.TFunction<T.TSchema[], T.TSchema>;
export type TConstructorMapping<Input extends [unknown, unknown, unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['new', '(', infer ParameterList extends T.TSchema[], ')', '=>', infer InstanceType extends T.TSchema] ? T.TConstructor<ParameterList, InstanceType> : never;
export declare function ConstructorMapping(input: [unknown, unknown, unknown, unknown, unknown, unknown], context: unknown): T.TConstructor<T.TSchema[], T.TSchema>;
export type TMappedMapping<Input extends [unknown, unknown, unknown, unknown, unknown, unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['{', '[', infer _Key extends string, 'in', infer _Right extends T.TSchema, ']', ':', infer _Type extends T.TSchema, '}'] ? T.TLiteral<'Mapped types not supported'> : never;
export declare function MappedMapping(input: [unknown, unknown, unknown, unknown, unknown, unknown, unknown, unknown, unknown], context: unknown): T.TLiteral<"Mapped types not supported">;
export type TAsyncIteratorMapping<Input extends [unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['AsyncIterator', '<', infer Type extends T.TSchema, '>'] ? T.TAsyncIterator<Type> : never;
export declare function AsyncIteratorMapping(input: [unknown, unknown, unknown, unknown], context: unknown): T.TAsyncIterator<T.TSchema>;
export type TIteratorMapping<Input extends [unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['Iterator', '<', infer Type extends T.TSchema, '>'] ? T.TIterator<Type> : never;
export declare function IteratorMapping(input: [unknown, unknown, unknown, unknown], context: unknown): T.TIterator<T.TSchema>;
export type TArgumentMapping<Input extends [unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['Argument', '<', infer Type extends T.TSchema, '>'] ? Type extends T.TLiteral<infer Index extends number> ? T.TArgument<Index> : T.TNever : never;
export declare function ArgumentMapping(input: [unknown, unknown, unknown, unknown], context: unknown): T.TNever | T.TArgument<number>;
export type TAwaitedMapping<Input extends [unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['Awaited', '<', infer Type extends T.TSchema, '>'] ? T.TAwaited<Type> : never;
export declare function AwaitedMapping(input: [unknown, unknown, unknown, unknown], context: unknown): T.TSchema;
export type TArrayMapping<Input extends [unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['Array', '<', infer Type extends T.TSchema, '>'] ? T.TArray<Type> : never;
export declare function ArrayMapping(input: [unknown, unknown, unknown, unknown], context: unknown): T.TArray<T.TSchema>;
export type TRecordMapping<Input extends [unknown, unknown, unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['Record', '<', infer Key extends T.TSchema, ',', infer Type extends T.TSchema, '>'] ? T.TRecordOrObject<Key, Type> : never;
export declare function RecordMapping(input: [unknown, unknown, unknown, unknown, unknown, unknown], context: unknown): T.TNever;
export type TPromiseMapping<Input extends [unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['Promise', '<', infer Type extends T.TSchema, '>'] ? T.TPromise<Type> : never;
export declare function PromiseMapping(input: [unknown, unknown, unknown, unknown], context: unknown): T.TPromise<T.TSchema>;
export type TConstructorParametersMapping<Input extends [unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['ConstructorParameters', '<', infer Type extends T.TSchema, '>'] ? T.TConstructorParameters<Type> : never;
export declare function ConstructorParametersMapping(input: [unknown, unknown, unknown, unknown], context: unknown): T.TNever;
export type TFunctionParametersMapping<Input extends [unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['Parameters', '<', infer Type extends T.TSchema, '>'] ? T.TParameters<Type> : never;
export declare function FunctionParametersMapping(input: [unknown, unknown, unknown, unknown], context: unknown): T.TNever;
export type TInstanceTypeMapping<Input extends [unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['InstanceType', '<', infer Type extends T.TSchema, '>'] ? T.TInstanceType<Type> : never;
export declare function InstanceTypeMapping(input: [unknown, unknown, unknown, unknown], context: unknown): T.TNever;
export type TReturnTypeMapping<Input extends [unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['ReturnType', '<', infer Type extends T.TSchema, '>'] ? T.TReturnType<Type> : never;
export declare function ReturnTypeMapping(input: [unknown, unknown, unknown, unknown], context: unknown): T.TNever;
export type TPartialMapping<Input extends [unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['Partial', '<', infer Type extends T.TSchema, '>'] ? T.TPartial<Type> : never;
export declare function PartialMapping(input: [unknown, unknown, unknown, unknown], context: unknown): T.TObject<{}>;
export type TRequiredMapping<Input extends [unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['Required', '<', infer Type extends T.TSchema, '>'] ? T.TRequired<Type> : never;
export declare function RequiredMapping(input: [unknown, unknown, unknown, unknown], context: unknown): T.TObject<{}>;
export type TPickMapping<Input extends [unknown, unknown, unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['Pick', '<', infer Type extends T.TSchema, ',', infer Key extends T.TSchema, '>'] ? T.TPick<Type, Key> : never;
export declare function PickMapping(input: [unknown, unknown, unknown, unknown, unknown, unknown], context: unknown): T.TObject<{}>;
export type TOmitMapping<Input extends [unknown, unknown, unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['Omit', '<', infer Type extends T.TSchema, ',', infer Key extends T.TSchema, '>'] ? T.TOmit<Type, Key> : never;
export declare function OmitMapping(input: [unknown, unknown, unknown, unknown, unknown, unknown], context: unknown): T.TObject<{}>;
export type TExcludeMapping<Input extends [unknown, unknown, unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['Exclude', '<', infer Type extends T.TSchema, ',', infer Key extends T.TSchema, '>'] ? T.TExclude<Type, Key> : never;
export declare function ExcludeMapping(input: [unknown, unknown, unknown, unknown, unknown, unknown], context: unknown): T.TNever;
export type TExtractMapping<Input extends [unknown, unknown, unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['Extract', '<', infer Type extends T.TSchema, ',', infer Key extends T.TSchema, '>'] ? T.TExtract<Type, Key> : never;
export declare function ExtractMapping(input: [unknown, unknown, unknown, unknown, unknown, unknown], context: unknown): T.TSchema;
export type TUppercaseMapping<Input extends [unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['Uppercase', '<', infer Type extends T.TSchema, '>'] ? T.TUppercase<Type> : never;
export declare function UppercaseMapping(input: [unknown, unknown, unknown, unknown], context: unknown): T.TSchema;
export type TLowercaseMapping<Input extends [unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['Lowercase', '<', infer Type extends T.TSchema, '>'] ? T.TLowercase<Type> : never;
export declare function LowercaseMapping(input: [unknown, unknown, unknown, unknown], context: unknown): T.TSchema;
export type TCapitalizeMapping<Input extends [unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['Capitalize', '<', infer Type extends T.TSchema, '>'] ? T.TCapitalize<Type> : never;
export declare function CapitalizeMapping(input: [unknown, unknown, unknown, unknown], context: unknown): T.TSchema;
export type TUncapitalizeMapping<Input extends [unknown, unknown, unknown, unknown], Context extends T.TProperties> = Input extends ['Uncapitalize', '<', infer Type extends T.TSchema, '>'] ? T.TUncapitalize<Type> : never;
export declare function UncapitalizeMapping(input: [unknown, unknown, unknown, unknown], context: unknown): T.TSchema;
export type TDateMapping<Input extends 'Date', Context extends T.TProperties> = T.TDate;
export declare function DateMapping(input: 'Date', context: unknown): T.TDate;
export type TUint8ArrayMapping<Input extends 'Uint8Array', Context extends T.TProperties> = T.TUint8Array;
export declare function Uint8ArrayMapping(input: 'Uint8Array', context: unknown): T.TUint8Array;
export type TReferenceMapping<Input extends string, Context extends T.TProperties> = Context extends T.TProperties ? Input extends string ? TDereference<Context, Input> : never : never;
export declare function ReferenceMapping(input: string, context: unknown): T.TSchema;
export {};

491
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"use strict";
var __createBinding = (this && this.__createBinding) || (Object.create ? (function(o, m, k, k2) {
if (k2 === undefined) k2 = k;
var desc = Object.getOwnPropertyDescriptor(m, k);
if (!desc || ("get" in desc ? !m.__esModule : desc.writable || desc.configurable)) {
desc = { enumerable: true, get: function() { return m[k]; } };
}
Object.defineProperty(o, k2, desc);
}) : (function(o, m, k, k2) {
if (k2 === undefined) k2 = k;
o[k2] = m[k];
}));
var __setModuleDefault = (this && this.__setModuleDefault) || (Object.create ? (function(o, v) {
Object.defineProperty(o, "default", { enumerable: true, value: v });
}) : function(o, v) {
o["default"] = v;
});
var __importStar = (this && this.__importStar) || (function () {
var ownKeys = function(o) {
ownKeys = Object.getOwnPropertyNames || function (o) {
var ar = [];
for (var k in o) if (Object.prototype.hasOwnProperty.call(o, k)) ar[ar.length] = k;
return ar;
};
return ownKeys(o);
};
return function (mod) {
if (mod && mod.__esModule) return mod;
var result = {};
if (mod != null) for (var k = ownKeys(mod), i = 0; i < k.length; i++) if (k[i] !== "default") __createBinding(result, mod, k[i]);
__setModuleDefault(result, mod);
return result;
};
})();
Object.defineProperty(exports, "__esModule", { value: true });
exports.GenericReferenceParameterListMapping = GenericReferenceParameterListMapping;
exports.GenericReferenceMapping = GenericReferenceMapping;
exports.GenericArgumentsListMapping = GenericArgumentsListMapping;
exports.GenericArgumentsMapping = GenericArgumentsMapping;
exports.KeywordStringMapping = KeywordStringMapping;
exports.KeywordNumberMapping = KeywordNumberMapping;
exports.KeywordBooleanMapping = KeywordBooleanMapping;
exports.KeywordUndefinedMapping = KeywordUndefinedMapping;
exports.KeywordNullMapping = KeywordNullMapping;
exports.KeywordIntegerMapping = KeywordIntegerMapping;
exports.KeywordBigIntMapping = KeywordBigIntMapping;
exports.KeywordUnknownMapping = KeywordUnknownMapping;
exports.KeywordAnyMapping = KeywordAnyMapping;
exports.KeywordNeverMapping = KeywordNeverMapping;
exports.KeywordSymbolMapping = KeywordSymbolMapping;
exports.KeywordVoidMapping = KeywordVoidMapping;
exports.KeywordMapping = KeywordMapping;
exports.LiteralStringMapping = LiteralStringMapping;
exports.LiteralNumberMapping = LiteralNumberMapping;
exports.LiteralBooleanMapping = LiteralBooleanMapping;
exports.LiteralMapping = LiteralMapping;
exports.KeyOfMapping = KeyOfMapping;
exports.IndexArrayMapping = IndexArrayMapping;
exports.ExtendsMapping = ExtendsMapping;
exports.BaseMapping = BaseMapping;
exports.FactorMapping = FactorMapping;
exports.ExprTermTailMapping = ExprTermTailMapping;
exports.ExprTermMapping = ExprTermMapping;
exports.ExprTailMapping = ExprTailMapping;
exports.ExprMapping = ExprMapping;
exports.TypeMapping = TypeMapping;
exports.PropertyKeyMapping = PropertyKeyMapping;
exports.ReadonlyMapping = ReadonlyMapping;
exports.OptionalMapping = OptionalMapping;
exports.PropertyMapping = PropertyMapping;
exports.PropertyDelimiterMapping = PropertyDelimiterMapping;
exports.PropertyListMapping = PropertyListMapping;
exports.ObjectMapping = ObjectMapping;
exports.ElementListMapping = ElementListMapping;
exports.TupleMapping = TupleMapping;
exports.ParameterMapping = ParameterMapping;
exports.ParameterListMapping = ParameterListMapping;
exports.FunctionMapping = FunctionMapping;
exports.ConstructorMapping = ConstructorMapping;
exports.MappedMapping = MappedMapping;
exports.AsyncIteratorMapping = AsyncIteratorMapping;
exports.IteratorMapping = IteratorMapping;
exports.ArgumentMapping = ArgumentMapping;
exports.AwaitedMapping = AwaitedMapping;
exports.ArrayMapping = ArrayMapping;
exports.RecordMapping = RecordMapping;
exports.PromiseMapping = PromiseMapping;
exports.ConstructorParametersMapping = ConstructorParametersMapping;
exports.FunctionParametersMapping = FunctionParametersMapping;
exports.InstanceTypeMapping = InstanceTypeMapping;
exports.ReturnTypeMapping = ReturnTypeMapping;
exports.PartialMapping = PartialMapping;
exports.RequiredMapping = RequiredMapping;
exports.PickMapping = PickMapping;
exports.OmitMapping = OmitMapping;
exports.ExcludeMapping = ExcludeMapping;
exports.ExtractMapping = ExtractMapping;
exports.UppercaseMapping = UppercaseMapping;
exports.LowercaseMapping = LowercaseMapping;
exports.CapitalizeMapping = CapitalizeMapping;
exports.UncapitalizeMapping = UncapitalizeMapping;
exports.DateMapping = DateMapping;
exports.Uint8ArrayMapping = Uint8ArrayMapping;
exports.ReferenceMapping = ReferenceMapping;
const T = __importStar(require("../type/index"));
// prettier-ignore
const Dereference = (context, key) => {
return key in context ? context[key] : T.Ref(key);
};
// prettier-ignore
const DelimitedDecode = (input, result = []) => {
return input.reduce((result, left) => {
return T.ValueGuard.IsArray(left) && left.length === 2
? [...result, left[0]]
: [...result, left];
}, []);
};
// prettier-ignore
const Delimited = (input) => {
const [left, right] = input;
return DelimitedDecode([...left, ...right]);
};
// prettier-ignore
function GenericReferenceParameterListMapping(input, context) {
return Delimited(input);
}
// prettier-ignore
function GenericReferenceMapping(input, context) {
const type = Dereference(context, input[0]);
const args = input[2];
return T.Instantiate(type, args);
}
// prettier-ignore
function GenericArgumentsListMapping(input, context) {
return Delimited(input);
}
// ...
// prettier-ignore
const GenericArgumentsContext = (_arguments, context) => {
return _arguments.reduce((result, arg, index) => {
return { ...result, [arg]: T.Argument(index) };
}, context);
};
// prettier-ignore
function GenericArgumentsMapping(input, context) {
return input.length === 3
? GenericArgumentsContext(input[1], context)
: {};
}
// prettier-ignore
function KeywordStringMapping(input, context) {
return T.String();
}
// prettier-ignore
function KeywordNumberMapping(input, context) {
return T.Number();
}
// prettier-ignore
function KeywordBooleanMapping(input, context) {
return T.Boolean();
}
// prettier-ignore
function KeywordUndefinedMapping(input, context) {
return T.Undefined();
}
// prettier-ignore
function KeywordNullMapping(input, context) {
return T.Null();
}
// prettier-ignore
function KeywordIntegerMapping(input, context) {
return T.Integer();
}
// prettier-ignore
function KeywordBigIntMapping(input, context) {
return T.BigInt();
}
// prettier-ignore
function KeywordUnknownMapping(input, context) {
return T.Unknown();
}
// prettier-ignore
function KeywordAnyMapping(input, context) {
return T.Any();
}
// prettier-ignore
function KeywordNeverMapping(input, context) {
return T.Never();
}
// prettier-ignore
function KeywordSymbolMapping(input, context) {
return T.Symbol();
}
// prettier-ignore
function KeywordVoidMapping(input, context) {
return T.Void();
}
// prettier-ignore
function KeywordMapping(input, context) {
return input;
}
// prettier-ignore
function LiteralStringMapping(input, context) {
return T.Literal(input);
}
// prettier-ignore
function LiteralNumberMapping(input, context) {
return T.Literal(parseFloat(input));
}
// prettier-ignore
function LiteralBooleanMapping(input, context) {
return T.Literal(input === 'true');
}
// prettier-ignore
function LiteralMapping(input, context) {
return input;
}
// prettier-ignore
function KeyOfMapping(input, context) {
return input.length > 0;
}
// prettier-ignore
function IndexArrayMapping(input, context) {
return input.reduce((result, current) => {
return current.length === 3
? [...result, [current[1]]]
: [...result, []];
}, []);
}
// prettier-ignore
function ExtendsMapping(input, context) {
return input.length === 6
? [input[1], input[3], input[5]]
: [];
}
// prettier-ignore
function BaseMapping(input, context) {
return T.ValueGuard.IsArray(input) && input.length === 3 ? input[1] : input;
}
// ...
// prettier-ignore
const FactorIndexArray = (Type, indexArray) => {
return indexArray.reduceRight((result, right) => {
const _right = right;
return (_right.length === 1 ? T.Index(result, _right[0]) :
_right.length === 0 ? T.Array(result, _right[0]) :
T.Never());
}, Type);
};
// prettier-ignore
const FactorExtends = (Type, Extends) => {
return Extends.length === 3
? T.Extends(Type, Extends[0], Extends[1], Extends[2])
: Type;
};
// prettier-ignore
function FactorMapping(input, context) {
const [KeyOf, Type, IndexArray, Extends] = input;
return KeyOf
? FactorExtends(T.KeyOf(FactorIndexArray(Type, IndexArray)), Extends)
: FactorExtends(FactorIndexArray(Type, IndexArray), Extends);
}
// prettier-ignore
function ExprBinaryMapping(Left, Rest) {
return (Rest.length === 3 ? (() => {
const [Operator, Right, Next] = Rest;
const Schema = ExprBinaryMapping(Right, Next);
if (Operator === '&') {
return T.TypeGuard.IsIntersect(Schema)
? T.Intersect([Left, ...Schema.allOf])
: T.Intersect([Left, Schema]);
}
if (Operator === '|') {
return T.TypeGuard.IsUnion(Schema)
? T.Union([Left, ...Schema.anyOf])
: T.Union([Left, Schema]);
}
throw 1;
})() : Left);
}
// prettier-ignore
function ExprTermTailMapping(input, context) {
return input;
}
// prettier-ignore
function ExprTermMapping(input, context) {
const [left, rest] = input;
return ExprBinaryMapping(left, rest);
}
// prettier-ignore
function ExprTailMapping(input, context) {
return input;
}
// prettier-ignore
function ExprMapping(input, context) {
const [left, rest] = input;
return ExprBinaryMapping(left, rest);
}
// prettier-ignore
function TypeMapping(input, context) {
return input;
}
// prettier-ignore
function PropertyKeyMapping(input, context) {
return input;
}
// prettier-ignore
function ReadonlyMapping(input, context) {
return input.length > 0;
}
// prettier-ignore
function OptionalMapping(input, context) {
return input.length > 0;
}
// prettier-ignore
function PropertyMapping(input, context) {
const [isReadonly, key, isOptional, _colon, type] = input;
return {
[key]: (isReadonly && isOptional ? T.ReadonlyOptional(type) :
isReadonly && !isOptional ? T.Readonly(type) :
!isReadonly && isOptional ? T.Optional(type) :
type)
};
}
// prettier-ignore
function PropertyDelimiterMapping(input, context) {
return input;
}
// prettier-ignore
function PropertyListMapping(input, context) {
return Delimited(input);
}
// prettier-ignore
function ObjectMapping(input, context) {
const propertyList = input[1];
return T.Object(propertyList.reduce((result, property) => {
return { ...result, ...property };
}, {}));
}
// prettier-ignore
function ElementListMapping(input, context) {
return Delimited(input);
}
// prettier-ignore
function TupleMapping(input, context) {
return T.Tuple(input[1]);
}
// prettier-ignore
function ParameterMapping(input, context) {
const [_ident, _colon, type] = input;
return type;
}
// prettier-ignore
function ParameterListMapping(input, context) {
return Delimited(input);
}
// prettier-ignore
function FunctionMapping(input, context) {
const [_lparan, parameterList, _rparan, _arrow, returnType] = input;
return T.Function(parameterList, returnType);
}
// prettier-ignore
function ConstructorMapping(input, context) {
const [_new, _lparan, parameterList, _rparan, _arrow, instanceType] = input;
return T.Constructor(parameterList, instanceType);
}
// prettier-ignore
function MappedMapping(input, context) {
const [_lbrace, _lbracket, _key, _in, _right, _rbracket, _colon, _type] = input;
return T.Literal('Mapped types not supported');
}
// prettier-ignore
function AsyncIteratorMapping(input, context) {
const [_name, _langle, type, _rangle] = input;
return T.AsyncIterator(type);
}
// prettier-ignore
function IteratorMapping(input, context) {
const [_name, _langle, type, _rangle] = input;
return T.Iterator(type);
}
// prettier-ignore
function ArgumentMapping(input, context) {
return T.KindGuard.IsLiteralNumber(input[2])
? T.Argument(Math.trunc(input[2].const))
: T.Never();
}
// prettier-ignore
function AwaitedMapping(input, context) {
const [_name, _langle, type, _rangle] = input;
return T.Awaited(type);
}
// prettier-ignore
function ArrayMapping(input, context) {
const [_name, _langle, type, _rangle] = input;
return T.Array(type);
}
// prettier-ignore
function RecordMapping(input, context) {
const [_name, _langle, key, _comma, type, _rangle] = input;
return T.Record(key, type);
}
// prettier-ignore
function PromiseMapping(input, context) {
const [_name, _langle, type, _rangle] = input;
return T.Promise(type);
}
// prettier-ignore
function ConstructorParametersMapping(input, context) {
const [_name, _langle, type, _rangle] = input;
return T.ConstructorParameters(type);
}
// prettier-ignore
function FunctionParametersMapping(input, context) {
const [_name, _langle, type, _rangle] = input;
return T.Parameters(type);
}
// prettier-ignore
function InstanceTypeMapping(input, context) {
const [_name, _langle, type, _rangle] = input;
return T.InstanceType(type);
}
// prettier-ignore
function ReturnTypeMapping(input, context) {
const [_name, _langle, type, _rangle] = input;
return T.ReturnType(type);
}
// prettier-ignore
function PartialMapping(input, context) {
const [_name, _langle, type, _rangle] = input;
return T.Partial(type);
}
// prettier-ignore
function RequiredMapping(input, context) {
const [_name, _langle, type, _rangle] = input;
return T.Required(type);
}
// prettier-ignore
function PickMapping(input, context) {
const [_name, _langle, key, _comma, type, _rangle] = input;
return T.Pick(key, type);
}
// prettier-ignore
function OmitMapping(input, context) {
const [_name, _langle, key, _comma, type, _rangle] = input;
return T.Omit(key, type);
}
// prettier-ignore
function ExcludeMapping(input, context) {
const [_name, _langle, key, _comma, type, _rangle] = input;
return T.Exclude(key, type);
}
// prettier-ignore
function ExtractMapping(input, context) {
const [_name, _langle, key, _comma, type, _rangle] = input;
return T.Extract(key, type);
}
// prettier-ignore
function UppercaseMapping(input, context) {
const [_name, _langle, type, _rangle] = input;
return T.Uppercase(type);
}
// prettier-ignore
function LowercaseMapping(input, context) {
const [_name, _langle, type, _rangle] = input;
return T.Lowercase(type);
}
// prettier-ignore
function CapitalizeMapping(input, context) {
const [_name, _langle, type, _rangle] = input;
return T.Capitalize(type);
}
// prettier-ignore
function UncapitalizeMapping(input, context) {
const [_name, _langle, type, _rangle] = input;
return T.Uncapitalize(type);
}
// prettier-ignore
function DateMapping(input, context) {
return T.Date();
}
// prettier-ignore
function Uint8ArrayMapping(input, context) {
return T.Uint8Array();
}
// prettier-ignore
function ReferenceMapping(input, context) {
const target = Dereference(context, input);
return target;
}

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import { Static } from '../parser/index';
import * as T from '../type/index';
import * as S from './mapping';
export type TGenericReferenceParameterList_0<Input extends string, Context extends T.TProperties, Result extends unknown[] = []> = (TType<Input, Context> extends [infer _0, infer Input extends string] ? (Static.Token.Const<',', Input> extends [infer _1, infer Input extends string] ? [[_0, _1], Input] : []) : []) extends [infer _0, infer Input extends string] ? TGenericReferenceParameterList_0<Input, Context, [...Result, _0]> : [Result, Input];
export type TGenericReferenceParameterList<Input extends string, Context extends T.TProperties = {}> = (TGenericReferenceParameterList_0<Input, Context> extends [infer _0, infer Input extends string] ? ((TType<Input, Context> extends [infer _0, infer Input extends string] ? [[_0], Input] : []) extends [infer _0, infer Input extends string] ? [_0, Input] : [[], Input] extends [infer _0, infer Input extends string] ? [_0, Input] : []) extends [infer _1, infer Input extends string] ? [[_0, _1], Input] : [] : []) extends [infer _0 extends [unknown, unknown], infer Input extends string] ? [S.TGenericReferenceParameterListMapping<_0, Context>, Input] : [];
export type TGenericReference<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Ident<Input> extends [infer _0, infer Input extends string] ? Static.Token.Const<'<', Input> extends [infer _1, infer Input extends string] ? TGenericReferenceParameterList<Input, Context> extends [infer _2, infer Input extends string] ? Static.Token.Const<'>', Input> extends [infer _3, infer Input extends string] ? [[_0, _1, _2, _3], Input] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TGenericReferenceMapping<_0, Context>, Input] : [];
export type TGenericArgumentsList_0<Input extends string, Context extends T.TProperties, Result extends unknown[] = []> = (Static.Token.Ident<Input> extends [infer _0, infer Input extends string] ? (Static.Token.Const<',', Input> extends [infer _1, infer Input extends string] ? [[_0, _1], Input] : []) : []) extends [infer _0, infer Input extends string] ? TGenericArgumentsList_0<Input, Context, [...Result, _0]> : [Result, Input];
export type TGenericArgumentsList<Input extends string, Context extends T.TProperties = {}> = (TGenericArgumentsList_0<Input, Context> extends [infer _0, infer Input extends string] ? ((Static.Token.Ident<Input> extends [infer _0, infer Input extends string] ? [[_0], Input] : []) extends [infer _0, infer Input extends string] ? [_0, Input] : [[], Input] extends [infer _0, infer Input extends string] ? [_0, Input] : []) extends [infer _1, infer Input extends string] ? [[_0, _1], Input] : [] : []) extends [infer _0 extends [unknown, unknown], infer Input extends string] ? [S.TGenericArgumentsListMapping<_0, Context>, Input] : [];
export type TGenericArguments<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'<', Input> extends [infer _0, infer Input extends string] ? TGenericArgumentsList<Input, Context> extends [infer _1, infer Input extends string] ? Static.Token.Const<'>', Input> extends [infer _2, infer Input extends string] ? [[_0, _1, _2], Input] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown], infer Input extends string] ? [S.TGenericArgumentsMapping<_0, Context>, Input] : [];
export type TKeywordString<Input extends string, Context extends T.TProperties = {}> = Static.Token.Const<'string', Input> extends [infer _0 extends 'string', infer Input extends string] ? [S.TKeywordStringMapping<_0, Context>, Input] : [];
export type TKeywordNumber<Input extends string, Context extends T.TProperties = {}> = Static.Token.Const<'number', Input> extends [infer _0 extends 'number', infer Input extends string] ? [S.TKeywordNumberMapping<_0, Context>, Input] : [];
export type TKeywordBoolean<Input extends string, Context extends T.TProperties = {}> = Static.Token.Const<'boolean', Input> extends [infer _0 extends 'boolean', infer Input extends string] ? [S.TKeywordBooleanMapping<_0, Context>, Input] : [];
export type TKeywordUndefined<Input extends string, Context extends T.TProperties = {}> = Static.Token.Const<'undefined', Input> extends [infer _0 extends 'undefined', infer Input extends string] ? [S.TKeywordUndefinedMapping<_0, Context>, Input] : [];
export type TKeywordNull<Input extends string, Context extends T.TProperties = {}> = Static.Token.Const<'null', Input> extends [infer _0 extends 'null', infer Input extends string] ? [S.TKeywordNullMapping<_0, Context>, Input] : [];
export type TKeywordInteger<Input extends string, Context extends T.TProperties = {}> = Static.Token.Const<'integer', Input> extends [infer _0 extends 'integer', infer Input extends string] ? [S.TKeywordIntegerMapping<_0, Context>, Input] : [];
export type TKeywordBigInt<Input extends string, Context extends T.TProperties = {}> = Static.Token.Const<'bigint', Input> extends [infer _0 extends 'bigint', infer Input extends string] ? [S.TKeywordBigIntMapping<_0, Context>, Input] : [];
export type TKeywordUnknown<Input extends string, Context extends T.TProperties = {}> = Static.Token.Const<'unknown', Input> extends [infer _0 extends 'unknown', infer Input extends string] ? [S.TKeywordUnknownMapping<_0, Context>, Input] : [];
export type TKeywordAny<Input extends string, Context extends T.TProperties = {}> = Static.Token.Const<'any', Input> extends [infer _0 extends 'any', infer Input extends string] ? [S.TKeywordAnyMapping<_0, Context>, Input] : [];
export type TKeywordNever<Input extends string, Context extends T.TProperties = {}> = Static.Token.Const<'never', Input> extends [infer _0 extends 'never', infer Input extends string] ? [S.TKeywordNeverMapping<_0, Context>, Input] : [];
export type TKeywordSymbol<Input extends string, Context extends T.TProperties = {}> = Static.Token.Const<'symbol', Input> extends [infer _0 extends 'symbol', infer Input extends string] ? [S.TKeywordSymbolMapping<_0, Context>, Input] : [];
export type TKeywordVoid<Input extends string, Context extends T.TProperties = {}> = Static.Token.Const<'void', Input> extends [infer _0 extends 'void', infer Input extends string] ? [S.TKeywordVoidMapping<_0, Context>, Input] : [];
export type TKeyword<Input extends string, Context extends T.TProperties = {}> = (TKeywordString<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TKeywordNumber<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TKeywordBoolean<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TKeywordUndefined<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TKeywordNull<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TKeywordInteger<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TKeywordBigInt<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TKeywordUnknown<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TKeywordAny<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TKeywordNever<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TKeywordSymbol<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TKeywordVoid<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : []) extends [infer _0 extends unknown, infer Input extends string] ? [S.TKeywordMapping<_0, Context>, Input] : [];
export type TLiteralString<Input extends string, Context extends T.TProperties = {}> = Static.Token.String<["'", '"', '`'], Input> extends [infer _0 extends string, infer Input extends string] ? [S.TLiteralStringMapping<_0, Context>, Input] : [];
export type TLiteralNumber<Input extends string, Context extends T.TProperties = {}> = Static.Token.Number<Input> extends [infer _0 extends string, infer Input extends string] ? [S.TLiteralNumberMapping<_0, Context>, Input] : [];
export type TLiteralBoolean<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'true', Input> extends [infer _0, infer Input extends string] ? [_0, Input] : Static.Token.Const<'false', Input> extends [infer _0, infer Input extends string] ? [_0, Input] : []) extends [infer _0 extends 'true' | 'false', infer Input extends string] ? [S.TLiteralBooleanMapping<_0, Context>, Input] : [];
export type TLiteral<Input extends string, Context extends T.TProperties = {}> = (TLiteralBoolean<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TLiteralNumber<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TLiteralString<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : []) extends [infer _0 extends unknown, infer Input extends string] ? [S.TLiteralMapping<_0, Context>, Input] : [];
export type TKeyOf<Input extends string, Context extends T.TProperties = {}> = ((Static.Token.Const<'keyof', Input> extends [infer _0, infer Input extends string] ? [[_0], Input] : []) extends [infer _0, infer Input extends string] ? [_0, Input] : [[], Input] extends [infer _0, infer Input extends string] ? [_0, Input] : []) extends [infer _0 extends [unknown] | [], infer Input extends string] ? [S.TKeyOfMapping<_0, Context>, Input] : [];
export type TIndexArray_0<Input extends string, Context extends T.TProperties, Result extends unknown[] = []> = ((Static.Token.Const<'[', Input> extends [infer _0, infer Input extends string] ? TType<Input, Context> extends [infer _1, infer Input extends string] ? Static.Token.Const<']', Input> extends [infer _2, infer Input extends string] ? [[_0, _1, _2], Input] : [] : [] : []) extends [infer _0, infer Input extends string] ? [_0, Input] : (Static.Token.Const<'[', Input> extends [infer _0, infer Input extends string] ? (Static.Token.Const<']', Input> extends [infer _1, infer Input extends string] ? [[_0, _1], Input] : []) : []) extends [
infer _0,
infer Input extends string
] ? [_0, Input] : []) extends [infer _0, infer Input extends string] ? TIndexArray_0<Input, Context, [...Result, _0]> : [Result, Input];
export type TIndexArray<Input extends string, Context extends T.TProperties = {}> = TIndexArray_0<Input, Context> extends [infer _0 extends ([unknown, unknown, unknown] | [unknown, unknown])[], infer Input extends string] ? [S.TIndexArrayMapping<_0, Context>, Input] : [];
export type TExtends<Input extends string, Context extends T.TProperties = {}> = ((Static.Token.Const<'extends', Input> extends [infer _0, infer Input extends string] ? TType<Input, Context> extends [infer _1, infer Input extends string] ? Static.Token.Const<'?', Input> extends [infer _2, infer Input extends string] ? TType<Input, Context> extends [infer _3, infer Input extends string] ? Static.Token.Const<':', Input> extends [infer _4, infer Input extends string] ? TType<Input, Context> extends [infer _5, infer Input extends string] ? [[_0, _1, _2, _3, _4, _5], Input] : [] : [] : [] : [] : [] : []) extends [infer _0, infer Input extends string] ? [_0, Input] : [[], Input] extends [infer _0, infer Input extends string] ? [_0, Input] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown, unknown, unknown] | [], infer Input extends string] ? [S.TExtendsMapping<_0, Context>, Input] : [];
export type TBase<Input extends string, Context extends T.TProperties = {}> = ((Static.Token.Const<'(', Input> extends [infer _0, infer Input extends string] ? TType<Input, Context> extends [infer _1, infer Input extends string] ? Static.Token.Const<')', Input> extends [infer _2, infer Input extends string] ? [[_0, _1, _2], Input] : [] : [] : []) extends [infer _0, infer Input extends string] ? [_0, Input] : TKeyword<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TObject<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TTuple<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TLiteral<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TConstructor<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TFunction<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TMapped<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TAsyncIterator<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TIterator<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TConstructorParameters<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TFunctionParameters<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TInstanceType<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TReturnType<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TArgument<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TAwaited<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TArray<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TRecord<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TPromise<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TPartial<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TRequired<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TPick<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TOmit<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TExclude<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TExtract<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TUppercase<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TLowercase<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TCapitalize<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TUncapitalize<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TDate<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TUint8Array<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TGenericReference<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : TReference<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : []) extends [infer _0 extends [unknown, unknown, unknown] | unknown, infer Input extends string] ? [S.TBaseMapping<_0, Context>, Input] : [];
export type TFactor<Input extends string, Context extends T.TProperties = {}> = (TKeyOf<Input, Context> extends [infer _0, infer Input extends string] ? TBase<Input, Context> extends [infer _1, infer Input extends string] ? TIndexArray<Input, Context> extends [infer _2, infer Input extends string] ? TExtends<Input, Context> extends [infer _3, infer Input extends string] ? [[_0, _1, _2, _3], Input] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TFactorMapping<_0, Context>, Input] : [];
export type TExprTermTail<Input extends string, Context extends T.TProperties = {}> = ((Static.Token.Const<'&', Input> extends [infer _0, infer Input extends string] ? TFactor<Input, Context> extends [infer _1, infer Input extends string] ? TExprTermTail<Input, Context> extends [infer _2, infer Input extends string] ? [[_0, _1, _2], Input] : [] : [] : []) extends [infer _0, infer Input extends string] ? [_0, Input] : [[], Input] extends [infer _0, infer Input extends string] ? [_0, Input] : []) extends [infer _0 extends [unknown, unknown, unknown] | [], infer Input extends string] ? [S.TExprTermTailMapping<_0, Context>, Input] : [];
export type TExprTerm<Input extends string, Context extends T.TProperties = {}> = (TFactor<Input, Context> extends [infer _0, infer Input extends string] ? (TExprTermTail<Input, Context> extends [infer _1, infer Input extends string] ? [[_0, _1], Input] : []) : []) extends [infer _0 extends [unknown, unknown], infer Input extends string] ? [S.TExprTermMapping<_0, Context>, Input] : [];
export type TExprTail<Input extends string, Context extends T.TProperties = {}> = ((Static.Token.Const<'|', Input> extends [infer _0, infer Input extends string] ? TExprTerm<Input, Context> extends [infer _1, infer Input extends string] ? TExprTail<Input, Context> extends [infer _2, infer Input extends string] ? [[_0, _1, _2], Input] : [] : [] : []) extends [infer _0, infer Input extends string] ? [_0, Input] : [[], Input] extends [infer _0, infer Input extends string] ? [_0, Input] : []) extends [infer _0 extends [unknown, unknown, unknown] | [], infer Input extends string] ? [S.TExprTailMapping<_0, Context>, Input] : [];
export type TExpr<Input extends string, Context extends T.TProperties = {}> = (TExprTerm<Input, Context> extends [infer _0, infer Input extends string] ? (TExprTail<Input, Context> extends [infer _1, infer Input extends string] ? [[_0, _1], Input] : []) : []) extends [infer _0 extends [unknown, unknown], infer Input extends string] ? [S.TExprMapping<_0, Context>, Input] : [];
export type TType<Input extends string, Context extends T.TProperties = {}> = (TGenericArguments<Input, Context> extends [infer _0 extends T.TProperties, infer Input extends string] ? TExpr<Input, _0> : [] extends [infer _0, infer Input extends string] ? [_0, Input] : TExpr<Input, Context> extends [infer _0, infer Input extends string] ? [_0, Input] : []) extends [infer _0 extends unknown, infer Input extends string] ? [S.TTypeMapping<_0, Context>, Input] : [];
export type TPropertyKey<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Ident<Input> extends [infer _0, infer Input extends string] ? [_0, Input] : Static.Token.String<["'", '"'], Input> extends [infer _0, infer Input extends string] ? [_0, Input] : []) extends [infer _0 extends string, infer Input extends string] ? [S.TPropertyKeyMapping<_0, Context>, Input] : [];
export type TReadonly<Input extends string, Context extends T.TProperties = {}> = ((Static.Token.Const<'readonly', Input> extends [infer _0, infer Input extends string] ? [[_0], Input] : []) extends [infer _0, infer Input extends string] ? [_0, Input] : [[], Input] extends [infer _0, infer Input extends string] ? [_0, Input] : []) extends [infer _0 extends [unknown] | [], infer Input extends string] ? [S.TReadonlyMapping<_0, Context>, Input] : [];
export type TOptional<Input extends string, Context extends T.TProperties = {}> = ((Static.Token.Const<'?', Input> extends [infer _0, infer Input extends string] ? [[_0], Input] : []) extends [infer _0, infer Input extends string] ? [_0, Input] : [[], Input] extends [infer _0, infer Input extends string] ? [_0, Input] : []) extends [infer _0 extends [unknown] | [], infer Input extends string] ? [S.TOptionalMapping<_0, Context>, Input] : [];
export type TProperty<Input extends string, Context extends T.TProperties = {}> = (TReadonly<Input, Context> extends [infer _0, infer Input extends string] ? TPropertyKey<Input, Context> extends [infer _1, infer Input extends string] ? TOptional<Input, Context> extends [infer _2, infer Input extends string] ? Static.Token.Const<':', Input> extends [infer _3, infer Input extends string] ? TType<Input, Context> extends [infer _4, infer Input extends string] ? [[_0, _1, _2, _3, _4], Input] : [] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TPropertyMapping<_0, Context>, Input] : [];
export type TPropertyDelimiter<Input extends string, Context extends T.TProperties = {}> = ((Static.Token.Const<',', Input> extends [infer _0, infer Input extends string] ? (Static.Token.Const<'\n', Input> extends [infer _1, infer Input extends string] ? [[_0, _1], Input] : []) : []) extends [
infer _0,
infer Input extends string
] ? [_0, Input] : (Static.Token.Const<';', Input> extends [infer _0, infer Input extends string] ? (Static.Token.Const<'\n', Input> extends [infer _1, infer Input extends string] ? [[_0, _1], Input] : []) : []) extends [
infer _0,
infer Input extends string
] ? [_0, Input] : (Static.Token.Const<',', Input> extends [infer _0, infer Input extends string] ? [[_0], Input] : []) extends [infer _0, infer Input extends string] ? [_0, Input] : (Static.Token.Const<';', Input> extends [infer _0, infer Input extends string] ? [[_0], Input] : []) extends [infer _0, infer Input extends string] ? [_0, Input] : (Static.Token.Const<'\n', Input> extends [infer _0, infer Input extends string] ? [[_0], Input] : []) extends [infer _0, infer Input extends string] ? [_0, Input] : []) extends [infer _0 extends [unknown, unknown] | [unknown], infer Input extends string] ? [S.TPropertyDelimiterMapping<_0, Context>, Input] : [];
export type TPropertyList_0<Input extends string, Context extends T.TProperties, Result extends unknown[] = []> = (TProperty<Input, Context> extends [infer _0, infer Input extends string] ? (TPropertyDelimiter<Input, Context> extends [infer _1, infer Input extends string] ? [[_0, _1], Input] : []) : []) extends [infer _0, infer Input extends string] ? TPropertyList_0<Input, Context, [...Result, _0]> : [Result, Input];
export type TPropertyList<Input extends string, Context extends T.TProperties = {}> = (TPropertyList_0<Input, Context> extends [infer _0, infer Input extends string] ? ((TProperty<Input, Context> extends [infer _0, infer Input extends string] ? [[_0], Input] : []) extends [infer _0, infer Input extends string] ? [_0, Input] : [[], Input] extends [infer _0, infer Input extends string] ? [_0, Input] : []) extends [infer _1, infer Input extends string] ? [[_0, _1], Input] : [] : []) extends [infer _0 extends [unknown, unknown], infer Input extends string] ? [S.TPropertyListMapping<_0, Context>, Input] : [];
export type TObject<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'{', Input> extends [infer _0, infer Input extends string] ? TPropertyList<Input, Context> extends [infer _1, infer Input extends string] ? Static.Token.Const<'}', Input> extends [infer _2, infer Input extends string] ? [[_0, _1, _2], Input] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown], infer Input extends string] ? [S.TObjectMapping<_0, Context>, Input] : [];
export type TElementList_0<Input extends string, Context extends T.TProperties, Result extends unknown[] = []> = (TType<Input, Context> extends [infer _0, infer Input extends string] ? (Static.Token.Const<',', Input> extends [infer _1, infer Input extends string] ? [[_0, _1], Input] : []) : []) extends [infer _0, infer Input extends string] ? TElementList_0<Input, Context, [...Result, _0]> : [Result, Input];
export type TElementList<Input extends string, Context extends T.TProperties = {}> = (TElementList_0<Input, Context> extends [infer _0, infer Input extends string] ? ((TType<Input, Context> extends [infer _0, infer Input extends string] ? [[_0], Input] : []) extends [infer _0, infer Input extends string] ? [_0, Input] : [[], Input] extends [infer _0, infer Input extends string] ? [_0, Input] : []) extends [infer _1, infer Input extends string] ? [[_0, _1], Input] : [] : []) extends [infer _0 extends [unknown, unknown], infer Input extends string] ? [S.TElementListMapping<_0, Context>, Input] : [];
export type TTuple<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'[', Input> extends [infer _0, infer Input extends string] ? TElementList<Input, Context> extends [infer _1, infer Input extends string] ? Static.Token.Const<']', Input> extends [infer _2, infer Input extends string] ? [[_0, _1, _2], Input] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown], infer Input extends string] ? [S.TTupleMapping<_0, Context>, Input] : [];
export type TParameter<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Ident<Input> extends [infer _0, infer Input extends string] ? Static.Token.Const<':', Input> extends [infer _1, infer Input extends string] ? TType<Input, Context> extends [infer _2, infer Input extends string] ? [[_0, _1, _2], Input] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown], infer Input extends string] ? [S.TParameterMapping<_0, Context>, Input] : [];
export type TParameterList_0<Input extends string, Context extends T.TProperties, Result extends unknown[] = []> = (TParameter<Input, Context> extends [infer _0, infer Input extends string] ? (Static.Token.Const<',', Input> extends [infer _1, infer Input extends string] ? [[_0, _1], Input] : []) : []) extends [infer _0, infer Input extends string] ? TParameterList_0<Input, Context, [...Result, _0]> : [Result, Input];
export type TParameterList<Input extends string, Context extends T.TProperties = {}> = (TParameterList_0<Input, Context> extends [infer _0, infer Input extends string] ? ((TParameter<Input, Context> extends [infer _0, infer Input extends string] ? [[_0], Input] : []) extends [infer _0, infer Input extends string] ? [_0, Input] : [[], Input] extends [infer _0, infer Input extends string] ? [_0, Input] : []) extends [infer _1, infer Input extends string] ? [[_0, _1], Input] : [] : []) extends [infer _0 extends [unknown, unknown], infer Input extends string] ? [S.TParameterListMapping<_0, Context>, Input] : [];
export type TFunction<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'(', Input> extends [infer _0, infer Input extends string] ? TParameterList<Input, Context> extends [infer _1, infer Input extends string] ? Static.Token.Const<')', Input> extends [infer _2, infer Input extends string] ? Static.Token.Const<'=>', Input> extends [infer _3, infer Input extends string] ? TType<Input, Context> extends [infer _4, infer Input extends string] ? [[_0, _1, _2, _3, _4], Input] : [] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TFunctionMapping<_0, Context>, Input] : [];
export type TConstructor<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'new', Input> extends [infer _0, infer Input extends string] ? Static.Token.Const<'(', Input> extends [infer _1, infer Input extends string] ? TParameterList<Input, Context> extends [infer _2, infer Input extends string] ? Static.Token.Const<')', Input> extends [infer _3, infer Input extends string] ? Static.Token.Const<'=>', Input> extends [infer _4, infer Input extends string] ? TType<Input, Context> extends [infer _5, infer Input extends string] ? [[_0, _1, _2, _3, _4, _5], Input] : [] : [] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TConstructorMapping<_0, Context>, Input] : [];
export type TMapped<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'{', Input> extends [infer _0, infer Input extends string] ? Static.Token.Const<'[', Input> extends [infer _1, infer Input extends string] ? Static.Token.Ident<Input> extends [infer _2, infer Input extends string] ? Static.Token.Const<'in', Input> extends [infer _3, infer Input extends string] ? TType<Input, Context> extends [infer _4, infer Input extends string] ? Static.Token.Const<']', Input> extends [infer _5, infer Input extends string] ? Static.Token.Const<':', Input> extends [infer _6, infer Input extends string] ? TType<Input, Context> extends [infer _7, infer Input extends string] ? Static.Token.Const<'}', Input> extends [infer _8, infer Input extends string] ? [[_0, _1, _2, _3, _4, _5, _6, _7, _8], Input] : [] : [] : [] : [] : [] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown, unknown, unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TMappedMapping<_0, Context>, Input] : [];
export type TAsyncIterator<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'AsyncIterator', Input> extends [infer _0, infer Input extends string] ? Static.Token.Const<'<', Input> extends [infer _1, infer Input extends string] ? TType<Input, Context> extends [infer _2, infer Input extends string] ? Static.Token.Const<'>', Input> extends [infer _3, infer Input extends string] ? [[_0, _1, _2, _3], Input] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TAsyncIteratorMapping<_0, Context>, Input] : [];
export type TIterator<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'Iterator', Input> extends [infer _0, infer Input extends string] ? Static.Token.Const<'<', Input> extends [infer _1, infer Input extends string] ? TType<Input, Context> extends [infer _2, infer Input extends string] ? Static.Token.Const<'>', Input> extends [infer _3, infer Input extends string] ? [[_0, _1, _2, _3], Input] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TIteratorMapping<_0, Context>, Input] : [];
export type TArgument<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'Argument', Input> extends [infer _0, infer Input extends string] ? Static.Token.Const<'<', Input> extends [infer _1, infer Input extends string] ? TType<Input, Context> extends [infer _2, infer Input extends string] ? Static.Token.Const<'>', Input> extends [infer _3, infer Input extends string] ? [[_0, _1, _2, _3], Input] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TArgumentMapping<_0, Context>, Input] : [];
export type TAwaited<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'Awaited', Input> extends [infer _0, infer Input extends string] ? Static.Token.Const<'<', Input> extends [infer _1, infer Input extends string] ? TType<Input, Context> extends [infer _2, infer Input extends string] ? Static.Token.Const<'>', Input> extends [infer _3, infer Input extends string] ? [[_0, _1, _2, _3], Input] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TAwaitedMapping<_0, Context>, Input] : [];
export type TArray<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'Array', Input> extends [infer _0, infer Input extends string] ? Static.Token.Const<'<', Input> extends [infer _1, infer Input extends string] ? TType<Input, Context> extends [infer _2, infer Input extends string] ? Static.Token.Const<'>', Input> extends [infer _3, infer Input extends string] ? [[_0, _1, _2, _3], Input] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TArrayMapping<_0, Context>, Input] : [];
export type TRecord<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'Record', Input> extends [infer _0, infer Input extends string] ? Static.Token.Const<'<', Input> extends [infer _1, infer Input extends string] ? TType<Input, Context> extends [infer _2, infer Input extends string] ? Static.Token.Const<',', Input> extends [infer _3, infer Input extends string] ? TType<Input, Context> extends [infer _4, infer Input extends string] ? Static.Token.Const<'>', Input> extends [infer _5, infer Input extends string] ? [[_0, _1, _2, _3, _4, _5], Input] : [] : [] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TRecordMapping<_0, Context>, Input] : [];
export type TPromise<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'Promise', Input> extends [infer _0, infer Input extends string] ? Static.Token.Const<'<', Input> extends [infer _1, infer Input extends string] ? TType<Input, Context> extends [infer _2, infer Input extends string] ? Static.Token.Const<'>', Input> extends [infer _3, infer Input extends string] ? [[_0, _1, _2, _3], Input] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TPromiseMapping<_0, Context>, Input] : [];
export type TConstructorParameters<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'ConstructorParameters', Input> extends [infer _0, infer Input extends string] ? Static.Token.Const<'<', Input> extends [infer _1, infer Input extends string] ? TType<Input, Context> extends [infer _2, infer Input extends string] ? Static.Token.Const<'>', Input> extends [infer _3, infer Input extends string] ? [[_0, _1, _2, _3], Input] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TConstructorParametersMapping<_0, Context>, Input] : [];
export type TFunctionParameters<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'Parameters', Input> extends [infer _0, infer Input extends string] ? Static.Token.Const<'<', Input> extends [infer _1, infer Input extends string] ? TType<Input, Context> extends [infer _2, infer Input extends string] ? Static.Token.Const<'>', Input> extends [infer _3, infer Input extends string] ? [[_0, _1, _2, _3], Input] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TFunctionParametersMapping<_0, Context>, Input] : [];
export type TInstanceType<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'InstanceType', Input> extends [infer _0, infer Input extends string] ? Static.Token.Const<'<', Input> extends [infer _1, infer Input extends string] ? TType<Input, Context> extends [infer _2, infer Input extends string] ? Static.Token.Const<'>', Input> extends [infer _3, infer Input extends string] ? [[_0, _1, _2, _3], Input] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TInstanceTypeMapping<_0, Context>, Input] : [];
export type TReturnType<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'ReturnType', Input> extends [infer _0, infer Input extends string] ? Static.Token.Const<'<', Input> extends [infer _1, infer Input extends string] ? TType<Input, Context> extends [infer _2, infer Input extends string] ? Static.Token.Const<'>', Input> extends [infer _3, infer Input extends string] ? [[_0, _1, _2, _3], Input] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TReturnTypeMapping<_0, Context>, Input] : [];
export type TPartial<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'Partial', Input> extends [infer _0, infer Input extends string] ? Static.Token.Const<'<', Input> extends [infer _1, infer Input extends string] ? TType<Input, Context> extends [infer _2, infer Input extends string] ? Static.Token.Const<'>', Input> extends [infer _3, infer Input extends string] ? [[_0, _1, _2, _3], Input] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TPartialMapping<_0, Context>, Input] : [];
export type TRequired<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'Required', Input> extends [infer _0, infer Input extends string] ? Static.Token.Const<'<', Input> extends [infer _1, infer Input extends string] ? TType<Input, Context> extends [infer _2, infer Input extends string] ? Static.Token.Const<'>', Input> extends [infer _3, infer Input extends string] ? [[_0, _1, _2, _3], Input] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TRequiredMapping<_0, Context>, Input] : [];
export type TPick<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'Pick', Input> extends [infer _0, infer Input extends string] ? Static.Token.Const<'<', Input> extends [infer _1, infer Input extends string] ? TType<Input, Context> extends [infer _2, infer Input extends string] ? Static.Token.Const<',', Input> extends [infer _3, infer Input extends string] ? TType<Input, Context> extends [infer _4, infer Input extends string] ? Static.Token.Const<'>', Input> extends [infer _5, infer Input extends string] ? [[_0, _1, _2, _3, _4, _5], Input] : [] : [] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TPickMapping<_0, Context>, Input] : [];
export type TOmit<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'Omit', Input> extends [infer _0, infer Input extends string] ? Static.Token.Const<'<', Input> extends [infer _1, infer Input extends string] ? TType<Input, Context> extends [infer _2, infer Input extends string] ? Static.Token.Const<',', Input> extends [infer _3, infer Input extends string] ? TType<Input, Context> extends [infer _4, infer Input extends string] ? Static.Token.Const<'>', Input> extends [infer _5, infer Input extends string] ? [[_0, _1, _2, _3, _4, _5], Input] : [] : [] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TOmitMapping<_0, Context>, Input] : [];
export type TExclude<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'Exclude', Input> extends [infer _0, infer Input extends string] ? Static.Token.Const<'<', Input> extends [infer _1, infer Input extends string] ? TType<Input, Context> extends [infer _2, infer Input extends string] ? Static.Token.Const<',', Input> extends [infer _3, infer Input extends string] ? TType<Input, Context> extends [infer _4, infer Input extends string] ? Static.Token.Const<'>', Input> extends [infer _5, infer Input extends string] ? [[_0, _1, _2, _3, _4, _5], Input] : [] : [] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TExcludeMapping<_0, Context>, Input] : [];
export type TExtract<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'Extract', Input> extends [infer _0, infer Input extends string] ? Static.Token.Const<'<', Input> extends [infer _1, infer Input extends string] ? TType<Input, Context> extends [infer _2, infer Input extends string] ? Static.Token.Const<',', Input> extends [infer _3, infer Input extends string] ? TType<Input, Context> extends [infer _4, infer Input extends string] ? Static.Token.Const<'>', Input> extends [infer _5, infer Input extends string] ? [[_0, _1, _2, _3, _4, _5], Input] : [] : [] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TExtractMapping<_0, Context>, Input] : [];
export type TUppercase<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'Uppercase', Input> extends [infer _0, infer Input extends string] ? Static.Token.Const<'<', Input> extends [infer _1, infer Input extends string] ? TType<Input, Context> extends [infer _2, infer Input extends string] ? Static.Token.Const<'>', Input> extends [infer _3, infer Input extends string] ? [[_0, _1, _2, _3], Input] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TUppercaseMapping<_0, Context>, Input] : [];
export type TLowercase<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'Lowercase', Input> extends [infer _0, infer Input extends string] ? Static.Token.Const<'<', Input> extends [infer _1, infer Input extends string] ? TType<Input, Context> extends [infer _2, infer Input extends string] ? Static.Token.Const<'>', Input> extends [infer _3, infer Input extends string] ? [[_0, _1, _2, _3], Input] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TLowercaseMapping<_0, Context>, Input] : [];
export type TCapitalize<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'Capitalize', Input> extends [infer _0, infer Input extends string] ? Static.Token.Const<'<', Input> extends [infer _1, infer Input extends string] ? TType<Input, Context> extends [infer _2, infer Input extends string] ? Static.Token.Const<'>', Input> extends [infer _3, infer Input extends string] ? [[_0, _1, _2, _3], Input] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TCapitalizeMapping<_0, Context>, Input] : [];
export type TUncapitalize<Input extends string, Context extends T.TProperties = {}> = (Static.Token.Const<'Uncapitalize', Input> extends [infer _0, infer Input extends string] ? Static.Token.Const<'<', Input> extends [infer _1, infer Input extends string] ? TType<Input, Context> extends [infer _2, infer Input extends string] ? Static.Token.Const<'>', Input> extends [infer _3, infer Input extends string] ? [[_0, _1, _2, _3], Input] : [] : [] : [] : []) extends [infer _0 extends [unknown, unknown, unknown, unknown], infer Input extends string] ? [S.TUncapitalizeMapping<_0, Context>, Input] : [];
export type TDate<Input extends string, Context extends T.TProperties = {}> = Static.Token.Const<'Date', Input> extends [infer _0 extends 'Date', infer Input extends string] ? [S.TDateMapping<_0, Context>, Input] : [];
export type TUint8Array<Input extends string, Context extends T.TProperties = {}> = Static.Token.Const<'Uint8Array', Input> extends [infer _0 extends 'Uint8Array', infer Input extends string] ? [S.TUint8ArrayMapping<_0, Context>, Input] : [];
export type TReference<Input extends string, Context extends T.TProperties = {}> = Static.Token.Ident<Input> extends [infer _0 extends string, infer Input extends string] ? [S.TReferenceMapping<_0, Context>, Input] : [];
export declare const GenericReferenceParameterList_0: (input: string, context: T.TProperties, result?: unknown[]) => [unknown[], string];
export declare const GenericReferenceParameterList: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const GenericReference: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const GenericArgumentsList_0: (input: string, context: T.TProperties, result?: unknown[]) => [unknown[], string];
export declare const GenericArgumentsList: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const GenericArguments: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const KeywordString: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const KeywordNumber: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const KeywordBoolean: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const KeywordUndefined: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const KeywordNull: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const KeywordInteger: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const KeywordBigInt: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const KeywordUnknown: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const KeywordAny: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const KeywordNever: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const KeywordSymbol: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const KeywordVoid: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Keyword: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const LiteralString: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const LiteralNumber: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const LiteralBoolean: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Literal: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const KeyOf: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const IndexArray_0: (input: string, context: T.TProperties, result?: unknown[]) => [unknown[], string];
export declare const IndexArray: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Extends: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Base: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Factor: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const ExprTermTail: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const ExprTerm: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const ExprTail: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Expr: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Type: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const PropertyKey: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Readonly: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Optional: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Property: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const PropertyDelimiter: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const PropertyList_0: (input: string, context: T.TProperties, result?: unknown[]) => [unknown[], string];
export declare const PropertyList: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const _Object: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const ElementList_0: (input: string, context: T.TProperties, result?: unknown[]) => [unknown[], string];
export declare const ElementList: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Tuple: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Parameter: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const ParameterList_0: (input: string, context: T.TProperties, result?: unknown[]) => [unknown[], string];
export declare const ParameterList: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Function: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Constructor: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Mapped: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const AsyncIterator: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Iterator: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Argument: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Awaited: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Array: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Record: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Promise: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const ConstructorParameters: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const FunctionParameters: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const InstanceType: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const ReturnType: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Partial: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Required: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Pick: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Omit: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Exclude: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Extract: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Uppercase: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Lowercase: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Capitalize: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Uncapitalize: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Date: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Uint8Array: (input: string, context?: T.TProperties) => [unknown, string] | [];
export declare const Reference: (input: string, context?: T.TProperties) => [unknown, string] | [];

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extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/syntax/parser.js generated vendored Normal file
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@ -0,0 +1,191 @@
"use strict";
var __createBinding = (this && this.__createBinding) || (Object.create ? (function(o, m, k, k2) {
if (k2 === undefined) k2 = k;
var desc = Object.getOwnPropertyDescriptor(m, k);
if (!desc || ("get" in desc ? !m.__esModule : desc.writable || desc.configurable)) {
desc = { enumerable: true, get: function() { return m[k]; } };
}
Object.defineProperty(o, k2, desc);
}) : (function(o, m, k, k2) {
if (k2 === undefined) k2 = k;
o[k2] = m[k];
}));
var __setModuleDefault = (this && this.__setModuleDefault) || (Object.create ? (function(o, v) {
Object.defineProperty(o, "default", { enumerable: true, value: v });
}) : function(o, v) {
o["default"] = v;
});
var __importStar = (this && this.__importStar) || (function () {
var ownKeys = function(o) {
ownKeys = Object.getOwnPropertyNames || function (o) {
var ar = [];
for (var k in o) if (Object.prototype.hasOwnProperty.call(o, k)) ar[ar.length] = k;
return ar;
};
return ownKeys(o);
};
return function (mod) {
if (mod && mod.__esModule) return mod;
var result = {};
if (mod != null) for (var k = ownKeys(mod), i = 0; i < k.length; i++) if (k[i] !== "default") __createBinding(result, mod, k[i]);
__setModuleDefault(result, mod);
return result;
};
})();
Object.defineProperty(exports, "__esModule", { value: true });
exports.Constructor = exports.Function = exports.ParameterList = exports.ParameterList_0 = exports.Parameter = exports.Tuple = exports.ElementList = exports.ElementList_0 = exports._Object = exports.PropertyList = exports.PropertyList_0 = exports.PropertyDelimiter = exports.Property = exports.Optional = exports.Readonly = exports.PropertyKey = exports.Type = exports.Expr = exports.ExprTail = exports.ExprTerm = exports.ExprTermTail = exports.Factor = exports.Base = exports.Extends = exports.IndexArray = exports.IndexArray_0 = exports.KeyOf = exports.Literal = exports.LiteralBoolean = exports.LiteralNumber = exports.LiteralString = exports.Keyword = exports.KeywordVoid = exports.KeywordSymbol = exports.KeywordNever = exports.KeywordAny = exports.KeywordUnknown = exports.KeywordBigInt = exports.KeywordInteger = exports.KeywordNull = exports.KeywordUndefined = exports.KeywordBoolean = exports.KeywordNumber = exports.KeywordString = exports.GenericArguments = exports.GenericArgumentsList = exports.GenericArgumentsList_0 = exports.GenericReference = exports.GenericReferenceParameterList = exports.GenericReferenceParameterList_0 = void 0;
exports.Reference = exports.Uint8Array = exports.Date = exports.Uncapitalize = exports.Capitalize = exports.Lowercase = exports.Uppercase = exports.Extract = exports.Exclude = exports.Omit = exports.Pick = exports.Required = exports.Partial = exports.ReturnType = exports.InstanceType = exports.FunctionParameters = exports.ConstructorParameters = exports.Promise = exports.Record = exports.Array = exports.Awaited = exports.Argument = exports.Iterator = exports.AsyncIterator = exports.Mapped = void 0;
const index_1 = require("../parser/index");
const S = __importStar(require("./mapping"));
const If = (result, left, right = () => []) => (result.length === 2 ? left(result) : right());
const GenericReferenceParameterList_0 = (input, context, result = []) => If(If((0, exports.Type)(input, context), ([_0, input]) => If(index_1.Runtime.Token.Const(',', input), ([_1, input]) => [[_0, _1], input])), ([_0, input]) => (0, exports.GenericReferenceParameterList_0)(input, context, [...result, _0]), () => [result, input]);
exports.GenericReferenceParameterList_0 = GenericReferenceParameterList_0;
const GenericReferenceParameterList = (input, context = {}) => If(If((0, exports.GenericReferenceParameterList_0)(input, context), ([_0, input]) => If(If(If((0, exports.Type)(input, context), ([_0, input]) => [[_0], input]), ([_0, input]) => [_0, input], () => If([[], input], ([_0, input]) => [_0, input], () => [])), ([_1, input]) => [[_0, _1], input])), ([_0, input]) => [S.GenericReferenceParameterListMapping(_0, context), input]);
exports.GenericReferenceParameterList = GenericReferenceParameterList;
const GenericReference = (input, context = {}) => If(If(index_1.Runtime.Token.Ident(input), ([_0, input]) => If(index_1.Runtime.Token.Const('<', input), ([_1, input]) => If((0, exports.GenericReferenceParameterList)(input, context), ([_2, input]) => If(index_1.Runtime.Token.Const('>', input), ([_3, input]) => [[_0, _1, _2, _3], input])))), ([_0, input]) => [S.GenericReferenceMapping(_0, context), input]);
exports.GenericReference = GenericReference;
const GenericArgumentsList_0 = (input, context, result = []) => If(If(index_1.Runtime.Token.Ident(input), ([_0, input]) => If(index_1.Runtime.Token.Const(',', input), ([_1, input]) => [[_0, _1], input])), ([_0, input]) => (0, exports.GenericArgumentsList_0)(input, context, [...result, _0]), () => [result, input]);
exports.GenericArgumentsList_0 = GenericArgumentsList_0;
const GenericArgumentsList = (input, context = {}) => If(If((0, exports.GenericArgumentsList_0)(input, context), ([_0, input]) => If(If(If(index_1.Runtime.Token.Ident(input), ([_0, input]) => [[_0], input]), ([_0, input]) => [_0, input], () => If([[], input], ([_0, input]) => [_0, input], () => [])), ([_1, input]) => [[_0, _1], input])), ([_0, input]) => [S.GenericArgumentsListMapping(_0, context), input]);
exports.GenericArgumentsList = GenericArgumentsList;
const GenericArguments = (input, context = {}) => If(If(index_1.Runtime.Token.Const('<', input), ([_0, input]) => If((0, exports.GenericArgumentsList)(input, context), ([_1, input]) => If(index_1.Runtime.Token.Const('>', input), ([_2, input]) => [[_0, _1, _2], input]))), ([_0, input]) => [S.GenericArgumentsMapping(_0, context), input]);
exports.GenericArguments = GenericArguments;
const KeywordString = (input, context = {}) => If(index_1.Runtime.Token.Const('string', input), ([_0, input]) => [S.KeywordStringMapping(_0, context), input]);
exports.KeywordString = KeywordString;
const KeywordNumber = (input, context = {}) => If(index_1.Runtime.Token.Const('number', input), ([_0, input]) => [S.KeywordNumberMapping(_0, context), input]);
exports.KeywordNumber = KeywordNumber;
const KeywordBoolean = (input, context = {}) => If(index_1.Runtime.Token.Const('boolean', input), ([_0, input]) => [S.KeywordBooleanMapping(_0, context), input]);
exports.KeywordBoolean = KeywordBoolean;
const KeywordUndefined = (input, context = {}) => If(index_1.Runtime.Token.Const('undefined', input), ([_0, input]) => [S.KeywordUndefinedMapping(_0, context), input]);
exports.KeywordUndefined = KeywordUndefined;
const KeywordNull = (input, context = {}) => If(index_1.Runtime.Token.Const('null', input), ([_0, input]) => [S.KeywordNullMapping(_0, context), input]);
exports.KeywordNull = KeywordNull;
const KeywordInteger = (input, context = {}) => If(index_1.Runtime.Token.Const('integer', input), ([_0, input]) => [S.KeywordIntegerMapping(_0, context), input]);
exports.KeywordInteger = KeywordInteger;
const KeywordBigInt = (input, context = {}) => If(index_1.Runtime.Token.Const('bigint', input), ([_0, input]) => [S.KeywordBigIntMapping(_0, context), input]);
exports.KeywordBigInt = KeywordBigInt;
const KeywordUnknown = (input, context = {}) => If(index_1.Runtime.Token.Const('unknown', input), ([_0, input]) => [S.KeywordUnknownMapping(_0, context), input]);
exports.KeywordUnknown = KeywordUnknown;
const KeywordAny = (input, context = {}) => If(index_1.Runtime.Token.Const('any', input), ([_0, input]) => [S.KeywordAnyMapping(_0, context), input]);
exports.KeywordAny = KeywordAny;
const KeywordNever = (input, context = {}) => If(index_1.Runtime.Token.Const('never', input), ([_0, input]) => [S.KeywordNeverMapping(_0, context), input]);
exports.KeywordNever = KeywordNever;
const KeywordSymbol = (input, context = {}) => If(index_1.Runtime.Token.Const('symbol', input), ([_0, input]) => [S.KeywordSymbolMapping(_0, context), input]);
exports.KeywordSymbol = KeywordSymbol;
const KeywordVoid = (input, context = {}) => If(index_1.Runtime.Token.Const('void', input), ([_0, input]) => [S.KeywordVoidMapping(_0, context), input]);
exports.KeywordVoid = KeywordVoid;
const Keyword = (input, context = {}) => If(If((0, exports.KeywordString)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.KeywordNumber)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.KeywordBoolean)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.KeywordUndefined)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.KeywordNull)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.KeywordInteger)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.KeywordBigInt)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.KeywordUnknown)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.KeywordAny)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.KeywordNever)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.KeywordSymbol)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.KeywordVoid)(input, context), ([_0, input]) => [_0, input], () => [])))))))))))), ([_0, input]) => [S.KeywordMapping(_0, context), input]);
exports.Keyword = Keyword;
const LiteralString = (input, context = {}) => If(index_1.Runtime.Token.String(["'", '"', '`'], input), ([_0, input]) => [S.LiteralStringMapping(_0, context), input]);
exports.LiteralString = LiteralString;
const LiteralNumber = (input, context = {}) => If(index_1.Runtime.Token.Number(input), ([_0, input]) => [S.LiteralNumberMapping(_0, context), input]);
exports.LiteralNumber = LiteralNumber;
const LiteralBoolean = (input, context = {}) => If(If(index_1.Runtime.Token.Const('true', input), ([_0, input]) => [_0, input], () => If(index_1.Runtime.Token.Const('false', input), ([_0, input]) => [_0, input], () => [])), ([_0, input]) => [S.LiteralBooleanMapping(_0, context), input]);
exports.LiteralBoolean = LiteralBoolean;
const Literal = (input, context = {}) => If(If((0, exports.LiteralBoolean)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.LiteralNumber)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.LiteralString)(input, context), ([_0, input]) => [_0, input], () => []))), ([_0, input]) => [S.LiteralMapping(_0, context), input]);
exports.Literal = Literal;
const KeyOf = (input, context = {}) => If(If(If(index_1.Runtime.Token.Const('keyof', input), ([_0, input]) => [[_0], input]), ([_0, input]) => [_0, input], () => If([[], input], ([_0, input]) => [_0, input], () => [])), ([_0, input]) => [S.KeyOfMapping(_0, context), input]);
exports.KeyOf = KeyOf;
const IndexArray_0 = (input, context, result = []) => If(If(If(index_1.Runtime.Token.Const('[', input), ([_0, input]) => If((0, exports.Type)(input, context), ([_1, input]) => If(index_1.Runtime.Token.Const(']', input), ([_2, input]) => [[_0, _1, _2], input]))), ([_0, input]) => [_0, input], () => If(If(index_1.Runtime.Token.Const('[', input), ([_0, input]) => If(index_1.Runtime.Token.Const(']', input), ([_1, input]) => [[_0, _1], input])), ([_0, input]) => [_0, input], () => [])), ([_0, input]) => (0, exports.IndexArray_0)(input, context, [...result, _0]), () => [result, input]);
exports.IndexArray_0 = IndexArray_0;
const IndexArray = (input, context = {}) => If((0, exports.IndexArray_0)(input, context), ([_0, input]) => [S.IndexArrayMapping(_0, context), input]);
exports.IndexArray = IndexArray;
const Extends = (input, context = {}) => If(If(If(index_1.Runtime.Token.Const('extends', input), ([_0, input]) => If((0, exports.Type)(input, context), ([_1, input]) => If(index_1.Runtime.Token.Const('?', input), ([_2, input]) => If((0, exports.Type)(input, context), ([_3, input]) => If(index_1.Runtime.Token.Const(':', input), ([_4, input]) => If((0, exports.Type)(input, context), ([_5, input]) => [[_0, _1, _2, _3, _4, _5], input])))))), ([_0, input]) => [_0, input], () => If([[], input], ([_0, input]) => [_0, input], () => [])), ([_0, input]) => [S.ExtendsMapping(_0, context), input]);
exports.Extends = Extends;
const Base = (input, context = {}) => If(If(If(index_1.Runtime.Token.Const('(', input), ([_0, input]) => If((0, exports.Type)(input, context), ([_1, input]) => If(index_1.Runtime.Token.Const(')', input), ([_2, input]) => [[_0, _1, _2], input]))), ([_0, input]) => [_0, input], () => If((0, exports.Keyword)(input, context), ([_0, input]) => [_0, input], () => If((0, exports._Object)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.Tuple)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.Literal)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.Constructor)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.Function)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.Mapped)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.AsyncIterator)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.Iterator)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.ConstructorParameters)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.FunctionParameters)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.InstanceType)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.ReturnType)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.Argument)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.Awaited)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.Array)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.Record)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.Promise)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.Partial)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.Required)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.Pick)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.Omit)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.Exclude)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.Extract)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.Uppercase)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.Lowercase)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.Capitalize)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.Uncapitalize)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.Date)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.Uint8Array)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.GenericReference)(input, context), ([_0, input]) => [_0, input], () => If((0, exports.Reference)(input, context), ([_0, input]) => [_0, input], () => []))))))))))))))))))))))))))))))))), ([_0, input]) => [S.BaseMapping(_0, context), input]);
exports.Base = Base;
const Factor = (input, context = {}) => If(If((0, exports.KeyOf)(input, context), ([_0, input]) => If((0, exports.Base)(input, context), ([_1, input]) => If((0, exports.IndexArray)(input, context), ([_2, input]) => If((0, exports.Extends)(input, context), ([_3, input]) => [[_0, _1, _2, _3], input])))), ([_0, input]) => [S.FactorMapping(_0, context), input]);
exports.Factor = Factor;
const ExprTermTail = (input, context = {}) => If(If(If(index_1.Runtime.Token.Const('&', input), ([_0, input]) => If((0, exports.Factor)(input, context), ([_1, input]) => If((0, exports.ExprTermTail)(input, context), ([_2, input]) => [[_0, _1, _2], input]))), ([_0, input]) => [_0, input], () => If([[], input], ([_0, input]) => [_0, input], () => [])), ([_0, input]) => [S.ExprTermTailMapping(_0, context), input]);
exports.ExprTermTail = ExprTermTail;
const ExprTerm = (input, context = {}) => If(If((0, exports.Factor)(input, context), ([_0, input]) => If((0, exports.ExprTermTail)(input, context), ([_1, input]) => [[_0, _1], input])), ([_0, input]) => [S.ExprTermMapping(_0, context), input]);
exports.ExprTerm = ExprTerm;
const ExprTail = (input, context = {}) => If(If(If(index_1.Runtime.Token.Const('|', input), ([_0, input]) => If((0, exports.ExprTerm)(input, context), ([_1, input]) => If((0, exports.ExprTail)(input, context), ([_2, input]) => [[_0, _1, _2], input]))), ([_0, input]) => [_0, input], () => If([[], input], ([_0, input]) => [_0, input], () => [])), ([_0, input]) => [S.ExprTailMapping(_0, context), input]);
exports.ExprTail = ExprTail;
const Expr = (input, context = {}) => If(If((0, exports.ExprTerm)(input, context), ([_0, input]) => If((0, exports.ExprTail)(input, context), ([_1, input]) => [[_0, _1], input])), ([_0, input]) => [S.ExprMapping(_0, context), input]);
exports.Expr = Expr;
const Type = (input, context = {}) => If(If(If((0, exports.GenericArguments)(input, context), ([_0, input]) => (0, exports.Expr)(input, _0), () => []), ([_0, input]) => [_0, input], () => If((0, exports.Expr)(input, context), ([_0, input]) => [_0, input], () => [])), ([_0, input]) => [S.TypeMapping(_0, context), input]);
exports.Type = Type;
const PropertyKey = (input, context = {}) => If(If(index_1.Runtime.Token.Ident(input), ([_0, input]) => [_0, input], () => If(index_1.Runtime.Token.String(["'", '"'], input), ([_0, input]) => [_0, input], () => [])), ([_0, input]) => [S.PropertyKeyMapping(_0, context), input]);
exports.PropertyKey = PropertyKey;
const Readonly = (input, context = {}) => If(If(If(index_1.Runtime.Token.Const('readonly', input), ([_0, input]) => [[_0], input]), ([_0, input]) => [_0, input], () => If([[], input], ([_0, input]) => [_0, input], () => [])), ([_0, input]) => [S.ReadonlyMapping(_0, context), input]);
exports.Readonly = Readonly;
const Optional = (input, context = {}) => If(If(If(index_1.Runtime.Token.Const('?', input), ([_0, input]) => [[_0], input]), ([_0, input]) => [_0, input], () => If([[], input], ([_0, input]) => [_0, input], () => [])), ([_0, input]) => [S.OptionalMapping(_0, context), input]);
exports.Optional = Optional;
const Property = (input, context = {}) => If(If((0, exports.Readonly)(input, context), ([_0, input]) => If((0, exports.PropertyKey)(input, context), ([_1, input]) => If((0, exports.Optional)(input, context), ([_2, input]) => If(index_1.Runtime.Token.Const(':', input), ([_3, input]) => If((0, exports.Type)(input, context), ([_4, input]) => [[_0, _1, _2, _3, _4], input]))))), ([_0, input]) => [S.PropertyMapping(_0, context), input]);
exports.Property = Property;
const PropertyDelimiter = (input, context = {}) => If(If(If(index_1.Runtime.Token.Const(',', input), ([_0, input]) => If(index_1.Runtime.Token.Const('\n', input), ([_1, input]) => [[_0, _1], input])), ([_0, input]) => [_0, input], () => If(If(index_1.Runtime.Token.Const(';', input), ([_0, input]) => If(index_1.Runtime.Token.Const('\n', input), ([_1, input]) => [[_0, _1], input])), ([_0, input]) => [_0, input], () => If(If(index_1.Runtime.Token.Const(',', input), ([_0, input]) => [[_0], input]), ([_0, input]) => [_0, input], () => If(If(index_1.Runtime.Token.Const(';', input), ([_0, input]) => [[_0], input]), ([_0, input]) => [_0, input], () => If(If(index_1.Runtime.Token.Const('\n', input), ([_0, input]) => [[_0], input]), ([_0, input]) => [_0, input], () => []))))), ([_0, input]) => [S.PropertyDelimiterMapping(_0, context), input]);
exports.PropertyDelimiter = PropertyDelimiter;
const PropertyList_0 = (input, context, result = []) => If(If((0, exports.Property)(input, context), ([_0, input]) => If((0, exports.PropertyDelimiter)(input, context), ([_1, input]) => [[_0, _1], input])), ([_0, input]) => (0, exports.PropertyList_0)(input, context, [...result, _0]), () => [result, input]);
exports.PropertyList_0 = PropertyList_0;
const PropertyList = (input, context = {}) => If(If((0, exports.PropertyList_0)(input, context), ([_0, input]) => If(If(If((0, exports.Property)(input, context), ([_0, input]) => [[_0], input]), ([_0, input]) => [_0, input], () => If([[], input], ([_0, input]) => [_0, input], () => [])), ([_1, input]) => [[_0, _1], input])), ([_0, input]) => [S.PropertyListMapping(_0, context), input]);
exports.PropertyList = PropertyList;
const _Object = (input, context = {}) => If(If(index_1.Runtime.Token.Const('{', input), ([_0, input]) => If((0, exports.PropertyList)(input, context), ([_1, input]) => If(index_1.Runtime.Token.Const('}', input), ([_2, input]) => [[_0, _1, _2], input]))), ([_0, input]) => [S.ObjectMapping(_0, context), input]);
exports._Object = _Object;
const ElementList_0 = (input, context, result = []) => If(If((0, exports.Type)(input, context), ([_0, input]) => If(index_1.Runtime.Token.Const(',', input), ([_1, input]) => [[_0, _1], input])), ([_0, input]) => (0, exports.ElementList_0)(input, context, [...result, _0]), () => [result, input]);
exports.ElementList_0 = ElementList_0;
const ElementList = (input, context = {}) => If(If((0, exports.ElementList_0)(input, context), ([_0, input]) => If(If(If((0, exports.Type)(input, context), ([_0, input]) => [[_0], input]), ([_0, input]) => [_0, input], () => If([[], input], ([_0, input]) => [_0, input], () => [])), ([_1, input]) => [[_0, _1], input])), ([_0, input]) => [S.ElementListMapping(_0, context), input]);
exports.ElementList = ElementList;
const Tuple = (input, context = {}) => If(If(index_1.Runtime.Token.Const('[', input), ([_0, input]) => If((0, exports.ElementList)(input, context), ([_1, input]) => If(index_1.Runtime.Token.Const(']', input), ([_2, input]) => [[_0, _1, _2], input]))), ([_0, input]) => [S.TupleMapping(_0, context), input]);
exports.Tuple = Tuple;
const Parameter = (input, context = {}) => If(If(index_1.Runtime.Token.Ident(input), ([_0, input]) => If(index_1.Runtime.Token.Const(':', input), ([_1, input]) => If((0, exports.Type)(input, context), ([_2, input]) => [[_0, _1, _2], input]))), ([_0, input]) => [S.ParameterMapping(_0, context), input]);
exports.Parameter = Parameter;
const ParameterList_0 = (input, context, result = []) => If(If((0, exports.Parameter)(input, context), ([_0, input]) => If(index_1.Runtime.Token.Const(',', input), ([_1, input]) => [[_0, _1], input])), ([_0, input]) => (0, exports.ParameterList_0)(input, context, [...result, _0]), () => [result, input]);
exports.ParameterList_0 = ParameterList_0;
const ParameterList = (input, context = {}) => If(If((0, exports.ParameterList_0)(input, context), ([_0, input]) => If(If(If((0, exports.Parameter)(input, context), ([_0, input]) => [[_0], input]), ([_0, input]) => [_0, input], () => If([[], input], ([_0, input]) => [_0, input], () => [])), ([_1, input]) => [[_0, _1], input])), ([_0, input]) => [S.ParameterListMapping(_0, context), input]);
exports.ParameterList = ParameterList;
const Function = (input, context = {}) => If(If(index_1.Runtime.Token.Const('(', input), ([_0, input]) => If((0, exports.ParameterList)(input, context), ([_1, input]) => If(index_1.Runtime.Token.Const(')', input), ([_2, input]) => If(index_1.Runtime.Token.Const('=>', input), ([_3, input]) => If((0, exports.Type)(input, context), ([_4, input]) => [[_0, _1, _2, _3, _4], input]))))), ([_0, input]) => [S.FunctionMapping(_0, context), input]);
exports.Function = Function;
const Constructor = (input, context = {}) => If(If(index_1.Runtime.Token.Const('new', input), ([_0, input]) => If(index_1.Runtime.Token.Const('(', input), ([_1, input]) => If((0, exports.ParameterList)(input, context), ([_2, input]) => If(index_1.Runtime.Token.Const(')', input), ([_3, input]) => If(index_1.Runtime.Token.Const('=>', input), ([_4, input]) => If((0, exports.Type)(input, context), ([_5, input]) => [[_0, _1, _2, _3, _4, _5], input])))))), ([_0, input]) => [S.ConstructorMapping(_0, context), input]);
exports.Constructor = Constructor;
const Mapped = (input, context = {}) => If(If(index_1.Runtime.Token.Const('{', input), ([_0, input]) => If(index_1.Runtime.Token.Const('[', input), ([_1, input]) => If(index_1.Runtime.Token.Ident(input), ([_2, input]) => If(index_1.Runtime.Token.Const('in', input), ([_3, input]) => If((0, exports.Type)(input, context), ([_4, input]) => If(index_1.Runtime.Token.Const(']', input), ([_5, input]) => If(index_1.Runtime.Token.Const(':', input), ([_6, input]) => If((0, exports.Type)(input, context), ([_7, input]) => If(index_1.Runtime.Token.Const('}', input), ([_8, input]) => [[_0, _1, _2, _3, _4, _5, _6, _7, _8], input]))))))))), ([_0, input]) => [S.MappedMapping(_0, context), input]);
exports.Mapped = Mapped;
const AsyncIterator = (input, context = {}) => If(If(index_1.Runtime.Token.Const('AsyncIterator', input), ([_0, input]) => If(index_1.Runtime.Token.Const('<', input), ([_1, input]) => If((0, exports.Type)(input, context), ([_2, input]) => If(index_1.Runtime.Token.Const('>', input), ([_3, input]) => [[_0, _1, _2, _3], input])))), ([_0, input]) => [S.AsyncIteratorMapping(_0, context), input]);
exports.AsyncIterator = AsyncIterator;
const Iterator = (input, context = {}) => If(If(index_1.Runtime.Token.Const('Iterator', input), ([_0, input]) => If(index_1.Runtime.Token.Const('<', input), ([_1, input]) => If((0, exports.Type)(input, context), ([_2, input]) => If(index_1.Runtime.Token.Const('>', input), ([_3, input]) => [[_0, _1, _2, _3], input])))), ([_0, input]) => [S.IteratorMapping(_0, context), input]);
exports.Iterator = Iterator;
const Argument = (input, context = {}) => If(If(index_1.Runtime.Token.Const('Argument', input), ([_0, input]) => If(index_1.Runtime.Token.Const('<', input), ([_1, input]) => If((0, exports.Type)(input, context), ([_2, input]) => If(index_1.Runtime.Token.Const('>', input), ([_3, input]) => [[_0, _1, _2, _3], input])))), ([_0, input]) => [S.ArgumentMapping(_0, context), input]);
exports.Argument = Argument;
const Awaited = (input, context = {}) => If(If(index_1.Runtime.Token.Const('Awaited', input), ([_0, input]) => If(index_1.Runtime.Token.Const('<', input), ([_1, input]) => If((0, exports.Type)(input, context), ([_2, input]) => If(index_1.Runtime.Token.Const('>', input), ([_3, input]) => [[_0, _1, _2, _3], input])))), ([_0, input]) => [S.AwaitedMapping(_0, context), input]);
exports.Awaited = Awaited;
const Array = (input, context = {}) => If(If(index_1.Runtime.Token.Const('Array', input), ([_0, input]) => If(index_1.Runtime.Token.Const('<', input), ([_1, input]) => If((0, exports.Type)(input, context), ([_2, input]) => If(index_1.Runtime.Token.Const('>', input), ([_3, input]) => [[_0, _1, _2, _3], input])))), ([_0, input]) => [S.ArrayMapping(_0, context), input]);
exports.Array = Array;
const Record = (input, context = {}) => If(If(index_1.Runtime.Token.Const('Record', input), ([_0, input]) => If(index_1.Runtime.Token.Const('<', input), ([_1, input]) => If((0, exports.Type)(input, context), ([_2, input]) => If(index_1.Runtime.Token.Const(',', input), ([_3, input]) => If((0, exports.Type)(input, context), ([_4, input]) => If(index_1.Runtime.Token.Const('>', input), ([_5, input]) => [[_0, _1, _2, _3, _4, _5], input])))))), ([_0, input]) => [S.RecordMapping(_0, context), input]);
exports.Record = Record;
const Promise = (input, context = {}) => If(If(index_1.Runtime.Token.Const('Promise', input), ([_0, input]) => If(index_1.Runtime.Token.Const('<', input), ([_1, input]) => If((0, exports.Type)(input, context), ([_2, input]) => If(index_1.Runtime.Token.Const('>', input), ([_3, input]) => [[_0, _1, _2, _3], input])))), ([_0, input]) => [S.PromiseMapping(_0, context), input]);
exports.Promise = Promise;
const ConstructorParameters = (input, context = {}) => If(If(index_1.Runtime.Token.Const('ConstructorParameters', input), ([_0, input]) => If(index_1.Runtime.Token.Const('<', input), ([_1, input]) => If((0, exports.Type)(input, context), ([_2, input]) => If(index_1.Runtime.Token.Const('>', input), ([_3, input]) => [[_0, _1, _2, _3], input])))), ([_0, input]) => [S.ConstructorParametersMapping(_0, context), input]);
exports.ConstructorParameters = ConstructorParameters;
const FunctionParameters = (input, context = {}) => If(If(index_1.Runtime.Token.Const('Parameters', input), ([_0, input]) => If(index_1.Runtime.Token.Const('<', input), ([_1, input]) => If((0, exports.Type)(input, context), ([_2, input]) => If(index_1.Runtime.Token.Const('>', input), ([_3, input]) => [[_0, _1, _2, _3], input])))), ([_0, input]) => [S.FunctionParametersMapping(_0, context), input]);
exports.FunctionParameters = FunctionParameters;
const InstanceType = (input, context = {}) => If(If(index_1.Runtime.Token.Const('InstanceType', input), ([_0, input]) => If(index_1.Runtime.Token.Const('<', input), ([_1, input]) => If((0, exports.Type)(input, context), ([_2, input]) => If(index_1.Runtime.Token.Const('>', input), ([_3, input]) => [[_0, _1, _2, _3], input])))), ([_0, input]) => [S.InstanceTypeMapping(_0, context), input]);
exports.InstanceType = InstanceType;
const ReturnType = (input, context = {}) => If(If(index_1.Runtime.Token.Const('ReturnType', input), ([_0, input]) => If(index_1.Runtime.Token.Const('<', input), ([_1, input]) => If((0, exports.Type)(input, context), ([_2, input]) => If(index_1.Runtime.Token.Const('>', input), ([_3, input]) => [[_0, _1, _2, _3], input])))), ([_0, input]) => [S.ReturnTypeMapping(_0, context), input]);
exports.ReturnType = ReturnType;
const Partial = (input, context = {}) => If(If(index_1.Runtime.Token.Const('Partial', input), ([_0, input]) => If(index_1.Runtime.Token.Const('<', input), ([_1, input]) => If((0, exports.Type)(input, context), ([_2, input]) => If(index_1.Runtime.Token.Const('>', input), ([_3, input]) => [[_0, _1, _2, _3], input])))), ([_0, input]) => [S.PartialMapping(_0, context), input]);
exports.Partial = Partial;
const Required = (input, context = {}) => If(If(index_1.Runtime.Token.Const('Required', input), ([_0, input]) => If(index_1.Runtime.Token.Const('<', input), ([_1, input]) => If((0, exports.Type)(input, context), ([_2, input]) => If(index_1.Runtime.Token.Const('>', input), ([_3, input]) => [[_0, _1, _2, _3], input])))), ([_0, input]) => [S.RequiredMapping(_0, context), input]);
exports.Required = Required;
const Pick = (input, context = {}) => If(If(index_1.Runtime.Token.Const('Pick', input), ([_0, input]) => If(index_1.Runtime.Token.Const('<', input), ([_1, input]) => If((0, exports.Type)(input, context), ([_2, input]) => If(index_1.Runtime.Token.Const(',', input), ([_3, input]) => If((0, exports.Type)(input, context), ([_4, input]) => If(index_1.Runtime.Token.Const('>', input), ([_5, input]) => [[_0, _1, _2, _3, _4, _5], input])))))), ([_0, input]) => [S.PickMapping(_0, context), input]);
exports.Pick = Pick;
const Omit = (input, context = {}) => If(If(index_1.Runtime.Token.Const('Omit', input), ([_0, input]) => If(index_1.Runtime.Token.Const('<', input), ([_1, input]) => If((0, exports.Type)(input, context), ([_2, input]) => If(index_1.Runtime.Token.Const(',', input), ([_3, input]) => If((0, exports.Type)(input, context), ([_4, input]) => If(index_1.Runtime.Token.Const('>', input), ([_5, input]) => [[_0, _1, _2, _3, _4, _5], input])))))), ([_0, input]) => [S.OmitMapping(_0, context), input]);
exports.Omit = Omit;
const Exclude = (input, context = {}) => If(If(index_1.Runtime.Token.Const('Exclude', input), ([_0, input]) => If(index_1.Runtime.Token.Const('<', input), ([_1, input]) => If((0, exports.Type)(input, context), ([_2, input]) => If(index_1.Runtime.Token.Const(',', input), ([_3, input]) => If((0, exports.Type)(input, context), ([_4, input]) => If(index_1.Runtime.Token.Const('>', input), ([_5, input]) => [[_0, _1, _2, _3, _4, _5], input])))))), ([_0, input]) => [S.ExcludeMapping(_0, context), input]);
exports.Exclude = Exclude;
const Extract = (input, context = {}) => If(If(index_1.Runtime.Token.Const('Extract', input), ([_0, input]) => If(index_1.Runtime.Token.Const('<', input), ([_1, input]) => If((0, exports.Type)(input, context), ([_2, input]) => If(index_1.Runtime.Token.Const(',', input), ([_3, input]) => If((0, exports.Type)(input, context), ([_4, input]) => If(index_1.Runtime.Token.Const('>', input), ([_5, input]) => [[_0, _1, _2, _3, _4, _5], input])))))), ([_0, input]) => [S.ExtractMapping(_0, context), input]);
exports.Extract = Extract;
const Uppercase = (input, context = {}) => If(If(index_1.Runtime.Token.Const('Uppercase', input), ([_0, input]) => If(index_1.Runtime.Token.Const('<', input), ([_1, input]) => If((0, exports.Type)(input, context), ([_2, input]) => If(index_1.Runtime.Token.Const('>', input), ([_3, input]) => [[_0, _1, _2, _3], input])))), ([_0, input]) => [S.UppercaseMapping(_0, context), input]);
exports.Uppercase = Uppercase;
const Lowercase = (input, context = {}) => If(If(index_1.Runtime.Token.Const('Lowercase', input), ([_0, input]) => If(index_1.Runtime.Token.Const('<', input), ([_1, input]) => If((0, exports.Type)(input, context), ([_2, input]) => If(index_1.Runtime.Token.Const('>', input), ([_3, input]) => [[_0, _1, _2, _3], input])))), ([_0, input]) => [S.LowercaseMapping(_0, context), input]);
exports.Lowercase = Lowercase;
const Capitalize = (input, context = {}) => If(If(index_1.Runtime.Token.Const('Capitalize', input), ([_0, input]) => If(index_1.Runtime.Token.Const('<', input), ([_1, input]) => If((0, exports.Type)(input, context), ([_2, input]) => If(index_1.Runtime.Token.Const('>', input), ([_3, input]) => [[_0, _1, _2, _3], input])))), ([_0, input]) => [S.CapitalizeMapping(_0, context), input]);
exports.Capitalize = Capitalize;
const Uncapitalize = (input, context = {}) => If(If(index_1.Runtime.Token.Const('Uncapitalize', input), ([_0, input]) => If(index_1.Runtime.Token.Const('<', input), ([_1, input]) => If((0, exports.Type)(input, context), ([_2, input]) => If(index_1.Runtime.Token.Const('>', input), ([_3, input]) => [[_0, _1, _2, _3], input])))), ([_0, input]) => [S.UncapitalizeMapping(_0, context), input]);
exports.Uncapitalize = Uncapitalize;
const Date = (input, context = {}) => If(index_1.Runtime.Token.Const('Date', input), ([_0, input]) => [S.DateMapping(_0, context), input]);
exports.Date = Date;
const Uint8Array = (input, context = {}) => If(index_1.Runtime.Token.Const('Uint8Array', input), ([_0, input]) => [S.Uint8ArrayMapping(_0, context), input]);
exports.Uint8Array = Uint8Array;
const Reference = (input, context = {}) => If(index_1.Runtime.Token.Ident(input), ([_0, input]) => [S.ReferenceMapping(_0, context), input]);
exports.Reference = Reference;

12
extensions/memory-lancedb/node_modules/@sinclair/typebox/build/cjs/syntax/syntax.d.ts generated vendored Normal file
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@ -0,0 +1,12 @@
import * as t from '../type/index';
import { TType } from './parser';
/** `[Experimental]` Parses type expressions into TypeBox types but does not infer */
export declare function NoInfer<Context extends Record<PropertyKey, t.TSchema>, Input extends string>(context: Context, input: Input, options?: t.SchemaOptions): t.TSchema;
/** `[Experimental]` Parses type expressions into TypeBox types but does not infer */
export declare function NoInfer<Input extends string>(input: Input, options?: t.SchemaOptions): t.TSchema;
/** `[Experimental]` Parses type expressions into TypeBox types */
export type TSyntax<Context extends Record<PropertyKey, t.TSchema>, Code extends string> = (TType<Code, Context> extends [infer Type extends t.TSchema, string] ? Type : t.TNever);
/** `[Experimental]` Parses type expressions into TypeBox types */
export declare function Syntax<Context extends Record<PropertyKey, t.TSchema>, Input extends string>(context: Context, input: Input, options?: t.SchemaOptions): TSyntax<Context, Input>;
/** `[Experimental]` Parses type expressions into TypeBox types */
export declare function Syntax<Input extends string>(annotation: Input, options?: t.SchemaOptions): TSyntax<{}, Input>;

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