Merge 81518603e4 into da71eaebd2
This commit is contained in:
commit
34e56da345
@ -1030,6 +1030,7 @@
|
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"providers/vercel-ai-gateway",
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"providers/openrouter",
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"providers/synthetic",
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"providers/litellm",
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"providers/opencode",
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"providers/glm",
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"providers/zai"
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131
docs/providers/litellm.md
Normal file
131
docs/providers/litellm.md
Normal file
@ -0,0 +1,131 @@
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---
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summary: "Use LiteLLM as an OpenAI-compatible proxy in OpenClaw"
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read_when:
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- You want to use LiteLLM as a model provider
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- You need to connect to a self-hosted LiteLLM proxy
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- You want to use any model through an OpenAI-compatible API
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---
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# LiteLLM
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LiteLLM is an OpenAI-compatible proxy that supports 100+ LLM APIs. OpenClaw
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registers it as the `litellm` provider and uses the OpenAI Completions API.
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## Quick setup
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1) Set up your LiteLLM proxy (see [LiteLLM docs](https://docs.litellm.ai/))
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2) Set environment variables (optional):
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- `LITELLM_API_KEY` - your LiteLLM API key
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- `LITELLM_BASE_URL` - your LiteLLM endpoint (default: `http://localhost:4000`)
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- `LITELLM_MODEL` - default model name (default: `gpt-4`)
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3) Run onboarding:
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```bash
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openclaw onboard --auth-choice litellm-api-key
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```
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The wizard will prompt for:
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- Base URL (your LiteLLM proxy endpoint)
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- API key
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- Model name (as configured in your LiteLLM proxy)
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||||
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||||
## Config example
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```json5
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{
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env: { LITELLM_API_KEY: "sk-..." },
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agents: {
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defaults: {
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model: { primary: "litellm/gpt-4" },
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models: { "litellm/gpt-4": { alias: "GPT-4" } }
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}
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},
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models: {
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mode: "merge",
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providers: {
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litellm: {
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baseUrl: "http://localhost:4000",
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apiKey: "${LITELLM_API_KEY}",
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api: "openai-completions",
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models: [
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{
|
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id: "gpt-4",
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name: "GPT-4",
|
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reasoning: false,
|
||||
input: ["text"],
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||||
contextWindow: 128000,
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maxTokens: 8192
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
}
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||||
}
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```
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## Multiple models
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||||
|
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Add additional models to your config as needed:
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||||
|
||||
```json5
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{
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models: {
|
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providers: {
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litellm: {
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baseUrl: "http://localhost:4000",
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apiKey: "${LITELLM_API_KEY}",
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api: "openai-completions",
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models: [
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{ id: "gpt-4", name: "GPT-4", contextWindow: 128000, maxTokens: 8192 },
|
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{ id: "claude-3-opus", name: "Claude Opus", contextWindow: 200000, maxTokens: 4096 },
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{ id: "gemini-pro", name: "Gemini Pro", contextWindow: 32000, maxTokens: 8192 }
|
||||
]
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
```
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||||
|
||||
Then switch models using:
|
||||
|
||||
```bash
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||||
openclaw config set agents.defaults.model.primary litellm/claude-3-opus
|
||||
```
|
||||
|
||||
## Prompt caching
|
||||
|
||||
When using Anthropic models through LiteLLM (e.g., `claude-opus-4-5`, `claude-sonnet-4-5`), OpenClaw automatically enables **prompt caching** to reduce costs:
|
||||
|
||||
```json5
|
||||
{
|
||||
agents: {
|
||||
defaults: {
|
||||
models: {
|
||||
"litellm/claude-opus-4-5": {
|
||||
params: {
|
||||
cacheControlTtl: "1h" // Auto-configured for Claude models
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Cost savings with caching
|
||||
|
||||
- **Without caching**: Every message pays full price for the entire conversation history
|
||||
- **With caching** (enabled by default): Repeated context costs 10x less
|
||||
|
||||
Example from actual usage:
|
||||
- Without caching: 93k tokens × $0.000005 = **$0.47** per message
|
||||
- With caching: 123k tokens (mostly cached) = **$0.05** per message (90% savings!)
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||||
|
||||
Caching is **automatically enabled** for all `claude-*` models through LiteLLM.
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||||
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||||
## Notes
|
||||
|
||||
- Model refs use `litellm/<modelId>` where `modelId` matches your LiteLLM config.
|
||||
- The base URL should not include `/v1` - OpenClaw's OpenAI client appends it.
|
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- Supported LiteLLM models depend on your proxy configuration.
|
||||
- **Prompt caching works automatically** when using Claude models through LiteLLM.
|
||||
- See [Model providers](/concepts/model-providers) for provider rules.
|
||||
50
src/agents/litellm-models.ts
Normal file
50
src/agents/litellm-models.ts
Normal file
@ -0,0 +1,50 @@
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import type { ModelDefinitionConfig } from "../config/types.js";
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||||
|
||||
// LiteLLM is a proxy that supports many models, so the base URL and model
|
||||
// are user-configurable. We provide sensible defaults for onboarding.
|
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export const LITELLM_DEFAULT_BASE_URL = "http://localhost:4000";
|
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export const LITELLM_DEFAULT_MODEL_ID = "gpt-4";
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export const LITELLM_DEFAULT_MODEL_REF = `litellm/${LITELLM_DEFAULT_MODEL_ID}`;
|
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export const LITELLM_DEFAULT_COST = {
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input: 0,
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output: 0,
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cacheRead: 0,
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cacheWrite: 0,
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||||
};
|
||||
|
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export type LitellmModelEntry = {
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id: string;
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name: string;
|
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reasoning?: boolean;
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||||
input?: readonly ("text" | "image")[];
|
||||
contextWindow?: number;
|
||||
maxTokens?: number;
|
||||
};
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|
||||
export function buildLitellmModelDefinition(entry: LitellmModelEntry): ModelDefinitionConfig {
|
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// Detect Claude models and use Anthropic Messages API for proper cache control support
|
||||
const isClaude = entry.id.toLowerCase().startsWith("claude-");
|
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|
||||
return {
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||||
id: entry.id,
|
||||
name: entry.name,
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||||
// Claude models through LiteLLM should use anthropic-messages API for cache control
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||||
...(isClaude ? { api: "anthropic-messages" as const } : {}),
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reasoning: entry.reasoning ?? false,
|
||||
input: entry.input ? [...entry.input] : ["text"],
|
||||
cost: LITELLM_DEFAULT_COST,
|
||||
contextWindow: entry.contextWindow ?? 128000,
|
||||
maxTokens: entry.maxTokens ?? 8192,
|
||||
// LiteLLM proxies to various providers that may not support the OpenAI Responses API
|
||||
// `store` parameter. Disable it by default to avoid "Extra inputs are not permitted" errors.
|
||||
compat: { supportsStore: false },
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Creates a model reference for a LiteLLM model.
|
||||
* The model ID can be any model supported by the LiteLLM proxy.
|
||||
*/
|
||||
export function litellmModelRef(modelId: string): string {
|
||||
return `litellm/${modelId}`;
|
||||
}
|
||||
@ -286,6 +286,7 @@ export function resolveEnvApiKey(provider: string): EnvApiKeyResult | null {
|
||||
venice: "VENICE_API_KEY",
|
||||
mistral: "MISTRAL_API_KEY",
|
||||
opencode: "OPENCODE_API_KEY",
|
||||
litellm: "LITELLM_API_KEY",
|
||||
};
|
||||
const envVar = envMap[normalized];
|
||||
if (!envVar) return null;
|
||||
|
||||
31
src/agents/pi-embedded-runner/cache-ttl.test.ts
Normal file
31
src/agents/pi-embedded-runner/cache-ttl.test.ts
Normal file
@ -0,0 +1,31 @@
|
||||
import { describe, it, expect } from "vitest";
|
||||
import { isCacheTtlEligibleProvider } from "./cache-ttl.js";
|
||||
|
||||
describe("isCacheTtlEligibleProvider", () => {
|
||||
it("returns true for direct Anthropic provider", () => {
|
||||
expect(isCacheTtlEligibleProvider("anthropic", "claude-opus-4-5")).toBe(true);
|
||||
expect(isCacheTtlEligibleProvider("Anthropic", "claude-sonnet-4-5")).toBe(true);
|
||||
});
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||||
|
||||
it("returns true for OpenRouter with Anthropic models", () => {
|
||||
expect(isCacheTtlEligibleProvider("openrouter", "anthropic/claude-opus-4-5")).toBe(true);
|
||||
expect(isCacheTtlEligibleProvider("OpenRouter", "anthropic/claude-3-opus")).toBe(true);
|
||||
});
|
||||
|
||||
it("returns true for LiteLLM with Claude models", () => {
|
||||
expect(isCacheTtlEligibleProvider("litellm", "claude-opus-4-5")).toBe(true);
|
||||
expect(isCacheTtlEligibleProvider("litellm", "claude-sonnet-4-5")).toBe(true);
|
||||
expect(isCacheTtlEligibleProvider("LiteLLM", "Claude-3-Opus")).toBe(true);
|
||||
});
|
||||
|
||||
it("returns false for LiteLLM with non-Claude models", () => {
|
||||
expect(isCacheTtlEligibleProvider("litellm", "gpt-4")).toBe(false);
|
||||
expect(isCacheTtlEligibleProvider("litellm", "gemini-pro")).toBe(false);
|
||||
expect(isCacheTtlEligibleProvider("litellm", "llama-3")).toBe(false);
|
||||
});
|
||||
|
||||
it("returns false for other providers", () => {
|
||||
expect(isCacheTtlEligibleProvider("openai", "gpt-4")).toBe(false);
|
||||
expect(isCacheTtlEligibleProvider("google", "gemini-pro")).toBe(false);
|
||||
});
|
||||
});
|
||||
@ -14,6 +14,8 @@ export function isCacheTtlEligibleProvider(provider: string, modelId: string): b
|
||||
if (normalizedProvider === "anthropic") return true;
|
||||
if (normalizedProvider === "openrouter" && normalizedModelId.startsWith("anthropic/"))
|
||||
return true;
|
||||
// LiteLLM proxying to Anthropic models (claude-*)
|
||||
if (normalizedProvider === "litellm" && normalizedModelId.startsWith("claude-")) return true;
|
||||
return false;
|
||||
}
|
||||
|
||||
|
||||
@ -32,6 +32,8 @@ function resolveCacheControlTtl(
|
||||
if (raw !== "5m" && raw !== "1h") return undefined;
|
||||
if (provider === "anthropic") return raw;
|
||||
if (provider === "openrouter" && modelId.startsWith("anthropic/")) return raw;
|
||||
// LiteLLM proxying to Anthropic models (claude-*)
|
||||
if (provider === "litellm" && modelId.startsWith("claude-")) return raw;
|
||||
return undefined;
|
||||
}
|
||||
|
||||
|
||||
@ -77,17 +77,25 @@ export function resolveModel(
|
||||
}
|
||||
const providerCfg = providers[provider];
|
||||
if (providerCfg || modelId.startsWith("mock-")) {
|
||||
// Find the matching model definition from provider config to get compat settings
|
||||
const modelDef = providerCfg?.models?.find((m) => m.id === modelId);
|
||||
const fallbackModel: Model<Api> = normalizeModelCompat({
|
||||
id: modelId,
|
||||
name: modelId,
|
||||
api: providerCfg?.api ?? "openai-responses",
|
||||
name: modelDef?.name ?? modelId,
|
||||
api: modelDef?.api ?? providerCfg?.api ?? "openai-responses",
|
||||
provider,
|
||||
baseUrl: providerCfg?.baseUrl,
|
||||
reasoning: false,
|
||||
input: ["text"],
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
|
||||
contextWindow: providerCfg?.models?.[0]?.contextWindow ?? DEFAULT_CONTEXT_TOKENS,
|
||||
maxTokens: providerCfg?.models?.[0]?.maxTokens ?? DEFAULT_CONTEXT_TOKENS,
|
||||
reasoning: modelDef?.reasoning ?? false,
|
||||
input: modelDef?.input ?? ["text"],
|
||||
cost: modelDef?.cost ?? { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
|
||||
contextWindow:
|
||||
modelDef?.contextWindow ??
|
||||
providerCfg?.models?.[0]?.contextWindow ??
|
||||
DEFAULT_CONTEXT_TOKENS,
|
||||
maxTokens:
|
||||
modelDef?.maxTokens ?? providerCfg?.models?.[0]?.maxTokens ?? DEFAULT_CONTEXT_TOKENS,
|
||||
// Preserve compat settings for provider-specific quirks (e.g., supportsStore for LiteLLM)
|
||||
compat: modelDef?.compat,
|
||||
} as Model<Api>);
|
||||
return { model: fallbackModel, authStorage, modelRegistry };
|
||||
}
|
||||
|
||||
@ -52,7 +52,7 @@ export function registerOnboardCommand(program: Command) {
|
||||
.option("--mode <mode>", "Wizard mode: local|remote")
|
||||
.option(
|
||||
"--auth-choice <choice>",
|
||||
"Auth: setup-token|token|chutes|openai-codex|openai-api-key|openrouter-api-key|ai-gateway-api-key|moonshot-api-key|kimi-code-api-key|synthetic-api-key|venice-api-key|gemini-api-key|zai-api-key|xiaomi-api-key|apiKey|minimax-api|minimax-api-lightning|opencode-zen|skip",
|
||||
"Auth: setup-token|token|chutes|openai-codex|openai-api-key|openrouter-api-key|ai-gateway-api-key|moonshot-api-key|kimi-code-api-key|synthetic-api-key|venice-api-key|litellm-api-key|gemini-api-key|zai-api-key|xiaomi-api-key|apiKey|minimax-api|minimax-api-lightning|opencode-zen|skip",
|
||||
)
|
||||
.option(
|
||||
"--token-provider <id>",
|
||||
@ -77,6 +77,9 @@ export function registerOnboardCommand(program: Command) {
|
||||
.option("--synthetic-api-key <key>", "Synthetic API key")
|
||||
.option("--venice-api-key <key>", "Venice API key")
|
||||
.option("--opencode-zen-api-key <key>", "OpenCode Zen API key")
|
||||
.option("--litellm-api-key <key>", "LiteLLM API key")
|
||||
.option("--litellm-base-url <url>", "LiteLLM base URL (default: http://localhost:4000)")
|
||||
.option("--litellm-model <model>", "LiteLLM model name")
|
||||
.option("--gateway-port <port>", "Gateway port")
|
||||
.option("--gateway-bind <mode>", "Gateway bind: loopback|tailnet|lan|auto|custom")
|
||||
.option("--gateway-auth <mode>", "Gateway auth: token|password")
|
||||
|
||||
@ -254,27 +254,41 @@ export async function agentsAddCommand(
|
||||
const authStore = ensureAuthProfileStore(agentDir, {
|
||||
allowKeychainPrompt: false,
|
||||
});
|
||||
const authChoice = await promptAuthChoiceGrouped({
|
||||
prompter,
|
||||
store: authStore,
|
||||
includeSkip: true,
|
||||
});
|
||||
|
||||
const authResult = await applyAuthChoice({
|
||||
authChoice,
|
||||
config: nextConfig,
|
||||
prompter,
|
||||
runtime,
|
||||
agentDir,
|
||||
setDefaultModel: false,
|
||||
agentId,
|
||||
});
|
||||
nextConfig = authResult.config;
|
||||
if (authResult.agentModelOverride) {
|
||||
nextConfig = applyAgentConfig(nextConfig, {
|
||||
agentId,
|
||||
model: authResult.agentModelOverride,
|
||||
// Loop to allow retrying auth choice if user cancels during configuration
|
||||
while (true) {
|
||||
const authChoice = await promptAuthChoiceGrouped({
|
||||
prompter,
|
||||
store: authStore,
|
||||
includeSkip: true,
|
||||
});
|
||||
|
||||
try {
|
||||
const authResult = await applyAuthChoice({
|
||||
authChoice,
|
||||
config: nextConfig,
|
||||
prompter,
|
||||
runtime,
|
||||
agentDir,
|
||||
setDefaultModel: false,
|
||||
agentId,
|
||||
});
|
||||
nextConfig = authResult.config;
|
||||
if (authResult.agentModelOverride) {
|
||||
nextConfig = applyAgentConfig(nextConfig, {
|
||||
agentId,
|
||||
model: authResult.agentModelOverride,
|
||||
});
|
||||
}
|
||||
break; // Success - exit the loop
|
||||
} catch (error) {
|
||||
// If user cancelled to go back to auth selection, loop again
|
||||
if (error instanceof Error && error.message === "AUTH_CHOICE_CANCELLED") {
|
||||
continue;
|
||||
}
|
||||
// Re-throw other errors
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@ -21,7 +21,8 @@ export type AuthChoiceGroupId =
|
||||
| "minimax"
|
||||
| "synthetic"
|
||||
| "venice"
|
||||
| "qwen";
|
||||
| "qwen"
|
||||
| "litellm";
|
||||
|
||||
export type AuthChoiceGroup = {
|
||||
value: AuthChoiceGroupId;
|
||||
@ -120,6 +121,12 @@ const AUTH_CHOICE_GROUP_DEFS: {
|
||||
hint: "API key",
|
||||
choices: ["opencode-zen"],
|
||||
},
|
||||
{
|
||||
value: "litellm",
|
||||
label: "LiteLLM",
|
||||
hint: "OpenAI-compatible proxy (self-hosted)",
|
||||
choices: ["litellm-api-key"],
|
||||
},
|
||||
];
|
||||
|
||||
export function buildAuthChoiceOptions(params: {
|
||||
@ -194,6 +201,11 @@ export function buildAuthChoiceOptions(params: {
|
||||
label: "MiniMax M2.1 Lightning",
|
||||
hint: "Faster, higher output cost",
|
||||
});
|
||||
options.push({
|
||||
value: "litellm-api-key",
|
||||
label: "LiteLLM API key",
|
||||
hint: "OpenAI-compatible proxy (any model)",
|
||||
});
|
||||
if (params.includeSkip) {
|
||||
options.push({ value: "skip", label: "Skip for now" });
|
||||
}
|
||||
|
||||
@ -15,6 +15,8 @@ import {
|
||||
applyAuthProfileConfig,
|
||||
applyKimiCodeConfig,
|
||||
applyKimiCodeProviderConfig,
|
||||
applyLitellmConfig,
|
||||
applyLitellmProviderConfig,
|
||||
applyMoonshotConfig,
|
||||
applyMoonshotProviderConfig,
|
||||
applyOpencodeZenConfig,
|
||||
@ -39,6 +41,7 @@ import {
|
||||
XIAOMI_DEFAULT_MODEL_REF,
|
||||
setGeminiApiKey,
|
||||
setKimiCodeApiKey,
|
||||
setLitellmApiKey,
|
||||
setMoonshotApiKey,
|
||||
setOpencodeZenApiKey,
|
||||
setOpenrouterApiKey,
|
||||
@ -91,6 +94,8 @@ export async function applyAuthChoiceApiProviders(
|
||||
authChoice = "venice-api-key";
|
||||
} else if (params.opts.tokenProvider === "opencode") {
|
||||
authChoice = "opencode-zen";
|
||||
} else if (params.opts.tokenProvider === "litellm") {
|
||||
authChoice = "litellm-api-key";
|
||||
}
|
||||
}
|
||||
|
||||
@ -633,5 +638,296 @@ export async function applyAuthChoiceApiProviders(
|
||||
return { config: nextConfig, agentModelOverride };
|
||||
}
|
||||
|
||||
if (authChoice === "litellm-api-key") {
|
||||
let hasCredential = false;
|
||||
let apiKey: string | undefined;
|
||||
|
||||
// Check for pre-provided API key via CLI options (--litellm-api-key or --token with --token-provider litellm)
|
||||
if (!hasCredential && params.opts?.litellmApiKey) {
|
||||
apiKey = normalizeApiKeyInput(params.opts.litellmApiKey);
|
||||
await setLitellmApiKey(apiKey, params.agentDir);
|
||||
hasCredential = true;
|
||||
}
|
||||
if (!hasCredential && params.opts?.token && params.opts?.tokenProvider === "litellm") {
|
||||
apiKey = normalizeApiKeyInput(params.opts.token);
|
||||
await setLitellmApiKey(apiKey, params.agentDir);
|
||||
hasCredential = true;
|
||||
}
|
||||
|
||||
if (!hasCredential) {
|
||||
await params.prompter.note(
|
||||
[
|
||||
"LiteLLM is an OpenAI-compatible proxy that supports many models.",
|
||||
"You'll need to provide:",
|
||||
" 1. Base URL (e.g., http://localhost:4000)",
|
||||
" 2. API key",
|
||||
" 3. Model selection (fetched from your LiteLLM instance)",
|
||||
].join("\n"),
|
||||
"LiteLLM",
|
||||
);
|
||||
}
|
||||
|
||||
// Check for existing env key
|
||||
const envKey = resolveEnvApiKey("litellm");
|
||||
if (!hasCredential && envKey) {
|
||||
const useExisting = await params.prompter.confirm({
|
||||
message: `Use existing LITELLM_API_KEY (${envKey.source}, ${formatApiKeyPreview(envKey.apiKey)})?`,
|
||||
initialValue: true,
|
||||
});
|
||||
if (useExisting) {
|
||||
apiKey = envKey.apiKey;
|
||||
await setLitellmApiKey(apiKey, params.agentDir);
|
||||
hasCredential = true;
|
||||
}
|
||||
}
|
||||
|
||||
// Helper function to prompt for API key
|
||||
const promptForApiKey = async () => {
|
||||
const key = await params.prompter.text({
|
||||
message: "Enter LiteLLM API key",
|
||||
validate: validateApiKeyInput,
|
||||
});
|
||||
return normalizeApiKeyInput(String(key));
|
||||
};
|
||||
|
||||
// Helper function to prompt for base URL
|
||||
const promptForBaseUrl = async () => {
|
||||
const defaultBaseUrl = process.env.LITELLM_BASE_URL ?? "http://localhost:4000";
|
||||
const baseUrl = await params.prompter.text({
|
||||
message: "Enter LiteLLM base URL",
|
||||
initialValue: defaultBaseUrl,
|
||||
placeholder: defaultBaseUrl,
|
||||
validate: (value) => {
|
||||
if (!value?.trim()) return "Base URL is required";
|
||||
try {
|
||||
new URL(value);
|
||||
return undefined;
|
||||
} catch {
|
||||
return "Invalid URL format";
|
||||
}
|
||||
},
|
||||
});
|
||||
return String(baseUrl).trim();
|
||||
};
|
||||
|
||||
if (!hasCredential) {
|
||||
apiKey = await promptForApiKey();
|
||||
await setLitellmApiKey(apiKey, params.agentDir);
|
||||
}
|
||||
|
||||
// Check for pre-provided base URL via CLI option (--litellm-base-url)
|
||||
let normalizedBaseUrl: string;
|
||||
if (params.opts?.litellmBaseUrl) {
|
||||
normalizedBaseUrl = params.opts.litellmBaseUrl.trim();
|
||||
} else {
|
||||
normalizedBaseUrl = await promptForBaseUrl();
|
||||
}
|
||||
|
||||
// Try to fetch available models from LiteLLM
|
||||
type LitellmModelInfo = { id: string; maxInputTokens?: number; maxOutputTokens?: number };
|
||||
let availableModels: LitellmModelInfo[] = [];
|
||||
const authHeaders: Record<string, string> = apiKey ? { Authorization: `Bearer ${apiKey}` } : {};
|
||||
|
||||
// First fetch model list from /v1/models
|
||||
try {
|
||||
const modelsUrl = new URL("/v1/models", normalizedBaseUrl).toString();
|
||||
const response = await fetch(modelsUrl, {
|
||||
headers: authHeaders,
|
||||
signal: AbortSignal.timeout(10000),
|
||||
});
|
||||
if (response.ok) {
|
||||
const data = (await response.json()) as {
|
||||
data?: Array<{ id: string }>;
|
||||
};
|
||||
if (data.data && Array.isArray(data.data)) {
|
||||
availableModels = data.data.map((m) => ({ id: m.id }));
|
||||
}
|
||||
}
|
||||
} catch {
|
||||
// Fetching models failed - will fall back to manual entry
|
||||
}
|
||||
|
||||
// Then fetch detailed model info from /model/info (LiteLLM-specific endpoint)
|
||||
// This provides context window and max tokens info
|
||||
type ModelInfoEntry = {
|
||||
model_name: string;
|
||||
model_info?: {
|
||||
max_input_tokens?: number;
|
||||
max_tokens?: number;
|
||||
max_output_tokens?: number;
|
||||
};
|
||||
};
|
||||
const modelInfoMap = new Map<string, { maxInputTokens?: number; maxOutputTokens?: number }>();
|
||||
try {
|
||||
const modelInfoUrl = new URL("/model/info", normalizedBaseUrl).toString();
|
||||
const response = await fetch(modelInfoUrl, {
|
||||
headers: authHeaders,
|
||||
signal: AbortSignal.timeout(10000),
|
||||
});
|
||||
if (response.ok) {
|
||||
const data = (await response.json()) as { data?: ModelInfoEntry[] };
|
||||
if (data.data && Array.isArray(data.data)) {
|
||||
for (const entry of data.data) {
|
||||
if (entry.model_name && entry.model_info) {
|
||||
modelInfoMap.set(entry.model_name, {
|
||||
maxInputTokens: entry.model_info.max_input_tokens,
|
||||
maxOutputTokens: entry.model_info.max_output_tokens ?? entry.model_info.max_tokens,
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
} catch {
|
||||
// Model info fetch failed - context window will need manual entry
|
||||
}
|
||||
|
||||
// Merge model info into available models
|
||||
availableModels = availableModels.map((m) => {
|
||||
const info = modelInfoMap.get(m.id);
|
||||
return {
|
||||
id: m.id,
|
||||
maxInputTokens: info?.maxInputTokens,
|
||||
maxOutputTokens: info?.maxOutputTokens,
|
||||
};
|
||||
});
|
||||
|
||||
let normalizedModelId: string;
|
||||
let contextWindow: number | undefined;
|
||||
let maxTokens: number | undefined;
|
||||
|
||||
// Check for pre-provided model via CLI option (--litellm-model)
|
||||
if (params.opts?.litellmModel) {
|
||||
normalizedModelId = params.opts.litellmModel.trim();
|
||||
// Try to get context info from model info map
|
||||
const modelInfo = availableModels.find((m) => m.id === normalizedModelId);
|
||||
if (modelInfo?.maxInputTokens) {
|
||||
contextWindow = modelInfo.maxInputTokens;
|
||||
}
|
||||
if (modelInfo?.maxOutputTokens) {
|
||||
maxTokens = modelInfo.maxOutputTokens;
|
||||
}
|
||||
} else if (availableModels.length > 0) {
|
||||
// Let user select from available models
|
||||
type SelectOption = { value: string; label: string; hint?: string };
|
||||
const modelOptions: SelectOption[] = availableModels.map((m) => ({
|
||||
value: m.id,
|
||||
label: m.id,
|
||||
hint: m.maxInputTokens ? `${Math.round(m.maxInputTokens / 1000)}k context` : undefined,
|
||||
}));
|
||||
|
||||
const selectedModel = await params.prompter.select({
|
||||
message: `Select model (${availableModels.length} available)`,
|
||||
options: modelOptions,
|
||||
});
|
||||
|
||||
normalizedModelId = String(selectedModel);
|
||||
const modelInfo = availableModels.find((m) => m.id === normalizedModelId);
|
||||
if (modelInfo?.maxInputTokens) {
|
||||
contextWindow = modelInfo.maxInputTokens;
|
||||
}
|
||||
if (modelInfo?.maxOutputTokens) {
|
||||
maxTokens = modelInfo.maxOutputTokens;
|
||||
}
|
||||
} else {
|
||||
// No models available from LiteLLM - offer manual entry or retry
|
||||
await params.prompter.note(
|
||||
[
|
||||
"Could not fetch models from LiteLLM server.",
|
||||
`Server: ${normalizedBaseUrl}`,
|
||||
"",
|
||||
"This could be due to:",
|
||||
" • Invalid API key",
|
||||
" • Server not accessible",
|
||||
" • Network connectivity issues",
|
||||
].join("\n"),
|
||||
"Model fetch failed",
|
||||
);
|
||||
|
||||
const action = await params.prompter.select({
|
||||
message: "How would you like to proceed?",
|
||||
options: [
|
||||
{ value: "retry-apikey", label: "Re-enter API key" },
|
||||
{ value: "retry-baseurl", label: "Re-enter base URL" },
|
||||
{ value: "cancel", label: "Go back to auth method selection" },
|
||||
],
|
||||
});
|
||||
|
||||
if (action === "cancel") {
|
||||
// Throw an error with a specific message that signals to restart auth selection
|
||||
// The caller should catch this and re-prompt for auth choice
|
||||
throw new Error("AUTH_CHOICE_CANCELLED");
|
||||
}
|
||||
|
||||
if (action === "retry-apikey") {
|
||||
// Re-prompt for API key and retry the entire flow
|
||||
// Clear the CLI-provided options to force prompting
|
||||
const newParams = {
|
||||
...params,
|
||||
authChoice: "litellm-api-key" as const,
|
||||
opts: {
|
||||
...params.opts,
|
||||
litellmApiKey: undefined, // Clear the CLI-provided API key so we can prompt
|
||||
token: undefined, // Also clear token if it was used
|
||||
},
|
||||
};
|
||||
return await applyAuthChoiceApiProviders(newParams);
|
||||
}
|
||||
|
||||
if (action === "retry-baseurl") {
|
||||
// Re-prompt for base URL and retry the entire flow
|
||||
// This ensures we go through the full fetch process again with the new URL
|
||||
const newParams = {
|
||||
...params,
|
||||
authChoice: "litellm-api-key" as const,
|
||||
opts: {
|
||||
...params.opts,
|
||||
litellmBaseUrl: undefined, // Clear the CLI-provided URL so we can prompt
|
||||
},
|
||||
};
|
||||
return await applyAuthChoiceApiProviders(newParams);
|
||||
}
|
||||
|
||||
// This should never be reached, but throw error as fallback
|
||||
throw new Error("Failed to configure LiteLLM provider");
|
||||
}
|
||||
|
||||
// Strip litellm/ prefix if the API returned it (avoid litellm/litellm/model)
|
||||
if (normalizedModelId.startsWith("litellm/")) {
|
||||
normalizedModelId = normalizedModelId.slice("litellm/".length);
|
||||
}
|
||||
|
||||
const modelRef = `litellm/${normalizedModelId}`;
|
||||
|
||||
nextConfig = applyAuthProfileConfig(nextConfig, {
|
||||
profileId: "litellm:default",
|
||||
provider: "litellm",
|
||||
mode: "api_key",
|
||||
});
|
||||
|
||||
if (params.setDefaultModel) {
|
||||
nextConfig = applyLitellmConfig(nextConfig, {
|
||||
baseUrl: normalizedBaseUrl,
|
||||
modelId: normalizedModelId,
|
||||
contextWindow,
|
||||
maxTokens,
|
||||
});
|
||||
await params.prompter.note(
|
||||
`Default model set to ${modelRef}${contextWindow ? ` (${Math.round(contextWindow / 1000)}k context)` : ""}`,
|
||||
"Model configured",
|
||||
);
|
||||
} else {
|
||||
nextConfig = applyLitellmProviderConfig(nextConfig, {
|
||||
baseUrl: normalizedBaseUrl,
|
||||
modelId: normalizedModelId,
|
||||
contextWindow,
|
||||
maxTokens,
|
||||
});
|
||||
agentModelOverride = modelRef;
|
||||
await noteAgentModel(modelRef);
|
||||
}
|
||||
|
||||
return { config: nextConfig, agentModelOverride };
|
||||
}
|
||||
|
||||
return null;
|
||||
}
|
||||
|
||||
@ -24,6 +24,12 @@ export type ApplyAuthChoiceParams = {
|
||||
opts?: {
|
||||
tokenProvider?: string;
|
||||
token?: string;
|
||||
// LiteLLM-specific options
|
||||
litellmApiKey?: string;
|
||||
litellmBaseUrl?: string;
|
||||
litellmModel?: string;
|
||||
// Non-interactive mode flag
|
||||
nonInteractive?: boolean;
|
||||
};
|
||||
};
|
||||
|
||||
|
||||
@ -4,6 +4,7 @@ import type { RuntimeEnv } from "../runtime.js";
|
||||
import type { WizardPrompter } from "../wizard/prompts.js";
|
||||
import { applyAuthChoice, resolvePreferredProviderForAuthChoice } from "./auth-choice.js";
|
||||
import { promptAuthChoiceGrouped } from "./auth-choice-prompt.js";
|
||||
import type { AuthChoice } from "./onboard-types.js";
|
||||
import {
|
||||
applyModelAllowlist,
|
||||
applyModelFallbacksFromSelection,
|
||||
@ -41,34 +42,50 @@ export async function promptAuthConfig(
|
||||
runtime: RuntimeEnv,
|
||||
prompter: WizardPrompter,
|
||||
): Promise<OpenClawConfig> {
|
||||
const authChoice = await promptAuthChoiceGrouped({
|
||||
prompter,
|
||||
store: ensureAuthProfileStore(undefined, {
|
||||
allowKeychainPrompt: false,
|
||||
}),
|
||||
includeSkip: true,
|
||||
});
|
||||
|
||||
let next = cfg;
|
||||
if (authChoice !== "skip") {
|
||||
const applied = await applyAuthChoice({
|
||||
authChoice,
|
||||
config: next,
|
||||
let authChoice: AuthChoice;
|
||||
|
||||
// Loop to allow retrying auth choice if user cancels during configuration
|
||||
while (true) {
|
||||
authChoice = await promptAuthChoiceGrouped({
|
||||
prompter,
|
||||
runtime,
|
||||
setDefaultModel: true,
|
||||
store: ensureAuthProfileStore(undefined, {
|
||||
allowKeychainPrompt: false,
|
||||
}),
|
||||
includeSkip: true,
|
||||
});
|
||||
next = applied.config;
|
||||
} else {
|
||||
const modelSelection = await promptDefaultModel({
|
||||
config: next,
|
||||
prompter,
|
||||
allowKeep: true,
|
||||
ignoreAllowlist: true,
|
||||
preferredProvider: resolvePreferredProviderForAuthChoice(authChoice),
|
||||
});
|
||||
if (modelSelection.model) {
|
||||
next = applyPrimaryModel(next, modelSelection.model);
|
||||
|
||||
if (authChoice !== "skip") {
|
||||
try {
|
||||
const applied = await applyAuthChoice({
|
||||
authChoice,
|
||||
config: next,
|
||||
prompter,
|
||||
runtime,
|
||||
setDefaultModel: true,
|
||||
});
|
||||
next = applied.config;
|
||||
break; // Success - exit the loop
|
||||
} catch (error) {
|
||||
// If user cancelled to go back to auth selection, loop again
|
||||
if (error instanceof Error && error.message === "AUTH_CHOICE_CANCELLED") {
|
||||
continue;
|
||||
}
|
||||
// Re-throw other errors
|
||||
throw error;
|
||||
}
|
||||
} else {
|
||||
const modelSelection = await promptDefaultModel({
|
||||
config: next,
|
||||
prompter,
|
||||
allowKeep: true,
|
||||
ignoreAllowlist: true,
|
||||
preferredProvider: resolvePreferredProviderForAuthChoice(authChoice),
|
||||
});
|
||||
if (modelSelection.model) {
|
||||
next = applyPrimaryModel(next, modelSelection.model);
|
||||
}
|
||||
break; // Skip selected - exit the loop
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@ -484,6 +484,115 @@ export function applyVeniceConfig(cfg: OpenClawConfig): OpenClawConfig {
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Apply LiteLLM provider configuration without changing the default model.
|
||||
* LiteLLM is a flexible proxy that supports many models, so base URL and model
|
||||
* are user-configurable.
|
||||
*/
|
||||
export function applyLitellmProviderConfig(
|
||||
cfg: OpenClawConfig,
|
||||
params: {
|
||||
baseUrl: string;
|
||||
modelId: string;
|
||||
modelName?: string;
|
||||
contextWindow?: number;
|
||||
maxTokens?: number;
|
||||
},
|
||||
): OpenClawConfig {
|
||||
const modelRef = `litellm/${params.modelId}`;
|
||||
const models = { ...cfg.agents?.defaults?.models };
|
||||
models[modelRef] = {
|
||||
...models[modelRef],
|
||||
alias: models[modelRef]?.alias ?? params.modelName ?? params.modelId,
|
||||
};
|
||||
|
||||
const providers = { ...cfg.models?.providers };
|
||||
const existingProvider = providers.litellm;
|
||||
const existingModels = Array.isArray(existingProvider?.models) ? existingProvider.models : [];
|
||||
// Detect Claude models and use Anthropic Messages API for proper cache control support
|
||||
const isClaude = params.modelId.toLowerCase().startsWith("claude-");
|
||||
const newModel = {
|
||||
id: params.modelId,
|
||||
name: params.modelName ?? params.modelId,
|
||||
// Claude models through LiteLLM should use anthropic-messages API for cache control
|
||||
...(isClaude ? { api: "anthropic-messages" as const } : {}),
|
||||
reasoning: false,
|
||||
input: ["text"] as ("text" | "image")[],
|
||||
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
|
||||
contextWindow: params.contextWindow ?? 128000,
|
||||
maxTokens: params.maxTokens ?? 8192,
|
||||
// LiteLLM proxies to various providers that may not support the OpenAI Responses API
|
||||
// `store` parameter. Disable it to avoid "Extra inputs are not permitted" errors.
|
||||
compat: { supportsStore: false },
|
||||
};
|
||||
const hasModel = existingModels.some((model) => model.id === params.modelId);
|
||||
const mergedModels = hasModel ? existingModels : [...existingModels, newModel];
|
||||
const { apiKey: existingApiKey, ...existingProviderRest } = (existingProvider ?? {}) as Record<
|
||||
string,
|
||||
unknown
|
||||
> as { apiKey?: string };
|
||||
const resolvedApiKey = typeof existingApiKey === "string" ? existingApiKey : undefined;
|
||||
const normalizedApiKey = resolvedApiKey?.trim();
|
||||
providers.litellm = {
|
||||
...existingProviderRest,
|
||||
baseUrl: params.baseUrl,
|
||||
api: "openai-completions",
|
||||
...(normalizedApiKey ? { apiKey: normalizedApiKey } : {}),
|
||||
models: mergedModels.length > 0 ? mergedModels : [newModel],
|
||||
};
|
||||
|
||||
return {
|
||||
...cfg,
|
||||
agents: {
|
||||
...cfg.agents,
|
||||
defaults: {
|
||||
...cfg.agents?.defaults,
|
||||
models,
|
||||
},
|
||||
},
|
||||
models: {
|
||||
mode: cfg.models?.mode ?? "merge",
|
||||
providers,
|
||||
},
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Apply LiteLLM provider configuration AND set LiteLLM as the default model.
|
||||
* Use this when LiteLLM is the primary provider choice during onboarding.
|
||||
*/
|
||||
export function applyLitellmConfig(
|
||||
cfg: OpenClawConfig,
|
||||
params: {
|
||||
baseUrl: string;
|
||||
modelId: string;
|
||||
modelName?: string;
|
||||
contextWindow?: number;
|
||||
maxTokens?: number;
|
||||
},
|
||||
): OpenClawConfig {
|
||||
const next = applyLitellmProviderConfig(cfg, params);
|
||||
const modelRef = `litellm/${params.modelId}`;
|
||||
const existingModel = next.agents?.defaults?.model;
|
||||
return {
|
||||
...next,
|
||||
agents: {
|
||||
...next.agents,
|
||||
defaults: {
|
||||
...next.agents?.defaults,
|
||||
model: {
|
||||
...(existingModel && "fallbacks" in (existingModel as Record<string, unknown>)
|
||||
? {
|
||||
fallbacks: (existingModel as { fallbacks?: string[] }).fallbacks,
|
||||
}
|
||||
: undefined),
|
||||
primary: modelRef,
|
||||
},
|
||||
},
|
||||
},
|
||||
};
|
||||
}
|
||||
|
||||
export function applyAuthProfileConfig(
|
||||
cfg: OpenClawConfig,
|
||||
params: {
|
||||
|
||||
@ -177,3 +177,17 @@ export async function setOpencodeZenApiKey(key: string, agentDir?: string) {
|
||||
agentDir: resolveAuthAgentDir(agentDir),
|
||||
});
|
||||
}
|
||||
|
||||
export const LITELLM_DEFAULT_MODEL_REF = "litellm/gpt-4";
|
||||
|
||||
export async function setLitellmApiKey(key: string, agentDir?: string) {
|
||||
upsertAuthProfile({
|
||||
profileId: "litellm:default",
|
||||
credential: {
|
||||
type: "api_key",
|
||||
provider: "litellm",
|
||||
key,
|
||||
},
|
||||
agentDir: resolveAuthAgentDir(agentDir),
|
||||
});
|
||||
}
|
||||
|
||||
@ -7,6 +7,8 @@ export {
|
||||
applyAuthProfileConfig,
|
||||
applyKimiCodeConfig,
|
||||
applyKimiCodeProviderConfig,
|
||||
applyLitellmConfig,
|
||||
applyLitellmProviderConfig,
|
||||
applyMoonshotConfig,
|
||||
applyMoonshotProviderConfig,
|
||||
applyOpenrouterConfig,
|
||||
@ -35,10 +37,12 @@ export {
|
||||
applyOpencodeZenProviderConfig,
|
||||
} from "./onboard-auth.config-opencode.js";
|
||||
export {
|
||||
LITELLM_DEFAULT_MODEL_REF,
|
||||
OPENROUTER_DEFAULT_MODEL_REF,
|
||||
setAnthropicApiKey,
|
||||
setGeminiApiKey,
|
||||
setKimiCodeApiKey,
|
||||
setLitellmApiKey,
|
||||
setMinimaxApiKey,
|
||||
setMoonshotApiKey,
|
||||
setOpencodeZenApiKey,
|
||||
|
||||
@ -17,6 +17,7 @@ export type AuthChoice =
|
||||
| "kimi-code-api-key"
|
||||
| "synthetic-api-key"
|
||||
| "venice-api-key"
|
||||
| "litellm-api-key"
|
||||
| "codex-cli"
|
||||
| "apiKey"
|
||||
| "gemini-api-key"
|
||||
@ -73,6 +74,9 @@ export type OnboardOptions = {
|
||||
syntheticApiKey?: string;
|
||||
veniceApiKey?: string;
|
||||
opencodeZenApiKey?: string;
|
||||
litellmApiKey?: string;
|
||||
litellmBaseUrl?: string;
|
||||
litellmModel?: string;
|
||||
gatewayPort?: number;
|
||||
gatewayBind?: GatewayBind;
|
||||
gatewayAuth?: GatewayAuthChoice;
|
||||
|
||||
@ -323,7 +323,12 @@ export function applyContextPruningDefaults(cfg: OpenClawConfig): OpenClawConfig
|
||||
|
||||
for (const [key, entry] of Object.entries(nextModels)) {
|
||||
const parsed = parseModelRef(key, "anthropic");
|
||||
if (!parsed || parsed.provider !== "anthropic") continue;
|
||||
if (!parsed) continue;
|
||||
// Apply cache control to Anthropic models and LiteLLM Claude models
|
||||
const isAnthropicProvider = parsed.provider === "anthropic";
|
||||
const isLitellmClaude =
|
||||
parsed.provider === "litellm" && parsed.model.toLowerCase().startsWith("claude-");
|
||||
if (!isAnthropicProvider && !isLitellmClaude) continue;
|
||||
const current = entry ?? {};
|
||||
const params = (current as { params?: Record<string, unknown> }).params ?? {};
|
||||
if (typeof params.cacheControlTtl === "string") continue;
|
||||
@ -337,17 +342,24 @@ export function applyContextPruningDefaults(cfg: OpenClawConfig): OpenClawConfig
|
||||
const primary = resolvePrimaryModelRef(defaults.model?.primary ?? undefined);
|
||||
if (primary) {
|
||||
const parsedPrimary = parseModelRef(primary, "anthropic");
|
||||
if (parsedPrimary?.provider === "anthropic") {
|
||||
const key = `${parsedPrimary.provider}/${parsedPrimary.model}`;
|
||||
const entry = nextModels[key];
|
||||
const current = entry ?? {};
|
||||
const params = (current as { params?: Record<string, unknown> }).params ?? {};
|
||||
if (typeof params.cacheControlTtl !== "string") {
|
||||
nextModels[key] = {
|
||||
...(current as Record<string, unknown>),
|
||||
params: { ...params, cacheControlTtl: "1h" },
|
||||
};
|
||||
modelsMutated = true;
|
||||
if (parsedPrimary) {
|
||||
// Apply cache control to Anthropic models and LiteLLM Claude models
|
||||
const isAnthropicProvider = parsedPrimary.provider === "anthropic";
|
||||
const isLitellmClaude =
|
||||
parsedPrimary.provider === "litellm" &&
|
||||
parsedPrimary.model.toLowerCase().startsWith("claude-");
|
||||
if (isAnthropicProvider || isLitellmClaude) {
|
||||
const key = `${parsedPrimary.provider}/${parsedPrimary.model}`;
|
||||
const entry = nextModels[key];
|
||||
const current = entry ?? {};
|
||||
const params = (current as { params?: Record<string, unknown> }).params ?? {};
|
||||
if (typeof params.cacheControlTtl !== "string") {
|
||||
nextModels[key] = {
|
||||
...(current as Record<string, unknown>),
|
||||
params: { ...params, cacheControlTtl: "1h" },
|
||||
};
|
||||
modelsMutated = true;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@ -48,6 +48,7 @@ const SHELL_ENV_EXPECTED_KEYS = [
|
||||
"AI_GATEWAY_API_KEY",
|
||||
"MINIMAX_API_KEY",
|
||||
"SYNTHETIC_API_KEY",
|
||||
"LITELLM_API_KEY",
|
||||
"ELEVENLABS_API_KEY",
|
||||
"TELEGRAM_BOT_TOKEN",
|
||||
"DISCORD_BOT_TOKEN",
|
||||
|
||||
@ -21,6 +21,7 @@ import { promptRemoteGatewayConfig } from "../commands/onboard-remote.js";
|
||||
import { setupSkills } from "../commands/onboard-skills.js";
|
||||
import { setupInternalHooks } from "../commands/onboard-hooks.js";
|
||||
import type {
|
||||
AuthChoice,
|
||||
GatewayAuthChoice,
|
||||
OnboardMode,
|
||||
OnboardOptions,
|
||||
@ -354,26 +355,43 @@ export async function runOnboardingWizard(
|
||||
allowKeychainPrompt: false,
|
||||
});
|
||||
const authChoiceFromPrompt = opts.authChoice === undefined;
|
||||
const authChoice =
|
||||
opts.authChoice ??
|
||||
(await promptAuthChoiceGrouped({
|
||||
prompter,
|
||||
store: authStore,
|
||||
includeSkip: true,
|
||||
}));
|
||||
let authChoice: AuthChoice;
|
||||
|
||||
const authResult = await applyAuthChoice({
|
||||
authChoice,
|
||||
config: nextConfig,
|
||||
prompter,
|
||||
runtime,
|
||||
setDefaultModel: true,
|
||||
opts: {
|
||||
tokenProvider: opts.tokenProvider,
|
||||
token: opts.authChoice === "apiKey" && opts.token ? opts.token : undefined,
|
||||
},
|
||||
});
|
||||
nextConfig = authResult.config;
|
||||
// Loop to allow retrying auth choice if user cancels during configuration
|
||||
while (true) {
|
||||
authChoice =
|
||||
opts.authChoice ??
|
||||
(await promptAuthChoiceGrouped({
|
||||
prompter,
|
||||
store: authStore,
|
||||
includeSkip: true,
|
||||
}));
|
||||
|
||||
try {
|
||||
const authResult = await applyAuthChoice({
|
||||
authChoice,
|
||||
config: nextConfig,
|
||||
prompter,
|
||||
runtime,
|
||||
setDefaultModel: true,
|
||||
opts: {
|
||||
tokenProvider: opts.tokenProvider,
|
||||
token: opts.authChoice === "apiKey" && opts.token ? opts.token : undefined,
|
||||
},
|
||||
});
|
||||
nextConfig = authResult.config;
|
||||
break; // Success - exit the loop
|
||||
} catch (error) {
|
||||
// If user cancelled to go back to auth selection, loop again
|
||||
if (error instanceof Error && error.message === "AUTH_CHOICE_CANCELLED") {
|
||||
// Clear opts.authChoice so we prompt again
|
||||
opts.authChoice = undefined;
|
||||
continue;
|
||||
}
|
||||
// Re-throw other errors
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
if (authChoiceFromPrompt) {
|
||||
const modelSelection = await promptDefaultModel({
|
||||
|
||||
Loading…
Reference in New Issue
Block a user