openclaw/extensions/memory-lancedb
2026-01-28 17:10:49 -05:00
..
clawdbot.plugin.json fix: enforce plugin config schemas (#1272) (thanks @thewilloftheshadow) 2026-01-20 11:03:17 +00:00
config.ts feat(memory-lancedb): Venice embeddings support (text-embedding-bge-m3) 2026-01-28 16:56:52 -05:00
index.test.ts refactor: rename clawdbot to moltbot with legacy compat 2026-01-27 12:21:02 +00:00
index.ts feat(memory-lancedb): Venice embeddings support (text-embedding-bge-m3) 2026-01-28 16:56:52 -05:00
package.json chore: prep 2026.1.27-beta.1 release 2026-01-28 01:35:58 +01:00
README.md docs(memory-lancedb): add clean Venice embeddings guide 2026-01-28 17:10:49 -05:00

Memory (LanceDB) Extension

LanceDB-backed long-term memory with semantic search.

Venice Embeddings (New!)

Uncensored embeddings w/o OpenAI key:

{
  "extensions": {
    "memory-lancedb": {
      "embedding": {
        "provider": "venice",
        "model": "text-embedding-bge-m3",
        "apiKey": "VENICE-INFERENCE-KEY-...",
        "baseUrl": "https://api.venice.ai/api/v1"
      },
      "autoCapture": true,
      "autoRecall": true
    }
  }
}
  • Model: text-embedding-bge-m3 (1024 dims)
  • Compatible: OpenAI client proxy
  • Fallback: OpenAI text-embedding-3-small/large

Setup

  1. Add to Clawdbot config.
  2. clawdbot gateway restart
  3. Use memory_search "query" works!

Tools

  • memory_search: Semantic recall from MEMORY.md + memory/*.md
  • memory_get: Snippet read
  • Auto-capture/recall on conversations

Tested Venice API response.