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memory-lancedb-setup

Configure OpenClaw's memory-lancedb plugin for semantic vector memory using a local LanceDB database. Use when: (1) setting up vector memory for the first time, (2) memory-lancedb fails with module not found errors, (3) migrating from flat-file MEMORY.md to vector-based recall, (4) configuring an embedding provider (Gemini, OpenAI-compatible). NOT for: general memory_store/memory_recall usage (just use the tools directly).

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knownasnaffy/prompthound
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6 de julio de 2026 a las 07:03
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SKILL.md
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memory-lancedb-setup
description
Configure OpenClaw's memory-lancedb plugin for semantic vector memory using a local LanceDB database. Use when: (1) setting up vector memory for the first time, (2) memory-lancedb fails with module not found errors, (3) migrating from flat-file MEMORY.md to vector-based recall, (4) configuring an embedding provider (Gemini, OpenAI-compatible). NOT for: general memory_store/memory_recall usage (just use the tools directly).
# memory-lancedb Setup Enables semantic vector memory in OpenClaw: memories stored with `memory_store` are embedded and indexed locally, then recalled on-demand via `memory_recall` — no full-context load. ## Prerequisites - OpenClaw installed at `/usr/local/lib/node_modules/openclaw` - An OpenAI-compatible embedding API key (Gemini AI Studio free key works well) ## Setup Steps ### 1. Get a Gemini API Key (free) Go to [aistudio.google.com](https://aistudio.google.com) → Get API key → Create API key. ### 2. Configure the plugin ```bash openclaw config set plugins.entries.memory-lancedb.enabled true openclaw config set plugins.entries.memory-lancedb.config.embedding.baseUrl "https://generativelanguage.googleapis.com/v1beta/openai/" openclaw config set plugins.entries.memory-lancedb.config.embedding.model "text-embedding-004" openclaw config set plugins.entries.memory-lancedb.config.embedding.apiKey "YOUR_API_KEY" openclaw config set plugins.entries.memory-lancedb.config.embedding.dimensions 768 ``` ### 3. Install dependencies ```bash # Step 1: install main package in openclaw root cd /usr/local/lib/node_modules/openclaw npm install @lancedb/lancedb # Step 2: install platform-specific native binding in plugin dir cd /usr/local/lib/node_modules/openclaw/extensions/memory-lancedb npm install @lancedb/lancedb-darwin-arm64 # Apple Silicon (arm64) # npm install @lancedb/lancedb-darwin-x64 # Intel Mac # npm install @lancedb/lancedb-linux-x64-gnu # Linux x64 ``` ### 4. Patch native.js (Apple Silicon only) LanceDB's `native.js` tries x64 first, hits `break` on failure, and never reaches arm64. Run the patch script: ```bash python3 ~/.openclaw/workspace/skills/memory-lancedb-setup/references/patch_native.py ``` ### 5. Restart gateway and verify ```bash openclaw gateway restart ``` Then test: ``` memory_store → should return: Stored: "..." memory_recall → should return matching entries with similarity % ``` ## Migrating from MEMORY.md If MEMORY.md is large, migrate key facts to the vector store and shrink MEMORY.md to a 20-30 line index. Group by topic and call `memory_store` for each: - Identity & permissions - Execution rules - Project configurations (cron IDs, doc tokens) - Technical knowledge (API quirks, field names) - Workflows and SOPs Keep only "must-know-every-session" rules in MEMORY.md. ## Troubleshooting See `references/troubleshooting.md` for common errors and fixes.
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