--- summary: "Install the official llama.cpp provider for local GGUF memory embeddings" read_when: - You want memory search embeddings from a local GGUF model - You are configuring memorySearch.provider = "local" - You need the OpenClaw plugin that owns the node-llama-cpp runtime title: "llama.cpp Provider" sidebarTitle: "llama.cpp Provider" --- `llama-cpp` is the official external provider plugin for local GGUF embeddings. It registers embedding provider id `local` and owns the `node-llama-cpp` runtime dependency used by `memorySearch.provider: "local"`. Install it before using local memory embeddings: ```bash openclaw plugins install @openclaw/llama-cpp-provider ``` The main `openclaw` npm package does not include `node-llama-cpp`. Keeping the native dependency in this plugin prevents normal OpenClaw npm updates from deleting a manually installed runtime inside the OpenClaw package directory. ## Configuration Set `memorySearch.provider` to `local`: ```json5 { agents: { defaults: { memorySearch: { provider: "local", local: { modelPath: "hf:ggml-org/embeddinggemma-300m-qat-q8_0-GGUF/embeddinggemma-300m-qat-Q8_0.gguf", }, }, }, }, } ``` `local.modelPath` defaults to the `hf:` URI shown above (`embeddinggemma-300m-qat-Q8_0.gguf`). Point it at a different `hf:` URI or a local `.gguf` file to use another model. `local.modelCacheDir` overrides where downloaded models are cached (default: `~/.node-llama-cpp/models`), and `local.contextSize` accepts an integer or `"auto"`. ## Native Runtime Use Node 24 for the smoothest native install path. Source checkouts using pnpm may need to approve and rebuild the native dependency: ```bash pnpm approve-builds pnpm rebuild node-llama-cpp ``` ## Troubleshooting If `node-llama-cpp` is missing or fails to load, OpenClaw reports the failure with: 1. Install the plugin: `openclaw plugins install @openclaw/llama-cpp-provider`. 2. Use Node 24 for native installs/updates. 3. From a pnpm source checkout: `pnpm approve-builds`, then `pnpm rebuild node-llama-cpp`. For lower-friction local embeddings without the native build step, set `memorySearch.provider` to a remote embedding provider such as `lmstudio`, `ollama`, `openai`, or `voyage` instead.