Ayaan Zaidi
06038f9df8
Allow low-memory local-memory setups to install only the verified managed server and embedding model while preserving every configured chat route. Co-authored-by: Ayaan Zaidi <hi@obviy.us>
2.5 KiB
@openclaw/llama-cpp-provider
Official llama.cpp provider for managed and external OpenClaw model servers.
The llama-cpp provider either installs a pinned, integrity-verified
llama-server under OpenClaw's localService supervisor or connects to a
server that you already operate. Both choices use llama-cpp/<model> references
and OpenClaw's normal OpenAI-compatible chat transport. Local embeddings require
the managed choice.
Install
openclaw plugins install @openclaw/llama-cpp-provider
Restart the Gateway after installing or updating the plugin. Interactive setup shows Managed local server and Existing llama-server under one Local llama.cpp group.
Configure managed text inference
After explicit consent, OpenClaw installs the matching server build and downloads Gemma 4 E4B IT Q4_K_M (approximately 5.0 GB) plus EmbeddingGemma (approximately 0.3 GB). The default chat download is offered only on machines with at least 16 GiB of RAM.
When local memory search is configured and chat setup is unavailable or declined, OpenClaw offers a separate embedding-only setup. After explicit consent, it installs only the server and EmbeddingGemma. It leaves the current chat model unchanged. Move any llama.cpp chat routes and remove its configured chat model entries first. Remove an existing external server config before retrying embedding-only setup.
Custom GGUF models remain supported through params.modelPath. Rerun llama.cpp
setup after changing the model so OpenClaw can verify the file and regenerate
the managed router preset.
See the llama.cpp provider guide for platform requirements, custom GGUF configuration, diagnostics, and repair.
Connect to an existing server
Choose Existing llama-server during setup and enter the endpoint and optional API key. OpenClaw passively discovers single-model and router catalogs. It never installs, starts, stops, or reconfigures the external process.
See the llama.cpp provider guide for authentication, router behavior, manual configuration, and troubleshooting.
Configure embeddings
Set memory.search.provider to local. The plugin preserves the historical
local embedding provider and index identity while serving requests through
the managed server's /v1/embeddings endpoint.
Package
- Plugin id:
llama-cpp - Provider id:
llama-cpp - Package:
@openclaw/llama-cpp-provider - Minimum OpenClaw host:
2026.6.2