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@gguf/claw

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Multi-channel AI gateway with extensible messaging integrations

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--- summary: "Run OpenClaw with Ollama (local LLM runtime)" read_when: - You want to run OpenClaw with local models via Ollama - You need Ollama setup and configuration guidance title: "Ollama" --- # Ollama Ollama is a local LLM runtime that makes it easy to run open-source models on your machine. OpenClaw integrates with Ollama's native API (`/api/chat`), supporting streaming and tool calling, and can **auto-discover tool-capable models** when you opt in with `OLLAMA_API_KEY` (or an auth profile) and do not define an explicit `models.providers.ollama` entry. ## Quick start 1. Install Ollama: [https://ollama.ai](https://ollama.ai) 2. Pull a model: ```bash ollama pull gpt-oss:20b # or ollama pull llama3.3 # or ollama pull qwen2.5-coder:32b # or ollama pull deepseek-r1:32b ``` 3. Enable Ollama for OpenClaw (any value works; Ollama doesn't require a real key): ```bash # Set environment variable export OLLAMA_API_KEY="ollama-local" # Or configure in your config file openclaw config set models.providers.ollama.apiKey "ollama-local" ``` 4. Use Ollama models: ```json5 { agents: { defaults: { model: { primary: "ollama/gpt-oss:20b" }, }, }, } ``` ## Model discovery (implicit provider) When you set `OLLAMA_API_KEY` (or an auth profile) and **do not** define `models.providers.ollama`, OpenClaw discovers models from the local Ollama instance at `http://127.0.0.1:11434`: - Queries `/api/tags` and `/api/show` - Keeps only models that report `tools` capability - Marks `reasoning` when the model reports `thinking` - Reads `contextWindow` from `model_info["<arch>.context_length"]` when available - Sets `maxTokens` to 10× the context window - Sets all costs to `0` This avoids manual model entries while keeping the catalog aligned with Ollama's capabilities. To see what models are available: ```bash ollama list openclaw models list ``` To add a new model, simply pull it with Ollama: ```bash ollama pull mistral ``` The new model will be automatically discovered and available to use. If you set `models.providers.ollama` explicitly, auto-discovery is skipped and you must define models manually (see below). ## Configuration ### Basic setup (implicit discovery) The simplest way to enable Ollama is via environment variable: ```bash export OLLAMA_API_KEY="ollama-local" ``` ### Explicit setup (manual models) Use explicit config when: - Ollama runs on another host/port. - You want to force specific context windows or model lists. - You want to include models that do not report tool support. ```json5 { models: { providers: { ollama: { baseUrl: "http://ollama-host:11434", apiKey: "ollama-local", api: "ollama", models: [ { id: "gpt-oss:20b", name: "GPT-OSS 20B", reasoning: false, input: ["text"], cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 }, contextWindow: 8192, maxTokens: 8192 * 10 } ] } } } } ``` If `OLLAMA_API_KEY` is set, you can omit `apiKey` in the provider entry and OpenClaw will fill it for availability checks. ### Custom base URL (explicit config) If Ollama is running on a different host or port (explicit config disables auto-discovery, so define models manually): ```json5 { models: { providers: { ollama: { apiKey: "ollama-local", baseUrl: "http://ollama-host:11434", }, }, }, } ``` ### Model selection Once configured, all your Ollama models are available: ```json5 { agents: { defaults: { model: { primary: "ollama/gpt-oss:20b", fallbacks: ["ollama/llama3.3", "ollama/qwen2.5-coder:32b"], }, }, }, } ``` ## Advanced ### Reasoning models OpenClaw marks models as reasoning-capable when Ollama reports `thinking` in `/api/show`: ```bash ollama pull deepseek-r1:32b ``` ### Model Costs Ollama is free and runs locally, so all model costs are set to $0. ### Streaming Configuration OpenClaw's Ollama integration uses the **native Ollama API** (`/api/chat`) by default, which fully supports streaming and tool calling simultaneously. No special configuration is needed. #### Legacy OpenAI-Compatible Mode If you need to use the OpenAI-compatible endpoint instead (e.g., behind a proxy that only supports OpenAI format), set `api: "openai-completions"` explicitly: ```json5 { models: { providers: { ollama: { baseUrl: "http://ollama-host:11434/v1", api: "openai-completions", apiKey: "ollama-local", models: [...] } } } } ``` Note: The OpenAI-compatible endpoint may not support streaming + tool calling simultaneously. You may need to disable streaming with `params: { streaming: false }` in model config. ### Context windows For auto-discovered models, OpenClaw uses the context window reported by Ollama when available, otherwise it defaults to `8192`. You can override `contextWindow` and `maxTokens` in explicit provider config. ## Troubleshooting ### Ollama not detected Make sure Ollama is running and that you set `OLLAMA_API_KEY` (or an auth profile), and that you did **not** define an explicit `models.providers.ollama` entry: ```bash ollama serve ``` And that the API is accessible: ```bash curl http://localhost:11434/api/tags ``` ### No models available OpenClaw only auto-discovers models that report tool support. If your model isn't listed, either: - Pull a tool-capable model, or - Define the model explicitly in `models.providers.ollama`. To add models: ```bash ollama list # See what's installed ollama pull gpt-oss:20b # Pull a tool-capable model ollama pull llama3.3 # Or another model ``` ### Connection refused Check that Ollama is running on the correct port: ```bash # Check if Ollama is running ps aux | grep ollama # Or restart Ollama ollama serve ``` ## See Also - [Model Providers](/concepts/model-providers) - Overview of all providers - [Model Selection](/concepts/models) - How to choose models - [Configuration](/gateway/configuration) - Full config reference