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Ollama

Ollama is a local LLM runtime that makes it easy to run open-source models on your machine. Clawdia integrates with Ollama’s OpenAI-compatible API 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.

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Quick start

  1. Install Ollama: https://ollama.ai
  2. Pull a model: 
ollama pull llama3.3
# or
ollama pull qwen2.5-coder:32b
# or
ollama pull deepseek-r1:32b
  1. Enable Ollama for Clawdia (any value works; Ollama doesn’t require a real key):
# Set environment variable
export OLLAMA_API_KEY="ollama-local"

# Or configure in your config file
clawdia config set models.providers.ollama.apiKey "ollama-local"
  1. Use Ollama models:
{
  agents: {
    defaults: {
      model: { primary: "ollama/llama3.3" }
    }
  }
}

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Model discovery (implicit provider)

When you set OLLAMA_API_KEY (or an auth profile) and do not define models.providers.ollama, Clawdia 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: 
ollama list
clawdia models list
To add a new model, simply pull it with Ollama: 
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).

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Configuration

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Basic setup (implicit discovery)

The simplest way to enable Ollama is via environment variable: 
export OLLAMA_API_KEY="ollama-local"

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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.
{
  models: {
    providers: {
      ollama: {
        // Use a host that includes /v1 for OpenAI-compatible APIs
        baseUrl: "http://ollama-host:11434/v1",
        apiKey: "ollama-local",
        api: "openai-completions",
        models: [
          {
            id: "llama3.3",
            name: "Llama 3.3",
            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 Clawdia will fill it for availability checks.

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Custom base URL (explicit config)

If Ollama is running on a different host or port (explicit config disables auto-discovery, so define models manually): 
{
  models: {
    providers: {
      ollama: {
        apiKey: "ollama-local",
        baseUrl: "http://ollama-host:11434/v1"
      }
    }
  }
}

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Model selection

Once configured, all your Ollama models are available: 
{
  agents: {
    defaults: {
      model: {
        primary: "ollama/llama3.3",
        fallback: ["ollama/qwen2.5-coder:32b"]
      }
    }
  }
}

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Advanced

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Reasoning models

Clawdia marks models as reasoning-capable when Ollama reports thinking in /api/show: 
ollama pull deepseek-r1:32b

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Model Costs

Ollama is free and runs locally, so all model costs are set to $0.

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Context windows

For auto-discovered models, Clawdia uses the context window reported by Ollama when available, otherwise it defaults to 8192. You can override contextWindow and maxTokens in explicit provider config.

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Troubleshooting

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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: 
ollama serve
And that the API is accessible: 
curl http://localhost:11434/api/tags

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No models available

Clawdia 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: 
ollama list  # See what's installed
ollama pull llama3.3  # Pull a model

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Connection refused

Check that Ollama is running on the correct port: 
# Check if Ollama is running
ps aux | grep ollama

# Or restart Ollama
ollama serve

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See Also