bot/docs/providers/ollama.md

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summary	read_when	title
Run HanzoBot with Ollama (local LLM runtime)	You want to run HanzoBot with local models via Ollama You need Ollama setup and configuration guidance	Ollama

Ollama

Ollama is a local LLM runtime that makes it easy to run open-source models on your machine. HanzoBot 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.

**Remote Ollama users**: Do not use the `/v1` OpenAI-compatible URL (`http://host:11434/v1`) with HanzoBot. This breaks tool calling and models may output raw tool JSON as plain text. Use the native Ollama API URL instead: `baseUrl: "http://host:11434"` (no `/v1`).

Quick start

1. Install Ollama: https://ollama.ai

2. Pull a model:

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 HanzoBot (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
hanzo-bot config set models.providers.ollama.apiKey "ollama-local"

4. Use Ollama models:

{
  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, HanzoBot 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
hanzo-bot 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).

Configuration

Basic setup (implicit discovery)

The simplest way to enable Ollama is via environment variable:

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.

{
  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 HanzoBot 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):

{
  models: {
    providers: {
      ollama: {
        apiKey: "ollama-local",
        baseUrl: "http://ollama-host:11434", // No /v1 - use native Ollama API URL
        api: "ollama", // Set explicitly to guarantee native tool-calling behavior
      },
    },
  },
}

Do not add `/v1` to the URL. The `/v1` path uses OpenAI-compatible mode, where tool calling is not reliable. Use the base Ollama URL without a path suffix.

Model selection

Once configured, all your Ollama models are available:

{
  agents: {
    defaults: {
      model: {
        primary: "ollama/gpt-oss:20b",
        fallbacks: ["ollama/llama3.3", "ollama/qwen2.5-coder:32b"],
      },
    },
  },
}

Advanced

Reasoning models

HanzoBot marks models as reasoning-capable when Ollama reports thinking in /api/show:

ollama pull deepseek-r1:32b

Model Costs

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

Streaming Configuration

HanzoBot'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

**Tool calling is not reliable in OpenAI-compatible mode.** Use this mode only if you need OpenAI format for a proxy and do not depend on native tool calling behavior.

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:

{
  models: {
    providers: {
      ollama: {
        baseUrl: "http://ollama-host:11434/v1",
        api: "openai-completions",
        injectNumCtxForOpenAICompat: true, // default: true
        apiKey: "ollama-local",
        models: [...]
      }
    }
  }
}

This mode may not support streaming + tool calling simultaneously. You may need to disable streaming with params: { streaming: false } in model config.

When api: "openai-completions" is used with Ollama, HanzoBot injects options.num_ctx by default so Ollama does not silently fall back to a 4096 context window. If your proxy/upstream rejects unknown options fields, disable this behavior:

{
  models: {
    providers: {
      ollama: {
        baseUrl: "http://ollama-host:11434/v1",
        api: "openai-completions",
        injectNumCtxForOpenAICompat: false,
        apiKey: "ollama-local",
        models: [...]
      }
    }
  }
}

Context windows

For auto-discovered models, HanzoBot 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:

ollama serve

And that the API is accessible:

curl http://localhost:11434/api/tags

No models available

HanzoBot 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 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:

# Check if Ollama is running
ps aux | grep ollama

# Or restart Ollama
ollama serve

See Also

• Model Providers - Overview of all providers
• Model Selection - How to choose models
• Configuration - Full config reference