Ollama

Ollama runs open-source LLMs locally on your machine. It exposes an OpenAI-compatible API at localhost:11434, which AgentXchain connects to via the api_proxy adapter.

Which adapter?

api_proxy with provider: "ollama" — AgentXchain sends governed turn prompts to Ollama's local OpenAI-compatible endpoint.

Prerequisites

• Ollama installed (brew install ollama or download from ollama.com)
• A model pulled (ollama pull qwen3:32b or your preferred coding model)
• Ollama server running (ollama serve)
• agentxchain CLI installed

Configuration

{
  "runtimes": {
    "ollama-dev": {
      "type": "api_proxy",
      "provider": "ollama",
      "model": "qwen3:32b",
      "auth_env": "OLLAMA_API_KEY"
    }
  },
  "roles": {
    "dev": {
      "runtime": "ollama-dev",
      "mandate": "Implement features and fix bugs",
      "authority": "proposed"
    }
  }
}

Auth note

Ollama doesn't require an API key by default. Set a dummy value:

export OLLAMA_API_KEY="ollama"

The auth_env field is required by the adapter contract, but Ollama ignores the value.

Recommended coding models

Model	Size	Best for
qwen3-coder:32b	32B	Best local coding model
deepseek-coder-v3:33b	33B	Strong code generation
codestral:22b	22B	Fast Mistral coding model
llama4-scout:17b	17B	Meta's efficient coding model

Verify the connection

ollama serve &  # ensure server is running
export OLLAMA_API_KEY="ollama"
agentxchain connector check
agentxchain connector validate ollama-dev

Minimal working example

ollama pull qwen3:32b
ollama serve &
export OLLAMA_API_KEY="ollama"

agentxchain init --governed --template cli-tool --goal "Build a file renamer" --dir my-project -y
cd my-project
# Replace the scaffolded runtime wiring in agentxchain.json with the Ollama config above.
agentxchain doctor
agentxchain connector check
agentxchain connector validate ollama-dev
agentxchain run

Or use the guided interactive path (prompts for template, name, goal, and folder), then update agentxchain.json with the Ollama config above before agentxchain connector check and agentxchain connector validate ollama-dev:

agentxchain init --governed

Custom endpoint

If Ollama runs on a different host or port:

{
  "runtimes": {
    "ollama-remote": {
      "type": "api_proxy",
      "provider": "ollama",
      "model": "qwen3:32b",
      "auth_env": "OLLAMA_API_KEY",
      "base_url": "http://192.168.1.100:11434/v1/chat/completions"
    }
  }
}

Gotchas

• Model size vs. quality: Larger models produce better governed turn results but are slower. For QA/review roles, smaller models (7B-14B) may suffice. For implementation roles, use 32B+ models.
• Context window: Most Ollama models have 4K-32K context windows. AgentXchain dispatch bundles can be large. Check your model's context limit and set budget.max_tokens_per_turn accordingly.
• No internet required: Ollama runs entirely locally. This is ideal for air-gapped environments or privacy-sensitive codebases.
• GPU memory: Ensure you have enough VRAM for your chosen model. 32B models typically need 20GB+ VRAM.