LLM Models Configuration

Supported Models (via OpenRouter)

The project uses the following models for AI agents:

• google/gemini-3-flash-preview - Used by GeminiAgent (fast, cost-effective)
• x-ai/grok-4.1-fast - Used by GrokAgent (balanced performance)

IMPORTANT: These are the only models configured and tested. Do not suggest or implement other models without explicit approval.

Adding New Models

If you need to add a new model:

1. Verify model exists on OpenRouter: https://openrouter.ai/models
2. Create new agent class in src/agents/
3. Add model to database: INSERT INTO agents (name, model_name) VALUES ('agent_name', 'model/id')
4. Test thoroughly with test_agent.py
5. Update docker-compose.yml if needed
6. Document performance and cost characteristics

Model Selection Criteria

• Speed: Must return predictions within 30 seconds
• Cost: Keep per-prediction cost under acceptable threshold
• Reliability: Must handle race data format consistently
• Structured output: Must support JSON output format