A Learning Agent with Alloy Models

This demo showcases cagent's "alloy models" feature - the ability to use multiple AI models within a single agent.

Configuration

Create a file named alloy.yaml:

agents:
  root:
    model: claude,gpt-4o  # Multiple models!
    description: An agent that helps you learn new things
    instruction: |
      You are an expert learning companion.
      Help users learn effectively and enjoyably.

models:
  claude:
    provider: anthropic
    model: claude-3-5-sonnet-latest
  gpt-4o:
    provider: openai 
    model: gpt-4o

Prerequisites

Set up API keys for both providers:

export OPENAI_API_KEY=your_openai_key
export ANTHROPIC_API_KEY=your_anthropic_key

Running the Agent

./bin/cagent run alloy.yaml

How Alloy Models Work

When you specify multiple models separated by commas (model: claude,gpt-4o), cagent:

1. Routes requests intelligently between models
2. Can switch between Claude and GPT-4 automatically for best responses
3. Leverages each model's strengths for different types of queries

Use Cases

• Learning applications: Get explanations from different perspectives
• Research tasks: Cross-validate information across models
• Creative work: Combine different AI "voices" and styles
• Reliability: Fallback to another model if one is unavailable

Key Takeaways

• Alloy models let you combine multiple AI providers in one agent
• Define models separately in the models section
• Reference them by name in the agent's model field
• Great for applications requiring diverse AI capabilities