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:
- Routes requests intelligently between models
- Can switch between Claude and GPT-4 automatically for best responses
- 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
modelssection - Reference them by name in the agent's
modelfield - Great for applications requiring diverse AI capabilities