Agent API Reference

from aakit import Agent, AgentConfig, tool
import asyncio

# Define a custom tool
@tool(description="Search for information on the web")
def web_search(query: str) -> str:
    # Implementation here
    return f"Search results for: {query}"

# Configure the agent
config = AgentConfig(
    temperature=0.7,
    max_tokens=2000,
    timeout=30,
    cache_ttl=3600
)

# Create the agent
agent = Agent(
    name="research_assistant",
    instruction="""You are a research assistant that helps users find 
    and analyze information. Be thorough and cite sources.""",
    model=["gpt-4", "claude-3-opus"],  # Fallback chain
    tools=[web_search],
    memory="redis",
    reasoning="chain_of_thought",
    config=config
)

# Use the agent
async def main():
    # NEW: Synchronous API - no async/await needed!
    # Simple chat
    response = agent.chat("What is quantum computing?")
    print(response)
    
    # Streaming response
    print("\nStreaming response:")
    for chunk in agent.stream_chat("Explain the basics of machine learning"):
        print(chunk, end="", flush=True)
    
    # Get metrics
    metrics = agent.get_metrics()
    print(f"\n\nTotal tokens used: {metrics.total_tokens}")
    
    # Async version (when you need it)
    response = await agent.achat("What is AI?")
    async for chunk in agent.astream_chat("Write a poem"):
        print(chunk, end="")

# Run the example
asyncio.run(main())

# Serve as MCP server
if __name__ == "__main__":
    agent.serve_mcp(
        port=8080,
        name="Research Assistant",
        description="AI assistant with web search capabilities"
    )