livekit-plugins-anthropic

import os from livekit.agents import AgentSession, JobContext from livekit.plugins import anthropic # Set your Anthropic API key as an environment variable # os.environ["ANTHROPIC_API_KEY"] = "sk-your-anthropic-key" async def my_agent(ctx: JobContext): # Ensure ANTHROPIC_API_KEY is set in your environment or passed directly anthropic_api_key = os.environ.get('ANTHROPIC_API_KEY', '') if not anthropic_api_key: raise ValueError("ANTHROPIC_API_KEY environment variable is not set.") print("Starting agent session with Anthropic LLM...") session = AgentSession( llm=anthropic.LLM( model="claude-3-5-sonnet-20241022", api_key=anthropic_api_key # Can be omitted if env var is set ) ) # In a real agent, you'd process audio/text input and generate replies. # This is a minimal example to show LLM instantiation. print(f"Agent session created with LLM model: {session.llm.model}") # Example of a simple chat interaction (requires AgentSession context for full functionality) # from livekit.agents.llm import ChatContext, UserMessage # chat_ctx = ChatContext() # chat_ctx.append(UserMessage(text="Hello, what can you do?")) # response = await session.llm.chat(chat_ctx) # async for chunk in response.stream: # print(chunk.delta) await session.astop() print("Agent session stopped.") # To run this, you would typically integrate it with a LiveKit server # and an Agent runner, like: # if __name__ == "__main__": # from livekit.agents import cli # cli.run_agent(my_agent)