109 lines
3.9 KiB
Python
109 lines
3.9 KiB
Python
#!/usr/bin/env python3
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"""
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MaxClaw Agent - A configurable agent harness using DeepAgents
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Supports multiple LLM providers via LangChain's init_chat_model
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"""
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import os
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import sys
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from typing import Optional
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from deepagents import create_deep_agent
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from langchain.chat_models import init_chat_model
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from langchain_core.messages import HumanMessage, SystemMessage
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def load_model_from_config():
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"""
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Load the LLM model based on configuration.
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Configuration can come from environment variables or a config file.
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For simplicity, we'll use environment variables.
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Expected environment variables:
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- OPENAI_API_KEY: For OpenAI models
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- OLLAMA_BASE_URL: For Ollama (e.g., https://ollama.solarpi.net)
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- MODEL_PROVIDER: One of "openai", "ollama", "openrouter", etc.
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- MODEL_NAME: The specific model name (e.g., "gpt-4o", "gemma2:9b")
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"""
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provider = os.getenv("MODEL_PROVIDER", "openai").lower()
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model_name = os.getenv("MODEL_NAME", "gpt-4o")
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# Configure based on provider
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if provider == "openai":
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# Uses OPENAI_API_KEY from environment
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return init_chat_model(f"openai:{model_name}")
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elif provider == "ollama":
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# For Ollama, we need to specify the base URL
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base_url = os.getenv("OLLAMA_BASE_URL", "http://localhost:11434")
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return init_chat_model(f"ollama:{model_name}", base_url=base_url)
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elif provider == "openrouter":
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# For OpenRouter, we need OPENROUTER_API_KEY and optionally base URL
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# Note: LangChain's init_chat_model for openrouter might require specific setup
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# As of now, we assume it's supported via openai-compatible API
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base_url = os.getenv("OPENROUTER_BASE_URL", "https://openrouter.ai/api/v1")
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api_key = os.getenv("OPENROUTER_API_KEY")
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if not api_key:
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raise ValueError("OPENROUTER_API_KEY environment variable is required for OpenRouter")
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# Using openai-compatible API
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return init_chat_model(
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f"openai:{model_name}",
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base_url=base_url,
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api_key=api_key
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)
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else:
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# Fallback to openai for unknown providers (or add more as needed)
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return init_chat_model(f"openai:{model_name}")
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def create_maxclaw_agent(system_prompt: Optional[str] = None):
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"""
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Create and return a DeepAgent instance with configurable model.
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"""
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if system_prompt is None:
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system_prompt = """You are MaxClaw, a helpful AI agent that can plan, use tools,
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manage context, and delegate to subagents. You are designed to be configurable
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to work with various LLM providers."""
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model = load_model_from_config()
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agent = create_deep_agent(
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model=model,
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system_prompt=system_prompt
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)
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return agent
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def main():
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"""
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Main entry point for the MaxClaw agent.
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"""
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print("🚀 Initializing MaxClaw Agent...")
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try:
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agent = create_maxclaw_agent()
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print("✅ Agent initialized successfully!")
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# Simple test interaction
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print("\n💬 You can now interact with the agent. Type 'exit' to quit.")
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while True:
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user_input = input("\n👤 You: ").strip()
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if user_input.lower() in ['exit', 'quit']:
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print("👋 Goodbye!")
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break
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if not user_input:
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continue
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# Invoke the agent
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try:
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result = agent.invoke({"messages": [HumanMessage(content=user_input)]})
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# Extract the AI's response
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ai_message = result["messages"][-1]
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print(f"\n🤖 MaxClaw: {ai_message.content}")
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except Exception as e:
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print(f"\n❌ Error: {str(e)}")
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except Exception as e:
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print(f"❌ Failed to initialize agent: {str(e)}")
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sys.exit(1)
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if __name__ == "__main__":
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main() |