MCTS MCP Server

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Test script for MCTS MCP Server LLM Adapter =========================================== This script tests the LocalInferenceLLMAdapter which replaces the broken call_model approach. """ import os import sys import asyncio import logging # Set up logging logging.basicConfig( level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", ) logger = logging.getLogger("mcts_test") # Add the project root to the Python path project_root = os.path.dirname(os.path.abspath(__file__)) if project_root not in sys.path: sys.path.insert(0, project_root) # Import just the adapter sys.path.insert(0, os.path.join(project_root, "src")) from src.mcts_mcp_server.llm_adapter import LocalInferenceLLMAdapter async def test_llm_adapter(): """Test the local inference adapter.""" logger.info("Testing LocalInferenceLLMAdapter...") adapter = LocalInferenceLLMAdapter() # Test basic completion test_messages = [{"role": "user", "content": "Generate a thought about AI safety."}] result = await adapter.get_completion("default", test_messages) logger.info(f"Basic completion test result: {result}") # Test thought generation context = { "question_summary": "What are the implications of AI in healthcare?", "current_approach": "initial", "best_score": "0", "best_answer": "", "current_answer": "", "current_sequence": "1" } # Use a dictionary for config config = { "max_children": 10, "exploration_weight": 3.0, "max_iterations": 1, "simulations_per_iteration": 10, "debug_logging": False, } thought = await adapter.generate_thought(context, config) logger.info(f"Thought generation test result: {thought}") # Test evaluation context["answer_to_evaluate"] = "AI in healthcare presents both opportunities and challenges. While it can improve diagnosis accuracy, there are ethical concerns about privacy and decision-making." score = await adapter.evaluate_analysis(context["answer_to_evaluate"], context, config) logger.info(f"Evaluation test result (score 1-10): {score}") # Test tag generation tags = await adapter.generate_tags("AI in healthcare can revolutionize patient care through improved diagnostics and personalized treatment plans.", config) logger.info(f"Tag generation test result: {tags}") # Test streaming logger.info("Testing streaming completion...") stream_messages = [{"role": "user", "content": "This is a test of streaming."}] async for chunk in adapter.get_streaming_completion("default", stream_messages): logger.info(f"Received chunk: {chunk}") logger.info("All LLM adapter tests completed successfully!") return True async def main(): """Run tests for the MCTS MCP server components.""" try: # Test the LLM adapter adapter_result = await test_llm_adapter() if adapter_result: logger.info("✅ LLM adapter tests passed") logger.info("\nThe MCTS MCP server should now work with Claude Desktop.") logger.info("To use it with Claude Desktop:") logger.info("1. Copy the claude_desktop_config.json file to your Claude Desktop config location") logger.info("2. Restart Claude Desktop") logger.info("3. Ask Claude to analyze a topic using MCTS") except Exception as e: logger.error(f"Test failed with error: {e}") return False return True if __name__ == "__main__": asyncio.run(main())