OpenDiscourse MCP

#!/usr/bin/env python3.10 """ Performance Code Review Crew Specialized crew for performance analysis and optimization. """ import os import sys from crewai import Agent, Task, Crew from crewai_tools import CodeDocsSearchTool, DirectorySearchTool, FileReadTool from langchain_openai import ChatOpenAI from langfuse.callback import CallbackHandler # Initialize Langfuse for observability langfuse_handler = CallbackHandler() # Initialize LLM with Langfuse tracing llm = ChatOpenAI( model="microsoft/wizardlm-2-8x22b:free", base_url="https://openrouter.ai/api/v1", api_key=os.getenv("OPENROUTER_API_KEY"), temperature=0.1, callbacks=[langfuse_handler] ) # Define Tools code_search = CodeDocsSearchTool() dir_search = DirectorySearchTool() file_read = FileReadTool() # Define Performance Reviewer Agent performance_reviewer = Agent( role="Performance Code Reviewer", goal="Analyze code for performance bottlenecks and optimization opportunities", backstory="You are a performance engineering expert with deep knowledge of Python optimization techniques, algorithmic complexity, and efficient coding practices.", llm=llm, tools=[code_search, dir_search, file_read], verbose=True ) # Define Performance Task performance_task = Task( description="Analyze the code for performance issues such as inefficient algorithms, memory leaks, unnecessary computations, and database query optimizations.", expected_output="Performance analysis report with identified bottlenecks, optimization suggestions, and estimated impact.", agent=performance_reviewer ) # Create Performance Review Crew performance_crew = Crew( agents=[performance_reviewer], tasks=[performance_task], verbose=True ) def main(): """Run the performance review crew.""" print("Starting Performance Code Review Crew...") # Run the crew result = performance_crew.kickoff() print("\n=== Performance Review Results ===") print(result) if __name__ == "__main__": main()