#!/usr/bin/env python3 """ DeepCode - CLI Application Main Program 深度代码 - CLI应用主程序 🧬 Open-Source Code Agent by Data Intelligence Lab @ HKU ⚡ Revolutionizing research reproducibility through collaborative AI """ import os import sys import asyncio import time import json # 禁止生成.pyc文件 os.environ["PYTHONDONTWRITEBYTECODE"] = "1" # 添加项目根目录到路径 current_dir = os.path.dirname(os.path.abspath(__file__)) parent_dir = os.path.dirname(current_dir) if parent_dir not in sys.path: sys.path.insert(0, parent_dir) # 导入MCP应用和工作流 from cli.workflows import CLIWorkflowAdapter from cli.cli_interface import CLIInterface, Colors class CLIApp: """CLI应用主类 - 升级版智能体编排引擎""" def __init__(self): self.cli = CLIInterface() self.workflow_adapter = CLIWorkflowAdapter(cli_interface=self.cli) self.app = None # Will be initialized by workflow adapter self.logger = None self.context = None # Document segmentation configuration self.segmentation_config = {"enabled": True, "size_threshold_chars": 50000} async def initialize_mcp_app(self): """初始化MCP应用 - 使用工作流适配器""" # Workflow adapter will handle MCP initialization return await self.workflow_adapter.initialize_mcp_app() async def cleanup_mcp_app(self): """清理MCP应用 - 使用工作流适配器""" await self.workflow_adapter.cleanup_mcp_app() def update_segmentation_config(self): """Update document segmentation configuration in mcp_agent.config.yaml""" import yaml import os config_path = os.path.join( os.path.dirname(os.path.dirname(os.path.abspath(__file__))), "mcp_agent.config.yaml", ) try: # Read current config with open(config_path, "r", encoding="utf-8") as f: config = yaml.safe_load(f) # Update document segmentation settings if "document_segmentation" not in config: config["document_segmentation"] = {} config["document_segmentation"]["enabled"] = self.segmentation_config[ "enabled" ] config["document_segmentation"]["size_threshold_chars"] = ( self.segmentation_config["size_threshold_chars"] ) # Write updated config with open(config_path, "w", encoding="utf-8") as f: yaml.dump(config, f, default_flow_style=False, allow_unicode=True) self.cli.print_status( "📄 Document segmentation configuration updated", "success" ) except Exception as e: self.cli.print_status( f"⚠️ Failed to update segmentation config: {str(e)}", "warning" ) async def process_input(self, input_source: str, input_type: str): """处理输入源（URL或文件）- 使用升级版智能体编排引擎""" try: # Update segmentation configuration before processing self.update_segmentation_config() self.cli.print_separator() self.cli.print_status( "🚀 Starting intelligent agent orchestration...", "processing" ) # 显示处理阶段（根据配置决定） self.cli.display_processing_stages(0, self.cli.enable_indexing) # 使用工作流适配器进行处理 result = await self.workflow_adapter.process_input_with_orchestration( input_source=input_source, input_type=input_type, enable_indexing=self.cli.enable_indexing, ) if result["status"] == "success": # 显示完成状态 final_stage = 8 if self.cli.enable_indexing else 5 self.cli.display_processing_stages( final_stage, self.cli.enable_indexing ) self.cli.print_status( "🎉 Agent orchestration completed successfully!", "complete" ) # 显示结果 self.display_results( result.get("analysis_result", ""), result.get("download_result", ""), result.get("repo_result", ""), result.get("pipeline_mode", "comprehensive"), ) else: self.cli.print_status( f"❌ Processing failed: {result.get('error', 'Unknown error')}", "error", ) # 添加到历史记录 self.cli.add_to_history(input_source, result) return result except Exception as e: error_msg = str(e) self.cli.print_error_box("Agent Orchestration Error", error_msg) self.cli.print_status(f"Error during orchestration: {error_msg}", "error") # 添加错误到历史记录 error_result = {"status": "error", "error": error_msg} self.cli.add_to_history(input_source, error_result) return error_result def display_results( self, analysis_result: str, download_result: str, repo_result: str, pipeline_mode: str = "comprehensive", ): """显示处理结果""" self.cli.print_results_header() # 显示流水线模式 if pipeline_mode == "chat": mode_display = "💬 Chat Planning Mode" elif pipeline_mode == "comprehensive": mode_display = "🧠 Comprehensive Mode" else: mode_display = "⚡ Optimized Mode" print( f"{Colors.BOLD}{Colors.PURPLE}🤖 PIPELINE MODE: {mode_display}{Colors.ENDC}" ) self.cli.print_separator("─", 79, Colors.PURPLE) print(f"{Colors.BOLD}{Colors.OKCYAN}📊 ANALYSIS PHASE RESULTS:{Colors.ENDC}") self.cli.print_separator("─", 79, Colors.CYAN) # 尝试解析并格式化分析结果 try: if analysis_result.strip().startswith("{"): parsed_analysis = json.loads(analysis_result) print(json.dumps(parsed_analysis, indent=2, ensure_ascii=False)) else: print( analysis_result[:1000] + "..." if len(analysis_result) > 1000 else analysis_result ) except Exception: print( analysis_result[:1000] + "..." if len(analysis_result) > 1000 else analysis_result ) print(f"\n{Colors.BOLD}{Colors.PURPLE}📥 DOWNLOAD PHASE RESULTS:{Colors.ENDC}") self.cli.print_separator("─", 79, Colors.PURPLE) print( download_result[:1000] + "..." if len(download_result) > 1000 else download_result ) print( f"\n{Colors.BOLD}{Colors.GREEN}⚙️ IMPLEMENTATION PHASE RESULTS:{Colors.ENDC}" ) self.cli.print_separator("─", 79, Colors.GREEN) print(repo_result[:1000] + "..." if len(repo_result) > 1000 else repo_result) # 尝试提取生成的代码目录信息 if "Code generated in:" in repo_result: code_dir = ( repo_result.split("Code generated in:")[-1].strip().split("\n")[0] ) print( f"\n{Colors.BOLD}{Colors.YELLOW}📁 Generated Code Directory: {Colors.ENDC}{code_dir}" ) # 显示处理完成的工作流阶段 print( f"\n{Colors.BOLD}{Colors.OKCYAN}🔄 COMPLETED WORKFLOW STAGES:{Colors.ENDC}" ) if pipeline_mode == "chat": stages = [ "🚀 Engine Initialization", "💬 Requirements Analysis", "🏗️ Workspace Setup", "📝 Implementation Plan Generation", "⚙️ Code Implementation", ] else: stages = [ "📄 Document Processing", "🔍 Reference Analysis", "📋 Plan Generation", "📦 Repository Download", "🗂️ Codebase Indexing", "⚙️ Code Implementation", ] for stage in stages: print(f" ✅ {stage}") self.cli.print_separator() async def run_interactive_session(self): """运行交互式会话""" # 清屏并显示启动界面 self.cli.clear_screen() self.cli.print_logo() self.cli.print_welcome_banner() # 初始化MCP应用 await self.initialize_mcp_app() try: # 主交互循环 while self.cli.is_running: self.cli.create_menu() choice = self.cli.get_user_input() if choice in ["q", "quit", "exit"]: self.cli.print_goodbye() break elif choice in ["u", "url"]: url = self.cli.get_url_input() if url: await self.process_input(url, "url") elif choice in ["f", "file"]: file_path = self.cli.upload_file_gui() if file_path: await self.process_input(f"file://{file_path}", "file") elif choice in ["t", "chat", "text"]: chat_input = self.cli.get_chat_input() if chat_input: await self.process_input(chat_input, "chat") elif choice in ["h", "history"]: self.cli.show_history() elif choice in ["c", "config", "configure"]: # Sync current segmentation config from CLI interface self.segmentation_config["enabled"] = self.cli.segmentation_enabled self.segmentation_config["size_threshold_chars"] = ( self.cli.segmentation_threshold ) self.cli.show_configuration_menu() # Sync back from CLI interface after configuration changes self.segmentation_config["enabled"] = self.cli.segmentation_enabled self.segmentation_config["size_threshold_chars"] = ( self.cli.segmentation_threshold ) else: self.cli.print_status( "Invalid choice. Please select U, F, T, C, H, or Q.", "warning" ) # 询问是否继续 if self.cli.is_running and choice in ["u", "f", "t", "chat", "text"]: if not self.cli.ask_continue(): self.cli.is_running = False self.cli.print_status("Session ended by user", "info") except KeyboardInterrupt: print(f"\n{Colors.WARNING}⚠️ Process interrupted by user{Colors.ENDC}") except Exception as e: print(f"\n{Colors.FAIL}❌ Unexpected error: {str(e)}{Colors.ENDC}") finally: # 清理资源 await self.cleanup_mcp_app() async def main(): """主函数""" start_time = time.time() try: # 创建并运行CLI应用 app = CLIApp() await app.run_interactive_session() except KeyboardInterrupt: print(f"\n{Colors.WARNING}⚠️ Application interrupted by user{Colors.ENDC}") except Exception as e: print(f"\n{Colors.FAIL}❌ Application error: {str(e)}{Colors.ENDC}") finally: end_time = time.time() print( f"\n{Colors.BOLD}{Colors.CYAN}⏱️ Total runtime: {end_time - start_time:.2f} seconds{Colors.ENDC}" ) # 清理缓存文件 print(f"{Colors.YELLOW}🧹 Cleaning up cache files...{Colors.ENDC}") if os.name == "nt": # Windows os.system( "powershell -Command \"Get-ChildItem -Path . -Filter '__pycache__' -Recurse -Directory | Remove-Item -Recurse -Force\" 2>nul" ) else: # Unix/Linux/macOS os.system('find . -type d -name "__pycache__" -exec rm -r {} + 2>/dev/null') print( f"{Colors.OKGREEN}✨ Goodbye! Thanks for using DeepCode CLI! ✨{Colors.ENDC}" ) if __name__ == "__main__": asyncio.run(main())