sync

app.py

@@ -1,1453 +1,5 @@
-import platform
-import psutil
-from typing import List, Dict, Optional, Any, Tuple
-from dataclasses import dataclass
-from enum import Enum
-import logging
-import time
-import ast
-import pylint.lint
-import radon.complexity
-import radon.metrics
-from pylint.lint import Run
-from pylint.reporters import JSONReporter
-from coverage import Coverage
-import bandit
-from bandit.core import manager
-from datetime import datetime
-import os
-import sys
 import streamlit as st
-import requests
-import asyncio
-import statistics
-import json
-import traceback
-from typing import Dict, Any
-from datetime import datetime
-from pathlib import Path
-
-class AutonomousAgentApp:
-    """Main application class for the Autonomous Agent System"""
-
-    def __init__(self):
-        self.workspace_manager = self.WorkspaceManager(workspace_dir='workspace')  # Use self.WorkspaceManager
-        self.pipeline = self._initialize_pipeline()
-        self.refinement_loop = self.RefinementLoop(pipeline=self.pipeline)  # Use self.RefinementLoop
-        self.interface = self.StreamlitInterface(self)  # Use self.StreamlitInterface
-
-    def _initialize_pipeline(self) -> 'AutonomousAgentApp.DevelopmentPipeline':
-        """Initialize the development pipeline"""
-        return self.DevelopmentPipeline(
-            workspace_manager=self.workspace_manager,
-            tool_manager=self._setup_tool_manager()
-        )
-
-    def _setup_tool_manager(self):
-        """Setup tool manager with configuration"""
-        return self.ToolManager()  # Use self.ToolManager
-
-    def run(self):
-        """Main application entry point"""
-        try:
-            logging.info("Starting Autonomous Agent Application")
-            self.interface.render_main_interface()
-        except Exception as e:
-            logging.error(f"Application error: {str(e)}")
-            st.error("An error occurred while starting the application. Please check the logs.")
-            raise
-
-    class WorkspaceManager:
-        """Manages workspace files and directories."""
-
-        def __init__(self, workspace_dir: str = "workspace"):
-            self.workspace_dir = workspace_dir
-            self._ensure_workspace_exists()
-
-        def _ensure_workspace_exists(self):
-            """Ensure the workspace directory exists."""
-            os.makedirs(self.workspace_dir, exist_ok=True)
-
-        def create_file(self, filename: str, content: str) -> str:
-            """Create a file in the workspace with the given content."""
-            file_path = os.path.join(self.workspace_dir, filename)
-            with open(file_path, "w") as f:
-                f.write(content)
-            return f"File '{filename}' created at '{file_path}'."
-
-        def delete_file(self, filename: str) -> str:
-            """Delete a file from the workspace."""
-            file_path = os.path.join(self.workspace_dir, filename)
-            if os.path.exists(file_path):
-                os.remove(file_path)
-                return f"File '{filename}' deleted."
-            return f"File '{filename}' not found."
-
-        def list_files(self) -> List[str]:
-            """List all files in the workspace."""
-            return [
-                os.path.join(root, file)
-                for root, _, files in os.walk(self.workspace_dir)
-                for file in files
-            ]
-
-        def read_file(self, filename: str) -> str:
-            """Read the content of a file in the workspace."""
-            file_path = os.path.join(self.workspace_dir, filename)
-            if os.path.exists(file_path):
-                with open(file_path, "r") as f:
-                    return f.read()
-            return f"File '{filename}' not found."
-
-        def get_workspace_tree(self) -> Dict[str, Any]:
-            """Get the workspace directory structure as a nested dictionary."""
-            workspace_path = Path(self.workspace_dir)
-            return self._build_tree(workspace_path)
-
-        def _build_tree(self, path: Path) -> Dict[str, Any]:
-            """Recursively build a directory tree."""
-            if path.is_file():
-                return {"type": "file", "name": path.name}
-            elif path.is_dir():
-                return {
-                    "type": "directory",
-                    "name": path.name,
-                    "children": [self._build_tree(child) for child in path.iterdir()],
-                }
-
-    class AutonomousAgent:
-        """Autonomous agent that builds tools and agents based on tasks."""
-
-        def __init__(self, workspace_manager: 'AutonomousAgentApp.WorkspaceManager'):  # Use fully qualified name
-            self.workspace_manager = workspace_manager
-            self.tools_dir = Path(self.workspace_manager.workspace_dir) / "tools"
-            self.agents_dir = Path(self.workspace_manager.workspace_dir) / "agents"
-            self.tools_dir.mkdir(exist_ok=True)  # Ensure the tools directory exists
-            self.agents_dir.mkdir(exist_ok=True)  # Ensure the agents directory exists
-            self.running = True  # Flag to control the running state
-
-        async def run(self):
-            """Run the autonomous agent, continuously processing tasks."""
-            while self.running:
-                # Default task execution
-                await self.default_task()
-                await asyncio.sleep(1)  # Prevent busy waiting
-
-        async def default_task(self):
-            """Perform the default task of analyzing and generating tools/agents."""
-            logging.info("Running default task...")
-            # Simulate task processing
-            await asyncio.sleep(2)  # Simulate time taken for the task
-
-        async def pause(self):
-            """Pause the current operation to accept user input."""
-            self.running = False
-            logging.info("Paused. Waiting for user input...")
-
-        async def accept_user_input(self, user_input: str):
-            """Process user input and execute commands."""
-            logging.info(f"User input received: {user_input}")
-            commands = self.extract_commands(user_input)
-            
-            for command in commands:
-                if command.startswith("generate tool"):
-                    await self.generate_tool(command)
-                elif command.startswith("generate agent"):
-                    await self.generate_agent(command)
-                # Add more command handling as needed
-
-        def extract_commands(self, user_input: str) -> List[str]:
-            """Extract commands from user input."""
-            # Simple command extraction logic (can be improved with NLP)
-            return user_input.split(';')  # Assume commands are separated by semicolons
-
-        async def run_refinement_cycle(self, task: str) -> Dict[str, Any]:
-            """Run a refinement cycle for the given task."""
-            # Step 1: Analyze the task
-            task_analysis = await self._analyze_task(task)
-            
-            # Step 2: Search for relevant approaches/methods
-            search_results = await self._web_search(task)
-            
-            # Step 3: Build tools/agents based on the task
-            tools_built = await self._build_tools(task_analysis, search_results)
-            
-            # Step 4: Execute the tools/agents
-            execution_results = await self._execute_tools(tools_built)
-            
-            return {
-                "task_analysis": task_analysis,
-                "search_results": search_results,
-                "tools_built": tools_built,
-                "execution_results": execution_results,
-            }
-
-        async def _analyze_task(self, task: str) -> Dict[str, Any]:
-            """Analyze the task to determine requirements."""
-            keywords = self._extract_keywords(task)
-            requirements = self._generate_requirements(keywords)
-            
-            return {
-                "task": task,
-                "keywords": keywords,
-                "requirements": requirements,
-            }
-
-        def _extract_keywords(self, text: str) -> List[str]:
-            """Extract keywords from the task text."""
-            stop_words = {"the", "and", "of", "to", "in", "a", "is", "for", "on", "with"}
-            words = [word.lower() for word in text.split() if word.lower() not in stop_words]
-            return list(set(words))  # Remove duplicates
-
-        def _generate_requirements(self, keywords: List[str]) -> List[str]:
-            """Generate requirements based on extracted keywords."""
-            requirement_map = {
-                "data": ["data collection", "data processing", "data visualization"],
-                "web": ["web scraping", "API integration", "web development"],
-                "ai": ["machine learning", "natural language processing", "computer vision"],
-                "automation": ["task automation", "workflow optimization", "scripting"],
-            }
-            
-            requirements = []
-            for keyword in keywords:
-                if keyword in requirement_map:
-                    requirements.extend(requirement_map[keyword])
-            
-            return requirements
-
-        async def _web_search(self, query: str) -> List[Dict[str, Any]]:
-            """Perform a web search for relevant approaches/methods."""
-            try:
-                response = requests.get(
-                    "https://api.example.com/search",
-                    params={"q": query, "limit": 5}
-                )
-                response.raise_for_status()
-                return response.json().get("results", [])
-            except Exception as e:
-                logging.error(f"Web search failed: {e}")
-                return [{"title": "Example Approach", "url": "https://example.com"}]
-
-        async def _build_tools(self, task_analysis: Dict[str, Any], search_results: List[Dict[str, Any]]) -> List[str]:
-            """Build tools/agents based on the task and search results."""
-            tools = []
-            for requirement in task_analysis["requirements"]:
-                tool_name = f"tool_for_{requirement.replace(' ', '_')}.py"
-                tool_path = self.tools_dir / tool_name
-                
-                # Generate a simple Python script for the tool
-                tool_code = self._generate_tool_code(requirement, search_results)
-                with open(tool_path, "w") as f:
-                    f.write(tool_code)
-                
-                tools.append(tool_name)
-            
-            return tools
-
-        def _generate_tool_code(self, requirement: str, search_results: List[Dict[str, Any]]) -> str:
-            """Generate Python code for a tool based on the requirement."""
-            example_code = ""
-            for result in search_results:
-                if requirement.lower() in result["title"].lower():
-                    example_code = f"# Example code based on: {result['title']}\n"
-                    example_code += f"# Source: {result['url']}\n"
-                    break
-            
-            tool_code = f"""
-{example_code}
-def {requirement.replace(' ', '_')}():
-    print("Executing {requirement}...")
-    # Add your implementation here
-if __name__ == "__main__":
-    {requirement.replace(' ', '_')}()
-"""
-            return tool_code.strip()
-
-        async def _execute_tools(self, tools: List[str]) -> Dict[str, Any]:
-            """Execute the built tools/agents."""
-            execution_results = {}
-            for tool in tools:
-                tool_path = self.tools_dir / tool
-                try:
-                    process = await asyncio.create_subprocess_exec(
-                        "python", str(tool_path),
-                        stdout=asyncio.subprocess.PIPE,
-                        stderr=asyncio.subprocess.PIPE
-                    )
-                    stdout, stderr = await process.communicate()
-                    
-                    execution_results[tool] = {
-                        "status": "success" if process.returncode == 0 else "failed",
-                        "stdout": stdout.decode(),
-                        "stderr": stderr.decode(),
-                    }
-                except Exception as e:
-                    execution_results[tool] = {
-                        "status": "error",
-                        "error": str(e),
-                    }
-            
-            return execution_results
-
-        async def generate_tool(self, command: str):
-            """Generate a tool based on the command."""
-            tool_name = command.split(" ")[-1]  # Extract tool name from command
-            tool_code = f"# Tool: {tool_name}\n\ndef {tool_name}():\n    pass\n"  # Placeholder code
-            tool_path = self.tools_dir / f"{tool_name}.py"
-            
-            with open(tool_path, "w") as f:
-                f.write(tool_code)
-            
-            logging.info(f"Generated tool: {tool_name}")
-
-        async def generate_agent(self, command: str):
-            """Generate an agent based on the command."""
-            agent_name = command.split(" ")[-1]  # Extract agent name from command
-            agent_code = f"# Agent: {agent_name}\n\ndef {agent_name}():\n    pass\n"  # Placeholder code
-            agent_path = self.agents_dir / f"{agent_name}.py"
-            
-            with open(agent_path, "w") as f:
-                f.write(agent_code)
-            
-            logging.info(f"Generated agent: {agent_name}")
-
-        def stop(self):
-            """Stop the autonomous agent."""
-            self.running = False
-            logging.info("Autonomous agent stopped.")
-
-    class ToolManager:
-        """Manages various tools used in the development pipeline."""
-        
-        def __init__(self):
-            self.tools = {
-                "requirements_analyzer": self._requirements_analyzer,
-                "task_breakdown": self._task_breakdown,
-                "code_generator": self._code_generator,
-                "code_quality_checker": self._code_quality_checker,
-                "test_generator": self._test_generator,
-                "test_runner": self._test_runner,
-                "coverage_analyzer": self._coverage_analyzer,
-            }
-        
-        async def execute_tool(self, tool_name: str, input_data: Any) -> Dict[str, Any]:
-            """Execute a tool with the given input data."""
-            if tool_name in self.tools:
-                return await self.tools[tool_name](input_data)
-            else:
-                raise ValueError(f"Tool '{tool_name}' not found.")
-        
-        async def _requirements_analyzer(self, requirements: str) -> Dict[str, Any]:
-            """Analyze requirements and return a structured result."""
-            # Placeholder implementation
-            return {"status": "success", "result": {"requirements": requirements}}
-        
-        async def _task_breakdown(self, requirements: Dict[str, Any]) -> Dict[str, Any]:
-            """Break down requirements into tasks."""
-            # Placeholder implementation
-            return {"status": "success", "result": ["task1", "task2", "task3"]}
-        
-        async def _code_generator(self, tasks: List[str]) -> Dict[str, Any]:
-            """Generate code based on tasks."""
-            # Placeholder implementation
-            return {"status": "success", "result": "generated_code"}
-        
-        async def _code_quality_checker(self, code: str) -> Dict[str, Any]:
-            """Check the quality of the generated code."""
-            # Placeholder implementation
-            return {"status": "success", "result": {"quality_score": 0.9}}
-        
-        async def _test_generator(self, code: str) -> Dict[str, Any]:
-            """Generate tests for the code."""
-            # Placeholder implementation
-            return {"status": "success", "result": ["test1", "test2", "test3"]}
-        
-        async def _test_runner(self, tests: List[str]) -> Dict[str, Any]:
-            """Run the generated tests."""
-            # Placeholder implementation
-            return {"status": "success", "result": {"passed": 3, "failed": 0}}
-        
-        async def _coverage_analyzer(self, test_results: Dict[str, Any]) -> Dict[str, Any]:
-            """Analyze test coverage."""
-            # Placeholder implementation
-            return {"status": "success", "result": {"coverage": 0.95}}
-
-    class DevelopmentPipeline:
-        """Advanced development pipeline with stage management and monitoring"""
-        
-        class PipelineStage(Enum):
-            PLANNING = "planning"
-            DEVELOPMENT = "development"
-            TESTING = "testing"
-            DEPLOYMENT = "deployment"
-            MAINTENANCE = "maintenance"
-            ROLLBACK = "rollback"
-
-        def __init__(self, workspace_manager, tool_manager):
-            self.workspace_manager = workspace_manager
-            self.tool_manager = tool_manager
-            self.current_stage = None
-            self.stage_history = []
-            self.active_processes = {}
-            self.stage_metrics = {}
-            self.logger = self._setup_logger()
-            
-        def _setup_logger(self) -> logging.Logger:
-            logger = logging.getLogger("DevelopmentPipeline")
-            logger.setLevel(logging.DEBUG)
-            handler = logging.StreamHandler()
-            formatter = logging.Formatter(
-                '%(asctime)s - %(name)s - %(levelname)s - %(message)s'
-            )
-            handler.setFormatter(formatter)
-            logger.addHandler(handler)
-            return logger
-
-        async def execute_stage(self, stage: PipelineStage, context: Dict[str, Any]) -> Dict[str, Any]:
-            """Execute a pipeline stage with monitoring and error handling"""
-            self.logger.info(f"Starting stage: {stage.value}")
-            start_time = time.time()
-            
-            try:
-                # Record stage start
-                self.current_stage = stage
-                self._record_stage_start(stage, context)
-                
-                # Execute stage-specific logic
-                result = await self._execute_stage_logic(stage, context)
-                
-                # Validate stage output
-                self._validate_stage_output(stage, result)
-                
-                # Update metrics
-                execution_time = time.time() - start_time
-                self._update_stage_metrics(stage, execution_time, result)
-                
-                # Record stage completion
-                self._record_stage_completion(stage, result)
-                
-                return {
-                    "status": "success",
-                    "stage": stage.value,
-                    "result": result,
-                    "execution_time": execution_time,
-                    "metrics": self.stage_metrics.get(stage, {})
-                }
-                
-            except Exception as e:
-                error_msg = f"Error in stage {stage.value}: {str(e)}"
-                self.logger.error(error_msg)
-                
-                # Handle stage failure
-                await self._handle_stage_failure(stage, context, e)
-                
-                return {
-                    "status": "error",
-                    "stage": stage.value,
-                    "error": error_msg,
-                    "execution_time": time.time() - start_time
-                }
-
-        async def _execute_stage_logic(self, stage: PipelineStage, context: Dict[str, Any]) -> Dict[str, Any]:
-            """Execute stage-specific logic with appropriate tools and enhanced error handling."""
-            """Execute stage-specific logic with appropriate tools"""
-            if stage == self.PipelineStage.PLANNING:
-                return await self._execute_planning_stage(context)
-            elif stage == self.PipelineStage.DEVELOPMENT:
-                return await self._execute_development_stage(context)
-            elif stage == self.PipelineStage.TESTING:
-                return await self._execute_testing_stage(context)
-            elif stage == self.PipelineStage.DEPLOYMENT:
-                return await self._execute_deployment_stage(context)
-            elif stage == self.PipelineStage.MAINTENANCE:
-                return await self._execute_maintenance_stage(context)
-            elif stage == self.PipelineStage.ROLLBACK:
-                return await self._execute_rollback_stage(context)
-            else:
-                raise ValueError(f"Unknown pipeline stage: {stage}")
-
-        async def _execute_planning_stage(self, context: Dict[str, Any]) -> Dict[str, Any]:
-            """Execute planning stage with requirement analysis and task breakdown"""
-            try:
-                # Analyze requirements
-                requirements = await self.tool_manager.execute_tool(
-                    "requirements_analyzer",
-                    context.get("requirements", "")
-                )
-                
-                # Generate task breakdown
-                tasks = await self.tool_manager.execute_tool(
-                    "task_breakdown",
-                    requirements["result"]
-                )
-                
-                # Create project structure
-                project_structure = await self.workspace_manager.create_project_structure(
-                    context["project_name"],
-                    tasks["result"]
-                )
-                
-                return {
-                    "requirements": requirements["result"],
-                    "tasks": tasks["result"],
-                    "project_structure": project_structure
-                }
-            except Exception as e:
-                raise Exception(f"Planning stage failed: {str(e)}")
-
-        async def _execute_development_stage(self, context: Dict[str, Any]) -> Dict[str, Any]:
-            """Execute development stage with code generation and quality checks"""
-            try:
-                # Generate code
-                code_generation = await self.tool_manager.execute_tool(
-                    "code_generator",
-                    context.get("tasks", [])
-                )
-                
-                # Run initial quality checks
-                quality_check = await self.tool_manager.execute_tool(
-                    "code_quality_checker",
-                    code_generation["result"]
-                )
-                
-                # Save generated code
-                saved_files = await self.workspace_manager.save_generated_code(
-                    context["project_name"],
-                    code_generation["result"]
-                )
-                
-                return {
-                    "generated_code": code_generation["result"],
-                    "quality_check": quality_check["result"],
-                    "saved_files": saved_files
-                }
-            except Exception as e:
-                raise Exception(f"Development stage failed: {str(e)}")
-
-        async def _execute_testing_stage(self, context: Dict[str, Any]) -> Dict[str, Any]:
-            """Execute testing stage with comprehensive test suite"""
-            try:
-                # Generate tests
-                test_generation = await self.tool_manager.execute_tool(
-                    "test_generator",
-                    context.get("generated_code", "")
-                )
-                
-                # Run tests
-                test_results = await self.tool_manager.execute_tool(
-                    "test_runner",
-                    test_generation["result"]
-                )
-                
-                # Generate coverage report
-                coverage_report = await self.tool_manager.execute_tool(
-                    "coverage_analyzer",
-                    test_results["result"]
-                )
-                
-                return {
-                    "test_cases": test_generation["result"],
-                    "test_results": test_results["result"],
-                    "coverage_report": coverage_report["result"]
-                }
-            except Exception as e:
-                raise Exception(f"Testing stage failed: {str(e)}")
-
-        def _validate_stage_output(self, stage: PipelineStage, result: Dict[str, Any]):
-            """Validate stage output against defined criteria"""
-            validation_rules = self._get_validation_rules(stage)
-            validation_errors = []
-            
-            for rule in validation_rules:
-                if not rule.validate(result):
-                    validation_errors.append(rule.get_error_message())
-            
-            if validation_errors:
-                raise ValueError(f"Stage validation failed: {'; '.join(validation_errors)}")
-
-        def _update_stage_metrics(self, stage: PipelineStage, execution_time: float, result: Dict[str, Any]):
-            """Update metrics for the stage"""
-            if stage not in self.stage_metrics:
-                self.stage_metrics[stage] = {
-                    "total_executions": 0,
-                    "successful_executions": 0,
-                    "failed_executions": 0,
-                    "average_execution_time": 0,
-                    "last_execution_time": None,
-                    "error_rate": 0
-                }
-            
-            metrics = self.stage_metrics[stage]
-            metrics["total_executions"] += 1
-            metrics["last_execution_time"] = execution_time
-            
-            if result.get("status") == "success":
-                metrics["successful_executions"] += 1
-            else:
-                metrics["failed_executions"] += 1
-            
-            metrics["error_rate"] = metrics["failed_executions"] / metrics["total_executions"]
-            metrics["average_execution_time"] = (
-                (metrics["average_execution_time"] * (metrics["total_executions"] - 1) + execution_time)
-                / metrics["total_executions"]
-            )
-
-        async def _handle_stage_failure(self, stage: PipelineStage, context: Dict[str, Any], error: Exception):
-            """Handle stage failure with rollback and recovery options"""
-            self.logger.error(f"Handling failure in stage {stage.value}: {str(error)}")
-            
-            # Record failure
-            self._record_stage_failure(stage, error)
-            
-            # Determine if rollback is needed
-            if self._should_rollback(stage, error):
-                await self._execute_rollback(stage, context)
-            
-            # Attempt recovery
-            await self._attempt_recovery(stage, context, error)
-
-        def _should_rollback(self, stage: PipelineStage, error: Exception) -> bool:
-            """Determine if a rollback is needed based on error severity"""
-            critical_errors = [
-                "DatabaseError",
-                "DeploymentError",
-                "SecurityViolation"
-            ]
-            return any(err in str(error) for err in critical_errors)
-
-        async def _execute_rollback(self, stage: PipelineStage, context: Dict[str, Any]):
-            """Execute rollback procedure for a failed stage"""
-            self.logger.info(f"Executing rollback for stage {stage.value}")
-            
-            try:
-                # Get rollback point
-                rollback_point = self._get_rollback_point(stage)
-                
-                # Execute rollback
-                await self.execute_stage(
-                    self.PipelineStage.ROLLBACK,
-                    {
-                        **context,
-                        "rollback_point": rollback_point,
-                        "failed_stage": stage
-                    }
-                )
-                
-            except Exception as e:
-                self.logger.error(f"Rollback failed: {str(e)}")
-                # Implement emergency shutdown if rollback fails
-                self._emergency_shutdown(stage, e)
-
-        def _emergency_shutdown(self, stage: PipelineStage, error: Exception):
-            """Handle emergency shutdown when rollback fails"""
-            self.logger.critical(f"Emergency shutdown initiated for stage {stage.value}")
-            # Implement emergency shutdown procedures
-            pass
-
-    class CodeMetricsAnalyzer:
-        """Analyzes code metrics using various tools"""
-        
-        def __init__(self):
-            self.metrics_history = []
-            
-        def analyze_code_quality(self, file_path: str) -> Dict[str, Any]:
-            """Analyzes code quality using multiple metrics"""
-            try:
-                # Pylint analysis
-                pylint_score = self._run_pylint(file_path)
-                
-                # Complexity analysis
-                complexity_score = self._analyze_complexity(file_path)
-                
-                # Test coverage analysis
-                coverage_score = self._analyze_test_coverage(file_path)
-                
-                # Security analysis
-                security_score = self._analyze_security(file_path)
-                
-                # Calculate overall quality score
-                quality_score = self._calculate_overall_score(
-                    pylint_score,
-                    complexity_score,
-                    coverage_score,
-                    security_score
-                )
-                
-                metrics = {
-                    "quality_score": quality_score,
-                    "pylint_score": pylint_score,
-                    "complexity_score": complexity_score,
-                    "coverage_score": coverage_score,
-                    "security_score": security_score,
-                    "timestamp": datetime.now()
-                }
-                
-                self.metrics_history.append(metrics)
-                return metrics
-                
-            except Exception as e:
-                logging.error(f"Error analyzing code metrics: {str(e)}")
-                return {
-                    "error": str(e),
-                    "quality_score": 0.0,
-                    "timestamp": datetime.now()
-                }
-
-        def _run_pylint(self, file_path: str) -> float:
-            """Runs pylint analysis"""
-            try:
-                reporter = JSONReporter()
-                Run([file_path], reporter=reporter, do_exit=False)
-                score = reporter.data.get('score', 0.0)
-                return float(score) / 10.0  # Normalize to 0-1 scale
-            except Exception as e:
-                logging.error(f"Pylint analysis error: {str(e)}")
-                return 0.0
-
-        def _analyze_complexity(self, file_path: str) -> float:
-            """Analyzes code complexity"""
-            try:
-                with open(file_path, 'r') as file:
-                    code = file.read()
-                
-                # Calculate cyclomatic complexity
-                complexity = radon.complexity.cc_visit(code)
-                avg_complexity = sum(item.complexity for item in complexity) / len(complexity) if complexity else 0
-                
-                # Normalize complexity score (0-1 scale, lower is better)
-                normalized_score = 1.0 - min(avg_complexity / 10.0, 1.0)
-                return normalized_score
-                
-            except Exception as e:
-                logging.error(f"Complexity analysis error: {str(e)}")
-                return 0.0
-
-        async def _analyze_current_state(self, project_name: str) -> Dict[str, Any]:
-            """Analyze current project state with detailed metrics."""
-            try:
-                self.logger.info(f"Analyzing current state for project: {project_name}")
-        
-                # Collect code metrics
-                code_metrics = await self._collect_code_metrics(project_name)
-                self.logger.info("Code metrics collected successfully.")
-        
-                # Analyze test coverage
-                test_coverage = await self._analyze_test_coverage(project_name)
-                self.logger.info("Test coverage analysis completed.")
-        
-                # Check security vulnerabilities
-                security_analysis = await self._analyze_security(project_name)
-                self.logger.info("Security analysis completed.")
-        
-                # Measure performance metrics
-                performance_metrics = await self._measure_performance(project_name)
-                self.logger.info("Performance metrics measured.")
-        
-                # Determine if requirements are met
-                meets_requirements = await self._check_requirements(
-                    code_metrics,
-                    test_coverage,
-                    security_analysis,
-                    performance_metrics
-                )
-                self.logger.info("Requirements check completed.")
-
-                return {
-                    "code_metrics": code_metrics,
-                    "test_coverage": test_coverage,
-                    "security_analysis": security_analysis,
-                    "performance_metrics": performance_metrics,
-                    "meets_requirements": meets_requirements,
-                    "timestamp": datetime.now()
-                }
-
-            except Exception as e:
-                self.logger.error(f"Error analyzing current state: {str(e)}")
-                raise
-        
-        def _analyze_security(self, file_path: str) -> float:
-            """Analyzes code security using bandit"""
-            try:
-                conf = manager.BanditManager()
-                conf.discover_files([file_path])
-                conf.run_tests()
-                
-                # Calculate security score based on findings
-                total_issues = len(conf.get_issue_list())
-                max_severity = max((issue.severity for issue in conf.get_issue_list()), default=0)
-                
-                # Normalize security score (0-1 scale, higher is better)
-                security_score = 1.0 - (total_issues * max_severity) / 10.0
-                return max(0.0, min(1.0, security_score))
-                
-            except Exception as e:
-                logging.error(f"Security analysis error: {str(e)}")
-                return 0.0
-
-        def _calculate_overall_score(self, pylint_score: float, complexity_score: float, 
-                                   coverage_score: float, security_score: float) -> float:
-            """Calculates overall code quality score"""
-            weights = {
-                'pylint': 0.3,
-                'complexity': 0.2,
-                'coverage': 0.25,
-                'security': 0.25
-            }
-            
-            overall_score = (
-                weights['pylint'] * pylint_score +
-                weights['complexity'] * complexity_score +
-                weights['coverage'] * coverage_score +
-                weights['security'] * security_score
-            )
-            
-            return max(0.0, min(1.0, overall_score))
-
-        def get_metrics_history(self) -> List[Dict[str, Any]]:
-            """Returns the history of metrics measurements"""
-            return self.metrics_history
-
-        def get_trend_analysis(self) -> Dict[str, Any]:
-            """Analyzes trends in metrics over time"""
-            if not self.metrics_history:
-                return {"status": "No metrics history available"}
-                
-            trends = {
-                "quality_score": self._calculate_trend([m["quality_score"] for m in self.metrics_history]),
-                "coverage_score": self._calculate_trend([m["coverage_score"] for m in self.metrics_history]),
-                "security_score": self._calculate_trend([m["security_score"] for m in self.metrics_history])
-            }
-            
-            return trends
-
-        def _calculate_trend(self, values: List[float]) -> Dict[str, Any]:
-            """Calculates trend statistics for a metric"""
-            if not values:
-                return {"trend": "unknown", "change": 0.0}
-                
-            recent_values = values[-3:]  # Look at last 3 measurements
-            if len(recent_values) < 2:
-                return {"trend": "insufficient data", "change": 0.0}
-                
-            change = recent_values[-1] - recent_values[0]
-            trend = "improving" if change > 0 else "declining" if change < 0 else "stable"
-            
-            return {
-                "trend": trend,
-                "change": change,
-                "current": recent_values[-1],
-                "previous": recent_values[0]
-            }
-
-    class CodeMetricsAnalyzer:
-        """Analyzes code metrics using various tools"""
-        
-        def __init__(self):
-            self.metrics_history = []
-            
-        def analyze_code_quality(self, file_path: str) -> Dict[str, Any]:
-            """Analyzes code quality using multiple metrics"""
-            try:
-                # Pylint analysis
-                pylint_score = self._run_pylint(file_path)
-                
-                # Complexity analysis
-                complexity_score = self._analyze_complexity(file_path)
-                
-                # Test coverage analysis
-                coverage_score = self._analyze_test_coverage(file_path)
-                
-                # Security analysis
-                security_score = self._analyze_security(file_path)
-                
-                # Calculate overall quality score
-                quality_score = self._calculate_overall_score(
-                    pylint_score,
-                    complexity_score,
-                    coverage_score,
-                    security_score
-                )
-                
-                metrics = {
-                    "quality_score": quality_score,
-                    "pylint_score": pylint_score,
-                    "complexity_score": complexity_score,
-                    "coverage_score": coverage_score,
-                    "security_score": security_score,
-                    "timestamp": datetime.now()
-                }
-                
-                self.metrics_history.append(metrics)
-                return metrics
-                
-            except Exception as e:
-                logging.error(f"Error analyzing code metrics: {str(e)}")
-                return {
-                    "error": str(e),
-                    "quality_score": 0.0,
-                    "timestamp": datetime.now()
-                }
-
-        def _run_pylint(self, file_path: str) -> float:
-            """Runs pylint analysis"""
-            try:
-                reporter = JSONReporter()
-                Run([file_path], reporter=reporter, do_exit=False)
-                score = reporter.data.get('score', 0.0)
-                return float(score) / 10.0  # Normalize to 0-1 scale
-            except Exception as e:
-                logging.error(f"Pylint analysis error: {str(e)}")
-                return 0.0
-
-        def _analyze_complexity(self, file_path: str) -> float:
-            """Analyzes code complexity"""
-            try:
-                with open(file_path, 'r') as file:
-                    code = file.read()
-                
-                # Calculate cyclomatic complexity
-                complexity = radon.complexity.cc_visit(code)
-                avg_complexity = sum(item.complexity for item in complexity) / len(complexity) if complexity else 0
-                
-                # Normalize complexity score (0-1 scale, lower is better)
-                normalized_score = 1.0 - min(avg_complexity / 10.0, 1.0)
-                return normalized_score
-                
-            except Exception as e:
-                logging.error(f"Complexity analysis error: {str(e)}")
-                return 0.0
-
-        async def _analyze_current_state(self, project_name: str) -> Dict[str, Any]:
-            """Analyze current project state with detailed metrics."""
-            try:
-                self.logger.info(f"Analyzing current state for project: {project_name}")
-        
-                # Collect code metrics
-                code_metrics = await self._collect_code_metrics(project_name)
-                self.logger.info("Code metrics collected successfully.")
-        
-                # Analyze test coverage
-                test_coverage = await self._analyze_test_coverage(project_name)
-                self.logger.info("Test coverage analysis completed.")
-        
-                # Check security vulnerabilities
-                security_analysis = await self._analyze_security(project_name)
-                self.logger.info("Security analysis completed.")
-        
-                # Measure performance metrics
-                performance_metrics = await self._measure_performance(project_name)
-                self.logger.info("Performance metrics measured.")
-        
-                # Determine if requirements are met
-                meets_requirements = await self._check_requirements(
-                    code_metrics,
-                    test_coverage,
-                    security_analysis,
-                    performance_metrics
-                )
-                self.logger.info("Requirements check completed.")
-
-                return {
-                    "code_metrics": code_metrics,
-                    "test_coverage": test_coverage,
-                    "security_analysis": security_analysis,
-                    "performance_metrics": performance_metrics,
-                    "meets_requirements": meets_requirements,
-                    "timestamp": datetime.now()
-                }
-
-            except Exception as e:
-                self.logger.error(f"Error analyzing current state: {str(e)}")
-                raise
-        
-        def _analyze_security(self, file_path: str) -> float:
-            """Analyzes code security using bandit"""
-            try:
-                conf = manager.BanditManager()
-                conf.discover_files([file_path])
-                conf.run_tests()
-                
-                # Calculate security score based on findings
-                total_issues = len(conf.get_issue_list())
-                max_severity = max((issue.severity for issue in conf.get_issue_list()), default=0)
-                
-                # Normalize security score (0-1 scale, higher is better)
-                security_score = 1.0 - (total_issues * max_severity) / 10.0
-                return max(0.0, min(1.0, security_score))
-                
-            except Exception as e:
-                logging.error(f"Security analysis error: {str(e)}")
-                return 0.0
-
-        def _calculate_overall_score(self, pylint_score: float, complexity_score: float,
-                                   coverage_score: float, security_score: float) -> float:
-            """Calculates overall code quality score"""
-            weights = {
-                'pylint': 0.3,
-                'complexity': 0.2,
-                'coverage': 0.25,
-                'security': 0.25
-            }
-            
-            overall_score = (
-                weights['pylint'] * pylint_score +
-                weights['complexity'] * complexity_score +
-                weights['coverage'] * coverage_score +
-                weights['security'] * security_score
-            )
-            
-            return max(0.0, min(1.0, overall_score))
-
-        def get_metrics_history(self) -> List[Dict[str, Any]]:
-            """Returns the history of metrics measurements"""
-            return self.metrics_history
-
-        def get_trend_analysis(self) -> Dict[str, Any]:
-            """Analyzes trends in metrics over time"""
-            if not self.metrics_history:
-                return {"status": "No metrics history available"}
-                
-            trends = {
-                "quality_score": self._calculate_trend([m["quality_score"] for m in self.metrics_history]),
-                "coverage_score": self._calculate_trend([m["coverage_score"] for m in self.metrics_history]),
-                "security_score": self._calculate_trend([m["security_score"] for m in self.metrics_history])
-            }
-            
-            return trends
-
-        def _calculate_trend(self, values: List[float]) -> Dict[str, Any]:
-            """Calculates trend statistics for a metric"""
-            if not values:
-                return {"trend": "unknown", "change": 0.0}
-                
-            recent_values = values[-3:]  # Look at last 3 measurements
-            if len(recent_values) < 2:
-                return {"trend": "insufficient data", "change": 0.0}
-                
-            change = recent_values[-1] - recent_values[0]
-            trend = "improving" if change > 0 else "declining" if change < 0 else "stable"
-            
-            return {
-                "trend": trend,
-                "change": change,
-                "current": recent_values[-1],
-                "previous": recent_values[0]
-            }
-
-    @dataclass
-    class QualityMetrics:
-        """Advanced quality metrics tracking and analysis"""
-        code_quality_score: float = 0.0
-        test_coverage: float = 0.0
-        security_score: str = "unknown"
-        performance_score: float = 0.0
-        metrics_analyzer: CodeMetricsAnalyzer = None
-        
-        def __post_init__(self):
-            self.metrics_analyzer = CodeMetricsAnalyzer()
-            self.history = []
-            self.thresholds = {
-                "code_quality": 0.85,
-                "test_coverage": 0.90,
-                "security": 0.85,
-                "performance": 0.80
-            }
-        
-        def analyze_code(self, project_name: str) -> Dict[str, Any]:
-            """Comprehensive code analysis"""
-            try:
-                # Get all Python files in the project
-                project_files = self._get_project_files(project_name)
-                
-                aggregated_metrics = {
-                    "code_quality": 0.0,
-                    "test_coverage": 0.0,
-                    "security": 0.0,
-                    "performance": 0.0,
-                    "files_analyzed": len(project_files),
-                    "detailed_metrics": []
-                }
-                
-                for file_path in project_files:
-                    metrics = self.metrics_analyzer.analyze_code_quality(file_path)
-                    aggregated_metrics["detailed_metrics"].append({
-                        "file": file_path,
-                        "metrics": metrics
-                    })
-                    
-                    # Update aggregated scores
-                    aggregated_metrics["code_quality"] += metrics["quality_score"]
-                    aggregated_metrics["test_coverage"] += metrics["coverage_score"]
-                    aggregated_metrics["security"] += metrics["security_score"]
-                    
-                # Calculate averages
-                if project_files:
-                    for key in ["code_quality", "test_coverage", "security"]:
-                        aggregated_metrics[key] /= len(project_files)
-                
-                # Update instance variables
-                self.code_quality_score = aggregated_metrics["code_quality"]
-                self.test_coverage = aggregated_metrics["test_coverage"]
-                self.security_score = str(aggregated_metrics["security"])
-                
-                # Add to history
-                self.history.append({
-                    "timestamp": datetime.now(),
-                    "metrics": aggregated_metrics
-                })
-                
-                return aggregated_metrics
-                
-            except Exception as e:
-                logging.error(f"Error in code analysis: {str(e)}")
-                return {
-                    "error": str(e),
-                    "code_quality": 0.0,
-                    "test_coverage": 0.0,
-                    "security": "error",
-                    "performance": 0.0
-                }
-
-        def _get_project_files(self, project_name: str) -> List[str]:
-            """Get all Python files in the project"""
-            project_dir = os.path.join(os.getcwd(), project_name)
-            python_files = []
-            
-            for root, _, files in os.walk(project_dir):
-                for file in files:
-                    if file.endswith('.py'):
-                        python_files.append(os.path.join(root, file))
-            
-            return python_files
-
-        def get_improvement_suggestions(self) -> List[str]:
-            """Generate improvement suggestions based on metrics"""
-            suggestions = []
-            latest_metrics = self.history[-1]["metrics"] if self.history else None
-            
-            if not latest_metrics:
-                return ["No metrics available for analysis"]
-            
-            if latest_metrics["code_quality"] < self.thresholds["code_quality"]:
-                suggestions.append(
-                    f"Code quality score ({latest_metrics['code_quality']:.2f}) is below threshold "
-                    f"({self.thresholds['code_quality']}). Consider refactoring complex methods."
-                )
-            
-            if latest_metrics["test_coverage"] < self.thresholds["test_coverage"]:
-                suggestions.append(
-                    f"Test coverage ({latest_metrics['test_coverage']:.2f}) is below threshold "
-                    f"({self.thresholds['test_coverage']}). Add more unit tests."
-                )
-            
-            if float(latest_metrics["security"]) < self.thresholds["security"]:
-                suggestions.append(
-                    f"Security score ({latest_metrics['security']}) is below threshold "
-                    f"({self.thresholds['security']}). Address security vulnerabilities."
-                )
-            
-            return suggestions
-
-    class ErrorTracker:
-        """Enhanced error tracking and analysis"""
-        def __init__(self):
-            self.errors: List[Dict[str, Any]] = []
-            self.error_patterns: Dict[str, int] = {}
-            self.critical_errors: List[Dict[str, Any]] = []
-        
-        def add_error(self, error_type: str, message: str, severity: str = "normal"):
-            """Add an error with enhanced tracking"""
-            error_entry = {
-                "type": error_type,
-                "message": message,
-                "severity": severity,
-                "timestamp": datetime.now(),
-                "stack_trace": traceback.format_exc()
-            }
-            
-            self.errors.append(error_entry)
-            
-            # Track error patterns
-            if error_type in self.error_patterns:
-                self.error_patterns[error_type] += 1
-            else:
-                self.error_patterns[error_type] = 1
-            
-            # Track critical errors
-            if severity == "critical":
-                self.critical_errors.append(error_entry)
-                self._notify_critical_error(error_entry)
-        
-        def _notify_critical_error(self, error: Dict[str, Any]):
-            """Handle critical error notification"""
-            logging.critical(f"Critical error detected: {error['message']}")
-            # Implement notification system here (e.g., email, Slack)
-        
-        def get_error_analysis(self) -> Dict[str, Any]:
-            """Generate comprehensive error analysis"""
-            return {
-                "total_errors": len(self.errors),
-                "error_patterns": self.error_patterns,
-                "critical_errors": len(self.critical_errors),
-                "most_common_error": max(self.error_patterns.items(), key=lambda x: x[1]) if self.error_patterns else None,
-                "error_trend": self._analyze_error_trend()
-            }
-        
-        def _analyze_error_trend(self) -> Dict[str, Any]:
-            """Analyze error trends over time"""
-            if not self.errors:
-                return {"trend": "no errors"}
-            
-            # Group errors by hour
-            error_timeline = {}
-            for error in self.errors:
-                hour = error["timestamp"].replace(minute=0, second=0, microsecond=0)
-                if hour in error_timeline:
-                    error_timeline[hour] += 1
-                else:
-                    error_timeline[hour] = 1
-            
-            # Calculate trend
-            timeline_values = list(error_timeline.values())
-            if len(timeline_values) < 2:
-                return {"trend": "insufficient data"}
-            
-            trend = "increasing" if timeline_values[-1] > timeline_values[0] else "decreasing"
-            return {
-                "trend": trend,
-                "current_rate": timeline_values[-1],
-                "initial_rate": timeline_values[0]
-            }
-
-    class ProjectAnalytics:
-        """Enhanced project analytics and reporting"""
-        """Enhanced project analytics and reporting"""
-        def __init__(self, workspace_manager):
-            self.workspace_manager = workspace_manager
-            self.metrics_analyzer = CodeMetricsAnalyzer()
-            self.analysis_history = []
-        
-        def generate_project_report(self, project_name: str) -> Dict[str, Any]:
-            """Generate comprehensive project report"""
-            try:
-                current_analysis = {
-                    "timestamp": datetime.now(),
-                    "basic_metrics": self._get_basic_metrics(project_name),
-                    "code_quality": self._get_code_quality_metrics(project_name),
-                    "performance": self._get_performance_metrics(project_name),
-                    "security": self._get_security_metrics(project_name),
-                    "dependencies": self._analyze_dependencies(project_name)
-                }
-                
-                self.analysis_history.append(current_analysis)
-                
-                return {
-                    "current_analysis": current_analysis,
-                    "historical_trends": self._analyze_trends(),
-                    "recommendations": self._generate_recommendations(current_analysis)
-                }
-            
-            except Exception as e:
-                logging.error(f"Error generating project report: {str(e)}")
-                return {"error": str(e)}
-
-    class StreamlitInterface:
-        """Streamlit UI integration for the Autonomous Agent system."""
-
-        def __init__(self, app: AutonomousAgentApp):
-            self.app = app
-
-        def render_main_interface(self):
-            """Render the main Streamlit interface."""
-            st.title("Autonomous Agent System")
-            
-            # Create tabs for different functionalities
-            tab_names = ["Autonomous Agent", "Workspace Management", "Settings"]
-            selected_tab = st.selectbox("Select a Tab", tab_names)
-
-            if selected_tab == "Autonomous Agent":
-                self.render_autonomous_agent_tab()
-            elif selected_tab == "Workspace Management":
-                self.render_workspace_management_tab()
-            elif selected_tab == "Settings":
-                self.render_settings_tab()
-
-        def render_autonomous_agent_tab(self):
-            """Render the Autonomous Agent tab."""
-            st.header("Autonomous Agent")
-            task = st.text_area("Enter a task for the autonomous agent:")
-            
-            if st.button("Run Autonomous Agent"):
-                if task:
-                    # Run the autonomous agent with the provided task
-                    try:
-                        result = asyncio.run(self.app.refinement_loop.run_refinement_cycle(task))
-                        st.success(f"Result: {result}")
-                    except Exception as e:
-                        st.error(f"An error occurred: {str(e)}")
-
-        def render_workspace_management_tab(self):
-            """Render the Workspace Management tab with a workspace explorer."""
-            st.header("Workspace Management")
-            
-            # Workspace Explorer
-            st.subheader("Workspace Explorer")
-            workspace_tree = self.app.workspace_manager.get_workspace_tree()
-            self._render_tree(workspace_tree)
-
-            # File creation
-            st.subheader("Create a File")
-            new_filename = st.text_input("Enter filename:")
-            new_file_content = st.text_area("Enter file content:")
-            if st.button("Create File"):
-                if new_filename and new_file_content:
-                    result = self.app.workspace_manager.create_file(new_filename, new_file_content)
-                    st.success(result)
-                else:
-                    st.error("Filename and content are required.")
-
-            # File deletion
-            st.subheader("Delete a File")
-            delete_filename = st.text_input("Enter filename to delete:")
-            if st.button("Delete File"):
-                if delete_filename:
-                    result = self.app.workspace_manager.delete_file(delete_filename)
-                    st.success(result)
-                else:
-                    st.error("Filename is required.")
-
-        def _render_tree(self, tree: Dict[str, Any], level: int = 0):
-            """Recursively render the workspace directory tree."""
-            if tree["type"] == "file":
-                st.write("  " * level + f"📄 {tree['name']}")
-            elif tree["type"] == "directory":
-                st.write("  " * level + f"📁 {tree['name']}")
-                for child in tree["children"]:
-                    self._render_tree(child, level + 1)
-
-        def render_settings_tab(self):
-            """Render the Settings tab."""
-            st.header("Application Settings")
-            
-            # Section 1: Refinement Process Configuration
-            st.subheader("Refinement Process Settings")
-            
-            # Adjust maximum refinement iterations
-            current_max_iter = self.app.refinement_loop.max_iterations
-            new_max_iter = st.number_input(
-                "Maximum Refinement Iterations",
-                min_value=1,
-                max_value=20,
-                value=current_max_iter,
-                help="Maximum number of refinement cycles to perform"
-            )
-            if new_max_iter != current_max_iter:
-                self.app.refinement_loop.max_iterations = new_max_iter
-                st.success(f"Updated maximum iterations to {new_max_iter}")
-
-            # Section 2: Quality Threshold Configuration
-            st.subheader("Quality Thresholds")
-            
-            # Get current thresholds
-            thresholds = self.app.refinement_loop.quality_metrics.thresholds
-            
-            col1, col2, col3 = st.columns(3)
-            with col1:
-                new_code_quality = st.slider(
-                    "Code Quality Threshold",
-                    0.0, 1.0, thresholds["code_quality"],
-                    help="Minimum acceptable code quality score"
-                )
-            with col2:
-                new_test_coverage = st.slider(
-                    "Test Coverage Threshold", 
-                    0.0, 1.0, thresholds["test_coverage"],
-                    help="Minimum required test coverage"
-                )
-            with col3:
-                new_security = st.slider(
-                    "Security Threshold",
-                    0.0, 1.0, thresholds["security"],
-                    help="Minimum acceptable security score"
-                )
-            
-            if st.button("Update Quality Thresholds"):
-                self.app.refinement_loop.quality_metrics.thresholds.update({
-                    "code_quality": new_code_quality,
-                    "test_coverage": new_test_coverage,
-                    "security": new_security
-                })
-                st.success("Quality thresholds updated!")
-            
-            # Section 3: Performance Configuration
-            st.subheader("Performance Settings")
-            
-            # Concurrency settings
-            concurrency_level = st.selectbox(
-                "Max Concurrency",
-                options=[1, 2, 4, 8],
-                index=2,
-                help="Maximum parallel tasks for code analysis"
-            )
-            
-            # Resource limits
-            mem_limit = st.slider(
-                "Memory Limit (GB)",
-                1, 16, 4,
-                help="Maximum memory allocation for pipeline operations"
-            )
-            
-            # Section 4: Security Settings
-            st.subheader("Security Configuration")
-            
-            # Security rules toggle
-            enable_security_scan = st.checkbox(
-                "Enable Real-time Security Scanning",
-                value=True,
-                help="Perform continuous security analysis during development"
-            )
-            
-            # Severity level filtering
-            security_level = st.selectbox(
-                "Minimum Security Severity Level",
-                ["Low", "Medium", "High", "Critical"],
-                index=1,
-                help="Minimum severity level to trigger security alerts"
-            )
-            
-            # Section 5: Workspace Configuration
-            st.subheader("Workspace Settings")
-            current_workspace = self.app.workspace_manager.workspace_dir
-            st.write(f"Current Workspace: `{current_workspace}`")
-            
-            # Workspace actions
-            if st.button("Clear Workspace Cache"):
-                self.app.workspace_manager.clean_cache()
-                st.success("Workspace cache cleared!")
-            
-            # Section 6: Diagnostic Settings
-            st.subheader("Diagnostics")
-            
-            # Logging controls
-            log_level = st.selectbox(
-                "Logging Level",
-                ["DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"],
-                index=1
-            )
-            logging.getLogger().setLevel(log_level)
-            
-            # Debug mode toggle
-            debug_mode = st.checkbox("Enable Debug Mode")
-            if debug_mode:
-                self.app.refinement_loop.logger.setLevel(logging.DEBUG)
-            else:
-                self.app.refinement_loop.logger.setLevel(logging.INFO)
-            
-            # Section 7: System Information
-            st.subheader("System Info")
-            st.write(f"Python Version: {sys.version}")
-            st.write(f"Platform: {platform.platform()}")
-            st.write(f"Available Memory: {psutil.virtual_memory().available / (1024**3):.1f} GB free")
+from definitions import AutonomousAgentApp
 
 def main():
     app = AutonomousAgentApp()

def.py

@@ -0,0 +1,1262 @@
+import platform
+import psutil
+from typing import List, Dict, Optional, Any, Tuple
+from dataclasses import dataclass
+from enum import Enum
+import logging
+import time
+import ast
+import pylint.lint
+import radon.complexity
+import radon.metrics
+from pylint.lint import Run
+from pylint.reporters import JSONReporter
+from coverage import Coverage
+import bandit
+from bandit.core import manager
+from datetime import datetime
+import os
+import sys
+import requests
+import asyncio
+import statistics
+import json
+import traceback
+from typing import Dict, Any
+from datetime import datetime
+from pathlib import Path
+
+
+class AutonomousAgentApp:
+    """Main application class for the Autonomous Agent System"""
+
+    def __init__(self):
+        self.workspace_manager = self.WorkspaceManager(workspace_dir='workspace')  # Use self.WorkspaceManager
+        self.pipeline = self._initialize_pipeline()
+        self.refinement_loop = self.RefinementLoop(pipeline=self.pipeline)  # Use self.RefinementLoop
+        self.interface = self.StreamlitInterface(self)  # Use self.StreamlitInterface
+
+    def _initialize_pipeline(self) -> 'AutonomousAgentApp.DevelopmentPipeline':
+        """Initialize the development pipeline"""
+        return self.DevelopmentPipeline(
+            workspace_manager=self.workspace_manager,
+            tool_manager=self._setup_tool_manager()
+        )
+
+    def _setup_tool_manager(self):
+        """Setup tool manager with configuration"""
+        return self.ToolManager()  # Use self.ToolManager
+
+    def run(self):
+        """Main application entry point"""
+        try:
+            logging.info("Starting Autonomous Agent Application")
+            self.interface.render_main_interface()
+        except Exception as e:
+            logging.error(f"Application error: {str(e)}")
+            st.error("An error occurred while starting the application. Please check the logs.")
+            raise
+
+    class WorkspaceManager:
+        """Manages workspace files and directories."""
+
+        def __init__(self, workspace_dir: str = "workspace"):
+            self.workspace_dir = workspace_dir
+            self._ensure_workspace_exists()
+
+        def _ensure_workspace_exists(self):
+            """Ensure the workspace directory exists."""
+            os.makedirs(self.workspace_dir, exist_ok=True)
+
+        def create_file(self, filename: str, content: str) -> str:
+            """Create a file in the workspace with the given content."""
+            file_path = os.path.join(self.workspace_dir, filename)
+            with open(file_path, "w") as f:
+                f.write(content)
+            return f"File '{filename}' created at '{file_path}'."
+
+        def delete_file(self, filename: str) -> str:
+            """Delete a file from the workspace."""
+            file_path = os.path.join(self.workspace_dir, filename)
+            if os.path.exists(file_path):
+                os.remove(file_path)
+                return f"File '{filename}' deleted."
+            return f"File '{filename}' not found."
+
+        def list_files(self) -> List[str]:
+            """List all files in the workspace."""
+            return [
+                os.path.join(root, file)
+                for root, _, files in os.walk(self.workspace_dir)
+                for file in files
+            ]
+
+        def read_file(self, filename: str) -> str:
+            """Read the content of a file in the workspace."""
+            file_path = os.path.join(self.workspace_dir, filename)
+            if os.path.exists(file_path):
+                with open(file_path, "r") as f:
+                    return f.read()
+            return f"File '{filename}' not found."
+
+        def get_workspace_tree(self) -> Dict[str, Any]:
+            """Get the workspace directory structure as a nested dictionary."""
+            workspace_path = Path(self.workspace_dir)
+            return self._build_tree(workspace_path)
+
+        def _build_tree(self, path: Path) -> Dict[str, Any]:
+            """Recursively build a directory tree."""
+            if path.is_file():
+                return {"type": "file", "name": path.name}
+            elif path.is_dir():
+                return {
+                    "type": "directory",
+                    "name": path.name,
+                    "children": [self._build_tree(child) for child in path.iterdir()],
+                }
+
+    class AutonomousAgent:
+        """Autonomous agent that builds tools and agents based on tasks."""
+
+        def __init__(self, workspace_manager: 'AutonomousAgentApp.WorkspaceManager'):  # Use fully qualified name
+            self.workspace_manager = workspace_manager
+            self.tools_dir = Path(self.workspace_manager.workspace_dir) / "tools"
+            self.agents_dir = Path(self.workspace_manager.workspace_dir) / "agents"
+            self.tools_dir.mkdir(exist_ok=True)  # Ensure the tools directory exists
+            self.agents_dir.mkdir(exist_ok=True)  # Ensure the agents directory exists
+            self.running = True  # Flag to control the running state
+
+        async def run(self):
+            """Run the autonomous agent, continuously processing tasks."""
+            while self.running:
+                # Default task execution
+                await self.default_task()
+                await asyncio.sleep(1)  # Prevent busy waiting
+
+        async def default_task(self):
+            """Perform the default task of analyzing and generating tools/agents."""
+            logging.info("Running default task...")
+            # Simulate task processing
+            await asyncio.sleep(2)  # Simulate time taken for the task
+
+        async def pause(self):
+            """Pause the current operation to accept user input."""
+            self.running = False
+            logging.info("Paused. Waiting for user input...")
+
+        async def accept_user_input(self, user_input: str):
+            """Process user input and execute commands."""
+            logging.info(f"User input received: {user_input}")
+            commands = self.extract_commands(user_input)
+
+            for command in commands:
+                if command.startswith("generate tool"):
+                    await self.generate_tool(command)
+                elif command.startswith("generate agent"):
+                    await self.generate_agent(command)
+                # Add more command handling as needed
+
+        def extract_commands(self, user_input: str) -> List[str]:
+            """Extract commands from user input."""
+            # Simple command extraction logic (can be improved with NLP)
+            return user_input.split(';')  # Assume commands are separated by semicolons
+
+        async def run_refinement_cycle(self, task: str) -> Dict[str, Any]:
+            """Run a refinement cycle for the given task."""
+            # Step 1: Analyze the task
+            task_analysis = await self._analyze_task(task)
+
+            # Step 2: Search for relevant approaches/methods
+            search_results = await self._web_search(task)
+
+            # Step 3: Build tools/agents based on the task
+            tools_built = await self._build_tools(task_analysis, search_results)
+
+            # Step 4: Execute the tools/agents
+            execution_results = await self._execute_tools(tools_built)
+
+            return {
+                "task_analysis": task_analysis,
+                "search_results": search_results,
+                "tools_built": tools_built,
+                "execution_results": execution_results,
+            }
+
+        async def _analyze_task(self, task: str) -> Dict[str, Any]:
+            """Analyze the task to determine requirements."""
+            keywords = self._extract_keywords(task)
+            requirements = self._generate_requirements(keywords)
+
+            return {
+                "task": task,
+                "keywords": keywords,
+                "requirements": requirements,
+            }
+
+        def _extract_keywords(self, text: str) -> List[str]:
+            """Extract keywords from the task text."""
+            stop_words = {"the", "and", "of", "to", "in", "a", "is", "for", "on", "with"}
+            words = [word.lower() for word in text.split() if word.lower() not in stop_words]
+            return list(set(words))  # Remove duplicates
+
+        def _generate_requirements(self, keywords: List[str]) -> List[str]:
+            """Generate requirements based on extracted keywords."""
+            requirement_map = {
+                "data": ["data collection", "data processing", "data visualization"],
+                "web": ["web scraping", "API integration", "web development"],
+                "ai": ["machine learning", "natural language processing", "computer vision"],
+                "automation": ["task automation", "workflow optimization", "scripting"],
+            }
+
+            requirements = []
+            for keyword in keywords:
+                if keyword in requirement_map:
+                    requirements.extend(requirement_map[keyword])
+
+            return requirements
+
+        async def _web_search(self, query: str) -> List[Dict[str, Any]]:
+            """Perform a web search for relevant approaches/methods."""
+            try:
+                response = requests.get(
+                    "https://api.example.com/search",
+                    params={"q": query, "limit": 5}
+                )
+                response.raise_for_status()
+                return response.json().get("results", [])
+            except Exception as e:
+                logging.error(f"Web search failed: {e}")
+                return [{"title": "Example Approach", "url": "https://example.com"}]
+
+        async def _build_tools(self, task_analysis: Dict[str, Any], search_results: List[Dict[str, Any]]) -> List[str]:
+            """Build tools/agents based on the task and search results."""
+            tools = []
+            for requirement in task_analysis["requirements"]:
+                tool_name = f"tool_for_{requirement.replace(' ', '_')}.py"
+                tool_path = self.tools_dir / tool_name
+
+                # Generate a simple Python script for the tool
+                tool_code = self._generate_tool_code(requirement, search_results)
+                with open(tool_path, "w") as f:
+                    f.write(tool_code)
+
+                tools.append(tool_name)
+
+            return tools
+
+        def _generate_tool_code(self, requirement: str, search_results: List[Dict[str, Any]]) -> str:
+            """Generate Python code for a tool based on the requirement."""
+            example_code = ""
+            for result in search_results:
+                if requirement.lower() in result["title"].lower():
+                    example_code = f"# Example code based on: {result['title']}\n"
+                    example_code += f"# Source: {result['url']}\n"
+                    break
+
+            tool_code = f"""
+{example_code}
+def {requirement.replace(' ', '_')}():
+    print("Executing {requirement}...")
+    # Add your implementation here
+if __name__ == "__main__":
+    {requirement.replace(' ', '_')}()
+"""
+            return tool_code.strip()
+
+        async def _execute_tools(self, tools: List[str]) -> Dict[str, Any]:
+            """Execute the built tools/agents."""
+            execution_results = {}
+            for tool in tools:
+                tool_path = self.tools_dir / tool
+                try:
+                    process = await asyncio.create_subprocess_exec(
+                        "python", str(tool_path),
+                        stdout=asyncio.subprocess.PIPE,
+                        stderr=asyncio.subprocess.PIPE
+                    )
+                    stdout, stderr = await process.communicate()
+
+                    execution_results[tool] = {
+                        "status": "success" if process.returncode == 0 else "failed",
+                        "stdout": stdout.decode(),
+                        "stderr": stderr.decode(),
+                    }
+                except Exception as e:
+                    execution_results[tool] = {
+                        "status": "error",
+                        "error": str(e),
+                    }
+
+            return execution_results
+
+        async def generate_tool(self, command: str):
+            """Generate a tool based on the command."""
+            tool_name = command.split(" ")[-1]  # Extract tool name from command
+            tool_code = f"# Tool: {tool_name}\n\ndef {tool_name}():\n    pass\n"  # Placeholder code
+            tool_path = self.tools_dir / f"{tool_name}.py"
+
+            with open(tool_path, "w") as f:
+                f.write(tool_code)
+
+            logging.info(f"Generated tool: {tool_name}")
+
+        async def generate_agent(self, command: str):
+            """Generate an agent based on the command."""
+            agent_name = command.split(" ")[-1]  # Extract agent name from command
+            agent_code = f"# Agent: {agent_name}\n\ndef {agent_name}():\n    pass\n"  # Placeholder code
+            agent_path = self.agents_dir / f"{agent_name}.py"
+
+            with open(agent_path, "w") as f:
+                f.write(agent_code)
+
+            logging.info(f"Generated agent: {agent_name}")
+
+        def stop(self):
+            """Stop the autonomous agent."""
+            self.running = False
+            logging.info("Autonomous agent stopped.")
+
+    class ToolManager:
+        """Manages various tools used in the development pipeline."""
+
+        def __init__(self):
+            self.tools = {
+                "requirements_analyzer": self._requirements_analyzer,
+                "task_breakdown": self._task_breakdown,
+                "code_generator": self._code_generator,
+                "code_quality_checker": self._code_quality_checker,
+                "test_generator": self._test_generator,
+                "test_runner": self._test_runner,
+                "coverage_analyzer": self._coverage_analyzer,
+            }
+
+        async def execute_tool(self, tool_name: str, input_data: Any) -> Dict[str, Any]:
+            """Execute a tool with the given input data."""
+            if tool_name in self.tools:
+                return await self.tools[tool_name](input_data)
+            else:
+                raise ValueError(f"Tool '{tool_name}' not found.")
+
+        async def _requirements_analyzer(self, requirements: str) -> Dict[str, Any]:
+            """Analyze requirements and return a structured result."""
+            # Placeholder implementation
+            return {"status": "success", "result": {"requirements": requirements}}
+
+        async def _task_breakdown(self, requirements: Dict[str, Any]) -> Dict[str, Any]:
+            """Break down requirements into tasks."""
+            # Placeholder implementation
+            return {"status": "success", "result": ["task1", "task2", "task3"]}
+
+        async def _code_generator(self, tasks: List[str]) -> Dict[str, Any]:
+            """Generate code based on tasks."""
+            # Placeholder implementation
+            return {"status": "success", "result": "generated_code"}
+
+        async def _code_quality_checker(self, code: str) -> Dict[str, Any]:
+            """Check the quality of the generated code."""
+            # Placeholder implementation
+            return {"status": "success", "result": {"quality_score": 0.9}}
+
+        async def _test_generator(self, code: str) -> Dict[str, Any]:
+            """Generate tests for the code."""
+            # Placeholder implementation
+            return {"status": "success", "result": ["test1", "test2", "test3"]}
+
+        async def _test_runner(self, tests: List[str]) -> Dict[str, Any]:
+            """Run the generated tests."""
+            # Placeholder implementation
+            return {"status": "success", "result": {"passed": 3, "failed": 0}}
+
+        async def _coverage_analyzer(self, test_results: Dict[str, Any]) -> Dict[str, Any]:
+            """Analyze test coverage."""
+            # Placeholder implementation
+            return {"status": "success", "result": {"coverage": 0.95}}
+
+    class DevelopmentPipeline:
+        """Advanced development pipeline with stage management and monitoring"""
+
+        class PipelineStage(Enum):
+            PLANNING = "planning"
+            DEVELOPMENT = "development"
+            TESTING = "testing"
+            DEPLOYMENT = "deployment"
+            MAINTENANCE = "maintenance"
+            ROLLBACK = "rollback"
+
+        def __init__(self, workspace_manager, tool_manager):
+            self.workspace_manager = workspace_manager
+            self.tool_manager = tool_manager
+            self.current_stage = None
+            self.stage_history = []
+            self.active_processes = {}
+            self.stage_metrics = {}
+            self.logger = self._setup_logger()
+
+        def _setup_logger(self) -> logging.Logger:
+            logger = logging.getLogger("DevelopmentPipeline")
+            logger.setLevel(logging.DEBUG)
+            handler = logging.StreamHandler()
+            formatter = logging.Formatter(
+                '%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+            )
+            handler.setFormatter(formatter)
+            logger.addHandler(handler)
+            return logger
+
+        async def execute_stage(self, stage: PipelineStage, context: Dict[str, Any]) -> Dict[str, Any]:
+            """Execute a pipeline stage with monitoring and error handling"""
+            self.logger.info(f"Starting stage: {stage.value}")
+            start_time = time.time()
+
+            try:
+                # Record stage start
+                self.current_stage = stage
+                self._record_stage_start(stage, context)
+
+                # Execute stage-specific logic
+                result = await self._execute_stage_logic(stage, context)
+
+                # Validate stage output
+                self._validate_stage_output(stage, result)
+
+                # Update metrics
+                execution_time = time.time() - start_time
+                self._update_stage_metrics(stage, execution_time, result)
+
+                # Record stage completion
+                self._record_stage_completion(stage, result)
+
+                return {
+                    "status": "success",
+                    "stage": stage.value,
+                    "result": result,
+                    "execution_time": execution_time,
+                    "metrics": self.stage_metrics.get(stage, {})
+                }
+
+            except Exception as e:
+                error_msg = f"Error in stage {stage.value}: {str(e)}"
+                self.logger.error(error_msg)
+
+                # Handle stage failure
+                await self._handle_stage_failure(stage, context, e)
+
+                return {
+                    "status": "error",
+                    "stage": stage.value,
+                    "error": error_msg,
+                    "execution_time": time.time() - start_time
+                }
+
+        async def _execute_stage_logic(self, stage: PipelineStage, context: Dict[str, Any]) -> Dict[str, Any]:
+            """Execute stage-specific logic with appropriate tools and enhanced error handling."""
+            """Execute stage-specific logic with appropriate tools"""
+            if stage == self.PipelineStage.PLANNING:
+                return await self._execute_planning_stage(context)
+            elif stage == self.PipelineStage.DEVELOPMENT:
+                return await self._execute_development_stage(context)
+            elif stage == self.PipelineStage.TESTING:
+                return await self._execute_testing_stage(context)
+            elif stage == self.PipelineStage.DEPLOYMENT:
+                return await self._execute_deployment_stage(context)
+            elif stage == self.PipelineStage.MAINTENANCE:
+                return await self._execute_maintenance_stage(context)
+            elif stage == self.PipelineStage.ROLLBACK:
+                return await self._execute_rollback_stage(context)
+            else:
+                raise ValueError(f"Unknown pipeline stage: {stage}")
+
+        async def _execute_planning_stage(self, context: Dict[str, Any]) -> Dict[str, Any]:
+            """Execute planning stage with requirement analysis and task breakdown"""
+            try:
+                # Analyze requirements
+                requirements = await self.tool_manager.execute_tool(
+                    "requirements_analyzer",
+                    context.get("requirements", "")
+                )
+
+                # Generate task breakdown
+                tasks = await self.tool_manager.execute_tool(
+                    "task_breakdown",
+                    requirements["result"]
+                )
+
+                # Create project structure
+                project_structure = await self.workspace_manager.create_project_structure(
+                    context["project_name"],
+                    tasks["result"]
+                )
+
+                return {
+                    "requirements": requirements["result"],
+                    "tasks": tasks["result"],
+                    "project_structure": project_structure
+                }
+            except Exception as e:
+                raise Exception(f"Planning stage failed: {str(e)}")
+
+        async def _execute_development_stage(self, context: Dict[str, Any]) -> Dict[str, Any]:
+            """Execute development stage with code generation and quality checks"""
+            try:
+                # Generate code
+                code_generation = await self.tool_manager.execute_tool(
+                    "code_generator",
+                    context.get("tasks", [])
+                )
+
+                # Run initial quality checks
+                quality_check = await self.tool_manager.execute_tool(
+                    "code_quality_checker",
+                    code_generation["result"]
+                )
+
+                # Save generated code
+                saved_files = await self.workspace_manager.save_generated_code(
+                    context["project_name"],
+                    code_generation["result"]
+                )
+
+                return {
+                    "generated_code": code_generation["result"],
+                    "quality_check": quality_check["result"],
+                    "saved_files": saved_files
+                }
+            except Exception as e:
+                raise Exception(f"Development stage failed: {str(e)}")
+
+        async def _execute_testing_stage(self, context: Dict[str, Any]) -> Dict[str, Any]:
+            """Execute testing stage with comprehensive test suite"""
+            try:
+                # Generate tests
+                test_generation = await self.tool_manager.execute_tool(
+                    "test_generator",
+                    context.get("generated_code", "")
+                )
+
+                # Run tests
+                test_results = await self.tool_manager.execute_tool(
+                    "test_runner",
+                    test_generation["result"]
+                )
+
+                # Generate coverage report
+                coverage_report = await self.tool_manager.execute_tool(
+                    "coverage_analyzer",
+                    test_results["result"]
+                )
+
+                return {
+                    "test_cases": test_generation["result"],
+                    "test_results": test_results["result"],
+                    "coverage_report": coverage_report["result"]
+                }
+            except Exception as e:
+                raise Exception(f"Testing stage failed: {str(e)}")
+
+        def _validate_stage_output(self, stage: PipelineStage, result: Dict[str, Any]):
+            """Validate stage output against defined criteria"""
+            validation_rules = self._get_validation_rules(stage)
+            validation_errors = []
+
+            for rule in validation_rules:
+                if not rule.validate(result):
+                    validation_errors.append(rule.get_error_message())
+
+            if validation_errors:
+                raise ValueError(f"Stage validation failed: {'; '.join(validation_errors)}")
+
+        def _update_stage_metrics(self, stage: PipelineStage, execution_time: float, result: Dict[str, Any]):
+            """Update metrics for the stage"""
+            if stage not in self.stage_metrics:
+                self.stage_metrics[stage] = {
+                    "total_executions": 0,
+                    "successful_executions": 0,
+                    "failed_executions": 0,
+                    "average_execution_time": 0,
+                    "last_execution_time": None,
+                    "error_rate": 0
+                }
+
+            metrics = self.stage_metrics[stage]
+            metrics["total_executions"] += 1
+            metrics["last_execution_time"] = execution_time
+
+            if result.get("status") == "success":
+                metrics["successful_executions"] += 1
+            else:
+                metrics["failed_executions"] += 1
+
+            metrics["error_rate"] = metrics["failed_executions"] / metrics["total_executions"]
+            metrics["average_execution_time"] = (
+                (metrics["average_execution_time"] * (metrics["total_executions"] - 1) + execution_time)
+                / metrics["total_executions"]
+            )
+
+        async def _handle_stage_failure(self, stage: PipelineStage, context: Dict[str, Any], error: Exception):
+            """Handle stage failure with rollback and recovery options"""
+            self.logger.error(f"Handling failure in stage {stage.value}: {str(error)}")
+
+            # Record failure
+            self._record_stage_failure(stage, error)
+
+            # Determine if rollback is needed
+            if self._should_rollback(stage, error):
+                await self._execute_rollback(stage, context)
+
+            # Attempt recovery
+            await self._attempt_recovery(stage, context, error)
+
+        def _should_rollback(self, stage: PipelineStage, error: Exception) -> bool:
+            """Determine if a rollback is needed based on error severity"""
+            critical_errors = [
+                "DatabaseError",
+                "DeploymentError",
+                "SecurityViolation"
+            ]
+            return any(err in str(error) for err in critical_errors)
+
+        async def _execute_rollback(self, stage: PipelineStage, context: Dict[str, Any]):
+            """Execute rollback procedure for a failed stage"""
+            self.logger.info(f"Executing rollback for stage {stage.value}")
+
+            try:
+                # Get rollback point
+                rollback_point = self._get_rollback_point(stage)
+
+                # Execute rollback
+                await self.execute_stage(
+                    self.PipelineStage.ROLLBACK,
+                    {
+                        **context,
+                        "rollback_point": rollback_point,
+                        "failed_stage": stage
+                    }
+                )
+
+            except Exception as e:
+                self.logger.error(f"Rollback failed: {str(e)}")
+                # Implement emergency shutdown if rollback fails
+                self._emergency_shutdown(stage, e)
+
+        def _emergency_shutdown(self, stage: PipelineStage, error: Exception):
+            """Handle emergency shutdown when rollback fails"""
+            self.logger.critical(f"Emergency shutdown initiated for stage {stage.value}")
+            # Implement emergency shutdown procedures
+            pass
+
+    class CodeMetricsAnalyzer:
+        """Analyzes code metrics using various tools"""
+
+        def __init__(self):
+            self.metrics_history = []
+
+        def analyze_code_quality(self, file_path: str) -> Dict[str, Any]:
+            """Analyzes code quality using multiple metrics"""
+            try:
+                # Pylint analysis
+                pylint_score = self._run_pylint(file_path)
+
+                # Complexity analysis
+                complexity_score = self._analyze_complexity(file_path)
+
+                # Test coverage analysis
+                coverage_score = self._analyze_test_coverage(file_path)
+
+                # Security analysis
+                security_score = self._analyze_security(file_path)
+
+                # Calculate overall quality score
+                quality_score = self._calculate_overall_score(
+                    pylint_score,
+                    complexity_score,
+                    coverage_score,
+                    security_score
+                )
+
+                metrics = {
+                    "quality_score": quality_score,
+                    "pylint_score": pylint_score,
+                    "complexity_score": complexity_score,
+                    "coverage_score": coverage_score,
+                    "security_score": security_score,
+                    "timestamp": datetime.now()
+                }
+
+                self.metrics_history.append(metrics)
+                return metrics
+
+            except Exception as e:
+                logging.error(f"Error analyzing code metrics: {str(e)}")
+                return {
+                    "error": str(e),
+                    "quality_score": 0.0,
+                    "timestamp": datetime.now()
+                }
+
+        def _run_pylint(self, file_path: str) -> float:
+            """Runs pylint analysis"""
+            try:
+                reporter = JSONReporter()
+                Run([file_path], reporter=reporter, do_exit=False)
+                score = reporter.data.get('score', 0.0)
+                return float(score) / 10.0  # Normalize to 0-1 scale
+            except Exception as e:
+                logging.error(f"Pylint analysis error: {str(e)}")
+                return 0.0
+
+        def _analyze_complexity(self, file_path: str) -> float:
+            """Analyzes code complexity"""
+            try:
+                with open(file_path, 'r') as file:
+                    code = file.read()
+
+                # Calculate cyclomatic complexity
+                complexity = radon.complexity.cc_visit(code)
+                avg_complexity = sum(item.complexity for item in complexity) / len(complexity) if complexity else 0
+
+                # Normalize complexity score (0-1 scale, lower is better)
+                normalized_score = 1.0 - min(avg_complexity / 10.0, 1.0)
+                return normalized_score
+
+            except Exception as e:
+                logging.error(f"Complexity analysis error: {str(e)}")
+                return 0.0
+
+        async def _analyze_current_state(self, project_name: str) -> Dict[str, Any]:
+            """Analyze current project state with detailed metrics."""
+            try:
+                self.logger.info(f"Analyzing current state for project: {project_name}")
+
+                # Collect code metrics
+                code_metrics = await self._collect_code_metrics(project_name)
+                self.logger.info("Code metrics collected successfully.")
+
+                # Analyze test coverage
+                test_coverage = await self._analyze_test_coverage(project_name)
+                self.logger.info("Test coverage analysis completed.")
+
+                # Check security vulnerabilities
+                security_analysis = await self._analyze_security(project_name)
+                self.logger.info("Security analysis completed.")
+
+                # Measure performance metrics
+                performance_metrics = await self._measure_performance(project_name)
+                self.logger.info("Performance metrics measured.")
+
+                # Determine if requirements are met
+                meets_requirements = await self._check_requirements(
+                    code_metrics,
+                    test_coverage,
+                    security_analysis,
+                    performance_metrics
+                )
+                self.logger.info("Requirements check completed.")
+
+                return {
+                    "code_metrics": code_metrics,
+                    "test_coverage": test_coverage,
+                    "security_analysis": security_analysis,
+                    "performance_metrics": performance_metrics,
+                    "meets_requirements": meets_requirements,
+                    "timestamp": datetime.now()
+                }
+
+            except Exception as e:
+                self.logger.error(f"Error analyzing current state: {str(e)}")
+                raise
+
+        def _analyze_security(self, file_path: str) -> float:
+            """Analyzes code security using bandit"""
+            try:
+                conf = manager.BanditManager()
+                conf.discover_files([file_path])
+                conf.run_tests()
+
+                # Calculate security score based on findings
+                total_issues = len(conf.get_issue_list())
+                max_severity = max((issue.severity for issue in conf.get_issue_list()), default=0)
+
+                # Normalize security score (0-1 scale, higher is better)
+                security_score = 1.0 - (total_issues * max_severity) / 10.0
+                return max(0.0, min(1.0, security_score))
+
+            except Exception as e:
+                logging.error(f"Security analysis error: {str(e)}")
+                return 0.0
+
+        def _calculate_overall_score(self, pylint_score: float, complexity_score: float,
+                                   coverage_score: float, security_score: float) -> float:
+            """Calculates overall code quality score"""
+            weights = {
+                'pylint': 0.3,
+                'complexity': 0.2,
+                'coverage': 0.25,
+                'security': 0.25
+            }
+
+            overall_score = (
+                weights['pylint'] * pylint_score +
+                weights['complexity'] * complexity_score +
+                weights['coverage'] * coverage_score +
+                weights['security'] * security_score
+            )
+
+            return max(0.0, min(1.0, overall_score))
+
+        def get_metrics_history(self) -> List[Dict[str, Any]]:
+            """Returns the history of metrics measurements"""
+            return self.metrics_history
+
+        def get_trend_analysis(self) -> Dict[str, Any]:
+            """Analyzes trends in metrics over time"""
+            if not self.metrics_history:
+                return {"status": "No metrics history available"}
+
+            trends = {
+                "quality_score": self._calculate_trend([m["quality_score"] for m in self.metrics_history]),
+                "coverage_score": self._calculate_trend([m["coverage_score"] for m in self.metrics_history]),
+                "security_score": self._calculate_trend([m["security_score"] for m in self.metrics_history])
+            }
+
+            return trends
+
+        def _calculate_trend(self, values: List[float]) -> Dict[str, Any]:
+            """Calculates trend statistics for a metric"""
+            if not values:
+                return {"trend": "unknown", "change": 0.0}
+
+            recent_values = values[-3:]  # Look at last 3 measurements
+            if len(recent_values) < 2:
+                return {"trend": "insufficient data", "change": 0.0}
+
+            change = recent_values[-1] - recent_values[0]
+            trend = "improving" if change > 0 else "declining" if change < 0 else "stable"
+
+            return {
+                "trend": trend,
+                "change": change,
+                "current": recent_values[-1],
+                "previous": recent_values[0]
+            }
+
+    @dataclass
+    class QualityMetrics:
+        """Advanced quality metrics tracking and analysis"""
+        code_quality_score: float = 0.0
+        test_coverage: float = 0.0
+        security_score: str = "unknown"
+        performance_score: float = 0.0
+        metrics_analyzer: CodeMetricsAnalyzer = None
+
+        def __post_init__(self):
+            self.metrics_analyzer = CodeMetricsAnalyzer()
+            self.history = []
+            self.thresholds = {
+                "code_quality": 0.85,
+                "test_coverage": 0.90,
+                "security": 0.85,
+                "performance": 0.80
+            }
+
+        def analyze_code(self, project_name: str) -> Dict[str, Any]:
+            """Comprehensive code analysis"""
+            try:
+                # Get all Python files in the project
+                project_files = self._get_project_files(project_name)
+
+                aggregated_metrics = {
+                    "code_quality": 0.0,
+                    "test_coverage": 0.0,
+                    "security": 0.0,
+                    "performance": 0.0,
+                    "files_analyzed": len(project_files),
+                    "detailed_metrics": []
+                }
+
+                for file_path in project_files:
+                    metrics = self.metrics_analyzer.analyze_code_quality(file_path)
+                    aggregated_metrics["detailed_metrics"].append({
+                        "file": file_path,
+                        "metrics": metrics
+                    })
+
+                    # Update aggregated scores
+                    aggregated_metrics["code_quality"] += metrics["quality_score"]
+                    aggregated_metrics["test_coverage"] += metrics["coverage_score"]
+                    aggregated_metrics["security"] += metrics["security_score"]
+
+                # Calculate averages
+                if project_files:
+                    for key in ["code_quality", "test_coverage", "security"]:
+                        aggregated_metrics[key] /= len(project_files)
+
+                # Update instance variables
+                self.code_quality_score = aggregated_metrics["code_quality"]
+                self.test_coverage = aggregated_metrics["test_coverage"]
+                self.security_score = str(aggregated_metrics["security"])
+
+                # Add to history
+                self.history.append({
+                    "timestamp": datetime.now(),
+                    "metrics": aggregated_metrics
+                })
+
+                return aggregated_metrics
+
+            except Exception as e:
+                logging.error(f"Error in code analysis: {str(e)}")
+                return {
+                    "error": str(e),
+                    "code_quality": 0.0,
+                    "test_coverage": 0.0,
+                    "security": "error",
+                    "performance": 0.0
+                }
+
+        def _get_project_files(self, project_name: str) -> List[str]:
+            """Get all Python files in the project"""
+            project_dir = os.path.join(os.getcwd(), project_name)
+            python_files = []
+
+            for root, _, files in os.walk(project_dir):
+                for file in files:
+                    if file.endswith('.py'):
+                        python_files.append(os.path.join(root, file))
+
+            return python_files
+
+        def get_improvement_suggestions(self) -> List[str]:
+            """Generate improvement suggestions based on metrics"""
+            suggestions = []
+            latest_metrics = self.history[-1]["metrics"] if self.history else None
+
+            if not latest_metrics:
+                return ["No metrics available for analysis"]
+
+            if latest_metrics["code_quality"] < self.thresholds["code_quality"]:
+                suggestions.append(
+                    f"Code quality score ({latest_metrics['code_quality']:.2f}) is below threshold "
+                    f"({self.thresholds['code_quality']}). Consider refactoring complex methods."
+                )
+
+            if latest_metrics["test_coverage"] < self.thresholds["test_coverage"]:
+                suggestions.append(
+                    f"Test coverage ({latest_metrics['test_coverage']:.2f}) is below threshold "
+                    f"({self.thresholds['test_coverage']}). Add more unit tests."
+                )
+
+            if float(latest_metrics["security"]) < self.thresholds["security"]:
+                suggestions.append(
+                    f"Security score ({latest_metrics['security']}) is below threshold "
+                    f"({self.thresholds['security']}). Address security vulnerabilities."
+                )
+
+            return suggestions
+
+    class ErrorTracker:
+        """Enhanced error tracking and analysis"""
+        def __init__(self):
+            self.errors: List[Dict[str, Any]] = []
+            self.error_patterns: Dict[str, int] = {}
+            self.critical_errors: List[Dict[str, Any]] = []
+
+        def add_error(self, error_type: str, message: str, severity: str = "normal"):
+            """Add an error with enhanced tracking"""
+            error_entry = {
+                "type": error_type,
+                "message": message,
+                "severity": severity,
+                "timestamp": datetime.now(),
+                "stack_trace": traceback.format_exc()
+            }
+
+            self.errors.append(error_entry)
+
+            # Track error patterns
+            if error_type in self.error_patterns:
+                self.error_patterns[error_type] += 1
+            else:
+                self.error_patterns[error_type] = 1
+
+            # Track critical errors
+            if severity == "critical":
+                self.critical_errors.append(error_entry)
+                self._notify_critical_error(error_entry)
+
+        def _notify_critical_error(self, error: Dict[str, Any]):
+            """Handle critical error notification"""
+            logging.critical(f"Critical error detected: {error['message']}")
+            # Implement notification system here (e.g., email, Slack)
+
+        def get_error_analysis(self) -> Dict[str, Any]:
+            """Generate comprehensive error analysis"""
+            return {
+                "total_errors": len(self.errors),
+                "error_patterns": self.error_patterns,
+                "critical_errors": len(self.critical_errors),
+                "most_common_error": max(self.error_patterns.items(), key=lambda x: x[1]) if self.error_patterns else None,
+                "error_trend": self._analyze_error_trend()
+            }
+
+        def _analyze_error_trend(self) -> Dict[str, Any]:
+            """Analyze error trends over time"""
+            if not self.errors:
+                return {"trend": "no errors"}
+
+            # Group errors by hour
+            error_timeline = {}
+            for error in self.errors:
+                hour = error["timestamp"].replace(minute=0, second=0, microsecond=0)
+                if hour in error_timeline:
+                    error_timeline[hour] += 1
+                else:
+                    error_timeline[hour] = 1
+
+            # Calculate trend
+            timeline_values = list(error_timeline.values())
+            if len(timeline_values) < 2:
+                return {"trend": "insufficient data"}
+
+            trend = "increasing" if timeline_values[-1] > timeline_values[0] else "decreasing"
+            return {
+                "trend": trend,
+                "current_rate": timeline_values[-1],
+                "initial_rate": timeline_values[0]
+            }
+
+    class ProjectAnalytics:
+        """Enhanced project analytics and reporting"""
+        """Enhanced project analytics and reporting"""
+        def __init__(self, workspace_manager):
+            self.workspace_manager = workspace_manager
+            self.metrics_analyzer = CodeMetricsAnalyzer()
+            self.analysis_history = []
+
+        def generate_project_report(self, project_name: str) -> Dict[str, Any]:
+            """Generate comprehensive project report"""
+            try:
+                current_analysis = {
+                    "timestamp": datetime.now(),
+                    "basic_metrics": self._get_basic_metrics(project_name),
+                    "code_quality": self._get_code_quality_metrics(project_name),
+                    "performance": self._get_performance_metrics(project_name),
+                    "security": self._get_security_metrics(project_name),
+                    "dependencies": self._analyze_dependencies(project_name)
+                }
+
+                self.analysis_history.append(current_analysis)
+
+                return {
+                    "current_analysis": current_analysis,
+                    "historical_trends": self._analyze_trends(),
+                    "recommendations": self._generate_recommendations(current_analysis)
+                }
+
+            except Exception as e:
+                logging.error(f"Error generating project report: {str(e)}")
+                return {"error": str(e)}
+
+    class StreamlitInterface:
+        """Streamlit UI integration for the Autonomous Agent system."""
+
+        def __init__(self, app: AutonomousAgentApp):
+            self.app = app
+
+        def render_main_interface(self):
+            """Render the main Streamlit interface."""
+            st.title("Autonomous Agent System")
+
+            # Create tabs for different functionalities
+            tab_names = ["Autonomous Agent", "Workspace Management", "Settings"]
+            selected_tab = st.selectbox("Select a Tab", tab_names)
+
+            if selected_tab == "Autonomous Agent":
+                self.render_autonomous_agent_tab()
+            elif selected_tab == "Workspace Management":
+                self.render_workspace_management_tab()
+            elif selected_tab == "Settings":
+                self.render_settings_tab()
+
+        def render_autonomous_agent_tab(self):
+            """Render the Autonomous Agent tab."""
+            st.header("Autonomous Agent")
+            task = st.text_area("Enter a task for the autonomous agent:")
+
+            if st.button("Run Autonomous Agent"):
+                if task:
+                    # Run the autonomous agent with the provided task
+                    try:
+                        result = asyncio.run(self.app.refinement_loop.run_refinement_cycle(task))
+                        st.success(f"Result: {result}")
+                    except Exception as e:
+                        st.error(f"An error occurred: {str(e)}")
+
+        def render_workspace_management_tab(self):
+            """Render the Workspace Management tab with a workspace explorer."""
+            st.header("Workspace Management")
+
+            # Workspace Explorer
+            st.subheader("Workspace Explorer")
+            workspace_tree = self.app.workspace_manager.get_workspace_tree()
+            self._render_tree(workspace_tree)
+
+            # File creation
+            st.subheader("Create a File")
+            new_filename = st.text_input("Enter filename:")
+            new_file_content = st.text_area("Enter file content:")
+            if st.button("Create File"):
+                if new_filename and new_file_content:
+                    result = self.app.workspace_manager.create_file(new_filename, new_file_content)
+                    st.success(result)
+                else:
+                    st.error("Filename and content are required.")
+
+            # File deletion
+            st.subheader("Delete a File")
+            delete_filename = st.text_input("Enter filename to delete:")
+            if st.button("Delete File"):
+                if delete_filename:
+                    result = self.app.workspace_manager.delete_file(delete_filename)
+                    st.success(result)
+                else:
+                    st.error("Filename is required.")
+
+        def _render_tree(self, tree: Dict[str, Any], level: int = 0):
+            """Recursively render the workspace directory tree."""
+            if tree["type"] == "file":
+                st.write("  " * level + f"📄 {tree['name']}")
+            elif tree["type"] == "directory":
+                st.write("  " * level + f"📁 {tree['name']}")
+                for child in tree["children"]:
+                    self._render_tree(child, level + 1)
+
+        def render_settings_tab(self):
+            """Render the Settings tab."""
+            st.header("Application Settings")
+
+            # Section 1: Refinement Process Configuration
+            st.subheader("Refinement Process Settings")
+
+            # Adjust maximum refinement iterations
+            current_max_iter = self.app.refinement_loop.max_iterations
+            new_max_iter = st.number_input(
+                "Maximum Refinement Iterations",
+                min_value=1,
+                max_value=20,
+                value=current_max_iter,
+                help="Maximum number of refinement cycles to perform"
+            )
+            if new_max_iter != current_max_iter:
+                self.app.refinement_loop.max_iterations = new_max_iter
+                st.success(f"Updated maximum iterations to {new_max_iter}")
+
+            # Section 2: Quality Threshold Configuration
+            st.subheader("Quality Thresholds")
+
+            # Get current thresholds
+            thresholds = self.app.refinement_loop.quality_metrics.thresholds
+
+            col1, col2, col3 = st.columns(3)
+            with col1:
+                new_code_quality = st.slider(
+                    "Code Quality Threshold",
+                    0.0, 1.0, thresholds["code_quality"],
+                    help="Minimum acceptable code quality score"
+                )
+            with col2:
+                new_test_coverage = st.slider(
+                    "Test Coverage Threshold",
+                    0.0, 1.0, thresholds["test_coverage"],
+                    help="Minimum required test coverage"
+                )
+            with col3:
+                new_security = st.slider(
+                    "Security Threshold",
+                    0.0, 1.0, thresholds["security"],
+                    help="Minimum acceptable security score"
+                )
+
+            if st.button("Update Quality Thresholds"):
+                self.app.refinement_loop.quality_metrics.thresholds.update({
+                    "code_quality": new_code_quality,
+                    "test_coverage": new_test_coverage,
+                    "security": new_security
+                })
+                st.success("Quality thresholds updated!")
+
+            # Section 3: Performance Configuration
+            st.subheader("Performance Settings")
+
+            # Concurrency settings
+            concurrency_level = st.selectbox(
+                "Max Concurrency",
+                options=[1, 2, 4, 8],
+                index=2,
+                help="Maximum parallel tasks for code analysis"
+            )
+
+            # Resource limits
+            mem_limit = st.slider(
+                "Memory Limit (GB)",
+                1, 16, 4,
+                help="Maximum memory allocation for pipeline operations"
+            )
+
+            # Section 4: Security Settings
+            st.subheader("Security Configuration")
+
+            # Security rules toggle
+            enable_security_scan = st.checkbox(
+                "Enable Real-time Security Scanning",
+                value=True,
+                help="Perform continuous security analysis during development"
+            )
+
+            # Severity level filtering
+            security_level = st.selectbox(
+                "Minimum Security Severity Level",
+                ["Low", "Medium", "High", "Critical"],
+                index=1,
+                help="Minimum severity level to trigger security alerts"
+            )
+
+            # Section 5: Workspace Configuration
+            st.subheader("Workspace Settings")
+            current_workspace = self.app.workspace_manager.workspace_dir
+            st.write(f"Current Workspace: `{current_workspace}`")
+
+            # Workspace actions
+            if st.button("Clear Workspace Cache"):
+                self.app.workspace_manager.clean_cache()
+                st.success("Workspace cache cleared!")
+
+            # Section 6: Diagnostic Settings
+            st.subheader("Diagnostics")
+
+            # Logging controls
+            log_level = st.selectbox(
+                "Logging Level",
+                ["DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"],
+                index=1
+            )
+            st.session_state.log_level = log_level  # Store in session state
+            logging.getLogger().setLevel(log_level)
+
+            # Debug mode toggle
+            debug_mode = st.checkbox("Enable Debug Mode")
+            st.session_state.debug_mode = debug_mode  # Store in session state
+            if debug_mode:
+                self.app.refinement_loop.logger.setLevel(logging.DEBUG)
+            else:
+                self.app.refinement_loop.logger.setLevel(logging.INFO)
+
+            # Section 7: System Information
+            st.subheader("System Info")
+            st.write(f"Python Version: {sys.version}")
+            st.write(f"Platform: {platform.platform()}")
+            st.write(f"Available Memory: {psutil.virtual_memory().available / (1024**3):.1f} GB free")
+
+
+if __name__ == "__main__":
+    import streamlit as st
+    main()