Update definitions.py

definitions.py

@@ -1,421 +1,1081 @@
-import os
-import google.generativeai as genai
-import gradio as gr
-from gradio.themes.base import Base
-from gradio.themes.utils import colors, sizes, fonts
-import re
+import platform
+import streamlit as st
+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 List, Dict, AsyncIterator, Optional
-from dataclasses import dataclass, field
-
-# --- Logging Setup ---
-logging.basicConfig(level=logging.INFO)
-
-# --- Custom Exception ---
-class APIConfigError(Exception):
-    """Custom exception for API configuration issues."""
-    pass
-
-# --- Data Classes ---
-@dataclass
-class ChatMessage:
-    role: str
-    content: str
-
-@dataclass
-class DevelopmentContext:
-    user_task: str
-    relevant_code: Optional[str] = None
-    tech_stack: List[str] = field(default_factory=list)
-    user_intent: Optional[str] = None
-    code_language: Optional[str] = None
-
-# --- GeminiDevAssistant Class ---
-class GeminiDevAssistant:
-    def __init__(self, api_key: str):
+from pathlib import Path
+
+# Set logging level from environment variable
+logging.basicConfig(level=os.getenv('LOG_LEVEL', 'INFO'))
+
+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:
-            self.configure_api(api_key)
-            self.model = genai.GenerativeModel('gemini-1.5-flash-002')
-            logging.info("GeminiDevAssistant initialized successfully.")
+            # 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 initializing Gemini API: {e}")
-            raise APIConfigError(f"Error initializing Gemini API: {e}")
-
-    @staticmethod
-    def configure_api(api_key: str) -> None:
-        genai.configure(api_key=api_key)
-
-    def analyze_development_task(self, user_message: str) -> DevelopmentContext:
-        """Analyzes the user's development task and extracts relevant context."""
-        logging.info("Analyzing development task...")
-        code_blocks = self._extract_code_blocks(user_message)
-        code = code_blocks[0]['code'] if code_blocks else None
-        language = code_blocks[0]['language'] if code_blocks else None
-
-        intent = self._infer_user_intent(user_message)
-        tech_stack = self._detect_tech_stack(user_message, code, language)
-
-        logging.debug(f"Detected code: {code}")
-        logging.debug(f"Detected language: {language}")
-        logging.debug(f"Inferred intent: {intent}")
-        logging.debug(f"Detected tech stack: {tech_stack}")
-
-        return DevelopmentContext(
-            user_task=user_message,
-            relevant_code=code,
-            tech_stack=tech_stack,
-            user_intent=intent,
-            code_language=language
-        )
+            logging.error(f"Error analyzing code metrics: {str(e)}")
+            return {
+                "error": str(e),
+                "quality_score": 0.0,
+                "timestamp": datetime.now()
+            }
 
-    def _extract_code_blocks(self, text: str) -> List[Dict[str, str]]:
-        """Extracts code blocks from text using regex."""
-        code_blocks = []
-        matches = re.findall(r"```(\w+)?\n(.*?)\n```", text, re.DOTALL)
-        for match in matches:
-            language = match[0] if match[0] else "plaintext"
-            code = match[1].strip()
-            code_blocks.append({"language": language, "code": code})
-        return code_blocks
-
-    def _infer_user_intent(self, user_message: str) -> Optional[str]:
-        """Basic intent inference based on keywords."""
-        message_lower = user_message.lower()
-        if "debug" in message_lower or "error" in message_lower or "fix" in message_lower:
-            return "debugging"
-        elif "optimize" in message_lower or "performance" in message_lower or "improve" in message_lower:
-            return "optimization"
-        elif "test" in message_lower or "unit test" in message_lower:
-            return "unit testing"
-        elif "refactor" in message_lower or "clean up" in message_lower:
-            return "refactoring"
-        elif "document" in message_lower or "comment" in message_lower:
-            return "documentation elif "generate" in message_lower or "create" in message_lower or "write" in message_lower:
-            return "code generation"
-        return "general development task"
-
-    def _detect_tech_stack(self, user_message: str, code: Optional[str], language: Optional[str]) -> List[str]:
-        """Basic tech stack detection based on keywords and code analysis."""
-        tech_stack = set()
-        message_lower = user_message.lower()
-
-        if language:
-            tech_stack.add(language)
-
-        common_tech_keywords = {
-            "python": ["python", "django", "flask", "pandas", "numpy"],
-            "javascript": ["javascript", "react", "vue", "angular", "node.js", "express"],
-            "java": ["java", "spring", "hibernate"],
-            "c++": ["c++", "qt"],
-            "c#": ["c#", ".net", "asp.net"],
-            "typescript": ["typescript", "react", "angular"],
-            "html": ["html", "css", "javascript"],
-            "css": ["css", "html", "javascript"],
-            "sql": ["sql", "mysql", "postgresql", "sqlite", "database"],
-            "docker": ["docker", "container", "dockerfile"],
-            "kubernetes": ["kubernetes", "k8s", "cluster"],
-            "git": ["git", "version control", "repository"],
-            "aws": ["aws", "amazon web services", "ec2", "s3", "lambda"],
-            "azure": ["azure", "microsoft azure", "cloud services"],
-            "gcp": ["gcp", "google cloud platform", "google cloud"],
-        }
+    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
 
-        for tech, keywords in common_tech_keywords.items():
-            for keyword in keywords:
-                if keyword in message_lower or (code and keyword in code.lower()):
-                    tech_stack.add(tech)
-                    break
-
-        return list(tech_stack)
-
-    def format_chat_history(self, messages: List[Dict]) -> List[Dict]:
-        """Formats chat history for Gemini API."""
-        formatted_history = []
-        for msg in messages:
-            if isinstance(msg, dict) and "role" in msg and "content" in msg:
-                role = msg["role"]
-                content = msg["content"]
-                formatted_history.append({"role": role, "parts": [content]})
-            else:
-                logging.warning(f"Unexpected message format: {msg}")
-        return formatted_history
+    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
 
-    async def stream_development_response(self, user_message: str, messages: List[Dict]) -> AsyncIterator[List[Dict]]:
-        """Streams development responses from Gemini API (Synchronous Iteration)."""
-        development_context = self.analyze_development_task(user_message)
-        prompt = self._build_development_prompt(development_context)
-        chat_history = self.format_chat_history(messages)
+            # Normalize complexity score (0-1 scale, lower is better)
+            normalized_score = 1.0 - min(avg_complexity / 10.0, 1.0)
+            return normalized_score
 
-        logging.info("Sending prompt to Gemini API...")
-        logging.debug(f"Prompt being sent: {prompt}")
+        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:
-            chat = self.model.start_chat(history=chat_history)
-            response = chat.send_message(prompt, stream=True)
+            self.logger.info(f"Analyzing current state for project: {project_name}")
 
-            response_iterator = iter(response)
+            # Collect code metrics
+            code_metrics = await self._collect_code_metrics(project_name)
+            self.logger.info("Code metrics collected successfully.")
 
-            try:
-                while True:
-                    chunk = next(response_iterator)
+            # Analyze test coverage
+            test_coverage = await self._analyze_test_coverage(project_name)
+            self.logger.info("Test coverage analysis completed.")
 
-                    updated_messages, code_block_buffer = self._process_development_stream(
-                        chunk, messages, "", "", False, "", development_context.code_language
-                    )
-                    gradio_messages_format = [(msg.role, self._format_content_for_gradio(msg.content, development_context.code_language)) if msg.role == 'user' else (None, self._format_content_for_gradio(msg.content, development_context.code_language)) for msg in updated_messages]
-                    yield gradio_messages_format
+            # Check security vulnerabilities
+            security_analysis = await self._analyze_security(project_name)
+            self.logger.info("Security analysis completed.")
 
-            except StopIteration:
-                pass
-            except Exception as e:
-                error_message = self._format_development_error(e)
-                logging.error(f"Error during Gemini API call (in loop): {e}\n{traceback.format_exc()}")
-                yield messages + [(None, error_message)]
+            # 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:
-            error_message = self._format_development_error(e)
-            logging.error(f"Error during Gemini API call (outer): {e}\n{traceback.format_exc()}")
-            yield messages + [(None, error_message)]
-
-    def _process_development_stream(self, chunk, messages, thought_buffer, response_buffer, thinking_complete, code_block_buffer, code_language):
-        """Processes a chunk of the development stream and updates messages, handling code blocks."""
-        text_chunk = chunk.text
-
-        response_buffer += text_chunk
-
-        if "```" in response_buffer:
-            parts = response_buffer.split("```")
-            response_buffer = parts[-1]
-            code_block = "```" + parts[-2] + "```" if len(parts) > 1 else ""
-            if code_block:
-                code_block_buffer += code_block
-
-        if messages and messages[-1].role == "assistant":
-            messages[-1].content = response_buffer
-            if code_block_buffer:
-                messages [-1].content = code_block_buffer + "\n" + messages[-1].content
-                code_block_buffer = ""
-        elif messages:
-            messages.append(ChatMessage(role="assistant", content=response_buffer))
-        else:
-            messages.append(ChatMessage(role="assistant", content=response_buffer))
-
-        return messages, code_block_buffer
-
-    def _format_content_for_gradio(self, content: str, code_language: Optional[str]) -> str:
-        """Formats content for Gradio chatbot, adding syntax highlighting for code blocks."""
-        formatted_content = content
-        code_blocks = self._extract_code_blocks(content)
-
-        if code_blocks:
-            for block in code_blocks:
-                lang = block['language']
-                code = block['code']
-                formatted_code = f"```{lang}\n{code}\n```"
-                formatted_content = formatted_content.replace(f"```{lang}\n{code}\n```", formatted_code)
-
-        return formatted_content
-
-    def _build_development_prompt(self, development_context: DevelopmentContext) -> str:
-        """Builds a more detailed and effective prompt for the Gemini model."""
-        prompt_parts = [
-            "You are an expert Development Assistant. Your goal is to provide the most helpful and effective assistance to users with their development tasks.",
-            "Focus on providing practical solutions, code examples, debugging guidance, optimization suggestions, and best practices.",
-            "When providing code, ensure it is correct, efficient, and well-formatted. Use markdown code blocks with appropriate language syntax highlighting.",
-            "Clearly explain your reasoning and thought process step-by-step, especially for complex tasks like debugging or optimization.",
-            "If the user provides code, analyze it carefully and provide specific feedback related to their task.",
-            f"**User 's Development Task:** {development_context.user_task}.",
-        ]
-
-        if development_context.relevant_code:
-            prompt_parts.append(f"\n**Relevant Code Snippet (Language: {development_context.code_language or 'unknown'}):**\n```{development_context.code_language or 'plaintext'}\n{development_context.relevant_code}\n```")
-
-        if development_context.tech_stack:
-            prompt_parts.append(f"\n**Detected Technologies/Tech Stack:** {', '.join(development_context.tech_stack)}.")
-
-        if development_context.user_intent:
-            prompt_parts.append(f"\n**Inferred User Intent:** User seems to be asking for help with {development_context.user_intent}.")
-
-        prompt_parts.append(
-            "\n**Instructions for Response Formatting:**\n"
-            "1. Start with a brief summary of your understanding of the user's task and intent.\n"
-            "2. If providing code, use markdown code blocks with language syntax highlighting.\n"
-            "3. Clearly separate your thought process, explanations, and code examples.\n"
-            "4. Be concise but comprehensive. Avoid unnecessary verbosity.\n"
-            "5. If you identify errors or issues, clearly point them out and suggest solutions.\n"
-            "6. If suggesting optimizations, explain the benefits and trade-offs.\n"
-            "7. End with a helpful concluding remark or next steps for the user."
+            self.logger.error(f"Error analyzing current state: {str(e)}")
+            raise
+
+    def _analyze_security (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 " ".join(prompt_parts)
-
-    def _format_development_error(self, error: Exception) -> str:
-        """Formats an enhanced error message for display to the user."""
-        error_type = type(error).__name__
-        error_details = str(error)
-        full_traceback = traceback.format_exc()
-
-        error_message = f"**Oops! Development Task Encountered an Error:**\n\n"
-        error_message += f"**Error Type:** `{error_type}`\n"
-        error_message += f"**Details:** {error_details}\n\n"
-        error_message += "**Detailed Error Traceback (for debugging):**\n```\n{full_traceback}\n```\n\n"
-        error_message += "**Suggestions to Troubleshoot:**\n"
-        error_message += "* **Check your Gemini API key:** Ensure it's correctly set as an environment variable `GEMINI_API_KEY`.\n"
-        error_message += "* **Verify your network connection:** Make sure you have internet access.\n"
-        error_message += "* **Simplify your request:** Try breaking down complex tasks into smaller, more manageable steps.\n"
-        error_message += "* **Provide more context:** The more information you give, the better the assistant can understand your request.\n"
-        error_message += "* **Review the error traceback:** The 'Detailed Error Traceback' above might contain clues about the underlying issue. If you're a developer, this is often the most helpful part.\n"
-
-        logging.error(f"Formatted Error Message: {error_message}")
-
-        return error_message
-
-# --- Gradio Interface ---
-def create_dev_assistant_interface():
-    try:
-        api_key = os.getenv("GEMINI_API_KEY")
-        if not api_key:
-            raise APIConfigError("GEMINI_API_KEY environment variable not set. Please set your Gemini API key.")
-
-        assistant = Gemini DevAssistant(api_key)
-
-        async def process_input(msg, history_gradio):
-            history = []
-            for human, assistant_response in history_gradio:
-                if human is not None:
-                    history.append({"role": "user", "content": human})
-                if assistant_response is not None:
-                    history.append({"role": "model", "content": assistant_response})
-
-            async def stream_output():
-                async for messages_list in assistant.stream_development_response(msg, history):
-                    yield messages_list
-
-            collected_messages = []
-            async for message_chunk in stream_output():
-                collected_messages = message_chunk
-                yield collected_messages
-
-        # --- Custom Theme ---
-        class ModernDevTheme(Base):
-            def __init__(self):
-                super().__init__(
-                    primary_hue="indigo",
-                    secondary_hue="blue",
-                    neutral_hue="slate",
-                    font=fonts.GoogleFont("Inter"),
-                    font_mono=fonts.GoogleFont("JetBrains Mono")
-                )
+        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 WorkspaceManager:
+    """Manages the workspace for the Autonomous Agent System."""
+    
+    def __init__(self, workspace_dir: str):
+        self.workspace_dir = workspace_dir
+
+    def get_workspace_tree(self) -> Dict[str, Any]:
+        """Get the structure of the workspace."""
+        # Placeholder implementation
+        return {"workspace": "tree_structure"}
+
+    def create_file(self, filename: str, content: str) -> str:
+        """Create a new file in the workspace."""
+        file_path = os.path.join(self.workspace_dir, filename)
+        with open(file_path, 'w') as file:
+            file.write(content)
+        return f"File '{filename}' created successfully."
+
+    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 successfully."
+        return f"File '{filename}' not found."
+
+class ToolManager:
+    """Manages tools for the autonomous agent system."""
+    
+    def __init__(self):
+        self.tools = {}
+
+    def add_tool(self, tool_name, tool_config):
+        """Add a tool to the tool manager."""
+        self.tools[tool_name] = tool_config
+
+    def get_tool(self, tool_name):
+        """Get a tool from the tool manager."""
+        return self.tools.get(tool_name)
+
+    def remove_tool(self, tool_name):
+        """Remove a tool from the tool manager."""
+        if tool_name in self.tools:
+            del self.tools[tool_name]
+
+class QualityMetrics:
+    """Advanced quality metrics tracking and analysis"""
+    def __init__(self):
+        self.metrics_analyzer = CodeMetricsAnalyzer()
+        self.code_quality_score = 0.0
+        self.test_coverage = 0.0
+        self.security_score = "unknown"
+        self.performance_score = 0.0
+        self.history = []
+        self.thresholds = {
+            "code_quality": 0.85,
+            "test_coverage": 0.90,
+            "security": 0.85,
+            "performance": 0.80
+        }
+
+class AutonomousAgent:
+    """Autonomous agent for the system."""
+    def __init__(self):
+        self.chat_system = None
+        self.refinement_loop = None
+        self.tool_repository = None
+
+    def initialize_tool_repository(self, tool_repository):
+        """Initializes the tool repository."""
+        self.tool_repository = tool_repository
+
+    def build_tool(self, tool_name, task):
+        """Builds a tool."""
+        tool = self.tool_repository.get_tool(tool_name)
+        if tool:
+            tool.run(task)
+            return f"{tool_name} built and ran successfully."
+        else:
+            return f"{tool_name} not found in tool repository."
+
+    def build_agent(self, agent_name, role):
+        """Builds an agent."""
+        agent = self._create_agent(agent_name, role)
+        if agent:
+            return f"{agent_name} agent built successfully."
+        else:
+            return f"{agent_name} agent creation failed."
+
+    def _create_agent(self, agent_name, role):
+        """Creates a new agent."""
+        if role == "development":
+            return self.DevelopmentAgent(agent_name)
+        elif role == "testing":
+            return self.TestingAgent(agent_name)
+        elif role == "security":
+            return self.SecurityAgent(agent_name)
+        else:
+            return None
+
+    class DevelopmentAgent:
+        """Development agent."""
+        def __init__(self, name):
+            self.name = name
+
+        def build_tool(self, tool_name, task):
+            """Builds a development tool."""
+            return f"{self.name} built {tool_name} development tool."
+
+    class TestingAgent:
+        """Testing agent."""
+        def __init__(self, name):
+            self.name = name
+
+        def build_tool(self, tool_name, task):
+            """Builds a testing tool."""
+            return f"{self.name} built {tool_name} testing tool."
+
+    class SecurityAgent:
+        """Security agent."""
+        def __init__(self, name):
+            self.name = name
+
+        def build_tool(self, tool_name, task):
+            """Builds a security tool."""
+            return f"{self.name} built {tool_name} security tool."
+
+    class ToolRepository:
+        """Tool repository."""
+        def __init__(self):
+            self.tools = []
+
+        def add_tool(self, tool):
+            """Adds a tool to the repository."""
+            self.tools.append(tool)
+
+        def get_tool(self, tool_name):
+            """Gets a tool from the repository."""
+            for tool in self.tools:
+                if tool.name == tool_name:
+                    return tool
+
+    class Tool:
+        """Tool."""
+        def __init__(self, name, task):
+            self.name = name
+            self.task = task
+
+        def run(self, task):
+            """Runs the tool."""
+            print(f"Running {self.name} tool for {task}")
+
+    class ChatSystem:
+        """Manages the chat interaction between users and the autonomous system."""
+        def __init__(self, agent: 'AutonomousAgentApp.AutonomousAgent'):
+            self.agent = agent
+            self.chat_history = []
+            self.active_tasks = {}
+            self.command_handlers = {
+                '/task': self.handle_task_command,
+                '/status': self.handle_status_command,
+                '/stop': self.handle_stop_command,
+                '/help': self.handle_help_command,
+                '/modify': self.handle_modify_command
+            }
+
+        def render_chat_interface(self):
+            """Render the chat interface in Streamlit sidebar."""
+            with st.sidebar:
+                st.markdown("---")
+                st.subheader("System Chat")
                 
-                # Enhanced colors
-                self.colors = {
-                    "background": {
-                        "primary": "#ffffff",
-                        "secondary": "#f8fafc", 
-                        "tertiary": "#f1f5f9"
-                    },
-                    "border": "#e2e8f0",
-                    "text": {
-                        "primary": "#1e293b",
-                        "secondary": "#64748b"
-                    },
-                    "primary": "#4f46e5",
-                    "secondary": "#3b82f6",
-                    "success": "#22c55e",
-                    "error": "#ef4444"
-                }
+                # Chat controls
+                if st.button("Clear Chat History"):
+                    self.clear_chat_history()
+
+                # Chat history display
+                chat_container = st.container()
+                with chat_container:
+                    for message in self.chat_history:
+                        self._render_message(message)
+
+                # Input area
+                user_input = st.text_input("Type message/command...", key="chat_input")
+                if st.button("Send", key="send_message"):
+                    self.process_user_input(user_input)
 
-                # Enhanced components
-                self.spacing = sizes.spacing_md
-                self.radius = sizes.radius_md
+class RefinementLoop:
+    """Manages the iterative refinement process."""
+    def __init__(self, pipeline):
+        self.pipeline = pipeline
+        self.max_iterations = 10
+        self.quality_metrics = QualityMetrics()
+        self.logger = logging.getLogger(__name__)
+        self.current_iteration = 0
+        self.history = []
+
+    async def run_refinement_cycle(self, task: str) -> Dict[str, Any]:
+        """Run a complete refinement cycle for the given task."""
+        self.logger.info(f"Starting refinement cycle for task: {task}")
+        self.current_iteration = 0
+        
+        try:
+            while self.current_iteration < self.max_iterations:
+                self.logger.info(f"Starting iteration {self.current_iteration + 1}")
                 
-                # Component styles
-                self.button_primary = {
-                    "background": self.colors["primary"],
-                    "text_color": "#ffffff",
-                    "border": "none",
-                    "padding": "12px 20px",
-                    "border_radius": "8px",
-                    "font_weight": "600",
-                    "hover": {"opacity": 0.9}
-                }
+                # Execute pipeline stages
+                planning_result = await self.pipeline.execute_stage(
+                    self.pipeline.PipelineStage.PLANNING,
+                    {"task": task}
+                )
                 
-                self.input = {
-                    "background": "#ffffff",
-                    "border": f"1px solid {self.colors['border']}",
-                    "border_radius": "8px",
-                    "padding": "12px 16px"
-                }
+                development_result = await self.pipeline.execute_stage(
+                    self.pipeline.PipelineStage.DEVELOPMENT,
+                    planning_result["result"]
+                )
+                
+                testing_result = await self.pipeline.execute_stage(
+                    self.pipeline.PipelineStage.TESTING,
+                    development_result["result"]
+                )
+                
+                # Analyze results
+                quality_analysis = self._analyze_quality(testing_result["result"])
+                
+                # Record iteration history
+                self.history.append({
+                    "iteration": self.current_iteration,
+                    "quality_metrics": quality_analysis,
+                    "timestamp": datetime.now()
+                })
+                
+                # Check if quality requirements are met
+                if self._meets_quality_requirements(quality_analysis):
+                    self.logger.info("Quality requirements met. Refinement cycle complete.")
+                    return self._prepare_final_result(quality_analysis)
+                
+                self.current_iteration += 1
+            
+            return {
+                "status": "max_iterations_reached",
+                "iterations_completed": self.current_iteration,
+                "final_quality": quality_analysis
+            }
+            
+        except Exception as e:
+            self.logger.error(f"Error in refinement cycle: {str(e)}")
+            return {"status": "error", "error": str(e)}
+
+    def _analyze_quality(self, result: Dict[str, Any]) -> Dict[str, float]:
+        """Analyze the quality metrics of the current iteration."""
+        return {
+            "code_quality": self.quality_metrics.code_quality_score,
+            "test_coverage": self.quality_metrics.test_coverage,
+            "security_score": float(self.quality_metrics.security_score)
+        }
+
+    def _meets_quality_requirements(self, quality_analysis: Dict[str, float]) -> bool:
+        """Check if the current quality metrics meet the requirements."""
+        thresholds = self.quality_metrics.thresholds
+        return (
+            quality_analysis["code_quality"] >= thresholds["code_quality"] and
+            quality_analysis["test_coverage"] >= thresholds["test_coverage"] and
+            quality_analysis["security_score"] >= thresholds["security"]
+        )
+
+    def _prepare_final_result(self, quality_analysis: Dict[str, float]) -> Dict[str, Any]:
+        """Prepare the final result of the refinement cycle."""
+        return {
+            "status": "success",
+            "iterations_completed": self.current_iteration,
+            "final_quality": quality_analysis,
+            "history": self.history
+        }
+
+    def get_refinement_history(self) -> List[Dict[str, Any]]:
+        """Get the history of refinement iterations."""
+        return self.history
+
+class AutonomousAgentApp:
+    """Main application class for the Autonomous Agent System."""
+    def __init__(self):
+        self.workspace_manager = WorkspaceManager(workspace_dir=os.getenv('WORKSPACE_DIR', 'workspace'))
+        self.pipeline = self._initialize_pipeline()
+        self.refinement_loop = self.RefinementLoop(pipeline=self.pipeline)  # Corrected line
+        self.interface = self.StreamlitInterface(self)
+        self.autonomous_agent = self.AutonomousAgent()
+        self.tools_repository = self._initialize_tool_repository()
+        self.autonomous_agent.initialize_tool_repository(self.tools_repository)
+        
+    def _initialize_tool_repository(self):
+        """Initializes the tool repository."""
+        tool_repository = ToolRepository()
+        tool_repository.add_tool(Tool(name="Code Review Tool", task="Review Code Quality"))
+        tool_repository.add_tool(Tool(name="Automated Testing Tool", task="Run Automated Tests"))
+        tool_repository.add_tool(Tool(name="Security Audit Tool", task="Run Security Audits"))
+        return tool_repository
+
+    def _initialize_pipeline(self) -> 'AutonomousAgentApp.DevelopmentPipeline':
+        """Initialize the development pipeline."""
+        return self.__class__.DevelopmentPipeline(
+            workspace_manager=self.workspace_manager,
+            tool_manager=self._setup_tool_manager()
+        )
+
+    def _setup_tool_manager(self):
+        """Setup tool manager with configuration."""
+        return ToolManager()
 
-        # --- UI Layout Function ---
-        def create_ui(assistant):
-            with gr.Blocks(theme=ModernDevTheme()) as interface:
-                gr.Markdown(
-                    """
-                    # AI Development Assistant
-                    Get expert help with coding, debugging, and software development
-                    """
+class RefinementLoop:
+    """Manages the iterative refinement process."""
+    def __init__(self, pipeline):
+        self.pipeline = pipeline
+        self.max_iterations = 10
+        self.quality_metrics = QualityMetrics()
+        self.logger = logging.getLogger(__name__)
+        self.current_iteration = 0
+        self.history = []
+
+    async def run_refinement_cycle(self, task: str) -> Dict[str, Any]:
+        """Run a complete refinement cycle for the given task."""
+        self.logger.info(f"Starting refinement cycle for task: {task}")
+        self.current_iteration = 0
+        
+        try:
+            while self.current_iteration < self.max_iterations:
+                self.logger.info(f"Starting iteration {self.current_iteration + 1}")
+                
+                # Execute pipeline stages
+                planning_result = await self.pipeline.execute_stage(
+                    self.pipeline.PipelineStage.PLANNING,
+                    {"task": task}
+                )
+                
+                development_result = await self.pipeline.execute_stage(
+                    self.pipeline.PipelineStage.DEVELOPMENT,
+                    planning_result["result"]
+                )
+                
+                testing_result = await self.pipeline.execute_stage(
+                    self.pipeline.PipelineStage.TESTING,
+                    development_result["result"]
                 )
                 
-                with gr.Row():
-                    with gr.Column(scale=3):
-                        chatbot = gr.Chatbot(
-                            height=600,
-                            show_label=False,
-                            container=True,
-                            bubble_full_width=False,
-                            show_copy_button=True,
-                            avatar_images=("👤", "🤖")
-                        )
-                        
-                        with gr.Row():
-                            msg = gr.Textbox(
-                                placeholder="Ask your development question...",
-                                show_label=False,
-                                container=False,
-                                scale=12
-                            )
-                            submit = gr.Button(
-                                "Send",
-                                variant="primary",
-                                scale=1
-                            )
-                    
-                    with gr.Column(scale=1):
-                        gr.Markdown("### Development Context")
-                        context_info = gr.JSON(
-                            label="Current Task Analysis",
-                            value={}
-                        )
+                # Analyze results
+                quality_analysis = self._analyze_quality(testing_result["result"])
+                
+                # Record iteration history
+                self.history.append({
+                    "iteration": self.current_iteration,
+                    "quality_metrics": quality_analysis,
+                    "timestamp": datetime.now()
+                })
+                
+                # Check if quality requirements are met
+                if self._meets_quality_requirements(quality_analysis):
+                    self.logger.info("Quality requirements met. Refinement cycle complete.")
+                    return self._prepare_final_result(quality_analysis)
+                
+                self.current_iteration += 1
             
-                # Event handlers remain the same
-                msg.submit(assistant.stream_development_response)
-                submit.click(assistant.stream_development_response)
-
-            return interface
-
-    except APIConfigError as e:
-        return gr.Interface(
-            fn=lambda: [None],
-            inputs=None,
-            outputs=gr.Chatbot(label="Development Assistant"),
-            title="System Initialization Error",
-            description=str(e)
+            return {
+                "status": "max_iterations_reached",
+                "iterations_completed": self.current_iteration,
+                "final_quality": quality_analysis
+            }
+            
+        except Exception as e:
+            self.logger.error(f"Error in refinement cycle: {str(e)}")
+            return {"status": "error", "error": str(e)}
+
+    def _analyze_quality(self, result: Dict[str, Any]) -> Dict[str, float]:
+        """Analyze the quality metrics of the current iteration."""
+        return {
+            "code_quality": self.quality_metrics.code_quality_score,
+            "test_coverage": self.quality_metrics.test_coverage,
+            "security_score": float(self.quality_metrics.security_score)
+        }
+
+    def _meets_quality_requirements(self, quality_analysis: Dict[str, float]) -> bool:
+        """Check if the current quality metrics meet the requirements."""
+        thresholds = self.quality_metrics.thresholds
+        return (
+            quality_analysis["code_quality"] >= thresholds["code_quality"] and
+            quality_analysis["test_coverage"] >= thresholds["test_coverage"] and
+            quality_analysis["security_score"] >= thresholds["security"]
         )
-    except Exception as e:
-        return gr.Interface(
-            fn=lambda: [None],
-            inputs=None,
-            outputs=gr.Chatbot(label="Development Assistant"),
-            title="Interface Malfunction",
-            description=f"System interface encountered an unexpected malfunction: {str(e)}"
+
+    def _prepare_final_result(self, quality_analysis: Dict[str, float]) -> Dict[str, Any]:
+        """Prepare the final result of the refinement cycle."""
+        return {
+            "status": "success",
+            "iterations_completed": self.current_iteration,
+            "final_quality": quality_analysis,
+            "history": self.history
+        }
+
+    def get_refinement_history(self) -> List[Dict[str, Any]]:
+        """Get the history of refinement iterations."""
+        return self.history    
+
+    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 AutonomousAgentApp:
+    """Main application class for the Autonomous Agent System."""
+
+    def __init__(self):
+        self.workspace_manager = WorkspaceManager(workspace_dir=os.getenv('WORKSPACE_DIR', 'workspace'))
+        self.pipeline = self._initialize_pipeline()
+        self.refinement_loop = self.RefinementLoop(pipeline=self.pipeline)
+        self.interface = self.StreamlitInterface(self)
+        self.autonomous_agent = self.AutonomousAgent()
+        self.tools_repository = self._initialize_tool_repository()
+        self.autonomous_agent.initialize_tool_repository(self.tools_repository)
+
+    def _initialize_tool_repository(self):
+        """Initializes the tool repository."""
+        tool_repository = ToolRepository()
+        tool_repository.add_tool(Tool(name="Code Review Tool", task="Review Code Quality"))
+        tool_repository.add_tool(Tool(name="Automated Testing Tool", task="Run Automated Tests"))
+        tool_repository.add_tool(Tool(name="Security Audit Tool", task="Run Security Audits"))
+        return tool_repository
+
+    def _initialize_pipeline(self) -> 'DevelopmentPipeline':
+        """Initialize the development pipeline."""
+        return self.DevelopmentPipeline(
+            workspace_manager=self.workspace_manager,
+            tool_manager=self._setup_tool_manager()
         )
 
-# --- Main execution ---
+    def _setup_tool_manager(self):
+        """Setup tool manager with configuration."""
+        return ToolManager()
+
+    class DevelopmentPipeline:
+        """Manages the development pipeline stages."""
+        
+        class PipelineStage(Enum):
+            PLANNING = "planning"
+            DEVELOPMENT = "development"
+            TESTING = "testing"
+            REVIEW = "review"
+
+        def __init__(self, workspace_manager: WorkspaceManager, tool_manager: 'ToolManager'):
+            self.workspace_manager = workspace_manager
+            self.tool_manager = tool_manager
+            self.logger = logging.getLogger(__name__)
+
+        async def execute_stage(self, stage: PipelineStage, input_data: Dict) -> Dict[str, Any]:
+            """Execute a pipeline stage and return results."""
+            self.logger.info(f"Executing pipeline stage: {stage.value}")
+            
+            try:
+                if stage == self.PipelineStage.PLANNING:
+                    return await self._handle_planning(input_data)
+                elif stage == self.PipelineStage.DEVELOPMENT:
+                    return await self._handle_development(input_data)
+                elif stage == self.PipelineStage.TESTING:
+                    return await self._handle_testing(input_data)
+                else:
+                    raise ValueError(f"Unknown pipeline stage: {stage}")
+            except Exception as e:
+                self.logger.error(f"Error in {stage.value} stage: {str(e)}")
+                return {"status": "error", "error": str(e)}
+
+        async def _handle_planning(self, input_data: Dict) -> Dict:
+            """Handle planning stage execution."""
+            # Example implementation
+            return {
+                "status": "success",
+                "result": {"plan": "Sample plan"},
+                "artifacts": ["requirements.txt"]
+            }
+
+        async def _handle_development(self, input_data: Dict) -> Dict:
+            """Handle development stage execution."""
+            # Example implementation
+            return {
+                "status": "success",
+                "result": {"code": "print('Hello World')"},
+                "artifacts": ["main.py"]
+            }
+
+        async def _handle_testing(self, input_data: Dict) -> Dict:
+            """Handle testing stage execution."""
+            # Example implementation
+            return {
+                "status": "success",
+                "result": {"test_results": "All tests passed"},
+                "artifacts": ["test_report.html"]
+            }
+
+    class ToolManager:
+        """Manages tools used by the development pipeline."""
+        
+        def __init__(self):
+            self.tools = {}
+            self.logger = logging.getLogger(__name__)
+
+        def register_tool(self, name: str, tool: Any):
+            """Register a new tool."""
+            self.tools[name] = tool
+            self.logger.info(f"Registered tool: {name}")
+
+        def get_tool(self, name: str) -> Optional[Any]:
+            """Retrieve a registered tool."""
+            return self.tools.get(name)
+            
+    @dataclass
+    class QualityMetrics:
+        """Advanced quality metrics tracking and analysis"""
+        metrics_analyzer: CodeMetricsAnalyzer = None
+        code_quality_score: float = 0.0
+        test_coverage: float = 0.0
+        security_score: str = "unknown"
+        performance_score: float = 0.0
+
+        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
+            }
+
+    class CodeAnalyzer:
+        def __init__(self):
+            self.history = []
+            self.code_quality_score = 0.0
+            self.test_coverage = 0.0
+            self.security_score = "0.0"
+
+        def _get_project_files(self, project_name: str) -> list:
+            # Dummy implementation for example purposes
+            return ["file1.py", "file2.py"]
+
+        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:
+                print(f"An error occurred: {e}")
+                return {}
+
+            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 StreamlitInterface:
+        """Streamlit UI integration for the Autonomous Agent system."""
+        
+        def main():
+            autonomous_agent_app = AutonomousAgentApp()
+            app.run()
+
+        def __init__(self, app: 'AutonomousAgentApp'):  # Use string forward reference
+            self.app = app
+            self.chat_system = self.app.ChatSystem(self.app.autonomous_agent)
+
+        def render_main_interface(self):
+            """Render the main Streamlit interface."""
+            st.title("Autonomous Agent System")
+
+            # Add chat interface to sidebar
+            self.chat_system.render_chat_interface()
+
+            # Main content tabs
+            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__":
-    demo = create_dev_assistant_interface()
-    if demo:
-        demo.launch()
-    else:
-        print("Gradio demo could not be initialized due to errors.")
+    app = AutonomousAgentApp()  # Create an instance of the app
+    app.run()  # Call the run method to start the application