definitions.py

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 pathlib import Path

class PipelineStage(Enum):
    """Pipeline stages for the development process."""
    PLANNING = 1
    DEVELOPMENT = 2
    TESTING = 3

# Set logging level from environment variable
logging.basicConfig(level=os.getenv('LOG_LEVEL', 'INFO'))

def main():
    autonomous_agent_app = AutonomousAgentApp()
    app.run()

class AutonomousAgentApp:
    """Main application class for the Autonomous Agent System"""
    
    def __init__(self):
        self.autonomous_agent = AutonomousAgent(self)
        self.workspace_manager = self.autonomous_agent.workspace_manager
        self.refinement_loop = self.autonomous_agent.refinement_loop
        self.interface = self.autonomous_agent.interface

    def run(self):
        """Main entry point for the application"""
        self.interface.render_main_interface()

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

    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 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, app):
        self.app = app
        self.workspace_manager = WorkspaceManager(workspace_dir=os.getenv('WORKSPACE_DIR', 'workspace'))
        self.pipeline = self._initialize_pipeline()
        self.refinement_loop = RefinementLoop(pipeline=self.pipeline)
        self.interface = self.StreamlitInterface(self)
        self.tools_repository = self._initialize_tool_repository()
        self.chat_system = ChatSystem(self)

    def _setup_tool_manager(self):
        """Setup tool manager with configuration."""
        return ToolManager()
    
    def _initialize_pipeline(self) -> 'DevelopmentPipeline':
        """Initialize the development pipeline."""
        return DevelopmentPipeline(
            workspace_manager=self.workspace_manager,
            tool_manager=self._setup_tool_manager()
        )

    def initialize_tool_repository(self, tool_repository: object) -> None:
        """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 DevelopmentAgent(agent_name)
        elif role == "testing":
            return TestingAgent(agent_name)
        elif role == "security":
            return SecurityAgent(agent_name)
        else:
            return None

class DevelopmentPipeline:
    def __init__(self, workspace_manager, tool_manager):
        """Initialize the development pipeline with the given workspace and tool managers."""
        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 == PipelineStage.PLANNING:
                return await self._handle_planning(input_data)
            elif stage == PipelineStage.DEVELOPMENT:
                return await self._handle_development(input_data)
            elif stage == 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."""
        self.logger.info("Handling planning stage")
        
        try:
            task = input_data.get("task", "")
            if not task:
                raise ValueError("No task provided for planning")
    
            # Step 1: Analyze the task and break it into subtasks
            subtasks = self._break_down_task(task)
            
            # Step 2: Generate a development plan
            development_plan = {
                "task": task,
                "subtasks": subtasks,
                "milestones": self._define_milestones(subtasks),
                "timeline": self._estimate_timeline(subtasks)
            }
    
            # Step 3: Create initial project artifacts (e.g., requirements.txt)
            self.workspace_manager.create_file("requirements.txt", self._generate_requirements(subtasks))
        
            return {
                "status": "success",
                "result": {"plan": development_plan},
                "artifacts": ["requirements.txt"]
            }

        except Exception as e:
            self.logger.error(f"Error in planning stage: {str(e)}")
            return {"status": "error", "error": str(e)}

    def _break_down_task(self, task: str) -> List[str]:
        """Break down a task into smaller subtasks."""
        return [f"Subtask {i+1}: {part}" for i, part in enumerate(task.split(","))]

    def _define_milestones(self, subtasks: List[str]) -> List[str]:
        """Define milestones based on subtasks."""
        return [f"Complete {subtask}" for subtask in subtasks]

    def _estimate_timeline(self, subtasks: List[str]) -> Dict[str, int]:
        """Estimate a timeline for the subtasks."""
        return {subtask: 1 for subtask in subtasks}
    
    def _generate_requirements(self, subtasks: List[str]) -> str:
        """Generate a requirements document based on subtasks."""
        return "\n".join([f"Requirement: {subtask}" for subtask in subtasks])

    async def _handle_development(self, input_data: Dict) -> Dict:
        """Handle development stage execution."""
        self.logger.info("Handling development stage")
        
        try:
            plan = input_data.get("result", {}).get("plan", {})
            if not plan:
                raise ValueError("No development plan provided")
    
            # Step 1: Generate boilerplate code
            self.workspace_manager.create_file("main.py", self._generate_boilerplate_code(plan))
    
            # Step 2: Implement functionality for each subtask
            for subtask in plan.get("subtasks", []):
                self._implement_subtask(subtask)
    
            return {
                "status": "success",
                "result": {"code": "print('Hello World')"},
                "artifacts": ["main.py"]
            }

        except Exception as e:
            self.logger.error(f"Error in development stage: {str(e)}")
            return {"status": "error", "error": str(e)}

    def _generate_boilerplate_code(self, plan: Dict) -> str:
        """Generated boilerplate code based on the development plan."""
        return """f"# Project: {plan.get('task', 'Untitled')}
               # Subtasks:
               {''.join([f'# {subtask} for subtask in plan.get('subtasks', [])])}
               def main():
                   print('Hello World')
               if __name__ == '__main__':
                   main()"""""
    
    def _implement_subtask(self, subtask: str) -> None:
        """Implement functionality for a subtask."""
        with open(os.path.join(self.workspace_manager.workspace_dir, "main.py"), "a") as file:
            file.write(f"\n# Implementation for {subtask}\n")

    async def _handle_testing(self, input_data: Dict) -> Dict:
        """Handle testing stage execution."""
        self.logger.info("Handling testing stage")

        try:
            code_path = os.path.join(self.workspace_manager.workspace_dir, "main.py")
            if not os.path.exists(code_path):
                raise FileNotFoundError("No code found for testing")
    
            # Step 1: Run unit tests
            test_results = self._run_unit_tests(code_path)
    
            # Step 2: Generate a test report
            test_report = self._generate_test_report(test_results)
            self.workspace_manager.create_file("test_report.html", test_report)
    
            return {
                "status": "success",
                "result": {"test_results": test_results},
                "artifacts": ["test_report.html"]
            }

        except Exception as e:
            self.logger.error(f"Error in testing stage: {str(e)}")
            return {"status": "error", "error": str(e)}

    def _run_unit_tests(self, code_path: str) -> Dict[str, Any]:
        """Run unit tests on the code."""
        return {
            "tests_run": 5,
            "tests_passed": 5,
            "tests_failed": 0,
            "coverage": "100%"
        }

    def _generate_test_report(self, test_results: Dict) -> str:
        """Generate an HTML test report."""
        return f"""
        <html>
            <head><title>Test Report</title></head>
            <body>
                <h1>Test Report</h1>
                <ul>
                    <li>Tests Run: {test_results.get('tests_run', 0)}</li>
                    <li>Tests Passed: {test_results.get('tests_passed', 0)}</li>
                    <li>Tests Failed: {test_results.get('tests_failed', 0)}</li>
                    <li>Coverage: {test_results.get('coverage', '0%')}</li>
                </ul>
            </body>
        </html>
        """

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(
                    PipelineStage.PLANNING,
                    {"task": task}
                )
                
                development_result = await self.pipeline.execute_stage(
                    PipelineStage.DEVELOPMENT,
                    planning_result["result"]
                )
                
                testing_result = await self.pipeline.execute_stage(
                    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 ChatSystem:
    """Manages chat interaction between users and the autonomous system."""
    def __init__(self, agent):
        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
        }
        self.logger = logging.getLogger(__name__)

    def render_chat_interface(self):
        """Render the chat interface in Streamlit sidebar."""
        with st.sidebar:
            st.markdown("---")
            st.subheader("System Chat")
            
            if st.button("Clear Chat History"):
                self.clear_chat_history()
            
            chat_container = st.container()
            with chat_container:
                for message in self.chat_history:
                    self._render_message(message)

                user_input = st.text_input("Type message/command...", key="chat_input")
                if st.button("Send", key="send_message"):
                    self.process_user_input(user_input)

    def handle_task_command(self, input_data: Dict):
        """Handle task command."""
        self.logger.info("Handling task command")
        task = input_data.get("task", input_data.get("input", ""))
        asyncio.create_task(self.agent.app.refinement_loop.run_refinement_cycle(task))
        return "Task command initiated"

    def handle_status_command(self, input_data: Dict):
        """Handle status command."""
        self.logger.info("Handling status command")
        return {
            "status": "success",
            "history": self.agent.app.refinement_loop.get_refinement_history()
        }

    def handle_stop_command(self, input_data: Dict):
        """Handle stop command."""
        self.logger.info("Handling stop command")
        # Add logic to stop current task
        return "Stop command handled"

    def handle_help_command(self, input_data: Dict):
        """Handle help command."""
        self.logger.info("Handling help command")
        return """
        Available commands:
        /task <task_name> - Run the autonomous agent with the given task
        /status - Get the current status of the refinement cycle
        /stop - Stop the current task
        /help - Show this help message
        /modify - Modify current task parameters
        """

    def handle_modify_command(self, input_data: Dict):
        """Handle modify command."""
        self.logger.info("Handling modify command")
        return "Modify command handled"

    def clear_chat_history(self):
        """Clear the chat history."""
        self.logger.info("Clearing chat history")
        self.chat_history.clear()
        return "Chat history cleared"

    def _render_message(self, message: str):
        """Render a chat message."""
        st.write(message)

    def process_user_input(self, user_input: str):
        """Process user input."""
        self.logger.info("Processing user input")
        command = user_input.strip().split()[0]
        if command in self.command_handlers:
            result = self.command_handlers[command]({"input": user_input})
            self.chat_history.append(f"User: {user_input}")
            self.chat_history.append(f"System: {result}")

class StreamlitInterface:
    """Streamlit UI integration for the Autonomous Agent system."""
    
    def __init__(self, app):
        self.app = app
        self.chat_system = 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:
                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."""
        st.header("Workspace Management")
        workspace_tree = self.app.workspace_manager.get_workspace_tree()
        st.write(workspace_tree)

    def render_settings_tab(self):
        """Render the Settings tab."""
        st.header("Settings")
        
        # Refinement Process Settings
        st.subheader("Refinement Process")
        max_iterations = st.slider(
            "Maximum Iterations",
            min_value=1,
            max_value=20,
            value=self.app.refinement_loop.max_iterations
        )
        if max_iterations != self.app.refinement_loop.max_iterations:
            self.app.refinement_loop.max_iterations = max_iterations
            st.success(f"Updated maximum iterations to {max_iterations}")

        # Quality Metrics Settings
        st.subheader("Quality Metrics")
        metrics = self.app.refinement_loop.quality_metrics
        
        col1, col2 = st.columns(2)
        with col1:
            code_quality = st.slider(
                "Code Quality Threshold",
                0.0, 1.0,
                metrics.thresholds["code_quality"]
            )
        with col2:
            test_coverage = st.slider(
                "Test Coverage Threshold",
                0.0, 1.0,
                metrics.thresholds["test_coverage"]
            )

        if st.button("Update Thresholds"):
            metrics.thresholds.update({
                "code_quality": code_quality,
                "test_coverage": test_coverage
            })
            st.success("Quality thresholds updated")

if __name__ == "__main__":
    app = AutonomousAgentApp()
    app.interface.render_main_interface()