app.py

import gradio as gr
import json
import logging
from enum import Enum, auto
from typing import Protocol, List, Dict, Any
from dataclasses import dataclass, field
from datetime import datetime
import difflib
import pytest
from concurrent.futures import ThreadPoolExecutor
import asyncio

# Initialize logger
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

class AgentRole(Enum):
    ARCHITECT = auto()
    FRONTEND = auto()
    BACKEND = auto()
    DATABASE = auto()
    TESTER = auto()
    REVIEWER = auto()
    DEPLOYER = auto()

@dataclass
class AgentDecision:
    agent: 'Agent'
    decision: str
    confidence: float
    reasoning: str
    timestamp: datetime = field(default_factory=datetime.now)
    dependencies: List['AgentDecision'] = field(default_factory=list)

class AgentProtocol(Protocol):
    async def decide(self, context: Dict[str, Any]) -> AgentDecision: ...
    async def validate(self, decision: AgentDecision) -> bool: ...
    async def implement(self, decision: AgentDecision) -> Any: ...
    async def test(self, implementation: Any) -> bool: ...

@dataclass
class Agent:
    role: AgentRole
    name: str
    autonomy_level: float  # 0-10
    expertise: List[str]
    confidence_threshold: float = 0.7

    async def reason(self, context: Dict[str, Any]) -> str:
        """Generate reasoning based on context and expertise"""
        prompt = f"""
        As {self.name}, a {self.role.name} expert with expertise in {', '.join(self.expertise)},
        analyze the following context and provide reasoning:

        Context:
        {json.dumps(context, indent=2)}

        Consider:
        1. Required components and their interactions
        2. Potential challenges and solutions
        3. Best practices and patterns
        4. Security and performance implications

        Reasoning:
        """
        return await self.rag_system.generate_reasoning(prompt)

class AgentSystem:
    def __init__(self, config: Config):
        self.config = config
        self.autonomy_level = 0.0  # 0-10
        self.agents: Dict[AgentRole, Agent] = self._initialize_agents()
        self.decision_history: List[AgentDecision] = []
        self.executor = ThreadPoolExecutor(max_workers=10)
        self.rag_system = RAGSystem(config)

    def _initialize_agents(self) -> Dict[AgentRole, Agent]:
        return {
            AgentRole.ARCHITECT: Agent(
                role=AgentRole.ARCHITECT,
                name="System Architect",
                autonomy_level=self.autonomy_level,
                expertise=["system design", "architecture patterns", "integration"]
            ),
            AgentRole.FRONTEND: Agent(
                role=AgentRole.FRONTEND,
                name="Frontend Developer",
                autonomy_level=self.autonomy_level,
                expertise=["UI/UX", "React", "Vue", "Angular"]
            ),
            AgentRole.BACKEND: Agent(
                role=AgentRole.BACKEND,
                name="Backend Developer",
                autonomy_level=self.autonomy_level,
                expertise=["API design", "database", "security"]
            ),
            AgentRole.TESTER: Agent(
                role=AgentRole.TESTER,
                name="Quality Assurance",
                autonomy_level=self.autonomy_level,
                expertise=["testing", "automation", "quality assurance"]
            ),
            AgentRole.REVIEWER: Agent(
                role=AgentRole.REVIEWER,
                name="Code Reviewer",
                autonomy_level=self.autonomy_level,
                expertise=["code quality", "best practices", "security"]
            ),
        }

    async def set_autonomy_level(self, level: float) -> None:
        """Update autonomy level for all agents"""
        self.autonomy_level = max(0.0, min(10.0, level))
        for agent in self.agents.values():
            agent.autonomy_level = self.autonomy_level

    async def process_request(self, description: str, context: Dict[str, Any] = None) -> Dict[str, Any]:
        """Process a user request with current autonomy level"""
        try:
            context = context or {}
            context['description'] = description
            context['autonomy_level'] = self.autonomy_level

            # Start with architect's decision
            arch_decision = await self.agents[AgentRole.ARCHITECT].decide(context)
            self.decision_history.append(arch_decision)

            if self.autonomy_level < 3:
                # Low autonomy: Wait for user confirmation
                return {
                    'status': 'pending_confirmation',
                    'decision': arch_decision,
                    'next_steps': self._get_next_steps(arch_decision)
                }

            # Medium to high autonomy: Proceed with implementation
            implementation_plan = await self._create_implementation_plan(arch_decision)

            if self.autonomy_level >= 7:
                # High autonomy: Automatic implementation and testing
                return await self._automated_implementation(implementation_plan)

            # Medium autonomy: Return plan for user review
            return {
                'status': 'pending_review',
                'plan': implementation_plan,
                'decisions': self.decision_history
            }

        except Exception as e:
            logger.error(f"Error in request processing: {e}")
            return {'status': 'error', 'message': str(e)}

    async def _create_implementation_plan(self, arch_decision: AgentDecision) -> Dict[str, Any]:
        """Create detailed implementation plan based on architect's decision"""
        tasks = []

        # Frontend tasks
        if 'frontend' in arch_decision.decision.lower():
            tasks.append(self._create_frontend_tasks(arch_decision))

        # Backend tasks
        if 'backend' in arch_decision.decision.lower():
            tasks.append(self._create_backend_tasks(arch_decision))

        # Testing tasks
        tasks.append(self._create_testing_tasks(arch_decision))

        return {
            'tasks': await asyncio.gather(*tasks),
            'dependencies': arch_decision.dependencies,
            'estimated_time': self._estimate_implementation_time(tasks)
        }

    async def _automated_implementation(self, plan: Dict[str, Any]) -> Dict[str, Any]:
        """Execute implementation plan automatically"""
        results = {
            'frontend': None,
            'backend': None,
            'tests': None,
            'review': None
        }

        try:
            # Parallel implementation of frontend and backend
            impl_tasks = []
            if 'frontend' in plan['tasks']:
                impl_tasks.append(self._implement_frontend(plan['tasks']['frontend']))
            if 'backend' in plan['tasks']:
                impl_tasks.append(self._implement_backend(plan['tasks']['backend']))

            implementations = await asyncio.gather(*impl_tasks)

            # Testing
            test_results = await self.agents[AgentRole.TESTER].test(implementations)

            # Code review
            review_results = await self.agents[AgentRole.REVIEWER].validate({
                'implementations': implementations,
                'test_results': test_results
            })

            return {
                'status': 'completed',
                'implementations': implementations,
                'test_results': test_results,
                'review': review_results,
                'decisions': self.decision_history
            }

        except Exception as e:
            return {
                'status': 'error',
                'message': str(e),
                'partial_results': results
            }

    async def _handle_implementation_failure(self, error: Exception, context: Dict[str, Any]) -> Dict[str, Any]:
        """Handle implementation failures with adaptive response"""
        try:
            # Analyze error
            error_analysis = await self.agents[AgentRole.REVIEWER].reason({
                'error': str(error),
                'context': context
            })

            # Determine correction strategy
            if self.autonomy_level >= 8:
                # High autonomy: Attempt automatic correction
                correction = await self._attempt_automatic_correction(error_analysis)
                if correction['success']:
                    return await self.process_request(context['description'], correction['context'])

            return {
                'status': 'failure',
                'error': str(error),
                'analysis': error_analysis,
                'suggested_corrections': self._suggest_corrections(error_analysis)
            }

        except Exception as e:
            logger.error(f"Error handling implementation failure: {e}")
            return {'status': 'critical_error', 'message': str(e)}

class AgentTester:
    def __init__(self):
        self.test_suites = {
            'frontend': self._test_frontend,
            'backend': self._test_backend,
            'integration': self._test_integration
        }

    async def _test_frontend(self, implementation: Dict[str, Any]) -> Dict[str, Any]:
        """Run frontend tests"""
        results = {
            'passed': [],
            'failed': [],
            'warnings': []
        }

        # Component rendering tests
        for component in implementation.get('components', []):
            try:
                # Test component rendering
                result = await self._test_component_render(component)
                if result['success']:
                    results['passed'].append(f"Component {component['name']} renders correctly")
                else:
                    results['failed'].append(f"Component {component['name']}: {result['error']}")
            except Exception as e:
                results['failed'].append(f"Error testing {component['name']}: {str(e)}")

        return results

    async def _test_backend(self, implementation: Dict[str, Any]) -> Dict[str, Any]:
        """Run backend tests"""
        results = {
            'passed': [],
            'failed': [],
            'warnings': []
        }

        # API endpoint tests
        for endpoint in implementation.get('endpoints', []):
            try:
                # Test endpoint functionality
                result = await self._test_endpoint(endpoint)
                if result['success']:
                    results['passed'].append(f"Endpoint {endpoint['path']} works correctly")
                else:
                    results['failed'].append(f"Endpoint {endpoint['path']}: {result['error']}")
            except Exception as e:
                results['failed'].append(f"Error testing {endpoint['path']}: {str(e)}")

        return results

    async def _test_integration(self, implementation: Dict[str, Any]) -> Dict[str, Any]:
        """Run integration tests"""
        results = {
            'passed': [],
            'failed': [],
            'warnings': []
        }

        # Test frontend-backend integration
        try:
            result = await self._test_frontend_backend_integration(implementation)
            if result['success']:
                results['passed'].append("Frontend-Backend integration successful")
            else:
                results['failed'].append(f"Integration error: {result['error']}")
        except Exception as e:
            results['failed'].append(f"Integration test error: {str(e)}")

        return results

class AgentValidator:
    def __init__(self):
        self.validators = {
            'code_quality': self._validate_code_quality,
            'security': self._validate_security,
            'performance': self._validate_performance
        }

    async def validate_implementation(self, implementation: Dict[str, Any]) -> Dict[str, Any]:
        """Validate implementation against best practices"""
        results = {
            'passed': [],
            'failed': [],
            'warnings': []
        }

        for validator_name, validator in self.validators.items():
            try:
                validation_result = await validator(implementation)
                results['passed'].extend(validation_result.get('passed', []))
                results['failed'].extend(validation_result.get('failed', []))
                results['warnings'].extend(validation_result.get('warnings', []))
            except Exception as e:
                results['warnings'].append(f"Validator {validator_name} error: {str(e)}")

        return results

class GradioInterface:
    def __init__(self, config: Config):
        self.config = config
        self.agent_system = AgentSystem(config)
        self.explorer = CodeExplorer()
        self.backend_generator = BackendGenerator(config)
        self.file_handler = FileHandler()
        self.preview_size = {"width": "100%", "height": "600px"}
        self.is_preview_loading = False

    def launch(self) -> None:
        with gr.Blocks(theme=gr.themes.Base()) as interface:
            # Header
            gr.Markdown("# AI-Powered Development Environment")

            with gr.Tabs() as tabs:
                # Code Generation Tab
                with gr.Tab("Code Generation"):
                    with gr.Row():
                        with gr.Column(scale=1):
                            code_input = gr.Code(
                                label="Input Code",
                                language="python",
                                lines=20
                            )
                            generate_button = gr.Button("Generate")

                        with gr.Column(scale=1):
                            code_output = gr.Code(
                                label="Generated Code",
                                language="python",
                                lines=20
                            )
                            status_message = gr.Markdown("")

                # Agent Control Tab
                with gr.Tab("Agent Control"):
                    with gr.Row():
                        autonomy_slider = gr.Slider(
                            minimum=0,
                            maximum=10,
                            value=0,
                            step=0.1,
                            label="Agent Autonomy Level",
                            info="0: Manual, 10: Fully Autonomous"
                        )

                    with gr.Row():
                        with gr.Column(scale=1):
                            project_description = gr.Textbox(
                                label="Project Description",
                                placeholder="Describe what you want to build...",
                                lines=5
                            )

                            with gr.Accordion("Advanced Options", open=False):
                                framework_choice = gr.Dropdown(
                                    choices=["React", "Vue", "Angular", "FastAPI", "Flask", "Django"],
                                    multiselect=True,
                                    label="Preferred Frameworks"
                                )
                                architecture_style = gr.Radio(
                                    choices=["Monolithic", "Microservices", "Serverless"],
                                    label="Architecture Style",
                                    value="Monolithic"
                                )
                                testing_preference = gr.Checkbox(
                                    label="Include Tests",
                                    value=True
                                )

                            process_button = gr.Button("Process Request")

                        with gr.Column(scale=2):
                            with gr.Tabs() as agent_tabs:
                                with gr.Tab("Decision Log"):
                                    decision_log = gr.JSON(
                                        label="Agent Decisions",
                                        show_label=True
                                    )

                                with gr.Tab("Implementation"):
                                    with gr.Tabs() as impl_tabs:
                                        with gr.Tab("Frontend"):
                                            frontend_code = gr.Code(
                                                label="Frontend Implementation",
                                                language="javascript",
                                                lines=20
                                            )
                                        with gr.Tab("Backend"):
                                            backend_code = gr.Code(
                                                label="Backend Implementation",
                                                language="python",
                                                lines=20
                                            )
                                        with gr.Tab("Database"):
                                            database_code = gr.Code(
                                                label="Database Schema",
                                                language="sql",
                                                lines=20
                                            )

                                with gr.Tab("Test Results"):
                                    test_results = gr.JSON(
                                        label="Test Results"
                                    )
                                    rerun_tests_button = gr.Button("Rerun Tests")

                                with gr.Tab("Agent Chat"):
                                    agent_chat = gr.Chatbot(
                                        label="Agent Discussion",
                                        height=400
                                    )
                                    chat_input = gr.Textbox(
                                        label="Ask Agents",
                                        placeholder="Type your question here..."
                                    )
                                    chat_button = gr.Button("Send")

                    with gr.Row():
                        status_output = gr.Markdown("System ready.")
                        with gr.Column():
                            progress = gr.Progress(
                                label="Implementation Progress",
                                show_progress=True
                            )

                # Explorer Tab
                with gr.Tab("Code Explorer"):
                    with gr.Row():
                        with gr.Column(scale=1):
                            component_list = gr.Dropdown(
                                label="Components",
                                choices=list(self.explorer.components.keys()),
                                interactive=True
                            )
                            refresh_button = gr.Button("Refresh")

                            with gr.Accordion("Add Component", open=False):
                                component_name = gr.Textbox(label="Name")
                                component_type = gr.Dropdown(
                                    label="Type",
                                    choices=['frontend', 'backend', 'database', 'api']
                                )
                                component_code = gr.Code(
                                    label="Code",
                                    language="python"
                                )
                                add_button = gr.Button("Add")

                        with gr.Column(scale=2):
                            component_details = gr.JSON(
                                label="Component Details"
                            )
                            dependency_graph = gr.Plot(
                                label="Dependencies"
                            )

            # Event Handlers
            async def update_autonomy(level):
                await self.agent_system.set_autonomy_level(level)
                return f"Autonomy level set to {level}"

            async def process_request(description, level):
                try:
                    # Update autonomy level
                    await self.agent_system.set_autonomy_level(level)

                    # Process request
                    result = await self.agent_system.process_request(description)

                    # Update UI based on result status
                    if result['status'] == 'pending_confirmation':
                        return {
                            decision_log: result['decision'],
                            frontend_code: "",
                            backend_code: "",
                            database_code: "",
                            test_results: {},
                            status_output: "Waiting for user confirmation...",
                            progress: 0.3
                        }
                    elif result['status'] == 'completed':
                        return {
                            decision_log: result['decisions'],
                            frontend_code: result['implementations'].get('frontend', ''),
                            backend_code: result['implementations'].get('backend', ''),
                            database_code: result['implementations'].get('database', ''),
                            test_results: result['test_results'],
                            status_output: "Implementation completed successfully!",
                            progress: 1.0
                        }
                    else:
                        return {
                            status_output: f"Error: {result['message']}",
                            progress: 0
                        }

                except Exception as e:
                    return {
                        status_output: f"Error: {str(e)}",
                        progress: 0
                    }

            async def handle_chat(message, history):
                try:
                    response = await self.agent_system.process_chat(message, history)
                    history.append((message, response))
                    return history
                except Exception as e:
                    logger.error(f"Chat error: {e}")
                    return history + [(message, f"Error: {str(e)}")]

            async def refresh_components():
                return gr.Dropdown(choices=list(self.explorer.components.keys()))

            async def add_component(name, type, code):
                try:
                    success = await self.explorer.add_component(name, type, code)
                    return {
                        component_list: gr.Dropdown(choices=list(self.explorer.components.keys())),
                        status_output: "Component added successfully" if success else "Failed to add component"
                    }
                except Exception as e:
                    return {
                        status_output: f"Error adding component: {str(e)}"
                    }

            async def show_component_details(name):
                try:
                    component = await self.explorer.get_component(name)
                    if not component:
                        return None, None

                    graph = await self.explorer.visualize_dependencies(name)
                    return component, graph
                except Exception as e:
                    logger.error(f"Error showing component details: {e}")
                    return None, None

            # Connect event handlers
            autonomy_slider.change(
                fn=update_autonomy,
                inputs=[autonomy_slider],
                outputs=[status_output]
            )

            process_button.click(
                fn=process_request,
                inputs=[
                    project_description,
                    autonomy_slider,
                ],
                outputs=[
                    decision_log,
                    frontend_code,
                    backend_code,
                    database_code,
                    test_results,
                    status_output,
                    progress
                ]
            )

            chat_button.click(
                fn=handle_chat,
                inputs=[chat_input, agent_chat],
                outputs=[agent_chat]
            )

            refresh_button.click(
                fn=refresh_components,
                outputs=[component_list]
            )

            add_button.click(
                fn=add_component,
                inputs=[component_name, component_type, component_code],
                outputs=[component_list, status_output]
            )

            component_list.change(
                fn=show_component_details,
                inputs=[component_list],
                outputs=[component_details, dependency_graph]
            )

        # Launch the interface
        interface.launch(
            server_port=self.config.port,
            share=self.config.share,
            debug=self.config.debug
        )