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 )