"""
Agent orchestrator for coordinating multiple AI agents
"""
import asyncio
import uuid
from typing import Dict, Any, Optional, List
from datetime import datetime
import structlog
logger = structlog.get_logger()
class AgentOrchestrator:
"""Coordinates multiple specialized AI agents for software generation"""
def __init__(self, correlation_id: str):
self.correlation_id = correlation_id
self.logger = logger.bind(correlation_id=correlation_id)
async def generate_complete_application(
self,
description: str,
project_type: str,
technology_stack: Optional[str] = None,
user_context: Optional[Dict[str, Any]] = None
) -> Dict[str, Any]:
"""
Generate a complete application with all components
"""
self.logger.info(
"starting_application_generation",
project_type=project_type,
technology_stack=technology_stack,
description_length=len(description)
)
# Simulate generation process
await asyncio.sleep(2)
# Placeholder implementation - in production this would coordinate multiple agents
result = {
"status": "completed",
"technology_stack": technology_stack or f"{project_type}-default-stack",
"files_count": 15,
"summary": f"Generated {project_type} application based on: {description[:100]}...",
"project_structure": self._generate_project_structure(project_type),
"components_generated": [
"frontend",
"backend",
"database",
"tests",
"deployment"
]
}
self.logger.info(
"application_generation_completed",
files_count=result["files_count"],
technology_stack=result["technology_stack"]
)
return result
async def generate_component(
self,
component_type: str,
description: str,
project_context: Optional[str] = None,
user_context: Optional[Dict[str, Any]] = None
) -> Dict[str, Any]:
"""
Generate a specific application component
"""
self.logger.info(
"starting_component_generation",
component_type=component_type,
description_length=len(description)
)
# Simulate component generation
await asyncio.sleep(1)
result = {
"status": "completed",
"component_type": component_type,
"files_modified": [f"src/{component_type}.py", f"tests/test_{component_type}.py"],
"code_generated": f"// Generated {component_type} component\n// {description}",
"integration_notes": f"Component {component_type} has been generated and integrated"
}
self.logger.info("component_generation_completed", component_type=component_type)
return result
async def enhance_application(
self,
project_id: str,
enhancement_description: str,
enhancement_type: str = "feature",
user_context: Optional[Dict[str, Any]] = None
) -> Dict[str, Any]:
"""
Enhance an existing application with new features
"""
self.logger.info(
"starting_application_enhancement",
project_id=project_id,
enhancement_type=enhancement_type
)
# Simulate enhancement process
await asyncio.sleep(1.5)
result = {
"status": "completed",
"enhancement_type": enhancement_type,
"changes_made": [
f"Added {enhancement_type} functionality",
"Updated tests",
"Modified documentation"
],
"files_modified": [
f"src/features/{enhancement_type}.py",
f"tests/test_{enhancement_type}.py",
"README.md"
],
"migration_notes": f"Enhancement {enhancement_type} requires database migration",
"testing_recommendations": [
"Run unit tests",
"Perform integration testing",
"Validate user acceptance"
]
}
self.logger.info("application_enhancement_completed", project_id=project_id)
return result
async def apply_automated_fixes(
self,
project_id: str,
fix_recommendations: List[Dict[str, Any]],
user_context: Optional[Dict[str, Any]] = None
) -> Dict[str, Any]:
"""
Apply automated fixes to a project
"""
self.logger.info(
"starting_automated_fixes",
project_id=project_id,
fixes_count=len(fix_recommendations)
)
# Simulate fix application
await asyncio.sleep(2)
fixes_applied = []
fixes_failed = []
for fix in fix_recommendations:
# Simulate some fixes succeeding and others failing
if "critical" not in fix.get("severity", "").lower():
fixes_applied.append(fix)
else:
fixes_failed.append(fix)
result = {
"status": "completed",
"fixes_applied": fixes_applied,
"fixes_failed": fixes_failed,
"total_fixes": len(fix_recommendations),
"success_rate": len(fixes_applied) / len(fix_recommendations) if fix_recommendations else 0
}
self.logger.info(
"automated_fixes_completed",
project_id=project_id,
fixes_applied=len(fixes_applied),
fixes_failed=len(fixes_failed)
)
return result
def _generate_project_structure(self, project_type: str) -> str:
"""Generate a project structure based on type"""
structures = {
"fullstack": """
project/
├── frontend/
│ ├── src/
│ ├── public/
│ └── package.json
├── backend/
│ ├── src/
│ ├── tests/
│ └── requirements.txt
├── database/
│ └── migrations/
└── docker-compose.yml
""",
"frontend": """
project/
├── src/
│ ├── components/
│ ├── pages/
│ └── utils/
├── public/
├── tests/
└── package.json
""",
"backend": """
project/
├── src/
│ ├── api/
│ ├── models/
│ └── services/
├── tests/
├── migrations/
└── requirements.txt
""",
"api": """
project/
├── src/
│ ├── endpoints/
│ ├── models/
│ └── middleware/
├── tests/
├── docs/
└── requirements.txt
"""
}
return structures.get(project_type, structures["fullstack"]).strip()
