app.py

"""
Advanced Agentic System Interface
-------------------------------
Provides a chat interface to interact with the autonomous agent teams:
- Team A: Coders (App/Software Developers)
- Team B: Business (Entrepreneurs)
- Team C: Research (Deep Online Research)
- Team D: Crypto & Sports Trading
"""

import os
import socket
import gradio as gr
from fastapi import FastAPI, HTTPException
from fastapi.middleware.cors import CORSMiddleware
import uvicorn
from typing import Dict, Any, List, Tuple, Optional
import logging
from pathlib import Path
import asyncio
from datetime import datetime
import json
import requests
from requests.adapters import HTTPAdapter, Retry
from dataclasses import dataclass

from agentic_system import AgenticSystem
from orchestrator import AgentOrchestrator
from team_management import TeamManager, TeamType
from reasoning import (
    UnifiedReasoningEngine,
    StrategyType,
    UnifiedResult
)
from api.openai_compatible import OpenAICompatibleAPI
from api.venture_api import VentureAPI
from api.groq_api import GroqAPI

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

def setup_requests_session():
    """Set up requests session with retries."""
    session = requests.Session()
    retries = Retry(
        total=5,
        backoff_factor=0.1,
        status_forcelist=[500, 502, 503, 504]
    )
    session.mount('http://', HTTPAdapter(max_retries=retries))
    session.mount('https://', HTTPAdapter(max_retries=retries))
    return session

def check_network():
    """Check network connectivity."""
    try:
        # Try DNS resolution first
        socket.gethostbyname('huggingface.co')
        return True
    except socket.gaierror:
        logger.warning("DNS resolution failed")
    
    try:
        # Try HTTP request as backup
        session = setup_requests_session()
        response = session.get('https://huggingface.co.', timeout=5)
        return response.status_code == 200
    except (requests.RequestException, socket.gaierror) as e:
        logger.warning(f"Network connectivity check failed: {e}")
        return False

class ChatInterface:
    """Chat interface for interacting with the agentic system."""
    
    def __init__(self):
        """Initialize the chat interface."""
        # Check network connectivity
        if not check_network():
            raise ConnectionError("No network connectivity. Please check your connection.")
            
        # Initialize core components with consistent configuration
        config = {
            "min_confidence": 0.7,
            "parallel_threshold": 3,
            "learning_rate": 0.1,
            "strategy_weights": {
                "LOCAL_LLM": 0.8,
                "CHAIN_OF_THOUGHT": 0.6,
                "TREE_OF_THOUGHTS": 0.5,
                "META_LEARNING": 0.4
            }
        }
        
        # Initialize chat state
        self.chat_history = []
        self.active_objectives = {}
        
        # Initialize components
        self.orchestrator = AgentOrchestrator(config)
        self.team_manager = TeamManager(self.orchestrator)
        self.reasoning_engine = UnifiedReasoningEngine()
        self.groq_api = GroqAPI()
        
        # Set up the agentic system
        self.agentic_system = AgenticSystem(config)
        
        # Initialize FastAPI app
        self.app = FastAPI()
        self.setup_cors()
        self.setup_routes()
        
        # Create Gradio interface
        self.interface = self.create_interface()
        
        # Launch background tasks
        self.background_tasks = []
        self.launch_background_tasks()
        
    async def initialize(self):
        """Initialize async components."""
        await self.team_manager.initialize_team_agents()
        
    def launch_background_tasks(self):
        """Launch background tasks."""
        loop = asyncio.get_event_loop()
        self.background_tasks.append(
            loop.create_task(self.initialize())
        )

    def setup_cors(self):
        """Set up CORS middleware."""
        self.app.add_middleware(
            CORSMiddleware,
            allow_origins=["*"],
            allow_credentials=True,
            allow_methods=["*"],
            allow_headers=["*"],
        )

    def setup_routes(self):
        """Set up API routes."""
        # Include OpenAI-compatible routes
        openai_api = OpenAICompatibleAPI(self.reasoning_engine)
        self.app.include_router(openai_api.router, tags=["OpenAI Compatible"])

        # Original API routes
        @self.app.get("/api/health")
        async def health_check():
            """Health check endpoint."""
            return {
                "status": "healthy",
                "version": "1.0.0",
                "endpoints": {
                    "openai_compatible": "/v1/chat/completions",
                    "venture": "/api/venture",
                    "ui": "/"
                }
            }

        @self.app.post("/api/reason")
        async def reason(query: str, context: Optional[Dict[str, Any]] = None):
            """Reasoning endpoint."""
            try:
                result = await self.reasoning_engine.reason(query, context or {})
                return result
            except Exception as e:
                logger.error(f"Reasoning error: {e}")
                raise HTTPException(status_code=500, detail=str(e))

        @self.app.post("/api/venture/analyze")
        async def analyze_venture(
            venture_type: str,
            description: str,
            metrics: Optional[Dict[str, Any]] = None
        ):
            """Venture analysis endpoint."""
            try:
                result = await VentureAPI(self.reasoning_engine).analyze_venture(
                    venture_type=venture_type,
                    description=description,
                    metrics=metrics or {}
                )
                return result
            except Exception as e:
                logger.error(f"Analysis error: {e}")
                raise HTTPException(status_code=500, detail=str(e))

        @self.app.get("/api/venture/types")
        async def get_venture_types():
            """Get available venture types."""
            return VentureAPI(self.reasoning_engine).get_venture_types()

    def create_interface(self) -> gr.Blocks:
        """Create the Gradio interface."""
        with gr.Blocks(
            title="Advanced Agentic System",
            css=None,  # Disable custom CSS
            theme=gr.themes.Soft(),  # Use built-in theme
        ) as interface:
            gr.Markdown("""
                # 🤖 Advanced Agentic System Chat Interface
                
                Welcome to our AI-powered autonomous agent teams! Each team specializes in different domains:
                
                - 💻 **Team A: Coders** - Expert software developers and architects
                - 💼 **Team B: Business** - Strategic entrepreneurs and analysts
                - 🔍 **Team C: Research** - Deep online research specialists
                - 📈 **Team D: Trading** - Crypto & sports trading experts
                
                You can:
                1. Ask questions about any domain
                2. Create new objectives for teams
                3. Check status of ongoing work
                4. Get insights and recommendations
                
                ---
            """)
            
            chatbot = gr.Chatbot(
                value=[],  # Initialize with empty list
                type="messages",  # Use OpenAI-style message format
                height=500,
                show_label=False,
                render_markdown=True,
                avatar_images=None,  # Disable avatars to prevent asset loading issues
            )
            
            with gr.Row():
                msg = gr.Textbox(
                    show_label=False,
                    placeholder="Chat with the Agentic System...",
                    container=False,
                    autofocus=True,
                )
                submit = gr.Button("Send 🚀")
            
            with gr.Row():
                clear = gr.ClearButton([msg, chatbot], value="Clear")
                retry = gr.Button("Retry")
            
            async def respond(message, history):
                """Handle chat responses with proper formatting."""
                try:
                    # Convert history to the format expected by process_message
                    history_list = [[msg["content"] for msg in exchange] for exchange in history] if history else []
                    response = await self.process_message(message, history_list)
                    
                    # Format response for markdown rendering
                    formatted_response = response.replace('```', '\n```\n')
                    
                    # Update history with the new message format
                    return "", history + [
                        {"role": "user", "content": message},
                        {"role": "assistant", "content": formatted_response}
                    ]
                except Exception as e:
                    logger.error(f"Error in chat response: {str(e)}")
                    error_msg = "I apologize, but I encountered an error. Please try again."
                    
                    return "", history + [
                        {"role": "user", "content": message},
                        {"role": "assistant", "content": error_msg}
                    ]

            async def retry_last(history):
                """Retry the last message with proper formatting."""
                if not history:
                    return history
                last_user_msg = history[-2]["content"]  # Get the last user message
                history = history[:-2]  # Remove last exchange
                return await respond(last_user_msg, history)

            # Submit handlers with loading states
            submit_event = msg.submit(
                fn=respond,
                inputs=[msg, chatbot],
                outputs=[msg, chatbot],
                api_name=False
            ).then(
                lambda: (gr.update(value="", interactive=True), gr.update(interactive=True)),
                None,
                [msg, submit]
            )

            # Click handlers with loading states
            click_event = submit.click(
                fn=respond,
                inputs=[msg, chatbot],
                outputs=[msg, chatbot],
                api_name=False
            ).then(
                lambda: (gr.update(value="", interactive=True), gr.update(interactive=True)),
                None,
                [msg, submit]
            )

            # Retry handler
            retry.click(
                fn=retry_last,
                inputs=[chatbot],
                outputs=[chatbot],
                api_name=False
            )

            # Auto-focus and dynamic submit button state
            msg.change(
                lambda x: (
                    gr.update(interactive=bool(x.strip())), 
                    gr.update(interactive=bool(x.strip()), variant="primary" if x.strip() else "secondary")
                ),
                [msg],
                [msg, submit]
            )
            
            # Example queries with emojis
            gr.Examples(
                examples=[
                    "💻 Can Team A help me build a web application?",
                    "💼 Create a new objective: Analyze market trends for AI startups",
                    "🔍 Research the latest developments in quantum computing",
                    "📈 What's the current status of all teams?"
                ],
                inputs=msg,
                label="Example Queries",
                examples_per_page=4
            )

        return interface

    async def process_message(
        self,
        message: str,
        history: List[List[str]] = None
    ) -> str:
        """Process a user message."""
        try:
            # Initialize history if None
            if history is None:
                history = []
            
            # Update chat history
            self.chat_history = history
            
            # Analyze message intent
            intent = await self._analyze_intent(message)
            
            # Process based on intent
            if intent.get('type') == 'objective':
                response = await self._handle_objective(message, intent)
            elif intent.get('type') == 'status':
                response = await self._get_status()
            elif intent.get('type') == 'chat':
                response = await self._handle_chat(message)
            else:
                response = await self._handle_chat(message)  # Default to chat handler
            
            return response
            
        except Exception as e:
            logger.error(f"Error processing message: {str(e)}")
            return "I encountered an error processing your message. Please try again."

    async def _analyze_intent(self, message: str) -> Dict[str, Any]:
        """Analyze user message intent with error handling."""
        try:
            # Use reasoning engine to analyze intent
            result = await self.reasoning_engine.reason(
                query=message,
                context={
                    "chat_history": self.chat_history,
                    "active_objectives": self.active_objectives
                }
            )
            
            # Handle UnifiedResult object
            if isinstance(result, UnifiedResult):
                return {
                    "type": "chat",
                    "confidence": getattr(result, 'confidence', 0.5),
                    "metadata": getattr(result, 'metadata', {})
                }
            elif isinstance(result, dict):
                return result
            else:
                return {"type": "chat", "confidence": 0.5}
            
        except Exception as e:
            logger.error(f"Error analyzing intent: {str(e)}")
            return {"type": "chat", "error": str(e)}

    async def _handle_objective(self, message: str, intent: Dict[str, Any]) -> str:
        """Handle objective creation and management."""
        try:
            # Extract objective details
            objective = intent.get('objective', {})
            
            # Create objective
            objective_id = await self.team_manager.create_cross_team_objective(
                objective=objective.get('description', message),
                required_teams=objective.get('teams', []),
                priority=objective.get('priority', 'MEDIUM')
            )
            
            # Monitor progress
            status = await self.team_manager.monitor_objective_progress(objective_id)
            
            return f"Created objective {objective_id}. Current status: {status}"
            
        except Exception as e:
            logger.error(f"Error handling objective: {str(e)}")
            return "Failed to create objective. Please try again."

    async def _handle_chat(self, message: str) -> str:
        """Handle general chat interactions with error recovery."""
        try:
            # First try using the reasoning engine
            try:
                result = await self.reasoning_engine.reason(
                    query=message,
                    context={
                        "chat_history": self.chat_history,
                        "active_objectives": self.active_objectives,
                        "groq_api": self.groq_api
                    }
                )
                
                # Handle UnifiedResult object
                if isinstance(result, UnifiedResult):
                    if not result.success:
                        # If reasoning engine fails, fallback to Groq API
                        groq_result = await self.groq_api.predict(message)
                        if groq_result["success"]:
                            return groq_result["answer"]
                        else:
                            return "I encountered an error. Please try rephrasing your question."
                    return result.answer if hasattr(result, 'answer') else str(result)
                elif isinstance(result, dict):
                    return result.get('response', str(result))
                else:
                    return str(result)
                
            except Exception as reasoning_error:
                logger.error(f"Reasoning engine error: {str(reasoning_error)}")
                # Fallback to Groq API
                groq_result = await self.groq_api.predict(message)
                if groq_result["success"]:
                    return groq_result["answer"]
                else:
                    raise Exception(f"Both reasoning engine and Groq API failed: {groq_result.get('error')}")
            
        except Exception as e:
            logger.error(f"Error in chat response: {str(e)}")
            return "I encountered an error generating a response. Please try again."

    async def _get_status(self) -> str:
        """Get system status information."""
        try:
            # Get team status
            team_status = await self.team_manager.get_team_status()
            
            # Get objective status
            objective_status = await self.team_manager.get_objective_status()
            
            # Format status information
            status = "Current System Status:\n\n"
            
            # Add team information
            status += "Teams:\n"
            for team, info in team_status.items():
                status += f"- {team}: {info['status']}\n"
                status += f"  Active Projects: {info['active_projects']}\n"
                status += f"  Success Rate: {info['success_rate']}%\n\n"
            
            # Add objective information
            status += "\nActive Objectives:\n"
            for obj, info in objective_status.items():
                status += f"- {obj}: {info['status']}\n"
                status += f"  Progress: {info['progress']}%\n"
                status += f"  Teams: {', '.join(info['teams'])}\n\n"
            
            return status
            
        except Exception as e:
            logger.error(f"Error formatting status: {str(e)}")
            return "Error formatting status information."

def create_chat_interface() -> gr.Blocks:
    """Create Gradio chat interface."""
    chat = ChatInterface()
    return chat.interface

# Initialize FastAPI
app = FastAPI(
    title="Advanced Agentic System API",
    description="API for interacting with the autonomous agent teams",
    version="1.0.0"
)

# Create Gradio interface
interface = create_chat_interface()

# Mount Gradio app to FastAPI
app = gr.mount_gradio_app(app, interface, path="/")

if __name__ == "__main__":
    chat_interface = ChatInterface()
    interface = chat_interface.create_interface()
    interface.queue()
    interface.launch(
        server_name="0.0.0.0",
        server_port=7860,
        share=True,
        debug=True,
        enable_queue=True,
        show_error=True,
        favicon_path=None,  # Disable favicon to prevent 404
        show_api=False,  # Disable API docs to reduce asset loading
        reload=False,  # Disable auto-reload to use workers properly
        max_threads=40,
    )