#!/usr/bin/env python3
"""
MCPEnhancedLlamaIndex - Llama Index Integration with MCP

This module provides enhanced llama index integration with MCP client support,
enabling AI-powered workflows with Atlassian data access.

Based on SPIKE-001 llama index integration patterns.
"""

import asyncio
import logging
from typing import Dict, Any, Optional

from .simple_mcp_client import SimpleMCPClient

# Configure logging
logger = logging.getLogger(__name__)


class MCPEnhancedLlamaIndex:
    """
    Enhanced llama index with multi-MCP server support.
    
    This class integrates SimpleMCPClient with llama index processing,
    implementing patterns validated in SPIKE-001.
    """
    
    def __init__(self):
        """Initialize MCPEnhancedLlamaIndex."""
        self.mcp_client = SimpleMCPClient()
        self._initialized = False
        
        logger.info("MCPEnhancedLlamaIndex initialized")
    
    async def initialize(self):
        """Initialize MCP connections."""
        if not self._initialized:
            await self.mcp_client.connect_all()
            self._initialized = True
            logger.info("MCP connections initialized")
    
    async def enhanced_query(self, query: str, capability: str = None) -> Dict[str, Any]:
        """
        Enhanced query method that integrates MCP data retrieval with llama index processing.
        
        Args:
            query: The query string to process
            capability: Optional specific MCP capability to target
            
        Returns:
            Dictionary containing both MCP data and processed results
        """
        if not self._initialized:
            await self.initialize()
        
        logger.debug(f"Processing enhanced query: {query[:100]}...")
        
        try:
            # Get data from MCP server
            mcp_data = await self.mcp_client.query(query, capability)
            
            # Process with llama index (simplified implementation)
            processed_result = await self.process_with_llama_index(mcp_data, query)
            
            return {
                "query": query,
                "mcp_data": mcp_data,
                "processed_result": processed_result,
                "capability_used": capability or self.mcp_client._detect_capability(query),
                "success": True
            }
            
        except Exception as e:
            logger.error(f"Enhanced query failed: {e}")
            return {
                "query": query,
                "error": str(e),
                "success": False
            }
    
    async def process_with_llama_index(self, mcp_data: Any, query: str) -> Dict[str, Any]:
        """
        Process MCP data with llama index.
        
        This is a simplified implementation. In production, this would integrate
        with actual llama index processing pipeline.
        
        Args:
            mcp_data: Data retrieved from MCP server
            query: Original query string
            
        Returns:
            Processed results from llama index
        """
        # Simplified processing implementation
        # In production, this would include:
        # - Vector indexing of MCP data
        # - Semantic search capabilities
        # - AI-powered analysis and summarization
        
        processed = {
            "summary": f"Processed query '{query}' with MCP data",
            "data_source": "mcp",
            "processing_method": "llama_index_enhanced",
            "raw_data_size": len(str(mcp_data)) if mcp_data else 0
        }
        
        logger.debug(f"Processed MCP data with llama index: {processed}")
        
        return processed
    
    async def get_mcp_status(self) -> Dict[str, Any]:
        """Get status of MCP connections."""
        if not self._initialized:
            return {"initialized": False, "servers": {}}
        
        return {
            "initialized": True,
            "servers": self.mcp_client.get_server_status(),
            "health": await self.mcp_client.health_check()
        }
    
    async def close(self):
        """Close all MCP connections."""
        if self._initialized:
            await self.mcp_client.disconnect_all()
            self._initialized = False
            logger.info("MCP connections closed")