# ────────────────────────────── memo/history.py ──────────────────────────────
"""
History Management

Functions for managing conversation history and context.
"""

from typing import List, Dict, Any, Tuple, Optional
import os

from utils.logger import get_logger
from memo.nvidia import summarize_qa, files_relevance, related_recent_context
from memo.context import semantic_context, get_legacy_context
from utils.rag.embeddings import EmbeddingClient

logger = get_logger("HISTORY_MANAGER", __name__)

class HistoryManager:
    """
    Enhanced history manager that provides both legacy and enhanced functionality.
    Automatically uses enhanced features when available.
    """
    
    def __init__(self, memory_system=None):
        self.memory_system = memory_system
    
    async def summarize_qa_with_nvidia(self, question: str, answer: str, nvidia_rotator) -> str:
        """Summarize Q&A using NVIDIA model (enhanced version)"""
        return await summarize_qa(question, answer, nvidia_rotator)
    
    async def files_relevance(self, question: str, file_summaries: List[Dict[str, str]], nvidia_rotator) -> Dict[str, bool]:
        """Determine file relevance using NVIDIA model (enhanced version)"""
        return await files_relevance(question, file_summaries, nvidia_rotator)
    
    async def related_recent_and_semantic_context(self, user_id: str, question: str, 
                                                embedder: EmbeddingClient, 
                                                topk_sem: int = 3, nvidia_rotator=None) -> Tuple[str, str]:
        """Get related recent and semantic context (enhanced version)"""
        try:
            if self.memory_system and self.memory_system.is_enhanced_available():
                # Use enhanced context retrieval
                recent_context, semantic_context = await self.memory_system.get_conversation_context(
                    user_id, question
                )
                return recent_context, semantic_context
            else:
                # Fallback to original implementation with NVIDIA support
                return await self._get_legacy_context(user_id, question, self.memory_system, embedder, topk_sem, nvidia_rotator)
        except Exception as e:
            logger.error(f"[HISTORY_MANAGER] Context retrieval failed: {e}")
            return "", ""
    
    async def _get_legacy_context(self, user_id: str, question: str, memory_system, 
                                embedder: EmbeddingClient, topk_sem: int, nvidia_rotator=None) -> Tuple[str, str]:
        """Get context using legacy method with enhanced semantic selection"""
        if not memory_system:
            return "", ""
        
        recent3 = memory_system.recent(user_id, 3)
        rest17 = memory_system.rest(user_id, 3)
        
        recent_text = ""
        if recent3:
            # Use NVIDIA to select most relevant recent memories (enhanced)
            if nvidia_rotator:
                try:
                    recent_text = await related_recent_context(question, recent3, nvidia_rotator)
                except Exception as e:
                    logger.warning(f"[HISTORY_MANAGER] NVIDIA recent context selection failed: {e}")
                    # Fallback to semantic similarity
                    try:
                        recent_text = await semantic_context(question, recent3, embedder, 2)
                    except Exception as e2:
                        logger.warning(f"[HISTORY_MANAGER] Semantic fallback failed: {e2}")
            else:
                # Use semantic similarity directly if no NVIDIA rotator
                try:
                    recent_text = await semantic_context(question, recent3, embedder, 2)
                except Exception as e:
                    logger.warning(f"[HISTORY_MANAGER] Semantic recent context failed: {e}")
        
        sem_text = ""
        if rest17:
            sem_text = await semantic_context(question, rest17, embedder, topk_sem)
        
        return recent_text, sem_text

# ────────────────────────────── Legacy Functions (Backward Compatibility) ──────────────────────────────

# These legacy functions have been removed as they are no longer needed with the new memory planning system.
# Use the appropriate methods from the core memory system or memory planner instead.

# ────────────────────────────── Global Instance ──────────────────────────────

_history_manager: Optional[HistoryManager] = None

def get_history_manager(memory_system=None) -> HistoryManager:
    """Get the global history manager instance"""
    global _history_manager
    
    if _history_manager is None:
        _history_manager = HistoryManager(memory_system)
        logger.info("[HISTORY_MANAGER] Global history manager initialized")
    
    return _history_manager

# def reset_history_manager():
#     """Reset the global history manager (for testing)"""
#     global _history_manager
#     _history_manager = None