tools/todo.py

import time
from typing import List, Optional
import re
import os
from dotenv import load_dotenv

load_dotenv()

def analyze_query_type(prompt: str) -> dict:
    """Analyse le type de requête pour adapter la stratégie de réflexion"""
    prompt_lower = prompt.lower()
    
    analysis = {
        "type": "general",
        "needs_web": False,
        "needs_memory": False,
        "needs_docs": False,
        "complexity": "simple",
        "temporal": False,
        "geographical": False
    }
    
    temporal_keywords = ["aujourd'hui", "maintenant", "récent", "actuel", "dernier", "2024", "2025"]
    if any(kw in prompt_lower for kw in temporal_keywords):
        analysis["temporal"] = True
        analysis["needs_web"] = True
    
    geo_keywords = ["gabon", "libreville", "port-gentil", "franceville", "oyem", "où", "localisation"]
    if any(kw in prompt_lower for kw in geo_keywords):
        analysis["geographical"] = True
    
    doc_keywords = ["selon le document", "d'après le pdf", "dans le fichier", "uploadé"]
    if any(kw in prompt_lower for kw in doc_keywords):
        analysis["needs_docs"] = True
        analysis["type"] = "document_query"
    
    continuation_keywords = ["ils", "elles", "lui", "leur", "donc", "alors", "ensuite", "aussi", "également"]
    if any(kw in prompt_lower for kw in continuation_keywords) or len(prompt.split()) < 5:
        analysis["needs_memory"] = True
        analysis["type"] = "continuation"
    
    if len(prompt.split()) > 15 or (prompt.count("?") > 1):
        analysis["complexity"] = "complex"
    elif any(kw in prompt_lower for kw in ["pourquoi", "comment", "expliquer"]):
        analysis["complexity"] = "medium"
    
    web_keywords = ["actualité", "news", "prix", "cours", "météo", "horaire"]
    if any(kw in prompt_lower for kw in web_keywords):
        analysis["needs_web"] = True
        analysis["type"] = "real_time"
    
    return analysis

def detect_subject_shift(prompt: str, current_subject: str, subject_keywords: List[str]) -> dict:
    """Détecte un changement de sujet et évalue la force du changement"""
    if not current_subject or not subject_keywords:
        return {"shift_detected": False, "shift_strength": 0.0, "new_subject_detected": True, "reason": "Init"}
    
    prompt_lower = prompt.lower()
    prompt_words = set(re.findall(r'\b\w{4,}\b', prompt_lower))
    keyword_overlap = len(prompt_words.intersection(set(subject_keywords)))
    overlap_ratio = keyword_overlap / max(len(subject_keywords), 1)
    
    shift_markers = ["maintenant", "sinon", "autre chose", "parlons de", "passons à", "nouveau sujet"]
    has_shift_marker = any(marker in prompt_lower for marker in shift_markers)
    
    shift_strength = 0.0
    if overlap_ratio < 0.2: shift_strength += 0.5
    if has_shift_marker: shift_strength += 0.3
    
    return {
        "shift_detected": shift_strength > 0.4,
        "shift_strength": shift_strength,
        "new_subject_detected": shift_strength > 0.6,
        "reason": f"Overlap: {overlap_ratio:.1%}"
    }

def generate_search_strategy(analysis: dict, subject_keywords: List[str], geo_info: dict) -> dict:
    """Génère une stratégie de recherche optimisée"""
    strategy = {
        "use_rag": analysis["needs_docs"],
        "use_memory": analysis["needs_memory"],
        "use_web": analysis["needs_web"],
        "memory_k": 5, "rag_k": 3,
        "web_enhanced": False, "search_query_suffix": ""
    }
    
    if analysis["complexity"] == "complex":
        strategy.update({"memory_k": 8, "rag_k": 5})
    
    if analysis["needs_web"]:
        strategy["web_enhanced"] = True
        suffix = " ".join(subject_keywords[:3]) if subject_keywords else ""
        strategy["search_query_suffix"] = f"{suffix} {geo_info.get('city', 'Gabon')}"
    
    return strategy

def execute_reflection_plan(
    prompt: str, 
    geo_info: Optional[dict] = None, 
    messages: Optional[List] = None,
    current_subject: Optional[str] = None,
    subject_keywords: Optional[List[str]] = None
):
    """Phase de réflexion structurée compatible FastAPI (sans Streamlit)"""
    geo_info = geo_info or {}
    subject_keywords = subject_keywords or []
    
    query_analysis = analyze_query_type(prompt)
    subject_shift = detect_subject_shift(prompt, current_subject, subject_keywords)
    search_strategy = generate_search_strategy(query_analysis, subject_keywords, geo_info)
    
    # Logs internes (visibles dans Docker)
    print(f"🧠 [REFLECTION] Type: {query_analysis['type']} | Web: {search_strategy['use_web']}")
    
    return {
        "analysis": query_analysis,
        "subject_shift": subject_shift,
        "strategy": search_strategy,
        "execution_plan_ready": True
    }