modules/travel_assistant.py

# modules/travel_assistant.py - 正确版本
from .config_loader import ConfigLoader
from .ai_model import AIModel
from .knowledge_base import KnowledgeBase
from .intent_classifier import IntentClassifier
from .info_extractor import InfoExtractor
from .session_manager import SessionManager
from .response_generator import ResponseGenerator
from utils.logger import log

class TravelAssistant:
    def __init__(self):
        # 依赖注入：在这里实例化所有需要的模块
        log.info("开始初始化 Travel Assistant 核心模块...")
        self.config = ConfigLoader()
        self.kb = KnowledgeBase()
        self.ai_model = AIModel()
        self.session_manager = SessionManager()
        self.info_extractor = InfoExtractor()
        self.intent_classifier = IntentClassifier(self.ai_model) 
        self.response_generator = ResponseGenerator(self.ai_model, self.kb)
        log.info("✅ Travel Assistant 核心模块全部初始化完成！")


    def chat(self, message: str, session_id: str, history: list, persona_key: str = None):
        log.info(f"📞 === 聊天请求开始 ===")
        log.info(f"📝 消息: '{message[:30]}...'")
        log.info(f"🆔 前端传入session_id: '{session_id}'")
        log.info(f"🎭 persona_key: '{persona_key}'")
        
        # 1. 获取或创建会话
        session_state = self.session_manager.get_or_create_session(session_id)
        current_session_id = session_state['session_id']
        
        log.info(f"📋 使用后端session_id: '{current_session_id}'")
        
        # 2. 设置persona
        if persona_key and persona_key in self.config.personas:
            persona_info = {
                'key': persona_key,
                'name': self.config.personas[persona_key]['name'],
                'style': self.config.personas[persona_key]['style'],
                'source': 'frontend_selection'
            }
            self.session_manager.update_session(current_session_id, {'persona': persona_info})
            session_state = self.session_manager.get_or_create_session(current_session_id)
            log.info(f"✅ 设置persona: {persona_info['name']}")

        # 3. 意图识别 (前置守卫)
        raw_intent = self.intent_classifier.classify(message)
        log.info(f"🔍 用户意图识别结果: '{raw_intent}'")

        extracted_info = {}
        intent = 'OTHER' 

        if 'PROVIDING_TRAVEL_INFO' in raw_intent:
            intent = 'PROVIDING_TRAVEL_INFO'
        elif 'GREETING' in raw_intent:
            intent = 'GREETING'

        log.info(f"✅ 解析后用户意图: '{intent}'")
        
        # 4.: 根据意图进行逻辑分流
        if intent == 'PROVIDING_TRAVEL_INFO':
            # 场景A: 用户提供了旅行信息，执行完整的信息提取
            extracted_info = self.info_extractor.extract(message)
            if extracted_info:
                self.session_manager.update_session(current_session_id, extracted_info)
                session_state = self.session_manager.get_or_create_session(current_session_id)
            
            # 无论是否提取成功，都让 response_generator 来生成上下文感知的回复
            bot_response = self.response_generator.generate(message, session_state, extracted_info)

        else:
            # 场景B: 用户意图是问候或其它，直接生成引导性回复，完全绕过信息提取
            log.info(f"💬 意图为 '{intent}'，绕过信息提取，直接生成引导性回复。")
            if intent == 'GREETING':
                bot_response = "您好！很高兴能为您规划旅程。请问您想去哪里，玩几天，预算大概是多少呢？您可以输入：我想去巴黎玩三天"
            elif intent == 'INQUIRY':
                bot_response = "当然！为了给您更精准的推荐，可以告诉我您的兴趣偏好吗？比如您对历史文化、自然风光、美食购物还是夜生活更感兴趣呢？这样我才能更好地为您量身定制哦！"
            else: # 'OTHER'
                # 对于其它问题，可以调用通用的生成器，让它决定如何回复
                bot_response = self.response_generator.generate(message, session_state, {})

        
        # 6. 返回结果
        status_info = self.session_manager.format_session_info(session_state)
        new_history = history + [[message, bot_response]]
        
        log.info(f"✅ 聊天完成，返回session_id: {current_session_id}")
        log.info(f"📊 最终状态: {self.session_manager._get_session_summary(current_session_id)}")
        log.info(f"📞 === 聊天请求结束 ===")
        
        return bot_response, current_session_id, status_info, new_history