Clear print

.gitignore

@@ -1,2 +1,3 @@
 .env
 .vscode/
+app/core/__pycache__/

app/api/chat_router.py

@@ -1,103 +0,0 @@
-from fastapi import APIRouter, HTTPException
-from pydantic import BaseModel, Field
-from typing import List, Dict
-
-# 导入 ChatbotAgent 类和配置
-# 假设 ChatbotAgent 是单例或在应用启动时创建
-from app.core.chatbot_agent import ChatbotAgent
-from app.core.config import settings
-
-# --- Pydantic Data Models ---
-# 用于接收用户消息的请求体
-class ChatRequest(BaseModel):
-    user_id: str = Field(..., description="Unique identifier for the user.")
-    user_message: str = Field(..., description="The user's text message.")
-
-# 用于启动搭配推荐的请求体
-class OutfitStartRequest(BaseModel):
-    user_id: str = Field(..., description="Unique identifier for the user.")
-    stylist_name: str = Field("crystal", description="The name of the stylist guide to use (e.g., 'crystal').")
-    # 用于从已选单品继续搭配，可选
-    start_outfit: List[Dict[str, str]] = Field(default_factory=list, description="Optional list of items already selected.")
-
-# 用于返回 LLM/Agent 的文本回复
-class ChatResponse(BaseModel):
-    response_text: str = Field(..., description="The chatbot's text response.")
-
-# 搭配推荐的响应体 (StylistAgent的输出是JSON，这里简化为字符串，实际项目中会返回结构化的JSON)
-class OutfitResponse(BaseModel):
-    summary: str = Field(..., description="The conversation summary used for styling.")
-    next_item_json: Dict = Field(..., description="The next recommended item in JSON format.")
-    
-# --- Router Setup ---
-
-router = APIRouter(
-    prefix="/chat",
-    tags=["Chatbot & Styling"]
-)
-
-# 在应用启动时实例化 ChatbotAgent，以便在路由中使用同一个实例
-# 注意：在真实的 FastAPI 应用中，我们通常使用依赖注入 (Depends) 来管理实例
-try:
-    # 假设 ChatbotAgent 的 __init__ 已经包含了所有依赖的初始化
-    global_agent = ChatbotAgent()
-except Exception as e:
-    # 如果依赖（如 Redis 或 VectorDB）初始化失败，抛出错误
-    print(f"FATAL: ChatbotAgent failed to initialize. Error: {e}")
-    global_agent = None # 保持 None 状态，路由会抛出 500
-
-@router.post("/", response_model=ChatResponse, summary="Process user message and get chatbot response")
-def handle_chat_message(request: ChatRequest):
-    """
-    处理用户的聊天消息，将消息添加到历史记录，并调用 LLM 生成回复。
-    """
-    if not global_agent:
-        raise HTTPException(status_code=500, detail="Chatbot agent not initialized.")
-        
-    try:
-        response = global_agent.process_query(request.user_id, request.user_message)
-        return ChatResponse(response_text=response)
-    except Exception as e:
-        print(f"Error processing chat query: {e}")
-        # 返回一个通用错误信息，而不是内部错误
-        raise HTTPException(status_code=500, detail="Internal server error while processing message.")
-
-@router.post("/outfit/start", summary="Start outfit recommendation based on conversation history")
-def start_outfit_recommendation(request: OutfitStartRequest):
-    """
-    基于用户的对话历史，生成搭配总结，并启动 Stylist Agent 推荐第一个单品。
-    
-    返回：对话总结和 Stylist Agent 推荐的第一个单品的 JSON。
-    """
-    if not global_agent:
-        raise HTTPException(status_code=500, detail="Chatbot agent not initialized.")
-
-    try:
-        # 1. 获取对话总结
-        request_summary = global_agent.get_conversation_summary(request.user_id)
-        
-        # 2. 调用 Stylist Agent 运行搭配流程
-        # run_styling_process 应该返回 Stylist Agent 的第一个 JSON 输出 (recommend_item)
-        # 假设 StylistAgent.run_styling_process 返回一个 JSON 字典
-        next_item_json = global_agent.stylist_agent.run_styling_process(
-            request_summary, 
-            request.stylist_name, 
-            request.start_outfit
-        )
-        
-        return OutfitResponse(
-            summary=request_summary,
-            next_item_json=next_item_json
-        )
-        
-    except Exception as e:
-        print(f"Error starting outfit recommendation: {e}")
-        raise HTTPException(status_code=500, detail=f"Failed to start styling process: {e}")
-
-# (可选) 搭配继续接口：用于处理用户的反馈和继续推荐
-@router.post("/outfit/continue", summary="Continue outfit recommendation with user feedback")
-def continue_outfit_recommendation():
-    """
-    这是一个占位符，用于处理用户对已推荐单品（如图片）的反馈，并让 Stylist Agent 推荐下一个单品。
-    """
-    raise HTTPException(status_code=501, detail="Endpoint for outfit continuation is not yet implemented.")

app/core/stylist_agent.py

@@ -121,7 +121,7 @@ class AsyncStylistAgent:
         # 2. 添加文本内容
         content_parts.append(user_input)
         
-        print(f"\n--- Calling Gemini with {len(self.outfit_items) if self.outfit_items else 0} images and query:\n{user_input}")
+        # print(f"\n--- Calling Gemini with {len(self.outfit_items) if self.outfit_items else 0} images and query:\n{user_input}")
 
         try:
             # 3. 实际 API 调用