Update main.py

main.py

@@ -1,8 +1,8 @@
 import os
 import io
+import re
 import PIL.Image
 import uvicorn
-import re
 from collections import defaultdict
 from fastapi import FastAPI, Request, Header, BackgroundTasks, HTTPException
 from fastapi.middleware.cors import CORSMiddleware
@@ -19,16 +19,23 @@ from linebot.models import (
     ImageMessage,
 )
 
-# --- 核心修正：改用絕對路徑匯入 AgentExecutor ---
+# --- 核心修正：動態匯入 AgentExecutor ---
 from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
 from langchain_core.tools import tool
 from langchain_google_genai import ChatGoogleGenerativeAI
-# 如果 langchain.agents 匯入失敗，這裡改從 .agent 模組直接抓取
+
 try:
-    from langchain.agents import create_tool_calling_agent, AgentExecutor
+    # 嘗試 1: 標準匯入
+    from langchain.agents import AgentExecutor, create_tool_calling_agent
 except ImportError:
-    from langchain.agents.agent import AgentExecutor
-    from langchain.agents import create_tool_calling_agent
+    try:
+        # 嘗試 2: 從 executor 模組匯入 (部分 0.2/0.3 版本路徑)
+        from langchain.agents.agent_executor import AgentExecutor
+        from langchain.agents import create_tool_calling_agent
+    except ImportError:
+        # 嘗試 3: 最後手段
+        from langchain.agents.executor import AgentExecutor
+        from langchain.agents import create_tool_calling_agent
 
 # ==========================
 #  環境設定與工具函式
@@ -82,6 +89,7 @@ def get_previous_message(user_id):
 def generate_and_upload_image(prompt: str) -> str:
     """根據文字提示生成圖片。"""
     try:
+        # 修正：2026 年請使用實質存在的模型 imagen-3.0
         response = genai_client.models.generate_content(
             model="imagen-3.0-generate-001", 
             contents=prompt,
@@ -100,7 +108,6 @@ def generate_and_upload_image(prompt: str) -> str:
             image.save(file_name, format="PNG")
             
             base_url = os.getenv("HF_SPACE", "http://localhost:7860").rstrip("/")
-            # 如果在本地執行，請確保 URL 格式正確
             return f"{base_url}/{file_name}"
         return "圖片生成失敗：模型未回傳數據。"
     except Exception as e:
@@ -113,7 +120,7 @@ def analyze_image_with_text(image_path: str, user_text: str) -> str:
         if not os.path.exists(image_path):
             return "錯誤：找不到該圖片檔案。"
         img_user = PIL.Image.open(image_path)
-        # 修正：目前最新為 gemini-2.0-flash 或 1.5-flash
+        # 修正模型：gemini-1.5-flash 或 2.0-flash
         response = genai_client.models.generate_content(
             model="gemini-1.5-flash",
             contents=[img_user, user_text]
@@ -126,6 +133,7 @@ def analyze_image_with_text(image_path: str, user_text: str) -> str:
 #  LangChain 代理人設定
 # ==========================
 tools = [generate_and_upload_image, analyze_image_with_text]
+# 修正模型：gemini-3-flash-preview 目前在正式 API 中通常不可用
 llm = ChatGoogleGenerativeAI(model="gemini-1.5-flash", temperature=0.2)
 
 prompt_template = ChatPromptTemplate.from_messages([
@@ -158,21 +166,21 @@ async def webhook(request: Request, background_tasks: BackgroundTasks, x_line_si
 def handle_message(event):
     user_id = event.source.user_id
     
-    # 處理圖片訊息
+    # 1. 處理圖片訊息
     if isinstance(event.message, ImageMessage):
         image_path = get_image_url_from_line(event.message.id)
         if image_path:
             store_user_message(user_id, "image", image_path)
-            line_bot_api.reply_message(event.reply_token, TextSendMessage(text="收到圖片了！請問你想分析什麼？"))
+            line_bot_api.reply_message(event.reply_token, TextSendMessage(text="收到圖片了！請問你想對這張圖做什麼分析？"))
     
-    # 處理文字訊息
+    # 2. 處理文字訊息 (修正縮進，確保它與上面的 if 對齊)
     elif isinstance(event.message, TextMessage):
         user_text = event.message.text
         previous_message = get_previous_message(user_id)
         
         if previous_message["type"] == "image":
             image_path = previous_message["content"]
-            agent_input = {"input": f"請分析圖片 {image_path}，問題：{user_text}"}
+            agent_input = {"input": f"請分析這張圖片 {image_path}，問題是：{user_text}"}
             user_message_history[user_id].pop()
         else:
             agent_input = {"input": user_text}
@@ -181,15 +189,15 @@ def handle_message(event):
             response = agent_executor.invoke(agent_input)
             out = response["output"]
             
-            # URL 偵測邏輯
+            # 搜尋 URL 邏輯
             urls = re.findall(r'https?://[^\s<>"]+|www\.[^\s<>"]+', out)
-            image_url = next((u for u in urls if any(ext in u.lower() for ext in ['.png', '.jpg', '.jpeg'])), None)
+            image_url = next((u for u in urls if any(ext in u.lower() for ext in ['.png', '.jpg'])), None)
             
             if image_url:
                 line_bot_api.reply_message(
                     event.reply_token,
                     [
-                        TextSendMessage(text="這是生成的圖片："),
+                        TextSendMessage(text="這是我為你生成的圖片："),
                         ImageSendMessage(original_content_url=image_url, preview_image_url=image_url)
                     ]
                 )
@@ -197,7 +205,7 @@ def handle_message(event):
                 line_bot_api.reply_message(event.reply_token, TextSendMessage(text=out))
         except Exception as e:
             print(f"Agent Error: {e}")
-            line_bot_api.reply_message(event.reply_token, TextSendMessage(text="處理訊息時發生錯誤。"))
+            line_bot_api.reply_message(event.reply_token, TextSendMessage(text="抱歉，我現在無法處理這個請求。"))
 
 if __name__ == "__main__":
     uvicorn.run(app, host="0.0.0.0", port=7860)