Update main.py

main.py

@@ -1,52 +1,50 @@
-from fastapi import FastAPI, Request, Header, BackgroundTasks, HTTPException, status
+import os
+import io
+from collections import defaultdict
 from fastapi.middleware.cors import CORSMiddleware
+from fastapi import FastAPI, Request, Header, BackgroundTasks, HTTPException
+from fastapi.staticfiles import StaticFiles
+from google import genai
+from google.genai import types
 from linebot import LineBotApi, WebhookHandler
 from linebot.exceptions import InvalidSignatureError
-from linebot.models import MessageEvent, TextMessage, TextSendMessage, ImageMessage, ImageSendMessage
-import json
-import os
-import requests
-import base64
-from collections import defaultdict
+from linebot.models import (
+    MessageEvent,
+    TextMessage,
+    TextSendMessage,
+    ImageSendMessage,
+    ImageMessage,
+)
+import PIL.Image
 import uvicorn
-import logging
-from PIL import Image
-import io
-import requests.exceptions
 
-# 設置日誌記錄
-logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+# LangChain 相關匯入
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_core.tools import tool
+from langchain_google_genai import ChatGoogleGenerativeAI
+from langchain.agents import AgentExecutor, create_tool_calling_agent
+
 
-# 檢查環境變數
-if not all(k in os.environ for k in ["CHANNEL_ACCESS_TOKEN", "CHANNEL_SECRET", "GOOGLE_API_KEY", "IMGBB_API_KEY", "HF_SPACE"]):
-    logging.error("Missing environment variables. Please set CHANNEL_ACCESS_TOKEN, CHANNEL_SECRET, GOOGLE_API_KEY, IMGBB_API_KEY, and HF_SPACE.")
-    raise ValueError("Missing environment variables. Please set CHANNEL_ACCESS_TOKEN, CHANNEL_SECRET, GOOGLE_API_KEY, IMGBB_API_KEY, and HF_SPACE.")
+# ==========================
+#  環境設定與工具函式
+# ==========================
 
-# Line Bot API 設定
+# 設置 Google AI API 金鑰
+google_api = os.environ["GOOGLE_API_KEY"]
+genai_client = genai.Client(api_key=google_api)
+
+# 設置 Line Bot 的 API 金鑰和秘密金鑰
 line_bot_api = LineBotApi(os.environ["CHANNEL_ACCESS_TOKEN"])
 line_handler = WebhookHandler(os.environ["CHANNEL_SECRET"])
 
-# 使用者狀態追蹤
-user_states = defaultdict(lambda: {
-    "upper_body_images": [],
-    "lower_body_images": [],
-    "current_mode": None, # "upper" or "lower"
-    "is_ready_for_outfit": False, # 標記衣物是否收集完畢
-    "is_ready_for_photo": False, # 標記個人照片是否上傳
-    "user_info": {}, # 儲存身高、三圍、場合
-    "personal_photo": None, # 儲存個人照片
-    "personal_photo_base64": None # 新增：儲存個人照片的 Base64 字串
-})
-
-MAX_IMAGES_PER_TYPE = 3
-GEMINI_API_URL = "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-preview-05-20:generateContent"
-IMAGIN_API_URL = "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image-preview:generateContent"
-GOOGLE_API_KEY = os.environ["GOOGLE_API_KEY"]
-IMGBB_API_KEY = os.environ["IMGBB_API_KEY"]
-HF_SPACE_URL = os.environ["HF_SPACE"]
+# 使用字典模擬用戶訊息歷史存儲
+user_message_history = defaultdict(list)
 
+# 建立 FastAPI 應用程式
 app = FastAPI()
+app.mount("/static", StaticFiles(directory="static"), name="static")
 
+# 設定 CORS
 app.add_middleware(
     CORSMiddleware,
     allow_origins=["*"],
@@ -55,502 +53,210 @@ app.add_middleware(
     allow_headers=["*"],
 )
 
-@app.get("/")
-def root():
-    return {"title": "Line Bot 穿搭建議"}
-
-@app.post("/webhook")
-async def webhook(
-    request: Request,
-    background_tasks: BackgroundTasks,
-    x_line_signature=Header(None),
-):
-    body = await request.body()
-    try:
-        background_tasks.add_task(line_handler.handle, body.decode("utf-8"), x_line_signature)
-    except InvalidSignatureError:
-        raise HTTPException(status_code=400, detail="Invalid signature")
-    return "ok"
-
-def get_base64_image(message_id: str):
-    logging.info(f"Fetching image content for message ID: {message_id}")
-    message_content = line_bot_api.get_message_content(message_id)
-    image_bytes = message_content.content
-    return base64.b64encode(image_bytes).decode('utf-8')
-
-def upload_to_imgbb(image_base64: str):
-    """
-    將 Base64 編碼的圖片上傳到 Imgbb。
-    """
-    logging.info("Attempting to upload image to Imgbb.")
-    url = "https://api.imgbb.com/1/upload"
-    payload = {
-        "key": IMGBB_API_KEY,
-        "image": image_base64
-    }
-    try:
-        response = requests.post(url, data=payload)
-        response.raise_for_status()
-        imgbb_link = response.json()["data"]["url"]
-        logging.info(f"Image successfully uploaded to Imgbb: {imgbb_link}")
-        return imgbb_link
-    except requests.exceptions.RequestException as e:
-        logging.error(f"Error uploading to Imgbb: {e}")
-        if 'response' in locals() and response is not None:
-            logging.error(f"Imgbb API Response: {response.status_code} - {response.text}")
-        return None
-
-def get_base64_from_url(image_url: str):
+def get_image_url_from_line(message_id):
     """
-    從 URL 下載圖片並轉換為 Base64 編碼。
+    從 Line 訊息 ID 獲取圖片內容並儲存到暫存檔案。
     """
     try:
-        response = requests.get(image_url)
-        response.raise_for_status()
-        return base64.b64encode(response.content).decode('utf-8')
-    except requests.exceptions.RequestException as e:
-        logging.error(f"Error fetching image from URL: {image_url}, error: {e}")
+        message_content = line_bot_api.get_message_content(message_id)
+        file_path = f"/tmp/{message_id}.png"
+        with open(file_path, "wb") as f:
+            for chunk in message_content.iter_content():
+                f.write(chunk)
+        print(f"✅ 圖片成功儲存到：{file_path}")
+        return file_path
+    except Exception as e:
+        print(f"❌ 圖片取得失敗：{e}")
         return None
 
-def get_gemini_response(prompt: str, images: list, api_url: str):
-    logging.info("Sending request to Gemini API.")
-    payload = {
-        "contents": [
-            {
-                "parts": [
-                    {"text": prompt}
-                ] + [
-                    {"inlineData": {"mimeType": "image/jpeg", "data": img}} for img in images
-                ]
-            }
-        ]
-    }
-    
-    try:
-        response = requests.post(f"{api_url}?key={GOOGLE_API_KEY}", json=payload, timeout=120) # Increased timeout for image generation
-        response.raise_for_status()
-        response_data = response.json()
-        if 'candidates' in response_data and response_data['candidates']:
-            gemini_text = response_data['candidates'][0]['content']['parts'][0]['text']
-            logging.info("Successfully received response from Gemini.")
-            return gemini_text
-        else:
-            logging.error(f"Gemini API response has no candidates: {response.text}")
-            return "Gemini API 暫時無法提供服務，請稍後再試。"
-    except requests.exceptions.RequestException as e:
-        logging.error(f"Gemini API request failed: {e}")
-        return f"Gemini API 請求失敗：{e}"
-
-def get_virtual_tryon_image(user_photo_base64: str, upper_body_image_base64: str, lower_body_image_base64: str):
+def store_user_message(user_id, message_type, message_content):
     """
-    使用 gemini-2.5-flash-image-preview (nanobanana) 模擬虛擬試穿。
+    儲存用戶的訊息。
     """
-    logging.info("Attempting virtual try-on with gemini-2.5-flash-image-preview.")
-    
-    prompt = "請將提供的上衣和褲子，虛擬試穿到第一張人像照片上。結果必須看起來真實且自然，衣服的紋理和細節必須保留。"
-    
-    all_images_base64 = [user_photo_base64, upper_body_image_base64, lower_body_image_base64]
-    
-    payload = {
-        "contents": [
-            {
-                "parts": [
-                    {"text": prompt}
-                ] + [
-                    {"inlineData": {"mimeType": "image/jpeg", "data": img_base64}} for img_base64 in all_images_base64
-                ]
-            }
-        ],
-        "generationConfig": {
-            "responseModalities": ['IMAGE']
-        }
-    }
-    
-    try:
-        response = requests.post(f"{IMAGIN_API_URL}?key={GOOGLE_API_KEY}", json=payload, timeout=120)
-        response.raise_for_status()
-        response_data = response.json()
-        if 'candidates' in response_data and response_data['candidates']:
-            # 從回應中提取 Base64 編碼的圖片
-            image_part = response_data['candidates'][0]['content']['parts'][0]
-            if image_part and 'inlineData' in image_part:
-                generated_image_base64 = image_part['inlineData']['data']
-                # 將生成的 Base64 圖片上傳到 Imgbb
-                virtual_tryon_url = upload_to_imgbb(generated_image_base64)
-                if virtual_tryon_url:
-                    logging.info(f"Successfully generated and uploaded virtual try-on image: {virtual_tryon_url}")
-                    return virtual_tryon_url
-                else:
-                    logging.error("Failed to upload generated image to Imgbb.")
-                    return None
-            else:
-                logging.error("Gemini image response format is invalid.")
-                return None
-        else:
-            logging.error(f"Gemini image generation response has no candidates: {response.text}")
-            return None
-    except requests.exceptions.RequestException as e:
-        logging.error(f"Gemini image generation API request failed: {e}")
-        return None
+    user_message_history[user_id].append(
+        {"type": message_type, "content": message_content}
+    )
 
-def generate_outfit_image(upper_body_images: list, lower_body_images: list):
+def get_previous_message(user_id):
     """
-    使用 gemini-2.5-flash-image-preview 生成一套全新的穿搭圖片。
+    獲取用戶的上一則訊息。
     """
-    logging.info("Attempting to generate a new outfit image.")
-
-    prompt = "使用提供的上���和褲子/裙子圖片，生成一套完整且時尚的穿搭圖片。請將衣服呈現在一個有模特兒穿著或是在平面上呈現的完整畫面中。風格應與提供的衣物相符。"
-    
-    all_images_base64 = (
-        [get_base64_from_url(url) for url in upper_body_images] +
-        [get_base64_from_url(url) for url in lower_body_images]
-    )
+    if user_id in user_message_history and len(user_message_history[user_id]) > 0:
+        return user_message_history[user_id][-1]
+    return {"type": "text", "content": "No message!"}
 
-    payload = {
-        "contents": [
-            {
-                "parts": [
-                    {"text": prompt}
-                ] + [
-                    {"inlineData": {"mimeType": "image/jpeg", "data": img_base64}} for img_base64 in all_images_base64
-                ]
-            }
-        ],
-        "generationConfig": {
-            "responseModalities": ['IMAGE']
-        }
-    }
 
-    try:
-        response = requests.post(f"{IMAGIN_API_URL}?key={GOOGLE_API_KEY}", json=payload, timeout=120)
-        response.raise_for_status()
-        response_data = response.json()
-        if 'candidates' in response_data and response_data['candidates']:
-            image_part = response_data['candidates'][0]['content']['parts'][0]
-            if image_part and 'inlineData' in image_part:
-                generated_image_base64 = image_part['inlineData']['data']
-                generated_image_url = upload_to_imgbb(generated_image_base64)
-                if generated_image_url:
-                    logging.info(f"Successfully generated and uploaded new outfit image: {generated_image_url}")
-                    return generated_image_url
-                else:
-                    logging.error("Failed to upload generated outfit image to Imgbb.")
-                    return None
-            else:
-                logging.error("Gemini image response format is invalid for outfit generation.")
-                return None
-        else:
-            logging.error(f"Gemini outfit generation response has no candidates: {response.text}")
-            return None
-    except requests.exceptions.RequestException as e:
-        logging.error(f"Gemini outfit generation API request failed: {e}")
-        return None
+# ==========================
+#  LangChain 工具定義
+# ==========================
 
-def save_image_locally(image_binary: bytes):
+@tool
+def generate_and_upload_image(prompt: str) -> str:
     """
-    將二進位圖片資料儲存到本地，並返回一個可供外部存取的 URL。
+    這個工具可以根據文字提示生成圖片，並將其上傳到伺服器。
+    
+    Args:
+        prompt: 用於生成圖片的文字提示。
+        
+    Returns:
+        回傳生成圖片的 URL。
     """
     try:
-        # 確保 'static' 資料夾存在
-        if not os.path.exists("static"):
-            os.makedirs("static")
+        response = genai_client.models.generate_content(
+            model="gemini-2.0-flash-preview-image-generation",
+            contents=prompt,
+            config=types.GenerateContentConfig(response_modalities=['Text', 'Image'])
+        )
         
-        image = Image.open(io.BytesIO(image_binary))
-        # 隨機生成一個檔案名以避免衝突
-        file_name = f"static/{os.urandom(16).hex()}.png"
-        image.save(file_name, format="PNG")
+        image_binary = None
+        for part in response.candidates[0].content.parts:
+            if part.inline_data is not None:
+                image_binary = part.inline_data.data
+                break
         
-        image_url = os.path.join(HF_SPACE_URL, file_name)
-        logging.info(f"Image successfully saved locally: {image_url}")
-        return image_url
+        if image_binary:
+            image = PIL.Image.open(io.BytesIO(image_binary))
+            # 隨機生成一個檔案名以避免衝突
+            file_name = f"static/{os.urandom(16).hex()}.png"
+            image.save(file_name, format="PNG")
+            
+            image_url = os.path.join(os.getenv("HF_SPACE"), file_name)
+            return image_url
+            
+        return "圖片生成失敗。"
     except Exception as e:
-        logging.error(f"Error saving image locally: {e}")
-        return None
-
-
-@line_handler.add(MessageEvent, message=TextMessage)
-def handle_text_message(event):
-    user_id = event.source.user_id
-    text = event.message.text.lower()
-    reply_token = event.reply_token
-
-    logging.info(f"Received text message from user {user_id}: '{text}'")
+        return f"圖片生成與上傳失敗: {e}"
 
-    # 新增 重置 功能
-    if text in ["重置", "重來", "重新開始", "再一次"]:
-        user_states[user_id] = defaultdict(lambda: {"upper_body_images": [], "lower_body_images": [], "current_mode": None, "is_ready_for_outfit": False, "is_ready_for_photo": False, "user_info": {}, "personal_photo": None, "personal_photo_base64": None})[user_id]
-        line_bot_api.reply_message(
-            reply_token,
-            TextSendMessage(text="狀態已重置。請重新輸入個人資訊，格式為：身高,胸圍,腰圍,臀圍,場合。例如：165,85,65,90,約會")
-        )
-        return
+@tool
+def analyze_image_with_text(image_path: str, user_text: str) -> str:
+    """
+    這個工具可以根據圖片和文字提示來回答問題。
     
-    # 新增 圖片生成穿搭功能
-    if text in ["生成穿搭", "圖片推薦"] and user_states[user_id]["is_ready_for_outfit"]:
-        if len(user_states[user_id]["upper_body_images"]) == MAX_IMAGES_PER_TYPE and len(user_states[user_id]["lower_body_images"]) == MAX_IMAGES_PER_TYPE:
-            line_bot_api.reply_message(
-                reply_token,
-                TextSendMessage(text="好的，正在為您生成一套新的穿搭圖片，請稍候...")
-            )
-            
-            generated_outfit_url = generate_outfit_image(
-                user_states[user_id]["upper_body_images"],
-                user_states[user_id]["lower_body_images"]
-            )
-
-            if generated_outfit_url:
-                line_bot_api.push_message(
-                    user_id,
-                    ImageSendMessage(original_content_url=generated_outfit_url, preview_image_url=generated_outfit_url)
-                )
-                line_bot_api.push_message(
-                    user_id,
-                    TextSendMessage(text="這是根據您的衣物生成的圖片推薦。如果想再次使用，請輸入「重置」。")
-                )
-            else:
-                line_bot_api.push_message(
-                    user_id,
-                    TextSendMessage(text="圖片生成失敗，請稍後再試。")
-                )
+    Args:
+        image_path: 圖片在本地端儲存的路徑。
+        user_text: 針對圖片提出的文字問題。
+        
+    Returns:
+        模型針對圖片和文字提示給出的回應。
+    """
+    try:
+        if not os.path.exists(image_path):
+            return "圖片路徑無效，無法進行分析。"
             
-            # 生成後重置狀態
-            user_states[user_id] = defaultdict(lambda: {"upper_body_images": [], "lower_body_images": [], "current_mode": None, "is_ready_for_outfit": False, "is_ready_for_photo": False, "user_info": {}, "personal_photo": None, "personal_photo_base64": None})[user_id]
-            return
+        img_user = PIL.Image.open(image_path)
+        response = genai_client.models.generate_content(
+                    model="gemini-2.5-flash",
+                    contents=[img_user, user_text]
+        )
+        if (response.text != None):
+            out = response.text
         else:
-            line_bot_api.reply_message(
-                reply_token,
-                TextSendMessage(text="請先上傳三件上衣和三件褲子/裙子圖片。")
-            )
-            return
-
-    # 處理個人資訊輸入
-    if not user_states[user_id]["is_ready_for_outfit"] and not user_states[user_id]["is_ready_for_photo"]:
-        try:
-            parts = text.split(',')
-            if len(parts) == 5:
-                height = float(parts[0])
-                bust = float(parts[1])
-                waist = float(parts[2])
-                hip = float(parts[3])
-                occasion = parts[4].strip()
-                
-                user_states[user_id]["user_info"] = {
-                    "height": height,
-                    "bust": bust,
-                    "waist": waist,
-                    "hip": hip,
-                    "occasion": occasion
-                }
-                user_states[user_id]["is_ready_for_outfit"] = True
-                
-                line_bot_api.reply_message(
-                    reply_token,
-                    TextSendMessage(text=f"已收到您的資訊！接下來請上傳三件上衣和三件褲子的圖片。請先輸入「上衣」或「褲子」來開始。")
-                )
-                return
-        except ValueError:
-            logging.error(f"Invalid user info format: '{text}'")
-            line_bot_api.reply_message(
-                reply_token,
-                TextSendMessage(text="請依照格式輸入：身高,胸圍,腰圍,臀圍,場合。例如：165,85,65,90,約會")
-            )
-            return
-
-    # 處理衣物上傳模式
-    if user_states[user_id]["is_ready_for_outfit"]:
-        if text == "上衣":
-            user_states[user_id]["current_mode"] = "upper"
-            line_bot_api.reply_message(
-                reply_token,
-                TextSendMessage(text=f"請上傳三件上衣圖片，您已上傳 {len(user_states[user_id]['upper_body_images'])}/{MAX_IMAGES_PER_TYPE} 張。")
-            )
-            return
-        elif text in ["褲子", "裙子"]:
-            user_states[user_id]["current_mode"] = "lower"
-            line_bot_api.reply_message(
-                reply_token,
-                TextSendMessage(text=f"請上傳三件褲子/裙子圖片，您已上傳 {len(user_states[user_id]['lower_body_images'])}/{MAX_IMAGES_PER_TYPE} 張。")
-            )
-            return
+            out = "Gemini沒答案!請換個說法！"
+    except Exception as e:
+        # 處理錯誤
+        out = f"Gemini執行出錯: {e}"
         
-    # 如果沒有進入任何模式，給予提示
-    line_bot_api.reply_message(
-        reply_token,
-        TextSendMessage(text="請先依照格式輸入個人資訊，格式為：身高,胸圍,腰圍,臀圍,場合。例如：165,85,65,90,約會")
-    )
+    return out
 
 
-@line_handler.add(MessageEvent, message=ImageMessage)
-def handle_image_message(event):
-    user_id = event.source.user_id
-    reply_token = event.reply_token
-    
-    logging.info(f"Received image message from user {user_id}")
+# ==========================
+#  LangChain 代理人設定
+# ==========================
 
-    # 檢查是否已準備好處理圖片
-    if not user_states[user_id]["is_ready_for_outfit"]:
-        logging.warning("User is not in outfit collection mode.")
-        line_bot_api.reply_message(
-            reply_token,
-            TextSendMessage(text="請先輸入個人資訊，格式為：身高,胸圍,腰圍,臀圍,場合。例如：165,85,65,90,約會")
-        )
-        return
+# 結合所有工具
+tools = [generate_and_upload_image, analyze_image_with_text]
 
-    # 檢查是否所有衣物都已上傳
-    is_outfit_complete = (
-        len(user_states[user_id]["upper_body_images"]) == MAX_IMAGES_PER_TYPE and
-        len(user_states[user_id]["lower_body_images"]) == MAX_IMAGES_PER_TYPE
-    )
+# 建立 LLM 模型實例
+llm = ChatGoogleGenerativeAI(google_api_key=google_api, model="gemini-2.5-flash", temperature=0.2)
 
-    # 處理個人照片上傳
-    if is_outfit_complete and not user_states[user_id]["personal_photo"]:
-        try:
-            image_id = event.message.id
-            # 取得圖片的二進位資料
-            image_content = line_bot_api.get_message_content(image_id).content
-            
-            # 使用新函式來儲存圖片並取得 URL
-            photo_url = save_image_locally(image_content)
-            if not photo_url:
-                raise Exception("Failed to save personal photo locally.")
+# 建立提示模板
+prompt_template = ChatPromptTemplate([
+    ("system", "你是一個強大的圖像生成與問答助理，可以根據用戶的請求使用提供的工具。當你執行 generate_and_upload_image 工具\
+    成功後會獲得一個 URL，然後你回答的 output 要包含有這個 URL 的完整資訊。如果工具有產生錯誤訊息請解讀並回應。"),
+    ("user", "{input}"),
+    ("placeholder", "{agent_scratchpad}"),
+])
 
-            user_states[user_id]["personal_photo"] = photo_url
-            user_states[user_id]["is_ready_for_photo"] = True
-            
-            line_bot_api.reply_message(
-                reply_token,
-                TextSendMessage(text="已收到您的個人照片，正在為您準備穿搭... 請稍候。")
-            )
-            
-            # 準備 Gemini 提示
-            user_info = user_states[user_id]["user_info"]
-            occasion = user_info["occasion"]
-            
-            prompt = (
-                f"我提供了三件上衣圖片和三件下半身圖片，以及使用者的一張個人照片。使用者資訊：身高 {user_info['height']}cm，三圍 {user_info['bust']}-{user_info['waist']}-{user_info['hip']}，場合是「{occasion}」。"
-                "請根據這些衣物，為我推薦一套最適合的穿搭，並詳細說明為何這套搭配適合這個場合。請以繁體中文回答。"
-                "請在描述中以圖片連結的形式（例如：'https://example.com/outfit1.jpg'）顯示你搭配好的衣物組合。"
-            )
-            
-            # 取得圖片的 Base64 編碼，用於 Gemini API 呼叫
-            all_images_base64 = (
-                [get_base64_from_url(url) for url in user_states[user_id]["upper_body_images"]] +
-                [get_base64_from_url(url) for url in user_states[user_id]["lower_body_images"]] +
-                [get_base64_from_url(photo_url)]
-            )
-            
-            response_text = get_gemini_response(prompt, all_images_base64, GEMINI_API_URL)
-            
-            # 從 Gemini 建議中找出最佳搭配的衣物圖片（這裡需要更複雜的邏輯，我們使用佔位符）
-            # 在實際應用中，您可以設計一個提示，讓 Gemini 返回最佳搭配的圖片索引
-            best_upper_index = 0
-            best_lower_index = 0
-
-            best_upper_body_image = user_states[user_id]["upper_body_images"][best_upper_index]
-            best_lower_body_image = user_states[user_id]["lower_body_images"][best_lower_index]
+# 建立代理人
+agent = create_tool_calling_agent(llm, tools, prompt_template)
+agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
 
-            # 呼叫虛擬試穿 API，並取得結果圖片 URL
-            virtual_tryon_url = get_virtual_tryon_image(get_base64_from_url(photo_url), get_base64_from_url(best_upper_body_image), get_base64_from_url(best_lower_body_image))
-            
-            # 發送 Gemini 的文字建議
-            line_bot_api.push_message(
-                user_id,
-                TextSendMessage(text=f"這是為您推薦的搭配：\n\n{response_text}")
-            )
-            
-            # 發送虛擬試穿照片
-            if virtual_tryon_url:
-                line_bot_api.push_message(
-                    user_id,
-                    ImageSendMessage(original_content_url=virtual_tryon_url, preview_image_url=virtual_tryon_url)
-                )
+# ==========================
+#  FastAPI 路由
+# ==========================
 
-            # 重置狀態以便下一次使用
-            user_states[user_id] = defaultdict(lambda: {"upper_body_images": [], "lower_body_images": [], "current_mode": None, "is_ready_for_outfit": False, "is_ready_for_photo": False, "user_info": {}, "personal_photo": None, "personal_photo_base64": None})[user_id]
-            return
-            
-        except Exception as e:
-            logging.error(f"Error processing personal photo: {e}")
-            line_bot_api.reply_message(
-                reply_token,
-                TextSendMessage(text=f"圖片處理失敗，請稍後再試。錯誤：{e}")
-            )
-            return
+@app.get("/")
+def root():
+    return {"title": "Line Bot"}
 
-    # 處理衣物圖片上傳
-    mode = user_states[user_id]["current_mode"]
-    if not mode:
-        logging.warning("User is not in a defined upload mode.")
-        line_bot_api.reply_message(
-            reply_token,
-            TextSendMessage(text="請先傳送「上衣」或「褲子」來選擇要上傳的衣服類型。")
+@app.post("/webhook")
+async def webhook(
+    request: Request,
+    background_tasks: BackgroundTasks,
+    x_line_signature=Header(None),
+):
+    body = await request.body()
+    try:
+        background_tasks.add_task(
+            line_handler.handle, body.decode("utf-8"), x_line_signature
         )
-        return
+    except InvalidSignatureError:
+        raise HTTPException(status_code=400, detail="Invalid signature")
+    return "ok"
 
-    try:
-        image_id = event.message.id
-        image_content = line_bot_api.get_message_content(image_id).content
-        
-        # 使用新函式來儲存圖片並取得 URL
-        image_url = save_image_locally(image_content)
-        if not image_url:
-            logging.error("Failed to save image locally.")
+@line_handler.add(MessageEvent, message=(ImageMessage, TextMessage))
+def handle_message(event):
+    user_id = event.source.user_id
+    
+    # 處理圖片上傳
+    if event.message.type == "image":
+        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(
-                reply_token,
-                TextSendMessage(text="圖片上傳失敗，請稍後再試。")
+                event.reply_token, TextSendMessage(text="圖片已接收成功囉，幫我輸入你想詢問的問題喔~")
             )
-            return
-            
-        if mode == "upper":
-            if len(user_states[user_id]["upper_body_images"]) < MAX_IMAGES_PER_TYPE:
-                user_states[user_id]["upper_body_images"].append(image_url)
-                reply_text = f"已接收上衣。上衣: {len(user_states[user_id]['upper_body_images'])}/{MAX_IMAGES_PER_TYPE}，褲子/裙子: {len(user_states[user_id]['lower_body_images'])}/{MAX_IMAGES_PER_TYPE}。"
-                if len(user_states[user_id]["upper_body_images"]) == MAX_IMAGES_PER_TYPE:
-                    reply_text += "上衣已收集完畢。"
-                line_bot_api.reply_message(
-                    reply_token,
-                    TextSendMessage(text=reply_text)
-                )
-                return
-            else:
-                logging.info("Upper body image count is full.")
-                line_bot_api.reply_message(
-                    reply_token,
-                    TextSendMessage(text="上衣數量已滿，請傳送「褲子」來上傳褲子圖片。")
-                )
-                return
-        else: # mode == "lower"
-            if len(user_states[user_id]["lower_body_images"]) < MAX_IMAGES_PER_TYPE:
-                user_states[user_id]["lower_body_images"].append(image_url)
-                reply_text = f"已接收褲子/裙子。上衣: {len(user_states[user_id]['upper_body_images'])}/{MAX_IMAGES_PER_TYPE}，褲子/裙子: {len(user_states[user_id]['lower_body_images'])}/{MAX_IMAGES_PER_TYPE}。"
-                if len(user_states[user_id]["lower_body_images"]) == MAX_IMAGES_PER_TYPE:
-                    reply_text += "褲子/裙子已收集完畢。"
-                line_bot_api.reply_message(
-                    reply_token,
-                    TextSendMessage(text=reply_text)
+        else:
+            line_bot_api.reply_message(
+                event.reply_token, TextSendMessage(text="沒有接收到圖片~")
+            )
+    
+    # 處理文字訊息
+    elif event.message.type == "text":
+        user_text = event.message.text
+        previous_message = get_previous_message(user_id)
+        print(previous_message)
+
+        # 根據上一則訊息類型，動態傳遞給代理人
+        if previous_message["type"] == "image":
+            image_path = previous_message["content"]
+            agent_input = {
+                "input": f"請根據這張圖片回答問題。圖片的路徑是 {image_path}，我的問題是：{user_text}"
+            }
+            # 清除上一則圖片訊息，避免重複觸發
+            user_message_history[user_id].pop()
+        else:
+            agent_input = {"input": user_text}
+        try:
+            # 運行代理人
+            response = agent_executor.invoke(agent_input)
+            out = response["output"]
+            if 'https' in out:
+                img_tmp = 'https'+out.split('https')[1]
+                image_url = img_tmp.split('png')[0]+'png'
+                line_bot_api.push_message(
+                    event.source.user_id,
+                    [
+                        TextSendMessage(text="✨ 這是我為你生成的圖片喔～"),
+                        ImageSendMessage(original_content_url=image_url, preview_image_url=image_url)
+                    ]
                 )
-                # 檢查是否所有圖片都已上傳完畢
-                if (len(user_states[user_id]["upper_body_images"]) == MAX_IMAGES_PER_TYPE and
-                    len(user_states[user_id]["lower_body_images"]) == MAX_IMAGES_PER_TYPE):
-                    line_bot_api.push_message(
-                        user_id,
-                        TextSendMessage(text="所有衣物圖片已收集完畢！\n\n現在您可以上傳**個人照片**進行虛擬試穿，或輸入「**生成穿搭**」來獲得圖片推薦。")
-                    )
-                return
             else:
-                logging.info("Lower body image count is full.")
-                line_bot_api.reply_message(
-                    reply_token,
-                    TextSendMessage(text="褲子數量已滿，請傳送「上衣」來上傳上衣圖片。")
-                )
-                return
-
-    except Exception as e:
-        logging.error(f"Error processing outfit image: {e}")
-        line_bot_api.reply_message(
-            reply_token,
-            TextSendMessage(text=f"圖片處理失敗，請稍後再試。錯誤：{e}")
-        )
+                line_bot_api.reply_message(event.reply_token, TextSendMessage(text=out))
+        except Exception as e:
+            print(f"代理人執行出錯: {e}")
+            out = f"代理人執行出錯!錯誤訊息：{e}"
+            line_bot_api.reply_message(event.reply_token, TextSendMessage(text=out))
 
 if __name__ == "__main__":
-    uvicorn.run(app, host="0.0.0.0", port=int(os.environ.get("PORT", 8080)))
+    uvicorn.run("app:app", host="0.0.0.0", port=7860, reload=True)