Update main.py

main.py

@@ -1,51 +1,36 @@
-import os
-import io
-import tempfile
-from collections import defaultdict
+from fastapi import FastAPI, Request, Header, BackgroundTasks, HTTPException, status
 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,
-    ImageSendMessage,
-    ImageMessage,
-)
-import PIL.Image
+from linebot.models import MessageEvent, TextMessage, TextSendMessage, ImageMessage
+import json
+import os
+import requests
+import base64
+from collections import defaultdict
 import uvicorn
 
-# 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"]):
+    raise ValueError("Missing environment variables. Please set CHANNEL_ACCESS_TOKEN, CHANNEL_SECRET, and GOOGLE_API_KEY.")
 
-
-# ==========================
-#  環境設定與工具函式
-# ==========================
-
-# 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 設定
 line_bot_api = LineBotApi(os.environ["CHANNEL_ACCESS_TOKEN"])
 line_handler = WebhookHandler(os.environ["CHANNEL_SECRET"])
 
-# 使用字典模擬用戶訊息歷史存儲
-user_message_history = defaultdict(list)
+# 使用者狀態追蹤
+user_states = defaultdict(lambda: {
+    "upper_body_images": [],
+    "lower_body_images": [],
+    "current_mode": None, # "upper" or "lower"
+})
+
+MAX_IMAGES = 6
+GEMINI_API_URL = "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-preview-05-20:generateContent"
+GOOGLE_API_KEY = os.environ["GOOGLE_API_KEY"]
 
-# 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=["*"],
@@ -54,141 +39,9 @@ app.add_middleware(
     allow_headers=["*"],
 )
 
-def get_image_url_from_line(message_id):
-    """
-    從 Line 訊息 ID 獲取圖片內容並儲存到暫存檔案。
-    """
-    try:
-        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 store_user_message(user_id, message_type, message_content):
-    """
-    儲存用戶的訊息。
-    """
-    user_message_history[user_id].append(
-        {"type": message_type, "content": message_content}
-    )
-
-def get_previous_message(user_id):
-    """
-    獲取用戶的上一則訊息。
-    """
-    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!"}
-
-
-# ==========================
-#  LangChain 工具定義
-# ==========================
-
-@tool
-def generate_and_upload_image(prompt: str) -> str:
-    """
-    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:
-        生成圖片的 URL。
-    """
-    try:
-        response = genai_client.models.generate_content(
-            model="gemini-2.0-flash-preview-image-generation",
-            contents=prompt,
-            config=types.GenerateContentConfig(response_modalities=['Text', 'Image'])
-        )
-        
-        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
-        
-        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:
-        return f"圖片生成與上傳失敗: {e}"
-
-@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。
-    
-    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。"
-            
-        img_user = PIL.Image.open(image_path)
-        response = genai_client.models.generate_content(
-                    model="gemini-2.5-flash",
-                    config=types.GenerateContentConfig(response_mime_type="application/json"),
-                    contents=[img_user, user_text]
-        )
-        if (response.text != None):
-            out = response.text
-        else:
-            out = "Gemini沒答案!請換個說法！"
-    except:
-        # 處理錯誤
-        out = "Gemini執行出錯!請換個說法！"
-        
-    return out
-
-
-# ==========================
-#  LangChain 代理人設定
-# ==========================
-
-# 結合所有工具
-tools = [generate_and_upload_image, analyze_image_with_text]
-
-# 建立 LLM 模型實例
-llm = ChatGoogleGenerativeAI(google_api_key=google_api, model="gemini-2.5-flash", temperature=0.2)
-
-# 建立提示模板
-prompt_template = ChatPromptTemplate([
-    ("system", "你是一個強大的助理，可以根據用戶的請求使用提供的工具。"),
-    ("user", "{input}"),
-    ("placeholder", "{agent_scratchpad}"),
-])
-
-# 建立代理人
-agent = create_tool_calling_agent(llm, tools, prompt_template)
-agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
-
-# ==========================
-#  FastAPI 路由
-# ==========================
-
 @app.get("/")
 def root():
-    return {"title": "Line Bot"}
+    return {"title": "Line Bot 穿搭建議"}
 
 @app.post("/webhook")
 async def webhook(
@@ -198,67 +51,141 @@ async def webhook(
 ):
     body = await request.body()
     try:
-        background_tasks.add_task(
-            line_handler.handle, body.decode("utf-8"), x_line_signature
-        )
+        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"
 
-@line_handler.add(MessageEvent, message=(ImageMessage, TextMessage))
-def handle_message(event):
+def get_base64_image(message_id: str):
+    message_content = line_bot_api.get_message_content(message_id)
+    image_bytes = message_content.content
+    return base64.b64encode(image_bytes).decode('utf-8')
+
+def get_gemini_response(prompt: str, images: list):
+    payload = {
+        "contents": [
+            {
+                "parts": [
+                    {"text": prompt}
+                ] + [
+                    {"inlineData": {"mimeType": "image/jpeg", "data": img}} for img in images
+                ]
+            }
+        ]
+    }
+    
+    response = requests.post(f"{GEMINI_API_URL}?key={GOOGLE_API_KEY}", json=payload)
+    if response.status_code == 200:
+        return response.json()['candidates'][0]['content']['parts'][0]['text']
+    else:
+        return f"Gemini API 請求失敗：{response.status_code}, {response.text}"
+
+@line_handler.add(MessageEvent, message=TextMessage)
+def handle_text_message(event):
     user_id = event.source.user_id
+    text = event.message.text.lower()
     
-    # 處理圖片上傳
-    if event.message.type == "image":
-        image_path = get_image_url_from_line(event.message.id)
-        print(image_path)
-        if image_path:
-            store_user_message(user_id, "image", image_path)
+    if text == "上衣":
+        user_states[user_id]["current_mode"] = "upper"
+        line_bot_api.reply_message(
+            event.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} 張。")
+        )
+    elif text == "褲子":
+        user_states[user_id]["current_mode"] = "lower"
+        line_bot_api.reply_message(
+            event.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} 張。")
+        )
+    elif text == "重置":
+        user_states[user_id] = defaultdict(lambda: {"upper_body_images": [], "lower_body_images": [], "current_mode": None})[user_id]
+        line_bot_api.reply_message(
+            event.reply_token,
+            TextSendMessage(text="狀態已重置。請傳送「上衣」或「褲子」來開始上傳。")
+        )
+    else:
+        line_bot_api.reply_message(
+            event.reply_token,
+            TextSendMessage(text="請先傳送「上衣」或「褲子」來選擇要上傳的衣服類型。")
+        )
+
+@line_handler.add(MessageEvent, message=ImageMessage)
+def handle_image_message(event):
+    user_id = event.source.user_id
+    reply_token = event.reply_token
+    
+    mode = user_states[user_id]["current_mode"]
+    
+    if not 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。")
+        )
+        return
+
+    try:
+        image_id = event.message.id
+        base64_img = get_base64_image(image_id)
+        
+        if mode == "upper":
+            if len(user_states[user_id]["upper_body_images"]) < MAX_IMAGES:
+                user_states[user_id]["upper_body_images"].append(base64_img)
+            else:
+                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:
+                user_states[user_id]["lower_body_images"].append(base64_img)
+            else:
+                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
+
+        upper_count = len(user_states[user_id]["upper_body_images"])
+        lower_count = len(user_states[user_id]["lower_body_images"])
+        
+        if upper_count < MAX_IMAGES or lower_count < MAX_IMAGES:
             line_bot_api.reply_message(
-                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~")
+                reply_token,
+                TextSendMessage(text=f"已接收。上衣: {upper_count}/{MAX_IMAGES}，褲子/裙子: {lower_count}/{MAX_IMAGES}。")
             )
         else:
             line_bot_api.reply_message(
-                event.reply_token, TextSendMessage(text="沒有接收到圖片~")
+                reply_token,
+                TextSendMessage(text="已收到所有圖片，正在為您分析並產生穿搭建議... 請稍候。")
+            )
+            
+            all_images = user_states[user_id]["upper_body_images"] + user_states[user_id]["lower_body_images"]
+            
+            prompt = (
+                f"我提供了 {MAX_IMAGES} 張上衣圖片和 {MAX_IMAGES} 張下半身圖片（共 {MAX_IMAGES*2} 張）。"
+                "請根據這些衣服，為我推薦三種不同場合的穿搭建議，並盡可能將不同的上衣和下衣進行搭配。"
+                "請考慮以下場合：1. 約會，2. 結婚典禮，3. 工作。\n\n"
+                "對於每種場合，請提供一個簡短的段落說明，解釋為何這個搭配適合該場合，並詳細描述你推薦的上衣與下衣組合。請以繁體中文回答。"
+            )
+            
+            response_text = get_gemini_response(prompt, all_images)
+            
+            line_bot_api.push_message(
+                user_id,
+                TextSendMessage(text=response_text)
             )
-    
-    # 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)
-                    ]
-                )
-            else:
-                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))
+            # 重置狀態以便下一次使用
+            user_states[user_id]["upper_body_images"] = []
+            user_states[user_id]["lower_body_images"] = []
+            user_states[user_id]["current_mode"] = None
+            
+    except Exception as 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}")
+        )
 
 if __name__ == "__main__":
-    uvicorn.run("app:app", host="0.0.0.0", port=7860, reload=True)
+    uvicorn.run(app, host="0.0.0.0", port=int(os.environ.get("PORT", 8080)))