Update app.py

app.py

@@ -1,9 +1,10 @@
 import os
+import gradio as gr
 from fastapi import FastAPI, UploadFile, Form, HTTPException
 from fastapi.responses import JSONResponse
 from openai import OpenAI
-import gradio as gr
 
+# === 初始化 ===
 print("===== 🚀 啟動中 =====")
 OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
 APP_PASSWORD = os.getenv("APP_PASSWORD")
@@ -13,18 +14,19 @@ print(f"APP_PASSWORD: {APP_PASSWORD}")
 
 client = OpenAI(api_key=OPENAI_API_KEY)
 
-# === FastAPI 主應用 ===
-api = FastAPI(title="Voice Transcribe API")
+# === FastAPI 主要後端 ===
+app = FastAPI(title="LINE Audio Transcriber")
 
-@api.get("/ping")
+@app.get("/ping")
 async def ping():
-    return {"status": "ok", "APP_PASSWORD": APP_PASSWORD is not None}
+    return {"status": "ok", "APP_PASSWORD": bool(APP_PASSWORD)}
 
-@api.post("/api/transcribe")
+@app.post("/api/transcribe")
 async def transcribe_api(file: UploadFile, token: str = Form(...)):
-    print(f"📥 收到 API 請求：{file.filename}, token={token}")
+    print(f"📥 收到請求: {file.filename}, token={token}")
+
     if not APP_PASSWORD:
-        raise HTTPException(status_code=500, detail="APP_PASSWORD not set")
+        raise HTTPException(status_code=500, detail="APP_PASSWORD not set.")
     if token != APP_PASSWORD:
         raise HTTPException(status_code=403, detail="Forbidden: invalid token")
 
@@ -32,13 +34,13 @@ async def transcribe_api(file: UploadFile, token: str = Form(...)):
     with open(temp_path, "wb") as f:
         f.write(await file.read())
 
-    # 語音轉文字
+    # whisper 轉錄
     with open(temp_path, "rb") as audio_file:
         transcript = client.audio.transcriptions.create(model="whisper-1", file=audio_file)
     text = transcript.text.strip()
 
-    # 生成摘要
-    summary_prompt = f"請幫我用中文摘要以下內容：\n\n{text}"
+    # AI 摘要
+    summary_prompt = f"請用繁體中文摘要以下內容：\n\n{text}"
     summary = client.chat.completions.create(
         model="gpt-4o-mini",
         messages=[{"role": "user", "content": summary_prompt}]
@@ -46,15 +48,14 @@ async def transcribe_api(file: UploadFile, token: str = Form(...)):
 
     return JSONResponse({"text": text, "summary": summary})
 
-# === Gradio UI ===
+# === Gradio 介面 ===
 def gradio_ui(audio):
     if audio is None:
         return "請上傳音訊檔案", ""
     with open(audio, "rb") as f:
         transcript = client.audio.transcriptions.create(model="whisper-1", file=f)
     text = transcript.text.strip()
-
-    summary_prompt = f"請幫我用中文摘要以下內容：\n\n{text}"
+    summary_prompt = f"請用繁體中文摘要以下內容：\n\n{text}"
     summary = client.chat.completions.create(
         model="gpt-4o-mini",
         messages=[{"role": "user", "content": summary_prompt}]
@@ -66,10 +67,14 @@ demo = gr.Interface(
     inputs=gr.Audio(type="filepath", label="上傳音訊"),
     outputs=[gr.Textbox(label="轉錄文字"), gr.Textbox(label="AI 摘要")],
     title="LINE 語音轉錄與摘要 (API + UI)",
-    description="可透過網頁或捷徑呼叫 /api/transcribe"
+    description="可透過捷徑上傳音訊並取得文字摘要"
 )
 
-# ✅ 關鍵：讓 Hugging Face 找到 FastAPI 應用
-app = gr.mount_gradio_app(api, demo, path="/")
-# 暴露 app 物件給 Spaces runtime
-application = app
+# ✅ 關鍵修正：Spaces 預期的是 "app" 為 FastAPI，而不是混合物件
+# 我們手動掛上 Gradio，而不是使用 mount_gradio_app
+from gradio.routes import mount_gradio_app
+
+gr_app = mount_gradio_app(app, demo, path="/")
+
+# Hugging Face 需要一個變數叫 application
+application = gr_app