Delete app.py

app.py

@@ -1,131 +0,0 @@
-import os
-import time
-import shutil
-from pydub import AudioSegment
-from openai import OpenAI
-import gradio as gr
-from fastapi import FastAPI, UploadFile, File, Form
-from threading import Thread
-import uvicorn
-
-# ======================================================
-# 🔐 設定區
-# ======================================================
-PASSWORD = os.getenv("APP_PASSWORD", "chou")
-MAX_SIZE = 25 * 1024 * 1024
-client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
-
-print("===== 🚀 啟動中 =====")
-print(f"APP_PASSWORD: {'✅ 已載入' if PASSWORD else '❌ 未載入'}")
-print(f"目前密碼內容：{PASSWORD}")
-
-# ======================================================
-# 🎧 音訊轉錄核心
-# ======================================================
-def split_audio_if_needed(path):
-    size = os.path.getsize(path)
-    if size <= MAX_SIZE:
-        return [path]
-    audio = AudioSegment.from_file(path)
-    n = int(size / MAX_SIZE) + 1
-    chunk_ms = len(audio) / n
-    parts = []
-    for i in range(n):
-        fn = f"chunk_{i+1}.wav"
-        audio[int(i * chunk_ms):int((i + 1) * chunk_ms)].export(fn, format="wav")
-        parts.append(fn)
-    return parts
-
-def transcribe_core(path, model="whisper-1"):
-    if path.lower().endswith(".mp4"):
-        fixed = path[:-4] + ".m4a"
-        try:
-            shutil.copy(path, fixed)
-            path = fixed
-        except Exception as e:
-            print(f"⚠️ mp4→m4a 轉檔失敗：{e}")
-
-    chunks = split_audio_if_needed(path)
-    txts = []
-    for f in chunks:
-        with open(f, "rb") as af:
-            res = client.audio.transcriptions.create(model=model, file=af, response_format="text")
-            txts.append(res)
-    full_raw = "\n".join(txts)
-
-    conv_prompt = (
-        "請將以下內容完整轉換為「繁體中文（台灣用語）」：\n"
-        "規則：1) 僅做簡→繁字形轉換；2) 不要意譯或改寫；3) 不要添加任何前後綴。\n-----\n" + full_raw
-    )
-    trad = client.chat.completions.create(
-        model="gpt-4o-mini",
-        messages=[
-            {"role": "system", "content": "你是嚴格的繁體中文轉換器。"},
-            {"role": "user", "content": conv_prompt}
-        ],
-        temperature=0.0,
-    ).choices[0].message.content.strip()
-
-    sum_prompt = (
-        "請用台灣繁體中文撰寫摘要。若內容資訊多，可條列出重點；"
-        "若內容簡短，請用一句話概述即可。\n\n" + trad
-    )
-    summ = client.chat.completions.create(
-        model="gpt-4o-mini",
-        messages=[
-            {"role": "system", "content": "你是一位精準且嚴格使用台灣繁體中文的摘要助手。"},
-            {"role": "user", "content": sum_prompt}
-        ],
-        temperature=0.2,
-    ).choices[0].message.content.strip()
-
-    return trad, summ
-
-# ======================================================
-# 🌐 FastAPI for 捷徑
-# ======================================================
-api_app = FastAPI()
-
-@api_app.post("/api/transcribe")
-async def api_transcribe(file: UploadFile = File(...), token: str = Form(...)):
-    if token != PASSWORD:
-        return {"error": "Invalid token"}
-    temp = file.filename
-    with open(temp, "wb") as f:
-        f.write(await file.read())
-    text, summary = transcribe_core(temp)
-    os.remove(temp)
-    return {"text": text, "summary": summary}
-
-# ======================================================
-# 💬 Gradio 介面
-# ======================================================
-def transcribe_with_password(password, file):
-    if password.strip() != PASSWORD:
-        return "❌ 密碼錯誤", "", ""
-    if not file:
-        return "⚠️ 未選擇檔案", "", ""
-    text, summary = transcribe_core(file.name)
-    return "✅ 完成", text, summary
-
-with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    gr.Markdown("## 🎧 LINE 語音轉錄與摘要（支援 .m4a / .mp4）")
-    pw = gr.Textbox(label="輸入密碼", type="password")
-    f = gr.File(label="上傳音訊檔")
-    run = gr.Button("開始轉錄 🚀")
-    s = gr.Textbox(label="狀態", interactive=False)
-    t = gr.Textbox(label="轉錄結果", lines=10)
-    su = gr.Textbox(label="AI 摘要", lines=8)
-    run.click(transcribe_with_password, [pw, f], [s, t, su])
-
-# ======================================================
-# 🚀 啟動
-# ======================================================
-def run_api():
-    uvicorn.run(api_app, host="0.0.0.0", port=7861)
-
-Thread(target=run_api, daemon=True).start()
-app = demo  # ✅ Hugging Face 主入口使用 Gradio
-
-if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0", server_port=7860)