Delete app.py

app.py

@@ -1,92 +0,0 @@
-import os
-import tempfile
-import asyncio
-from fastapi import FastAPI, WebSocket, WebSocketDisconnect
-from fastapi.middleware.cors import CORSMiddleware
-from faster_whisper import WhisperModel
-
-app = FastAPI()
-
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
-
-# ─── Model Load ───────────────────────────────────────────────────────────────
-print("Loading Whisper model...")
-model = WhisperModel("large-v3", device="cpu", compute_type="int8")
-print("Whisper model ready!")
-
-# ─── Health ───────────────────────────────────────────────────────────────────
-@app.get("/health")
-async def health():
-    return {"status": "ok", "message": "SubFlow backend is running"}
-
-# ─── WebSocket Transcribe ─────────────────────────────────────────────────────
-@app.websocket("/transcribe")
-async def transcribe(websocket: WebSocket):
-    await websocket.accept()
-    tmp_path = None
-
-    try:
-        # مرحله ۱ — دریافت فایل صوتی
-        await websocket.send_json({"status": "receiving"})
-        audio_bytes = await websocket.receive_bytes()
-
-        # مرحله ۲ — ذخیره موقت روی دیسک
-        with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as tmp:
-            tmp.write(audio_bytes)
-            tmp_path = tmp.name
-
-        # مرحله ۳ — transcription
-        await websocket.send_json({"status": "transcribing"})
-
-        segments, info = model.transcribe(
-            tmp_path,
-            language="en",
-            word_timestamps=True,
-            vad_filter=True,
-        )
-
-        # مرحله ۴ — ساخت SRT
-        await websocket.send_json({"status": "processing"})
-
-        srt_entries = []
-        index = 1
-
-        for segment in segments:
-            words = list(segment.words)
-            if not words:
-                continue
-
-            start = words[0].start
-            end = words[-1].end
-            text = segment.text.strip()
-
-            srt_entries.append({
-                "index": index,
-                "start": start,
-                "end": end,
-                "text": text,
-                "words": [{"word": w.word, "start": w.start, "end": w.end} for w in words]
-            })
-            index += 1
-
-        # مرحله ۵ — ارسال نتیجه
-        await websocket.send_json({
-            "status": "done",
-            "segments": srt_entries,
-            "language": info.language,
-            "duration": info.duration,
-        })
-
-    except WebSocketDisconnect:
-        pass
-    except Exception as e:
-        await websocket.send_json({"status": "error", "message": str(e)})
-    finally:
-        if tmp_path and os.path.exists(tmp_path):
-            os.remove(tmp_path)
-        await websocket.close()