Update app.py

app.py

@@ -14,34 +14,34 @@ app.add_middleware(
     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
+        print("Step 1: sending receiving status")
         await websocket.send_json({"status": "receiving"})
+
+        print("Step 2: waiting for bytes")
         audio_bytes = await websocket.receive_bytes()
+        print(f"Step 3: received {len(audio_bytes)} bytes")
 
-        # مرحله ۲ — ذخیره موقت روی دیسک
         with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as tmp:
             tmp.write(audio_bytes)
             tmp_path = tmp.name
+        print(f"Step 4: saved to {tmp_path}")
 
-        # مرحله ۳ — transcription
         await websocket.send_json({"status": "transcribing"})
+        print("Step 5: starting transcription")
 
         segments_raw, info = model.transcribe(
             tmp_path,
@@ -49,8 +49,8 @@ async def transcribe(websocket: WebSocket):
             word_timestamps=True,
             vad_filter=True,
         )
+        print("Step 6: transcription generator ready")
 
-        # مرحله ۴ — تبدیل به لیست قابل پردازش
         await websocket.send_json({"status": "processing"})
 
         segments = []
@@ -67,22 +67,29 @@ async def transcribe(websocket: WebSocket):
                     for w in words
                 ],
             })
+        print(f"Step 7: got {len(segments)} segments")
 
-        # مرحله ۵ — Post-Processing (اون ۲۰٪ طلایی)
         srt_content = process(segments)
+        print(f"Step 8: SRT built, length={len(srt_content)}")
 
-        # مرحله ۶ — ارسال نتیجه
         await websocket.send_json({
             "status": "done",
             "srt": srt_content,
             "language": info.language,
             "duration": info.duration,
         })
+        print("Step 9: done sent!")
 
     except WebSocketDisconnect:
-        pass
+        print("WebSocket disconnected by client")
     except Exception as e:
-        await websocket.send_json({"status": "error", "message": str(e)})
+        print(f"ERROR: {type(e).__name__}: {e}")
+        import traceback
+        traceback.print_exc()
+        try:
+            await websocket.send_json({"status": "error", "message": str(e)})
+        except Exception:
+            pass
     finally:
         if tmp_path and os.path.exists(tmp_path):
             os.remove(tmp_path)