Update app.py

app.py

@@ -24,7 +24,7 @@ try:
         "ivrit-ai/pyannote-speaker-diarization-3.1",
         use_auth_token=HF_TOKEN,
     )
-    pipeline.to(device)
+    pipeline.to(torch.device(device))  # ✅ תיקון כאן!
     print("✅ Model loaded successfully!")
 except Exception as e:
     print(f"❌ Failed to load model: {e}")
@@ -65,7 +65,6 @@ def estimate_duration(file_path: str) -> float:
     """אומדן אורך קובץ בדקות"""
     try:
         file_size_mb = os.path.getsize(file_path) / (1024 * 1024)
-        # אומדן: ~2MB לדקה (ממוצע)
         return file_size_mb / 2.0
     except Exception:
         return 0
@@ -128,39 +127,32 @@ async def diarize(file: UploadFile = File(...)):
     wav_path = None
     
     try:
-        # קריאת הקובץ
         content = await file.read()
         file_size_mb = len(content) / (1024 * 1024)
         
-        # בדיקת גודל
         if file_size_mb > MAX_FILE_SIZE_MB:
             raise HTTPException(
                 status_code=400,
                 detail=f"File too large: {file_size_mb:.1f}MB (max: {MAX_FILE_SIZE_MB}MB)"
             )
         
-        # בדיקת תור
         if active_requests >= MAX_CONCURRENT_REQUESTS:
             raise HTTPException(
                 status_code=503,
                 detail=f"Server busy ({active_requests}/{MAX_CONCURRENT_REQUESTS} active). Try again later."
             )
         
-        # עיבוד
         async with processing_semaphore:
             active_requests += 1
             
             try:
-                # שמירה זמנית
                 suffix = Path(file.filename).suffix or ".tmp"
                 with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as tmp:
                     tmp.write(content)
                     tmp_path = tmp.name
                 
-                # המרה ל-WAV
                 wav_path = ensure_wav_16k_mono(tmp_path)
                 
-                # אומדן אורך
                 duration = estimate_duration(wav_path)
                 if duration > MAX_DURATION_MINUTES:
                     raise HTTPException(
@@ -168,7 +160,6 @@ async def diarize(file: UploadFile = File(...)):
                         detail=f"File too long: ~{duration:.1f} min (max: {MAX_DURATION_MINUTES} min)"
                     )
                 
-                # זיהוי דוברים
                 print(f"🎤 Processing: {file.filename} ({file_size_mb:.1f}MB)")
                 start_time = datetime.now()
                 
@@ -177,7 +168,6 @@ async def diarize(file: UploadFile = File(...)):
                 processing_time = (datetime.now() - start_time).total_seconds()
                 print(f"✅ Done in {processing_time:.1f}s")
                 
-                # בניית תוצאות
                 segments = []
                 last_segment = None
                 
@@ -186,7 +176,6 @@ async def diarize(file: UploadFile = File(...)):
                     end = round(float(segment.end), 3)
                     speaker_id = str(speaker)
                     
-                    # איחוד מקטעים צמודים של אותו דובר
                     if (last_segment and 
                         last_segment["speaker"] == speaker_id and 
                         abs(start - last_segment["end"]) < 0.1):
@@ -203,7 +192,6 @@ async def diarize(file: UploadFile = File(...)):
                 if last_segment:
                     segments.append(last_segment)
                 
-                # סינון מקטעים קצרים
                 segments = [s for s in segments if s["end"] - s["start"] >= 0.2]
                 
                 return JSONResponse({
@@ -224,7 +212,6 @@ async def diarize(file: UploadFile = File(...)):
         print(f"❌ Error: {str(e)}")
         raise HTTPException(status_code=500, detail=f"Processing error: {str(e)}")
     finally:
-        # ניקוי
         for path in [tmp_path, wav_path]:
             if path and os.path.exists(path):
                 try:
@@ -235,4 +222,21 @@ async def diarize(file: UploadFile = File(...)):
 
 if __name__ == "__main__":
     import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=7860)
+    uvicorn.run(app, host="0.0.0.0", port=7860)
+```
+
+---
+
+## 🚀 עכשיו זה אמור לעבוד!
+
+1. **עדכן את `app.py`** ב-Space
+2. שמור
+3. המתן לבנייה (~1-2 דקות - כי יש cache)
+4. בדוק `/health`
+
+אחרי התיקון הזה, אמור לראות בלוגים:
+```
+🚀 Loading model on cpu...
+✅ Model loaded successfully!
+INFO:     Started server process
+INFO:     Uvicorn running on http://0.0.0.0:7860