Update app.py

app.py

@@ -1,16 +1,17 @@
-from pyannote.audio import Pipeline
-import gradio as gr
 import os
+import tempfile
+import gradio as gr
+from pyannote.audio import Pipeline
 
-# טען את ה-Token
+# שליפת Hugging Face Token מה-Secret
 hf_token = os.getenv("HF_TOKEN")
 if not hf_token:
-    raise ValueError("HF_TOKEN is missing. Set it in the Secrets section.")
+    raise ValueError("HF_TOKEN is missing. Please set it in the Secrets section.")
 
-# טען את המודל
+# טעינת מודל pyannote לזיהוי דוברים
 try:
     pipeline = Pipeline.from_pretrained(
-        "pyannote/speaker-diarization", 
+        "pyannote/speaker-diarization",
         use_auth_token=hf_token
     )
 except Exception as e:
@@ -19,21 +20,36 @@ except Exception as e:
 # פונקציה לזיהוי דוברים
 def diarize(audio):
     try:
-        diarization = pipeline(audio)
+        # שמירת האודיו לקובץ זמני
+        with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as temp_audio:
+            temp_audio.write(audio.read())
+            temp_audio_path = temp_audio.name
+
+        # עיבוד האודיו עם pyannote
+        diarization = pipeline(temp_audio_path)
+
+        # עיבוד התוצאה לזיהוי דוברים
         result = []
         for turn, _, speaker in diarization.itertracks(yield_label=True):
             result.append(f"{speaker}: {turn.start:.1f}s - {turn.end:.1f}s")
+
+        # מחיקת קובץ זמני לאחר שימוש
+        os.remove(temp_audio_path)
+
         return "\n".join(result)
+
     except Exception as e:
         return f"Error during diarization: {e}"
 
-# ממשק משתמש
+# יצירת ממשק Gradio
 interface = gr.Interface(
-    fn=diarize, 
-    inputs="audio", 
-    outputs="text", 
+    fn=diarize,
+    inputs="audio",
+    outputs="text",
     title="Speaker Diarization",
-    description="Upload an audio file to detect speakers and their timestamps."
+    description="Upload an audio file (WAV, MP3, etc.) to detect speakers and their timestamps."
 )
 
-interface.launch()
+# הפעלת הממשק
+if __name__ == "__main__":
+    interface.launch()