Update app.py

app.py

@@ -20,50 +20,37 @@ ner_model = AutoModelForTokenClassification.from_pretrained("dslim/bert-base-NER
 ner_pipeline = pipeline("ner", model=ner_model, tokenizer=ner_tokenizer)  # Renamed variable
 
 
-def convert_audio(input_path, output_path):
-    try:
-        ffmpeg.input(input_path).output(output_path, acodec='pcm_s16le').run()
-        return True
-    except ffmpeg.Error as e:
-        print(f"FFmpeg error: {e.stderr.decode()}")
-        return False
-        
 @app.route('/transcribe', methods=['POST'])
 def transcribe_audio():
+    # Check if a file was uploaded
     if 'file' not in request.files:
         return jsonify({'error': 'No file uploaded'}), 400
-        
+
     file = request.files['file']
-    
+
+    # Check if the file is empty
     if file.filename == '':
         return jsonify({'error': 'No selected file'}), 400
-        
-    if not allowed_file(file.filename):
-        return jsonify({'error': 'Unsupported file type'}), 400
 
     try:
-        temp_path = "temp_audio"
-        file.save(temp_path)
-        
-        # Convert audio to a format Whisper can process
-        converted_path = "converted_audio.wav"
-        if not convert_audio(temp_path, converted_path):
-            return jsonify({'error': 'Audio conversion failed'}), 500
-        
-        # Transcribe the converted audio
-        result = whisper_model.transcribe(converted_path)
+        # Save the uploaded file to a temporary file
+        with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as temp_audio:
+            file.save(temp_audio)
+            temp_path = temp_audio.name
+
+        # Transcribe the audio using Whisper
+        result = whisper_model.transcribe(temp_path)
         transcription = result["text"]
-        
-        # Clean up temporary files
-        if os.path.exists(temp_path):
-            os.remove(temp_path)
-        if os.path.exists(converted_path):
-            os.remove(converted_path)
-            
+
+        # Clean up the temporary file
+        os.remove(temp_path)
+
         return jsonify({'transcription': transcription})
-    
+
     except Exception as e:
         return jsonify({'error': str(e)}), 500
+
+        
         
 @app.route('/classify', methods=['POST'])
 def classify():