Update app.py

app.py

@@ -62,6 +62,36 @@
 
 # if __name__ == "__main__":
 #     demo.launch()
+# import gradio as gr
+# from faster_whisper import WhisperModel
+
+# # Try to load the model on startup
+# try:
+#     model = WhisperModel("medium", device="cpu", compute_type="int8")
+# except Exception as e:
+#     # You could log the error or handle it more gracefully if needed
+#     model = None
+#     model_error = f"Failed to load model: {e}"
+
+# def transcribe(audio_file):
+#     if model is None:
+#         return model_error
+#     try:
+#         segments, info = model.transcribe(audio_file.name, beam_size=5)
+#         text = " ".join([seg.text for seg in segments])
+#         return text
+#     except Exception as e:
+#         return f"Transcription failed: {e}"
+
+# iface = gr.Interface(
+#     fn=transcribe,
+#     inputs=gr.Audio(sources=["upload"], type="filepath", label="Audio file"),
+#     outputs="text",
+#     title="Faster Whisper Transcription API",
+#     description="Upload audio and get transcription text."
+# )
+
+# iface.launch(server_name="0.0.0.0", server_port=7860)
 import gradio as gr
 from faster_whisper import WhisperModel
 
@@ -69,7 +99,6 @@ from faster_whisper import WhisperModel
 try:
     model = WhisperModel("medium", device="cpu", compute_type="int8")
 except Exception as e:
-    # You could log the error or handle it more gracefully if needed
     model = None
     model_error = f"Failed to load model: {e}"
 
@@ -77,7 +106,7 @@ def transcribe(audio_file):
     if model is None:
         return model_error
     try:
-        segments, info = model.transcribe(audio_file.name, beam_size=5)
+        segments, info = model.transcribe(audio_file, beam_size=5)
         text = " ".join([seg.text for seg in segments])
         return text
     except Exception as e:
@@ -91,4 +120,5 @@ iface = gr.Interface(
     description="Upload audio and get transcription text."
 )
 
-iface.launch(server_name="0.0.0.0", server_port=7860)
+iface.launch(server_name="0.0.0.0", server_port=7880)
+