Update app.py

app.py

@@ -1,7 +1,6 @@
 import os
 from transformers import pipeline
 import gradio as gr
-import numpy as np
 
 # Fetch the token from the environment
 hf_token = os.getenv("HUGGINGFACE_HUB_TOKEN")
@@ -9,10 +8,11 @@ model_id = "akadriu/whisper-medium-sq"  # update with your model id
 pipe = pipeline("automatic-speech-recognition", model=model_id, token=hf_token)
 
 def transcribe_speech(filepath):
-    # Load the audio file into a numpy array
+    # Check if the filepath is valid
     if filepath is None:
         raise ValueError("No audio file provided.")
     
+    # Perform speech transcription
     output = pipe(
         filepath,
         max_new_tokens=256,
@@ -25,16 +25,16 @@ def transcribe_speech(filepath):
     )
     return output["text"]
 
-# Create Gradio interface
+# Create Gradio interfaces without the 'source' argument
 mic_transcribe = gr.Interface(
     fn=transcribe_speech,
-    inputs=gr.Audio(source="microphone", type="filepath"),  # Removed plural from "sources"
+    inputs=gr.Audio(type="filepath"),
     outputs="text",
 )
 
 file_transcribe = gr.Interface(
     fn=transcribe_speech,
-    inputs=gr.Audio(source="upload", type="filepath"),  # Removed plural from "sources"
+    inputs=gr.Audio(type="filepath"),
     outputs="text",
 )
 
@@ -48,3 +48,4 @@ with demo:
 
 demo.launch(debug=True)
 
+