Update app.py

app.py

@@ -1,22 +1,26 @@
 import gradio as gr
 import whisper
 
-# Load the Whisper model (you can change to "base", "small", "medium", etc.)
-model = whisper.load_model("base")
-
-# Function to process the audio file and transcribe
-def transcribe_audio(audio):
-    # Transcribe the audio using Whisper
+# Function to process the audio file
+def transcribe_audio(model_size, audio):
+    # Load the Whisper model based on the user's choice
+    model = whisper.load_model(model_size)
+    
+    # Transcribe the audio file
     result = model.transcribe(audio)
+    
     return result['text']
 
-# Create a Gradio interface for audio transcription
+# Gradio interface with model selection
 iface = gr.Interface(
-    fn=transcribe_audio,                # The function that will process the audio
-    inputs=gr.Audio(source="upload", type="filepath"),  # Upload audio input
-    outputs="text",                     # Output transcription as text
-    title="Whisper Audio Transcription",  # Title of the interface
-    description="Upload an audio file and get the transcription using OpenAI's Whisper model." # Description
+    fn=transcribe_audio,                           # The function that will process the audio and model choice
+    inputs=[
+        gr.Dropdown(label="Choose Whisper Model", choices=["tiny", "base", "small", "medium", "large"], value="base"),  # Model selection
+        gr.Audio(source="upload", type="filepath")  # Audio upload input
+    ],
+    outputs="text",                                # Output transcription as text
+    title="Whisper Audio Transcription",
+    description="Upload an audio file and select a Whisper model to get the transcription."
 )
 
 # Launch the interface