Update app.py

app.py

@@ -1,37 +1,16 @@
 import gradio as gr
-import requests
 
-# Updated API Endpoint
-API_URL = "https://api-inference.huggingface.co/models/openai/whisper-large-v2"
-HEADERS = {"Authorization": "Bearer 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"}
+# Load the model without launching the interface
+loaded_model = gr.Interface.load("models/openai/whisper-large-v2", allow_launch=False)
 
-def transcribe_audio(audio_path: str) -> str:
-    # Read audio file
-    with open(audio_path, "rb") as f:
-        audio_data = f.read()
-    
-    # Make API request to OpenAI Whisper v2 API
-    try:
-        response = requests.post(API_URL, headers=HEADERS, data=audio_data)
-        response.raise_for_status()  # Raises an HTTPError if the HTTP request returned an unsuccessful status code
-    except requests.RequestException as error:
-        print(f"API request failed: {error}")
-        return "Failed to transcribe. Please try again."
-    
-    result = response.json()
-    
-    # Print the full JSON response for troubleshooting
-    print(result)
-    
-    # Extract the transcribed text from the response
-    # TODO: Replace 'your-key-here' with the actual key used by the API's response
-    transcribed_text = result.get("your-key-here", "Failed to retrieve transcription.")
-    
-    return transcribed_text
+def transcribe_audio(audio_file):
+    # Use the loaded model to transcribe the audio
+    return loaded_model(audio_file)
 
 audio_input = gr.inputs.Audio(type="filepath")
 text_output = gr.outputs.Textbox()
 
+# Setup the custom Gradio interface with your configurations
 iface = gr.Interface(
     fn=transcribe_audio,
     inputs=audio_input,