Update app.py

app.py

@@ -12,21 +12,35 @@ available_models = {
     "mskov/distilbert-base-toxicity" : "Distillbert Finetuned Model"
 }
 
-# Create a Gradio interface with a radio button to select the model
-def classify_toxicity(text, selected_model):
-    # Load the selected model
-    module = evaluate.load("toxicity", selected_model)
-    results = module.compute(predictions=[text])
-    toxicity_score = results["toxicity"][0]
+
+# Create a Gradio interface with audio file and text inputs
+def classify_toxicity(audio_file, text_input, selected_model):
+    # Transcribe the audio file using Whisper ASR
+    whisper_module = evaluate.load("whisper")
+    transcription_results = whisper_module.compute(uploaded=audio_file)
+
+    # Extract the transcribed text
+    transcribed_text = transcription_results["transcription"]
+
+    # Load the selected toxicity classification model
+    toxicity_module = evaluate.load("toxicity", selected_model)
+    toxicity_results = toxicity_module.compute(predictions=[transcribed_text])
+
+    toxicity_score = toxicity_results["toxicity"][0]
+
     return f"Toxicity Score ({available_models[selected_model]}): {toxicity_score:.4f}"
 
 iface = gr.Interface(
     fn=classify_toxicity,
-    inputs=["text", gr.Radio(available_models, type="value", label="Select Model")],
+    inputs=[
+        gr.Audio(source="upload", type="file", label="Upload Audio File (Optional)"),
+        "text",
+        gr.Radio(available_models, type="value", label="Select Model")
+    ],
     outputs="text",
     live=True,
-    title="Toxicity Classifier",
-    description="Select a model and enter text to classify its toxicity.",
+    title="Toxicity Classifier with ASR",
+    description="Upload an audio file or enter text to classify its toxicity using the selected model.",
 )
 
 launch_gradio_widget(iface)