launch

app.py

@@ -12,7 +12,10 @@ translation_model = MBartForConditionalGeneration.from_pretrained("facebook/mbar
 translation_tokenizer = MBart50Tokenizer.from_pretrained("facebook/mbart-large-50-many-to-many-mmt", src_lang="ar_AR")
 
 def transcribe_audio(audio):
-    # Load the audio file from Gradio interface
+    if not audio:
+        return "No audio file provided", "No translation available"
+
+    # Load the audio file
     audio_array, sr = librosa.load(audio, sr=16000)
     
     # Tokenize the audio file
@@ -44,16 +47,16 @@ def translate_text(text):
     
     return translated_text
 
-# Create a Gradio interface for uploading audio or recording from the browser
-demo = gr.Interface(fn=transcribe_audio, 
-                    inputs=gr.Audio(type="filepath"),  # Corrected input component
-                    outputs=["text", "text"],  # Both transcription and translation outputs
-                    live=False,  # Disable live to prevent automatic execution
-                    title="Speech-to-Text and Translation", 
-                    description="Upload an audio file to transcribe and translate it from Darija to English.")
-
-# Add a submit button
-demo.add_button("Submit")
+# Create Gradio Blocks for better UI
+with gr.Blocks() as demo:
+    gr.Markdown("# Speech-to-Text and Translation")
+    gr.Markdown("Upload an audio file to transcribe and translate it from Darija to English.")
+    
+    audio_input = gr.Audio(type="filepath", label="Upload or Record Audio")
+    submit_button = gr.Button("Submit")
+    transcription_output = gr.Textbox(label="Transcription (Darija)")
+    translation_output = gr.Textbox(label="Translation (English)")
+    
+    submit_button.click(fn=transcribe_audio, inputs=audio_input, outputs=[transcription_output, translation_output])
 
 demo.launch()
-demo.launch(api=True, share=True)