Update app.py

app.py

@@ -1,23 +1,42 @@
-import gradio as gr
+
 from transformers import pipeline
+import gradio as gr
 
-# Load the Whisper pipeline from Hugging Face
-pipe = pipeline("automatic-speech-recognition", model="openai/whisper-base", device=-1)  # use device=0 for GPU
+# Load Whisper model
+print("Loading model...")
+pipe = pipeline(model="jsbeaudry/whisper-medium-oswald")
+print("Model loaded successfully.")
 
 # Transcription function
 def transcribe(audio_path):
-    print("Transcribing:", audio_path)
+    if audio_path is None:
+        return "Please upload or record an audio file first."
     result = pipe(audio_path)
     return result["text"]
 
-# Gradio interface
-app = gr.Interface(
-    fn=transcribe,
-    inputs=gr.Audio(source="microphone", type="filepath"),
-    outputs="text",
-    title="Whisper Speech Recognition",
-    description="Record your voice and transcribe it using Whisper from Hugging Face."
-)
+# Build Gradio interface
+def create_interface():
+    with gr.Blocks(title="Whisper Medium - Haitian Creole") as demo:
+        gr.Markdown("# 🎙️ Whisper Medium Creole ASR")
+        gr.Markdown(
+            "Upload an audio file or record your voice in Haitian Creole. "
+            "Then click **Transcribe** to see the result."
+        )
+
+        with gr.Row():
+            with gr.Column():
+                audio_input = gr.Audio(source="upload", type="filepath", label="🎧 Upload Audio")
+                audio_input2 = gr.Audio(source="microphone", type="filepath", label="🎤 Record Audio")
+            with gr.Column():
+                transcribe_button = gr.Button("🔍 Transcribe")
+                output_text = gr.Textbox(label="📝 Transcribed Text", lines=4)
+                
+    
+        transcribe_button.click(fn=transcribe, inputs=audio_input, outputs=output_text)
+        transcribe_button.click(fn=transcribe, inputs=audio_input2, outputs=output_text)
+
+    return demo
 
-# Run the app
-app.launch()
+if __name__ == "__main__":
+    interface = create_interface()
+    interface.launch()