Create app.py

app.py

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+
+# Import necessary modules
+import gradio as gr
+from transformers import pipeline
+
+# Load the fine-tuned model from Hugging Face
+pipe = pipeline("automatic-speech-recognition", model="Futuresony/whisper-small-sw")
+
+# Function to transcribe audio
+def transcribe(audio):
+    if audio is None:
+        return "Please upload or record an audio file."
+    print("Transcribing audio...")
+    result = pipe(audio)["text"]
+    return result
+
+# Gradio App
+with gr.Blocks() as demo:
+    gr.Markdown("# 🎙️ Swahili Speech-to-Text Transcription App")
+    
+    with gr.Row():
+        audio_input = gr.Audio(source="microphone", type="filepath", label="🎤 Record Audio")
+        file_input = gr.Audio(source="upload", type="filepath", label="📂 Upload Audio File")
+
+    transcribe_button = gr.Button("Transcribe")
+    output_text = gr.Textbox(label="📝 Transcription Output")
+
+    transcribe_button.click(transcribe, inputs=[audio_input], outputs=output_text)
+    transcribe_button.click(transcribe, inputs=[file_input], outputs=output_text)
+
+# Launch the app
+demo.launch()