Create app.py

app.py

@@ -0,0 +1,32 @@
+import gradio as gr
+from transformers import pipeline
+
+# Load the ASR pipeline
+pipe = pipeline(
+    "automatic-speech-recognition",
+    model="lyimo/whisper-small-sw-badili-v4"
+)
+
+def transcribe(audio):
+    if audio is None:
+        return ""
+    
+    # Process audio file path with pipeline
+    result = pipe(
+        audio,
+        generate_kwargs={"language": "swahili"}
+    )
+    return result["text"]
+
+# Create Gradio interface
+interface = gr.Interface(
+    fn=transcribe,
+    inputs=gr.Audio(sources=["microphone", "upload"], type="filepath"),
+    outputs=gr.Textbox(label="Transcription"),
+    title="Swahili Speech Recognition",
+    description="Record or upload Swahili audio to see the Whisper transcription",
+    allow_flagging="never"
+)
+
+# Launch the app
+interface.launch()