Create app.py

app.py

@@ -0,0 +1,34 @@
+import transformers
+import librosa
+import gradio as gr
+import spaces
+
+pipe = transformers.pipeline(
+    model='sarvamai/shuka_v1',
+    trust_remote_code=True,
+    device=0,
+    torch_dtype='bfloat16'
+)
+
+@spaces.GPU(duration=120)
+def transcribe_and_respond(audio_file):
+    audio, sr = librosa.load(audio_file, sr=16000)
+    
+    turns = [
+        {'role': 'system', 'content': 'Respond naturally and informatively.'},
+        {'role': 'user', 'content': ''}
+    ]
+    
+    response = pipe({'audio': audio, 'turns': turns, 'sampling_rate': sr}, max_new_tokens=512)
+    
+    return response
+
+iface = gr.Interface(
+    fn=transcribe_and_respond,
+    inputs=gr.Audio(source="microphone", type="filepath"),  # Use the microphone for audio input
+    outputs="text",  # The output will be a text response
+    title="Voice Input for Transcription and Response",
+    description="Record your voice, and the model will respond naturally and informatively."
+)
+
+iface.launch()