Update app.py

app.py

@@ -1,5 +1,37 @@
 import gradio as gr
-import os
-gr.load("models/vasista22/whisper-tamil-medium", examples = [
-    [os.path.join(os.path.abspath(''),"./sample1.wav")]    
-]).launch()
+import torch
+import soundfile as sf
+from transformers import pipeline
+
+device = "cuda:0" if torch.cuda.is_available() else "cpu"
+pipe = pipeline(
+    "automatic-speech-recognition",
+    model="models/vasista22/whisper-tamil-medium",
+    chunk_length_s=30,
+    device=device,
+)
+
+def transcribe(audio):
+    """Transcribes Tamil speech from an audio file."""
+    if audio is None:
+        return "Please record or upload an audio file."
+
+    audio_data, sample_rate = sf.read(audio)
+    transcription = pipe(
+        {"array": audio_data, "sampling_rate": sample_rate},
+        chunk_length_s=30,
+        batch_size=8,
+        return_timestamps=True,
+    )["text"]
+
+    return transcription
+
+iface = gr.Interface(
+    fn=transcribe,
+    inputs=gr.Audio(sources=["microphone", "upload"], type="filepath"),
+    outputs="text",
+    title="Tamil Speech Recognition",
+    description="Record or upload Tamil speech and get the transcribed text.",
+)
+
+iface.launch()