app.py

import gradio as gr
from transformers import pipeline

# Whisper pipeline (supports Hindi, Punjabi, etc.)
asr_pipeline = pipeline(
    task="automatic-speech-recognition",
    model="openai/whisper-small",
)

# Function to transcribe and detect language
def transcribe(audio_np, sample_rate):
    result = asr_pipeline({
        "array": audio_np,
        "sampling_rate": sample_rate
    })
    text = result["text"]
    lang = result.get("language", "unknown")
    return f"Detected Language: {lang}\n\nTranscription:\n{text}"

# Gradio Interface
interface = gr.Interface(
    fn=transcribe,
    inputs=gr.Audio(type="numpy", label="Upload or Record Audio"),  # FIXED
    outputs=gr.Textbox(label="Detected Language & Transcription"),
    title="Auto Language Detection - Whisper",
    description="Upload or record Hindi or Punjabi audio. Whisper will auto-detect language and transcribe."
)

interface.launch()