app.py

import os
import io
import streamlit as st
from groq import Groq
import soundfile as sf
#from st_audiorec import st_audiorec
from audiorecorder import audiorecorder

# Load environment variables
api_key = os.getenv('groqwhisper')
if api_key is None:
    st.error("The 'groq_whisper' environment variable is not set. Please set it and restart the app.")
    st.stop()

# Initialize Groq client
client = Groq(api_key=api_key)

def process_audio(audio_data):
    """Process audio data and return transcription."""
    try:
        sample_rate, samples = audio_data
        
        # Create in-memory WAV file
        with io.BytesIO() as wav_buffer:
            sf.write(wav_buffer, samples, sample_rate, format='WAV')
            wav_buffer.seek(0)
            
            # Send to Groq for transcription
            transcription = client.audio.transcriptions.create(
                file=("recording.wav", wav_buffer.read(), "audio/wav"),
                model="whisper-large-v3-turbo",
                prompt="transcribe",
                language="de",
                response_format="json",
                temperature=0.0
            )
        return transcription.text
    except Exception as e:
        return f"An error occurred: {str(e)}"

# Streamlit UI
st.title("🎤 Live Audio Transcription")
st.write("Record audio using your microphone and get real-time transcription")

# Audio recorder component
#audio_bytes = st.audio()
audio_bytes = st.audio_input("Click to record")

if audio_bytes:
    # Extrahiere die Bytes aus dem UploadedFile-Objekt
    audio_bytes_content = audio_bytes.getvalue()
    
    # Konvertiere die Bytes in ein numpy-Array mit soundfile
    with io.BytesIO(audio_bytes_content) as wav_io:
        samples, sample_rate = sf.read(wav_io)
        
        # Konvertiere Stereo in Mono, falls erforderlich
        if len(samples.shape) > 1 and samples.shape[1] == 2:
            samples = samples.mean(axis=1)
        
        # Verarbeite das Audio
        with st.spinner("Transcribing..."):
            transcription = process_audio((sample_rate, samples))
        
        # Ergebnisse anzeigen
        st.success(transcription)
        #st.subheader("Result:")
        #st.write(transcription)
        #st.audio(audio_bytes_content, format='audio/wav')