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import streamlit as st
import requests
import os
API_URL = "https://api-inference.huggingface.co/models/openai/whisper-large-v3-turbo"
headers = {"Authorization": f"Bearer {st.secrets['HF_API_KEY']}"}
def query(file):
data = file.read()
response = requests.post(API_URL, headers=headers, data=data)
return response.json()
st.title("Speech Recognition with Whisper")
uploaded_file = st.file_uploader("Choose an audio file", type=['wav', 'mp3', 'flac'])
if uploaded_file is not None:
st.audio(uploaded_file, format='audio/wav')
if st.button('Transcribe'):
with st.spinner('Transcribing...'):
result = query(uploaded_file)
if 'text' in result:
st.success("Transcription completed!")
st.write("Transcribed text:")
st.write(result['text'])
else:
st.error("An error occurred during transcription.")
st.write("Error details:")
st.write(result)
st.markdown("---")
st.write("Note: This app uses the Whisper API from Hugging Face.") |