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import os
import streamlit as st
from pydub import AudioSegment
from groq import Groq
# Set ffmpeg path
ffmpeg_path = r"ffmpeg.exe"
os.environ["PATH"] += os.pathsep + os.path.dirname(ffmpeg_path)
AudioSegment.converter = ffmpeg_path
# Groq API configuration
groq_api_key = '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' # Replace with your actual API key
client = Groq(api_key=groq_api_key)
model = 'whisper-large-v3'
# Function to ensure the file is in a suitable format
def ensure_suitable_format(file_path):
allowed_formats = ["flac", "mp3", "mp4", "mpeg", "mpga", "m4a", "ogg", "opus", "wav", "webm"]
file_extension = file_path.split('.')[-1].lower()
if file_extension not in allowed_formats:
new_file_path = f"{os.path.splitext(file_path)[0]}.wav"
os.rename(file_path, new_file_path)
return new_file_path
return file_path
# Function to convert audio to WAV
def convert_audio_to_wav(input_path, output_path):
audio = AudioSegment.from_file(input_path)
audio.export(output_path, format="wav")
return output_path
# Function to transcribe audio using Groq
def audio_to_text(filepath):
with open(filepath, "rb") as file:
translation = client.audio.translations.create(
file=(filepath, file.read()),
model=model,
)
return translation.text
# Streamlit App UI
st.title("Audio-to-Text Transcription")
st.write("Upload an audio file to get the transcribed text.")
# File upload
uploaded_file = st.file_uploader("Upload your audio file", type=["flac", "mp3", "mp4", "mpeg", "mpga", "m4a", "ogg", "opus", "wav", "webm"])
if uploaded_file:
# Save the uploaded file locally
file_path = os.path.join("uploaded_audio", uploaded_file.name)
os.makedirs("uploaded_audio", exist_ok=True)
with open(file_path, "wb") as f:
f.write(uploaded_file.getbuffer())
st.write(f"File uploaded: {uploaded_file.name}")
# Ensure file format is suitable
suitable_audio_path = ensure_suitable_format(file_path)
# Convert audio to WAV
wav_path = f"{os.path.splitext(suitable_audio_path)[0]}.wav"
converted_audio = convert_audio_to_wav(suitable_audio_path, wav_path)
# Transcribe audio
st.write("Processing transcription...")
try:
transcription = audio_to_text(converted_audio)
st.success("Transcription complete!")
st.text_area("Transcribed Text", transcription, height=200)
except Exception as e:
st.error(f"Error during transcription: {e}")
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