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import gradio as gr
import requests
from gtts import gTTS # Import gTTS for Text-to-Speech
import tempfile
# Function to convert text to speech and transcribe
def text_to_speech_transcribe(text):
# Convert text to speech
tts = gTTS(text, lang='en')
with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as tmp_audio:
audio_path = tmp_audio.name
tts.save(audio_path)
# Read audio file in binary mode
with open(audio_path, "rb") as audio_file:
audio_data = audio_file.read()
# Groq API endpoint for audio transcription
groq_api_endpoint = "https://api.groq.com/openai/v1/audio/transcriptions"
# Replace 'YOUR_GROQ_API_KEY' with your actual Groq API key
headers = {
"Authorization": "Bearer YOUR_GROQ_API_KEY", # Replace with your Groq API key
}
# Prepare the files and data for the request
files = {
'file': ('audio.wav', audio_data, 'audio/wav'),
}
data = {
'model': 'whisper-large-v3-turbo', # Specify the model to use
'response_format': 'json', # Desired response format
'language': 'en', # Language of the audio
}
# Send audio to Groq API
response = requests.post(groq_api_endpoint, headers=headers, files=files, data=data)
# Parse response
if response.status_code == 200:
result = response.json()
return result.get("text", "No transcription available.")
else:
return f"Error: {response.status_code}, {response.text}"
# Gradio interface
iface = gr.Interface(
fn=text_to_speech_transcribe,
inputs="text", # Input text to be converted to speech
outputs="text",
title="Text to Speech and Transcription",
description="Enter text to convert it to audio, then transcribe it with the Groq API."
)
iface.launch()
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