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Verified signatureimport gradio as gr import os import numpy as np import librosa import asyncio import edge_tts import soundfile as sf from groq import Groq from fastrtc import WebRTC, ReplyOnPause, get_hf_turn_credentials # Initialize Groq client = Groq(api_key=os.environ.get("GROQ_API_KEY")) async def text_to_speech_logic(text): communicate = edge_tts.Communicate(text, "en-US-AndrewNeural") await communicate.save("temp_op.mp3") audio, sr = librosa.load("temp_op.mp3", sr=16000) # FastRTC expects (channels, samples) if len(audio.shape) == 1: audio = audio.reshape(1, -1) return sr, audio def process_audio(audio: tuple[int, np.ndarray]): sr, y = audio sf.write("input.wav", y.T, sr) # Transpose for standard wav format with open("input.wav", "rb") as file: transcription = client.audio.transcriptions.create( file=("input.wav", file.read()), model="whisper-large-v3-turbo", ) response = client.chat.completions…1a68b9a -
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