File size: 1,511 Bytes
db1e5a4 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 |
import os
from uuid import uuid4
import edge_tts
from groq import Groq
from dotenv import load_dotenv
load_dotenv()
client = Groq()
# ==================================================
# 🎧 SPEECH TO TEXT
# ==================================================
async def STT(audio_file):
os.makedirs("uploads", exist_ok=True)
file_path = f"uploads/{uuid4().hex}.wav"
with open(file_path, "wb") as f:
f.write(await audio_file.read())
with open(file_path, "rb") as f:
transcription = client.audio.transcriptions.create(
file=f,
model="whisper-large-v3-turbo",
response_format="verbose_json",
temperature=0.0
)
# Optional: cleanup the uploaded file after processing
# os.remove(file_path)
return {
"text": transcription.text,
"segments": transcription.segments,
"language": transcription.language
}
# ==================================================
# 🗣️ TEXT TO SPEECH
# ==================================================
async def TTS(text: str, voice: str = "en-US-AriaNeural") -> str:
"""
Converts text to speech and saves it to a file.
Returns the path to the generated audio file.
"""
os.makedirs("outputs", exist_ok=True)
filename = f"outputs/{uuid4().hex}.mp3"
communicate = edge_tts.Communicate(text, voice)
await communicate.save(filename)
return filename |