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import os
import time
from fastapi import APIRouter, Depends, HTTPException, status
from libs.convert_to_audio import convert_to_audio
from libs.header_api_auth import get_api_key
from libs.transformer.open_ai_whisper import open_ai_whisper_api
from libs.transformer.get_transcript_gradio_api import api_gradio_transcribe
router = APIRouter(prefix="/get-transcript-gradio", tags=["transcript"])
@router.get("/")
def get_transcript(audio_path: str, model_size: str = "distil-whisper/distil-small.en", api_key: str = Depends(get_api_key)):
st = time.time()
output_audio_folder = f"./cached/audio"
# if not os.path.exists(output_audio_folder):
# os.makedirs(output_audio_folder)
# output_file = f"{output_audio_folder}/{audio_path.split('/')[-1].split(".")[0]}.mp3"
# convert_to_audio(audio_path.strip(), output_file)
try:
# text, chunks = open_ai_whisper_api(audio_path)
text = api_gradio_transcribe(audio_path)
except Exception as error:
raise HTTPException(status_code=status.HTTP_403_FORBIDDEN, detail=f"error>>>: {error}")
# finally:
# if os.path.exists(output_file):
# os.remove(output_file)
listSentences = []
# for chunk in chunks:
# listSentences.append({
# "start_time": chunk.get("timestamp")[0],
# "end_time": chunk.get("timestamp")[1],
# "text": chunk.get("text")
# })
et = time.time()
elapsed_time = et - st
return {"text": text,
'list_sentence': listSentences,
'elapsed_time': round(elapsed_time, 2)
}
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