from fastapi import FastAPI, File, Form, UploadFile
import shutil
import os
from huggingface_hub import HfApi,HfFileSystem
app = FastAPI()

if not os.path.exists('./tarun_1234'):
    os.mkdir('./tarun_1234')

hf_token = os.environ['HF_TOKEN']

api = HfApi(token = hf_token)

@app.post("/save_audio")
async def save_audio(audio: UploadFile = File(...), path: str = Form(...), script_name: str = Form(...)):

    # print('PATH ************************ >>>>>', path)
    folder_path = path.split('/')[1]
    filename = path.split('/')[-1]
    # script_name = script_name

    count = path.split('/')[-1].split('.')[0]

    # print('FOLDER PATH ----------->>>>>>>>>>>>>>', folder_path)
    
    if not os.path.exists(folder_path):
        os.mkdir(folder_path)
    
    print("Received Audio !!!!!")

    # Save the audio to the specified path
    with open(path, "wb") as buffer:
        shutil.copyfileobj(audio.file, buffer)

    # url = 'https://hellojarvis-asr-hindi.hf.space/transcribe'
    # headers = {
    #     'Authorization': f'Bearer {hf_token}',
    #     'accept': 'application/json'
    # }
    
    # with open(path, 'rb') as file:
    #     files = {'file': file}
    #     print('***********  Reached Here  *******************')
    #     response = requests.post(SERVER_URL, headers=headers, files=files)

    # if response.status_code == 200:
    #     transcription = response.json()
    #     # return transcription
    # else:
    #     # return "Failed to transcribe audio", None

    # if os.path.exists(f'{folder_path}.csv'):
    #     df = pd.read_csv(f'{folder_path}.csv')
    # else:
    #     df = pd.DataFrame(columns = ['script','response','transcription'])

    # df1 = pd.DataFrame(l,columns = ['script','response','transcription'])
        

    api.upload_file(
    path_or_fileobj=path,
    path_in_repo=f"{folder_path}/{script_name}/{filename}",
    repo_id="hellojarvis/agent_data",
    repo_type="dataset",)

    # api.upload_file(
    # path_or_fileobj=f'{folder_path}/transcription/state_wise_duplicates.csv',
    # path_in_repo=f"{folder_path}.csv",
    # repo_id="hellojarvis/agent_test",
    # repo_type="dataset",)

    return {"message": "Audio saved successfully"}

if __name__ == '__main__':
    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=7860)