import config.config as config from app.src.src import pipeline_sentiment from fastapi import FastAPI from pydantic import BaseModel from transformers import pipeline import uvicorn sentiment_model = pipeline(model=config.sentiment_model) app = FastAPI() class YouTubeUrl(BaseModel): url_video: str @app.get('/') def read_root(): return {'message': 'FastAPI+HuggingFace app sentiment + summarize YouTube comments'} @app.post('/comments') def get_comments(url_video: YouTubeUrl): data = pipeline_sentiment(url_video.url_video, config.API_KEY, sentiment_model) data.to_csv(f"{config.DATA_FILE}", index=False) return {'message': 'Success'} if __name__ == '__main__': uvicorn.run(app, host='127.0.0.1', port=80)