from fastapi import FastAPI

from config import __CONFIG__
import mysql_connector
from fastgpt_uploader import upload2fastgpt
from semanticscholar import search_paper

app = FastAPI()

def query(query:str):
    res = []
    list = search_paper(query)
    for i in list:
        res.append({
            'id':i['paperId'],
            'datasetId':__CONFIG__['fastgpt_setId'],
            'collectionId':__CONFIG__['fastgpt_colId'], 
            'sourceName':'Semantic Scholar',
            'sourceId?':'',
             'q':str(i['title']), 
             'a':str(i['abstract']),
             'score':[
                 {
                     'type': 'rrf',
                     'value':0.8
                 }
             ]
             })
    return res

@app.get("/fastdoi")
async def get_reference(questions):
    res = query(questions)
    new = []
    print(res)
    for i in res:
        if not mysql_connector.is_loaded(i['id']):
            new.append(i)
    if(upload2fastgpt(new)):
        for i in new:
            mysql_connector.new_load(i['id'])
            print('new: '+i['q'])
    return new

if __name__ == '__main__':
    import uvicorn
    uvicorn.run(app, host="127.0.0.1", port=8964)
    mysql_connector.end_mysql()