meet fastGPT knowledge base requirement

fastgpt_uploader.py

@@ -24,13 +24,13 @@ def __new_set():
     ).json()
     return result["data"]
 
-colId = __new_set()
+__CONFIG__['colId'] = __new_set()
 
 def upload2fastgpt(data):
     try:
         headers = {"Authorization": f"Bearer {key}", "Content-Type": "application/json"}
         payload = {
-            "collectionId": colId,
+            "collectionId": __CONFIG__['colId'],
             "trainingMode": "chunk",
             "data":  data
         }

main.py

@@ -1,7 +1,6 @@
-import config
-import json
 from fastapi import FastAPI
 
+from config import __CONFIG__
 # import mysql_connector
 from fastgpt_uploader import upload2fastgpt
 from semanticscholar import search_paper
@@ -10,9 +9,9 @@ app = FastAPI()
 
 def query(query:str):
     res = []
-    list = search_paper(json.loads(query))
+    list = search_paper(query)
     for i in list:
-        res.append({'q':i['title'], 'a':i['abstract']})
+        res.append({'id':'','datasetId':__CONFIG__['setId'], 'collectionId':__CONFIG__['colId'], 'sourceName':'Semantic Scholar','sourceId?':'', 'q':i['title'], 'a':i['abstract']})
         print(i['title'])
     return res
 
@@ -24,5 +23,5 @@ async def get_reference(questions):
 
 if __name__ == '__main__':
     import uvicorn
-    uvicorn.run(app, host="127.0.0.1", port=2501)
+    uvicorn.run(app, host="127.0.0.1", port=8964)
     # mysql_connector.end_mysql()