Spaces:
Sleeping
Sleeping
File size: 1,102 Bytes
91f89e5 1dd8a9e 3352b5e 1dd8a9e 56ff037 1dd8a9e 56ff037 1dd8a9e 56ff037 1dd8a9e 56ff037 1dd8a9e 56ff037 dd04f41 91f89e5 b83a24a 56ff037 0c29434 91f89e5 b83a24a 1dd8a9e 56ff037 91f89e5 56ff037 91f89e5 56ff037 91f89e5 56ff037 91f89e5 56ff037 91f89e5 e7047b6 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 |
from fastapi import FastAPI, Query
from pydantic import BaseModel
from typing import Any
import pandas as pd
from mojica_agent import MojicaAgent
from config import Config
app = FastAPI()
mojica_bot = MojicaAgent(Config)
# * Esquema de entrada como marshmellow
class QuestionRequest(BaseModel):
question: str
class AnswerResponse(BaseModel):
sql: str
result: Any
@app.post("/")
def ask_question(req: QuestionRequest):
sql, result = mojica_bot.consult(req.question)
# Si es dataframe lo convertimos a json
if isinstance(result, pd.DataFrame):
result = result.to_json(orient="records")
return {"sql": sql, "result": result}
# return {"sql": "WASA"}
# @app.post("/", response_model=AnswerResponse)
# def ask_question(req: QuestionRequest):
# sql, result = mojica_bot.consult(req.question)
# # * Si es dataframe lo convertimos a json
# if isinstance(result, pd.DataFrame):
# result = result.to_dict(orient="records")
# return {"sql": sql, "result": result}
# @app.get("/")
# def greet_json():
# return {"Hello": "World!"}
|