| |
|
|
| from fastapi import FastAPI |
| from fastapi.responses import RedirectResponse |
| from pydantic import BaseModel |
| import joblib |
| import pandas as pd |
|
|
| app = FastAPI() |
| model = joblib.load("./pipeline.joblib") |
|
|
| class Input(BaseModel): |
| CUST_NBR: str |
| MENU_TYP_DESC: str |
| PYR_SEG_CD: str |
| DIV_NBR: str |
| WKLY_ORDERS: float |
| PERC_EB: float |
| AVG_WKLY_SALES: float |
| AVG_WKLY_CASES: float |
|
|
| class Output(BaseModel): |
| prediction: list[int] |
|
|
| @app.post("/predict", response_model=Output) |
| def predict(data: list[Input]) -> Output: |
| print(data) |
| data = [item.model_dump() for item in data] |
| data = pd.DataFrame(data) |
| prediction = model.predict(data).tolist() |
| return {"prediction":prediction} |
|
|
| @app.get("/") |
| def home(): |
| return RedirectResponse(url="/docs", status_code=302) |
