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