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from fastapi import FastAPI
from fastapi.responses import HTMLResponse
from fastapi.templating import Jinja2Templates
from fastapi import FastAPI, Query, Request
from pydantic import BaseModel
from transformers import pipeline
from typing import Union
import pickle
import joblib
# Load the pickled XGBoost model
xgb_model = joblib.load("xgb_model.joblib")
app = FastAPI()
templates = Jinja2Templates(directory="templates")
@app.get("/display")
def display_params(
request: Request,
prg: float = Query(..., description="Plasma glucose"),
pl: float = Query(..., description="Blood Work Result-1 (mu U/ml)"),
pr: float = Query(..., description="Blood Pressure (mm Hg)"),
sk: float = Query(..., description="Blood Work Result-2 (mm)"),
ts: float = Query(..., description="Blood Work Result-3 (mu U/ml)"),
m11: float = Query(..., description="Body mass index (weight in kg/(height in m)^2"),
bd2: float = Query(..., description="Blood Work Result-4 (mu U/ml)"),
age: int = Query(..., description="Patient's age (years)")
):
#prepare input features for prediction
input_features = [prg,pl,pr,sk,ts,m11,bd2,age]
#Make predictions using the loaded model
prediction = xgb_model.predict([input_features])[0]
return templates.TemplateResponse(
"display_params.html",
{
"request": request,
"prg": prg,
"pl": pl,
"pr": pr,
"sk": sk,
"ts": ts,
"m11": m11,
"bd2": bd2,
"age": age
"prediction": prediction # Include the prediction in the response
}
)
# class Item(BaseModel):
# name: str
# price: float
# is_offer: Union[bool, None] = None
# @app.get("/")
# def read_root():
# return {"Hello": "World"}
# @app.get("/items/{item_id}")
# def read_item(item_id: int, q: Union[str, None] = None):
# return {"item_id": item_id, "q": q}
# @app.put("/items/{item_id}")
# def update_item(item_id: int, item: Item):
# return {"item_name": item.name, "item_id": item_id}
# @app.get("/display")
# def display_params(request: Request, item_id: int, q: Union[str, None] = None):
# return templates.TemplateResponse("display_params.html", {"request": request, "item_id": item_id, "q": q}) |