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query param to request body #110

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query param to request body #110

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421591e
query param to request body
debajyoti-truefoundry Aug 8, 2025
d5b0121
Update server.py
debajyoti-truefoundry Aug 8, 2025
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1 change: 1 addition & 0 deletions deploy-model-with-fastapi/requirements.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -5,3 +5,4 @@ pandas==2.2.3
scikit-learn==1.6.1
uvicorn-worker==0.3.0
uvicorn[standard]==0.34.3
pydantic
16 changes: 11 additions & 5 deletions deploy-model-with-fastapi/server.py
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Expand Up @@ -5,6 +5,7 @@
import joblib
import pandas as pd
from fastapi import FastAPI
from pydantic import BaseModel


def _get_model_dir():
Expand Down Expand Up @@ -34,18 +35,23 @@ async def lifespan(app: FastAPI):
async def health() -> Dict[str, bool]:
return {"healthy": True}

class RequestBody(BaseModel):
sepal_length: float
sepal_width: float
petal_length: float
petal_width: float

@app.post("/predict")
def predict(
sepal_length: float, sepal_width: float, petal_length: float, petal_width: float
request_body: RequestBody
):
global model
class_names = ["setosa", "versicolor", "virginica"]
data = dict(
sepal_length=sepal_length,
sepal_width=sepal_width,
petal_length=petal_length,
petal_width=petal_width,
sepal_length=request_body.sepal_length,
sepal_width=request_body.sepal_width,
petal_length=request_body.petal_length,
petal_width=request_body.petal_width,
)
prediction = model.predict_proba(pd.DataFrame([data]))[0]
predictions = []
Expand Down