Delete app.py

app.py

@@ -1,44 +0,0 @@
-from fastapi import FastAPI
-from pydantic import BaseModel
-import joblib
-import numpy as np
-from sklearn.datasets import load_iris
-
-# Load the trained model
-model = joblib.load("iris_model.pkl")
-
-app = FastAPI()
-
-
-class IrisInput(BaseModel):
-    sepal_length: float
-    sepal_width: float
-    petal_length: float
-    petal_width: float
-
-
-class IrisPrediction(BaseModel):
-    predicted_class: int
-    predicted_class_name: str
-
-
-@app.post("/predict", response_model=IrisPrediction)
-def predict(data: IrisInput):
-    # Convert the input data to a numpy array
-    input_data = np.array(
-        [[data.sepal_length, data.sepal_width, data.petal_length, data.petal_width]]
-    )
-
-    # Make a prediction
-    predicted_class = model.predict(input_data)[0]
-    predicted_class_name = load_iris().target_names[predicted_class]
-
-    return IrisPrediction(
-        predicted_class=predicted_class, predicted_class_name=predicted_class_name
-    )
-
-
-if __name__ == "__main__":
-    import uvicorn
-
-    uvicorn.run(app, host="127.0.0.1", port=8000)