api change

Dockerfile

@@ -0,0 +1,13 @@
+FROM python:3.12-slim
+
+WORKDIR /code
+
+COPY ./requirements.txt /code/requirements.txt
+
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+COPY . /code/
+
+EXPOSE 7860
+
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]

README.md

@@ -1,11 +1,9 @@
 ---
-title: Iris Detector Api
-emoji: 📊
-colorFrom: gray
-colorTo: red
+title: Iris Detector API
+emoji: 🌸
+colorFrom: blue
+colorTo: green
 sdk: docker
 pinned: false
 license: mit
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+from fastapi import FastAPI
+from pydantic import BaseModel
+import numpy as np
+import joblib
+
+app = FastAPI(
+    title="Iris KNN Prediction API",
+    description="API for predicting Iris species using KNN model",
+    version="1.0.0"
+)
+
+try:
+    model, target_names = joblib.load("iris_knn.pkl")
+except:
+    model = None
+    target_names = []
+
+class IrisData(BaseModel):
+    sepal_length: float
+    sepal_width: float
+    petal_length: float
+    petal_width: float
+
+@app.get("/")
+def root():
+    return {"message": "Iris KNN API Running! Visit /docs to test the API."}
+
+@app.post("/predict")
+def predict_iris(data: IrisData):
+    if model is None:
+        return {"error": "Model not found on server"}
+
+    arr = np.array([[
+        data.sepal_length,
+        data.sepal_width,
+        data.petal_length,
+        data.petal_width
+    ]])
+
+    pred = model.predict(arr)[0]
+    return {
+        "input": data.dict(),
+        "predicted_class": str(target_names[pred])
+    }
+

iris_knn.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:af2f61d7c8a95f19394fb776308cd844f5ce159bff513b77e808efe98241100b
+size 14315

requirements.txt

@@ -0,0 +1,6 @@
+fastapi
+uvicorn
+numpy
+joblib
+scikit-learn
+pydantic