Upload folder using huggingface_hub

Dockerfile

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+
+FROM python:3.10
+
+WORKDIR /code
+
+COPY app/requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY app /code/app
+
+EXPOSE 7860
+CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "7860"]

README.md

@@ -1,10 +1,3 @@
----
-title: Diabetes Api Fastapi
-emoji: 🔥
-colorFrom: blue
-colorTo: yellow
-sdk: docker
-pinned: false
----
+# Diabetes Prediction API using FastAPI
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+POST /predict

app/main.py

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+
+from fastapi import FastAPI
+from pydantic import BaseModel
+import joblib
+import pandas as pd
+
+model = joblib.load("app/model.pkl")
+app = FastAPI()
+
+class ModelInput(BaseModel):
+    input: list
+
+@app.post("/predict")
+def predict(data: ModelInput):
+    input_df = pd.DataFrame([data.input], columns=["preg", "plas", "pres", "skin", "test", "mass", "pedi", "age"])
+    prediction = int(model.predict(input_df)[0])
+    return {"prediction": prediction}

app/model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a493e8730770095a1d02381f1161cee2921db62a911918087c8386fbc15cf831
+size 15769

app/requirements.txt

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+fastapi
+uvicorn
+joblib
+pandas
+scikit-learn