Add application file

Dockerfile

@@ -0,0 +1,16 @@
+# Read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker
+# you will also find guides on how best to write your Dockerfile
+
+FROM python:3.9
+
+RUN useradd -m -u 1000 user
+USER user
+ENV PATH="/home/user/.local/bin:$PATH"
+
+WORKDIR /app
+
+COPY --chown=user ./requirements.txt requirements.txt
+RUN pip install --no-cache-dir --upgrade -r requirements.txt
+
+COPY --chown=user . /app
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

api.py

@@ -0,0 +1,20 @@
+import pickle
+
+import numpy as np
+from fastapi import FastAPI
+
+app = FastAPI()
+
+with open("model.pkl", "rb") as f:
+    model = pickle.load(f)
+
+with open("label_encoder.pkl", "rb") as f:
+    le = pickle.load(f)
+
+
+@app.post("/predict")
+def predict(embedding: np.ndarray):
+    embedding = embedding.reshape(1, -1)
+    pred = model.predict(embedding)
+    pred_class = le.inverse_transform(pred)[0]
+    return {"result": pred_class}

label_encoder.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4ad1489188bcc6e3f9a9650258fe8123e3797930d0b56b178564270e4b1e251f
+size 276

model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:789a2e60a17d42fd5a46a38af1d40c7274048dd441c93b410377e87897fea0d7
+size 11238840

requirements.txt

@@ -0,0 +1,12 @@
+# Core Python Utilities
+setuptools
+regex
+packaging
+build
+dm-tree
+scikit-learn
+pandas
+numpy
+xgboost==2.0.3
+fastapi
+uvicorn[standard]