Upload backend for Superkart (initial commit)

Dockerfile

@@ -1,20 +1,12 @@
-FROM python:3.13.5-slim
+FROM python:3.9-slim
 
 WORKDIR /app
 
-RUN apt-get update && apt-get install -y \
-    build-essential \
-    curl \
-    git \
-    && rm -rf /var/lib/apt/lists/*
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
 
-COPY requirements.txt ./
-COPY src/ ./src/
+COPY . .
 
-RUN pip3 install -r requirements.txt
+EXPOSE 7860
 
-EXPOSE 8501
-
-HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health
-
-ENTRYPOINT ["streamlit", "run", "src/streamlit_app.py", "--server.port=8501", "--server.address=0.0.0.0"]
+CMD ["python", "app.py"]

app.py

@@ -0,0 +1,30 @@
+
+from flask import Flask, request, jsonify
+import joblib
+import pandas as pd
+
+app = Flask(__name__)
+
+# Load the trained model
+model = joblib.load('model.joblib')
+
+@app.route('/predict', methods=['POST'])
+def predict():
+    try:
+        data = request.get_json()
+        # Convert to pandas DataFrame
+        if isinstance(data, dict):
+             df = pd.DataFrame([data])
+        else:
+             df = pd.DataFrame(data)
+
+        # Make prediction
+        prediction = model.predict(df)
+
+        # Return result
+        return jsonify({'prediction': prediction.tolist()})
+    except Exception as e:
+        return jsonify({'error': str(e)})
+
+if __name__ == '__main__':
+    app.run(host='0.0.0.0', port=7860)

model.joblib

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5f31600d3c9f8bfbfe6a09dd9a114a29b749b9c54d3b2d4012cec56fbbb8ede6
+size 39747074

requirements.txt

@@ -1,3 +1,5 @@
-altair
+flask
 pandas
-streamlit
+scikit-learn
+joblib
+numpy