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fahadcr14
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Commit
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7b26e4e
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Parent(s):
f678a54
test
Browse files- Dockerfile +20 -0
- app.py +23 -0
- templates/index.html +12 -0
Dockerfile
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# Use a lightweight Python base image
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FROM python:3.8-slim
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# Set environment variables
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ENV PYTHONDONTWRITEBYTECODE=1
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ENV PYTHONUNBUFFERED=1
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# Install dependencies
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WORKDIR /app
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COPY requirements.txt /app/
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RUN pip install --no-cache-dir -r requirements.txt
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# Copy app files
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COPY . /app
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# Expose the port Flask will run on
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EXPOSE 7860
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# Run the Flask app
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CMD ["python", "app.py"]
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app.py
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from flask import Flask, request, jsonify, render_template
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app = Flask(__name__)
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# Route for the home page
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@app.route('/')
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def index():
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return render_template('index.html')
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# Prediction endpoint (mock prediction for now)
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@app.route('/predict', methods=['POST'])
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def predict():
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data = request.json
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activities = data.get('activities')
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# Placeholder logic for prediction (replace with your ML model)
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if activities:
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predicted_score = sum(activities) / len(activities) # Example logic
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return jsonify({'predicted_score': predicted_score})
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return jsonify({'error': 'No activities provided'}), 400
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if __name__ == '__main__':
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app.run(host='0.0.0.0', port=7860)
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templates/index.html
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>Student Score Predictor</title>
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</head>
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<body>
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<h1>Welcome to the Student Score Predictor</h1>
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<p>Submit your activities scores via POST request to /predict to get the final score prediction.</p>
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</body>
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</html>
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