Pushpak21/Pharmacy

1import joblib2import pandas as pd3import numpy as np4from flask import Flask, request, jsonify5from flask_cors import CORS6 7# Initialize Flask app8app = Flask("Pharmacy College Predictor")9CORS(app)10 11# Load trained model & helpers12pipeline = joblib.load('xgb_pipeline_gpu.pkl')13target_encoder = joblib.load('target_encoder.pkl')14choice_code_map = pd.read_csv('choice_code_map.csv').set_index('Choice Code')15 16# Home route17@app.get('/')18def home():19    return "✅ Welcome to Pharmacy College Predictor API!"20 21# Predict route22@app.post('/predict')23def predict():24    try:25        # Parse input JSON26        data = request.get_json()27 28        # Validate input29        required_fields = ['Category', 'Rank', 'Percentage']30        missing = [f for f in required_fields if f not in data]31        if missing:32            return jsonify({"error": f"Missing fields: {missing}"}), 40033 34        # Build DataFrame35        sample_df = pd.DataFrame([{36            'Category': data['Category'],37            'Rank': data['Rank'],38            'Percentage': data['Percentage']39        }])40 41        # Predict probabilities42        proba = pipeline.predict_proba(sample_df)[0]43 44        # Get top-20 indices (highest probabilities)45        top_20_idx = np.argsort(proba)[::-1][:20]46 47        # Normalize top-20 probs to sum to 10048        top_20_probs = proba[top_20_idx]49        top_20_probs_normalized = top_20_probs / top_20_probs.sum() * 10050 51        results = []52        for rank, (idx, prob) in enumerate(zip(top_20_idx, top_20_probs_normalized), start=1):53            choice_code = target_encoder.inverse_transform([idx])[0]54            row = choice_code_map.loc[int(choice_code)]55            college_name = row['College Name']56            results.append({57                "rank": rank,58                "choice_code": choice_code,59                "college_name": college_name,60                "probability_percent": round(float(prob), 2)61            })62 63        return jsonify({"top_20_predictions": results})64 65    except Exception as e:66        return jsonify({"error": str(e)}), 50067 68# Run server69if __name__ == '__main__':70    app.run(debug=False, host='0.0.0.0', port=7860)71