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from flask import Flask, render_template, request, jsonify
from src.pipelines.prediction_pipeline import CustomData, PredictPipeline
from src.exception import CustomException
app = Flask(__name__)
@app.route('/')
def index():
return render_template('index.html')
@app.route('/predict', methods=['POST'])
def predict_route():
try:
# Get the form data from the request
data = request.form
# Extract values safely from the incoming form data
custom_data = CustomData(
age=data.get("age"),
sex=data.get("sex"),
chest_pain_type=data.get("chestPainType"),
resting_bp=data.get("restingBP"),
cholesterol=data.get("cholesterol"),
fasting_bs=data.get("fastingBS"),
resting_ecg=data.get("restingECG"),
max_hr=data.get("maxHR"),
oldpeak=data.get("oldpeak"),
exercise_angina=data.get("exerciseAngina"),
st_slope=data.get("stSlope")
)
# Convert to DataFrame
input_df = custom_data.get_data_as_dataframe()
# Create a PredictPipeline instance and make a prediction
prediction_pipeline = PredictPipeline()
prediction = prediction_pipeline.predict(input_df)
# Condition to check if prediction equals 1
if prediction[0] == 1:
result_message = "You are at moderate risk of experiencing a heart attack"
else:
result_message = "There are no immediate risk factors for a heart attack"
# Pass the result message back to the template for display
return render_template('index.html', results=result_message)
except ValueError as ve:
return jsonify({"error": str(ve)}), 400
except CustomException as ce:
return jsonify({"error": str(ce)}), 500
except Exception as e:
return jsonify({"error": "An error occurred: " + str(e)}), 500
if __name__ == '__main__':
app.run(debug=True)
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