app.py

from flask import Flask, request, render_template
import pandas as pd
from sklearn.linear_model import LogisticRegression

# Load dataset
url = "https://raw.githubusercontent.com/sarwansingh/Python/master/ClassExamples/data/iris.csv"
df = pd.read_csv(url, header=None)
X = df.iloc[:, :4].values
y = df.iloc[:, 4].values

# Train model
model = LogisticRegression(max_iter=200)
model.fit(X, y)

# Flask app
app = Flask(__name__)

@app.route("/", methods=["GET", "POST"])
def home():
    if request.method == "POST":
        try:
            sepal_length = float(request.form["sepal_length"])
            sepal_width = float(request.form["sepal_width"])
            petal_length = float(request.form["petal_length"])
            petal_width = float(request.form["petal_width"])

            prediction = model.predict([[sepal_length, sepal_width, petal_length, petal_width]])[0]
            return render_template("index.html", prediction_text=f"Predicted Flower: {prediction}")

        except Exception as e:
            return render_template("index.html", prediction_text=f"Error: {e}")

    return render_template("index.html", prediction_text="")

if __name__ == "__main__":
    app.run(host="0.0.0.0", port=7860, debug=True)