from flask import Flask, render_template, request, redirect, url_for, session, flash
from werkzeug.security import generate_password_hash, check_password_hash
import os

# ML imports
from sklearn.datasets import load_iris
from sklearn.linear_model import LogisticRegression
import numpy as np

app = Flask(__name__)

# Stable secret key (important for sessions in Hugging Face Spaces)
app.secret_key = os.environ.get("SECRET_KEY", "supersecretkey123")

# ----------------------------
# Train Iris Model (once only)
# ----------------------------
iris = load_iris(as_frame=True)
X = iris.data.values
y = iris.target
species = iris.target_names

iris_model = LogisticRegression(max_iter=300)
iris_model.fit(X, y)

# ----------------------------
# Simple in-memory "database"
# ----------------------------
users = {}

@app.route("/")
def home():
    if "user" in session:
        return redirect(url_for("dashboard"))
    return redirect(url_for("login"))

@app.route("/signup", methods=["GET", "POST"])
def signup():
    if request.method == "POST":
        username = request.form["username"]
        password = request.form["password"]
        confirm_password = request.form.get("confirmPassword")

        if password != confirm_password:
            flash("Passwords do not match.", "danger")
            return redirect(url_for("signup"))

        if username in users:
            flash("Username already exists!", "danger")
            return redirect(url_for("signup"))

        # Save user and auto-login
        users[username] = generate_password_hash(password)
        session["user"] = username
        flash("Signup successful! You are now logged in.", "success")
        return redirect(url_for("dashboard"))

    return render_template("signup.html")

@app.route("/login", methods=["GET", "POST"])
def login():
    if request.method == "POST":
        username = request.form["username"]
        password = request.form["password"]

        if username in users and check_password_hash(users[username], password):
            session["user"] = username
            # return render_template(
            #     "dashboard.html",
            #     username=session["user"],
            #     )
            flash("Login successful!", "success")
            return redirect(url_for("dashboard"))
        else:
            flash("Invalid username or password", "danger")

    return render_template("login.html")

@app.route("/dashboard")
def dashboard():
    if "user" not in session:
        return redirect(url_for("login"))
    return render_template("dashboard.html", username=session["user"])

@app.route("/predict", methods=["POST"])
def predict():
    if "user" not in session:
        return redirect(url_for("login"))

    try:
        sl = float(request.form["sepal_length"])
        sw = float(request.form["sepal_width"])
        pl = float(request.form["petal_length"])
        pw = float(request.form["petal_width"])
    except Exception:
        flash("Invalid input values!", "danger")
        return redirect(url_for("dashboard"))

    res_idx = iris_model.predict([[sl, sw, pl, pw]])[0]
    res = species[res_idx]
   # flash(f"The predicted flower species is: {res}", "success")
    # return redirect(url_for("dashboard"))
        # Render dashboard with prediction
    return render_template(
        "dashboard.html",
        username=session["user"],
        prediction=res,
        scroll_to="predict"
    )

@app.route("/portfolio")
def portfolio():
    if "user" not in session:
        return redirect(url_for("login"))
    return render_template("portfolio.html")

@app.route("/logout")
def logout():
    session.pop("user", None)
    flash("Logged out successfully.", "info")
    return redirect(url_for("login"))

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