import gradio as gr
import cv2
import numpy as np

# ---------------- FUNCTIONS ---------------- #

def diamond_price(carat):
    price = int(carat * 85000)
    return f"Estimated Diamond Price: ₹{price:,}"

def face_detect(image):
    if image is None:
        return None

    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    face_cascade = cv2.CascadeClassifier(
        cv2.data.haarcascades + "haarcascade_frontalface_default.xml"
    )
    faces = face_cascade.detectMultiScale(gray, 1.3, 5)

    for (x, y, w, h) in faces:
        cv2.rectangle(image, (x, y), (x + w, y + h), (0, 180, 255), 2)

    return image

# ---------------- CREATIVE SAFE CSS ---------------- #

css = """
body {
    background: linear-gradient(120deg, #fdf2f8, #eef2ff, #ecfeff);
    font-family: 'Segoe UI', sans-serif;
    color: #1e293b;
}

h1 {
    color: #4338ca;
}

h2 {
    color: #0f172a;
}

.card {
    background: white;
    border-radius: 16px;
    padding: 20px;
    box-shadow: 0 12px 30px rgba(0,0,0,0.08);
    margin-bottom: 20px;
}

.gr-button {
    background: linear-gradient(135deg, #6366f1, #ec4899);
    color: white;
    border-radius: 14px;
    font-weight: 600;
}

.gr-button:hover {
    box-shadow: 0 8px 20px rgba(236,72,153,0.35);
}
"""

# ---------------- UI ---------------- #

with gr.Blocks(css=css, title="Simranpreet Kaur | AI Portfolio") as demo:

    gr.Markdown("""
    <div class="card">
    <h1>Simranpreet Kaur</h1>
    <p><b>AI • Machine Learning • Computer Vision</b></p>
    <p>📍 Fatehgarh Sahib, Punjab</p>
    <p>📧 spreetkaur937@gmail.com</p>
    </div>
    """)

    gr.Markdown("""
    <div class="card">
    <h2>About Me</h2>
    <p>
    B.Tech Computer Science (2022–2026) student passionate about building
    intelligent and practical AI systems including prediction models and
    real-time computer vision applications.
    </p>
    </div>
    """)

    with gr.Tabs():

        with gr.Tab("💎 Diamond Price Prediction"):
            gr.Markdown("<div class='card'><h3>Diamond Price Prediction</h3></div>")
            carat = gr.Slider(0.1, 5.0, step=0.1, label="Carat")
            output = gr.Textbox(label="Predicted Price")
            carat.change(diamond_price, carat, output)

        with gr.Tab("🧑 Face Detection"):
            gr.Markdown("<div class='card'><h3>Face Detection</h3></div>")
            img = gr.Image(type="numpy", label="Upload Image")
            out = gr.Image(label="Detected Faces")
            img.change(face_detect, img, out)

        with gr.Tab("🔊 Text to Speech"):
            gr.Markdown("<div class='card'><h3>Text to Speech</h3></div>")
            gr.Textbox(label="Enter text (demo description only)")

        with gr.Tab("📊 Stock Market Analysis"):
            gr.Markdown("""
            <div class="card">
            <h3>Stock Market Analysis</h3>
            <ul>
              <li>Trend Analysis</li>
              <li>Pattern Recognition</li>
              <li>Data Visualization</li>
            </ul>
            </div>
            """)

    gr.Markdown("""
    <div class="card">
    <h3>Contact</h3>
    <p>Email: <b>spreetkaur937@gmail.com</b></p>
    <p>Hosted on Hugging Face Spaces</p>
    </div>
    """)

demo.launch()