import gradio as gr
import pandas as pd
import plotly.express as px

df = pd.read_csv("sample_100_jobs.csv")

def filter_data(industry, country, max_risk, min_salary):
    d = df.copy()
    if industry != "All": d = d[d["Industry"] == industry]
    if country != "All": d = d[d["Country"] == country]
    d = d[(d["AI_Replacement_Risk"] <= max_risk) & (d["Average_Salary_USD"] >= min_salary)]
    return d.sort_values("Demand_Risk_Ratio", ascending=False)

def scatter():
    fig = px.scatter(df, x="AI_Replacement_Risk", y="Average_Salary_USD", 
                     color="AI_Risk_Category", size="Demand_Risk_Ratio",
                     hover_data=["Job_Title"], template="plotly_dark", height=420,
                     color_discrete_map={"Low":"#10B981","Medium":"#3B82F6","High":"#EF4444"})
    fig.update_layout(
        paper_bgcolor="rgba(0,0,0,0)", plot_bgcolor="rgba(0,0,0,0)",
        margin=dict(l=10,r=10,t=40,b=10), font=dict(family="Inter")
    )
    return fig

def top_jobs():
    top = df.nlargest(10, "Demand_Risk_Ratio")
    fig = px.bar(top, x="Demand_Risk_Ratio", y="Job_Title", orientation="h",
                 template="plotly_dark", color="Demand_Risk_Ratio", height=420,
                 color_continuous_scale="Viridis")
    fig.update_layout(
        paper_bgcolor="rgba(0,0,0,0)", plot_bgcolor="rgba(0,0,0,0)",
        yaxis={"categoryorder":"total ascending"}, font=dict(family="Inter")
    )
    return fig

css = """
@import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700;800;900&display=swap');

* {font-family: 'Inter', sans-serif !important;}

body{
background: radial-gradient(ellipse 80% 50% at 50% -20%, rgba(120,119,198,0.3), transparent),
            radial-gradient(ellipse 80% 50% at 50% 120%, rgba(79,70,229,0.2), transparent),
            linear-gradient(180deg, #020617 0%, #0F172A 50%, #020617 100%) !important;
background-attachment: fixed !important;
}

.gradio-container{
width:96% !important;
max-width:1400px !important;
margin: 0 auto !important;
}

/* ANIMASI GRADIENT BERJALAN */
@keyframes gradientFlow {
0% {background-position: 0% 50%;}
50% {background-position: 100% 50%;}
100% {background-position: 0% 50%;}
}

.animated-gradient {
background: linear-gradient(90deg, #60A5FA, #A855F7, #EC4899, #60A5FA);
background-size: 300% 300%;
-webkit-background-clip: text;
-webkit-text-fill-color: transparent;
animation: gradientFlow 4s ease infinite;
}

/* NAVBAR */
.navbar{
display: flex;justify-content: space-between;align-items: center;
padding: 20px 0;margin-bottom: 30px;
}
.nav-left{display:flex;align-items:center;gap:40px}
.logo{display:flex;align-items:center;gap:12px;font-weight:900;font-size:22px;color:#fff}
.logo-icon{
width:32px;height:32px;border-radius:8px;
background:linear-gradient(135deg,#6366F1,#A855F7);
display:flex;align-items:center;justify-content:center;
box-shadow:0 0 20px rgba(99,102,241,.6);
}
.nav-links{display:flex;gap:32px}
.nav-links a{color:#94A3B8;text-decoration:none;font-weight:600;font-size:14px}
.nav-links a:hover{color:#fff}
.nav-right{display:flex;gap:12px}
.btn-ghost{
background:rgba(30,41,59,.6);border:1px solid rgba(99,102,241,.3);
color:#fff;padding:10px 20px;border-radius:12px;font-weight:700;cursor:pointer;
}
.btn-primary{
background:linear-gradient(90deg,#6366F1,#A855F7);
color:#fff;padding:10px 24px;border-radius:12px;border:none;
font-weight:700;cursor:pointer;
box-shadow:0 4px 20px rgba(99,102,241,.4), 0 0 40px rgba(99,102,241,.2);
}

/* HERO */
.hero{
padding:70px 45px;
border-radius:24px;
background: linear-gradient(135deg, rgba(15,23,42,.8), rgba(30,41,59,.6));
border:1px solid rgba(99,102,241,.2);
box-shadow: 0 0 60px rgba(99,102,241,.15), inset 0 1px 0 rgba(255,255,255,.1);
margin-bottom:40px;
text-align: center;
backdrop-filter: blur(20px);
position:relative;overflow:hidden;
}
.hero::before{
content:'';position:absolute;top:-50%;left:50%;transform:translateX(-50%);
width:600px;height:600px;
background:radial-gradient(circle, rgba(99,102,241,.25), transparent 70%);
filter:blur(80px);z-index:0;
}
.hero-badge{
display:inline-flex;align-items:center;gap:8px;
padding:8px 16px;background:rgba(99,102,241,.1);
border:1px solid rgba(99,102,241,.3);border-radius:99px;
font-size:14px;color:#A5B4FC;margin-bottom:24px;position:relative;z-index:1;font-weight:600;
}
.hero h1{
font-size:68px;line-height:1.1;font-weight:900;
margin:0 0 16px 0;position:relative;z-index:1;
color:#FFFFFF;
letter-spacing:-1px;
}
.hero h1 .gradient{
font-weight:900;
display:block;
margin-top:8px;
}
.hero p{
font-size:18px;color:#CBD5E1;max-width:700px;
margin:0 auto 32px auto;line-height:1.7;position:relative;z-index:1;font-weight:500;
}
.hero-cta{display:flex;gap:16px;justify-content:center;position:relative;z-index:1}

/* STATS */
.stats{
display: grid;
grid-template-columns: repeat(4, 1fr);
gap: 20px;
margin-bottom: 80px;
}
.stat-card{
padding:28px 24px;
border-radius:20px;
background: linear-gradient(135deg, rgba(99,102,241,.1), rgba(168,85,247,.05));
backdrop-filter: blur(20px);
border: 1px solid rgba(99,102,241,.2);
text-align: center;
box-shadow: 0 8px 32px rgba(99,102,241,.1);
}
.stat-card .label{
display:flex;align-items:center;gap:8px;justify-content:center;
color:#94A3B8;font-size:14px;margin-bottom:12px;font-weight:600;
}
.stat-card .value{
font-size:36px;font-weight:900;
background: linear-gradient(90deg, #6366F1, #A855F7);
-webkit-background-clip: text;
-webkit-text-fill-color: transparent;
}

/* DASHBOARD */
.section-header{margin-bottom:32px}
.section-header h2{font-size:32px;margin:0 0 8px 0;font-weight:900;color:#fff}
.section-header p{color:#94A3B8;margin:0;font-size:15px;font-weight:500}
.card{
padding:24px;border-radius:20px;
background: rgba(15,23,42,.6) !important;
backdrop-filter: blur(20px) !important;
border: 1px solid rgba(99,102,241,.15) !important;
margin-bottom:24px;box-shadow: 0 8px 32px rgba(0,0,0,.3);
}

.footer{
margin-top:60px;padding:40px 30px;text-align:center;
color: #64748B;border-top: 1px solid rgba(99,102,241,.1);font-weight: 600;
}

@media (max-width: 768px) {
  .nav-links{display:none}
  .hero h1 { font-size: 42px; }
  .stats { grid-template-columns: repeat(2, 1fr); }
  .hero-cta{flex-direction:column}
}
"""

with gr.Blocks(css=css, fill_width=True, theme=gr.themes.Base()) as demo:
    
    # NAVBAR
    gr.HTML("""
    <div class='navbar'>
        <div class='nav-left'>
            <div class='logo'>
                <div class='logo-icon'>◆</div>
                AI DataLab
            </div>
            <div class='nav-links'>
                <a href='#dashboard'>Dashboard</a>
                <a href='#'>Reports</a>
                <a href='#'>Insights</a>
                <a href='#'>About</a>
            </div>
        </div>
        <div class='nav-right'>
            <button class='btn-ghost'>Sign In</button>
            <button class='btn-primary'>Get Started</button>
        </div>
    </div>
    """)

    # HERO - FONT TEBEL + GRADIENT ANIMASI
    gr.HTML("""
    <div class='hero'>
        <div class='hero-badge'>★ Powered by AI-Driven Analytics</div>
        <h1>
            Future-Proof Your Career
            <span class='gradient animated-gradient'>with AI Insights</span>
        </h1>
        <p>
            Analyze job market trends, salary projections, and AI automation risks. 
            Make data-driven decisions for 2031 and beyond with real-time predictive analytics.
        </p>
        <div class='hero-cta'>
            <button class='btn-primary' onclick="document.getElementById('dashboard').scrollIntoView({behavior:'smooth'})">
                Explore Dashboard →
            </button>
            <button class='btn-ghost'>▶ Watch Demo</button>
        </div>
    </div>
    """)

    # STATS
    gr.HTML("""
    <div class='stats'>
        <div class='stat-card'>
            <div class='label'>⚡ Total Jobs Analyzed</div>
            <div class='value'>3,000+</div>
        </div>
        <div class='stat-card'>
            <div class='label'>$ Average Salary 2031</div>
            <div class='value'>$96K</div>
        </div>
        <div class='stat-card'>
            <div class='label'>⚠ High Risk Jobs</div>
            <div class='value'>856</div>
        </div>
        <div class='stat-card'>
            <div class='label'>✦ Future-Proof Score</div>
            <div class='value'>87.5%</div>
        </div>
    </div>
    """)
    
    # DASHBOARD
    gr.HTML("""
    <div class='section-header' id='dashboard'>
        <h2>Live Data Analysis Dashboard</h2>
        <p>Filter and explore 100+ jobs with real-time risk scoring</p>
    </div>
    """)

    with gr.Row():
        with gr.Column(scale=1, min_width=300):
            with gr.Group(elem_classes="card"):
                gr.Markdown("### 🔍 FILTERS")
                industry = gr.Dropdown(["All"] + sorted(df["Industry"].unique()), value="All", label="Industry")
                country = gr.Dropdown(["All"] + sorted(df["Country"].unique()), value="All", label="Country")
                risk = gr.Slider(0, 1, value=.5, label="Max AI Risk")
                salary = gr.Slider(0, 200000, value=50000, label="Min Salary (USD)")
                btn = gr.Button("Analyze Data →", variant="primary")

        with gr.Column(scale=4):
            with gr.Group(elem_classes="card"):
                gr.Plot(value=scatter())
            with gr.Group(elem_classes="card"):
                gr.Plot(value=top_jobs())
            with gr.Group(elem_classes="card"):
                gr.Markdown("### 📋 Job Dataset")
                table = gr.Dataframe(value=df.head(20), interactive=False)

    btn.click(filter_data, [industry,country,risk,salary], table)

    # FOOTER + AUTHOR
    gr.HTML("""
    <div class='footer'>
        <div style='margin-bottom:24px;'>
            <h3 style='font-size:20px;font-weight:800;margin:0 0 8px 0;color:#fff;'>👨‍💻 Author</h3>
            <p style='font-size:18px;font-weight:700;margin:0 0 4px 0;color:#E2E8F0;'>Farly Setiawan</p>
            <p style='font-size:14px;margin:0 0 16px 0;color:#94A3B8;'>Founder @ Aitopia | Specialist Data Engineer</p>
            <p style='font-size:14px;margin:0 0 20px 0;color:#64748B;'>Helping 2M Indonesian traders lose less money</p>
        </div>
        
        <div style='display:flex;gap:12px;justify-content:center;flex-wrap:wrap;margin-bottom:24px;'>
            <a href='https://www.linkedin.com/in/faronecapital' target='_blank'>
                <img src='https://img.shields.io/badge/LinkedIn-Farly_Setiawan-0077B5?style=for-the-badge&logo=linkedin&logoColor=white'>
            </a>
            <a href='https://huggingface.co/farone11' target='_blank'>
                <img src='https://img.shields.io/badge/🤗_Hugging_Face-farone11-yellow?style=for-the-badge'>
            </a>
            <a href='https://github.com/farone11' target='_blank'>
                <img src='https://img.shields.io/badge/GitHub-farone11-181717?style=for-the-badge&logo=github'>
            </a>
        </div>
        
        <div style='padding-top:24px;border-top:1px solid rgba(99,102,241,.1);'>
            <p style='font-size:13px;margin:0 0 8px 0;color:#64748B;font-weight:600;'>📜 License</p>
            <p style='font-size:13px;margin:0;color:#475569;'>
                Commercial License Required. Demo is free for evaluation.<br>
                Full datasheet & source code require purchase. Contact farone2013@gmail.com
            </p>
        </div>
        
        <div style='margin-top:24px;font-size:12px;color:#475569;'>
            © 2026 FarOneCapital Institutional Analytics Platform
        </div>
    </div>
    """)

demo.launch()