import gradio as gr
import matplotlib.pyplot as plt

def credit_scoring_model(
    name,
    number,
    job,
    income,
    employment_status,
    credit_history,
    gpa
):
    score = 0
    reasons = []

    # ============================
    # SCORING DETAIL (for chart)
    # ============================
    score_detail = {}

    # ----------------------------
    # INCOME (30%)
    # ----------------------------
    if income >= 15000000:
        income_score = 30
        reasons.append("Penghasilan sangat baik")
    elif income >= 8000000:
        income_score = 25
        reasons.append("Penghasilan baik")
    elif income >= 5000000:
        income_score = 20
        reasons.append("Penghasilan cukup")
    else:
        income_score = 10
        reasons.append("Penghasilan rendah")

    score += income_score
    score_detail["Penghasilan"] = income_score

    # ----------------------------
    # EMPLOYMENT STATUS (20%)
    # ----------------------------
    if employment_status == "Tetap":
        emp_score = 20
        reasons.append("Status pekerjaan tetap")
    elif employment_status == "Kontrak":
        emp_score = 12
        reasons.append("Status pekerjaan kontrak")
    else:
        emp_score = 5
        reasons.append("Status pekerjaan tidak tetap")

    score += emp_score
    score_detail["Status Pekerjaan"] = emp_score

    # ----------------------------
    # CREDIT HISTORY (30%)
    # ----------------------------
    if credit_history == "Lancar":
        credit_score = 30
        reasons.append("Riwayat kredit lancar")
    elif credit_history == "Pernah Tunggakan":
        credit_score = 15
        reasons.append("Pernah mengalami tunggakan")
    else:
        credit_score = 5
        reasons.append("Riwayat kredit buruk")

    score += credit_score
    score_detail["Riwayat Kredit"] = credit_score

    # ----------------------------
    # GPA (20%)
    # ----------------------------
    if gpa >= 3.75:
        gpa_score = 20
        reasons.append("IPK sangat baik")
    elif gpa >= 3.25:
        gpa_score = 15
        reasons.append("IPK baik")
    elif gpa >= 3.0:
        gpa_score = 10
        reasons.append("IPK cukup")
    else:
        gpa_score = 5
        reasons.append("IPK rendah / tidak tersedia")

    score += gpa_score
    score_detail["IPK"] = gpa_score

    # ----------------------------
    # FINAL DECISION
    # ----------------------------
    if score >= 80:
        grade = "A"
        decision = "✅ LAYAK KREDIT"
    elif score >= 65:
        grade = "B"
        decision = "🟡 DIPERTIMBANGKAN"
    elif score >= 50:
        grade = "C"
        decision = "🟠 RISIKO MENENGAH"
    else:
        grade = "D"
        decision = "❌ TIDAK LAYAK"

    # ============================
    # CREATE BAR CHART
    # ============================
    fig, ax = plt.subplots()
    ax.bar(score_detail.keys(), score_detail.values())
    ax.set_ylim(0, 30)
    ax.set_title("Distribusi Skor Credit Scoring")
    ax.set_ylabel("Skor")
    ax.set_xlabel("Komponen Penilaian")

    # ============================
    # TEXT REPORT
    # ============================
    report = f"""
👤 Nama              : {name}
📞 Nomor             : {number}
💼 Pekerjaan         : {job}

📊 HASIL CREDIT SCORING MODEL (CSM)
---------------------------------
Skor Total           : {score} / 100
Grade                : {grade}
Keputusan Kredit     : {decision}

🧠 Alasan Penilaian:
- """ + "\n- ".join(reasons) + """

📌 Catatan:
Model ini bersifat rule-based & explainable,
cocok untuk Bank, Fintech, Audit, dan Governance.
"""

    return report, fig


# ============================
# GRADIO UI
# ============================
with gr.Blocks() as demo:
    gr.Markdown("## 🏦 Credit Scoring Model (CSM)")
    gr.Markdown(
        "Simulasi penilaian kelayakan kredit berbasis "
        "**rule-based & explainable**."
    )

    with gr.Row():
        name = gr.Textbox(label="Nama Lengkap")
        number = gr.Textbox(label="Nomor (HP / ID)")

    job = gr.Textbox(label="Pekerjaan")
    income = gr.Number(label="Penghasilan Bulanan (Rp)", value=5000000)

    with gr.Row():
        employment_status = gr.Dropdown(
            ["Tetap", "Kontrak", "Tidak Tetap"],
            label="Status Pekerjaan"
        )
        credit_history = gr.Dropdown(
            ["Lancar", "Pernah Tunggakan", "Buruk"],
            label="Riwayat Kredit"
        )

    gpa = gr.Slider(2.0, 4.0, step=0.01, label="IPK (Opsional)")

    output_text = gr.Textbox(
        label="Hasil Analisis Credit Scoring",
        lines=18
    )

    output_plot = gr.Plot(label="Visual Distribusi Skor")

    submit = gr.Button("🔍 Hitung Skor Kredit")

    submit.click(
        credit_scoring_model,
        inputs=[
            name,
            number,
            job,
            income,
            employment_status,
            credit_history,
            gpa
        ],
        outputs=[output_text, output_plot]
    )

demo.launch()