refactor: rename engine and methods, enhance NBO logic with detailed steps, and overhaul report generation with new UI styling.

app.py

@@ -6,143 +6,160 @@ import plotly.graph_objects as go
 from google import genai
 from datetime import timedelta
 
-# --- INITIALIZATION ---
+# --- CONFIG AI ---
 GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
 client_ai = genai.Client(api_key=GOOGLE_API_KEY) if GOOGLE_API_KEY else None
 
-# --- UI STYLE BANK NAGARI PREMIUM ---
+# --- UI STYLE: BANK NAGARI REFINED ---
 custom_css = """
 @import url('https://fonts.googleapis.com/css2?family=Plus+Jakarta+Sans:wght@400;600;700;800&display=swap');
 body, .gradio-container { font-family: 'Plus Jakarta Sans', sans-serif !important; background-color: #FFFFFF !important; }
 .nagari-header { background: linear-gradient(135deg, #0514DE 0%, #82C3EB 100%); padding: 35px; border-radius: 15px; border-bottom: 6px solid #F7BD87; text-align: center; margin-bottom: 25px; }
 .nagari-header h1 { color: #FFFFFF !important; font-weight: 800 !important; margin: 0; font-size: 2.2em; }
-.report-card { background: #FFFFFF; border-radius: 12px; padding: 25px; border: 1.5px solid #E0EDF4; box-shadow: 0 4px 15px rgba(5, 20, 222, 0.05); margin-bottom: 20px; }
-.section-header { color: #0514DE; border-bottom: 2px solid #F7BD87; padding-bottom: 5px; margin-bottom: 15px; font-weight: 700; }
-.status-pill { padding: 10px 20px; border-radius: 30px; color: white; font-weight: 800; display: inline-block; font-size: 1.1em; }
+.card-left { background: #E0EDF4; border-radius: 15px; padding: 25px; border: 1.5px solid #82C3EB; box-shadow: 0 4px 12px rgba(5, 20, 222, 0.08); }
+.badge-item { background: white; padding: 10px; border-radius: 8px; margin-bottom: 10px; border-left: 4px solid #0514DE; font-size: 0.9em; }
+.report-card { background: white; border-radius: 12px; padding: 30px; border: 1px solid #E2E8F0; line-height: 1.8; color: #1e293b; }
+.nbo-box { background: #fffdf0; border: 2px solid #F7BD87; padding: 20px; border-radius: 10px; margin-top: 20px; }
 """
 
-class ArchonNarrativeEngine:
+class ArchonFinalEngine:
     def __init__(self):
         self.load_data()
 
     def load_data(self):
-        # FASE 1: Foundation
         self.df_txn = pd.read_csv('transactions.csv', parse_dates=['date']).sort_values('date')
         self.df_cust = pd.read_csv('customers.csv')
         self.df_bal = pd.read_csv('balances_revised.csv', parse_dates=['month']).sort_values('month')
         self.df_rep = pd.read_csv('repayments_revised.csv', parse_dates=['due_date']).fillna("on_time")
 
-    def run_full_pipeline(self, customer_id):
+    def analyze(self, customer_id):
         cid = str(customer_id).strip().upper()
         u_txn = self.df_txn[self.df_txn['customer_id'] == cid].copy()
         u_bal = self.df_bal[self.df_bal['customer_id'] == cid].sort_values('month')
         u_rep = self.df_rep[self.df_rep['customer_id'] == cid]
-        u_info = self.df_cust[self.df_cust['customer_id'] == cid].iloc[0] if cid in self.df_cust['customer_id'].values else None
+        u_info_list = self.df_cust[self.df_cust['customer_id'] == cid]
 
-        if u_txn.empty or u_info is None: return None
+        if u_txn.empty or u_info_list.empty: return None
+        u_info = u_info_list.iloc[0]
 
-        # --- FASE 2 & 3: INTELLIGENCE ---
+        # --- FASE 2: INTELLIGENCE ---
         income_txn = u_txn[u_txn['transaction_type'] == 'credit']['amount'].sum()
         ref_income = max(income_txn, u_info['monthly_income'])
         expense = u_txn[u_txn['transaction_type'] == 'debit']['amount'].sum()
-        er = min(expense / ref_income, 1.0)
+        er = min(expense / ref_income, 1.0) if ref_income > 0 else 1.0
         
         # --- FASE 4: RISK SCORING (30/20/20/20/10) ---
-        er_s = 1.0 if er > 0.8 else (0.5 if er > 0.5 else 0.0)
-        bt_s = 1.0 if len(u_bal) >= 2 and u_bal.iloc[-1]['avg_balance'] < u_bal.iloc[-2]['avg_balance'] else 0.0
-        od_s = 1.0 if (u_bal['min_balance'] <= 0).any() else 0.0
-        mp_s = 1.0 if (u_rep['status'] == 'late').any() else 0.0
+        # Normalisasi Skor 0 - 1
+        er_score_val = 1.0 if er > 0.8 else (0.5 if er > 0.5 else 0.0)
+        bt_val = 1.0 if len(u_bal) >= 2 and u_bal.iloc[-1]['avg_balance'] < u_bal.iloc[-2]['avg_balance'] else 0.0
+        od_val = 1.0 if (u_bal['min_balance'] <= 0).any() else 0.0
+        mp_val = 1.0 if (u_rep['status'] == 'late').any() else 0.0
         
-        score = (0.3 * er_s) + (0.2 * bt_s) + (0.2 * od_s) + (0.2 * mp_s) + 0.1
-        risk_lv = "HIGH" if score >= 0.7 else ("MEDIUM" if score >= 0.4 else "LOW")
+        final_score = (0.3 * er_score_val) + (0.2 * bt_s := bt_val) + (0.2 * od_s := od_val) + (0.2 * mp_s := mp_val) + 0.1
+        risk_lv = "HIGH" if final_score >= 0.7 else ("MEDIUM" if final_score >= 0.4 else "LOW")
+
+        # --- FASE 5: NBO ENGINE (SPENDING CONTROL FOCUS) ---
+        if risk_lv == "HIGH" or mp_val == 1:
+            action, nbo_detail = "Restructuring Suggestion", "Prioritas penyelamatan kredit melalui penjadwalan ulang cicilan."
+            steps = ["Penurunan suku bunga sementara", "Perpanjangan tenor pinjaman", "Konsolidasi utang harian."]
+        elif er > 0.6:
+            action, nbo_detail = "Spending Control", "Pengendalian pengeluaran non-esensial untuk menjaga likuiditas harian."
+            steps = ["Aktivasi limit harian transaksi QRIS", "Notifikasi otomatis saat belanja > Rp500rb", "Edukasi pemisahan rekening operasional."]
+        elif risk_lv == "LOW":
+            action, nbo_detail = "Promote Investment", "Optimalisasi surplus dana melalui produk investasi Bank Nagari."
+            steps = ["Penawaran Deposito Gold", "Reksa Dana pasar uang", "Tabungan berjangka otomatis."]
+        else:
+            action, nbo_detail = "Financial Education", "Edukasi pengelolaan arus kas agar status risiko tetap stabil."
+            steps = ["Webinar literasi keuangan", "E-book perencanaan budget", "Review bulanan bersama RM."]
+
+        return risk_lv, final_score, er, u_bal, u_txn, expense, ref_income, action, nbo_detail, steps, er_score_val, bt_val, od_val, mp_val
+
+    def get_report_text(self, risk_lv, score, er, u_bal, expense, income, action, nbo_detail, steps, cid, u_txn):
+        # Fase 6: Explainable Summary
+        report = f"### 📊 ANALISIS EKSEKUTIF ARCHON-AI\n\n"
+        report += f"**Identitas Nasabah:** {cid}\n"
+        report += f"Berdasarkan audit mutasi, tingkat resiliensi Bapak/Ibu berada pada kategori **{risk_lv}** (Skor: {score:.2f}).\n\n"
         
-        # --- FASE 5: NBO ---
-        if risk_lv == "HIGH": action, nbo_desc = "Restructuring Suggestion", "Fokus pada penyelamatan kredit."
-        elif er > 0.6: action, nbo_desc = "Spending Control", "Batasi pengeluaran non-esensial."
-        else: action, nbo_desc = "Promote Saving/Investment", "Optimalkan surplus dana nasabah."
-
-        return risk_lv, score, er, u_bal, u_txn, expense, ref_income, action, nbo_desc
-
-    def build_narrative_report(self, risk_lv, score, er, u_bal, expense, income, action, nbo_desc, cid, u_txn):
-        # FASE 6: EXPLAINABLE SUMMARY & RINGKASAN AI
-        report = f"<div class='report-card'>"
-        report += f"<h3 class='section-header'>🌟 EXECUTIVE SUMMARY (RINGKASAN AI)</h3>"
-        
-        # Ringkasan Naratif Otomatis
-        report += f"<p>Berdasarkan analisis menyeluruh terhadap data mutasi dan profil Bapak/Ibu ({cid}), sistem Archon menetapkan tingkat resiliensi finansial Anda berada pada kategori <b>{risk_lv}</b>. "
-        report += f"Hal ini disebabkan oleh kombinasi antara rasio pengeluaran sebesar {er:.1%} dan stabilitas saldo yang memerlukan perhatian khusus.</p>"
+        report += f"**1. Mengapa Skor Ini Muncul?**\n"
+        report += f"* **Efisiensi Dana**: Rasio belanja Anda {er:.1%}. Artinya dari pendapatan Rp{income:,.0f}, sebanyak Rp{expense:,.0f} terpakai. "
+        report += "Ini mengindikasikan tekanan likuiditas." if er > 0.8 else "Ini menunjukkan kondisi kas yang aman."
         
-        report += f"<h3 class='section-header'>🔍 MENGAPA SKOR ANDA {score:.2f}?</h3>"
-        report += f"<ul>"
-        report += f"<li><b>Rasio Pengeluaran ({er:.1%})</b>: Artinya, dari setiap Rp1.000.000 yang Bapak/Ibu terima, sebanyak Rp{int(er*1000000):,} habis digunakan. {'Angka ini kritis karena melebihi batas aman 80%.' if er > 0.8 else 'Kondisi ini sehat karena di bawah batas aman.'}</li>"
+        if not u_bal.empty:
+            report += f"\n* **Analisis Saldo**: Saldo rata-rata terakhir Rp{u_bal.iloc[-1]['avg_balance']:,.0f}. "
+            report += "Tren menurun terpantau, yang berarti cadangan dana darurat mulai menipis." if len(u_bal) > 1 and u_bal.iloc[-1]['avg_balance'] < u_bal.iloc[-2]['avg_balance'] else "Tren pertumbuhan saldo positif."
         
-        if len(u_bal) > 1:
-            trend = "menurun" if u_bal.iloc[-1]['avg_balance'] < u_bal.iloc[-2]['avg_balance'] else "meningkat"
-            report += f"<li><b>Tren Saldo</b>: Saldo rata-rata Anda terpantau <b>{trend}</b>. Tren ini digunakan bank untuk melihat kemampuan Bapak/Ibu dalam menghadapi kebutuhan mendadak di masa depan.</li>"
-        
-        report += f"</ul>"
+        report += f"\n\n<div class='nbo-box'>**🎯 REKOMENDASI STRATEGIS (NBO): {action}**\n\n"
+        report += f"**Definisi:** {nbo_detail}\n\n"
+        report += f"**Langkah-Langkah Implementasi:**\n"
+        for i, step in enumerate(steps, 1):
+            report += f"{i}. {step}\n"
+        report += f"</div>"
 
-        report += f"<h3 class='section-header'>🎯 REKOMENDASI TINDAKAN (NBO)</h3>"
-        report += f"<p>Sistem merekomendasikan aksi: <b>{action}</b>. <br><i>Mengapa?</i> {nbo_desc}</p>"
-        
-        # Gemini Section
         if client_ai:
             try:
                 tx = u_txn.tail(1)['raw_description'].iloc[0]
-                prompt = f"Advisor Bank Nagari: Nasabah {cid} risiko {risk_lv}, pengeluaran {er:.1%}. Terakhir belanja di {tx}. Beri saran hangat personal (Bapak/Ibu) maks 2 kalimat."
+                prompt = f"Advisor Bank Nagari: Nasabah {cid} risiko {risk_lv}, expense {er:.1%}. Terakhir belanja di {tx}. Beri 1 saran hangat personal (Bapak/Ibu) maks 2 kalimat."
                 resp = client_ai.models.generate_content(model="gemini-1.5-flash", contents=prompt)
-                report += f"<div style='background:#f0f9ff; padding:15px; border-radius:10px; margin-top:10px; border:1px solid #bae6fd;'><b>💡 Pesan Personal Advisor:</b><br>_{resp.text}_</div>"
+                report += f"\n---\n**💡 SARAN VIRTUAL ADVISOR:**\n_{resp.text}_"
             except: pass
-            
-        report += "</div>"
         return report
 
 # --- UI LOGIC ---
-engine = ArchonNarrativeEngine()
+engine = ArchonFinalEngine()
 
 def process(cust_id):
-    res = engine.run_full_pipeline(cust_id)
-    if not res: return "## ❌ ID Tidak Ditemukan", "Coba gunakan C0001 - C0120", None, None
+    res = engine.analyze(cust_id)
+    if not res: return "## ❌ ID Tidak Ditemukan", "Gunakan C0001 - C0120", None, None
     
-    risk_lv, score, er, u_bal, u_txn, exp, inc, action, nbo_desc = res
-    narrative = engine.build_narrative_report(risk_lv, score, er, u_bal, exp, inc, action, nbo_desc, cust_id, u_txn)
+    risk_lv, score, er, u_bal, u_txn, exp, inc, action, nbo_detail, steps, er_s, bt_s, od_s, mp_s = res
+    report = engine.get_report_text(risk_lv, score, er, u_bal, exp, inc, action, nbo_detail, steps, cust_id, u_txn)
     
-    # Graphs with Interpretation
-    color = "#0514DE"
+    # Graphs - CORRECTED LEGEND
     f1 = go.Figure()
-    f1.add_trace(go.Scatter(x=u_bal['month'], y=u_bal['avg_balance'], name='Rata-rata Saldo', line=dict(color='#F7BD87', width=4)))
-    f1.update_layout(title="Kesehatan Pertumbuhan Saldo", template="plotly_white")
-    
-    f2 = go.Figure()
     u_txn['m'] = u_txn['date'].dt.to_period('M').dt.to_timestamp()
     cf = u_txn.groupby(['m', 'transaction_type'])['amount'].sum().unstack().fillna(0)
-    f2.add_trace(go.Bar(x=cf.index, y=cf.get('credit', 0), name='Pemasukan', marker_color='#82C3EB'))
-    f2.add_trace(go.Bar(x=cf.index, y=cf.get('debit', 0), name='Pengeluaran', marker_color='#0514DE'))
-    f2.update_layout(title="Laporan Arus Kas", barmode='group', template='plotly_white')
+    f1.add_trace(go.Bar(x=cf.index, y=cf.get('credit', 0), name='Pemasukan (Inflow)', marker_color='#82C3EB'))
+    f1.add_trace(go.Bar(x=cf.index, y=cf.get('debit', 0), name='Pengeluaran (Outflow)', marker_color='#0514DE'))
+    f1.update_layout(title="Arus Kas Bulanan", barmode='group', template='plotly_white')
 
-    status_color = "#ef4444" if risk_lv == "HIGH" else ("#f59e0b" if risk_lv == "MEDIUM" else "#10b981")
-    status_html = f"""<div style='text-align:center;'><span class='status-pill' style='background:{status_color}'>{risk_lv} RISK</span><br><p style='margin-top:10px;'>Risk Score: <b>{score:.2f}</b></p></div>"""
+    f2 = go.Figure()
+    f2.add_trace(go.Scatter(x=u_bal['month'], y=u_bal['avg_balance'], name='Saldo Rata-rata', line=dict(color='#F7BD87', width=4)))
+    f2.update_layout(title="Tren Pertumbuhan Saldo", template='plotly_white')
+
+    # Sidebar Badges (Brainstorming Result)
+    color = "#ef4444" if risk_lv == "HIGH" else ("#f59e0b" if risk_lv == "MEDIUM" else "#10b981")
+    sidebar_html = f"""
+    <div class='card-left'>
+        <h2 style='color: #0514DE; margin:0;'>Dashboard Ringkasan</h2>
+        <div style='background:{color}; color:white; padding:10px 20px; border-radius:30px; font-weight:bold; display:inline-block; margin:15px 0;'>{risk_lv} RISK</div>
+        
+        <div class='badge-item'><b>Expense Ratio:</b> {er:.1%} {'⚠️' if er > 0.8 else '✅'}</div>
+        <div class='badge-item'><b>Balance Trend:</b> {'🔻 Menurun' if bt_s == 1 else '🔼 Stabil'}</div>
+        <div class='badge-item'><b>Overdraft:</b> {'❌ Pernah' if od_s == 1 else '✅ Tidak'}</div>
+        <div class='badge-item'><b>Credit Status:</b> {'❌ Late' if mp_s == 1 else '✅ On-Time'}</div>
+        
+        <p style='margin-top:20px; font-size:0.85em; color:#666;'>*Parameter dihitung menggunakan bobot resmi perbankan Nagari (Fase 4).</p>
+    </div>
+    """
     
-    return status_html, narrative, f1, f2
+    return sidebar_html, report, f1, f2
 
 with gr.Blocks(css=custom_css) as demo:
     gr.HTML("<div class='nagari-header'><h1>ARCHON-AI</h1></div>")
-    
     with gr.Row():
         with gr.Column(scale=1):
             id_in = gr.Textbox(label="Customer ID", placeholder="C0001")
             btn = gr.Button("ANALYZE CUSTOMER", variant="primary")
             out_status = gr.HTML()
-        
         with gr.Column(scale=2):
             with gr.Tabs():
-                with gr.Tab("📋 Executive Briefing"):
-                    out_report = gr.HTML()
-                with gr.Tab("📈 Visual Analytics"):
-                    gr.Markdown("### Interpretasi Arus Kas\nBatang biru (Pengeluaran) tidak boleh sering melebihi batang muda (Pemasukan).")
+                with gr.Tab("Audit Summary"):
+                    out_report = gr.Markdown(elem_classes="report-card")
+                with gr.Tab("Visual Analytics"):
+                    gr.Markdown("### Interpretasi Arus Kas\n**Batang Tua (Pengeluaran)** sebaiknya tidak lebih tinggi dari **Batang Muda (Pemasukan)**.")
                     plot_cf = gr.Plot()
                     gr.Markdown("---")
-                    gr.Markdown("### Tren Saldo\nGrafik yang naik menunjukkan nasabah memiliki daya tahan terhadap krisis ekonomi.")
+                    gr.Markdown("### Tren Saldo\nMenunjukkan daya tahan nasabah terhadap krisis.")
                     plot_bal = gr.Plot()
 
     btn.click(fn=process, inputs=id_in, outputs=[out_status, out_report, plot_cf, plot_bal])