requirements

app.py

@@ -4,130 +4,125 @@ import numpy as np
 import gradio as gr
 import plotly.graph_objects as go
 import google.generativeai as genai
+from transformers import pipeline
 
-# --- KONFIGURASI GEMINI (Ganti dari Mistral ke Gemini) ---
+# --- KONFIGURASI AI ---
+# Pastikan GOOGLE_API_KEY sudah ada di Secrets Hugging Face
 GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
 genai.configure(api_key=GOOGLE_API_KEY)
-gemini_model = genai.GenerativeModel('gemini-1.5-flash')
+gemini = genai.GenerativeModel('gemini-1.5-flash')
 
-# --- CSS CUSTOM: STYLE BANK NAGARI ---
+# --- STYLE CSS BANK NAGARI (Marun & Emas) ---
 custom_css = """
-@import url('https://fonts.googleapis.com/css2?family=Roboto:wght@400;700&display=swap');
-body { font-family: 'Roboto', sans-serif; background-color: #f4f4f4; }
-.gradio-container { max-width: 1250px !important; }
-.nagari-header { background-color: #800000; color: white; padding: 20px; border-radius: 10px 10px 0 0; border-bottom: 4px solid #FFD700; }
-.risk-card { padding: 25px; border-radius: 12px; background: white; box-shadow: 0 4px 6px rgba(0,0,0,0.1); border-top: 5px solid #800000; }
-.risk-high { border-left: 10px solid #d32f2f; }
-.risk-medium { border-left: 10px solid #f9a825; }
-.risk-low { border-left: 10px solid #2e7d32; }
+@import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;700&display=swap');
+body { font-family: 'Inter', sans-serif; background-color: #f0f2f5; }
+.gradio-container { max-width: 1200px !important; }
+.nagari-card { 
+    background: white; 
+    border-radius: 15px; 
+    padding: 25px; 
+    box-shadow: 0 10px 25px rgba(0,0,0,0.05); 
+    border-top: 6px solid #800000;
+}
+.header-box { 
+    background: linear-gradient(135deg, #800000 0%, #a52a2a 100%); 
+    color: white; 
+    padding: 30px; 
+    border-radius: 15px; 
+    margin-bottom: 20px;
+    border-bottom: 5px solid #FFD700;
+}
 """
 
-class ArchonNagariEngine:
+class ArchonProductionEngine:
     def __init__(self):
         self.load_data()
+        # Pilar 1: BERT Classifier (Fase 2)
+        try:
+            self.classifier = pipeline("text-classification", model="archon_v1", tokenizer="archon_v1")
+        except:
+            self.classifier = None
 
     def load_data(self):
-        # Fase 1: Foundation (Cek error pada data mentah)
+        # Fase 1: Data Foundation (Fixing C0014 error with fillna)
         self.df_txn = pd.read_csv('transactions.csv', parse_dates=['date']).fillna("")
         self.df_cust = pd.read_csv('customers.csv').fillna(0)
         self.df_bal = pd.read_csv('balances_revised.csv', parse_dates=['month']).fillna(0)
         self.df_rep = pd.read_csv('repayments_revised.csv', parse_dates=['due_date']).fillna("on_time")
 
-    def run_analysis(self, customer_id):
-        # Validasi Keberadaan Data
+    def analyze_customer(self, customer_id):
+        # Filter & Validate
         u_txn = self.df_txn[self.df_txn['customer_id'] == customer_id].copy()
         u_bal = self.df_bal[self.df_bal['customer_id'] == customer_id].sort_values('month')
         u_rep = self.df_rep[self.df_rep['customer_id'] == customer_id]
         
         if u_txn.empty or u_bal.empty:
-            return None
+            return None, "ID Nasabah tidak ditemukan.", None, None
 
-        # --- FASE 4: RISK SCORING (WEIGHTED 30/20/20/20/10) ---
+        # --- FASE 4: RISK SCORING (WEIGHTED) ---
         income = u_txn[u_txn['transaction_type'] == 'credit']['amount'].sum()
         expense = u_txn[u_txn['transaction_type'] == 'debit']['amount'].sum()
-        er = expense / income if income > 0 else 1.0
+        er = expense / income if income > 0 else 1.2
         
-        # Scoring Rules (Fase 4)
+        # Scoring Logic
         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
-        vol_s = 0.5 # Placeholder Volatility
-        
-        final_score = (0.3 * er_s) + (0.2 * bt_s) + (0.2 * od_s) + (0.2 * mp_s) + (0.1 * vol_s)
-        risk_lv = "HIGH" if final_score >= 0.7 else ("MEDIUM" if final_score >= 0.4 else "LOW")
         
-        return risk_lv, final_score, er, u_bal, u_txn
+        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")
 
-    def get_gemini_advice(self, risk_lv, er, cust_id, u_txn):
-        # FASE 5: NBO DENGAN GEMINI (Sangat Natural & Tidak Template)
-        tx_history = u_txn.tail(5)['raw_description'].tolist()
-        context = f"Nasabah {cust_id} memiliki risiko {risk_lv}, rasio belanja {er:.1%}. Transaksi terakhir: {', '.join(tx_history)}."
-        
+        # --- FASE 6: RINGKASAN LAPORAN ---
+        summary = f"### 📊 ANALISIS RISIKO: {risk_lv}\n"
+        summary += f"- **Rasio Pengeluaran**: {er:.1%}\n"
+        summary += f"- **Kesehatan Saldo**: {'⚠️ Tren Menurun' if bt_s == 1 else '✅ Tren Stabil'}\n"
+        summary += f"- **Status Kredit**: {'⚠️ Ada Keterlambatan' if mp_s == 1 else '✅ Lancar'}"
+
+        # --- FASE 5: NBO (DYNAMIC GEMINI) ---
+        recent_desc = ", ".join(u_txn.tail(3)['raw_description'].tolist())
         prompt = f"""
-        Tugas: Sebagai Virtual Advisor Bank Nagari yang bijak.
-        Data: {context}
-        Instruksi: Berikan saran finansial yang personal, hangat, dan solutif dalam Bahasa Indonesia. 
-        Gunakan sapaan 'Bapak/Ibu'. Jangan terlihat seperti bot. Fokus pada peningkatan ketahanan finansial (Resilience).
-        Maksimal 3 kalimat.
+        Bertindaklah sebagai Senior Advisor Bank Nagari. Nasabah {customer_id} memiliki risiko {risk_lv}.
+        Rasio belanja terhadap gaji: {er:.2%}. Transaksi terakhir: {recent_desc}.
+        Berikan saran finansial yang SANGAT spesifik (bukan template), hangat, dan gunakan sapaan 'Bapak/Ibu'.
+        Berikan 1 solusi produk bank (tabungan/investasi/kredit) yang relevan. Maksimal 3 kalimat.
         """
         try:
-            response = gemini_model.generate_content(prompt)
-            return response.text
+            advice = gemini.generate_content(prompt).text
         except:
-            return "Kami menyarankan Bapak/Ibu untuk meninjau kembali pos pengeluaran bulan ini agar saldo tetap terjaga sehat."
+            advice = "Mohon maaf, layanan konsultasi AI sedang sibuk. Silakan hubungi Relationship Manager Anda."
 
-    def create_viz(self, u_bal, u_txn):
-        # FASE 6: VISUALIZATION (BANK NAGARI STYLE)
-        # 1. Trend Saldo
-        fig_bal = go.Figure()
-        fig_bal.add_trace(go.Scatter(x=u_bal['month'], y=u_bal['avg_balance'], name='Rata-rata Saldo', line=dict(color='#800000', width=4)))
-        fig_bal.add_trace(go.Bar(x=u_bal['month'], y=u_bal['min_balance'], name='Saldo Minimum', marker_color='#FFD700', opacity=0.5))
-        fig_bal.update_layout(title="Laporan Tren Saldo Bulanan", template="plotly_white", legend=dict(orientation="h"))
-
-        # 2. Income vs Expense
+        # --- FASE 6: VISUALISASI ---
+        # Plot 1: Income vs Expense
         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)
-        fig_cf = go.Figure()
-        fig_cf.add_trace(go.Bar(x=cf.index, y=cf.get('credit', 0), name='Pemasukan', marker_color='#2e7d32'))
-        fig_cf.add_trace(go.Bar(x=cf.index, y=cf.get('debit', 0), name='Pengeluaran', marker_color='#800000'))
-        fig_cf.update_layout(title="Arus Kas Pemasukan vs Pengeluaran", barmode='group', template="plotly_white")
+        monthly_cf = u_txn.groupby(['m', 'transaction_type'])['amount'].sum().unstack().fillna(0)
         
-        return fig_bal, fig_cf
-
-# --- INTERFACE ---
-engine = ArchonNagariEngine()
-
-def run_archon(cust_id):
-    res = engine.run_analysis(cust_id)
-    if not res:
-        return "### ⚠️ Data Tidak Ditemukan", "ID tidak terdaftar di sistem.", None, None
-    
-    risk_lv, score, er, u_bal, u_txn = res
-    advice = engine.get_gemini_advice(risk_lv, er, cust_id, u_txn)
-    p_bal, p_cf = engine.create_viz(u_bal, u_txn)
-    
-    status_cls = "risk-high" if risk_lv == "HIGH" else ("risk-medium" if risk_lv == "MEDIUM" else "risk-low")
-    
-    report_html = f"""
-    <div class="risk-card {status_cls}">
-        <h2 style="color: #800000; margin-top:0;">📋 Ringkasan Risiko: {risk_lv}</h2>
-        <p><b>Risk Score:</b> {score:.2f} | <b>Expense Ratio:</b> {er:.1%}</p>
-        <p style="font-size: 0.9em; color: #666;">Berdasarkan bobot parameter Fase 4: Pengeluaran, Saldo, dan Riwayat Cicilan.</p>
-    </div>
-    """
-    return report_html, advice, p_bal, p_cf
+        fig1 = go.Figure()
+        fig1.add_trace(go.Bar(x=monthly_cf.index, y=monthly_cf.get('credit', 0), name='Income', marker_color='#2e7d32'))
+        fig1.add_trace(go.Bar(x=monthly_cf.index, y=monthly_cf.get('debit', 0), name='Expense', marker_color='#800000'))
+        fig1.update_layout(title="Inflow vs Outflow", barmode='group', template='plotly_white')
+
+        # Plot 2: Balance Trend
+        fig2 = go.Figure()
+        fig2.add_trace(go.Scatter(x=u_bal['month'], y=u_bal['avg_balance'], mode='lines+markers', name='Avg Balance', line=dict(color='#800000', width=4)))
+        fig2.update_layout(title="Tren Saldo Rata-rata", template='plotly_white')
+
+        return summary, advice, fig1, fig2
+
+# --- UI DASHBOARD ---
+engine = ArchonProductionEngine()
 
 with gr.Blocks(css=custom_css) as demo:
-    with gr.Div(elem_classes="nagari-header"):
-        gr.Markdown("# ARCHON-AI: FINANCIAL RESILIENCE ENGINE")
-        gr.Markdown("Pusat Intelijen Manajemen Risiko & Perilaku Nasabah")
+    with gr.Div(elem_id="header", elem_classes="header-box"):
+        gr.Markdown("# 🛡️ ARCHON-AI EXECUTIVE DASHBOARD")
+        gr.Markdown("Financial Resilience Engine | Bank Nagari Edition")
 
-    with gr.Row(variant="panel"):
+    with gr.Row():
         with gr.Column(scale=1):
-            id_input = gr.Textbox(label="Customer ID", placeholder="e.g., C0014")
-            btn = gr.Button("PROSES ANALISIS", variant="primary")
-            out_report = gr.HTML()
+            with gr.Div(elem_classes="nagari-card"):
+                id_in = gr.Textbox(label="Customer ID", placeholder="C0001 - C0120")
+                btn = gr.Button("PROSES ANALISIS", variant="primary")
+                out_sum = gr.Markdown()
         
         with gr.Column(scale=2):
             with gr.Tabs():
@@ -135,9 +130,10 @@ with gr.Blocks(css=custom_css) as demo:
                     plot_cf = gr.Plot()
                 with gr.TabItem("Tren Saldo"):
                     plot_bal = gr.Plot()
+                    
+    with gr.Div(elem_classes="nagari-card", style="margin-top: 20px;"):
+        out_adv = gr.Textbox(label="Virtual Advisor (Gemini Generative AI)", lines=4)
 
-    out_advice = gr.Textbox(label="Saran AI Virtual Advisor (Powered by Gemini)", lines=4)
-
-    btn.click(fn=run_archon, inputs=id_input, outputs=[out_report, out_advice, plot_bal, plot_cf])
+    btn.click(fn=engine.analyze_customer, inputs=id_in, outputs=[out_sum, out_adv, plot_cf, plot_bal])
 
 demo.launch()

requirements.txt

@@ -1,9 +1,7 @@
-transformers
-torch
-huggingface_hub
+google-generativeai
 gradio
 pandas
 numpy
-accelerate
 plotly
-google-generativeai
+transformers
+torch