Update sentiment_app.py

sentiment_app.py

@@ -12,8 +12,16 @@ MODEL_NAME = "w11wo/indonesian-roberta-base-sentiment-classifier"
 device = 0 if torch.cuda.is_available() else -1
 sentiment_pipeline = pipeline("sentiment-analysis", model=MODEL_NAME, device=device)
 
+# --- DATABASE SEDERHANA (In-Memory) ---
 all_messages = [] 
 
+# Mapping Label untuk Tampilan UI
+label_map = {
+    "POSITIVE": "Pujian/Apresiasi", 
+    "NEGATIVE": "Keluhan/Kritik", 
+    "NEUTRAL": "Pertanyaan/Info"
+}
+
 def process_submission(text):
     if not text or text.strip() == "":
         return "⚠️ Mohon isi komentar Anda terlebih dahulu.", gr.update()
@@ -22,102 +30,86 @@ def process_submission(text):
     result = sentiment_pipeline(text)[0]
     label = result['label'].upper()
     
-    # 2. Simpan ke "Database"
+    # 2. Simpan ke Database Lokal
     new_entry = {
-        "Waktu": datetime.now().strftime("%H:%M:%S"),
+        "Waktu": datetime.now().strftime("%Y-%m-%d %H:%M"),
         "Pesan": text.strip(),
         "Sentimen": label
     }
     all_messages.append(new_entry)
     
     # 3. Respons untuk User
-    thanks_msg = f"""
-    ### 🙏 Terima kasih atas pesan Anda!
-    Masukan Anda sangat berharga bagi kami di Posko. Pesan Anda telah kami terima dan akan segera diproses oleh tim admin.
-    """
-    
-    return thanks_msg, gr.update(value="") # Clear input box
+    thanks_msg = "### 🙏 Terima kasih atas pesan Anda!\nMasukan Anda telah kami terima dan akan segera ditinjau oleh tim admin posko."
+    return thanks_msg, gr.update(value="")
 
-def get_admin_dashboard():
+def get_admin_dashboard(filter_val):
     if not all_messages:
-        return None, "Belum ada data pesan yang masuk."
+        return None, pd.DataFrame(columns=["Pesan", "Sentimen", "Jumlah"]), "Belum ada data."
     
-    df = pd.DataFrame(all_messages)
+    df_all = pd.DataFrame(all_messages)
     
-    # --- VISUALISASI 1: Grafik Jenis Pesan Terbanyak ---
+    # --- LOGIKA FILTER ---
+    if filter_val != "SEMUA":
+        # Balik mapping untuk filter data asli
+        rev_map = {v: k for k, v in label_map.items()}
+        target = rev_map.get(filter_val)
+        df_filtered = df_all[df_all['Sentimen'] == target]
+    else:
+        df_filtered = df_all
+
+    if df_filtered.empty:
+        return None, pd.DataFrame(columns=["Pesan", "Sentimen", "Jumlah"]), f"Tidak ada data untuk kategori: {filter_val}"
+
+    # --- VISUALISASI TOTAL ---
     fig, ax = plt.subplots(figsize=(8, 5))
     color_map = {"POSITIVE": "#4CAF50", "NEGATIVE": "#F44336", "NEUTRAL": "#FFC107"}
-    label_map = {"POSITIVE": "Pujian/Apresiasi", "NEGATIVE": "Keluhan/Kritik", "NEUTRAL": "Pertanyaan/Info"}
-    
-    counts = df['Sentimen'].value_counts()
+    counts = df_all['Sentimen'].value_counts()
     counts.index = [label_map.get(i, i) for i in counts.index]
     
-    sns.barplot(x=counts.index, y=counts.values, palette=[color_map.get(i.split('/')[0].upper(), "#999999") for i in counts.index], ax=ax)
-    ax.set_title("Distribusi Jenis Pesan di Posko", fontsize=14, fontweight='bold')
-    ax.set_ylabel("Jumlah Pesan")
-    
-    # --- TABEL 2: Top 10 Pesan Terbanyak (Informasi Serupa) ---
-    # Kita mengelompokkan pesan yang mirip atau identik
-    counter = collections.Counter([m['Pesan'].lower() for m in all_messages])
-    top_10 = counter.most_common(10)
+    sns.barplot(x=counts.index, y=counts.values, palette="viridis", ax=ax)
+    ax.set_title("Proporsi Pesan Masuk (Total)", fontsize=12, fontweight='bold')
     
-    df_top = pd.DataFrame(top_10, columns=["Isi Pesan", "Jumlah Orang"])
+    # --- TABEL TOP 10 DENGAN KOLOM SENTIMEN ---
+    top_df = df_filtered.groupby(['Pesan', 'Sentimen']).size().reset_index(name='Jumlah')
+    top_df = top_df.sort_values(by='Jumlah', ascending=False).head(10)
+    top_df['Sentimen'] = top_df['Sentimen'].map(label_map) # Percantik label di tabel
     
-    return fig, df_top
+    return fig, top_df, f"Menampilkan {len(df_filtered)} pesan ({filter_val})"
 
 # --- INTERFACE GRADIO ---
-with gr.Blocks(theme=gr.themes.Soft(primary_hue="emerald"), title="PoskoLog - Sistem Aspirasi Pengungsi") as demo:
-    gr.Markdown("""
-    # 📦 PoskoLog: Suara Pengungsi
-    Selamat datang di layanan aspirasi digital posko. Silakan sampaikan keluhan, kebutuhan, atau pertanyaan Anda.
-    """)
+with gr.Blocks(theme=gr.themes.Soft(primary_hue="emerald"), title="PoskoLog Dashboard") as demo:
+    gr.Markdown("# 📦 PoskoLog: Suara Pengungsi")
     
     with gr.Tabs():
-        # --- TAB USER: FORM KOMENTAR ---
+        # TAB USER
         with gr.Tab("📝 Sampaikan Pesan"):
             with gr.Column(variant="panel"):
-                gr.Markdown("### Formulir Aspirasi Pengungsi")
-                user_input = gr.Textbox(
-                    label="Komentar / Masukan Anda", 
-                    placeholder="Tuliskan kebutuhan atau keluhan Anda di sini (Contoh: Air bersih habis di tenda C)...",
-                    lines=4
-                )
+                user_input = gr.Textbox(label="Komentar Anda", placeholder="Tulis masukan di sini...", lines=4)
                 submit_btn = gr.Button("Kirim Pesan", variant="primary")
-                
-                # Output area untuk ucapan terima kasih
                 user_feedback = gr.Markdown("")
-                
-            gr.Markdown("""
-            ---
-            *Catatan: Pesan Anda akan dianalisis secara otomatis untuk memprioritaskan bantuan yang paling mendesak.*
-            """)
 
-        # --- TAB ADMIN: DASHBOARD MONITORING ---
-        with gr.Tab("📊 Dashboard Admin (Real-time)"):
-            gr.Markdown("### Ringkasan Informasi Posko")
-            refresh_btn = gr.Button("🔄 Perbarui Data Dashboard", variant="secondary")
+        # TAB ADMIN
+        with gr.Tab("📊 Dashboard Admin"):
+            with gr.Row():
+                sentiment_filter = gr.Dropdown(
+                    choices=["SEMUA"] + list(label_map.values()), 
+                    value="SEMUA", 
+                    label="Filter Sentimen"
+                )
+                refresh_btn = gr.Button("🔄 Refresh & Filter", variant="secondary")
             
             with gr.Row():
                 with gr.Column():
-                    plot_output = gr.Plot(label="Grafik Sentimen")
+                    plot_output = gr.Plot(label="Grafik Distribusi")
                 with gr.Column():
-                    gr.Markdown("#### 📈 Top 10 Masukan Terbanyak")
-                    table_output = gr.Dataframe(
-                        headers=["Isi Pesan", "Jumlah Orang"],
-                        interactive=False
-                    )
+                    gr.Markdown("#### 📈 Top 10 Pesan Berdasarkan Filter")
+                    table_output = gr.Dataframe(headers=["Pesan", "Sentimen", "Jumlah"], interactive=False)
+            
+            status_txt = gr.Markdown("")
 
-    # Logic Interaksi
-    submit_btn.click(
-        fn=process_submission,
-        inputs=user_input,
-        outputs=[user_feedback, user_input]
-    )
-    
-    refresh_btn.click(
-        fn=get_admin_dashboard,
-        outputs=[plot_output, table_output]
-    )
+    # Binding Events
+    submit_btn.click(fn=process_submission, inputs=user_input, outputs=[user_feedback, user_input])
+    refresh_btn.click(fn=get_admin_dashboard, inputs=sentiment_filter, outputs=[plot_output, table_output, status_txt])
 
 if __name__ == "__main__":
     demo.launch(server_name="0.0.0.0", server_port=7860)