Update app.py

app.py

@@ -12,24 +12,23 @@ from dotenv import load_dotenv
 from supabase import create_client
 import os
 
+# --- Supabase & Gemini ---
+load_dotenv()
 SUPABASE_URL = os.getenv("SUPABASE_URL")
 SUPABASE_KEY = os.getenv("SBASEKEY")
-supabase = create_client(SUPABASE_URL, SUPABASE_KEY)
-
-# --- Load API Key dari .env ---
-load_dotenv()
 API_KEY = os.getenv("GEMINI_API_KEY")
+
+supabase = create_client(SUPABASE_URL, SUPABASE_KEY)
 genai.configure(api_key=API_KEY)
 
-# --- Load Data dari database ---
+# --- Load data dari Supabase ---
 def fetch_data_from_supabase():
     response = supabase.table("Maps").select("*").execute()
     return pd.DataFrame(response.data)
 
-# Load data dari Supabase
 df = fetch_data_from_supabase()
 
-# --- Fungsi Ekstraksi Kata Kunci ---
+# --- Ekstraksi Kata Kunci ---
 def extract_keywords(user_input):
     prompt = f"""
     Ekstrak 3–7 kata kunci penting dari deskripsi wisata berikut:
@@ -46,7 +45,7 @@ def extract_keywords(user_input):
     except Exception as e:
         return [f"Error: {e}"]
 
-# --- Fungsi Lokasi ---
+# --- Lokasi ---
 def get_coordinates_from_location(location_name):
     try:
         geolocator = Nominatim(user_agent="geoapi")
@@ -63,7 +62,20 @@ def get_location_name_from_coordinates(lat, lon):
     except GeocoderTimedOut:
         return "Tidak ditemukan"
 
-# --- Rekomendasi Tempat Wisata ---
+# --- Enhancement untuk deskripsi singkat ---
+def enhance_description_with_gemini(short_desc):
+    prompt = f"""
+    Deskripsi berikut terlalu singkat: "{short_desc}"
+    Tolong kembangkan menjadi paragraf singkat (2–3 kalimat) yang menggambarkan keinginan wisata pengguna secara lebih lengkap.
+    Contohnya: sebutkan suasana, aktivitas, atau lokasi ideal.
+    """
+    try:
+        response = genai.GenerativeModel("gemini-1.5-flash").generate_content(prompt)
+        return response.text.strip()
+    except Exception as e:
+        return short_desc
+
+# --- TF-IDF dan Cosine Similarity ---
 def prepare_and_recommend(df, user_description):
     tfidf = TfidfVectorizer()
     tfidf_matrix = tfidf.fit_transform(df['deskripsi'].astype(str).tolist() + [user_description])
@@ -71,6 +83,7 @@ def prepare_and_recommend(df, user_description):
     df['similarity'] = similarity
     return df.sort_values(by='similarity', ascending=False).head(10)
 
+# --- Jarak Lokasi ---
 def sort_by_nearest_location(df, user_lat, user_lon):
     df['distance_km'] = df.apply(
         lambda row: geodesic((user_lat, user_lon), (row['latitude'], row['longitude'])).km,
@@ -79,68 +92,57 @@ def sort_by_nearest_location(df, user_lat, user_lon):
     df['distance_km'] = df['distance_km'].round(2)
     return df.sort_values(by='distance_km')
 
-# --- Enhancement Deskripsi Singkat ---
-def enhance_description_with_gemini(short_desc):
-    prompt = f"""
-    Deskripsi berikut terlalu singkat: "{short_desc}"
-    Tolong kembangkan menjadi paragraf singkat (2–3 kalimat) yang menggambarkan keinginan wisata pengguna secara lebih lengkap.
-    Contohnya: sebutkan suasana, aktivitas, atau lokasi ideal.
-    """
-    try:
-        response = genai.GenerativeModel("gemini-1.5-flash").generate_content(prompt)
-        return response.text.strip()
-    except Exception as e:
-        return short_desc  # fallback ke deskripsi asli jika gagal
-
-# --- Fungsi Utama Gradio ---
+# --- Fungsi Utama ---
 def wisata_rekomendasi(deskripsi, lokasi):
     if df.empty:
-        return "Data tidak tersedia.", pd.DataFrame([["Data tidak tersedia", "", ""]], columns=["id","nama","alamat", "distance_km", "deskripsi","harga","rating","total_ulasan","gambar"])
+        return "Data tidak tersedia.", pd.DataFrame([["Data tidak tersedia"]], columns=["nama"])
 
-    # --- Enhancement jika deskripsi terlalu singkat ---
     if len(deskripsi.strip().split()) < 3 or len(deskripsi.strip()) < 20:
         deskripsi = enhance_description_with_gemini(deskripsi)
 
-    # --- Ekstraksi kata kunci ---
-    keywords = extract_keywords(deskripsi)
-    if "Error:" in str(keywords):
-        return f"Kata kunci gagal diambil: {keywords[0]}", pd.DataFrame([[keywords[0], "", ""]], columns=["id","nama","alamat", "distance_km", "deskripsi","harga","rating","total_ulasan","gambar"])
-    
-    # --- Gabungkan dengan lokasi pengguna ---
-    user_description_joined = " ".join(keywords + lokasi.lower().split())
-
-    # --- Geolokasi pengguna ---
+    # Lokasi → Koordinat
     lat, lon = get_coordinates_from_location(lokasi)
     if lat is None or lon is None:
-        return "Lokasi tidak ditemukan.", pd.DataFrame([["Lokasi tidak ditemukan", "", ""]], columns=["id","nama","alamat", "distance_km", "deskripsi","harga","rating","total_ulasan","gambar"])
+        return "Lokasi tidak ditemukan.", pd.DataFrame([["Lokasi tidak ditemukan"]], columns=["nama"])
 
-    # --- Rekomendasi berdasarkan similarity ---
-    top_place = prepare_and_recommend(df.copy(), user_description_joined)
+    # Tambahkan lokasi ke deskripsi
+    deskripsi_lengkap = f"{deskripsi} di sekitar {lokasi}"
 
-    # --- Filter tempat dengan total ulasan > 10 ---
-    top_place = top_place[top_place['total_ulasan'] > 10]
+    keywords = extract_keywords(deskripsi_lengkap)
+    if "Error:" in str(keywords):
+        return f"Kata kunci gagal diambil: {keywords[0]}", pd.DataFrame([[keywords[0]]], columns=["nama"])
 
-    # --- Urutkan berdasarkan jarak ---
+    user_description_joined = " ".join(keywords)
+
+    top_place = prepare_and_recommend(df.copy(), user_description_joined)
+    top_place = top_place[top_place['total_ulasan'] > 10]
     sorted_place = sort_by_nearest_location(top_place, lat, lon)
 
-    # --- Validasi gambar ---
     sorted_place = sorted_place[sorted_place["gambar"].apply(lambda x: isinstance(x, str) and x.startswith("https"))]
 
-    return f"Kata kunci: {', '.join(keywords)}", sorted_place[["id","nama","alamat", "distance_km", "deskripsi","harga","rating","total_ulasan","gambar"]]
+    # Urutkan berdasarkan similarity tertinggi dan tampilkan kolom similarity
+    sorted_place = sorted_place.sort_values(by='similarity', ascending=False)
+
+    return f"Kata kunci: {', '.join(keywords)}", sorted_place[[
+        "id", "nama", "alamat", "distance_km", "deskripsi", "harga", "rating", "total_ulasan", "gambar", "similarity"
+    ]]
 
-# --- UI Gradio ---
+# --- Gradio UI ---
 demo = gr.Interface(
     fn=wisata_rekomendasi,
     inputs=[
         gr.Textbox(label="Deskripsi Wisata yang Anda Inginkan"),
-        gr.Textbox(label="Lokasi Anda (Contoh: Cilacap, jawa tengah, Indonesia)"),
+        gr.Textbox(label="Lokasi Anda (Contoh: Cilacap, Jawa Tengah, Indonesia)"),
     ],
     outputs=[
         gr.Textbox(label="Kata Kunci yang Diekstrak"),
-        gr.Dataframe(headers=["id","nama","alamat", "distance_km", "deskripsi","harga","rating","total_ulasan","gambar"], label="Rekomendasi Tempat Wisata")
+        gr.Dataframe(
+            headers=["id", "nama", "alamat", "distance_km", "deskripsi", "harga", "rating", "total_ulasan", "gambar", "similarity"],
+            label="Rekomendasi Tempat Wisata"
+        )
     ],
     title="Sistem Rekomendasi Wisata",
-    description="Masukkan deskripsi dan lokasi, lalu dapatkan rekomendasi tempat wisata terdekat"
+    description="Masukkan deskripsi dan lokasi, lalu dapatkan rekomendasi tempat wisata terdekat beserta skor kecocokannya."
 )
 
 demo.launch()