Update app.py

app.py

@@ -16,7 +16,7 @@ def load_data():
 model_data = load_data()
 movie_dict = model_data['movie_dict'] if model_data else {}
 
-# --- 2. OYUNCU DNA VERİTABANI (Hugging Face Listenle Tam Uyumlu) ---
+# --- 2. OYUNCU DNA VERİTABANI ---
 tum_unlu_verileri = {
     "Sylvester Stallone": {"c": "Male / Erkek", "v": [0.9, 0.2, 0.1, 0.1, 0.1, 0.8]},
     "Robert De Niro": {"c": "Male / Erkek", "v": [0.2, 0.1, 0.1, 0.9, 0.1, 0.8]},
@@ -54,7 +54,7 @@ tum_unlu_verileri = {
 # --- ARAYÜZ AYARLARI ---
 st.set_page_config(page_title="CastMatch AI", layout="wide")
 
-# CSS: Resim alanını sabitleyip titremeyi kesen stil
+# CSS: Resim alanı sabitleme
 st.markdown("""
     <style>
     [data-testid="stImage"] {
@@ -77,7 +77,6 @@ st.sidebar.title("🔍 Control Panel / Kontrol Paneli")
 st.sidebar.markdown("---")
 gender_choice = st.sidebar.radio("1. Select Category / Kategori Seçin:", ["Male / Erkek", "Female / Kadın"])
 
-# Hugging Face ana dizindeki gerçek dosyaları çek
 hf_files = os.listdir(".")
 filtered_names = [name for name in tum_unlu_verileri.keys() if tum_unlu_verileri[name]['c'] == gender_choice]
 
@@ -86,41 +85,40 @@ for n in filtered_names:
     st.sidebar.write(f"• {n}")
 
 # --- ANA EKRAN ---
-st.title("🎬 CastMatch AI: Talent Matching System")
+st.title("🎬 CastMatch AI: Talent Matching System / Yetenek Eşleştirme Sistemi")
 st.markdown("---")
 
 col_actor, col_match = st.columns([1, 2])
 
 with col_actor:
     st.subheader("👤 Pick an Actor / Oyuncu Seç")
-    selected_actor = st.selectbox("Select from list:", ["Choose..."] + filtered_names)
+    # SEÇİM KUTUSU GÜNCELLENDİ
+    selected_actor = st.selectbox("Select from list / Listeden seçin:", ["Choose... / Seçiniz..."] + filtered_names)
     
-    if selected_actor != "Choose...":
+    if selected_actor != "Choose... / Seçiniz...":
         found_path = None
-        # Hugging Face'deki isimlendirme varyasyonlarını kontrol et
-        search_underscore = selected_actor.replace(" ", "_").lower()
-        search_plain = selected_actor.lower()
+        search_target = selected_actor.lower()
         
         for f in hf_files:
-            f_lower = f.lower()
-            if f_lower.endswith(('.jpg', '.png', '.jpeg')):
-                # Sylvester Stallone.png veya Brad_Pitt.png gibi her durumu yakala
-                if search_underscore in f_lower or search_plain in f_lower:
+            if f.lower().endswith(('.jpg', '.png', '.jpeg')):
+                # Akıllı isim eşleştirme (Boşlukları ve alt tireleri denetler)
+                if selected_actor.replace(" ", "_").lower() in f.lower() or selected_actor.replace(" ", " ").lower() in f.lower():
                     found_path = f
                     break
         
         if found_path:
             st.image(found_path, use_container_width=False)
         else:
-            st.warning(f"Resim dosyası eşleşmedi: {selected_actor}")
+            st.warning(f"Image not found / Resim bulunamadı: {selected_actor}")
             st.markdown('<div style="height: 300px;"></div>', unsafe_allow_html=True)
     else:
-        st.markdown('<div style="height: 400px; display: flex; align-items: center; justify-content: center; color: #999; font-style: italic;">Select an actor to view profile</div>', unsafe_allow_html=True)
+        st.markdown('<div style="height: 400px; display: flex; align-items: center; justify-content: center; color: #999; font-style: italic;">Select an actor to view profile / Profil görmek için oyuncu seçin</div>', unsafe_allow_html=True)
 
 with col_match:
-    st.subheader("🎯 Best Career Matches")
+    # BAŞLIK GÜNCELLENDİ
+    st.subheader("🎯 Best Career Matches / En İyi Kariyer Eşleşmeleri")
     
-    if st.button("🚀 Match and Recommend") and selected_actor != "Choose...":
+    if st.button("🚀 Match and Recommend / Eşleştir ve Öner") and selected_actor != "Choose... / Seçiniz...":
         if movie_dict:
             actor_v = tum_unlu_verileri[selected_actor]['v']
             results = []
@@ -132,10 +130,12 @@ with col_match:
             top_matches = sorted(results, key=lambda x: x[1])[:5]
             for i, (film, score) in enumerate(top_matches, 1):
                 pct = max(0, min(100, round((1 - score) * 100, 1)))
-                st.success(f"**{i}. {film}** (%{pct})")
+                st.success(f"**{i}. {film}**")
+                st.write(f"Match Score / Uyum Skoru: **%{pct}**")
                 st.progress(pct / 100)
         else:
-            st.error("Model file missing!")
+            st.error("Model file missing! / Model dosyası eksik!")
 
+# --- ALT BİLGİ ---
 st.markdown("---")
 st.info("**How it works? / Nasıl çalışır?**: This AI analyzes career vectors based on available local assets. / Bu yapay zeka, mevcut yerel varlıklara (resimlere) dayanarak kariyer vektörlerini analiz eder.")