Update app.py

app.py

@@ -1,105 +1,105 @@
-import gradio as gr
-import os
-import tempfile
-import time
-from facecomparison_multi_resume import DeepfakeDetector
-from PIL import Image
-
-# ===================================================================
-# 1. MENGAMBIL KUNCI API DARI ENVIRONMENT VARIABLES (SECRETS)
-#    Nama-nama ini harus sama persis dengan yang Anda set di Hugging Face Secrets!
-# ===================================================================
-
-API_KEYS = {
-    "qwen": os.environ.get("OPENROUTER_API_KEY_QWEN"),
-    "gpt": os.environ.get("OPENROUTER_API_KEY_GPT"),
-    "gemini": os.environ.get("OPENROUTER_API_KEY_GEMINI"),
-    "llama": os.environ.get("OPENROUTER_API_KEY_LLAMA"),
-    "cohere": os.environ.get("OPENROUTER_API_KEY_COHERE"),
-}
-
-MODEL_NAMES = ["qwen", "gpt", "gemini", "llama", "cohere"]
-
-# ===================================================================
-# 2. FUNGSI UTAMA UNTUK ANALISIS SATU GAMBAR
-# ===================================================================
-
-def analyze_image_with_llms(image_pil):
-    """
-    Menerima gambar PIL, memanggil 5 LLM secara berurutan, dan mengembalikan hasilnya.
-    """
-    if image_pil is None:
-        return "N/A", "N/A", "N/A", "N/A", "N/A"
-
-    # Simpan gambar yang diunggah sementara
-    with tempfile.NamedTemporaryFile(suffix=".jpg", delete=False) as tmp_file:
-        # Gunakan mode RGB untuk kompatibilitas yang lebih baik
-        image_pil.convert("RGB").save(tmp_file.name, "JPEG", quality=90)
-        temp_path = tmp_file.name
-
-    all_results = {}
-    
-    for model_name in MODEL_NAMES:
-        api_key = API_KEYS.get(model_name)
-        
-        if not api_key:
-            all_results[model_name] = f"❌ Key Missing"
-            continue
-
-        try:
-            # Inisialisasi Detektor
-            detector = DeepfakeDetector(
-                api_key=api_key,
-                model_name=model_name,
-                use_face_detector=True # Tetap gunakan cropping RetinaFace
-            )
-            
-            # Panggil fungsi deteksi inti
-            result, _, _ = detector.detect_deepfake_llm(temp_path)
-            
-            # Ubah output yang ambigu menjadi 'ERROR' untuk tampilan UI yang bersih
-            if result == "UNKNOWN" or result == "ERROR":
-                 all_results[model_name] = f"⚠️ LLM Gagal Tebak"
-            else:
-                 all_results[model_name] = result
-            
-        except Exception as e:
-            all_results[model_name] = f"❌ API Error: {str(e)[:50]}"
-
-        # Tambahkan delay untuk menghindari Rate Limit OpenRouter
-        time.sleep(1.5) 
-
-    # Bersihkan file sementara
-    os.unlink(temp_path)
-
-    # Kembalikan hasil dalam urutan yang benar
-    return (
-        all_results.get("qwen", "Error"),
-        all_results.get("gpt", "Error"),
-        all_results.get("gemini", "Error"),
-        all_results.get("llama", "Error"),
-        all_results.get("cohere", "Error"),
-    )
-
-# ===================================================================
-# 3. INTERFACE GRADIOL
-# ===================================================================
-
-iface = gr.Interface(
-    fn=analyze_image_with_llms,
-    inputs=gr.Image(type="pil", label="🖼️ Upload Wajah untuk Analisis Deepfake"),
-    outputs=[
-        gr.Textbox(label="1. Qwen Prediction", type="text"),
-        gr.Textbox(label="2. GPT-4o Prediction", type="text"),
-        gr.Textbox(label="3. Gemini 2.5 Flash Prediction", type="text"),
-        gr.Textbox(label="4. Llama 3.2 Vision Prediction", type="text"),
-        gr.Textbox(label="5. Cohere Command R+ Prediction", type="text")
-    ],
-    title="🔬 Perbandingan LLM Multimodal untuk Deteksi Deepfake Wajah",
-    description="Unggah gambar wajah. 5 LLM Multimodal (via OpenRouter) akan menganalisis dan menebak: **REAL** atau **FAKE**.",
-    allow_flagging="never",
-    theme=gr.themes.Soft()
-)
-
-if __name__ == "__main__":
+import gradio as gr
+import os
+import tempfile
+import time
+from facecomparison_multi_resume import DeepfakeDetector
+from PIL import Image
+
+# ===================================================================
+# 1. MENGAMBIL KUNCI API DARI ENVIRONMENT VARIABLES (SECRETS)
+#    Nama-nama ini harus sama persis dengan yang Anda set di Hugging Face Secrets!
+# ===================================================================
+
+API_KEYS = {
+    "qwen": os.environ.get("OPENROUTER_API_KEY_QWEN"),
+    "gpt": os.environ.get("OPENROUTER_API_KEY_GPT"),
+    "gemini": os.environ.get("OPENROUTER_API_KEY_GEMINI"),
+    "llama": os.environ.get("OPENROUTER_API_KEY_LLAMA"),
+    "cohere": os.environ.get("OPENROUTER_API_KEY_COHERE"),
+}
+
+MODEL_NAMES = ["qwen", "gpt", "gemini", "llama", "cohere"]
+
+# ===================================================================
+# 2. FUNGSI UTAMA UNTUK ANALISIS SATU GAMBAR
+# ===================================================================
+
+def analyze_image_with_llms(image_pil):
+    """
+    Menerima gambar PIL, memanggil 5 LLM secara berurutan, dan mengembalikan hasilnya.
+    """
+    if image_pil is None:
+        return "N/A", "N/A", "N/A", "N/A", "N/A"
+
+    # Simpan gambar yang diunggah sementara
+    with tempfile.NamedTemporaryFile(suffix=".jpg", delete=False) as tmp_file:
+        # Gunakan mode RGB untuk kompatibilitas yang lebih baik
+        image_pil.convert("RGB").save(tmp_file.name, "JPEG", quality=90)
+        temp_path = tmp_file.name
+
+    all_results = {}
+    
+    for model_name in MODEL_NAMES:
+        api_key = API_KEYS.get(model_name)
+        
+        if not api_key:
+            all_results[model_name] = f"❌ Key Missing"
+            continue
+
+        try:
+            # Inisialisasi Detektor
+            detector = DeepfakeDetector(
+                api_key=api_key,
+                model_name=model_name,
+                use_face_detector=True # Tetap gunakan cropping RetinaFace
+            )
+            
+            # Panggil fungsi deteksi inti
+            result, _, _ = detector.detect_deepfake_llm(temp_path)
+            
+            # Ubah output yang ambigu menjadi 'ERROR' untuk tampilan UI yang bersih
+            if result == "UNKNOWN" or result == "ERROR":
+                 all_results[model_name] = f"⚠️ LLM Gagal Tebak"
+            else:
+                 all_results[model_name] = result
+            
+        except Exception as e:
+            all_results[model_name] = f"❌ API Error: {str(e)[:50]}"
+
+        # Tambahkan delay untuk menghindari Rate Limit OpenRouter
+        time.sleep(1.5) 
+
+    # Bersihkan file sementara
+    os.unlink(temp_path)
+
+    # Kembalikan hasil dalam urutan yang benar
+    return (
+        all_results.get("qwen", "Error"),
+        all_results.get("gpt", "Error"),
+        all_results.get("gemini", "Error"),
+        all_results.get("llama", "Error"),
+        all_results.get("Deepseek", "Error"),
+    )
+
+# ===================================================================
+# 3. INTERFACE GRADIOL
+# ===================================================================
+
+iface = gr.Interface(
+    fn=analyze_image_with_llms,
+    inputs=gr.Image(type="pil", label="🖼️ Upload Wajah untuk Analisis Deepfake"),
+    outputs=[
+        gr.Textbox(label="1. Qwen Prediction", type="text"),
+        gr.Textbox(label="2. GPT-4o Prediction", type="text"),
+        gr.Textbox(label="3. Gemini 2.5 Flash Prediction", type="text"),
+        gr.Textbox(label="4. Llama 3.2 Vision Prediction", type="text"),
+        gr.Textbox(label="5. deepseek-r1-0528-qwen3-8b:free", type="text")
+    ],
+    title="🔬 Perbandingan LLM Multimodal untuk Deteksi Deepfake Wajah",
+    description="Unggah gambar wajah. 5 LLM Multimodal (via OpenRouter) akan menganalisis dan menebak: **REAL** atau **FAKE**.",
+    allow_flagging="never",
+    theme=gr.themes.Soft()
+)
+
+if __name__ == "__main__":
     iface.launch()