Update config/settings.py

config/settings.py

@@ -4,7 +4,15 @@ from dotenv import load_dotenv
 load_dotenv()
 
 class Settings:
-    GROQ_API_KEY = os.getenv("GROQ_API_KEY")
+    # Ưu tiên lấy từ environment variables (cho Hugging Face)
+    GROQ_API_KEY = os.getenv("GROQ_API_KEY") or os.getenv("X_GROQ_API_KEY")
+    
+    # Kiểm tra API Key
+    if not GROQ_API_KEY:
+        print("❌ CẢNH BÁO: Không tìm thấy GROQ_API_KEY")
+        print("💡 Trên Hugging Face Spaces, hãy thêm biến môi trường:")
+        print("   - Tên: GROQ_API_KEY")
+        print("   - Value: gsk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx")
     
     # Multilingual Model Settings
     VIETNAMESE_EMBEDDING_MODEL = 'keepitreal/vietnamese-sbert'
@@ -13,13 +21,6 @@ class Settings:
     MULTILINGUAL_EMBEDDING_MODEL = 'sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2'
     MULTILINGUAL_LLM_MODEL = "llama-3.1-8b-instant"
     
-    # Fallback models in case primary models fail
-    FALLBACK_MULTILINGUAL_EMBEDDING_MODEL = 'sentence-transformers/all-MiniLM-L6-v2'
-    
-    # Default models (fallback)
-    DEFAULT_EMBEDDING_MODEL = 'dangvantuan/vietnamese-embedding'
-    DEFAULT_LLM_MODEL = "Vietnamese_LLaMA2_13B_8K_SFT_General_Domain_Knowledge"
-    
     WHISPER_MODEL = "whisper-large-v3-turbo"
     
     # TTS Settings
@@ -30,9 +31,7 @@ class Settings:
     }
     
     # RAG Settings
-    EMBEDDING_DIMENSION = 768  # For Vietnamese model
-    MULTILINGUAL_EMBEDDING_DIMENSION = 4096  # For Nemotron model
-    
+    EMBEDDING_DIMENSION = 384
     TOP_K_RESULTS = 3
     
     # SpeechBrain VAD Settings