modify : llm factory file

backend/common/llm_factory.py

 """
-LLM Factory - Centralized LLM creation for OpenAI & Gemini.
-Manages initialization and caching of LLM models with automatic provider detection.
+LLM Factory - OpenAI LLM creation with caching.
+Manages initialization and caching of OpenAI models.
 """
 
 import contextlib
 import logging
 
 from langchain_core.language_models import BaseChatModel
-from langchain_google_genai import ChatGoogleGenerativeAI
 from langchain_openai import ChatOpenAI, OpenAIEmbeddings
 
-from config import GOOGLE_API_KEY, OPENAI_API_KEY
+from config import OPENAI_API_KEY
 
 logger = logging.getLogger(__name__)
 
 
 class LLMFactory:
-    """Singleton factory for managing LLM instances with caching and provider auto-detection."""
+    """Singleton factory for managing OpenAI LLM instances with caching."""
 
     COMMON_MODELS: list[str] = [
         "gpt-4o-mini",
-        "gemini-2.0-flash-lite-preview-02-05",
+        "gpt-4o",
+        "gpt-5-nano",
+        "gpt-5-mini",
     ]
 
     def __init__(self):
@@ -64,7 +65,7 @@ class LLMFactory:
         api_key: str | None = None,
     ) -> BaseChatModel:
         """
-        Create and cache a new LLM instance based on model name.
+        Create and cache a new OpenAI LLM instance.
 
         Args:
             model_name: Clean model identifier
@@ -76,12 +77,9 @@ class LLMFactory:
             Configured LLM instance
 
         Raises:
-            ValueError: If required API keys are missing
+            ValueError: If API key is missing
         """
         try:
-            if self._is_gemini_model(model_name):
-                llm = self._create_gemini(model_name, streaming, api_key)
-            else:
             llm = self._create_openai(model_name, streaming, api_key)
 
             if json_mode:
@@ -95,34 +93,12 @@ class LLMFactory:
             logger.error(f"❌ Failed to create model {model_name}: {e}")
             raise
 
-    def _is_gemini_model(self, model_name: str) -> bool:
-        """Check if model name is a Gemini model."""
-        return "gemini" in model_name.lower()
-
-    def _create_gemini(self, model_name: str, streaming: bool, api_key: str | None) -> BaseChatModel:
-        """Create Gemini model instance."""
-        key = api_key or GOOGLE_API_KEY
-        if not key:
-            raise ValueError("GOOGLE_API_KEY is required for Gemini models")
-
-        llm = ChatGoogleGenerativeAI(
-            model=model_name,
-            streaming=streaming,
-            google_api_key=key,
-            temperature=0,
-        )
-        logger.info(f"✨ Created Gemini: {model_name}")
-        return llm
-
     def _create_openai(self, model_name: str, streaming: bool, api_key: str | None) -> BaseChatModel:
-        """Create OpenAI model instance with fallback to Gemini if needed."""
+        """Create OpenAI model instance."""
         key = api_key or OPENAI_API_KEY
 
         if not key:
-            logger.warning("⚠️ No OpenAI key, attempting Gemini fallback")
-            if GOOGLE_API_KEY:
-                return self._create_gemini("gemini-1.5-flash", streaming, GOOGLE_API_KEY)
-            raise ValueError("Neither OPENAI_API_KEY nor GOOGLE_API_KEY is available")
+            raise ValueError("OPENAI_API_KEY is required")
 
         llm = ChatOpenAI(
             model=model_name,

backend/docker-compose.yml

@@ -5,11 +5,11 @@ services:
     container_name: canifa_backend
     env_file: .env
     ports:
-      - "8000:8000"
+      - "5000:5000"
     volumes:
       - .:/app
     environment:
-      - PORT=8000
+      - PORT=5000
     restart: unless-stopped
     logging:
       driver: "json-file"

backend/readme.md

@@ -36,7 +36,7 @@ http://localhost:8000
 ```json
 {
   "user_id": "user_12345",
-  "user_query": "Cho em xem áo sơ mi nam dưới 500k"
+  "user_query": "Cho em xem áo sơ mi nam dưới 5a00k"
 }
 ```
 

backend/server.py

@@ -11,25 +11,15 @@ Modules:
 - conversation: Conversation history management
 """
 
-import os
 import logging
+import os
 
 # Configure Logging
 logging.basicConfig(
-    level=logging.INFO,
-    format="%(asctime)s [%(levelname)s] %(name)s: %(message)s",
-    handlers=[logging.StreamHandler()]
+    level=logging.INFO, format="%(asctime)s [%(levelname)s] %(name)s: %(message)s", handlers=[logging.StreamHandler()]
 )
 logger = logging.getLogger(__name__)
 
-from config import LANGSMITH_API_KEY, LANGSMITH_ENDPOINT, LANGSMITH_PROJECT, LANGSMITH_TRACING
-
-# Ensure LangSmith Env Vars are set for the process
-os.environ["LANGSMITH_TRACING"] = LANGSMITH_TRACING
-os.environ["LANGSMITH_ENDPOINT"] = LANGSMITH_ENDPOINT
-os.environ["LANGSMITH_API_KEY"] = LANGSMITH_API_KEY
-os.environ["LANGSMITH_PROJECT"] = LANGSMITH_PROJECT
-
 
 import uvicorn
 from fastapi import FastAPI
@@ -39,8 +29,6 @@ from fastapi.staticfiles import StaticFiles  # Import StaticFiles
 # Updated APIs
 from api.chatbot_route import router as chatbot_router
 from api.conservation_route import router as conservation_router
-
-from common.middleware import ClerkAuthMiddleware
 from config import PORT
 
 app = FastAPI(
@@ -78,7 +66,6 @@ app.include_router(conservation_router)
 # Chatbot Agent (Mới)
 app.include_router(chatbot_router, prefix="/api/agent")
 
-# Mount Static Files
 # Mount this LAST to avoid conflicts with API routes
 try:
     static_dir = os.path.join(os.path.dirname(__file__), "static")
@@ -93,6 +80,7 @@ except Exception as e:
 async def root():
     return {"message": "Contract AI Service is running!", "status": "healthy"}
 
+
 if __name__ == "__main__":
     print("=" * 60)
     print("🚀 Contract AI Service Starting...")
@@ -104,15 +92,13 @@ if __name__ == "__main__":
     print("=" * 60)
 
     # ENABLE_RELOAD = os.getenv("ENABLE_RELOAD", "false").lower() in ("true", "1", "yes")
-    ENABLE_RELOAD = True
-    print("⚠️  Hot reload: FORCED ON (Dev Mode)")
+    ENABLE_RELOAD = False  # Tạm thời tắt reload để kiểm tra độ ổn định
+    print(f"⚠️  Hot reload: {ENABLE_RELOAD}")
 
     reload_dirs = [
-        "ai_contract",
-        "conversation",
         "common",
         "api",  # Watch api folder
-        "agent" # Watch agent folder
+        "agent",  # Watch agent folder
     ]
 
     uvicorn.run(