add gemini refferences

src/agents/gemini_chatbot.py

@@ -17,8 +17,11 @@ from langgraph.graph import StateGraph, END
 from langchain_core.prompts import ChatPromptTemplate
 from langchain_core.messages import HumanMessage, AIMessage, SystemMessage
 
-from src.gemini.file_search import GeminiFileSearchClient, GeminiFileSearchResult
+from src.config.loader import load_config
+from src.llm.adapters import get_llm_client
 from src.config.paths import CONVERSATIONS_DIR
+from src.gemini.file_search import GeminiFileSearchClient, GeminiFileSearchResult
+
 
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
 logger = logging.getLogger(__name__)
@@ -42,9 +45,18 @@ class GeminiState(TypedDict):
 class GeminiRAGChatbot:
     """Gemini File Search RAG chatbot (Beta version)"""
     
-    def __init__(self):
+    def __init__(self,  config_path: str = "src/config/settings.yaml"):
         """Initialize the Gemini chatbot"""
+        
         logger.info("🤖 INITIALIZING: Gemini File Search Chatbot (Beta)")
+        self.config = load_config(config_path)
+
+        # Get LLM provider from config
+        reader_config = self.config.get("reader", {})
+        default_type = reader_config.get("default_type", "INF_PROVIDERS")
+        provider_name = default_type.lower()
+        
+        self.llm_adapter = get_llm_client(provider_name, self.config)
         
         # Initialize Gemini File Search client
         try:
@@ -151,8 +163,7 @@ class GeminiRAGChatbot:
         
         # Use LLM to intelligently add document references and format nicely
         try:
-            from src.llm.adapters import get_llm_client
-            llm = get_llm_client()
+            llm = self.llm_adapter
             
             # Prepare document summaries for the LLM
             doc_summaries = []
@@ -389,4 +400,3 @@ Return ONLY the enhanced, well-formatted response with references added and any
 def get_gemini_chatbot():
     """Get Gemini chatbot instance"""
     return GeminiRAGChatbot()
-