Update agent.py

agent.py

@@ -12,11 +12,10 @@ from langchain_community.document_loaders import ArxivLoader
 
 from langchain_core.messages import SystemMessage, HumanMessage
 from langchain_core.tools import tool
-from langchain.chat_models import ChatHuggingFace
+
 
 from langchain_google_genai import ChatGoogleGenerativeAI
 
-from langchain.llms import HuggingFaceHub
 #load_dotenv()
 google_api_key = os.environ["GOOGLE_API_KEY"]
 hf_api_key = os.environ["HF_TOKEN"]
@@ -107,19 +106,13 @@ def build_graph(provider: str = "google"):
     if provider == "google":
         # Google Gemini
         llm = ChatGoogleGenerativeAI(model="gemini-2.0-flash", temperature=0,api_key=google_api_key)
-    elif provider == "huggingface":
-        llm = HuggingFaceHub(
-            repo_id="meta-llama/Llama-2-7b-chat-hf",  
-            huggingfacehub_api_token=hf_api_key,        
-            model_kwargs={"temperature": 0}
-        )
     # Bind tools to LLM
     llm_with_tools = llm.bind_tools(tools)
     
     def assistant(state: MessagesState):
         """ Use the tools to answer the query. you have add,subtract,multiply,divide,web_search,wikipedia_search,arxiv_search tools."""
         response = llm_with_tools.invoke([system_message]+state["messages"])
-        #time.sleep(4) # 무료 티어의 한계
+        time.sleep(4) # 무료 티어의 한계
         return {"messages": state["messages"] + [response]}