change llm

agent.py

@@ -1,8 +1,11 @@
+import getpass
 import os
 from dotenv import load_dotenv
 from typing import TypedDict, List, Dict, Any, Optional, Annotated
 
-from langchain_huggingface import ChatHuggingFace, HuggingFaceEndpoint, HuggingFaceEmbeddings
+from langchain_huggingface import HuggingFaceEmbeddings # Removed ChatHuggingFace, HuggingFaceEndpoint
+from langchain_google_genai import ChatGoogleGenerativeAI # Added ChatGoogleGenerativeAI
+
 
 from langgraph.graph import StateGraph, MessagesState, START, END
 from langgraph.graph.message import add_messages
@@ -13,7 +16,8 @@ from langchain.tools import Tool
 from langchain_core.tools import tool
 from langchain_community.tools import WikipediaQueryRun
 from langchain_community.utilities import WikipediaAPIWrapper
-from langchain_community.utilities import SerpAPIWrapper
+from langchain_community.tools import DuckDuckGoSearchResults
+from langchain_community.utilities import DuckDuckGoSearchAPIWrapper
 from langchain_community.utilities import ArxivAPIWrapper
 from langchain_community.retrievers import BM25Retriever
 
@@ -24,6 +28,8 @@ from langgraph.prebuilt import ToolNode, tools_condition
 load_dotenv()
 HUGGINGFACEHUB_API_TOKEN = os.getenv("HUGGINGFACEHUB_API_TOKEN")
 print(f"DEBUG: HUGGINGFACEHUB_API_TOKEN = {HUGGINGFACEHUB_API_TOKEN}")
+GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
+print(f"DEBUG: GOOGLE_API_KEY = {GOOGLE_API_KEY}")
 
 
 # maths tool
@@ -103,8 +109,9 @@ def search_web(query: str) -> Dict[str, str]:
     args:
         query: a search query
     """
-    docs = SerpAPIWrapper()
-    docs.run(query)
+    wrapper = DuckDuckGoSearchAPIWrapper(region="en-us", max_results=2)
+    docs = DuckDuckGoSearchResults(api_wrapper=wrapper)
+    docs.invoke(query)
     formatted_result = f'<Document source="{docs.metadata["source"]}" page="{docs.metadata.get("page", "")}"/>\n{docs.page_content}\n</Document>'
     return {"web_results": formatted_result}
 
@@ -150,25 +157,23 @@ tools = [
 # build graph function
 def build_graph():
     # llm
-    llm = HuggingFaceEndpoint(
-        repo_id="deepseek-ai/DeepSeek-V3-0324",
-        huggingfacehub_api_token=HUGGINGFACEHUB_API_TOKEN,
+    # Using ChatGoogleGenerativeAI as the LLM
+    llm = ChatGoogleGenerativeAI(
+        model="gemini-2.5-flash-preview-04-17",
+        google_api_key=GOOGLE_API_KEY
     )
     print(f"DEBUG: llm object = {llm}")
 
-    chat = ChatHuggingFace(llm=llm, verbose=False)
-    print(f"DEBUG: chat object = {chat}")
-
     # bind tools to llm
-    chat_with_tools = chat.bind_tools(tools)
-    print(f"DEBUG: chat_with_tools object = {chat_with_tools}")
+    llm_with_tools = llm.bind_tools(tools)
+    print(f"DEBUG: llm_with_tools object = {llm_with_tools}")
 
     # generate AgentState and Agent graph
     class AgentState(TypedDict):
         messages: Annotated[list[AnyMessage], add_messages]
 
     def assistant(state: AgentState):
-        result = chat_with_tools.invoke(state["messages"])
+        result = llm_with_tools.invoke(state["messages"])
         # Ensure the result is always wrapped in a list, even if invoke returns a single message
         # Add usage information if it's not already present
         if isinstance(result, AIMessage) and result.usage_metadata is None:

pyproject.toml

@@ -6,8 +6,10 @@ readme = "README.md"
 requires-python = ">=3.12"
 dependencies = [
     "dotenv>=0.9.9",
+    "duckduckgo-search>=8.0.1",
     "gradio>=5.29.0",
     "langchain-community>=0.3.23",
+    "langchain-google-genai>=2.1.4",
     "langchain-huggingface>=0.2.0",
     "langchain-openai>=0.3.16",
     "langchain-tools>=0.1.34",