Update agent.py

agent.py

@@ -5,9 +5,9 @@ from langgraph.graph import START, StateGraph, MessagesState
 from langgraph.prebuilt import tools_condition
 from langgraph.prebuilt import ToolNode
 from langchain_google_genai import ChatGoogleGenerativeAI
-from langchain_groq import ChatGroq
+#from langchain_groq import ChatGroq
 from langchain_huggingface import ChatHuggingFace, HuggingFaceEndpoint, HuggingFaceEmbeddings
-from langchain_community.tools.tavily_search import TavilySearchResults
+#from langchain_community.tools.tavily_search import TavilySearchResults
 from langchain_community.document_loaders import WikipediaLoader
 from langchain_community.document_loaders import ArxivLoader
 from langchain_community.vectorstores import SupabaseVectorStore
@@ -84,6 +84,7 @@ def wiki_search(query: str) -> str:
         ])
     return {"wiki_results": formatted_search_docs}
 
+"""
 @tool
 def web_search(query: str) -> str:
     """Search Tavily for a query and return maximum 3 results.
@@ -98,6 +99,8 @@ def web_search(query: str) -> str:
         ])
     return {"web_results": formatted_search_docs}
 
+"""
+
 @tool
 def arvix_search(query: str) -> str:
     """Search Arxiv for a query and return maximum 3 result.
@@ -118,18 +121,19 @@ def arvix_search(query: str) -> str:
 #with open("system_prompt.txt", "r", encoding="utf-8") as f:
 #   system_prompt = f.read()
 
-system_prompt = """ You are a helpful assistant tasked with answering questions using a set of tools. 
+system_prompt = """You are a helpful assistant tasked with answering questions using a set of tools. 
 Now, I will ask you a question. Report your thoughts, and finish your answer with the following template: 
 FINAL ANSWER: [YOUR FINAL ANSWER].
 YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings. 
 If you are asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise. 
 If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise. 
 If you are asked for a comma separated list, apply the above rules depending of whether the element to be put in the list is a number or a string.
-Your answer should only start with "FINAL ANSWER: ", then follows with the answer."""
+Your answer should only start with "FINAL ANSWER: ", then follows with the answer.""".strip()
     
 # System message
 sys_msg = SystemMessage(content=system_prompt)
 
+"""
 # build a retriever
 embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2") #  dim=768
 supabase: Client = create_client(
@@ -146,7 +150,7 @@ create_retriever_tool = create_retriever_tool(
     name="Question Search",
     description="A tool to retrieve similar questions from a vector store.",
 )
-
+"""
 
 
 tools = [
@@ -156,7 +160,7 @@ tools = [
     divide,
     modulus,
     wiki_search,
-    web_search,
+    #web_search,
     arvix_search,
 ]
 
@@ -197,11 +201,12 @@ def build_graph(provider: str = "huggingface"):
         return {"messages": [sys_msg] + state["messages"] + [example_msg]}
 
     builder = StateGraph(MessagesState)
-    builder.add_node("retriever", retriever)
+    #builder.add_node("retriever", retriever)
     builder.add_node("assistant", assistant)
     builder.add_node("tools", ToolNode(tools))
-    builder.add_edge(START, "retriever")
-    builder.add_edge("retriever", "assistant")
+    #builder.add_edge(START, "retriever")
+    builder.add_edge(START, "assistant")
+    #builder.add_edge("retriever", "assistant")
     builder.add_conditional_edges(
         "assistant",
         tools_condition,
@@ -215,7 +220,7 @@ def build_graph(provider: str = "huggingface"):
 if __name__ == "__main__":
     question = "When was a picture of St. Thomas Aquinas first added to the Wikipedia page on the Principle of double effect?"
     # Build the graph
-    graph = build_graph(provider="groq")
+    graph = build_graph(provider="huggingface")
     # Run the graph
     messages = [HumanMessage(content=question)]
     messages = graph.invoke({"messages": messages})