Update rag_langgraph.py

rag_langgraph.py

@@ -39,6 +39,13 @@ def agent_node(state, agent, name):
     result = agent.invoke(state)
     return {"messages": [HumanMessage(content=result["output"], name=name)]}
 
+@tool
+def today_tool(text: str) -> str:
+    """Returns today's date. Use this for any questions related to knowing today's date. 
+       The input should always be an empty string, and this function will always return today's date. 
+       Any date mathematics should occur outside this function."""
+    return str(date.today())
+    
 def create_graph(topic, word_count):
     tavily_tool = TavilySearchResults(max_results=10)
     
@@ -92,10 +99,10 @@ def create_graph(topic, word_count):
         | JsonOutputFunctionsParser()
     )
 
-    researcher_agent = create_agent(llm, [tavily_tool], system_prompt=f"Prioritizing research papers, research content on topic: {topic}.")
+    researcher_agent = create_agent(llm, [tavily_tool], system_prompt=f"Prioritizing research papers, research content on topic: '{topic}'.")
     researcher_node = functools.partial(agent_node, agent=researcher_agent, name="Researcher")
 
-    writer_agent = create_agent(llm, [None], system_prompt=f"Write a {word_count}-word article on topic: {topic}. Add a references section with research papers.")
+    writer_agent = create_agent(llm, [today_tool], system_prompt=f"Write a {word_count}-word article on topic: '{topic}'. Add a 'references' section with research papers. Add the 'current date' and 'author': Multi-AI-Agent System based on GPT-4o.")
     writer_node = functools.partial(agent_node, agent=writer_agent, name="Writer")
 
     workflow = StateGraph(AgentState)