Update rag_langgraph.py

rag_langgraph.py

@@ -46,17 +46,17 @@ def today_tool(text: str) -> str:
 def create_graph(topic):
     tavily_tool = TavilySearchResults(max_results=10)
     
-    members = ["Researcher", "Writer"]
+    agents = ["Researcher", "Writer"]
     
     system_prompt = (
-        "You are a manager tasked with managing a conversation between the"
-        " following workers: {members}. Given the following user request,"
-        " respond with the worker to act next. Each worker will perform a"
+        "You are a Manager tasked with managing a conversation between the"
+        " following agents: {agents}. Given the following user request,"
+        " respond with the agent to act next. Each agent will perform a"
         " task and respond with their results and status. When finished,"
         " respond with FINISH."
     )
 
-    options = ["FINISH"] + members
+    options = ["FINISH"] + agents
 
     function_def = {
         "name": "route",
@@ -86,7 +86,7 @@ def create_graph(topic):
                 " Or should we FINISH? Select one of: {options}",
             ),
         ]
-    ).partial(options=str(options), members=", ".join(members))
+    ).partial(options=str(options), members=", ".join(agents))
     
     llm = ChatOpenAI(model=LLM)
     
@@ -96,10 +96,10 @@ def create_graph(topic):
         | 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"Research content on topic: {topic}. Prioritize research papers, if available.")
     researcher_node = functools.partial(agent_node, agent=researcher_agent, name="Researcher")
 
-    writer_agent = create_agent(llm, [today_tool], system_prompt=f"Write a 2000-word article on topic: {topic}, including a reference section with research papers. At the top, add current date and author: Multi-AI-Agent System based on GPT-4o.")
+    writer_agent = create_agent(llm, [today_tool], system_prompt=f"Write a 2000-word article on topic: {topic}. At the beginning, add current date and author: Multi-AI-Agent System based on GPT-4o. At the end, add a reference section with research papers.")
     writer_node = functools.partial(agent_node, agent=writer_agent, name="Writer")
 
     workflow = StateGraph(AgentState)
@@ -107,10 +107,10 @@ def create_graph(topic):
     workflow.add_node("Writer", writer_node)
     workflow.add_node("Manager", supervisor_chain)
 
-    for member in members:
-        workflow.add_edge(member, "Manager")
+    for agent in agents:
+        workflow.add_edge(agent, "Manager")
 
-    conditional_map = {k: k for k in members}
+    conditional_map = {k: k for k in agents}
     conditional_map["FINISH"] = END
     
     workflow.add_conditional_edges("Manager", lambda x: x["next"], conditional_map)