Update multi_agent.py

multi_agent.py

@@ -46,7 +46,7 @@ def today_tool(text: str) -> str:
 def create_graph(model, max_tokens, temperature, topic):
     tavily_tool = TavilySearchResults(max_results=10)
     
-    members = ["Content Planner", "Article Author", "Article Editor"]
+    members = ["Content Planner", "Content Writer"]
     options = ["FINISH"] + members
    
     system_prompt = (
@@ -95,7 +95,7 @@ def create_graph(model, max_tokens, temperature, topic):
         | JsonOutputFunctionsParser()
     )
 
-    content_planner_agent = create_agent(llm, [tavily_tool, today_tool], system_prompt=
+    content_planner_agent = create_agent(llm, [tavily_tool], system_prompt=
                                     "You are a Content Planner working on planning a blog article "
               "about the topic: " + topic + "."
               "You collect information that helps the "
@@ -105,8 +105,8 @@ def create_graph(model, max_tokens, temperature, topic):
               "the Content Writer to write an article on this topic.")
     content_planner_node = functools.partial(agent_node, agent=content_planner_agent, name="Content Planner")
 
-    article_author_agent = create_agent(llm, [tavily_tool], system_prompt=
-                                    "You are an Article Writer working on writing "
+    content_writer_agent = create_agent(llm, [today_tool], system_prompt=
+                                    "You are a Content Writer working on writing "
               "a new opinion piece about the topic: " + topic + ". "
               "You base your writing on the work of "
               "the Content Planner, who provides an outline "
@@ -120,26 +120,13 @@ def create_graph(model, max_tokens, temperature, topic):
               "You acknowledge in your opinion piece "
               "when your statements are opinions "
               "as opposed to objective statements.")
-    article_author_node = functools.partial(agent_node, agent=article_author_agent, name="Article Author")
-
-    article_editor_agent = create_agent(llm, [tavily_tool], system_prompt=
-                                    "You are an Article Editor who receives a blog post "
-              "from the Content Writer. "
-              "Your goal is to review the blog post "
-              "to ensure that it follows journalistic best practices,"
-              "provides balanced viewpoints "
-              "when providing opinions or assertions, "
-              "and also avoids major controversial topics "
-              "or opinions when possible.")
-    article_editor_node = functools.partial(agent_node, agent=article_editor_agent, name="Article Editor")
-    ###
+    content_writer_node = functools.partial(agent_node, agent=content_writer_agent, name="Content Writer")
     
     workflow = StateGraph(AgentState)
 
     workflow.add_node("Manager", supervisor_chain)
     workflow.add_node("Content Planner", content_planner_node)
-    workflow.add_node("Article Author", article_author_node)
-    workflow.add_node("Article Editor", article_editor_node)
+    workflow.add_node("Content Writer", content_writer_node)
 
     for member in members:
         workflow.add_edge(member, "Manager")