I'm running the example LangChain/LangGraph code for "Basic Multi-agent Collaboration." I got the example from here (Github). There is also a blogpost/video.
After configuring my local virtual environment and copying and pasting the notebook, everything is working fine.
In the same virtual environment, I'm adapting the code to avoid to use the Jupyter Notebook. To do so, I decoupled the code into some classes.
Original code (working):
# Helper function to create a node for a given agentdef agent_node(state, agent, name): result = agent.invoke(state) # We convert the agent output into a format that is suitable to append to the global state if isinstance(result, FunctionMessage): pass else: result = HumanMessage(**result.dict(exclude={"type", "name"}), name=name) return {"messages": [result], # Since we have a strict workflow, we can # track the sender so we know who to pass to next."sender": name, }llm = ChatOpenAI(model="gpt-3.5-turbo", openai_api_key=open_ai_key)# Research agent and noderesearch_agent = create_agent( llm, [search], system_message="You should provide accurate data for the chart generator to use.",)research_node = functools.partial(agent_node, agent=research_agent, name="Researcher")# Chart Generatorchart_agent = create_agent( llm, [python_repl], system_message="Any charts you display will be visible by the user.",)chart_node = functools.partial(agent_node, agent=chart_agent, name="Chart Generator")#...some other cellsfor s in graph.stream( {"messages": [ HumanMessage( content="Fetch the UK's GDP over the past 5 years,"" then draw a line graph of it."" Once you code it up, finish." ) ], }, # Maximum number of steps to take in the graph {"recursion_limit": 100},): print(s) print("----")My adapted version (not working):
nodes.py
class Nodes: def __init__(self, llm, tools): self.llm = llm self.tools = tools def agent_node(state, agent, name): result = agent.invoke(state) if isinstance(result, FunctionMessage): pass else: result = HumanMessage(**result.dict(exclude={"type", "name"}), name=name) return {"messages": [result], # track the sender so we know who to pass to next."sender": name, } def research_agent_node(self): research_agent = create_agent( self.llm, [self.tools[0]], system_message="You should provide accurate data for the chart generator to use.", ) return functools.partial(self.agent_node, agent=research_agent, name="Researcher") def chart_generator_node(self): chart_agent = create_agent( self.llm, [self.tools[0]], system_message="Any charts you display will be visible by the user.", ) return functools.partial(self.agent_node, agent=chart_agent, name="Chart Generator")main.py
# Get the agent and tool nodesnodes = Nodes(llm, tools)research_agent_node = nodes.research_agent_node()chart_agent_node = nodes.chart_generator_node()#...more codefor s in graph.stream( {"messages": [ HumanMessage( content="Fetch the UK's GDP over the past 5 years,"" then draw a line graph of it."" Once you code it up, finish." ) ], }, # Maximum number of steps to take in the graph {"recursion_limit": 100}, ): print(s) print("----")The error message is TypeError: Nodes.agent_node() got multiple values for argument 'agent' and it's pretty straightforward to understand, but really hard to debug. Maybe I misunderstood how to return the functools.partial, but I don't know how to verify it.