langgraph/how-tos/create-react-agent-system-prompt/

[giscus[bot]]

langgraph/how-tos/create-react-agent-system-prompt/

Build language agents as graphs

https://langchain-ai.github.io/langgraph/how-tos/create-react-agent-system-prompt/

[Rohianon]

Is there a way a system prompt can be added to a self-discover model?

Also, how does one integrate the human-in-the-loop in self-discover so that the model allows self updates.

[SH781-a]

Caught me out

the state_modifier was removed see below:
@deprecated_parameter("messages_modifier", "0.1.9", "state_modifier", removal="0.2.0")
def create_react_agent(
model: LanguageModelLike,
tools: Union[ToolExecutor, Sequence[BaseTool]],
*,
state_schema: Optional[StateSchemaType] = None,
messages_modifier: Optional[MessagesModifier] = None,
state_modifier: Optional[StateModifier] = None,
checkpointer: Optional[BaseCheckpointSaver] = None,
interrupt_before: Optional[Sequence[str]] = None,
interrupt_after: Optional[Sequence[str]] = None,
debug: bool = False,

so check your versoin 

[vbarda]

@SH781-a no, the documentation is correct, you're misreading the deprecation message. messages_modifier is the parameter that will be deprecated, state_modifier is the one that should be used

[SH781-a]

you are correct I was changing as I got your comment, apologies

[duob-ai]

I try to use this react agent in a FastAPI server where I create an endpoint with langserve.

Problem is data validation. Currently deploying the endpoint with:
add_routes(app, agent, path="/agent", input_type=Any)

Is there any documentation on what the data model has to look like for LangGraph if you want to do input validation?

[EthanChen39]

Is there a way to integrate ReAct agent with StateGraph?

[nick-youngblut]

Why no use of langchain.agents.AgentExecutor for create_react_agent, even though langchain.agents.AgentExecutor is used for other agents, such as langchain.agents.create_openai_tools_agent?

[vbarda]

we do not recommend using langchain's AgentExecutor -- using create_react_agent or a custom langgraph implementation based on that is the recommended way

[qianL93]

What is the difference between 'tool calling agent'?

[afbarbaro]

I have a simple use of create_react_agent where I want to add different system messages, depending on the value of a property that I track in the agent state. Here's a simple example, where I want to track the number of calls to the LLM and key off that:

            def state_modifier(state: AgentState) -> Sequence[BaseMessage]:
                # Track the number of calls to the agent
                llm_calls = state.get("llm_calls", 0)
                state["llm_calls"] = llm_calls + 1       # problem, this does NOT update state

                # Add the adequate system message to the beginning of the messages
                messages = list(state.get("messages", []))
                content = (
                    SystemMessages.lg_react_last()
                    if llm_calls > 0
                    else SystemMessages.lg_react_first(self.seeq_context)
                )
                messages.insert(0, SystemMessage(content))

                # Return the messages
                return messages

So my question is how can I mutate the state so that new properties and/or values stick?

[p19ky]

You can maybe use the checkpointer parameter of create_react_agent? I am also new to langgraph but I am looking at the create_react_agent docs now. https://langchain-ai.github.io/langgraph/reference/prebuilt/