How to add a custom system prompt to the prebuilt ReAct agent¶

This tutorial will show how to add a custom system prompt to the prebuilt ReAct agent. Please see this tutorial for how to get started with the prebuilt ReAct agent

You can add a custom system prompt by passing a string to the state_modifier param.

Setup¶

First, let's install the required packages and set our API keys

In [1]:

%%capture --no-stderr
%pip install -U langgraph langchain-openai

%%capture --no-stderr %pip install -U langgraph langchain-openai

In [ ]:

import getpass
import os


def _set_env(var: str):
    if not os.environ.get(var):
        os.environ[var] = getpass.getpass(f"{var}: ")


_set_env("OPENAI_API_KEY")

import getpass import os def _set_env(var: str): if not os.environ.get(var): os.environ[var] = getpass.getpass(f"{var}: ") _set_env("OPENAI_API_KEY")

Set up LangSmith for LangGraph development

Sign up for LangSmith to quickly spot issues and improve the performance of your LangGraph projects. LangSmith lets you use trace data to debug, test, and monitor your LLM apps built with LangGraph — read more about how to get started here.

Code¶

In [1]:

# First we initialize the model we want to use.
from langchain_openai import ChatOpenAI

model = ChatOpenAI(model="gpt-4o", temperature=0)


# For this tutorial we will use custom tool that returns pre-defined values for weather in two cities (NYC & SF)

from typing import Literal

from langchain_core.tools import tool


@tool
def get_weather(city: Literal["nyc", "sf"]):
    """Use this to get weather information."""
    if city == "nyc":
        return "It might be cloudy in nyc"
    elif city == "sf":
        return "It's always sunny in sf"
    else:
        raise AssertionError("Unknown city")


tools = [get_weather]

# We can add our system prompt here

prompt = "Respond in Italian"

# Define the graph

from langgraph.prebuilt import create_react_agent

graph = create_react_agent(model, tools=tools, state_modifier=prompt)

# First we initialize the model we want to use. from langchain_openai import ChatOpenAI model = ChatOpenAI(model="gpt-4o", temperature=0) # For this tutorial we will use custom tool that returns pre-defined values for weather in two cities (NYC & SF) from typing import Literal from langchain_core.tools import tool @tool def get_weather(city: Literal["nyc", "sf"]): """Use this to get weather information.""" if city == "nyc": return "It might be cloudy in nyc" elif city == "sf": return "It's always sunny in sf" else: raise AssertionError("Unknown city") tools = [get_weather] # We can add our system prompt here prompt = "Respond in Italian" # Define the graph from langgraph.prebuilt import create_react_agent graph = create_react_agent(model, tools=tools, state_modifier=prompt)

Usage¶

In [2]:

def print_stream(stream):
    for s in stream:
        message = s["messages"][-1]
        if isinstance(message, tuple):
            print(message)
        else:
            message.pretty_print()

def print_stream(stream): for s in stream: message = s["messages"][-1] if isinstance(message, tuple): print(message) else: message.pretty_print()

In [4]:

inputs = {"messages": [("user", "What's the weather in NYC?")]}

print_stream(graph.stream(inputs, stream_mode="values"))

inputs = {"messages": [("user", "What's the weather in NYC?")]} print_stream(graph.stream(inputs, stream_mode="values"))

================================ Human Message =================================

What's the weather in NYC?
================================== Ai Message ==================================
Tool Calls:
  get_weather (call_b02uzBRrIm2uciJa8zDXCDxT)
 Call ID: call_b02uzBRrIm2uciJa8zDXCDxT
  Args:
    city: nyc
================================= Tool Message =================================
Name: get_weather

It might be cloudy in nyc
================================== Ai Message ==================================

A New York potrebbe essere nuvoloso.

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