How to beginner · 3 min read

How to use create_react_agent in LangChain

Q: How to use create_react_agent in LangChain

Use create_react_agent from langchain.agents to build an AI agent that uses React-style reasoning with tools. Initialize your language model and tools, then call create_react_agent with these to get an agent ready for interaction.

Quick answer

Use create_react_agent from langchain.agents to build an AI agent that uses React-style reasoning with tools. Initialize your language model and tools, then call create_react_agent with these to get an agent ready for interaction.

PREREQUISITES

Python 3.8+
OpenAI API key (free tier works)
pip install langchain openai

Setup

Install the required packages and set your OpenAI API key as an environment variable.

bash

pip install langchain openai

Step by step

This example demonstrates creating a React agent with LangChain using OpenAI's GPT-4o model and a simple tool. The agent uses React-style reasoning to decide which tool to call and how to respond.

python

import os
from langchain.agents import create_react_agent
from langchain_openai import ChatOpenAI
from langchain.tools import Tool

# Initialize the language model
llm = ChatOpenAI(model="gpt-4o", temperature=0)

# Define a simple tool
def greet(name: str) -> str:
    return f"Hello, {name}!"

greet_tool = Tool(
    name="greet",
    func=greet,
    description="Greets a person by name."
)

# Create the React agent with the LLM and tools
agent = create_react_agent(llm=llm, tools=[greet_tool])

# Run the agent with a user query
response = agent.invoke("Greet Alice")
print(response)

output

Hello, Alice!

Common variations

Use different LLMs like gpt-4o-mini or Anthropic models with LangChain adapters.
Integrate multiple tools for complex workflows.
Use async versions of LangChain components for concurrency.

Troubleshooting

If you get authentication errors, verify your OPENAI_API_KEY environment variable is set correctly.
Ensure your tools have clear description fields for better agent reasoning.
If the agent does not respond as expected, try lowering temperature to 0 for deterministic output.

✅

Key Takeaways

Use create_react_agent to build agents that reason step-by-step with tools in LangChain.
Always provide descriptive tools to improve agent decision-making.
Set temperature=0 for consistent agent responses during testing.
You can combine multiple tools for complex agent workflows.
Verify environment variables to avoid authentication issues.

Verified 2026-04 · gpt-4o, gpt-4o-mini

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