Build a ReAct Agent in Python Step by Step | LLM + Tools Explained

🚀 Build your first ReAct Agent in Python step by step!

In this tutorial, you'll learn how to create an AI agent that can reason step by step and use tools like a calculator and weather API to answer complex questions.

We’ll build a complete working example from scratch using Python and the OpenAI API.

📌 What You’ll Learn
What a ReAct Agent is
The difference between Reasoning and Acting
How to define custom Python tools
How to create tool schemas for the LLM
How to pass messages and tools to the OpenAI API
How to inspect tool_calls
How to execute tools dynamically
How to generate the final answer
🛠 Tools Used in This Tutorial
Python
OpenAI API
GPT-4o-mini
Custom tools:
Calculator
Weather Tool
🧠 Example Question

What is the weather in Tokyo, and what is that temperature in Celsius?

The agent will:

Call the Weather Tool
Get the temperature in Fahrenheit
Use the Calculator Tool to convert it to Celsius
Return the final answer
📂 Step-by-Step Workflow
Define the Tools
Create Tool Schemas
Prepare Messages
Call the LLM
Inspect tool_calls
Execute the Tools
Return the Final Answer
🎯 Why ReAct Agents Matter

ReAct Agents combine:

Reasoning → The LLM plans what to do
Acting → The agent calls tools to complete tasks

This is the foundation behind many modern AI agents and autonomous systems.

🔔 Subscribe for More AI Tutorials

If you're interested in:

AI Agents
LangChain
OpenAI API
Python Automation
Generative AI

Subscribe to the channel for more hands-on tutorials.

🏷️ Hashtags

#ReActAgent #pythonai #openai #aiagents #llm #pythontutorial #generativeai #ToolCalling #gpt4o #openaiapi #langchain #aiengineering #machinelearning #artificialintelligence

Github code: https://github.com/pranaydave/data_jarvis_public/blob/main/agent_building/react_agent.py

Try this out interactively: https://datajarvis.ai (select apps Agent Builder)

Видео Build a ReAct Agent in Python Step by Step | LLM + Tools Explained канала DATA JARVIS