Langgraph sql agent tutorial. You are an agent designed to interact with a SQL database.
- Langgraph sql agent tutorial. Mar 21, 2025 · I have implemented the SQL agent from (https://langchain-ai. Overview This lab demonstrate how you might build a Langgraph Agent that does the following: Inspects and classifies the request Depending on the request classifications, uses one of the two RAG stores or Search tool to retrieve data Verify quality of retrieved data, and fallback to web search For this lab, we will use Ollama to host and serve llama2 LLM as well as SurrealDB database to serve Feb 4, 2025 · We have built a LangGraph-based text-to-SQL agent that interacts with the database, generates SQL queries from user input, executes them, and retrieves the results. The problem is that when I ask how many rows are in a specific table, it always responds with "3," regardless of the table. Create autonomous workflows using memory, tools, and LLM orchestration. In this tutorial we In this tutorial, we’ll build an LLM-powered agentic graph using LangChain and LangGraph to combine RAG (Retrieval-Augmented Generation) with SQL agents. For this implementation, we are going to use watsonx Build resilient language agents as graphs. In general you can interact with a DB in two ways: Define functions as tools that expose specific queries the agent can make Define a DB tool that lets the agent write the actual sql query In either case, including examples in the docstrings about the schema, etc. It leverages langgraph for state management and OpenAI's GPT for intelligent query generation and response formatting. We'll also show how to evaluate it in 3 different ways. Am I the only one who feels LangGraph documentation and tutorials by lanfchain absolutely suck? I find langchain interesting to use as I’ve build some initial small pet projects off it but a lot of learning has been done by reading articles and watching some videos. 1. 🧠 SQL Agent with LangGraph This project demonstrates an agentic AI system using LangGraph, LangChain, and GROQ’s LLaMA 3 model to interact with a SQLite database via natural language. One of them is human-in-the-loop: we can interrupt our application before sensitive steps (such as the execution of a SQL query) for human review. The agent (an LLM) first determines whether to call a tool; if needed, it invokes the tool and uses its output, otherwise it responds directly. Data analysis has traditionally been inaccessible to those without extensive SQL or visualization expertise. Explained how to create SQL Agent using LangChain , LangGraph #langchain #langchaintutorial #langgraph Git:: https://github. In this cookbook, we will walk through how to build an agent that can answer questions about a SQL database. Oct 16, 2024 · LangGraph is also one of the most popular agent frameworks, which means there are a ton of example projects and tutorials to work from. from langgraph. It enables an LLM (like OpenAI's GPT models) to interact with a SQL database through multi-step reasoning, tool use, and error correction. To learn more about LangGraph, check out our first LangChain Academy course, Introduction to LangGraph, available here. Jun 22, 2024 · In fact of that, LangGraph you could achieve best results in customisation and performance. May 4, 2024 · Here we will build reliable RAG agents using LangGraph, Groq-Llama-3 and Chroma, We will combine the below concepts to build the RAG Agent. MCP + LangGraph Agent This is a minimal, functional example of an agent powered by LangGraph with tools implemented using MCP (Model Context Protocol) servers instead of traditional LangChain tools. com/course/advanced-langchain-techniques-mastering-rag-applications/?couponCode=F3FE5B004702C97234F Nov 29, 2024 · Learn to build a custom AI agent using LangGraph with RAG, NL2SQL, and Web Search. Learn about different architectures, memory, human in the loop, multi-agent systems and more. Deploy and scale with LangGraph Platform, with APIs for state management, a visual studio for debugging, and multiple deployment options. Built with LangGraph, LangChain, and Streamlit, the system allows users to chat with any SQL database, providing intuitive query generation and database exploration capabilities Use within an agent Following the SQL Q&A Tutorial, below we equip a simple question-answering agent with the tools in our toolkit. If you're looking to get started with chat models, vector stores, or other LangChain components from a specific provider, check out our supported Build a data analyst agent using LangGraph and the new Azure Container Apps dynamic sessions API. Jan 14, 2025 · This blog post explores the development of SQL agents using LangGraph, focusing on creating a workflow that connects language models with SQL databases. Jun 28, 2024 · Hello, thanks for this amazing explanation. Learn how to build agent systems with LangGraph. Simple for someone who never saw LangChain how it works. LangGraph is a great option for anyone to build agents, regardless of skill level. graph import StateGraph from typing import TypedDict, List, Dict, Any from langchain_openai import Sep 6, 2024 · In this article, we’ll explore how LangGraph transforms AI development and provide a step-by-step guide on how to build your own AI agent using an example that computes energy savings for solar Jan 14, 2025 · What is an Agentic RAG? An Agentic RAG builds on the basic RAG concept by introducing an agent that makes decisions during the workflow: Basic RAG: Retrieves relevant information from a database Nov 23, 2024 · 昨日ゴールド免許を取得した齊藤です。 久しぶりにLangGraphのチュートリアル確認してみたのですが、ぱっと見でわかりずらいので、簡易的にまとめてみました。（2024年11月23日） 無理矢理、翻訳した箇所もあるのでご愛嬌でお願いします。 こちら公式Tutorialになります Nov 4, 2024 · MY COURSES:ADVANCED RAG WITH LANGCHAIN: https://www. :::info Prerequisites This guide assumes familiarity with the following concepts: Chat models Tools Agents LangGraph ::: Enabling a LLM system to query structured data can be qualitatively different from unstructured text data. more LangGraph supports a number of features that can be useful for this workflow. Feb 28, 2025 · This section explains how to create a simple ReAct agent app (e. Aprende diferentes arquitecturas, memoria, human in the loop, sistemas multiagente y más. We're using the Multi Agent Collaboration approach. For example: "What songs do you have by Jimi Hendrix?" Feb 4, 2025 · In Part II, we built a LangGraph-based AI agent that translates natural language queries into SQL (Text-to-SQL agent), executes them, and retrieves the results. We will create an autonomous multi-step process that autonomically handles a data retrieval task and answers user's questions using multiple specialized AI agents This project is an SQL Query Assistant that automates the process of generating, executing, and explaining SQL queries using a combination of a Graph-based Workflow and a Large Language Model (LLM). Multi-agent supervisor Supervisor is a multi-agent architecture where specialized agents are coordinated by a central supervisor agent. The fundamental concept behind agents involves employing Jun 26, 2024 · Starting a first LangGraph Project Before starting your project you have to take a step back and think of what do you want to achieve ? For this tutorial, we want to build a simple application Sep 18, 2024 · Conclusion In this blog, we’ve explored the development of a sophisticated, voice-enabled SQL agent using LangGraph, Groq, and Flask. Throughout this tutorial, you'll discover the core features of LangGraph, get familiar Jun 9, 2025 · In this video, i will do a code walkthrough of how to build Knowledge base, Router Agent and how to dynamically route requests from Router agent to other age Aprender a crear sistemas de agente con LangGraph. . You will see how to leverage the LangGraph framework and the OpenAI GPT-4o model to retrieve natural language answers from an SQLite database, given a natural language query. Get started Familiarize yourself with LangChain's open-source components by building simple applications. Today, we’ll explore how to create a sophisticated SQL In this tutorial, we will walk through how to build an agent that can answer questions about a SQL database. prebuilt import create_react_agent system_prompt = """ You are an agent designed to interact with a SQL database. Jan 20, 2025 · Connecting MCP Servers to LangGraph In this article, I'll take you through the step-by-step process of building an MCP server and connecting it to a custom solution on LangGraph (client). Compared to other LLM frameworks, it offers these core benefits May 20, 2024 · How to build an agentic AI workflow using the Llama 3 open-source LLM model and LangGraph. LangGraph enables us to create stateful, multi-actor applications utilizing LLMs as easily as possible. Nov 24, 2024 · In this tutorial, you will learn how to set up LangGraph and create a multi-agent chatbot using ReAct agents. Introduction At the last MCP hackathon, I had the opportunity to delve into the Model Context Protocol (MCP), a transformative framework introduced by Anthropic in December 2024. To enable the agent to function end This guide explains how to set up PostgreSQL, create a project directory, build the database tables and import data, and run a LangGraph-based text-to-SQL AI agent. more Aug 15, 2024 · Building single- and multi-agent workflows with human-in-the-loop interactions このチュートリアルでは、SQLiteデータベースと対話するためのSQLエージェントの作成について説明します。テーブルの取得からクエリの実行までのワークフローを詳しく解説し、環境設定、ツールの定義、データクエリのための体系的なワークフローの実装について学びます。 This project demonstrates a simple yet powerful way to interact with SQL databases through a conversational interface. Apr 16, 2025 · Sample Agent Run You’d wrap the above steps as a LangGraph workflow from langgraph. LangGraph simplifies the process of building intelligent conversational agents and enhances their capabilities with state management. This video highlights a recent project demonstrating how agents can bridge the gap Transform the way you interact with your database! In this tutorial, we show you how to use LangGraph and SQL Server Agent to convert natural language queries into SQL and execute them instantly. Learn to build AI agents with LangChain and LangGraph. May 30, 2024 · In this blog post, we’ll introduce a simple tool created with LangGraph, designed to generate SQL validation rules that help detect errors in table columns on any relational database. After executing actions, the results can be fed back into the LLM to determine whether more actions are needed, or whether it is okay to finish. udemy. Criando um Agente SQL com SQLite Este tutorial aborda a criação de um agente SQL para interagir com um banco de dados SQLite. In this notebook we will show how those parameters map to the LangGraph react agent executor using the create_react_agent prebuilt helper method. Build resilient language agents as graphs. O guia detalha o fluxo de trabalho, desde a recuperação de tabelas até a execução de consultas, enquanto ensina sobre a configuração do ambiente, definição de ferramentas e implementação de um fluxo de trabalho sistemático para consultar dados. The main advantages of using the SQL Agent are: It can answer questions based on the databases' schema as well as on the databases' content (like describing a specific table). Compared to other LLM frameworks, it offers these core benefits: cycles, controllability, and persistence. In this tutorial, you will build a supervisor system with two agents — a research and a Jan 23, 2024 · Each agent can have its own prompt, LLM, tools, and other custom code to best collaborate with the other agents. ?” types of questions. com/chinnovinosoft/YouTube_Explai Introduction to LangGraph Learn the basics of LangGraph - our framework for building agentic and multi-agent applications. We began by designing a flexible LangGraph workflow to Feb 1, 2025 · In this article, we’ll explore how to build an intelligent SQL/BI agent using LangGraph, Vertex AI Agent Builder, and LangChain. Given an input question, create a syntactically correct {dialect} query to run, then look at the results of the query and return the answer. Here, we introduce how to manage agents through LLM-based Supervisor and coordinate the entire team based on the results of each agent node. I'm trying to convert this sql agent to gemini llm and BigQuery but in the following step I'm receiving an error: Sep 7, 2024 · This multi-agent system is designed to manage financial and consumption analysis tasks efficiently: · Financial Analysis: Uses the RAG system to retrieve and process unstructured data such as Nov 20, 2024 · We will explore how to use LangGraph within Langchain framework for multi agent setup and use openAI models for SQL query construction and retrieving information. Build controllable agents with LangGraph, our low-level agent orchestration framework. Jan 5, 2025 · Learn to build a scalable, modular multi-agent system using LangGraph with step-by-step guidance on agent orchestration and integration Tutorials New to LangChain or LLM app development in general? Read this material to quickly get up and running building your first applications. Build an Agent Introduction to LangGraph Explore the full list of LangChain tutorials here, and check out other LangGraph tutorials here. See our conceptual guide and agent tutorial for added context: Conceptual guide for evaluations Guide for agent evaluations Set up environment We'll set up our environment variables for OpenAI, and optionally, to enable tracing Dec 9, 2024 · In the world of AI and data analysis, the ability to interact with databases using natural language is becoming increasingly valuable. Jul 29, 2024 · LangGraph es una biblioteca del ecosistema LangChain que proporciona un marco para definir, coordinar y ejecutar múltiples agentes LLM (o cadenas) de forma estructurada y eficiente. The result is an automated chatbot Define the customer support agent We'll create a LangGraph agent with limited access to our database. Objectives In this tutorial, you will learn how to build and deploy an agent (model, tools, and agent) using the Vertex AI SDK for Python and Cloud SQL for PostgreSQL LangGraph integration. Great! We've got a SQL database that we can query. sql_agent_with_langgraph. io/langgraph/tutorials/sql-agent/) using LangGraph. In this article, we will focus on Part II, where we develop a LangGraph-based text-to-SQL agent and explore its various components in detail. is pretty important LangGraph docs on common agent architectures Pre-built agents in LangGraph Legacy agent concept: AgentExecutor LangChain previously introduced the AgentExecutor as a runtime for agents. Watching anything put out by landchain is far too complex. Let’s break it down step by step. Built on the LangGraph framework, this desktop tool lets you create agent workflows using a simple drag-and-drop interface. Now let's try hooking it up to an LLM. 🚀 Build a Powerful Text-to-SQL Agent with LangGraph! 🚀 Welcome to this complete 5-part tutorial series where I guide you step-by-step on how to build an inte Apr 26, 2025 · LangGraph is a library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows. Mar 1, 2025 · Learn how LangGraph, an AI agent framework built by LangChain, allows developers to create complex and flexible agent workflows using stateful graphs and built-in memory management. It covers the architecture, tools, and practical implementation steps, providing insights into the capabilities of AI in database management. The agent uses a Tavily-based language model client to convert natural language queries into SQL queries, executes them on a PostgreSQL database, and returns the results. Said that, the official guide of LangChain offers the simple solution based on create_react_agent or another simple based on create_sql_agent. The agent can store, retrieve, and use memories to enhance its interactions with users. In this tutorial, we'll explore how to build a multi-agent system using LangGraph , efficiently coordinate tasks between agents, and manage them through a Supervisor . Given an input question, create a syntactically correct u001b[33;1mu001b[1;3m{dialect}u001b[0m query to run, then look at the results of the query and return the answer. We will walk through the entire process, from installing the necessary libraries to configuring agents that can interact with external tools. ipynb Cannot retrieve latest commit at this time. With its flexible and Jun 16, 2025 · 🚀 Master LangGraph RAG agents from basics to advanced and build a multi-agent AI chatbot in a single session! Start with a raw LangChain LLM call, layer in tools and structured output, add 🧠 LangGraph SQL Agent Tutorial This project demonstrates how to build a powerful SQL Agent using LangGraph and LangChain. May 17, 2024 · From my experience with both LangChain and LangGraph, I find LangGraph more powerful and intuitive, offering more control over the agent’s behavior and easing the development process. Aug 2, 2024 · I am following the SQLAgent tutorial from Langgraph and adding RAG to it. Jun 20, 2025 · Have you ever found it frustrating to build AI agents that perform multiple tasks? LangGraph Studio is here to solve this problem by offering a visual and interactive way to design, manage, and debug agents. May 16, 2025 · 10 LangGraph project ideas and examples to build intelligent langgraph agents for real-world applications and gain valuable hands-on experience. This agent leverages generative AI to: Mar 5, 2025 · SQL Tutorial | LangGraph로 SQL AI 에이전트 만들기 Step-by-Step Tutorial: Building an AI-Powered SQL Agent Introduction Hello, and welcome to our tutorial on building an AI-powered SQL agent! In this tutorial, we will be exploring the process of creating an AI agent that can generate SQL queries based on user requests, and provide accurate answers. That means there are two main considerations when thinking about different multi-agent workflows: What are the multiple independent agents? How are those agents connected? This thinking lends itself incredibly well to a graph representation, such as that provided by langgraph. to check the weather) using LangGraph’s prebuilt ReAct agent. Jun 26, 2024 · LangGraph Tutorial: What Is LangGraph and How to Use It? LangGraph is a library within the LangChain ecosystem that provides a framework for defining, coordinating, and executing multiple LLM agents (or chains) in a structured and efficient manner. In Or, to learn how to build an agent workflow with a customizable architecture, long-term memory, and other complex task handling, see the LangGraph basics tutorials. This tutorial shows how to implement an agent with long-term memory capabilities using LangGraph. Chains Chains are compositions of predictable steps. This Sep 2, 2024 · Learn how to use LangGraph to build local AI Agents with Ollama and Llama 3. LangGraph Structure LangGraph provides a few abstractions that make building agents much easier. Welcome to the world of LangGraph! In this tutorial, we'll dive into LangGraph, a robust library tailored for creating stateful applications with large language models (LLMs). Separate from the LangChain package, LangGraph helps developers add better precision and control into agentic workflows. It can recover from errors by running a generated query, catching the traceback and regenerating it Aug 21, 2023 · A step-by-step guide to building a LangChain enabled SQL database question answering agent. Contribute to langchain-ai/langgraph development by creating an account on GitHub. ipynb youtubelive / sql_agent_with_langgraph. First we pull a relevant prompt and populate it with its required parameters: Welcome to our in-depth tutorial on the Advanced SQL Database Agent Integrated with LangGraph! In this video, we dive deep into the architecture and functionality of a comprehensive framework that May 20, 2025 · If you are new to LangGraph and wish to learn about it, then this beginner's guide and hands-on tutorial is the best free content for you. I tried to see if SQL tutorial can be repurposed The graph structure that I wanted to design is very simple. You are an agent designed to interact with a SQL database. github. It extends the capabilities of LangChain, introducing the ability to create and manage Sep 10, 2024 · In this tutorial, we will explore how to build a multi-agent system using LangGraph within the LangChain framework to get a better understanding at LangGraph for multi-agent applications. May 16, 2025 · A step-by-step, hands-on Langgraph tutorial that takes you from the basics to advanced concepts, helping you quickly build AI agents. Contribute to langchain-ai/langsmith-cookbook development by creating an account on GitHub. For demo purposes, our agent will support two basic types of requests: Lookup: The customer can look up song titles, artist names, and albums based on other identifying information. Whereas in the latter it is common to generate text that can be searched against a vector database, the approach for structured data is often for the LLM to write and How to add an Agent in a LangGraph as a node? Specifically agent created out of create_sql_agent I am trying to use the helper method create_sql_agent to create an agent and add it in a simple graph to create a database team. The supervisor agent controls all communication flow and task delegation, making decisions about which agent to invoke based on the current context and task requirements. While it served as an excellent starting point, its limitations became apparent when dealing with more sophisticated and customized agents. LangChain agents (the AgentExecutor in particular) have multiple configuration parameters. g. Here we focus on how to move from legacy LangChain agents to more flexible LangGraph agents. May 22, 2024 · The customer service bot tutorial queries a database. The idea is that we use RAG to fetch relevant DB table info and make the SQL agent job easier in finding the right table as Mar 10, 2025 · One approach is LangGraph Reflection, which helps validate and improve AI-generated SQL queries, ensuring they are both accurate and efficient. How-to guides Here you’ll find short answers to “How do I…. Agents LangChain has a SQL Agent which provides a more flexible way of interacting with SQL Databases than a chain. In LangGraph, we can represent a chain via simple sequence of nodes. Learn to build specialized AI agents for tasks like itinerary planning and flight booking, and explore the benefits of multi-agent systems in AI development. With LangGraph, you can build both basic and highly intricate agents using a consistent and flexible methodology. Jun 17, 2025 · Build an Agent LangChain supports the creation of agents, or systems that use LLMs as reasoning engines to determine which actions to take and the inputs necessary to perform the action. Nov 30, 2024 · This tutorial demonstrates how to build an AI agent that queries SQLite databases using natural language. In this video we will introduce LangGraph - a way to more easily create agent runtimes. "LLM-Powered SQL Database Agents with LangGraph"🚀 Get ready for an exciting live session where we explore the world of LLM-Powered SQL Database Agents using LangGraph! 🌟💾 Watch as I Tired of writing complex scripts just to query your MongoDB database? In this guide, you’ll learn how to build an AI agent that lets you chat with your data using plain English, powered by LangGraph, the Model Context Protocol (MCP), and Gradio. It's based on the official LangGraph tutorial, adapted to demonstrate how to integrate MCP servers as tools. Jan 31, 2025 · Discover how to create a multi-agent chatbot using LangGraph. Jul 4, 2025 · Learn to develop a MySQL chatbot agent in Python LangGraph, which allows you to ask questions and get answers from a MySQL database in a natural language. Let's create a sequence of steps that, given a question, does the following: converts the question into a SQL query; executes the query; uses the result to answer the original question LangChain / LangGraph SQL Agent Demo This repository demonstrates the use of LangChain and LangGraph for SQL query generation, execution and validation. Sep 6, 2024 · LangGraph is a library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows. Step-by-step tutorial for developers to create task-oriented agents. This is often achieved via tool-calling. pxvl ylfih uojn unhypwx ltyzu edj krlni hlwd nshem yxye