Langgraph sql agent. Chains Chains are compositions of predictable steps.

Langgraph sql agent. The fundamental concept behind agents involves employing Feb 27, 2025 · Up to this point, we’ve had one higher level abstraction and it’s lived in the main langgraph package. @Duba System Info Jun 13, 2024 · I'm designing custom SQL agents using LangGraph to have more control over the agent flow. py # Orchestrates the main workflow LangGraph supports a number of features that can be useful for this workflow. 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 In this cookbook, we will walk through how to build an agent that can answer questions about a SQL database. py # Implements safety checks ├── nodes. Simple for someone who never saw LangChain how it works. Plus, learn about LangGraph Cloud in open beta. 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. Build resilient language agents as graphs. We'll also show how to evaluate it in 3 different ways. agent_toolkits. Our multi-agent system aims to solve this issue by automatically turning plain-language questions into validated SQL queries, and then displaying the answers as text and visuals Mar 9, 2011 · About AI Agent RAG & SQL Chatbot enables natural language interaction with SQL databases, CSV files, and unstructured data (PDFs, text, vector DBs) using LLMs, LangChain, LangGraph, and LangSmith for retrieval and response generation, accessible via a Gradio UI, with LangSmith monitoring. 5. See the [reference doc] (https://langchain-ai. Given an input question, create a syntactically correct {dialect} query to run, then look at the results of the query and return the answer. The result is an automated chatbot Jan 5, 2025 · Learn to build a scalable, modular multi-agent system using LangGraph with step-by-step guidance on agent orchestration and integration Mar 11, 2025 · In production applications, storing both long-term and short-term memory in persistent storage is essential for maintaining agent state across sessions. Said that, the official guide of LangChain offers the simple solution based on create_react_agent or another simple based on create_sql_agent. In LangGraph, we can represent a chain via simple sequence of nodes. To enable the agent to function end The workflow is orchestrated using LangGraph, which provides a framework for easily building complex AI agents, a streaming API for real-time updates, and a visual studio for monitoring and experimenting with the agent's behavior. What if we could build an AI agent that automatically audits SQL scripts for best practices, performance issues, and Apr 11, 2025 · Analyze the responses from sql_agent and propose a better query or changes in database schema to improve the performance of the query if needed (Do it yourself). py # Handles configuration and initialization ├── tools. This template provides a robust foundation for building scalable, secure, and maintainable AI agent services. 🚀 Comprehensive LangGraph learning repository with hands-on examples, and practical implementations. May 20, 2024 · How to build an agentic AI workflow using the Llama 3 open-source LLM model and LangGraph. Oct 16, 2024 · Learn how to integrate LangGraph’s agent workflows with Arize and use LLMs as judges to evaluate agent performance. README. Around the LangGraph agent, the workflow uses a SQLite Server that supports file (SQLite and CSV) uploads under 1MB and a front-end that has prebuilt graph templates Nov 30, 2024 · Next we will develop a LangGraph agent that converts natural language questions into SQL queries to retrieve data from the titanic. Multi-agent using Genie and LangGraph Open notebook in new tab Copy to clipboard LangGraph quickstart This guide shows you how to set up and use LangGraph's prebuilt, reusable components, which are designed to help you construct agentic systems quickly and reliably. Full details and video recording available here: RAG on Azure SQL Server. This post explores how Waii’s capabilities can enhance LangGraph applications for conversational analytics. My current approach involves using the SQL agent with Langraph. Waii provides text-to-SQL and text-to-chart capabilities, enabling natural language interactions with databases and data visualization. Text embedding model: gte-large-en-v1. Sep 12, 2024 · Let's explore an exciting project that leverages LangGraph Cloud's streaming API to create a data visualization agent. Deploy and scale with LangGraph Platform, with APIs for state management, a visual studio for debugging, and multiple deployment options. Apr 28, 2025 · This document details the LangGraph Agent, which serves as the intelligence layer of the datavisualizationlanggraph system. 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. py # Defines workflow nodes for LangGraph ├── workflow. The underlying technologies (OpenAI, Anthropic, or others) can be flexibly swapped in and out thanks to MCP’s server-based architecture. ipynb youtubelive / sql_agent_with_langgraph. In this notebook we will show how those parameters map to the LangGraph react agent executor using the create_react_agent prebuilt helper method. It was create_react_agent, a wrapper for creating a simple tool calling agent. com/course/advanced-langchain-techniques-mastering-rag-applications/?couponCode=F3FE5B004702C97234F Aug 2, 2024 · I am following the SQLAgent tutorial from Langgraph and adding RAG to it. The agent takes natural language questions from a user, converts them into syntactically correct SQL queries, executes them against a database, and returns the final 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. For this implementation, we are going to use watsonx Feb 21, 2025 · """ project/ │ ├── state. 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. Install dependencies If you haven't already, install LangGraph and LangChain: Execute the agent to interact with an SQL database through the entire process. The agent processes natural language questions, translates them into SQL que Mar 26, 2025 · The end user asks simple questions in English, and the system should create an SQL query based on the table names and column names in the database, which is MSSQL. Setup: Install langchain-community. Enable tool use, reasoning, and explainability with OpenAI's GPT models in a traceable workflow. Query Processing and Response Generation Schema retrieval is crucial for ensuring that the agent generates accurate queries based on up-to-date table structures. . create_react_agent) for more information. When a user inputs a natural language query, the agent autonomously orchestrates May 16, 2025 · 10 LangGraph project ideas and examples to build intelligent langgraph agents for real-world applications and gain valuable hands-on experience. Build controllable agents with LangGraph, our low-level agent orchestration framework. Manual SQL code reviews are time-consuming and often miss critical issues. Post from LangChain with code for Text to SQL using Mistral AI, Neon… Aug 21, 2023 · A step-by-step guide to building a LangChain enabled SQL database question answering agent. The sample is build using plain LangChain (app. I need to define a sequence of tool executions in a knowledge graph and ensure the system executes them correctly. Feb 2, 2025 · So here we are, I’ve built a RAG that brings a similar reasoning process (CoT responses) to the LangGraph SQL agent with tool calling. 🚀 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 By combining a LangGraph ReAct agent with a secondary summarization step, we created a robust tool that can translate natural language into accurate SQL queries and deliver human-readable results. This agent will be capable of understanding questions Apr 26, 2025 · This post explores building an agentic SQL generation workflow using LangGraph, a framework in the LangChain ecosystem designed for creating stateful, multi-node graphs. g. Nov 4, 2024 · MY COURSES:ADVANCED RAG WITH LANGCHAIN: https://www. While it served as an excellent starting point, its limitations became apparent when dealing with more sophisticated and customized agents. LangGraph introduces the concept of cycles to the agent runtime, enabling repetitive loops essential for agent operation. Let's create these entities for our question/answering agent. is pretty important Mar 2, 2024 · By integrating LangGraph with Ollama, developers can harness the strengths of both libraries to create sophisticated applications that can maintain state, process complex interactions, and perform LangGraph: Build LLM based SQL Database Agents using LangGraph : Part 6 Aritra Sen 2. py) to define the RAG process. To improve your LLM application development, pair LangGraph with: LangSmith — Helpful for agent evals and observability. For a more robust and feature-rich implementation, we recommend using the create_react_agent function from the LangGraph library. The agent retrieves information from the database based on user queries, generates and executes SQL queries, and returns the results. This defines the logic within each node of the SQL agent, following the steps explained above. The agent can store, retrieve, and use memories to enhance its interactions with users. langchain. It enables users to query an SQLite database using natural language, dynamically converting the query into SQL using a custom agent workflow LangGraph’s ecosystem While LangGraph can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools for building agents. Handoffs 本教程介绍了如何创建一个SQL代理，以便与SQLite数据库进行交互，详细说明了从获取表格到执行查询的工作流程。您将学习环境设置、工具定义以及实现系统化数据查询工作流程。 FastAPI LangGraph Agent Template A production-ready FastAPI template for building AI agent applications with LangGraph integration. prebuilt. We began by designing a flexible LangGraph workflow to Define the customer support agent We'll create a LangGraph agent with limited access to our database. Great! We've got a SQL database that we can query. ReAct agents are uncomplicated, prototypical agents that can be flexibly extended to many tools. Streamlit Text to SQL Agentic ChatBot app built with langgraph workflow : Workflow : LangGraph Workflow with text-to-query, sqlite, and memory & session management 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. Some features were not in GA, so I signed up for the… Jun 3, 2025 · Multi-agent systems typically consist of a supervisor agent that directs and manages context for specialized worker agents. 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. py # Contains utility functions and tools ├── guardrails. 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 Nov 20, 2024 · In today’s rapidly evolving technological landscape, multi agent chatbots have become integral in enhancing customer experience. Spider dataset is used to test the pipeline. Now let's try hooking it up to an LLM. 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. May 22, 2024 · The customer service bot tutorial queries a database. 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 Apr 17, 2025 · Our agent will take a natural language query as input, write SQL on the fly, execute it against a Postgres database, and return the results. Azure SQL DB, Langchain, LangGraph and Chainlit Sample RAG pattern using Azure SQL DB, Langchain and Chainlit as demonstrated in the #RAGHack conference. I am able to use create_sql_query_chain just fine against either an OpenAI LLM or In this tutorial, we’ll build an LLM-powered agentic graph using LangChain and LangGraph to combine RAG (Retrieval-Augmented Generation) with SQL agents. io/langgraph/reference/prebuilt/#langgraph. Contribute to langchain-ai/langgraph development by creating an account on GitHub. sql_agent_with_langgraph. io/langgraph/tutorials/sql-agent/) using LangGraph. This blog is a brief dive into the agent’s workflow and key features. 랭체인 1-5SQL 데이터베이스 쿼리하기 과제를 수행할 때 아무 생각 없이 디버깅을 위해 SQL Query를 만드는 부분 Query문을 실행하는 부분 등을 단계적으로 나누어 실행하면서 출력을 확인해 봅니다 execute_query = QuerySQLDataBaseTooldb=db Feb 24, 2025 · 在本文中，我们将介绍如何使用 LangChain 和 LangGraph 构建一个能够与 SQL 数据库交互的代理。 这个代理可以回答关于 SQL 数据库的问题，通过一系列步骤来完成任务，包括获取数据库中的表信息、生成查询语句、执行查询并返回结果等。 Sep 24, 2024 · I have implemented a supervisor multi-agent structure that controls a User Intent Clarity Agent (which asks follow-up questions based on a schema) and an SQL Agent. udemy. The fusion of LangGraph with Text-to-SQL and RAG architecture empowers AI agents to handle structured data queries with contextual awareness, multi-turn reasoning, and accurate SQL generation. 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 Mar 16, 2025 · 4. It can recover from errors by running a generated query, catching the traceback and regenerating it This project is a Proof of Concept (POC) demonstrating the integration of LangGraph with a SQL database agent. Feb 28, 2025 · This section explains how to create a simple ReAct agent app (e. Built on the LangGraph framework, this desktop tool lets you create agent workflows using a simple drag-and-drop interface. May 16, 2025 · Qwen3의 하이브리드 사고 모드는 복잡한 SQL 최적화나 트랜잭션 논리 설계 등 심층 추론이 필요할 때는 Thinking Mode로 단계별 분석을 수행하고, 간단한 쿼리 생성이나 형식 검증처럼 빠른 응답이 요구될 때는 Non-Thinking Mode로 즉시 결과를 반환해, 에이전트의 지능적 유연성을 극대화합니다. Jun 22, 2024 · In fact of that, LangGraph you could achieve best results in customisation and performance. Learn about different architectures, memory, human in the loop, multi-agent systems and more. It uses LangGraph to define an agentic workflow that processes natural language questions, converts them to SQL, and returns meaningful results with visualizations. Mar 10, 2025 · One approach is LangGraph Reflection, which helps validate and improve AI-generated SQL queries, ensuring they are both accurate and efficient. chat_agent_executor. This project implements SQLAgent, an interactive SQL query agent built with LangGraph and ChatGroq LLM. Learn how to create a custom LangGraph schema agent in Databricks. LangGraph ReAct Agent Template This template showcases a ReAct agent implemented using LangGraph, designed for LangGraph Studio. 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. from langgraph. The agent dynamically queries an in-memory SQLite instance of the Chinook Sample Database (Music Store) and returns natural language answers to user questions. Jan 31, 2025 · Discover how to create a multi-agent chatbot using LangGraph. Mar 16, 2024 · LangGraph, developed by LangChain, is a pioneering framework designed to facilitate the creation and management of AI agents. Jun 17, 2025 · We will be using LangGraph to construct the agent. 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. 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. more Multi-Agent Chatbot with LangGraph and Azure Services A sophisticated chatbot implementation that uses multiple specialized agents to process queries through different search and processing methods, powered by Azure OpenAI, Azure AI Search, and Azure SQL Database. Now, we can initialize the agent with the LLM and the tools. py # Defines the agent's state ├── prompts. 2 includes new checkpointer libraries for increased customization — including a SQLite checkpointer for local workflows and an optimized Postgres checkpointer to take your app to production. Specifically, I want to build an agent that uses an adaptive RAG chain and an SQL agent. LangChain / LangGraph SQL Agent Demo This repository demonstrates the use of LangChain and LangGraph for SQL query generation, execution and validation. SQLDatabaseToolkit # class langchain_community. sql. Contribute to agola11/lg-sql-agent development by creating an account on GitHub. However, many users lack the technical background to do this comfortably. 3 release, and moving it into langgraph-prebuilt. 定义状态（State） LangGraph 的工作流需要定义一个状态对象，用于在节点之间传递信息。SQL Agent 的状态可能包括： 用户的自然语言问题。 生成的SQL查询。 查询结果。 最终答案。 from typing import TypedDict, List class SQLAgentState (TypedDict): user_query: str # 用户的自然语言问题 sql_query: str # 生成的SQL查询 query In this how-to guide, we’ll build an application that allows an end-user to engage in a multi-turn conversation with one or more agents. Apr 9, 2024 · The docs describe how to create an SQL agent using OpenAI as an example but implying that the approach is generic. You can upload an SQLite database or CSV file, ask questions about your data, and the agent will generate appropriate visualizations. Chroma is used as a vector database. 5-turbo The experiment runs In this Blog we will build a multi AI agent with RAG using Langraph and AstraDB with integration with the Llama 3. The agents will be implemented as tasks in a workflow that executes agent steps and determines the next action: Wait for user input to continue the An interactive agent built using LangGraph, powered by the Mistral-3. Apr 16, 2025 · Sample Agent Run You’d wrap the above steps as a LangGraph workflow from langgraph. This agent leverages generative AI to: 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. Contribute to langchain-ai/langsmith-cookbook development by creating an account on GitHub. Sep 12, 2024 · 整个工作流程都由 LangGraph Cloud 编排，它提供了一个框架，可以轻松构建复杂的 AI Agent，提供用于实时更新的流式 API，以及用于监控和实验 Agent 行为的可视化工作室。 首先，让我们看看当前最先进的文本到 SQL 工作流程 模式和元数据提取 系统处理提供的数据库（例如，SQLite 或 CSV）以提取关键信息 May 29, 2025 · To address these issues, we built a multi-agent system accelerator using LangGraph and Databricks’ hosted LLM. LangGraph offers a powerful framework to Mar 21, 2025 · I have implemented the SQL agent from (https://langchain-ai. Chains Chains are compositions of predictable steps. Build and deploy production-grade langgraph agents on Azure using Chinook database - shivachittamuru/langgraph-agents-on-azure Jun 20, 2024 · I am using the above code to create sql agent, the code runs, it generates reasonable sql queries, but the query results were all hallucinated, not the actual result based on the database. Setup This example uses Chinook database, which is a sample database available for SQL Server, Oracle, MySQL, etc. It leverages langgraph for state management and OpenAI's GPT for intelligent query generation and response formatting. LangChain agents (the AgentExecutor in particular) have multiple configuration parameters. This project demonstrates a simple yet powerful way to interact with SQL databases through a conversational interface. The problem is that when I ask how many rows are in a specific table, it always responds with "3," regardless of the table. It covers the message routing architecture, node interactions, and how user queries flow This project demonstrates a sophisticated, autonomous agent built with LangGraph and LangChain that can interact with a SQL database. 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). This tool extracts the table names and database metadata given the context, but the generated query isn’t always 📊How LinkedIn put a SQL agent using LangGraph into production Data teams often spend too much time helping colleagues find data, creating bottlenecks at companies. May 16, 2025 · 从高层次上讲，sql agent智能体做的内容： 从数据库中获取可用表 确定哪些表与问题相关 获取相关表的架构 根据问题和架构中的信息生成查询 使用 LLM 仔细检查查询中是否存在常见错误 执行查询并返回结果 纠正数据库引擎发现的错误，直到查询成功 根据结果制定响应 定义状态（State） LangGraph 的 Learn to build AI agents with LangChain and LangGraph. Create autonomous workflows using memory, tools, and LLM orchestration. An agent is a system driven by a language model that makes decisions about actions/tools to take. Your agent will be built from scratch by using LangGraph and the Mistral Medium 3 large language model (LLM). This guide covers the following: implementing handoffs between agents using handoffs and the prebuilt agent to build a custom multi-agent system To get started with building multi-agent systems, check out LangGraph prebuilt implementations of two of the most popular multi-agent architectures — supervisor and swarm. 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. 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. To set it up, follow these instructions, placing the . py # Manages prompt templates ├── config. github. This is not required to use the toolkit. Feb 23, 2024 · In the end of January, 2024, I received an email about LangGraph and LangSmith. toolkit. My goal is to implement this in Databricks, leveraging MLflow for model mana Jun 27, 2024 · Follow the Format Instructions: Ensure that the agent always follows the specified format in the FORMAT_INSTRUCTIONS to maintain consistency and clarity in the agent's actions and responses. May 16, 2025 · This document provides a detailed explanation of the LangGraph agent system in the SQL Support Bot repository. Aug 7, 2024 · LangGraph v0. This project implements a natural language to SQL query system for a PostgreSQL database containing the Pagila/IMDB dataset. db SQLite database. 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 Jun 28, 2024 · Hello, thanks for this amazing explanation. Mar 9, 2011 · AgentGraph: Intelligent SQL-agent Q&A and RAG System for Chatting with Multiple Databases This project demonstrates how to build an agentic system using Large Language Models (LLMs) that can interact with multiple databases and utilize various tools. text2sql-agent 🚀 A powerful text-to-SQL agent that converts natural language queries into SQL statements using LangGraph and LangChain 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 Oct 11, 2024 · LangGraph is a framework for building stateful, multi-agent applications using language models. Prerequisites Before you start this tutorial, ensure you have the following: An Anthropic API key 1. We can enforce a higher degree of control in LangGraph by customizing the agent. wondering how is the agent connected to db, since the agent arguments don't include db and why sql_db_query tool doesn't execute on the sql db. 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. This tool takes a user-uploaded CSV and answers natural language questions by generating and executing SQL queries — all within a few seconds. 외부 도구 In many organizations, making data-driven decisions requires writing precise SQL queries. It is a ReAct agent (Reason + Act) that combines LangGraph’s SQL toolkit with a graph-based execution. Multi-agent supervisor Supervisor is a multi-agent architecture where specialized agents are coordinated by a central supervisor agent. I'm trying to convert this sql agent to gemini llm and BigQuery but in the following step I'm receiving an error: query_check_system = """You are a SQL expert with a strong attention to detail. By fetching table and column names dynamically, the agent avoids assumptions about the data schema, enhancing its adaptability to real-time changes. Why It's a Valuable LangGraph Example This implementation serves as an excellent case study for LangGraph users by demonstrating: Integration of diverse AI agent types within a unified framework LangSmith - smith. Today, we are splitting that out of langgraph as part of a 0. Jul 22, 2024 · Adaptive Workflow: Showcases LangGraph's dynamic routing capabilities, adjusting the analysis approach based on the data and task at hand. md Advanced SQL Agent API This Flask-based API provides Advanced SQL query analysis and visualization services using LangChain and LangGraph. 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. ipynb Cannot retrieve latest commit at this time. com LangSmith Feb 1, 2025 · I am working on building an agent using the AI Cookbook Agent Template and would like to integrate LangGraph into the agent template. to check the weather) using LangGraph’s prebuilt ReAct agent. We'll create a node that uses an interrupt to collect user input and routes back to the active agent. (Chroma also supports default built-in text embedding model which is SentenceTransformer all-MiniLM-L6-v2 model. The experiment leverage CrewAI, AutoGen and LangChain - LangGraph frameworks to build the agentic RAG pipeline. 2-24B model via OpenRouter. db file in the directory where your code lives. If you want to get automated tracing from runs of individual tools LangGraph SQL Agent. SQLDatabaseToolkit [source] # Bases: BaseToolkit SQLDatabaseToolkit for interacting with SQL databases. Build a data analyst agent using LangGraph and the new Azure Container Apps dynamic sessions API. Learn how to build agent systems with LangGraph. Currently, we are using a high level interface to construct the agent, but the nice thing about LangGraph is that this high-level interface is backed by a low-level, highly controllable API in case you want to modify the agent logic. prebuilt import create_react_agent system_prompt = """ You are an agent designed to interact with a SQL database. 1 open source model using Groq API. graph import StateGraph from typing import TypedDict, List, Dict, Any from langchain_openai import May 30, 2024 · LangGraph dependencies LangChain is a framework which helps you to create LLM based workflows and agents. 29K subscribers Subscribed 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. Let’s break it down step by step. 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. Nov 29, 2024 · Learn to build a custom AI agent using LangGraph with RAG, NL2SQL, and Web Search. Step-by-step tutorial for developers to create task-oriented agents. Sep 6, 2024 · LangGraph is a library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows. It converts user queries into SQL, checks and corrects them, executes them, and returns accurate answers based on database contents. Master stateful multi-agent applications, RAG systems, SQL agents, custom tools, and debugging t Here we focus on how to move from legacy LangChain agents to more flexible LangGraph agents. In this tutorial, you will build an AI agent that can execute and generate Python and SQL queries for your custom SQLite database. This toolkit is useful for asking questions, performing queries, validating queries and more on a SQL database. This challenge creates slowdowns in analyzing data. 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 Agents LangChain has a SQL Agent which provides a more flexible way of interacting with SQL Databases than a chain. Below, we implement a simple ReAct-agent setup, with dedicated nodes for specific tool-calls. Developing a LangGraph Agent for Question/Answering Over SQL Data A LangGrah agent consists of an agent state, nodes, and edges. ) LLM: OpenAI gpt-3. py) or using LangGraph (app-langgraph. This system breaks down the migration process into modular, specialized agents that coordinate via natural language and perform critical steps of the migration automatically. Dec 9, 2024 · Today, we’ll explore how to create a sophisticated SQL agent using LangGraph, a powerful library for building complex AI workflows. We will also require langgraph to demonstrate the use of the toolkit with an agent. LLMs can solve this by making If using python, for example, the LangGraph agent is defined in backend_py/my_agent. It has a wide variety of agent tools that integrate with all types of systems — from Sep 18, 2024 · Conclusion In this blog, we’ve explored the development of a sophisticated, voice-enabled SQL agent using LangGraph, Groq, and Flask. 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). Mar 27, 2025 · Learn how to build a ReAct-style LLM agent in Databricks using LangGraph, LangChain, and LangSmith. Jun 27, 2024 · Text to SQL is one the many LLM use cases that is getting attention. Example notebook: Multi-agent system with Genie The following notebook shows you how to create a multi-agent system using LangGraph and Genie. Built with LangGraph, LangChain, and Streamlit, the system allows users to chat with any SQL database, providing intuitive query generation and database exploration capabilities May 22, 2025 · 构建 SQL 代理（Build a SQL agent） 在本教程中，我们将逐步介绍如何构建一个能够回答 SQL 数据库相关问题的代理。 从高层次来看，该代理将执行以下操作： 从数据库中获取可用表 决定哪些表与问题相关 获取相关表的模式（schema） 根据问题和模式信息生成查询 使用 LLM 双重检查查询是否存在常见错误 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 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 tutorial shows how to implement an agent with long-term memory capabilities using LangGraph. For example: "What songs do you have by Jimi Hendrix?" Jun 5, 2024 · This story is a follow-up of our previous story “Building SQL Validation Rules with LangGraph” and describes how you can create a more refined agent which generates SQL validation rules for For demonstration purposes, we will access a prompt in the LangChain Hub. zoe xygy ayfvz crh ewoxmre zfl kywa xbwpj tcwus kycspo