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Langgraph sql agent example. ipynb Cannot retrieve latest commit at this time.
Langgraph sql agent example. Always use this tool before executing a query with sql_db_query! 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. 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. The planning steps & generated code are all static values. SQLite Database — Comes with a sample Chinook. env. github. graph import StateGraph from typing import TypedDict, List, Dict, Any from langchain_openai import Jan 5, 2025 · Learn to build a scalable, modular multi-agent system using LangGraph with step-by-step guidance on agent orchestration and integration 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. env using . 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. Built on the LangGraph framework, this desktop tool lets you create agent workflows using a simple drag-and-drop interface. In Define the customer support agent We'll create a LangGraph agent with limited access to our database. Enabling a LLM system to query structured data can be qualitatively different from unstructured text data. 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. Learn to build AI agents with LangChain and LangGraph. Instead of directly ingesting the database, the agent connects to it and executes SQL queries dynamically based on your question. Setup First, get required packages and set environment variables: bash npm2yarn npm i langchain @langchain/community @langchain/langgraph Dec 20, 2024 · In this blog post, we've created an AI agent using LangGraph and Llama 3. It covers the following topics, along with complete code examples (using triple backticks) and the names of the required packages: Using the Prebuilt ReAct Agent Adding Thread-Level Memory Adding a Custom System Prompt Returning Structured Output Adding Semantic Search to Oct 16, 2024 · SQL Agent Example See here for the full notebook Now let’s look at an example. Introduction to LangGraph, a tool for implementing agents with cyclic graphs, demonstrating how to create a more structured and controllable agent using components like nodes, edges, and state management Mar 9, 2011 · 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. This template provides a robust foundation for building scalable, secure, and maintainable AI agent services. Said that, the official guide of LangChain offers the simple solution based on create_react_agent or another simple based on create_sql_agent. Aug 15, 2024 · As an example of a multi-agent workflow, I would like to build an application that can handle questions from various domains. Oct 11, 2024 · LangGraph is a framework for building stateful, multi-agent applications using language models. 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 Here we focus on how to move from legacy LangChain agents to more flexible LangGraph agents. To enable the agent to function end FastAPI LangGraph Agent Template A production-ready FastAPI template for building AI agent applications with LangGraph integration. py) or using LangGraph (app-langgraph. We began by designing a flexible LangGraph workflow to If using python, for example, the LangGraph agent is defined in backend_py/my_agent. May 16, 2025 · LangGraph 공식문서 (https://langchain-ai. md Advanced SQL Agent API This Flask-based API provides Advanced SQL query analysis and visualization services using LangChain and LangGraph. langgraph / examples / multi_agent / agent_supervisor. The fundamental concept behind agents involves employing 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. This guide covers environment setup, data retrieval, vector store with example code. It leverages langgraph for state management and OpenAI's GPT for intelligent query generation and response formatting. While it served as an excellent starting point, its limitations became apparent when dealing with more sophisticated and customized agents. LangGraph — used by Replit, Uber, LinkedIn, GitLab and more — is a low-level orchestration framework for building controllable agents. The process is broken down into several key steps, represented as nodes in LangGraph: Fetch available tables – Retrieve all available tables from the database. Learn how to build 3 types of planning agents in LangGraph in this post. db database for demonstration. Build resilient language agents as graphs. Samples on how to use the langchain_sqlserver library with SQL Server or Azure SQL as a vector store are: test-1. It can recover from errors by running a generated query, catching the traceback and regenerating it Example Input: table1, table2, table3 sql_db_list_tables: Input is an empty string, output is a comma-separated list of tables in the database. We’ve built an SQL agent that answers queries from a SQL database. Learn about different architectures, memory, human in the loop, multi-agent systems and more. 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. Execute SQL query: Execute the query. Deploy and scale with LangGraph Platform, with APIs for state management, a visual studio for debugging, and multiple deployment options. This repository demonstrates the use of LangChain and LangGraph for SQL query generation, execution and validation. Jan 14, 2025 · Leverage LangGraph to orchestrate a powerful Retrieval-Augmented Generation workflow Jun 27, 2024 · Text to SQL is one the many LLM use cases that is getting attention. Some features were not in GA, so I signed up for the… In this guide, we'll learn how to create a simple prompt template that provides the model with example inputs and outputs when generating. , SQLite or CSV In this cookbook, we will walk through how to build an agent that can answer questions about a SQL database. 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. example as a template. Jun 20, 2024 · To customize the prompt used by the create_sql_agent function, you can create a custom prompt template and pass it to the create_sql_agent function. Chatbots: Build a chatbot that incorporates memory. Sep 12, 2024 · The entire workflow is orchestrated using LangGraph Cloud, 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. In this notebook we will show how those parameters map to the LangGraph react agent executor using the create_react_agent prebuilt helper method. 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. Now, we can initialize the agent with the LLM and the tools. Dec 31, 2024 · Rexera: Great example of "single agent -> multi agent but uncontrollable (CrewAI) -> controllable multi agent (LangGraph)" journey that we see many user go through Komodo Health: Exciting to see agents working in highly-regulated domains like healthcare Airtop: Web agents are a big area, so it's great to see them for browser automation Mar 10, 2024 · LangGraph LangGraph, using LangChain at the core, helps in creating cyclic graphs in workflows. First, let us see the current SOTA text to sql workflow: Schema and Metadata Extraction: The system processes the provided database (e. Multi-agent using Genie and LangGraph Open notebook in new tab Copy to clipboard Expand notebook Jan 23, 2024 · Each agent can have its own prompt, LLM, tools, and other custom code to best collaborate with the other agents. For detailed documentation of all SQLDatabaseToolkit features and configurations head to the API reference. py # Manages prompt templates ├── config. Build controllable agents with LangGraph, our low-level agent orchestration framework. We will have a set of expert agents, each specializing in different types of questions, and a router agent that will find the best-suited expert to address each query. To improve your LLM application development, pair LangGraph with: LangSmith — Helpful for agent evals and observability. Convert question to SQL query: Model converts user input to a SQL query. 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 execute queries in a DSL, such as SQL. 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. Given an input question, create a syntactically correct {dialect} query to run, then look at the results of the query and return the answer. 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. Azure SQL DB, Langchain, LangGraph and Chainlit Sample RAG pattern using Azure SQL DB, Langchain and Chainlit as demonstrated in the #RAGHack conference. SQL Database Agent — Converts natural language queries into executable SQL. py # Implements safety checks ├── nodes. py # Defines the agent's state ├── prompts. Jun 26, 2024 · 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. While langchain provides integrations and composable components to streamline LLM application development, the LangGraph library enables agent orchestration — offering customizable architectures, long-term memory, and human-in-the-loop to reliably handle Example Input: table1, table2, table3 sql_db_list_tables: Input is an empty string, output is a comma-separated list of tables in the database. Unless the user specifies a specific number of examples they wish to obtain, always limit your query to at most 5 results. 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 sample is build using plain LangChain (app. The prompt must have input keys: tools: contains descriptions and arguments for each tool. py # Contains utility functions and tools ├── guardrails. Here’s an example: When generating the query: Output the SQL query that answers the input question without a tool call. Agents: Build an agent that interacts with external tools. This workflow leverages the pybaseball Python library to extract data which is then used for analysis based on the user's request. May 16, 2025 · It covers the message routing architecture, node interactions, and how user queries flow through the system to generate appropriate responses. This 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. Answer the question: Model responds to user input using the query results. However, LangGraph’s allows for the integration of various models, parameters, and tasks within each agent. LangGraph ReAct Agent Template This template showcases a ReAct agent implemented using LangGraph, designed for LangGraph Studio. The agent can store, retrieve, and use memories to enhance its interactions with users. Plus, learn about LangGraph Cloud in open beta. Feb 13, 2024 · Plan and execute agents promise faster, cheaper, and more performant task execution over previous agent designs. 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 agent leverages generative AI to: Sep 6, 2024 · LangGraph is a library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows. So, assume this example: You wish to build a RAG based retrieval system over your knowledge base Jun 6, 2025 · LangGraph is a powerful open-source framework designed to simplify building stateful, multi-agent applications using natural language and… LangChain Samples Make sure the create an . Compared… 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. Jun 26, 2024 · return {"output": response} In this example, all three agents use OpenAI’s model. Step-by-step tutorial for developers to create task-oriented agents. Jun 17, 2025 · We will be using LangGraph to construct the agent. 🚀 Features LangGraph Integration — Uses LangGraph to manage agent execution and workflows. This post explores how Waii’s capabilities can enhance LangGraph applications for conversational analytics. 1 that can answer questions about weather, travel, and general information related to India. Learn how to build agent systems with LangGraph. Mar 18, 2024 · Conducting debate and deciding a winner using Multi-Agent orchestration with codes and example This agent is solely used to demonstrate different UI components you can render with LangGraph, and will not actually generate new code. py # Orchestrates the main workflow Sep 18, 2024 · Conclusion In this blog, we’ve explored the development of a sophisticated, voice-enabled SQL agent using LangGraph, Groq, and Flask. LangChain agents (the AgentExecutor in particular) have multiple configuration parameters. It's based on the official LangGraph tutorial, adapted to demonstrate how to integrate MCP servers as tools. For information about specific node implementations, see Router Node, Music Node, Customer Node, and Tools Integration. 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. agent_scratchpad: contains previous agent actions and tool outputs as a string. Aug 21, 2023 · A step-by-step guide to building a LangChain enabled SQL database question answering agent. When building a multi-agent system using LangGraph, helper functions play a crucial role in creating and managing agent nodes. 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. Mar 2, 2024 · LangGraph and Ollama are two cutting-edge libraries that, when combined, can significantly enhance the capabilities of Python applications… 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. Why AI agent . Dec 13, 2024 · This is where a LangChain SQL Database Agent becomes valuable. py # Defines workflow nodes for LangGraph ├── workflow. 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 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 May 16, 2025 · 10 LangGraph project ideas and examples to build intelligent langgraph agents for real-world applications and gain valuable hands-on experience. By leveraging language models, these agents can understand and process user requests, translating them into SQL commands that can be executed against a database. 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). py: Basic sample to store vectors, content and metadata into SQL Server or Azure SQL and then do simple similarity searches. In this guide we'll go over the basic ways to create a Q&A system over tabular data 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. A few-shot prompt template can be constructed from either a set of examples, or Aug 7, 2024 · LangGraph v0. So, let's begin without ado. Contribute to langchain-ai/langgraph development by creating an account on GitHub. 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. Feb 28, 2025 · This document consolidates all core instructions and examples for using and extending LangGraph’s prebuilt ReAct agent. This is an example agent to deploy with LangGraph Cloud. tool_names: contains all tool names. This defines the logic within each node of the SQL agent, following the steps explained above. Always use this tool before executing a query with sql_db_query! Agents LangChain has a SQL Agent which provides a more flexible way of interacting with SQL Databases than a chain. These functions enhance code reusability and simplify interactions between agents. We can enforce a higher degree of control in LangGraph by customizing the agent. To learn more about evaluation strategies, check out our blog post. py) to define the RAG process. Create autonomous workflows using memory, tools, and LLM orchestration. py # Handles configuration and initialization ├── tools. Full details and video recording available here: RAG on Azure SQL Server. For example: "What songs do you have by Jimi Hendrix?" May 20, 2024 · How to build an agentic AI workflow using the Llama 3 open-source LLM model and LangGraph. Tools within the SQLDatabaseToolkit are designed to interact with a SQL database. from langgraph. 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. My goal is to implement this in Databricks, leveraging MLflow for model mana Evaluate LangGraph Agents In this tutorial, we will learn how to monitor the internal steps (traces) of LangGraph agents and evaluate its performance using Langfuse and Hugging Face Datasets. Here is an example of how to do this: The purpose of this repository is to demonstrate how LangGraph can be used to build a stateless multi-agent workflow to serve as an assistant for data analysis. Nov 30, 2024 · This tutorial demonstrates how to build an AI agent that queries SQLite databases using natural language. Feb 1, 2025 · Learn to build a RAG application with LangGraph and LangChain. ReAct agents are uncomplicated, prototypical agents that can be flexibly extended to many tools. Post from LangChain with code for Text to SQL using Mistral AI, Neon… 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 Jun 3, 2025 · Example notebook: Multi-agent system with Genie The following notebook shows you how to create a multi-agent system using LangGraph and Genie. 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 README. Below, we implement a simple ReAct-agent setup, with dedicated nodes for specific tool-calls. Orchestration Get started using LangGraph to assemble LangChain components into full-featured applications. Providing the LLM with a few such examples is called few-shotting, and is a simple yet powerful way to guide generation and in some cases drastically improve model performance. Retrieval Augmented Generation (RAG) Part 1: Build an application that uses your own documents to inform its responses. You can order the results by a relevant column to return the most interesting examples in the database. Jun 22, 2024 · In fact of that, LangGraph you could achieve best results in customisation and performance. Specifically, I want to build an agent that uses an adaptive RAG chain and an SQL agent. prebuilt import create_react_agent system_prompt = """ You are an agent designed to interact with a SQL database. Apr 16, 2025 · Sample Agent Run You’d wrap the above steps as a LangGraph workflow from langgraph. g. Contribute to langchain-ai/langsmith-cookbook development by creating an account on GitHub. 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. Dec 9, 2024 · Today, we’ll explore how to create a sophisticated SQL agent using LangGraph, a powerful library for building complex AI workflows. A common application is to enable agents to answer questions using data in a relational database, potentially in an Sep 6, 2024 · LangGraphのGitHubリポジトリには、 examples として、LangGraphを使ったさまざまな実装が共有されています。 このexamplesの中から Build a Customer Support Bot のnotebookを参考に、エージェントの作り方を学びたいと思います。 本notebookはPart1からPart4で構成されています。 すべて航空会社のカスタマーサポート Build resilient language agents as graphs. SQLDatabase Toolkit This will help you get started with the SQL Database toolkit. Prompt Engineering — Custom prompt templates for accurate query generation. 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. Feb 21, 2025 · """ project/ │ ├── state. io/langgraph/tutorials/sql-agent/)를 참고하여 작성했으며, 공식문서에서는 OpenAI를 이용해서 만든걸 최신 모델인 Qwen3을 이용해 적용하는 방법을 소개하겠습니다. We'll also show how to evaluate it in 3 different ways. Jan 31, 2025 · Discover how to create a multi-agent chatbot using LangGraph. sql_db_query_checker: Use this tool to double check if your query is correct before executing it. This agent will be capable of understanding questions about 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. It is a ReAct agent (Reason + Act) that combines LangGraph’s SQL toolkit with a graph-based execution. 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. 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. Feb 23, 2024 · In the end of January, 2024, I received an email about LangGraph and LangSmith. ipynb Cannot retrieve latest commit at this time. Jun 28, 2024 · Hello, thanks for this amazing explanation. This guide covers online and offline evaluation metrics used by teams to bring agents to production fast and reliably. Jan 14, 2025 · SQL agents are designed to interact with SQL databases using natural language queries. Waii provides text-to-SQL and text-to-chart capabilities, enabling natural language interactions with databases and data visualization. The 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). This tutorial shows how to implement an agent with long-term memory capabilities using LangGraph. Nov 29, 2024 · Learn to build a custom AI agent using LangGraph with RAG, NL2SQL, and Web Search. Simple for someone who never saw LangChain how it works. eagyvsoqrwmnorkwwxqekmffamevukrhmcerprafqt