Langchain sql agent github. I used the GitHub search to find a similar question and.

• Langchain sql agent github. This app will generate SQL queries using an LLM, execute them in DuckDB, and use the results to answer user questions. LLMs make it possible to interact with SQL databases using natural langugae. Built using LangChain, OpenAI/Groq LLMs, and Streamlit, this AI-agent can generate, execute, and refine SQL queries dynamically while providing explanations for the Youtube-Tutorials / Langchain_Agents_SQL_Database_Agent. It uses LangChain and FAISS to convert database content into vector format and generate SQL queries based on natural language questions. The dataset format should be May 28, 2024 · To fine-tune an open-source LLM like LLaMA 3 to a specific LangChain agent format, such as LangChain's create_sql_agent, you need to follow these steps: Prepare the Dataset: The dataset should include examples of inputs and expected outputs that the agent should handle. py: Simple app using StreamlitChatMessageHistory for LLM conversation memory (View the app) mrkl_demo. g. Once the code is stabilized, register the model, run evaluation, register and deploy. Natural language querying allows users to interact with databases more intuitively and efficiently. Contribute to langchain-ai/langgraph development by creating an account on GitHub. This method allows you to save the context of a conversation, which can be used to respond to queries, retain history, and remember context for subsequent queries. The goal of this repo is to provide users the ability to use Amazon Bedrock and generative AI to take natural language questions, and transform them into relational database queries against MSSQL Databases using LangChain SQL Agent. create_sql_agent (llm [, ]) Construct a SQL agent from an LLM and toolkit or database. Samples on how to use the langchain_sqlserver library with SQL Server or Azure SQL as a vector store are: test-1. js application that integrates a SQL agent using Langchain. LangChain’s ecosystem While the LangChain framework can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools when building LLM applications. A sample application demonstrates the usage of Langchain and SQL Agent - trguduru/langchain-sql-agent Construct a SQL agent from an LLM and toolkit or database. Nov 14, 2023 · LangChain SQL - Agent Setup. ts - Basic SQL query generation using generate_sql_query function agent. This repository demonstrates how to build a multi-agent AI system using: LangChain for natural language to SQL translation. We will also require langgraph to demonstrate the use of the toolkit with an agent. The agent is powered by Azure OpenAI's GPT model and is configured to interact with a SQLite database of the Chinook digital media store. This project is an AI-powered SQL query agent that can answer natural language questions by querying a SQLite database. Mar 10, 2010 · Langchain SQL Agent Bootstap This is a simple App for testing LLM to SQL commands on a sqlite database using Langchain SQL Agent. Aug 22, 2023 · HI! I recently started using Langchain to create some sort of an assistant for my user to answer any questions related to their data in my database. I used the GitHub search to find a similar question and C# implementation of LangChain. Agent Setup LangChain Agent: Created with create_sql_agent, which handles the logic of converting natural language into SQL queries. The project includes two example scripts: LangChain SQL Agent with TinyLlama A powerful SQL generation system that converts natural language queries into accurate SQL statements using LangChain, TinyLlama (via Ollama), and PostgreSQL. To improve your LLM application development, pair LangChain with: LangSmith - Helpful for agent evals and observability. Oct 29, 2024 · To customize the prompt template for the SQL query agent and achieve better results, you can follow these steps: Modify the Prompt Template: Ensure your prompt template is correctly structured and includes all necessary variables. Feb 19, 2024 · What's cooking in your code kitchen today? Yes, it is indeed possible to create an SQL agent for making queries on Google BigQuery using the latest version of LangChain. py: A A powerful text-to-SQL agent that converts natural language queries into SQL statements using LangGraph and LangChain A Streamlit app that allows users to query SQLite or MySQL databases using LangChain agents powered by Groq's LLM for natural language processing. GitHub Gist: instantly share code, notes, and snippets. AutoGen for coordinating AI agents in collaborative workflows. May 28, 2024 · To fine-tune an open-source LLM like LLaMA 3 to a specific LangChain agent format, such as LangChain's create_sql_agent, you need to follow these steps: Prepare the Dataset: The dataset should include examples of inputs and expected outputs that the agent should handle. This project demonstrates how to build a powerful multimodal agent for document analysis using Docling for PDF extraction and LangChain for creating AI chains and agents. The create_sql_agent function is still supported and can be used to construct a SQL agent from a Language Model and a toolkit or database. I used the GitHub search to find a similar question and This project demonstrates how to build an agentic system using Large Language Models (LLMs) that can interact with multiple databases and utilize various tools. Azure OpenAI GPT-4 for intelligent language understanding and generation of SQL queries in PostgreSQL. It leverages the power of OpenAI's GPT models and LangChain's memory and prompt engineering capabilities to optimize and execute queries, making it a robust tool This project integrates LangChain with a MySQL database to enable conversational interactions with the database. This allows you to interact with your BigQuery data using natural language, leveraging the power of Gemini's advanced language understanding capabilities. The repo comes with a setup script that loads a sqlite database with some sample data. The application interacts with a PostgreSQL database to retrieve and process data. This uses prompt templates to generate queries and show results from the queries executed via custom tools - MohakSriv/Langchain-SQL-Agent Apr 12, 2024 · However, based on the current version of LangChain you're using, there isn't a direct parameter in create_sql_agent to pass the schema explicitly to avoid the sql_db_schema invocation. Ask questions in plain English and get instant answers from your data! 🤖 Currently, SQLChat focuses on SELECT queries, enabling you to retrieve and analyze sql_agent. Toolkit is created using ‘db’ and Files file. After setting up the environment and installing Jun 28, 2024 · Hello, thanks for this amazing explanation. Full details and video recording available here: RAG on Azure SQL Server. For create_sql_agent, this would typically involve SQL queries and the corresponding responses. My current approach involves using the SQL agent with Langraph. The goal is to enable the agent to process user queries, interact with an SQL database, and return coherent, context-aware 🚀 An intelligent AI-powered SQL agent that allows users to interact with a PostgreSQL database using natural language queries. These systems will allow us to ask a question about the data in a database and get back a natural language answer. I've tried too many agents changing the whole toolkits and agent types still I get some errors regarding unexpected argument was passed. I am able to use create_sql_query_chain just fine against either an OpenAI LLM or Jul 11, 2024 · Description I'm trying to make an SQL agent with hugging face llm but it seems like the agent settings are only supposed to work with openai. Session Management Jan 23, 2024 · Based on your requirements, it seems like you want to modify the create_sql_agent function to return only the SQL query to reduce the latency caused by high completion tokens when generating HTML tables and summaries with LLM (GPT-4). The SQL Agent provided by LangChain is a tool that allows you to interact with SQL databases using natural language. Learn to use LangChain's SQL Database Chain and Agent with large language models to perform natural language queries (NLQ) of Amazon RDS for PostgreSQL. The agent is integrated with a set of tools, such as an SQL tool, and utilizes a memory buffer to maintain conversation history across sessions. agents. py: Simple streaming app with langchain. This README provides a step-by-step guide on how to set up and use the SQL Database Agent. Ask questions like "What is the average student score?" or "List top 5 entries from the student table" — and let the agent do the rest. I used the GitHub search to find a similar question and Langchain Agents. This project demonstrates how to use LangChain to build an AI agent that can query the Chinook database using SQL. You can achieve this by creating a new function that wraps around the create_sql_agent function. agent. In simple terms, langchain is a framework and library of useful templates and tools that make it easier to build large language model applications that use custom data and external tools. test-2. Users can ask natural language questions, which the system translates into SQL queries, executes against a SQLite database, and then provides detailed answers based on the query results. tsx # UI component for interacting with the SQL agent Interact with your SQL databases using natural language! This project lets you chat with SQLite or MySQL databases via a conversational agent built using LangChain, Streamlit, and Groq's ultra-fast LLMs like LLaMA3. Specifically, check the equality operator (==) used for llm and correct it to a single =. my-langchain-sqlagent-app ├── components │ └── AgentUI. ChatOpenAI (View the app) basic_memory. py) to define the RAG process. Jul 12, 2025 · LangChain SQL Agent Tutorial 2025. This code demo's how you can connect to an SQL database using langchain SQL agent, query the data with natural language and send it to the LLM for generating a insightful response create_sql_agent # langchain_community. 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 Jul 12, 2024 · Let's work together to solve this problem! To resolve the issues with creating an SQL agent using LangChain, you can follow these steps: Correct the create_sql_agent Function Call: Ensure that the parameters passed to the create_sql_agent function are correct. By leveraging the power of LangChain, SQL Agents, and OpenAI’s Large Language Models (LLMs) like GPT, we have created an application that enable users to query databases using NLP Jan 20, 2025 · LangChain + OpenAI + Azure SQL. - langchain-crashcourse/sql-agent-notebook. 这是一个基于 LangChain 和 DeepSeek 大语言模型构建的 SQL 智能代理系统，通过 Gradio 提供用户友好的界面 agent_executor_kwargs (Optional[Dict[str, Any]]) – Arbitrary additional AgentExecutor args. This project integrates LangChain ,SQLAlchemy, and OpenAI LLM to create a custom agent capable of interacting with local databases. LangChain Looker SQL Agent Connect LangChain to your Looker instance for conversational data querying using Looker's Open SQL Interface and its governed semantic layer. sql. py: An agent that replicates the MRKL demo (View the app) minimal_agent. Sep 23, 2024 · Checked other resources I added a very descriptive title to this question. ipynb at main · bhattbhavesh91/langchain-crashcourse Source code for the upcoming blog post, Generative AI for Analytics: Performing Natural Language Queries on Amazon RDS using SageMaker, LangChain, and LLMs. The LangChain Crash Course Repository is a concise and comprehensive collection of learning materials for the LangChain programming language. py) or using LangGraph (app-langgraph. This is not required to use the toolkit. The user will ask something general like "How ma Sep 21, 2023 · To add memory to the SQL agent in LangChain, you can use the save_context method of the ConversationBufferMemory class. Toolkit: Uses SQLDatabaseToolkit for database interactions. 8 or higher installed. This project demonstrates the integration of LangChain's SQL utilities and ChatGroq, a language model, to create an intelligent agent that can generate and execute SQL queries based on natural language user inputs. To use Google BigQuery, you would need to create an instance of SQLDatabase that connects to your Google BigQuery database and pass it to the create_sql_agent function. For this, four datasets from the European Statistical Office (Eurostat) are loaded Feb 19, 2024 · The function create_sql_agent you've used in your code is designed to construct a SQL agent from a language model and a toolkit or database. A step-by-step guide to building a LangChain enabled SQL database question answering agent. Azure SQL DB, Langchain, LangGraph and Chainlit Sample RAG pattern using Azure SQL DB, Langchain and Chainlit as demonstrated in the #RAGHack conference. Contribute to langchain-ai/langsmith-cookbook development by creating an account on GitHub. It leverages natural language processing (NLP) to query and manipulate database information using simple, conversational language. LangChain / LangGraph SQL Agent Demo This repository demonstrates the use of LangChain and LangGraph for SQL query generation, execution and validation. The SQL Database Agent is a tool designed to interact with SQL databases using natural language queries. I searched the LangChain documentation with the integrated search. Oct 27, 2024 · LangChain SQL Agent This project is a system that connects to a PostgreSQL database and runs AI-powered SQL queries. If anyone knows how to fix it please help. Integrated Ollama for language understanding and Flask for the web UI, reducing data analysis effort by 50% for non-technical users. The agents leverage a language model to interpret user queries, translate them into SQL statements, execute these statements against a database, and present the results. Aug 21, 2023 · In this tutorial, we will walk through step-by-step, the creation of a LangChain enabled, large language model (LLM) driven, agent that can use a SQL database to answer questions. py: Basic sample to store vectors, content and metadata into SQL Server or Azure SQL and then do simple similarity searches. About Built a natural language chatbot interface for SQL databases using LangChain Toolkit and Agents. chat_models. extra_tools (Sequence[BaseTool]) – Additional tools to give to agent on top of the ones that come with SQLDatabaseToolkit. This makes data retrieval from the database faster and more accurate. . Oct 27, 2023 · langchain. We try to be as close to the original as possible in terms of abstractions, but are open to new entities. ), and base prompt Run data_setup to create data tables for testing Review and customize 01_sql_react_agent as needed Test the agent code using 02_evaluate. Mar 10, 2025 · We will explain how to implement an SQL Agent using LangChain, OpenAI API, and DuckDB , and how to turn it into an application with Morph . py: Read books reviews from a file, store it in SQL Server or Azure SQL, and then do similarity searches. The key frameworks used in this project include OpenAI, LangChain Example application for constructing and running an LLM-based LangChain SQL Agent based on GPT-4o mini that can dynamically query a database and invoke multiple visualization tools - EliasK93/LangC This project integrates LangChain with a PostgreSQL database to enable conversational interactions with the database. I used the GitHub search to find a similar question and LangChain SQL Agent with TinyLlama A powerful SQL generation system that converts natural language queries into accurate SQL statements using LangChain, TinyLlama (via Ollama), and PostgreSQL. Aug 18, 2024 · Checked other resources I added a very descriptive title to this question. - tryAGI/LangChain Tutorial to LangChain SQL Agent This repo contains code snippets and datasets used in my Medium article "A Beginners Guide to LLM Agents and Toolkits". It utilizes the LangChain library and various language models, such as ChatGroq and ChatOpenAI, to generate SQL queries and provide responses. The main function create_sql_agent is responsible for constructing this agent, and it can be customized with various parameters such as the toolkit or database to use, agent type, prompt Aug 2, 2024 · I am following the SQLAgent tutorial from Langgraph and adding RAG to it. While it generally works fine, we've encountered an issue where the Large Language Model (LLM) truncates the expected answer. For demonstration purposes, we will access a prompt in the LangChain Hub. Local LLM Applications with Langchain and Ollama. The assistant connects to a PostgreSQL database and dynamically generates SQL queries based on natural language inputs. This tool extracts the table names and database metadata given the context, but the generated query isn’t always Jul 21, 2024 · Checked other resources I added a very descriptive title to this question. Contribute to nelfaro/Langchain-Ollama-SQL development by creating an account on GitHub. LangChain SQL Agent provides a more flexible way of interacting Jul 12, 2024 · Checked other resources I added a very descriptive title to this question. This project is a Streamlit-based web application that allows users to interact with SQL databases (SQLite or MySQL) using the LangChain framework and Example application for the construction and inference of an LLM-based LangChain SQL Agent that can dynamically query a database and invoke multiple visualization tools. Implemented schema-aware prompts and conversational context handling for complex query generation. I have mentioned the view name in the System Prompt and I have passed view_support=True to the SQLDa Jul 5, 2023 · Natural language querying allows users to interact with databases more intuitively and efficiently. MPT, from MosaicML) to query Databricks SQL. In this guide we'll go over the basic ways to create a Q&A system over tabular data in databases. #12458 Mar 27, 2024 · The current structure of the SQL agent in the LangChain codebase involves creating a SQL agent from a language model (LLM) and a toolkit or database. The LangChain agents will interact with data from the database when queried. ipynb Cannot retrieve latest commit at this time. Ensure you have Python 3. The sample is build using plain LangChain (app. README langchain-sql-databricks TLDR; this repo contains some starter examples for working with Langchain and LLM Instruction models (e. This repository demonstrates how to build a conversational SQL Query Assistant using LangChain's create_sql_agent. This repo is intended to be a starter for Langchain and also a starter for programming with co-pilot GPT-4. yaml with the Databricks Resources (warehouse, hostname, catalog, schema), model resources (model endpoints, temperature, max tokens, etc. Feb 7, 2024 · It seems like the create_sql_agent function in LangChain is indeed ignoring the custom prefix and suffix when the agent_type is set to "zero-shot-react-description". I used the GitHub search to find a similar question and Apr 9, 2024 · The docs describe how to create an SQL agent using OpenAI as an example but implying that the approach is generic. But also I would like to use CromaDB to save embeddings with local knowledge of the database structure, columns content, So this means thy I wou Mar 24, 2024 · Checked other resources I added a very descriptive title to this question. Contribute to TheAILearner/Langchain-Agents development by creating an account on GitHub. I will be using django rest framework for Post and get requests when a user query a search and the LangChain agents will retrieve knowledge from the database. create_sql_agent / SQLDatabaseToolkit - Agent never gets DB schema and tries to query nonexistent table names. ts - Agent-based SQL querying with formatted output examples_of_langchain_db_llm - Advanced graph-based query processing examples About A LangChain enabled SQL database question answering agent Activity 0 stars 1 watching This project is a Next. agent_toolkits. Oct 1, 2023 · How to build a LangChain agents that can interact with data from a postgresql database of an HR systems. It showcases the seamless integration of tabular and textual data extracted from PDFs into a unified query system This guide provides detailed steps to create a SQL agent that leverages Langchain, Composio, and ChatGPT to execute SQL queries, document them and plot graphs based on the data. It highlights the use of SQL agents to efficiently query large databases. This project demonstrates how to build an interactive SQL query system using LangChain, GPT-4, and a SQLite database. Jan 3, 2024 · I am trying to build a langchain SQL database agent where I want to query only one view for now. The project includes a custom Python script for extended functionality, integration with the Gemini API for advanced NLP tasks, a Jupyter notebook guide The model interprets user queries and formulates SQL queries to interact with the database. By leveraging the power of LangChain, SQL Agents, and OpenAI’s Large Language Models (LLMs) like Update agent_config. Langchain Agents. Feb 14, 2024 · Checked other resources I added a very descriptive title to this question. Jan 19, 2024 · As for the second part of your question, I wasn't able to find specific information on how the SQL agent in LangChain handles database connections, specifically for Oracle Database, within the repository. This project is designed to create and configure a ReAct (Reasoning and Acting) agent using LangChain and OpenAI's GPT-4o model. Contribute to sugarforever/LangChain-Tutorials development by creating an account on GitHub. It allows users to interact with a SQL database through a user-friendly interface. This repository demonstrates how to use a LangChain SQL agent to query Google Cloud BigQuery using the Gemini Generative AI through Vertex AI. base. The dataset format should be This project demonstrates how to use LangChain to build agents that can process natural language queries and interact with SQL databases. db (Optional[SQLDatabase]) – SQLDatabase from which to create a SQLDatabaseToolkit. Langchain_SQL_Agent Enterprise data is often stored in SQL databases. Build resilient language agents as graphs. We will cover implementations using both chains and agents. I used the GitHub search to find a similar question and TLDR; this repo contains some starter examples for working with Langchain and LLM Instruction models (e. This project provides a Python package, langchain-looker-agent, that allows you to build LangChain agents capable of interacting with your Looker data via its Avatica JDBC driver. create_sql_agent( llm: BaseLanguageModel, toolkit: SQLDatabaseToolkit | None = None, agent_type: AgentType | Literal['openai-tools', 'tool-calling'] | None = None, callback_manager: BaseCallbackManager | None = None, prefix: str | None = None, suffix: str | None = None, format_instructions: str | None = None, input_variables: List This repository contains reference implementations of various LangChain agents as Streamlit apps including: basic_streaming. It is designed to be more flexible and more powerful than the standard SQLDatabaseChain, and it can be used to answer more general questions about a database, as well as recover from errors. 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. Thanks System Info Oct 31, 2024 · We followed the LangChain tutorial to query our Azure SQL database using LangChain and OpenAI through a SQL Agent. Contribute to padmaDS/Langchain-sql-agent development by creating an account on GitHub. The language model used is OpenAIs GPT-4o mini. Azure Database for PostgreSQL for data storage and querying. 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. LangChain offers SQL Chains and Agents to build and run SQL queries based on natural language prompts. The application showcases a shipping company Dive into the world of conversational data exploration with SQLChat! 🚀 This project empowers you to interact with your SQL databases using natural language, thanks to the magic of LangChain, open-source LLMs (via Groq), and Streamlit. Nov 25, 2023 · I would like to use SQL Agent to query database. cswslf uyjyj ypzfyu xjak xhvgvs kjnhi fpsl arenu vcnr sesakt