Llm sql agent github. LLM (Large Language .

Llm sql agent github. All are working together to help you with your SQL request 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. RAG (Retrieval-Augmented Generation): Retrieves answers from the SQL database using a SQL query generated by LLM for users' questions in plain text, for specific and relevant questions (related to the 4 currencies BTC, ETH, SOL, and DOT, as mentioned below). For instance, it may not be aware of the actual data values in a column, leading to incorrect queries. In this notebook we'll explore agents and how to use them in LangChain. Contribute to disler/multi-agent-postgres-data-analytics development by creating an account on GitHub. For comprehensive details on the architectural patterns mentioned below, please refer to the accompanying article on Medium By including foreign key constraints, the LLM can create SQL queries with proper joins, ensuring more accurate data retrieval. py: python Copy Edit import os from sqlalchemy import create_engine, MetaData, Table, Column, Integer, String, Date Nov 28, 2024 · What would you like to see? I have a problem with the SQL-Agent: Connection to my MySQL-Database does not work. ai/docs/ agent sql database ai data-visualization text-to-sql rag llm Readme MIT license SQL Agent powered by LLMs. The SQL Agent provided by LangChain is a tool that allows you to interact with SQL databases using natural language. The failure is primarily due of a lack of the LLM's knowledge of the particular dataset it’s being asked to query. It translates natural language into optimized SQL, executes queries, and visualizes the results. Feb 12, 2018 · agent sql database ai data-visualization text-to-sql rag llm Updated on Apr 9 Python Aug 21, 2023 · A step-by-step guide to building a LangChain enabled SQL database question answering agent. LLM-powered SQL assistant using FastAPI and GPT4All - bonilokesh/LLM-SQL-Agent Oct 31, 2024 · We followed the LangChain tutorial to query our Azure SQL database using LangChain and OpenAI through a SQL Agent. 5, the LangChain framework, and an Agentic RAG (Retrieval-Augmented Generation) pipeline to transform the way we interact with databases. Using a chain-of-thought mechanism, it breaks Dec 1, 2024 · By integrating a powerful Llama 3 model, SQL database tools, and agent-based automation, you’ll learn how to create a seamless pipeline for handling database queries, analyzing results, and Sample database PostgreSQL See it in action Tech Stack Frontend: NextJS, TailwindCSS, Flowbite Backend: ExpressJS, NestJS Databases: Sqlite, PostgreSQL, MongoDB LLM: Langchain SQL Agent with Open AI LLM Jul 3, 2024 · How are you running AnythingLLM? Docker (local) What happened? After setting up a SQL Connector (MySQL) the agent answer there is no active connection to the database if I ask for the list of the t May 13, 2024 · The agent successfully utilized the Dataherald text-to-SQL tool to generate the SQL query and then proceeded to generate a plot based on the results obtained from executing the SQL query. It also includes **SQL injection detection** and **sensitive data logging** for compliance and security. Agentic AI personal Laboratory. Built with LangGraph, LangChain, and Streamlit, the system allows users to chat with any SQL database, providing intuitive query generation and database exploration capabilities The SQL Agent Tool is a Python-based utility designed to interact with PostgreSQL databases, allowing users to execute SQL queries safely and efficiently. LLM driven chat bot for querying a SQL database. I tried with several LLMs It would be helpful to have a "Test Connection" button to s Feb 19, 2024 · SQL Agent for Google Big Query🤖 Hey @hugoferrero! Great to see you back here, diving into the possibilities with LangChain and Google BigQuery. py: examples of using LLMs only for ontology matching. Contribute to jorgeandrespadilla/sql-agent development by creating an account on GitHub. A SQL agent to help you with your database. Mar 31, 2024 · The above video shows how SQL LLM agent is interacting with sqlite DB This blog introduces an agent that communicates with SQL databases, eliminating the need to know the schema beforehand. - asimadnan/LLM_SQL_agent This project enables users to **generate SQL queries from natural language** using **LLM** of their choice while enforcing **Role-Based Access Control (RBAC)** and **Row-Level Security (RLS)**. We also provide tutorial slides to summarize the key points of this survey. Contribute to EllianAbe/sql-agent development by creating an account on GitHub. Contribute to Atomix2402/LLM-Driven-SQL-Agent-Interface development by creating an account on GitHub. Apr 29, 2023 · In the documentation it is mentioned to create toolkit without LLM agent, but its one of the required fields for toolkit. To improve your LLM application development, pair LangGraph with: LangSmith — Helpful for agent evals and observability. That’s where the LLM aspect comes in; allowing the user the opportunity to query the information they desire is the solution! Please find below the architecture of the agent: However, a simple SQL generator isn’t the answer! There are several factors to consider, not the least of which is security. For detailed documentation of all SQLDatabaseToolkit features and configurations head to the API reference. But when i refresh the page nothing have changed Contribute to DenVelc/llm-sql-wolfram-assistant development by creating an account on GitHub. For this, four datasets from the European Statistical Office (Eurostat) are loaded The SQL Agent is a conversational AI tool designed to interpret natural language requests and automatically generate SQL queries against a target database. CrewAI Agents & Tasks: Automates SQL querying, data analysis, and report writing using AI agents. Click on image to enlarge This project demonstrates a simple yet powerful way to interact with SQL databases through a conversational interface. 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. 3 model (Open Source LLM). But I ask @agent Checking what are the available databases? The agent cannot connect to my SQL. PandasAI makes data analysis conversational using LLMs and RAG. I have used python to connect to my MySQL and can r Build effective agents using Model Context Protocol and simple workflow patterns - lastmile-ai/mcp-agent This is the official repository for the paper "MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQL". It integrates with multiple LLM providers (Groq, Google Gemini, OpenAI, DeepSeek) to convert natural language queries into SQL, and includes a robust test suite to ensure reliability. Build resilient language agents as graphs. LLM Chains: Workflows where the output of one LLM becomes the input for another task. We are excited to share this sandbox that enables you explore the capabilities of LLM to generate SQL queries (or SELECT statements): NL2SQL. toolkit (Optional[SQLDatabaseToolkit]) – SQLDatabaseToolkit for the agent to use. Contribute to Acilikola/llm-chatbot-langchain_streamlit_sql development by creating an account on GitHub. This agent involves tools like: sql_reply_tool: Uses an LLM to format the SQL result into a natural language response. Contribute to salonicmate/LLM_SQL_Agent development by creating an account on GitHub. This system is designed to translate natural language queries into SQL commands, enabling seamless interaction with a MySQL database. 1) This project is a Streamlit-based web application that uses LangChain and Groq's Llama 3. SQL Query Generator with LLM (Llama 3. Local LLM SQL agent notebook for SQL Server using Ollama and LangChain - tyronLee/Local-AI-SQL-Agent This solution integrates Amazon Bedrock agents, AWS Lambda, Amazon Athena, and AWS Glue to process real-time user queries by translating natural language inputs into SQL queries to interact with data stored in Amazon S3. It also includes advanced features like transaction Using a Local LLM that does not require an API key or even an internet connection instead of the subscription-based OpenAI. Apr 9, 2024 · The docs describe how to create an SQL agent using OpenAI as an example but implying that the approach is generic. It's designed to be an educational tool for security researchers, developers, and enthusiasts to understand and experiment with prompt injection Oct 21, 2024 · Second Agent (User-Friendly Response Generation): Based on the metadata generated from the SQL validation step, I use a second agent to generate a user-friendly response. The toolbox will be Semantic Kernel (examples and labs in C#) and AI Large Language Models (LLMs) running as services in the Azure AI Foundry. It can help you to write SQL queries, understand the data, and search in easily. py: examples of using LLMs with context information for ontology matching. Chat with your database or your datalake (SQL, CSV, parquet). Immortal-Pi / LLM-SQL-Agent Public Notifications You must be signed in to change notification settings Fork 0 Star 0 0 0 0 Query a database through natural language. The language model used is OpenAIs GPT-4o mini. It leverages LLMs (like GPT-4o), ChromaDB for vector search, and hybrid retrieval (semantic + keyword search) to understand and execute database queries efficiently. 0 license Code of conduct This repository contains all the relevant codes for building a RAG enhanced LLM for Text-to-SQL, evaluation data and also instructions on how to evaluate the performance by test-suite-sql-eval through Docker and customize your Text-to-SQL evaluation pipeline based on own data by Langsmith. The sky is the limit! Depending on how you run AnythingLLM, you can create custom agent skills that can run extra processes like running a local Python script or, on Dec 6, 2023 · I'm using langchain sql database agent and python REPL tool. Using this input, the LLM generates SQLite-compatible SQL queries to respond to user requests expressed in natural language. LangChain Tools: Provides tools for listing tables, fetching schemas, and executing SQL queries. While it generally works fine, we've encountered an issue where the Large Language Model (LLM) truncates the expected answer. Feb 22, 2025 · In this guide, I will walk you through the process of creating an LLM-powered Database agent using Google’s Gemini model and LangGraph that can directly interact with a database to query and Nov 14, 2023 · LangChain SQL - Agent Setup. This repository contains advanced LLM-based chatbots for Q&A using LLM agents, and Retrieval Augmented Generation (RAG) and with different databases. Contribute to TheAILearner/Langchain-Agents development by creating an account on GitHub. LangChain-Chat-with-SQL-Database- A Streamlit app that allows users to query SQLite or MySQL databases using LangChain agents powered by Groq's LLM for natural language processing. Learn to set up and use LangChain for complex queries, making data-driven decisions easier and accessible to all, even without technical expertise. vanna. The llm agent is able to get the data from the database successfully, however when i request the agent to plot the data its failing with Oct 31, 2024 · Help, How to add SQL Agent and ability to analyze SQL data directly from SQL and LLM provides the insight of the data set based on the Conversation bot Prompt Management: Tools for optimizing interactions with LLMs. Using a SQL Server database instead of SQLite. In this paper, we show that context is everything, and with The all-in-one Desktop & Docker AI application with built-in RAG, AI agents, No-code agent builder, MCP compatibility, and more. llm_om_with_context. Contribute to padmapria/llm_sql_agent development by creating an account on GitHub. Everything - Reference / test server with prompts, resources, and tools Fetch - Web content fetching and conversion for efficient LLM usage Filesystem - Secure file operations with configurable access controls Git - Tools to read, search, and manipulate Git repositories Memory - Knowledge graph-based persistent memory system Jul 5, 2023 · A SQL agent for e-commerce data, featuring LLM-driven natural language to SQL, semantic table selection, optimal join planning, and multi-step query generation with validation. Technically, it is a group chat with multiple LLM agents: a product manager, a SQL developer, and a quality analyst. - sinaptik-ai/pandas-ai This repository contains advanced LLM-based chatbots for Q&A using LLM agents, and Retrieval Augmented Generation (RAG) and with different databases. 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. A "DuckDb Agent" in Phidata is a specialized agent that allows users to analyze data using the DuckDB database engine within the Phidata platform, essentially enabling direct SQL queries and data manipulation on datasets through the Oct 30, 2024 · I turned on the Agent SQL settings and connected. LLM bot with SQL agent. In this cookbook, we will walk through how to build an agent that can answer questions about a SQL database. Conversational CryptoDB. About Using LangChain's SQL Database Chain and Agent with various LLMs to perform Natural Language Queries (NLQ) of an Amazon RDS for PostgreSQL database. Contribute to abhinav-neil/rag-llm development by creating an account on GitHub. Aug 17, 2023 · The promise of having an autonomous AI agent that can answer business users’ plain English questions is an attractive but thus far elusive proposition. Contribute to yhyu/agentic-text2sql development by creating an account on GitHub. LLM's Limited Domain Knowledge The LLM has knowledge of the database schema but doesn't know about the underlying data. Contribute to nofilamer/LLM-SQL-Agent-FASTAPI development by creating an account on GitHub. The dataset format should be Evaluate the accuracy of LLM generated outputs. With this app, you can interact with a natural language interface to generate SQL queries, making it easier for both beginners and experienced SQL users to work with databases. In this workshop, we provide hands-on experience to help you understand how to AI-enable your applications or create new AI-powered services. Contribute to luknda/llm_sql_agent development by creating an account on GitHub. This project utilizes Groq with Llama3 in the backend and connects to a Microsoft SQL Server running locally. This project develops an LLM-driven conversational agent for business data. This project is a Streamlit-based web application that allows users to interact with SQL databases (SQLite or MySQL) using the LangChain framework and Groq's LLM. 📦 Step 1: Install Dependencies bash Copy Edit pip install openai langchain sqlalchemy streamlit 🧠 Step 2: Python Code (In-Memory Trade Assistant) Save this as nl_sql_assistant. They allow a LLM to access Google search, perform complex calculations with Python, and even make SQL queries. SQLDatabase Toolkit This will help you get started with the SQL Database toolkit. 1 model to generate SQL queries from natural language questions, run those queries on a connected SQL database, and convert the results back into a human-readable format. Perfect for students, analysts, and developers! - nileshsonawanes/llm-s The AI SQL Agent is an intelligent tool designed to translate natural language into SQL queries, connect to a database using provided credentials, fetch the data, and summarize the output to match conversational requirements. Jun 6, 2025 · Contribute to Bas1210/LLM_sql_agent development by creating an account on GitHub. Contribute to danieljpalmer/llm-analyst development by creating an account on GitHub. If agent_type is “tool-calling” then llm is expected to support tool calling. Contribute to langchain-ai/langgraph development by creating an account on GitHub. Dynamic SQL Generation When the app starts, it incorporates the database schema and key data into the instructions for the Foundry Agent Service. 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. InferenceClientModel allows you to call LLMs using Hugging Face's Inference API, either via Serverless or Dedicated endpoint, but you could also use any proprietary API: check out this other cookbook to learn how to adapt it. Our goal is to make data exploration accessible to non-technical users and reduce the data querying effort for analysts by up to 60-70%. These skills can be anything you want from a simple API call to even operating-system invocations. Streamlit based frontend to chat with your SQL db, the llm agent can run queries to answer questions. AnythingLLM allows you to create custom agent skills that can be used to extend the capabilities of your @agent invocations. It serves as a basic framework with the potential to expand SQL-LLM-Agent is a natural language interface for querying SQL databases. - GitHub - jayzerky/sql-agent: The SQL A Jun 28, 2024 · Hello, thanks for this amazing explanation. -For example if continent is passed on, llama will be able to modify that for countries as well Query a database through natural language. This app will generate SQL queries using an LLM, execute them in DuckDB, and use the results to answer user questions. I am able to use create_sql_query_chain just fine against either an OpenAI LLM or an Ollama LLM (examples below). About Text2SQL-Eval is a Text-to-SQL evaluating component for LLM trained on an open-source training dataset. Based on language model trends, we've created a river diagram of Text-to-SQL methods to Contribute to debabratapruseth/AI-agent-with-LLM-and-SQL development by creating an account on GitHub. Contribute to lindsay888/llm-langchain-mysql-project development by creating an account on GitHub. The Aug 4, 2023 · We’ve heard from many in the community who want to use Semantic Kernel to query their relational database using natural language expressions. Contribute to rahulyad011/LLM_Based_SQL_DB_Agent development by creating an account on GitHub. Memory: Incorporate memory for context retention across interactions. Agent: Entry point for user questions, determining the user question's type and directing it to the relevant node. Let’s start with the golden question: why not keep it simple and use a standard text-to-SQL pipeline? A standard text-to-sql pipeline is brittle, since the generated SQL query can be incorrect. The Amazon Bedrock agent, acting as the central orchestrator, receives user inputs from an interface hosted on an EC2 instance. A common application is to enable agents to answer questions using data in a relational database, potentially in an Langchain Agents. GitHub Gist: instantly share code, notes, and snippets. Contribute to langchain-ai/langsmith-cookbook development by creating an account on GitHub. Contribute to keysKuo/llm-sql-optimization development by creating an account on GitHub. We are passing SQL schema by default and the result can be optimized via passing example queries. RAG with LLM agents for SQL & graph databases. md file. SQL-LLM-Agent is a cutting-edge project that leverages OpenAI's GPT-3. I hope all's been well on your side! Yes, it is indeed possible to create an SQL agent in the latest version of LangChain to query tables on Google BigQuery. For create_sql_agent, this would typically involve SQL queries and the corresponding responses. We'll also show how to evaluate it in 3 different ways. 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 . 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 These servers aim to demonstrate MCP features and the official SDKs. Many have tried, with limited success, to get ChatGPT to write. 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 Here llm is used to create sql query first and then through python pipe/chain the query is passed to sql database tool and finally llm sumarizes whatever outcome of the query. Thanks System Info Windows 11 SQL Database Setup: Converts an Excel/CSV file into an SQLite database. . Contribute to HassanAhmed0723/LLM-SQL-Agent development by creating an account on GitHub. With this app, you can interact with a natural language interface to generate SQL queries, making it easier for both beginners and experienced In this project, a Streamlit Application with AI Agent for Data Analysis has been built in Python with Phidata, DuckDbAgent and Llama3. Debug poor-performing LLM app runs, evaluate agent trajectories, gain visibility in production, and improve performance over time. We warmly welcome contributions from everyone, whether you've found a typo, a bug, have a suggestion, or want to share a resource related to LLM+Text2SQL. This handbook corresponds to our survey paper: 📖A Survey of Text-to-SQL in the Era of LLMs: Where are we, and where are we going?. This artifcats shows how LLMs can talk with SQL databases and can generate queries as well as results as per the prompt inputs provided in the streamlit app - VISHAL0713/SQL-LLM-Agent-Streamlit-app SQL-LLM-Agent is a cutting-edge project that leverages OpenAI's GPT-3. Contribute to defog-ai/sql-eval development by creating an account on GitHub. Sep 13, 2024 · Fredericcelerse / LLM-SQL-agent Public Notifications You must be signed in to change notification settings Fork 0 Star 0 The SQL Server Agent is a conversational AI Query CLI that enables you to interact with your SQL Server Database using natural language. a NL2SQL). I've tried too many agents changing the whole toolkits and agent types still I get some errors regarding unexpected argument was passed. Parameters: llm (BaseLanguageModel) – Language model to use for the agent. k. Powered by the Modal Context Protocol, it acts as a smart layer between your language model and the database, making it possible to: This project is an LLM-powered SQL Query Generator that allows users to generate SQL queries using natural language input. Built using GPT-4, it validates and executes queries against an SQLite database. Compared to other LLM frameworks, it offers these core benefits: cycles, controllability, and persistence. May 24, 2025 · Contribute to orangelc/llm-sql-agent-azure development by creating an account on GitHub. Instead of this, toolkit = SQLDatabaseToolkit (db=db) agent_executor = create_sql_agent ( llm=OpenAI (temperature=0), Feb 27, 2025 · In this post, I’ll walk through building a natural language to SQL agent that allows users to query databases using everyday language. 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. Agentic RAG for open domain text-to-query. The function create_sql_agent you've used in your code is designed to construct a SQL agent Contribute to Atomix2402/LLM-Driven-SQL-Agent-Interface development by creating an account on GitHub. LLM powered agent that analyses SQL databases. This has been an area of interest for years (WikiSQL, […] Aug 22, 2023 · 🤖 Hi there, Thanks for reaching out and using LangChain for your project. We tested an agentic approach with CrewAI, improving accuracy but ending up with high costs and slow From this repository, you can view the 📚 latest advancements in Text-to-SQL (a. Jun 21, 2023 · In our last blog post we discussed the topic of connecting a PostGres database to Large Language Model (LLM) and provided an example of how to use LangChain SQLChain to connect and ask questions 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). Construct a SQL agent from an LLM and toolkit or database. The text Pattern III: Using SQL Agents Adopting an autonomous agent-based approach where a BigQuery SQL agent, equipped with an ODBC connection, iteratively attempts and refines SQL queries with minimal external guidance. It leverages LLM's (OpenAI, gpt-35-turbo-instruct) powerful language model to convert plain English questions into SQL queries and fetch data from an Azure SQL database (as Data Warehouse). Are The way we interact with our data is changing. Integration: Connect with APIs, databases, and data sources. It leverages langgraph for state management and OpenAI's GPT for intelligent query generation and response formatting. In this paper, we propose a multi-agent collaborative Text-to-SQL framework MAC-SQL, which comprises three agents: the Selector, the Decomposer, and the Refiner. Contribute to SominZex/LangGraph-sql-agent development by creating an account on GitHub. Ask-a-Metric is a WhatsApp-based AI data analyst that uses LLMs to answer SQL database queries, facilitating data access for decision-making in the development sector (GitHub). 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 Text-to-SQL Agent is an AI-powered system that converts natural language queries into SQL queries. Tools within the SQLDatabaseToolkit are designed to interact with a SQL database. In this tutorial, we’ll see how to implement an agent that leverages SQL using smolagents. LLM (Large Language Streamlit based frontend to chat with your SQL db, the llm agent can run queries to answer questions. A comprehensive guide and implementation of architectural patterns that utilize Large Language Models (LLMs) for the efficient generation of SQL from natural language text. If anyone knows how to fix it please help. Or event we can send most sql agent solution leveraging llama 3 - 8B model The code used chromadb vector database to store tables description -This will be passed on as additional context to the llm Special instructions are also provided in the prompt to make it more accurate. Apr 26, 2025 · LangGraph is a library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows. The tool translates user queries into SQL commands, retrieves data from the database, and presents results in a user-friendly format Contribute to SALEX0R/SQL-LLM-Agent development by creating an account on GitHub. We'll start with the basics of Semantic Kernel, move on to implementing RAG patterns using Azure SQL DB's Welcome to the Damn Vulnerable LLM Agent! This project is a sample chatbot powered by a Large Language Model (LLM) ReAct agent, implemented with Langchain. Welcome to the AI SQL Brain App repository! This project leverages the power of OpenAI's Language Model Agents to create an intelligent SQL query assistant. LLM LangChain database conversation project. Specifically, check the equality operator (==) used for llm and correct it to a single =. SoTA LLM for converting natural language questions to SQL queries - defog-ai/sqlcoder This project is a chatbot application designed to provide automated responses to user queries using a LLM model, streamlit and langchain. Jul 11, 2024 · SQL Agent with open-source LLMDescription 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. Jun 6, 2024 · How are you running AnythingLLM? Docker (local) What happened? I can't delete my database connection , i click on the cross to delete and i valide. Initially, we used a simple pipeline for rapid feedback but faced challenges in accuracy and building it for scale. OpenAI GPT-4o-mini Integration: Uses OpenAI’s LLM for intelligent data processing. Jun 23, 2023 · SQLAgent 是一个 开源的（Open source）、大模型驱动的（LLM-Powered）、专注于私有化部署的Text2SQL 智能体（Agent） 项目（Project） - EquinorAB/SQLAgent This system utilizes a Large Language Model (LLM) to generate and execute SQL queries, enabling users to interact with databases using natural language. Easily query SQLite or MySQL databases in natural language. The complete code is available on GitHub at https://github NL2SQL_AGENT 是一个轻量级的自然语言到 SQL (NL2SQL) 智能体，旨在帮助用户通过自然语言查询 PostgreSQL 数据库。 该智能体结合了文档处理、向量检索、LLM 和数据库交互，为用户提供高效、便捷的数据库查询体验。 Jul 30, 2024 · Unlock the power of LLMs like ChatGPT and Ollama to effortlessly query and analyze your SQL database using natural language. ai/oss agent bigquery charts sql postgresql bedrock business-intelligence openai spreadsheets vertex genbi text-to-sql rag text2sql duckdb llm anthropic sqlai text-to-chart Readme AGPL-3. It sounds like an interesting use case! To help you better with your SQL Agent issue, I need a bit more information: Could you provide a brief overview of how you've structured your SQL Agent? This includes how you're handling user queries and how you're directing those queries to specific tables in your database. SQL Learning Support System with LLM. (VectorDB, GraphDB, SQLite, CSV, XLSX, etc. Agent Framework: Develop intelligent agents that autonomously decide actions based on user input. Contribute to git-ai-zyy/LLM-SQL-Agent development by creating an account on GitHub. - asimadnan/LLM_SQL_agent The llm_engine is the LLM that powers the agent system. 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. - raedmajid/schema-aware-ai-sql-agent Feb 9, 2024 · Build and deploy a chat application for complex database interaction with LangChain agents. 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. For detailed guidelines on how to contribute, please see our CONTRIBUTING. - Mintplex-Labs/anything-llm llm_om_only. - cgaravitoc/llm_sql_agent Jun 23, 2023 · SQLAgent 是一个 开源的（Open source）、大模型驱动的（LLM-Powered）、专注于私有化部署的Text2SQL 智能体（Agent） 项目（Project），我们的目标是提供产品级的Text2SQL解决方案，致力于解决Text2SQL在实际应用中遇到的各种问题如模型私有化部署、面向Text2SQL任务的RAG最佳方案等等。为此，我们将持续探索什么 getwren. Contribute to faizan1907/LLM-With-Sql-Agent-Test development by creating an account on GitHub. Lab Exercise In this lab, you will enable the function logic to execute dynamic SQL queries against the SQLite database. AI-powered SQL chatbot using LangChain, Groq LLMs, and Streamlit. sls ozfahk usj wjlaareb hwfvah kzxe sjpla geau ynfr jetsjk