text-to-sql-generation

Natural language to SQL — FastAPI + Groq LLM + RAG schema retrieval + sqlglot validation. Upload a CSV or connect Postgres/MySQL, ask questions in plain English, get safe validated SQL.

An enterprise-grade AI Business Intelligence dashboard that uses Groq and Llama 3.3 to securely translate conversational English queries into optimized SQL, execute them, and automatically render real-time interactive Plotly charts.

Ask your data. Trust the answer. — A text-to-SQL product for non-technical users.

SQLAgent is a natural-language analytics application for an ice cream shop database. A user submits a question, the agent retrieves the context needed to understand the database, generates SQL, validates and repairs the query, and returns a natural-language answer. When the result is suitable for visual analysis, the agent also returns a chart.

AI-powered Text-to-SQL app — supports any database and 100+ AI models

Agentic data assistant enabling secure, natural language exploration across multi-table SQL databases with advanced join-closure intelligence

ARGUS-SQL: A multi-agent Text-to-SQL architecture for Google BigQuery. Features reactive schema profiling for drift mitigation, augmented M-Schema representations, and a defense-in-depth execution guardrail for secure enterprise analytics. My master's degree capstone project from Mapua University

A powerful Agentic-Ai application that converts natural language queries into SQL commands and executes them against your database. Built with FastAPI, Streamlit, and Langgraph and LangChain Tools, Talk2Database makes database interaction accessible to everyone, regardless of their SQL expertise.

Point at a database, get an AI app. Auto-generates DAB SQL MCP servers with dynamic UI rendering and human-in-the-loop safety.

Self-hosted natural-language-to-SQL: ask questions in plain English, get dialect-aware SQL, results, and a feedback loop that improves future answers.

iaPredict a été concu dans l'objectif de faciliter la recuperation des informations dan une base de donnée en utilisant le language humain notamment le Text-To-SQL. Comme exemple: 1. Quel est notre chiffre d'affaires total ce mois-ci, et comment se compare-t-il au mois dernier ? 2. Quels produits sont en rupture de stock ou sous le seuil minimum

This repository contains the implementation, evaluation framework, experimental artifacts, and analysis notebooks associated with the paper: "Semantic Grounding over Brute-Force Inference: A Symbiotic Evaluation of Text-to-SQL Systems"