AI Tool for querying natural language on tabular data.
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Updated
Nov 29, 2023 - Python
AI Tool for querying natural language on tabular data.
Self-hosted RAG framework with RBAC, multi-LLM support, and natural language SQL over tabular data
Ask questions about your business data in plain English, Get automatic SQL queries and visualizations, Receive AI-powered insights and recommendations, No SQL knowledge required
QueryWise: Natural-language SQL assistant with semantic context, glossary- aware query generation, and a React/FastAPI stack.
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)**. It also includes **SQL injection detection** and **sensitive data logging** for compliance and security.
A hands-on RAG application that converts natural language questions into SQL queries for a real estate database. Built with LangChain, FastAPI, Streamlit, and OpenAI GPT-4o-mini. Perfect for learning Retrieval-Augmented Generation and LLM-powered database interactions.
🤖 DataWhisper is a system that translates natural language queries into SQL using an intelligent agent-based architecture. These agents work together to identify the relevant tables, generate SQL queries, execute the queries, and ultimately provide insights. It can be used with large-scale databases.
Self-correcting AI agent for natural language to SQL using HuggingFace smolagents and ReAct framework
MCP agent translating natural language questions into explainable, reproducible data insights with built-in quality checks and semantic layer integration.
A context-aware chatbot backend powered by Django and LLMs, supporting multi-turn conversations, SQL generation, and optional visual similarity search with FAISS.
Turn plain-English questions into executable SQL. LangChain agents over a schema-aware FastAPI service, with example-SQL retrieval (RAG), per-DB instructions, OpenAI fine-tuning, and streaming generation.
dbt-style context files for natural-language SQL agents across SQLite, DuckDB, Postgres, Snowflake, BigQuery, MySQL, and Azure SQL.
Production-grade Asymmetric Multi-Agent Text-to-SQL on BIRD-SQL. Offline CHESS/FAISS pruning + MCI-SQL enrichment feed ≤3 Groq API calls: gpt-oss-120b generator · llama-4-scout reflector · gpt-oss-20b critic. LangGraph · SQLAlchemy sandbox · LangSmith · Docker · MIT.
REAR is a fast, LLM-free framework for multi-table retrieval that separates semantic relevance from structural joinability. By retrieving relevant tables, expanding with joinable ones, and refining noisy candidates, it consistently improves multi-table QA and Text-to-SQL performance—matching LLM-based methods at much lower cost and latency.
Structured Text-to-SQL pipeline combining LLM sketch generation, schema-aware two-phase retrieval, and validation-driven refinement. Improves SQL controllability and correctness via schema embeddings, join-path constraints, and minimal-edit correction. Research-oriented, fully traceable POC on MiniDev / Spider-style datasets.
Two-stage LLM-based Text-to-SQL framework with schema retrieval, SQL validation, and self-correction.
Ask questions about your business data in plain English, Get automatic SQL queries and visualizations, Receive AI-powered insights and recommendations, No SQL knowledge required
🧠 Schema-Aware Natural Language to SQL Agent with Fine-tuned T5 Models
A modern MERISE database modeling tool built with Python and PySide6. Create MCD diagrams, generate MLD views, and export PostgreSQL SQL scripts.
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