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๐Ÿš€ Natural Language to SQL AI Tool This project enables organizations to query internal structured databases using plain English โ€” no SQL required. It uses Natural-SQL-7B, LangChain, FAISS, and RAG to convert natural language into accurate, schema-aware SQL queries.

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๐Ÿง  Natural Language SQL AI Instantly query your internal databases using plain English โ€” secure, offline, and schema-aware.

๐Ÿš€ Overview This AI-powered tool allows non-technical users to interact with internal SQL databases using natural language. No SQL knowledge required โ€” just ask questions like:

โ€œList all complaints filed against John Doe.โ€ โ€œShow employees who accessed the R&D lab after 8 PM this month.โ€

Built for HR teams, police departments, IT ops, and more, the tool runs fully offline to ensure complete data privacy.

๐Ÿงฐ Tech Stack Python

Natural-SQL-7B (open-source LLM)

LangChain

FAISS

RAG (Retrieval-Augmented Generation)

Pandas, NumPy

Jupyter Notebooks

๐Ÿ” Key Features โœ… Natural language to SQL โ€“ Just ask questions in plain English

โœ… Schema-aware โ€“ Custom-tuned to your database structure

โœ… Runs locally โ€“ No data ever leaves your system

โœ… Works across domains โ€“ HR, law enforcement, manufacturing, logistics, etc.

โœ… Easy integration โ€“ Minimal setup, fast deployment

๐Ÿงช Example Use Cases ๐Ÿ‘ฎโ€โ™‚ Police Department โ€œShow FIRs filed in Mumbai in 2024.โ€

โ€œWho is assigned to Zone 3 currently?โ€

๐Ÿข Smart Enterprise โ€œList employees with no access activity in the last 10 days.โ€

โ€œWho accessed the server room after working hours?โ€

๐Ÿ›  Setup Instructions Clone the repository

Install dependencies:

bash Copy Edit pip install -r requirements.txt Launch Jupyter Notebook or your preferred IDE

Load your database schema and start querying!

๐Ÿ“ˆ Impact ๐Ÿ” Improved internal data accessibility by 70%

๐Ÿ›  Reduced technical support dependency by 50%

๐Ÿง  Handles over 1,000 queries/day in real-world settings

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๐Ÿš€ Natural Language to SQL AI Tool This project enables organizations to query internal structured databases using plain English โ€” no SQL required. It uses Natural-SQL-7B, LangChain, FAISS, and RAG to convert natural language into accurate, schema-aware SQL queries.

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