Skip to content

Latest commit

 

History

History
54 lines (44 loc) · 1.93 KB

README.md

File metadata and controls

54 lines (44 loc) · 1.93 KB

MeshDB: Natural Language Multi-Database Query Agent

MeshDB is a system that enables natural language queries across multiple database systems, including PostgreSQL, Neo4j, and MongoDB. It dynamically generates multi-stage query pipelines, integrating SQL, Cypher, and NoSQL queries to provide seamless cross-database analytics.

Features

  • Multi-Database Query Support: Execute natural language queries across PostgreSQL, Neo4j, and MongoDB.
  • Dynamic Query Pipeline: Uses GPT-4 to generate multi-stage pipelines for cross-database queries.
  • Schema Inference: Automatically infers database schemas and saves them in a unified JSON format.
  • Query Optimization: Handles multi-stage queries with dynamic placeholder resolution.
  • REST API: Provides endpoints for database dump uploads and query execution.
  • Caching: Accelerates repeated queries using Redis-based caching.

Technologies Used

  • Databases:
    • PostgreSQL: Relational database for structured data.
    • Neo4j: Graph database for relationship-heavy queries.
    • MongoDB: NoSQL database for flexible document storage.
  • Backend:
    • Flask: Python web framework for API endpoints.
    • psycopg2: PostgreSQL driver.
    • neo4j: Neo4j Python driver.
    • pymongo: MongoDB driver.
  • AI Integration:
    • OpenAI GPT-4: Converts natural language into database-specific queries.
  • Other Tools:
    • Redis: Query result caching.
    • Docker: Containerization for deployment.

Setup Instructions

Prerequisites

  • Python 3.8+
  • PostgreSQL, Neo4j, and MongoDB installed and running.
  • Redis server installed and running.
  • OpenAI API key.

Installation

  1. Clone the repository: 
    git clone https://github.com/yash94404/MeshDB.git
cd MeshDB
  2. Install requirements: 
    pip install -r requirements.txt
  3. Run frontend module and navigate to http://127.0.0.1:5000 
    python3 run.py