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.

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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.

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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.

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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