An advanced AI-powered tool that bridges the gap between natural language and database operations, featuring an autonomous database agent and intelligent query generation
Project description
HyperXQL
Natural Language to SQL Database Operations
HyperXQL is a powerful tool that enables users to interact with databases using natural language. It leverages large language models to generate and execute SQL queries based on your instructions, without requiring you to write SQL code directly.
Features
- 🔄 Convert natural language to SQL
- 🗄️ Support for SQLite, PostgreSQL, and MySQL
- 🤖 Intelligent AI agent for database operations
- 🔍 Database schema analysis and visualization
- 📊 Interactive command-line interface
- 🌐 Web interface for query execution
- 🛠️ Automatic error detection and recovery
Installation
pip install hyperxql
Quick Start
- Initialize HyperXQL:
hyperxql init
This will guide you through setting up your configuration and database connection.
- Use the agent to perform database operations:
hyperxql agent "create a users table with columns for id, name, email and phone number"
- Query your database:
hyperxql query "show me all users who signed up in the last month"
Command Reference
Usage: hyperxql [OPTIONS] COMMAND [ARGS]...
HyperXQL - Natural Language to SQL Database Operations
This CLI tool allows non-technical users to perform database
operations using natural language, powered by LLMs.
Options:
--version Show the version and exit.
--help Show this message and exit.
Commands:
agent Interact with the database using an AI agent that can reason and execute operations
config View or update HyperXQL configuration
gui Launch the HyperXQL web interface
init Initialize HyperXQL configuration
query Execute a natural language database query
status Display the status of the HyperXQL configuration
Database Agent
The intelligent database agent can help you:
- Create tables and schema
- Insert, update, and delete data
- Generate sample data
- Query and analyze your database
- Fix errors and handle edge cases
The agent thinks aloud, explains its reasoning, and shows you exactly what it's doing.
Web Interface
Start the web interface with:
hyperxql gui
Then open your browser to http://localhost:5000
Requirements
- Python 3.8+
- SQLAlchemy-supported database (SQLite, PostgreSQL, MySQL)
- API key for OpenAI or Together AI (configurable)
License
MIT License
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file hyperxql-2.0.1.tar.gz.
File metadata
- Download URL: hyperxql-2.0.1.tar.gz
- Upload date:
- Size: 61.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.2
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
a3c42dacbd2c90bd920668f88b5635e73c7984edaa7d186b4ac3ac2079fb2607
|
|
| MD5 |
93aacebdc45d5e5b3b40b0d6cb018c0f
|
|
| BLAKE2b-256 |
4ddf113badd8f9130b99a4b4a4370defd9cb287dcb6d15a4f87750c2a2a867bc
|
File details
Details for the file hyperxql-2.0.1-py2.py3-none-any.whl.
File metadata
- Download URL: hyperxql-2.0.1-py2.py3-none-any.whl
- Upload date:
- Size: 52.8 kB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.2
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
28aef2a9e174365a7ae46539bb69c8267cc6efbb9c661b4fef578c42cc410797
|
|
| MD5 |
5f24698c19a16f908fd0f4243bf09f3f
|
|
| BLAKE2b-256 |
9483fd5508ad64ea99c8bbc903c9de4781b99548ece5b196518d014a44e28afd
|