Skip to content

AI-Text-To-SQL v0.2.0 Release

Latest
Latest
Compare
Choose a tag to compare
@MinuraPunchihewa MinuraPunchihewa released this 14 Jul 15:13
· 3 commits to main since this release
v0.2.0
346c153
This commit was created on GitHub.com and signed with GitHub’s verified signature. The key has expired.
GPG key ID: 4AEE18F83AFDEB23
Expired
Learn about vigilant mode.

The first release of AI-Text-To-SQL is now available, introducing an enchanting Python package that brings the magic of transforming text queries into SQL commands and executing them directly on the database. This release marks the beginning of a journey where text queries effortlessly express themselves in plain English, transform into perfectly formatted SQL queries, and unleash their power upon the database.

Features and Enhancements

  • Text-To-SQL Conversion: Experience the power of AI-Text-To-SQL as it gracefully converts natural language queries into SQL commands. Simply type your queries, and AI-Text-To-SQL will work its magic.
  • Direct Database Execution: Your natural language queries can also be directly executed on the database. Just type what you want done in plain englsh and AI-Text-To-SQL will handle the conversion to SQL behind the hood and return the results of the execution!
  • Pandas DataFrame Support: Store the results of executed queries in a DataFrame for further analysis, visualization, and sorcery.
  • Data Connector Compatibility: AI-Text-To-SQL supports multiple data connectors, including SQLite, PostgreSQL, MySQL, MariaDB, and MS SQLServer. Choose the preferred database realm, and AI-Text-To-SQL will seamlessly execute queries on it.
  • Language Learning Model Integration: This release features integration with OpenAI as the Language Learning Model (LLM) connector. The LLM enhances AI-Text-To-SQL's ability to comprehend text queries, making the transformation process even more accurate and powerful.
  • Ease of Use: With a simple installation process using pip and clear API documentation, AI-Text-To-SQL ensures a smooth and hassle-free experience for users.

Get Started with AI-Text-To-SQL

Embarking on the text-to-SQL transformation journey is as simple as the wave of a wand:

  • Installation: Install AI-Text-To-SQL by running pip install ai_text_to_sql in your Python environment. The magic is just a few commands away!
  • Import Connectors: Choose the desired data connector from SQLite, PostgreSQL, MySQL, MariaDB, or MS SQLServer. Additionally, import the LLM connector (currently supporting OpenAI) to enhance AI-Text-To-SQL's mystical abilities.
  • Craft SQL Incantations: Instantiate the TextToSQL object by passing the data connector and LLM connector objects. This union forms the core of AI-Text-To-SQL's powers.
  • Transform Your Queries: Utter magical incantations by passing text queries to the convert_text_to_sql method. Witness queries elegantly transform into SQL commands.
  • Harness the Results: Want results? Get the results of text queries directly or store them in a DataFrame using the query and query_df methods respectively. Analyze, visualize, and perform further sorcery thereafter.

Contributing and Feedback

Community participation is highly valued in making AI-Text-To-SQL even more enchanting! You can contribute to the project by reporting issues, suggesting new features, or making code improvements. Check out the CONTRIBUTING.md file in the project repository for detailed guidelines.

Your feedback and suggestions are invaluable. If you have ideas for new data connectors or LLM integrations, please share them by creating an issue on the GitHub repository.

Please feel free to pick up some of the existing issues as well!

License

AI-Text-To-SQL is released under the GNU General Public License v3.0 (GPL-3.0). This open-source license allows users to freely use, modify, and distribute the package in compliance with the license terms.

Let the Magic Begin!

Embrace the magic of AI-Text-To-SQL and experience the ease of talking to your database in plain English, unlocking a new level of simplicity and efficiency in your data exploration and analysis.

Assets 2
Loading