MindSQL is a Python RAG (Retrieval-Augmented Generation) library designed to simplify database interaction, allowing users to query databases in natural language with just a few lines of code.
Purpose: To translate natural language questions into SQL, thereby lowering the barrier to interacting with databases.
Main capabilities:
- Seamless integration with databases such as PostgreSQL, MySQL, and SQLite; by extending the IDatabase interface, it can also support major databases such as Snowflake and BigQuery.
- Use large language models such as GPT-4, Llama 2, and Google Gemini.
- Support knowledge bases such as ChromaDB and Faiss to provide context-aware responses.
Usage: MindSQL can be installed via pip; the library requires Python 3.10 or higher.
Code structure:
- _utils: Utility module containing constants and loggers.
- _helper: Helper module.
- core: Main core module, minds_core.py.
- databases: Database-related module.
- llms: Language model-related module.
- testing: Test scripts.
- vectorstores: Vector store-related module.
- poetry.lock and pyproject.toml: Poetry dependency and configuration files.
- tests: Test cases.
Use cases: Scenarios that require querying the above supported databases in natural language.
Limitations: Currently only PostgreSQL, MySQL, SQLite, Snowflake, and BigQuery are explicitly supported; other databases need to be implemented by extending the IDatabase interface. Other details regarding billing, pricing, and more features are not provided at this time.
