QueryChat facilitates safe and reliable natural language exploration of tabular data, powered by SQL and large language models (LLMs). For analysts, it offers an intuitive web application where they can quickly ask questions of their data and receive verifiable data-driven answers. For software developers, QueryChat provides a comprehensive Python API to access core functionality -- including chat UI, generated SQL statements, resulting data, and more. This capability enables the seamless integration of natural language querying into bespoke data applications.
Install the latest stable release from PyPI:
pip install querychatquerychat supports Gradio, Dash, and Streamlit. Install with the extras you need:
pip install "querychat[gradio]"
pip install "querychat[dash]"
pip install "querychat[streamlit]"Or install directly from GitHub:
pip install "querychat[gradio] @ git+https://github.com/posit-dev/querychat"The main entry point is the QueryChat class. It requires a data source (e.g., pandas, polars, etc) and a name for the data.
from querychat import QueryChat
from querychat.data import titanic
qc = QueryChat(titanic(), "titanic")
app = qc.app()
# app.run()
Build your own custom web apps with natural language querying capabilities, such as this one which provides a bespoke interface for exploring Airbnb listings:
See the website to learn more.