SQLucid is an interactive interface for SQL generation, presented in the UIST'24 paper:
SQLucid: Grounding Natural Language Database Queries with Interactive Explanations.
SQLucid bridges the gap between non-expert users and complex database querying processes through three key features:
- Editable step-by-step SQL explanations in natural language
- Intermediate query results visualization
- Visual correspondence highlighting
The project is built with:
We offer two versions with different deployment approaches:
This version is the one originally described in our paper.
- Includes a text-to-SQL model and our fine-tuned text-to-clause model.
- Project size: ~5GB (including 2 fine-tuned models and database files)
- For full backend deployment details, visit STEPS
- Download complete project (recommended): V1 Download Link
To support a more lightweight and up-to-date implementation, the latest version is powered by ChatGPT with a polished UI.
- Powered by ChatGPT with enhanced UI
- More lightweight project: ~400MB
- Download complete project: V2 Download Link
- Requires: Implementation of OpenAI API in
openai_api.py, where theget_openai_response()method takes a string prompt and returns a string response.
After you deploy the project folder, you should run the frontend and the backend in parallel.
First, start a terminal and run the following command:
cd frontend
PORT=3000 npm start
Second, start another terminal and run
python run.py
Finally, you can access SQLucid at localhost:3000
This project is licensed under the Apache License 2.0 - see the LICENSE file for details.
If you find this work helpful, please cite our paper:
@inproceedings{10.1145/3654777.3676368,
author = {Tian, Yuan and Kummerfeld, Jonathan K. and Li, Toby Jia-Jun and Zhang, Tianyi},
title = {SQLucid: Grounding Natural Language Database Queries with Interactive Explanations},
year = {2024},
isbn = {9798400706288},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3654777.3676368},
doi = {10.1145/3654777.3676368},
abstract = {Though recent advances in machine learning have led to significant improvements in natural language interfaces for databases, the accuracy and reliability of these systems remain limited, especially in high-stakes domains. This paper introduces SQLucid, a novel user interface that bridges the gap between non-expert users and complex database querying processes. SQLucid addresses existing limitations by integrating visual correspondence, intermediate query results, and editable step-by-step SQL explanations in natural language to facilitate user understanding and engagement. This unique blend of features empowers users to understand and refine SQL queries easily and precisely. Two user studies and one quantitative experiment were conducted to validate SQLucid’s effectiveness, showing significant improvement in task completion accuracy and user confidence compared to existing interfaces. Our code is available at https://github.com/magic-YuanTian/SQLucid.},
booktitle = {Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology},
articleno = {12},
numpages = {20},
keywords = {Databases, Explanations, Natural Language Interfaces},
location = {Pittsburgh, PA, USA},
series = {UIST '24}
}Please email tian211@purdue.edu for any questions. Thanks!