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SUQL: Conversational Search over Structured and Unstructured Data with LLMs
| Date | Stars |
|---|---|
| 2026-07-31 | 308 |
| 2026-08-06 | 308 |
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<b>SUQL (Structured and Unstructured Query Language)</b>
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<a href="https://arxiv.org/abs/2311.09818">
<img src="https://img.shields.io/badge/cs.CL-2311.09818-b31b1b" alt="arXiv">
</a>
<a href="https://github.com/stanford-oval/suql/stargazers">
<img src="https://img.shields.io/github/stars/stanford-oval/suql?style=social" alt="Github Stars">
</a>
<a href="https://pypi.org/project/suql/">
<img alt="PyPI version" src="https://img.shields.io/pypi/v/suql.svg"/>
</a>
</h1>
</p>
<p align="center">
Conversational Search over Structured and Unstructured Data with LLMs
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<p align="center">
Try it out at:
<a href="https://suql.genie.stanford.edu/" target="_blank">
https://suql.genie.stanford.edu/
</a>
<br>
</p>
# What is SUQL
SUQL stands for Structured and Unstructured Query Language. It augments SQL with several important free text primitives for a precise, succinct, and expressive representation. It can be used to build chatbots for relational data sources that contain both structured and unstructured information. Similar to how text-to-SQL has seen [great success](https://python.langchain.com/docs/use_cases/qa_structured/sql), SUQL can be used as the semantic parsing target language for hybrid databases, for instance, for:
Several important features:
- SUQL seamlessly integrates retrieval models, LLMs, and traditional SQL to deliver a clean, effective interface for hybrid data access;
- It utilizes techniques inherent to each component: retrieval model and LM for unstructured data and relational SQL for structured data;
- Index of free text fields built with [faiss](https://github.com/facebookresearch/faiss), natively supporting all your favorite dense vector processing methods, e.g. product quantizer, HNSW, etc.;
- A series of important optimizations to minimize expensive LLM calls;
- Scalability to large databases with PostgreSQL;
- Support for general SQLs, e.g. JOINs, GROUP BYs.
## The answer function
One important component of SUQL is the `answer` function. `answer` function allows for constraints from free text to be easily combined with structured constraints. Here is one high-level example:
For more details, see our paper at https://arxiv.org/abs/2311.09818.
# Installation / Usage tutorial
There are two main ways of installing the SUQL library.
## Install from `pip`
Ideal for integrating the SUQL compiler in a larger codebase / system. See [install_pip.md](https://github.com/stanford-oval/suql/blob/main/docs/install_pip.md) for details.
## Install from source
Ideal for using this repo to build a SUQL-powered conversational interface to your data out-of-the-box, like the one for the Yelp agent discussed in the paper. See [install_source.md](https://github.com/stanford-oval/suql/blob/main/docs/install_source.md) for details.
## Agent tutorial
Check out [conv_agent.md](https://github.com/stanford-oval/suql/blob/main/docs/conv_agent.md) for more information on best practices for using SUQL to power your conversational agent.
# Release notes
Check [release_notes.md](https://github.com/stanford-oval/suql/blob/main/docs/release_notes.md) for new release notes.
# Bugs / Contribution
If you encounter a problem, first check [known_issues.md](https://github.com/stanford-oval/suql/blob/main/docs/known_issues.md). If it is not listed there, we welcome Issues and/or PRs!
# Paper results
To replicate our results on HybridQA and restaurants in our paper, see [paper_results.md](https://github.com/stanford-oval/suql/blob/main/docs/paper_results.md) for details.
# Citation
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matched fp:b7f84ecd883f2ba3, llm:Repository description: 'SUQL: Conversational Search over Structured and Unstructured Data with LLMs' (Python) — enables conversational search using LLMs over structured and unstructured data.
matched fp:b7f84ecd883f2ba3, llm:Repository description: 'SUQL: Conversational Search over Structured and Unstructured Data with LLMs' (Python) — enables conversational search using LLMs over structured and unstructured data.
matched fp:b7f84ecd883f2ba3, llm:Repository description: 'SUQL: Conversational Search over Structured and Unstructured Data with LLMs' (Python) — enables conversational search using LLMs over structured and unstructured data.