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pramitchoudhary committed Jan 27, 2024
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# sql-sidekick
A simple SQL assistant (WIP)
Turn ★ into ⭐ (top-right corner) if you like the project! 🙏

## Motivation
- Historically, it’s common for data to be stored on Databases, democratize insight generation
- Historically, it’s common for data to be stored in Databases, democratizing insight generation.
- Enable a helpful assistant to help write complex queries across different database dialects with acceptable efficient execution accuracy (not just matching accuracy)
- Push to derive consistent generation without errors using smaller OSS models to save on compute costs.
- Provide a toolkit for users to mix and match different model sizes to optimize compute cost - e.g., smaller models for generation, remote bigger models for syntax correction or spell correction …
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- Entity mapping/Schema linking: Ability to build memory for mapping business context to the data schema dynamically; **Note: currently enabled only via CLI, others WIP.
- Ability to save the chat history of query/answer pairs for future reference and improvements.
- Self-correction loop back: Validates syntactic correction of generation. **Note: Self-correction is currently enabled for all openAI GPT models. WIP for other OSS models.
- Integration with different database dialects - currently, SQLite/Postgres is enabled. WIP to add support for Duckdb/Databricks next.
- Integration with different database dialects - currently, SQLite/Postgres(_might be broken temporarily_)/Databricks is enabled. WIP to add support for Duckdb and others.
- Debug mode: Ability to evaluate/modify and validate SQL query against the configured database via UI
- Recommendation sample questions: Often, given a dataset, we are unsure what to ask. To come around this problem, we have enabled the ability to generate recommendations for possible questions.
- Recommend sample questions: Often, given a dataset, we are unsure what to ask. To come around this problem, we have enabled the ability to generate recommendations for possible questions.

# Installation
## Dev
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7. make run
<img width="1670" alt="Screen Shot 2023-11-15 at 6 19 14 PM" src="https://github.com/h2oai/sql-sidekick/assets/1318029/5cf8a3ef-0d36-4416-ae2f-52672024fead">

Citation
## Citation & Acknowledgment
Please consider citing our project if you find it useful:

```bibtex
@software{sql-sidekick,
author = {h2o.ai/sql-sidekick Team},
title = {{sql-sidekick}},
title = {{sql-sidekick: A simple SQL assistant}},
author = {Pramit Choudhary, Michal Malohlava, Narasimha Durgam, Robin Liu, h2o.ai Team}
url = {https://github.com/h2oai/sql-sidekick},
year = {2023}
year = {2024}
}
```
LLM frameworks adopted: [h2ogpt](https://github.com/h2oai/h2ogpt), [h2ogpte](https://pypi.org/project/h2ogpte/), [LangChain](https://github.com/langchain-ai/langchain), [llama_index](https://github.com/run-llama/llama_index), [openai](https://openai.com/blog/openai-api)

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