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Hey ! This is awesome. I have been playing around with the dirty DIN-SQL repo for a couple of weeks, so this is a delight. A couple of questions: * How easy i
by screye 3y ago
Hey ! This is awesome. I have been playing around with the dirty DIN-SQL repo for a couple of weeks, so this is a delight.
A couple of questions:
* How easy is it to swap out the LLM ? (to Azure GPT4)
* Do you have 1 end2end custom user scenario ? It would really help to have 1 golden workflow (the fastest way to get things up and running) and 1 custom workflow (how to maximally configure the package to make it work the way you want) outlined in a demo/blog/tutorial.
Great work! I especially like how neat and transferrable the ideas in DIN-SQL are. Should naturally improve itself as new LLMs come out.
- aazo11 3y agoHi -- thanks for the kind words. While right now the engine only works with OpenAI, swapping out other LLMs simply from the envars is on the roadmap. Since we use Langchain for LLM calls this logic is already abstracted away so it will be a small code change. We have some samples (including a quickstart in the README and docs https://dataherald.readthedocs.io/en/latest/quickstart.html https://dataherald.readthedocs.io/en/latest/quickstart.html) but will be adding more tutorials in the coming days.
- MrezaPourreza 3y agoHello, and thank you for your positive feedback on our work with Dataherald. I'm currently in the process of tidying up the DIN-SQL repository, and I apologize for any inconvenience this may cause :). Regarding the usage of other Large Language Models (LLMs), we offer support for OpenAI, Anthropic, Google, and Cohere models. However, it's important to note that our testing and optimization efforts have primarily been concentrated on OpenAI models. If you intend to utilize other models, it's advisable to proceed with caution and be mindful of potential variations in performance and behavior.