lagoon VS refact

Building document Q&A apps using LLMs has become mainstream now and I built one a few months ago. Constructing a prompt with a context and getting a response from an LLM is pretty simple. Tools like the OpenAI library and the huggingface transformer library have made it a walk in the park. The fun part of building such apps is putting together the different layers of the application to generate a proper prompt with a context, that gives you a near-accurate response out of the LLM. So, this article will focus more on those layers and techniques rather than showing the complete source code for every operation. Because the code is pretty simple and it is the interaction between the different layers that makes this more interesting. Anyway, the entire project is available on Github for you to explore and hack out something creative

With over 1.3k stars on GitHub, more than 40k downloads and installs on both VS Code and JetBrains IDEs, and more than 50 positive reviews, it is worth saying that Refact is part of the best product in the AI coding assistant market.

On vscode i sometimes use continue.dev and refact.ai just for fun and they are great!

Refact was made for this: https://github.com/smallcloudai/refact

You should check-out [refact.ai](https://github.com/smallcloudai/refact). It has both autocomplete and chat. It's in active development, with lots of new features coming soon (context search, fine-tuning for larger models, etc)

I don’t recommend that, since that uses the cloud for the actual inference by default (and they provide no guidance for changing that).

I don’t consider cloud inference to count as getting it working “locally” as requested by the comment above yours.

Refact works nicely and works locally, but the challenge with any new model is making it be supported by the existing software: https://github.com/smallcloudai/refact/

Previously, we used Astro for our refact.ai website and wanted to stay within the Astro ecosystem for the documentation.

Refact LLM can be easily integrated into existing developers workflows with an open-source docker container and VS Code and JetBrains plugins. With Refact's intuitive user interface, developers can utilize the model easily for a variety of coding tasks. Finetune is available in the self-hosting (docker) and Enterprise versions, making suggestions more relevant for your private codebase.