llm-ls
refact
llm-ls | refact | |
---|---|---|
2 | 34 | |
471 | 1,436 | |
11.7% | 4.2% | |
8.2 | 9.8 | |
2 months ago | 6 days ago | |
Rust | JavaScript | |
Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
llm-ls
-
Continue will generate, refactor, and explain entire sections of code
> I'd have expected that the main lever the product has in being better than others is having a custom model that understands code edits much more than others.
True, but this is not something this particular product would solve. There are already models specifically trained to work on code. What's appealing to me is the flexibility of being able to choose which one to use, rather than my workflow being tied to a specific product or company.
> the IDE integration seems to be the "easy bit"
I admittedly haven't researched this much, but this is not currently the case. There is no generic API for LLMs that IDEs can plug into, so all plugins must target a specific model. We ultimately need an equivalent of an LSP server for LLMs, and while such a project exists[1], it looks to be in its infancy, as expected.
[1]: https://github.com/huggingface/llm-ls
-
LocalPilot: Open-source GitHub Copilot on your MacBook
Okay, I actually got local co-pilot set up. You will need these 4 things.
1) CodeLlama 13B or another FIM model https://huggingface.co/codellama/CodeLlama-13b-hf. You want "Fill in Middle" models because you're looking at context on both sides of your cursor.
2) HuggingFace llm-ls https://github.com/huggingface/llm-ls A large language mode Language Server (is this making sense yet)
3) HuggingFace inference framework. https://github.com/huggingface/text-generation-inference At least when I tested you couldn't use something like llama.cpp or exllama with the llm-ls, so you need to break out the heavy duty badboy HuggingFace inference server. Just config and run. Now config and run llm-ls.
4) Okay, I mean you need an editor. I just tried nvim, and this was a few weeks ago, so there may be better support. My expereicen was that is was full honest to god copilot. The CodeLlama models are known to be quite good for its size. The FIM part is great. Boilerplace works so much easier with the surrounding context. I'd like to see more models released that can work this way.
refact
- RefactAI: Use best-in-class LLMs for coding in your IDE
-
Supercharge Your Dev Workflow: How Refact's AI-powered Code Completion Boosts Developer Productivity
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.
-
What do you use to run your models?
On vscode i sometimes use continue.dev and refact.ai just for fun and they are great!
-
AI Code assistant for about 50-70 users
Refact was made for this: https://github.com/smallcloudai/refact
- Free WebUI for Fine-Tuning and Self-Hosting Open-Source LLMs for Coding
-
LocalPilot: Open-source GitHub Copilot on your MacBook
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)
-
Replit's new AI Model now available on Hugging Face
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/
- Refact.ai 1.0.0 Released
-
📝 🚀 Creating our first documentation from scratch using Astro and Refact AI coding assistant
Previously, we used Astro for our refact.ai website and wanted to stay within the Astro ecosystem for the documentation.
-
🤖We trained a small 1.6b code model and you can use it as a personal copilot in Refact for free🤖
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.
What are some alternatives?
OpenAI-sublime-text - Sublime Text OpenAI completion plugin with GPT-4 support!
tabby - Self-hosted AI coding assistant
text-generation-inference - Large Language Model Text Generation Inference
fauxpilot - FauxPilot - an open-source alternative to GitHub Copilot server
cody - AI that knows your entire codebase
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
localpilot
llama-cpp-python - Python bindings for llama.cpp
continue - ⏩ Open-source VS Code and JetBrains extensions that enable you to easily create your own modular AI software development system
developer - the first library to let you embed a developer agent in your own app!
supervision - We write your reusable computer vision tools. 💜
autodoc - Experimental toolkit for auto-generating codebase documentation using LLMs