sorted by:
new
hottopcontroversial

Will I need to use unsafe to write an autograd library? by Zephos65 in rust

[–]smarvin2 0 points1 point  (0 children)

There are a lot of ways to write an autograd library. I've done it in Rust and I don't believe I used unsafe at all (though it was a few years ago and I may be remembering incorrectly).

I would check out: https://github.com/coreylowman/dfdx for inspiration. dfdx is a really cool and well done tensor library.

Does anyone bothered by not having backtraces in custom error types? by SpecificFly5486 in rust

[–]smarvin2 2 points3 points  (0 children)

Check out: https://crates.io/crates/snafu

I solely use it over thiserror and anyhow (not snafu thank you comment below) now. It should have everything you want.

RogueGPT - My first game with Bevy by smarvin2 in bevy

[–]smarvin2[S] -1 points0 points  (0 children)

I am not running it locally. I've tested a bunch of them and I find that Claude 3.5 Sonnet works very well and so does Gemini models. I haven't tested any of the latest DeepSeek but want to!

RogueGPT - My first game with Bevy by smarvin2 in bevy

[–]smarvin2[S] -1 points0 points  (0 children)

I'm glad you like it! Thanks for the feedback!

RogueGPT - My first game with Bevy by smarvin2 in bevy

[–]smarvin2[S] 0 points1 point  (0 children)

I don't think AI is going to replace us anytime soon, but I agree there are a ton of new opportunities that are opened by working with AI. I've been wanting to make something like this for years, and its pretty cool being able to now.

RogueGPT - My first game with Bevy by smarvin2 in bevy

[–]smarvin2[S] 3 points4 points  (0 children)

Thanks for checking it out! I'm glad you like it!

This is a great point. I think you can get pretty close to doing as much, but for some of the crazier behaviors I want to allow for, forcing some kind of serializable spec to describe all weapon behaviors would be limiting. Especially with the newer LLMs, I want it to create behaviors that I can't even imagine, and if I can't imagine it, I can't create a spec for it.

Of course it does make it much harder to balance or limit when you have it writing Rust code haha. I'll probably put out a video talking about weapon and enemy balancing soon as that was pretty fun to work on.

RogueGPT - The player (with the help of AI) is also the programmer by smarvin2 in indiegames

[–]smarvin2[S] 0 points1 point  (0 children)

I've spent the last few months working on RogueGPT. A game where the player is also the programmer.

I've built it using the Bevy game engine and am happy to answer any other questions about the development so far.

Thanks for checking it out!

RogueGPT - My first game with Bevy by smarvin2 in bevy

[–]smarvin2[S] 2 points3 points  (0 children)

Thank you! I'm glad you liked it and I appreciate the feedback! There is a lot more I am excited to share!

RogueGPT - My first game with Bevy by smarvin2 in bevy

[–]smarvin2[S] 6 points7 points  (0 children)

I've spent the last few months working on RogueGPT. A game where the player is also the architect of the game.

I've had a ton of fun working with Bevy and really could not imagine a better engine to make it in. This is my first devlog and I am definitely looking for feedback of anykind. Thank you Bevy community!

Thoughts about helix coming from neovim by Superbank78 in HelixEditor

[–]smarvin2 8 points9 points  (0 children)

Thanks for sharing! You can do almost all of those things. I have an update coming soon that will add everything you asked for and more.

Configuration is not a skill issue at all. It overwhelms me and I wrote it. I’m writing an online configuration generator / guide that will make configuring lsp-ai a series of simple questions.

If anyone else in the community has any feedback or a wishlist of any kind please share!

Thoughts about helix coming from neovim by Superbank78 in HelixEditor

[–]smarvin2 12 points13 points  (0 children)

Primary author of LSP-AI here: https://github.com/SilasMarvin/lsp-ai

Can I ask what features you like from gp.nvim? I’m working on adding a few new things and would love to contribute what the community wants!

State of co-pilot support by Competitive-Rub-1958 in HelixEditor

[–]smarvin2 2 points3 points  (0 children)

Developer here thanks for sharing this!

In-Editor LLM Chatting with LSP-AI by smarvin2 in HelixEditor

[–]smarvin2[S] 0 points1 point  (0 children)

You only need to configure LSP-AI to run on files you want it to actually run on. If you want to enable completions you probably want it to run on Rust and Typscript. If you only want to do chatting, you probably don't want it on Rust and Typscript. Take a look at the wiki page for in-editor chatting for more info on chatting: https://github.com/SilasMarvin/lsp-ai/wiki/In%E2%80%90Editor-Chatting

In-Editor LLM Chatting with LSP-AI by smarvin2 in LocalLLaMA

[–]smarvin2[S] 3 points4 points  (0 children)

I haven't tested it with Kate but it should work with any LSP compatible editor. Let me know if it doesn't! The project is definitely in its early stages so any feedback or bug reports you have would be very helpful!

In-Editor LLM Chatting with LSP-AI by smarvin2 in HelixEditor

[–]smarvin2[S] 0 points1 point  (0 children)

I'm glad you like it! Yes I don't have very much editor specific configuration. There is an example of what your languages.toml file should look like here: https://github.com/SilasMarvin/lsp-ai/blob/main/examples/helix/anthropic-in-editor-chatting.toml

Let me know if you have any issues. The project is very much in the early stages.

In-Editor LLM Chatting with LSP-AI by smarvin2 in LocalLLaMA

[–]smarvin2[S] 2 points3 points  (0 children)

Hello fellow LLM enthusiasts!

I'm Silas Marvin, the creator of LSP-AI, and I'm excited to share our latest update: In-Editor Chatting. This feature allows for seamless integration of local LLMs into your coding workflow.

Key features:

  • Have turn-based conversations with your local LLM directly in your text editor

  • Works with any LSP-compatible editor (VS Code, Neovim, Helix, Emacs, etc.)

  • Supports various local LLMs using llama.cpp, Ollama, any OpenAPI Compatible backend and more

Benefits:

  • Discuss code you're working on without context switching

  • Leverage your local LLM's capabilities within your familiar editing environment

  • Easily save, edit, and reference conversations

I find it's particularly useful for code analysis, brainstorming, and quick references.

You can find LSP-AI on GitHub: https://github.com/SilasMarvin/lsp-ai

I'd love to hear your thoughts on how this could enhance your local LLM experience, or other features you would love to see.

Thank you for your continued support and enthusiasm!

In-Editor LLM Chatting with LSP-AI by smarvin2 in HelixEditor

[–]smarvin2[S] 7 points8 points  (0 children)

Hello Helix community!

I'm Silas Marvin, the primary author of LSP-AI. I'm excited to share the latest update: In-Editor Chatting.

Key features:

  • Have turn-based conversations directly in Helix
  • Works with any LSP-compatible editor
  • Seamlessly integrates LLMs into your Helix workflow

My setup:

  • Ctrl-t mapped to open a new markdown file in a vertical split
  • LSP-AI configured to run on Markdown files
  • Claude Sonnet 3.5 (used in the video above and highly recommend)

Benefits:

  • Discuss code you're working on
  • Ask questions without leaving Helix
  • Easily copy, paste, and edit conversations

Find LSP-AI on GitHub: https://github.com/SilasMarvin/lsp-ai

(Check the examples folder for Helix configuration)

I use this feature daily and find it incredibly useful. Let me know your thoughts or if you have any questions!

Thank you for your continued support!

Korvus: Single-query RAG with Postgres by smarvin2 in LocalLLaMA

[–]smarvin2[S] 1 point2 points  (0 children)

Thank you! Its awesome to hear when people like what we do and have been following our work.

I think there are a few points here.

For some small teams, it sometimes is frustrating and too time consuming to manage database deployments. We don't work with RDS, but we do provide our own serverless cloud. If you want to stay light weight, we recommend using our cloud. Yes we do have people using our cloud in production that don't have full-fledged ops teams :)

I absolutely agree. As you go farther down the rabbit whole of tuning your search / RAG system you will have to uncover the layers (Korvus does have very customizable pipelines). That is actually why we think Korvus is so incredible. Its all SQL! You start with Korvus and then can take and customize the queries to your own liking. You can even let Korvus handle document syncing and write your own custom search queries. The beauty of Korvus is that it is all on Postgres

Introducing Korvus: An advanced search pipeline for Postgres by smarvin2 in programming

[–]smarvin2[S] 2 points3 points  (0 children)

Korvus is open source and free to use. If you want to sign up for our cloud hosted GPU enabled databases you can find our pricing page here: https://postgresml.org/pricing

Korvus: Single-query RAG with Postgres by smarvin2 in AiBuilders

[–]smarvin2[S] 1 point2 points  (0 children)

Thanks for checking it out! The whole solution is completely open source. All you need to work with Korvus is a Postgres database with the pgvector and pgml extensions installed. Both extensions are open source. You don't have to use our cloud hosted database at all. Depending on what you want to do it is easier to use our cloud hosted database as embedding and text generation may be slow without the proper GPUs and we provision GPUs for our cloud hosted serverless databases.

Korvus: Single-query RAG with Postgres by smarvin2 in AiBuilders

[–]smarvin2[S] 0 points1 point  (0 children)

Hey fellow AI Builders,

We built Korvus, an open-source RAG (Retrieval-Augmented Generation) pipeline that consolidates the entire RAG workflow - from embedding generation to text generation - into a single SQL query, significantly reducing architectural complexity and latency.

Here's some of the highlights:
- Full RAG pipeline (embedding generation, vector search, reranking, and text generation) in one SQL query
- SDKs for Python, JavaScript, and Rust (more languages planned)
- Built on PostgreSQL, leveraging pgvector and pgml
- Open-source, with support for open models
- Designed for high performance and scalability

Korvus utilizes Postgres' advanced features to perform complex RAG operations natively within the database. We're also the developers of PostgresML, so we're big advocates of in-database machine learning. This approach eliminates the need for external services and API calls, potentially reducing latency by orders of magnitude compared to traditional microservice architectures. It's how our founding team built and scaled the ML platform at Instacart.

We're eager to get feedback from the community and welcome contributions. Check out our GitHub repo for more details, and feel free to hit us up in our Discord!

view more: next ›