llm-applications
model.nvim
llm-applications | model.nvim | |
---|---|---|
3 | 3 | |
1,573 | 280 | |
5.5% | - | |
8.3 | 9.5 | |
about 2 months ago | 22 days ago | |
Jupyter Notebook | Lua | |
Creative Commons Attribution 4.0 | MIT 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-applications
model.nvim
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A Comprehensive Guide for Building Rag-Based LLM Applications
For local stuff with a handful of documents, you can even just throw it into a json and call it a day. The similarity search is as simple as an np.dot: https://github.com/gsuuon/llm.nvim/blob/main/python3/store.p...
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Show HN: Script to Auto-Generate Commit Messages with AI
My plugin is here: https://github.com/gsuuon/llm.nvim -- one of the "starter prompts" is commit message, so with vim-fugitive I open up the git status window, stage my changes, press 'cc', then ':Llm commit\ message' (or just ':Llm mess' tab complete). Then I make changes as needed. I notice that normally it fails to capture my intent for larger changes (things that should be refactor for example get labeled as feat), and readme only changes are sometimes not labeled as 'docs' correctly.
Here's where the commit message prompt is: https://github.com/gsuuon/llm.nvim/blob/2d771cc882ad9edd8011...
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Burnout Because of ChatGPT?
I plug it directly into my editor (via https://github.com/gsuuon/llm.nvim) and have it fill out code for me. I write what I want with comments and ask it to fill the rest - if it's straightforward enough it basically always works. I also get it to write commit messages (based on git diff) - though I need to improve my prompt a bit as it gets verbose and I end up rewriting it most of the time. I was working on trying to feed it things like hover and tree-sitter information before I got distracted, but that'd be another power boost as well whenever I get around to it.
What are some alternatives?
llama-hub - A library of data loaders for LLMs made by the community -- to be used with LlamaIndex and/or LangChain
SeaGOAT - local-first semantic code search engine
go.nvim - A feature-rich Go development plugin, leveraging gopls, treesitter AST, Dap, and various Go tools to enhance the dev experience.
every-breath-you-take - Heart Rate Variability Training with the Polar H10 Monitor
neoai.nvim - Neovim plugin for intracting with GPT models from OpenAI
pyobd - open source program for OBD2 car diagnostics
llmflows - LLMFlows - Simple, Explicit and Transparent LLM Apps
vectara-answer - LLM-powered Conversational AI experience using Vectara
pyod - A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)