llama-hub
model.nvim
llama-hub | model.nvim | |
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5 | 3 | |
3,359 | 269 | |
- | - | |
9.6 | 9.6 | |
3 months ago | 13 days ago | |
Jupyter Notebook | Lua | |
MIT License | 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.
llama-hub
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LlamaCloud and LlamaParse
mean_faithfulness_score 0.667
Notably, the faithfulness score I measured for the baseline solution was actually higher than that reported for your proprietary LlamaParse based solution.
[1] https://github.com/run-llama/llama-hub/tree/main/llama_hub/l...
- Llama Hub
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A Comprehensive Guide for Building Rag-Based LLM Applications
My favorite example is the asana loader[0] for llama-index. It's literally just the most basic wrapper around the Asana SDK to concatenate some strings.
[0] - https://github.com/emptycrown/llama-hub/blob/main/llama_hub/...
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Outlook local calendar loader for LlamaIndex now in LLamaHub
My loader to get events from the local version of an Outlook calendar into documents suitable for LLamaIndex indexing is now available on github.. Like other loaders (there are a lot of them), it's available at https://github.com/emptycrown/llama-hub To make it easy for developers, this loader has a superset of the functions the Google calandar loader has and the same defaults. Since it works off the local calendar, however, no apikeys are needed. This is Windows only.
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Hello, is there a "BEST OF" prompts list here somewhere?
LLAMA GitHub repository
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?
gpt_index - LlamaIndex (GPT Index) is a project that provides a central interface to connect your LLM's with external data. [Moved to: https://github.com/jerryjliu/llama_index]
go.nvim - A feature-rich Go development plugin, leveraging gopls, treesitter AST, Dap, and various Go tools to enhance the dev experience.
LLMStack - No-code platform to build LLM Agents, workflows and applications with your data
neoai.nvim - Neovim plugin for intracting with GPT models from OpenAI
vectara-answer - LLM-powered Conversational AI experience using Vectara
llmflows - LLMFlows - Simple, Explicit and Transparent LLM Apps
llm-applications - A comprehensive guide to building RAG-based LLM applications for production.
pyod - A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
awesome-chatgpt-prompts - This repo includes ChatGPT prompt curation to use ChatGPT better.