AI

Open-source projects categorized as AI
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Topics: Machine Learning Python openai chatgpt llm
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Top 23 AI Open-Source Projects

  • AutoGPT

    AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.

    • Project mention: Accessible AI for Everyone | news.ycombinator.com | 2024-01-08

  • stable-diffusion-webui

    Stable Diffusion web UI

    • Project mention: Show HN: I made an app to use local AI as daily driver | news.ycombinator.com | 2024-02-27

    * LLaVA model: I'll add more documentation. You are right Llava could not generate images. For image generation I don't have immediate plans, but checkout these projects for local image generation.

    - https://diffusionbee.com/

    - https://github.com/comfyanonymous/ComfyUI

    - https://github.com/AUTOMATIC1111/stable-diffusion-webui

  • InfluxDB

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  • ChatGPT

    🔮 ChatGPT Desktop Application (Mac, Windows and Linux)

    • Project mention: What AI assistants are already bundled for Linux? | news.ycombinator.com | 2024-03-01

    > I wouldn't hold my breath waiting for a native Linux AI-assisted assistant.

    On Mac when I press Command + Space, it brings up Spotlight search

    That can't easily be added to be the equivalent of some kind of LLM prompt on GNOME/KDE/XFCE?

    I don't quite know what you'd ask it/do with it that would be of much value? Seems like a quicker way/a wrapper around either asking an LLM questions via CLI or basically Electron wrapping HTML (like this https://github.com/lencx/ChatGPT)?

  • generative-ai-for-beginners

    18 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/

    • Project mention: Build a serverless ChatGPT with RAG using LangChain.js | dev.to | 2024-04-10

    Generative AI For Beginners: a collection of resources to learn about Generative AI, including tutorials, code samples, and more.

  • ColossalAI

    Making large AI models cheaper, faster and more accessible

    • Project mention: FLaNK AI-April 22, 2024 | dev.to | 2024-04-22

  • Kong

    🦍 The Cloud-Native API Gateway and AI Gateway.

    • Project mention: Kong 3.6 with LLM Support | news.ycombinator.com | 2024-02-15

  • Open-Assistant

    OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.

    • Project mention: Best open source AI chatbot alternative? | /r/opensource | 2023-12-08

    For open assistant, the code: https://github.com/LAION-AI/Open-Assistant/tree/main/inference

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

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  • MockingBird

    🚀AI拟声: 5秒内克隆您的声音并生成任意语音内容 Clone a voice in 5 seconds to generate arbitrary speech in real-time

  • gold-miner

    🥇掘金翻译计划，可能是世界最大最好的英译中技术社区，最懂读者和译者的翻译平台：

  • google-research

    Google Research

    • Project mention: Show HN: Next-token prediction in JavaScript – build fast LLMs from scratch | news.ycombinator.com | 2024-04-10

    People on here will be happy to say that I do a similar thing, however my sequence length is dynamic because I also use a 2nd data structure - I'll use pretentious academic speak: I use a simple bigram LM (2-gram) for single next-word likeliness and separately a trie that models all words and phrases (so, n-gram). Not sure how many total nodes because sentence lengths vary in training data, but there are about 200,000 entry points (keys) so probably about 2-10 million total nodes in the default setup.

    "Constructing 7-gram LM": They likely started with bigrams (what I use) which only tells you the next word based on 1 word given, and thought to increase accuracy by modeling out more words in a sequence, and eventually let the user (developer) pass in any amount they want to model (https://github.com/google-research/google-research/blob/5c87...). I thought of this too at first, but I actually got more accuracy (and speed) out of just keeping them as bigrams and making a totally separate structure that models out an n-gram of all phrases (e.g. could be a 24-token long sequence or 100+ tokens etc. I model it all) and if that phrase is found, then I just get the bigram assumption of the last token of the phrase. This works better when the training data is more diverse (for a very generic model), but theirs would probably outperform mine on accuracy when the training data has a lot of nearly identical sentences that only change wildly toward the end - I don't find this pattern in typical data though, maybe for certain coding and other tasks there are those patterns though. But because it's not dynamic and they make you provide that number, even a low number (any phrase longer than 2 words) - theirs will always have to do more lookup work than with simple bigrams and they're also limited by that fixed number as far as accuracy. I wonder how scalable that is - if I need to train on occasional ~100-word long sentences but also (and mostly) just ~3-word long sentences, I guess I set this to 100 and have a mostly "undefined" trie.

    I also thought of the name "LMJS", theirs is "jslm" :) but I went with simply "next-token-prediction" because that's what it ultimately does as a library. I don't know what theirs is really designed for other than proving a concept. Most of their code files are actually comments and hypothetical scenarios.

    I recently added a browser example showing simple autocomplete using my library: https://github.com/bennyschmidt/next-token-prediction/tree/m... (video)

    And next I'm implementing 8-dimensional embeddings that are converted to normalized vectors between 0-1 to see if doing math on them does anything useful beyond similarity, right now they look like this:

      [nextFrequency, prevalence, specificity, length, firstLetter, lastLetter, firstVowel, lastVowel]

  • PhotoPrism

    AI-Powered Photos App for the Decentralized Web 🌈💎✨

    • Project mention: Show HN: Memories, FOSS Google Photos alternative built for high performance | news.ycombinator.com | 2024-03-21

    I have been using https://www.photoprism.app for a couple of years, and it works better than expected, with the latest updates it's actually quite fast and the face tagging works reasonably well.

  • AI-For-Beginners

    12 Weeks, 24 Lessons, AI for All!

    • Project mention: FREE AI Course By Microsoft: ZERO to HERO! 🔥 | dev.to | 2024-03-18

    🔗 https://github.com/microsoft/AI-For-Beginners 🔗 https://microsoft.github.io/AI-For-Beginners/

  • spaCy

    💫 Industrial-strength Natural Language Processing (NLP) in Python

    • Project mention: Step by step guide to create customized chatbot by using spaCy (Python NLP library) | dev.to | 2024-03-23

    Hi Community, In this article, I will demonstrate below steps to create your own chatbot by using spaCy (spaCy is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython):

  • Lobe Chat

    LobeChat is a open-source, extensible (Function Calling), high-performance chatbot framework.It supports one-click free deployment of your private ChatGPT/LLM web application.

    • Project mention: The AI Revolution Is Crushing Thousands of Languages | news.ycombinator.com | 2024-04-25

    Get your OpenAI API key and then use it on one of the hundreds of open source frontends available, such as: https://github.com/lobehub/lobe-chat

  • AI-Expert-Roadmap

    Roadmap to becoming an Artificial Intelligence Expert in 2022

    • Project mention: Best AI ML DL DS Roadmap | /r/deeplearning | 2023-12-07

    **[I.am.ai AI Expert Roadmap](https://i.am.ai/roadmap)**: This roadmap focuses more on AI and includes various aspects of machine learning and deep learning. It's suitable for those who want to delve deeper into AI, particularly in cutting-edge research and applications.

  • pytorch-lightning

    Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.

    • Project mention: Lightning AI Studios – A persistent GPU cloud environment | news.ycombinator.com | 2023-12-14

  • upscayl

    🆙 Upscayl - Free and Open Source AI Image Upscaler for Linux, MacOS and Windows built with Linux-First philosophy.

    • Project mention: Why Does Windows Use Backslash as Path Separator? | news.ycombinator.com | 2024-04-24

    Windows has caused us a lot of issues with Upscayl (https://upscayl.org).

    I personally do not use Windows but most of our errors are reported by Windows users where sometimes path parsing is a problem or the drivers mess up vulkan configuration.

  • netron

    Visualizer for neural network, deep learning and machine learning models

    • Project mention: Visualizer for neural network, deep learning and machine learning models | news.ycombinator.com | 2023-12-26

  • dify

    Dify is an open-source LLM app development platform. Dify's intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features and more, letting you quickly go from prototype to production.

    • Project mention: Dify, a visual workflow to build/test LLM applications | news.ycombinator.com | 2024-04-22

    > https://github.com/langgenius/dify/blob/main/LICENSE

    everyone is apparently a license pioneer

  • MindsDB

    The platform for customizing AI from enterprise data

    • Project mention: What’s the Difference Between Fine-tuning, Retraining, and RAG? | dev.to | 2024-04-08

    Check us out on GitHub.

  • learnopencv

    Learn OpenCV : C++ and Python Examples

    • Project mention: YOLO-NAS Pose | /r/pytorch | 2023-11-16

    Deci's YOLO-NAS Pose: Redefining Pose Estimation! Elevating healthcare, sports, tech, and robotics with precision and speed. Github link and blog link down below! Repo: https://github.com/spmallick/learnopencv/tree/master/YOLO-NAS-Pose

  • LocalAI

    :robot: The free, Open Source OpenAI alternative. Self-hosted, community-driven and local-first. Drop-in replacement for OpenAI running on consumer-grade hardware. No GPU required. Runs gguf, transformers, diffusers and many more models architectures. It allows to generate Text, Audio, Video, Images. Also with voice cloning capabilities.

    • Project mention: Drop-In Replacement for ChatGPT API | news.ycombinator.com | 2024-01-24

  • chatbox

    Chatbox is a desktop client for ChatGPT, Claude and other LLMs, available on Windows, Mac, Linux

    • Project mention: Chatbox (latest versions) is not open source; AskHN: anything similar? | news.ycombinator.com | 2024-02-08

  • SaaSHub

    SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

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NOTE: The open source projects on this list are ordered by number of github stars. The number of mentions indicates repo mentiontions in the last 12 Months or since we started tracking (Dec 2020).

AI related posts

Index

What are some of the best open-source AI projects? This list will help you:

Project Stars
1 AutoGPT 161,096
2 stable-diffusion-webui 129,299
3 ChatGPT 46,892
4 generative-ai-for-beginners 42,394
5 ColossalAI 37,836
6 Kong 37,482
7 Open-Assistant 36,622
8 MockingBird 33,796
9 gold-miner 33,359
10 google-research 32,804
11 PhotoPrism 32,525
12 AI-For-Beginners 30,927
13 spaCy 28,704
14 Lobe Chat 28,579
15 AI-Expert-Roadmap 28,388
16 pytorch-lightning 26,883
17 upscayl 26,216
18 netron 26,040
19 dify 23,073
20 MindsDB 21,223
21 learnopencv 20,363
22 LocalAI 19,593
23 chatbox 18,459

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