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Top 23 AI Open-Source Projects
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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.
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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generative-ai-for-beginners
18 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
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Open-Assistant
OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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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
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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.
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pytorch-lightning
Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.
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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.
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chatgpt-on-wechat
基于大模型搭建的聊天机器人，同时支持 企业微信、微信 公众号、飞书、钉钉 等接入，可选择GPT3.5/GPT4.0/Claude/文心一言/讯飞星火/通义千问/Gemini/GLM-4/Claude/Kimi/LinkAI，能处理文本、语音和图片，访问操作系统和互联网，支持基于自有知识库进行定制企业智能客服。
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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.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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
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: a collection of resources to learn about Generative AI, including tutorials, code samples, and more.
For open assistant, the code: https://github.com/LAION-AI/Open-Assistant/tree/main/inference
Project mention: Show HN: Next-token prediction in JavaScript – build fast LLMs from scratch | news.ycombinator.com | 2024-04-10People 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]
Project mention: Show HN: Memories, FOSS Google Photos alternative built for high performance | news.ycombinator.com | 2024-03-21I 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.
🔗 https://github.com/microsoft/AI-For-Beginners 🔗 https://microsoft.github.io/AI-For-Beginners/
Project mention: The AI Revolution Is Crushing Thousands of Languages | news.ycombinator.com | 2024-04-25Get 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
Project mention: Step by step guide to create customized chatbot by using spaCy (Python NLP library) | dev.to | 2024-03-23Hi 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):
**[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.
Project mention: SB-1047 will stifle open-source AI and decrease safety | news.ycombinator.com | 2024-04-29It's very easy to get started, right in your Terminal, no fees! No credit card at all.
And there are cloud providers like https://replicate.com/ and https://lightning.ai/ that will let you use your LLM via an API key just like you did with OpenAI if you need that.
You don't need OpenAI - nobody does.
Project mention: A smooth and sharp image interpolation you probably haven't heard of | news.ycombinator.com | 2024-05-02Yes, with Upscayl, we’re already doing that (https://upscayl.org).
It’s not as fast yet but it’s extremely good. Good enough that you could print a low resolution image after upscaling.
Project mention: What's the best PyTorch model visualization tool? | news.ycombinator.com | 2024-04-28Netron seems to be the best that I've seen so far. https://github.com/lutzroeder/netron
Project mention: Ask HN: LLM workflows to avoid copying and pasting from the web interfaces? | news.ycombinator.com | 2024-05-03This visual IDE for LLM pipelines was posted recently: https://github.com/langgenius/dify
See if it helps.
Project mention: What’s the Difference Between Fine-tuning, Retraining, and RAG? | dev.to | 2024-04-08Check us out on GitHub.
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
Project mention: LocalAI: Self-hosted OpenAI alternative reaches 2.14.0 | news.ycombinator.com | 2024-05-03
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).
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Integrate Copilot feature into your React applications using CopilotKit
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Ask HN: LLM workflows to avoid copying and pasting from the web interfaces?
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Ask HN: What's with the Gatekeeping in Open Source?
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What Are You Building? Share Your Projects
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A smooth and sharp image interpolation you probably haven't heard of
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A note from our sponsor - InfluxDB
www.influxdata.com | 3 May 2024
Index
What are some of the best open-source AI projects? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | AutoGPT | 161,405 |
| 2 | stable-diffusion-webui | 129,975 |
| 3 | ChatGPT | 46,989 |
| 4 | generative-ai-for-beginners | 43,008 |
| 5 | ColossalAI | 37,911 |
| 6 | Kong | 37,537 |
| 7 | Open-Assistant | 36,647 |
| 8 | MockingBird | 33,862 |
| 9 | gold-miner | 33,390 |
| 10 | google-research | 32,863 |
| 11 | PhotoPrism | 32,687 |
| 12 | AI-For-Beginners | 31,259 |
| 13 | Lobe Chat | 29,259 |
| 14 | spaCy | 28,751 |
| 15 | AI-Expert-Roadmap | 28,418 |
| 16 | pytorch-lightning | 26,952 |
| 17 | upscayl | 26,430 |
| 18 | netron | 26,110 |
| 19 | dify | 25,645 |
| 20 | chatgpt-on-wechat | 24,945 |
| 21 | MindsDB | 21,312 |
| 22 | learnopencv | 20,408 |
| 23 | LocalAI | 19,862 |
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