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Top 23 Python Artificial intelligence 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.
AutoGPT (agpt.co): Open-source autonomous agent framework, released in 2023. Pioneering example of general-purpose agent architecture; known for demonstrating both promise and limitations of autonomous systems.
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OpenHands AGENTS.md
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Project mention: MiniMind: End-to-end GPT-style LLM training pipeline in pure PyTorch | news.ycombinator.com | 2026-03-23
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We use spaCy’s en_core_web_lg (Large) model as the underlying NLP engine. This gives the Redactor the linguistic context to understand that "Gatsby" in a book title should stay, but "Gatsby" mentioned as a person's name in a private letter might need to go.
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pytorch-lightning
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
Project mention: Shai-Hulud Themed Malware Found in the PyTorch Lightning AI Training Library | news.ycombinator.com | 2026-04-30One thing that makes me wonder is that there are 4 security issues raised and all of them were closed by some bot called `pl-ghost` [1][2][3][4]. In the end, only this one [4] properly handled.
[1] https://github.com/Lightning-AI/pytorch-lightning/issues/216...
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datasets
🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools
Project mention: GSoC 2026 Predictions: 30 NEW AI/ML/Security Organizations You Should Start Contributing to NOW! | dev.to | 2026-02-06 -
marimo
A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor.
Project mention: Pluto.jl 1.0 release – reactive notebook for Julia | news.ycombinator.com | 2026-06-03Pluto is great. I use it all the time. If you like the reactivity/reproducibility but are wedded to Python, you might want to check out Marimo, which is also great. [https://marimo.io/]
It too puts the output of a cell above the code so if you're unable to adapt to things that are different it's also probably not for you.
FWIW, Observable's Notebooks (Javascript) work the same way: output above the code that produces it. [https://observablehq.com/]
I too did not like having the output above the code but got over it pretty quickly. For plots, it's arguably better: usually, I want to see the plot before I see the 15 line invocation of some plot command. The thing that bugs me the most about Pluto now is that it really wants you to only have a single evaluating statement per cell. You have to wrap stuff in "block......end" if you want to e.g. define more than one variable in a cell.
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owl
🦉 OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation
Project mention: Launch: Eigent – Open-Source Local-First Multi-Agent Workforce Built on Camel-AI | news.ycombinator.com | 2025-07-30We built on top of our previous project OWL which ranked top 1 on GAIA: https://github.com/camel-ai/owl in March. For the Eigent update, we haven't got to benchmark it on GAIA yet. Will do it soon in the up coming weeks. Sorry for the confusion.
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Project mention: Tongyi DeepResearch – open-source 30B MoE Model that rivals OpenAI DeepResearch | news.ycombinator.com | 2025-11-02
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SuperAGI
<⚡️> SuperAGI - A dev-first open source autonomous AI agent framework. Enabling developers to build, manage & run useful autonomous agents quickly and reliably.
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camel
🐫 CAMEL: The first and the best multi-agent framework. Finding the Scaling Law of Agents. https://www.camel-ai.org
Project mention: Eigent: An open source Claude cowork alternative | news.ycombinator.com | 2026-01-14You can have a try; almost all sota models are supported all powered thanks to https://github.com/camel-ai/camel
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reinforcement-learning-an-introduction
Python Implementation of Reinforcement Learning: An Introduction
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Project mention: Lightning.ai – an enterprise managed inference platform for AI | news.ycombinator.com | 2025-10-09
After making model training simpler with PyTorch Lightning, Lightning.AI is now tackling the next bottleneck — inference. Their new managed service targets enterprises deploying LLMs and deep learning models at scale, emphasizing performance, cost-efficiency, and developer-friendly tooling.
Platform: https://lightning.ai/
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DALLE2-pytorch
Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch
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In vmstat, watch r, wa, bi, and us plus sy together. r is runnable processes, and if it stays above your CPU core count, the CPU is saturated. wa is CPU time waiting on I/O, and sustained values above 10 to 15 during training often mean dataloader workers are blocked on disk reads. bi is blocks received from storage, and high bi with high wa points to storage bottlenecks instead of compute. us + sy is total active CPU time, and if it is high while GPU-Util is low, preprocessing is outrunning the GPU. If wa is high, increase dataloader workers or switch to faster storage. If us + sy is high with low GPU-Util, move transforms to GPU with a library such as Kornia.
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git submodule add https://github.com/The-Pocket/PocketFlow.git vendor/pocketflow
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inference
Swap GPT for any LLM by changing a single line of code. Xinference lets you run open-source, speech, and multimodal models on cloud, on-prem, or your laptop — all through one unified, production-ready inference API.
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).
Python Artificial intelligence discussion
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A protocol for auditing AI agent harnesses
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I'm Scared About Biological Computing
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Shai-Hulud Themed Malware Found in the PyTorch Lightning AI Training Library
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PyTorch Lightning project quarantined by PyPI
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A note from our sponsor - SaaSHub
www.saashub.com | 10 Jun 2026
Index
What are some of the best open-source Artificial intelligence projects in Python? This list will help you:
| # | Project | Stars |
|---|---|---|
| 1 | AutoGPT | 184,738 |
| 2 | Deep-Live-Cam | 93,642 |
| 3 | OpenHands | 75,905 |
| 4 | minimind | 51,130 |
| 5 | DragGAN | 35,861 |
| 6 | spaCy | 33,632 |
| 7 | pytorch-lightning | 31,174 |
| 8 | cs249r_book | 24,710 |
| 9 | recommenders | 21,733 |
| 10 | datasets | 21,586 |
| 11 | marimo | 21,294 |
| 12 | onnx | 20,933 |
| 13 | owl | 19,822 |
| 14 | DeepResearch | 19,255 |
| 15 | SuperAGI | 17,464 |
| 16 | camel | 17,122 |
| 17 | reinforcement-learning-an-introduction | 14,640 |
| 18 | litgpt | 13,408 |
| 19 | DALLE2-pytorch | 11,317 |
| 20 | Kornia | 11,227 |
| 21 | fiftyone | 10,764 |
| 22 | PocketFlow | 10,713 |
| 23 | inference | 9,338 |
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