AutoPR was a GitHub Action that autonomously generated pull requests in response to issues, triggered by adding a label containing AutoPR. It planned a fix, wrote code, pushed a branch and opened a pull request. The alpha-release action had limitations including incorrect references to code in other files, duplicated lines and calls to functions that don't exist, and worked only on GitHub. The repository was archived by the owner on Mar 5, 2026 and is now read-only.
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Automatic architecture search and hyperparameter optimization for PyTorch.
AutoRAG is a project developed by Marker-Inc-Korea that enables an agent to locate content on a user's computer. Its functionality improves with frequent use, and it includes an agent component with defined core values, architecture and operational details.
Automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator.
AutoViz is a Python library that automatically visualizes any dataset, any size, with a single line of code. It also offers the FixDQ() function for a quick assessment of dataset quality and fixing data quality issues. The project aims to provide an automated approach to exploratory data analysis through quick and easy data visualization plus data quality, abstracting away the complexities of various plotting libraries and techniques.
Awadb is an AI-native database built for working with embedding vectors. It is available as a public open-source repository on GitHub, where users can access the code, contribute to development, or deploy it locally on Mac OSX or Linux, or run it as a standalone service. The project is designed to support AI applications that rely on vector embedding functionality.
Awesome ADE is a curated GitHub list of open-source Agentic Development Environments, covering orchestrators, TUIs, tmux harnesses, sandboxes and the agents they run. It is maintained by KyroLabs and organized by packaging and stack layer.
Curated List of Top AI and ML Books.
A curated list of AI market maps from 2026, 2025, and 2024, by Joy Larkin.
A curated GitHub list of top AI models and large language models, organized into AI model hosting platforms and top LLMs sections. It includes hosting platforms such as Hugging Face and GitHub Models, and lists models from providers including Meta, Google, Mistral AI and DeepSeek. Contributions are made through pull requests.
You can also find more comprehensive list on and There's an AI AI Voice Cloning list.
A curated list of bootstrapped, pre-seed, and angel-funded AI products built by independent founders.
For a more complete list of AI writing assistants visit:.
Curated list of awesome projects and resources related to Argo.
Awesome AutoDL is a curated list of automated deep learning resources and an in-depth analysis, subtitled that neural architecture search is not the end. It collects papers, libraries and benchmarks covering neural architecture search and hyper-parameter optimization.
Curating a list of AutoML-related research, tools, projects and other resources.
Awesome AutoML Papers is a GitHub-hosted curated list focused on automated machine learning (AutoML). It aggregates academic papers, articles, tutorials, slide decks, and related projects in the AutoML field, serving as a centralized reference for users exploring automated machine learning research and developments.
A curated GitHub list of resources for ChatGPT and GPT-3 from OpenAI. It covers general resources such as the ChatGPT official app and API documentation, API tools, Chrome extensions, bots for platforms including Telegram, WhatsApp, Slack, Discord and Twitter, IDE plugins, desktop apps, tutorials, applications, CLI tools and example prompts.
Organizes AI tools and resources so people can browse and compare relevant services.
Organizes AI tools and resources so people can browse and compare relevant services.
Awesome Core ML Models is a GitHub repository that hosts the largest collection of Core ML models for iOS 11 and newer versions. It allows users to contribute new models to the list via GitHub.
A curated list of pretrained CoreML models.
Awesome Decision Tree Papers is a GitHub-hosted open repository that collects research papers on decision trees, classification trees, and regression trees. The repository includes associated code implementations for the papers, and organizes content by publication year, with entries covering 2020, 2021, and 2022. It serves as a resource for machine learning researchers and practitioners.
Organizes AI tools and resources so people can browse and compare relevant services.