alvinreal/awesome-opensource-ai

精心策划的开源人工智能模型、库、基础设施和开发者工具。

  svgdiagram.ai ·将你的笔记整理成干净、可编辑的SVG图表

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贡献

目录

• 1.核心框架与库
• 2.模型代码库与模型族
• 3.推理引擎与服务
• 4.智能人工智能与多智能体系统
• 5.检索增强生成（RAG）与知识
• 6.生成媒体工具
• 7.培训与微调生态系统
• 8.MLOps / LLMOps 与生产
• 9.评估、基准与数据集
• 10.人工智能安全、对齐与可解释性
• 11.专业领域
• 12.用户界面与自托管平台
• 13.开发工具与集成
• 14.资源与学习

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关于这份名单

Awesome Open Source AI 是一份为使用 AI 构建的开源项目精选列表。

目标是帮助读者在不通过目录转储中筛选的情况下，找到有用的模型、库、工具、基础设施、数据集和学习资源。

项目不需要包含最低数量的GitHub星号。星号可以作为有用的上下文，但它们只是一个信号。

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Contents

• 1. Core Frameworks & Libraries
• 2. Model Codebases & Model Families
• 3. Inference Engines & Serving
• 4. Agentic AI & Multi-Agent Systems
• 5. Retrieval-Augmented Generation (RAG) & Knowledge
• 6. Generative Media Tools
• 7. Training & Fine-tuning Ecosystem
• 8. MLOps / LLMOps & Production
• 9. Evaluation, Benchmarks & Datasets
• 10. AI Safety, Alignment & Interpretability
• 11. Specialized Domains
• 12. User Interfaces & Self-hosted Platforms
• 13. Developer Tools & Integrations
• 14. Resources & Learning

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About this list

Awesome Open Source AI is a curated list of open-source projects for people building with AI.

The goal is to help readers find useful models, libraries, tools, infrastructure, datasets, and learning resources without sorting through a directory dump.

Projects do not need a minimum number of GitHub stars to be included. Stars can be useful context, but they are only one signal. A smaller project may belong here if it is useful, well-maintained, technically interesting, clearly documented, or important to a specific part of the AI ecosystem.

Good entries should have a clear reason to exist. They should help people build, study, run, evaluate, or understand AI systems.

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1. Core Frameworks & Libraries

Core libraries and frameworks used to build, train, and run AI and machine learning systems.

Deep Learning Frameworks

• PyTorch - Dynamic computation graphs, Pythonic API, dominant in research and production. The current standard for most frontier AI work.