Open-source AI and machine learning tools on GitHub — LLM frameworks, model runtimes, agents and training libraries, ranked by stars and reviewed by TopGit.
Superpowers is an open-source (MIT) skills library and bootstrap instruction set that turns a coding agent's ad-hoc habits into a fixed pipeline: brainstorm a spec, write a plan, build under TDD, review, then close out the branch. Skills trigger automatically once installed, and the same methodology works across eleven different agent harnesses, each requiring its own install step.
TensorFlow is Google's open-source, end-to-end platform for machine learning, hosted at tensorflow/tensorflow under the Apache-2.0 license. It was originally built within Google Brain's Machine Intelligence team for ML and neural network research, and today it ships stable Python and C++ APIs alongside GPU, CPU-only, and Docker install paths. The README positions it as covering both research work and shipping ML-powered applications.
AutoGPT is an open-source platform designed for building, deploying, and running AI agents that can carry out complete workflows. Users can define tasks in plain English or use a visual builder to shape each step. The project offers two primary paths: a managed, hosted AutoGPT Platform that handles infrastructure and model access for a fee, and a self-hosting option that is free but requires users to provide their own infrastructure and model API keys. Agents can run on demand, on schedules, or from triggers, connecting to over 45 platforms and hundreds of AI models. It's presented as a tool to automate various functions, from executive operations and sales research to marketing campaign drafts and incident triage in engineering.
anthropics/skills is Anthropic's public collection of Agent Skills for Claude — SKILL.md folders spanning creative, technical, enterprise, and document tasks, plus a spec and a template for building your own.
prompts.chat is an open-source library of prompts written for AI chat assistants, first released in December 2022 under the name Awesome ChatGPT Prompts. The GitHub project has since grown and now distributes prompts through a website, a CSV file, a Markdown file, and a Hugging Face dataset, alongside a self-hosting option, a CLI, an MCP server, and a Claude Code plugin.
prompts.chat is the largest open-source prompt library for AI, formerly called Awesome ChatGPT Prompts. It hosts curated prompts in CSV and Markdown, available as a public website, Hugging Face dataset, or self-hosted instance. The project supports multiple LLM providers including ChatGPT, Claude, Gemini, Llama, and Mistral. Self-hosting uses a Next.js setup wizard that configures authentication via GitHub, Google, or Azure AD, with PostgreSQL as the recommended database. CLI access, an MCP server, and a Claude Code plugin extend its reach into developer workflows. The codebase is MIT-licensed while prompt data falls under CC0. Its 166k GitHub stars make it an AI resource on the platform with 166k GitHub stars, and it has been cited by Harvard, Columbia, and Forbes.
Hugging Face Transformers (huggingface/transformers) is a Python library that centralizes model definitions for text, computer vision, audio, video, and multimodal machine learning, covering both inference and training. The README describes it as a pivot point compatible with training frameworks such as Axolotl, DeepSpeed, and PyTorch-Lightning, and inference engines such as vLLM, SGLang, and TGI, with more than 1M+ model checkpoints listed on the Hugging Face Hub.
Firecrawl is an API and set of SDKs for turning any URL into Markdown, structured JSON, or a screenshot, handling JS rendering and proxy rotation itself. It's built for feeding AI agents and LLM pipelines clean web data, with dedicated search, crawl, map, and agent endpoints, an MCP server, and SDKs for nine languages.
JavaGuide là một repository tổng hợp kiến thức phỏng vấn Java và backend được duy trì bởi cộng đồng, bao phủ gần như toàn bộ các chủ đề mà một ứng viên backend cần nắm vững: từ Java core (collections, concurrency, JVM), hệ điều hành và mạng máy tính, cho đến cơ sở dữ liệu (MySQL, Redis), kiến trúc phân tán, và các công cụ devops như Docker, Git. Điểm mạnh rõ rệt là mỗi phần đều đi kèm bài tổng hợp câu hỏi phỏng vấn được đánh dấu "必看" (bắt buộc đọc), kèm theo phân tích source code chi tiết cho các cấu trúc dữ liệu phổ biến như HashMap, ConcurrentHashMap, và các topic nâng cao như AQS, JMM. Repository cũng mở rộng sang AI application development với một repo riêng (AIGuide) về LLM, Agent, RAG và MCP, phản ánh xu hướng hiện tại trong việc tuyển dụng backend. Nhược điểm là nội dung rất dàn trải — hơn 100 file markdown trải dài từ BigDecimal đến Elasticsearch, nên nếu bạn đã có nền tảng vững ở một số phần, việc lọc đúng nội dung cần ôn tập đòi hỏi thêm effort. Cá nhân tôi thấy đây là tài liệu tốt nhất để "làm quen" với toàn cảnh backend Java trước khi đi sâu vào từng chủ đề riêng lẻ, nhưng không nên dùng nó thay cho việc đọc source code thật hoặc tài liệu chính thức.
Langflow pairs a drag-and-drop canvas with editable Python components, letting you build an LLM-powered agent flow and ship it as an API, MCP server, or JSON export.
Dify is an open-source LLM app platform that packages a visual workflow/agent builder, RAG pipeline, model provider management, and app-level APIs into one self-hostable (or cloud) stack, aimed at teams who want to skip stitching those pieces together themselves.
LangChain is a Python framework (MIT-licensed) for assembling LLM-powered apps and agents from standard components: model wrappers, prompts, retrieval, tools, and chain/graph orchestration handed off to LangGraph. It's for developers gluing together model providers and data sources, not for a single prompt-response call.
A GPL-3.0 GitHub repo compiling system prompts, tool definitions, and model names for 25+ AI products, from Cursor and Claude Code to lesser-known agents like Cluely and Qoder.
The Agency is a collection of specialized AI agent personas — markdown prompt files with a defined identity, workflow, and success metrics — for Claude Code, Cursor, and other AI tools, installable through a CLI script or a native desktop app.
Shubhamsaboo/awesome-llm-apps is a substantial collection of over 100 open-source AI agents, agent skills, and Retrieval Augmented Generation (RAG) applications. Hand-built, end-to-end tested, and licensed under Apache-2.0, this Python-based repository supports a range of LLMs including Claude, Gemini, GPT, DeepSeek, Llama, and Qwen. It offers a wide array of examples, from single-file starter agents and advanced multi-agent teams to voice AI agents, generative UIs, autonomous game-playing agents, and various RAG implementations. The collection also includes LLM optimization tools, fine-tuning recipes, and crash courses on agent frameworks, providing practical, ready-to-deploy solutions for common LLM development challenges.
gstack is Garry Tan's open-source pack of 23 Claude Code skills and 8 power tools — a CEO, an eng manager, a QA lead, a security officer, and more — each a Markdown slash command that runs one stage of a sprint from idea to a shipped PR. It's MIT-licensed and free, documented as a roughly 30-second install for Claude Code, with setup support for OpenClaw, Cursor, and seven more agents.
llama.cpp is an open-source project at ggml-org/llama.cpp that implements LLM and VLM inference in plain C/C++ with no external dependencies, built on top of the ggml tensor library. The README documents support for x86 SIMD, Apple Silicon, RISC-V, and GPU backends including CUDA, HIP, MUSA, Vulkan, and SYCL, along with quantization down to 1.5-bit, a CLI, and an OpenAI-compatible server.
Microsoft's introductory course on building generative AI applications walks you through 21 structured lessons created by Microsoft Cloud Advocates. The curriculum alternates between conceptual 'Learn' lessons and hands-on 'Build' lessons, progressing from LLM fundamentals through advanced topics like RAG, AI agents, and fine-tuning. Each lesson includes a written explanation, video introduction, and working code samples in both Python and TypeScript. Basic Python or TypeScript knowledge is expected. The course supports Azure OpenAI, OpenAI API, Microsoft Foundry Models, and Foundry Local for fully offline execution. With over 50 language translations maintained via automated GitHub Actions, it's accessible to a global developer audience. MIT licensed with an active Discord community and developer forum for peer support.
Browser Use provides a framework for AI agents to interact with web browsers, enabling automated tasks like form filling, data extraction, and QA testing. It offers both a Python library for programmatic control and a CLI for agent-driven workflows, supporting various LLMs and offering cloud services for scalability and advanced browser fingerprinting.
MoneyPrinterTurbo is a self-hosted AI video generation pipeline that automates scriptwriting, stock footage selection, text-to-speech narration, subtitle rendering, and ffmpeg-based video assembly into HD MP4s. It ships with four interfaces (WebUI, API, CLI, AI Agent) and supports batch production. The tool is particularly attractive for creators who need volume at low per-video cost, since you supply your own API keys rather than paying per-export fees. Setup involves Python 3.11+, at least one LLM provider (many supported), and ffmpeg — Whisper captioning is optional but demands a multi-gigabyte model download. It's a legitimate workhorse for automated short video workflows, not a toy.
FastGPT is an AI Agent building platform that provides out-of-the-box capabilities for data processing, RAG retrieval, and model calling, all built on large language models. It allows for visual workflow orchestration via its Flow feature to create complex application scenarios. Users can deploy it via Docker or Sealos Cloud for self-hosting, use a cloud service version, or opt for a commercial version with additional features and support. Key functionalities include Agent Skill orchestration, knowledge base management with support for various file types (TXT, MD, HTML, PDF, Docx, PPTX, CSV, XLSX, URL), hybrid retrieval, and debugging tools like full call chain logs. The project is licensed under the FastGPT Open Source License, which permits direct commercial use as a backend service but prohibits SaaS offerings without specific commercial authorization.
Sim is a TypeScript-based platform for building, deploying, and managing AI agents and their associated workflows. It functions as a central intelligence layer, enabling connections to over 1,000 integrations and major LLMs such as OpenAI, Anthropic, DeepSeek, and Gemini. Users can construct agents visually, conversationally, or with code, and integrate various data sources like files, knowledge bases, and structured table data. The platform offers a unified workspace for chat, workflows, and data management, including built-in features for tables, file storage, and knowledge bases. It supports both a cloud-hosted version and self-hosting, requiring Bun and Docker, with installation options for local development, Docker Compose, or Kubernetes via Helm. Additionally, it integrates with local models through Ollama and vLLM. The project is licensed under Apache-2.0.
oh-my-openagent is an open-source project from code-yeongyu that adds multi-agent orchestration on top of coding-agent hosts. It ships as three editions — Ultimate for OpenCode, Light for Codex CLI (installed via LazyCodex), and a standalone Senpi beta — each layering agents, hooks, and MCP servers so a single `ultrawork` command can drive a task to completion.
LibreChat is an open-source, self-hosted AI chat platform designed as an enhanced ChatGPT clone, providing a unified interface for a broad spectrum of AI models from providers like OpenAI, Anthropic, Google, and AWS Bedrock, alongside support for custom and local endpoints. It focuses on user control and privacy, offering features such as a sandboxed Code Interpreter for various programming languages, customizable AI agents with skills and subagents, integrated web search, and generative UI for creating code artifacts. The platform also includes comprehensive multi-user authentication, an admin panel for managing users and configurations, multimodal interaction capabilities, and a multilingual interface, making it a versatile solution for individuals and organizations seeking to manage their AI conversations and infrastructure.
TensorFlow is Google's open-source, end-to-end platform for machine learning, hosted at tensorflow/tensorflow under the Apache-2.0 license. It was originally built within Google Brain's Machine Intelligence team for ML and neural network research, and today it ships stable Python and C++ APIs alongside GPU, CPU-only, and Docker install paths. The README positions it as covering both research work and shipping ML-powered applications.
DeepSeek-Reasonix is a Go-based AI coding agent designed to operate directly from your terminal, as a desktop application, or integrated into VS Code. It's engineered to work natively with DeepSeek models, focusing on prefix-cache stability to keep token costs down during long coding sessions. The project emphasizes configurability through a TOML file for defining providers, agents, and tools, and it supports any OpenAI-compatible endpoint. Its plugin-driven architecture and single-binary distribution make it a flexible and easy-to-deploy option for developers seeking an efficient, deeply integrated AI coding assistant.
Teable is an AI-powered spreadsheet and database collaboration platform built on PostgreSQL, designed to help businesses manage data, build custom applications, and automate workflows with AI. It combines a user-friendly spreadsheet interface with a backend with integrity and performance, enabling AI agents to interact directly with live data for tasks like natural language querying, app generation, workflow automation, and data enrichment. Available as a cloud service or a self-hosted solution, Teable offers features like various data views, real-time collaboration, and SQL querying, while its full self-hosted version includes an isolated agent sandbox and an app deployment platform. It aims to provide a controlled environment for integrating AI into business processes, allowing teams to develop tailored software extensions quickly.
Orca is a desktop, mobile, and VPS app written in TypeScript that runs several coding agents at once, each in its own git worktree, with a built-in terminal, a browser-based Design Mode, and a CLI for scripting the same workflow.
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
中文分词 词性标注 命名实体识别 依存句法分析 成分句法分析 语义依存分析 语义角色标注 指代消解 风格转换 语义相似度 新词发现 关键词短语提取 自动摘要 文本分类聚类 拼音简繁转换 自然语言处理
OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation
💫 Industrial-strength Natural Language Processing (NLP) in Python
Visualizer for neural network, deep learning and machine learning models
An LLM-powered knowledge curation system that researches a topic and generates a full-length report with citations.
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
Integrate cutting-edge LLM technology quickly and easily into your apps
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
