Project Library

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.

A video translation and dubbing tool powered by LLMs, offering professional-grade translations and one-click full-process deployment. It can generate content optimized for platforms like YouTube，TikTok, and Shorts. 基于AI大模型的视频翻译和配音工具，专业级翻译，一键部署全流程，可以生成适配抖音，小红书，哔哩哔哩，视频号，TikTok，Youtube Shorts等形态的内容

10 Lessons to Get Started Building AI Agents

Fast and extensible multi-platform HTTP/1-2-3 web server with automatic HTTPS

🔥 Turn entire websites into LLM-ready markdown or structured data. Scrape, crawl and extract with a single API.

The Google Cloud Client Libraries for Go provide Go packages to interact with Google Cloud Platform (GCP) services. These libraries support the two most recent major Go releases and offer seamless authentication using Application Default Credentials (ADC), simplifying integration in GCP environments like Compute Engine, Kubernetes Engine, and App Engine. For local development, authentication can be configured using the Google Cloud CLI or service account key files. The libraries are under active development, with occasional backward-incompatible changes. Contributions are encouraged, following the project’s Contributor Code of Conduct. Comprehensive documentation and quickstart guides are available for various GCP services, including App Engine, Cloud Functions, and Cloud Run.

The **AI Engineering Hub** is a comprehensive resource for AI practitioners, offering in-depth tutorials on **LLMs and RAGs**, real-world **AI agent** applications, and scalable implementation examples. Designed for all skill levels, it supports learning, experimentation, and project adaptation in AI engineering. Contributors are encouraged to enhance the repository through forks, branches, and pull requests. Stay updated with the latest insights and tutorials by subscribing to the newsletter, which includes a free Data Science eBook. The project is licensed under MIT, fostering open collaboration and community engagement. Connect via issues or direct communication for discussions and suggestions.

WeChatMsg is a project designed to empower users to take control of their WeChat data, emphasizing the preservation of personal memories and interactions. It supports WeChat 4.0, offering features like local database access, chat interface restoration, and comprehensive data export options (SQLite, HTML, CSV, TXT, Word). The project also includes chat data analysis and visualization, enabling users to generate personalized annual reports. With a focus on user-friendly design, it features a streamlined UI, lower memory usage, and faster export speeds. WeChatMsg is built on the principle of "My Data, My Control," ensuring users can retain and utilize their digital footprints responsibly. It is open-source, encouraging community contributions and fostering innovation in personal AI development.

This project is the first semester of the girafe-ai Machine Learning course, designed to provide foundational knowledge in ML. It includes weekly lectures, seminars, and assignments covering key topics such as Naive Bayes, kNN, linear regression, SVM, PCA, trees, ensembles, gradient boosting, and deep learning concepts like backpropagation, dropout, and embeddings. The course features recorded lectures, slides, and practical assignments with deadlines, supplemented by additional materials and literature. Prerequisites and an exam program are provided for structured learning. Authored by Radoslav Neychev and Vladislav Goncharenko, with contributions from several experts, the course is ideal for beginners seeking a comprehensive introduction to machine learning.

"Free-for.dev" is a curated list of SaaS, PaaS, IaaS, and other services offering free tiers specifically tailored for developers, system administrators, and DevOps practitioners. It focuses on infrastructure-related tools, excluding self-hosted software and short-term trials. The list emphasizes services with free tiers lasting at least a year and ensures security features like TLS are not restricted to paid plans. Contributions are community-driven, with over 1,600 contributors adding or updating entries via pull requests. Categories include cloud providers, CI/CD, monitoring, APIs, storage, and more, making it a valuable resource for developers seeking cost-effective solutions for their projects.

Swift is a high-performance, modern system programming language designed for safety, speed, and expressiveness. It features a clean syntax, seamless interoperability with C and Objective-C, and memory safety by default. Swift supports a wide range of platforms, including macOS, Ubuntu, Amazon Linux, Debian, Fedora, and Windows, across architectures like x86_64, AArch64, and ARM64. It also enables cross-compilation for targets such as WebAssembly (Wasm). Swift embraces modular design, eliminating headers and code duplication, while offering high-level constructs like objects, protocols, closures, and generics. The project encourages community contributions and provides comprehensive documentation for building, debugging, and contributing to the compiler. Swift aims to foster a diverse and inclusive developer community.

Protocol Buffers (protobuf) is Google's language-neutral, platform-neutral, and extensible data interchange format for serializing structured data. It includes a protocol compiler (`protoc`) for compiling `.proto` files and runtime libraries for multiple programming languages, such as C++, Java, Python, Go, and more. Protobuf supports installation via pre-built binaries or source compilation, with detailed instructions provided for each language. It integrates with Bazel for build management and offers extensive documentation, tutorials, and examples for quick onboarding. Protobuf is widely used for efficient data serialization, enabling seamless communication across diverse systems and platforms. Its active developer community and version support policy ensure ongoing reliability and updates.

Redmine is a versatile, open-source project management tool built on the Ruby on Rails framework. It offers a comprehensive suite of features including issue tracking, Gantt charts, calendars, time tracking, and document management. Designed for flexibility, Redmine supports multiple projects, roles, and workflows, making it suitable for teams of all sizes. Its plugin system allows for extensive customization, while integration with version control systems like Git and SVN enhances collaboration. Redmine’s user-friendly interface and multi-language support ensure accessibility for global teams. Ideal for managing complex projects, it provides robust tools for planning, monitoring, and reporting, streamlining project execution and improving productivity.

Union is a hyper-efficient zero-knowledge infrastructure layer designed for general message passing, asset transfers, NFTs, and DeFi. It operates without dependencies on trusted third parties, oracles, multi-signatures, or MPC, leveraging Consensus Verification for security. Union is compatible with Cosmos chains via IBC and connects to EVM chains like Ethereum, Berachain, and Arbitrum. Its decentralized governance controls contract upgrades, connections, token configurations, and protocol evolution. Key components include `uniond` (node implementation), `galoisd` (ZK prover), `voyager` (cross-ecosystem relayer), and `hubble` (chain indexer). Built with Go, Rust, and Solidity, Union supports reproducible builds via Nix and offers a TypeScript SDK for interaction. It aims to align priorities among users, validators, and operators through decentralized governance.

FunASR is a comprehensive end-to-end speech recognition toolkit designed to bridge academic research and industrial applications. It supports a wide range of functionalities, including speech recognition (ASR), voice activity detection (VAD), punctuation restoration, language models, speaker verification, and diarization. The toolkit offers pre-trained models like Paraformer-large, known for high accuracy and efficiency, and supports both streaming and non-streaming ASR. FunASR provides easy-to-use scripts, tutorials, and deployment options for inference and fine-tuning, making it accessible for researchers and developers. It also integrates with platforms like ModelScope and Hugging Face, offering a vast collection of models for various languages and tasks.