This repository contains tools and libraries for building AIR platforms, runtimes and compilers.

Local RAG is an offline, open-source tool that allows users to ingest files for retrieval augmented generation (RAG) using large language models (LLMs) without relying on third parties or exposing sensitive data. It supports offline embeddings and LLMs, multiple sources including local files, GitHub repos, and websites, streaming responses, conversational memory, and chat export. Users can set up and deploy the app, learn how to use Local RAG, explore the RAG pipeline, check planned features, known bugs and issues, access additional resources, and contribute to the project.

Docling simplifies document processing, parsing diverse formats including advanced PDF understanding, and providing seamless integrations with the general AI ecosystem. It offers features such as parsing multiple document formats, advanced PDF understanding, unified DoclingDocument representation format, various export formats, local execution capabilities, plug-and-play integrations with agentic AI tools, extensive OCR support, and a simple CLI. Coming soon features include metadata extraction, visual language models, chart understanding, and complex chemistry understanding. Docling is installed via pip and works on macOS, Linux, and Windows environments. It provides detailed documentation, examples, integrations with popular frameworks, and support through the discussion section. The codebase is under the MIT license and has been developed by IBM.

NanoLLM is a tool designed for optimized local inference for Large Language Models (LLMs) using HuggingFace-like APIs. It supports quantization, vision/language models, multimodal agents, speech, vector DB, and RAG. The tool aims to provide efficient and effective processing for LLMs on local devices, enhancing performance and usability for various AI applications.

This repository is a collection of notes and code examples related to AI, covering topics such as Tokenization, Architectures, GGML, Llama.cpp, Position Embeddings, GPUs, Vector Databases, and Vision. It also includes in-progress work on Model Context Protocol (MCP) and Voice Activity Detection (VAD) for whisper.cpp. The repository offers exploration code for various AI-related concepts and tools like GGML, Llama.cpp, GPU technologies (CUDA, Kompute, Metal, OpenCL, ROCm, Vulkan), Word embeddings, Huggingface API, and Qdrant Vector Database in both Rust and Python.

Awesome CS Books is a curated list of books on computer science and technology. The books are organized by topic, including programming languages, software engineering, computer networks, operating systems, databases, data structures and algorithms, big data, architecture, and interviews. The books are available in PDF format and can be downloaded for free. The repository also includes links to free online courses and other resources.

Aippt is a commercial-grade AI tool for generating, parsing, and rendering PowerPoint presentations. It offers functionalities such as AI-powered PPT generation, PPT to JSON conversion, and JSON to PPT rendering. Users can experience online editing, upload PPT files for rendering, and download edited PPT files. The tool also supports commercial partnerships for custom industry solutions, native chart and animation support, user-defined templates, and competitive pricing. Aippt is available for commercial use with options for agency support and private deployment. The official website offers open APIs and an open platform for API/UI integration.

Fast-stable-diffusion is a project that offers notebooks for RunPod, Paperspace, and Colab Pro adaptations with AUTOMATIC1111 Webui and Dreambooth. It provides tools for running and implementing Dreambooth, a stable diffusion project. The project includes implementations by XavierXiao and is sponsored by Runpod, Paperspace, and Colab Pro.

Tero Subtitler is an open source, cross-platform, and free subtitle editing software with a user-friendly interface. It offers fully fledged editing with SMPTE and MEDIA modes, support for various subtitle formats, multi-level undo/redo, search and replace, auto-backup, source and transcription modes, translation memory, audiovisual preview, timeline with waveform visualizer, manipulation tools, formatting options, quality control features, translation and transcription capabilities, validation tools, automation for correcting errors, and more. It also includes features like exporting subtitles to MP3, importing/exporting Blu-ray SUP format, generating blank video, generating video with hardcoded subtitles, video dubbing, and more. The tool utilizes powerful multimedia playback engines like mpv, advanced audio/video manipulation tools like FFmpeg, tools for automatic transcription like whisper.cpp/Faster-Whisper, auto-translation API like Google Translate, and ElevenLabs TTS for video dubbing.

Docling is a tool that bundles PDF document conversion to JSON and Markdown in an easy, self-contained package. It can convert any PDF document to JSON or Markdown format, understand detailed page layout, reading order, recover table structures, extract metadata such as title, authors, references, and language, and optionally apply OCR for scanned PDFs. The tool is designed to be stable, lightning fast, and suitable for macOS and Linux environments.

LightLLM is a Python-based LLM (Large Language Model) inference and serving framework known for its lightweight design, scalability, and high-speed performance. It offers features like tri-process asynchronous collaboration, Nopad for efficient attention operations, dynamic batch scheduling, FlashAttention integration, tensor parallelism, Token Attention for zero memory waste, and Int8KV Cache. The tool supports various models like BLOOM, LLaMA, StarCoder, Qwen-7b, ChatGLM2-6b, Baichuan-7b, Baichuan2-7b, Baichuan2-13b, InternLM-7b, Yi-34b, Qwen-VL, Llava-7b, Mixtral, Stablelm, and MiniCPM. Users can deploy and query models using the provided server launch commands and interact with multimodal models like QWen-VL and Llava using specific queries and images.

Dubbo Kubernetes provides support for building and deploying Dubbo applications in various environments, including Kubernetes and Alibaba Cloud ACK. It includes dubboctl for command line utility, dubbod for the control plane built on Istio, navigator for configuring proxies at runtime, and operator for user-friendly options to operate the dubbo proxyless mesh.

MaixCDK (Maix C/CPP Development Kit) is a C/C++ development kit that integrates practical functions such as AI, machine vision, and IoT. It provides easy-to-use encapsulation for quickly building projects in vision, artificial intelligence, IoT, robotics, industrial cameras, and more. It supports hardware-accelerated execution of AI models, common vision algorithms, OpenCV, and interfaces for peripheral operations. MaixCDK offers cross-platform support, easy-to-use API, simple environment setup, online debugging, and a complete ecosystem including MaixPy and MaixVision. Supported devices include Sipeed MaixCAM, Sipeed MaixCAM-Pro, and partial support for Common Linux.

1Panel is an open-source, modern web-based control panel for Linux server management. It provides efficient management through a user-friendly web graphical interface, enabling users to effortlessly manage their Linux servers. Key features include host monitoring, file management, database administration, container management, rapid website deployment with WordPress integration, an application store for easy installation and updates, security and reliability through containerization and secure application deployment practices, integrated firewall management, log auditing capabilities, and one-click backup & restore functionality supporting various cloud storage solutions.

SWE-agent is a tool that allows language models to autonomously fix issues in GitHub repositories, perform tasks on the web, find cybersecurity vulnerabilities, and handle custom tasks. It uses configurable agent-computer interfaces (ACIs) to interact with isolated computer environments. The tool is built and maintained by researchers from Princeton University and Stanford University.

A distributed Java game server based on chess, card, and MMORPG games, theoretically capable of infinitely scaling gateway, lobby, and game servers to accommodate player numbers. It implements a cluster registration center, common servers such as gateway, login, and backend server monitoring; encapsulates Redis cluster, MongoDB, and other database handling; encapsulates message queues, thread models, and tools such as data import. The gateway server uses Mina to encapsulate TCP, UDP, WebSocket, HTTP communication, allowing the framework to support multiple protocol clients for gaming. Each directory ending with 'scripts' contains script files for the corresponding projects.

This repository contains tools and libraries for building AIR platforms, runtimes and compilers.

A curated list of AI coding tools, including code completion, refactoring, and assistants. This list includes both open-source and commercial tools, as well as tools that are still in development. Some of the most popular AI coding tools include GitHub Copilot, CodiumAI, Codeium, Tabnine, and Replit Ghostwriter.

This repository extends the LLVM framework to generate code for use with AMD/Xilinx AI Engine processors. AI Engine processors are in-order, exposed-pipeline VLIW processors focused on application acceleration for AI, Machine Learning, and DSP applications. The repository adds LLVM support for specific features like non-power of 2 pointers, operand latencies, resource conflicts, negative operand latencies, slot assignment, relocations, code alignment restrictions, and register allocation. It includes support for Clang, LLD, binutils, Compiler-RT, and LLVM-LIBC.

AI Prompt Runner for VSCode is a research prototype project that provides a VSCode extension to run prompts. Users can install the extension, set a secret key, and run prompts to get results for any project. The tool is designed for developers and researchers to experiment with AI prompts within the VSCode environment.

Langtrace is an open source observability software that lets you capture, debug, and analyze traces and metrics from all your applications that leverage LLM APIs, Vector Databases, and LLM-based Frameworks. It supports Open Telemetry Standards (OTEL), and the traces generated adhere to these standards. Langtrace offers both a managed SaaS version (Langtrace Cloud) and a self-hosted option. The SDKs for both Typescript/Javascript and Python are available, making it easy to integrate Langtrace into your applications. Langtrace automatically captures traces from various vendors, including OpenAI, Anthropic, Azure OpenAI, Langchain, LlamaIndex, Pinecone, and ChromaDB.

AskUI is a reliable, automated end-to-end automation tool that only depends on what is shown on your screen instead of the technology or platform you are running on.

Air is a live-reloading command line utility for developing Go applications. It provides colorful log output, customizable build or any command, support for excluding subdirectories, and allows watching new directories after Air started. Users can overwrite specific configuration from arguments and pass runtime arguments for running the built binary. Air can be installed via `go install`, `install.sh`, or `goblin.run`, and can also be used with Docker/Podman. It supports debugging, Docker Compose, and provides a Q&A section for common issues. The tool requires Go 1.16+ for development and welcomes pull requests. Air is released under the GNU General Public License v3.0.

AgentNeo is an advanced, open-source Agentic AI Application Observability, Monitoring, and Evaluation Framework designed to provide deep insights into AI agents, Large Language Model (LLM) calls, and tool interactions. It offers robust logging, visualization, and evaluation capabilities to help debug and optimize AI applications with ease. With features like tracing LLM calls, monitoring agents and tools, tracking interactions, detailed metrics collection, flexible data storage, simple instrumentation, interactive dashboard, project management, execution graph visualization, and evaluation tools, AgentNeo empowers users to build efficient, cost-effective, and high-quality AI-driven solutions.

The ByteIR Project is a ByteDance model compilation solution. ByteIR includes compiler, runtime, and frontends, and provides an end-to-end model compilation solution. Although all ByteIR components (compiler/runtime/frontends) are together to provide an end-to-end solution, and all under the same umbrella of this repository, each component technically can perform independently. The name, ByteIR, comes from a legacy purpose internally. The ByteIR project is NOT an IR spec definition project. Instead, in most scenarios, ByteIR directly uses several upstream MLIR dialects and Google Mhlo. Most of ByteIR compiler passes are compatible with the selected upstream MLIR dialects and Google Mhlo.

This repository contains tools and libraries for building AIR platforms, runtimes and compilers.

Husky is a research-focused programming language designed for next-generation computing. It aims to provide a powerful and ergonomic development experience for various tasks, including system level programming, web/native frontend development, parser/compiler tasks, game development, formal verification, machine learning, and more. With a strong type system and support for human-in-the-loop programming, Husky enables users to tackle complex tasks such as explainable image classification, natural language processing, and reinforcement learning. The language prioritizes debugging, visualization, and human-computer interaction, offering agile compilation and evaluation, multiparadigm support, and a commitment to a good ecosystem.

Aiwnios is a HolyC Compiler/Runtime designed for 64-bit ARM, RISCV, and x86 machines, including Apple M1 Macs, with plans for supporting other architectures in the future. The project is currently a work in progress, with regular updates and improvements planned. Aiwnios includes a sockets API (currently tested on FreeBSD) and a HolyC assembler accessible through AARCH64. The heart of Aiwnios lies in `arm_backend.c`, where the compiler is located, and a powerful AARCH64 assembler in `arm64_asm.c`. The compiler uses reverse Polish notation and statements are reversed. The developer manual is intended for developers working on the C side, providing detailed explanations of the source code.

Llama3.java is a practical Llama 3 inference tool implemented in a single Java file. It serves as the successor of llama2.java and is designed for testing and tuning compiler optimizations and features on the JVM, especially for the Graal compiler. The tool features a GGUF format parser, Llama 3 tokenizer, Grouped-Query Attention inference, support for Q8_0 and Q4_0 quantizations, fast matrix-vector multiplication routines using Java's Vector API, and a simple CLI with 'chat' and 'instruct' modes. Users can download quantized .gguf files from huggingface.co for model usage and can also manually quantize to pure 'Q4_0'. The tool requires Java 21+ and supports running from source or building a JAR file for execution. Performance benchmarks show varying tokens/s rates for different models and implementations on different hardware setups.

This repository extends the LLVM framework to generate code for use with AMD/Xilinx AI Engine processors. AI Engine processors are in-order, exposed-pipeline VLIW processors focused on application acceleration for AI, Machine Learning, and DSP applications. The repository adds LLVM support for specific features like non-power of 2 pointers, operand latencies, resource conflicts, negative operand latencies, slot assignment, relocations, code alignment restrictions, and register allocation. It includes support for Clang, LLD, binutils, Compiler-RT, and LLVM-LIBC.

This repository contains an early-phase IREE compiler and runtime plugin for interfacing the AMD AIE accelerator to IREE. It provides architectural overview, developer setup instructions, building guidelines, and runtime driver setup details. The repository focuses on enabling the integration of the AMD AIE accelerator with IREE, offering developers the tools and resources needed to build and run applications leveraging this technology.

AILZ80ASM is a Z80 assembler that runs in a .NET 8 environment written in C#. It can be used to assemble Z80 assembly code and generate output files in various formats. The tool supports various command-line options for customization and provides features like macros, conditional assembly, and error checking. AILZ80ASM offers good performance metrics with fast assembly times and efficient output file sizes. It also includes support for handling different file encodings and provides a range of built-in functions for working with labels, expressions, and data types.