RoboMatrix is a skill-centric hierarchical framework for scalable robot task planning and execution in an open-world environment. It provides a structured approach to robot task execution using a combination of hardware components, environment configuration, installation procedures, and data collection methods. The framework is developed using the ROS2 framework on Ubuntu and supports robots from DJI's RoboMaster series. Users can follow the provided installation guidance to set up RoboMatrix and utilize it for various tasks such as data collection, task execution, and dataset construction. The framework also includes a supervised fine-tuning dataset and aims to optimize communication and release additional components in the future.

ShellChatGPT is a shell wrapper for OpenAI's ChatGPT, DALL-E, Whisper, and TTS, featuring integration with LocalAI, Ollama, Gemini, Mistral, Groq, and GitHub Models. It provides text and chat completions, vision, reasoning, and audio models, voice-in and voice-out chatting mode, text editor interface, markdown rendering support, session management, instruction prompt manager, integration with various service providers, command line completion, file picker dialogs, color scheme personalization, stdin and text file input support, and compatibility with Linux, FreeBSD, MacOS, and Termux for a responsive experience.

ControlLLM is a framework that empowers large language models to leverage multi-modal tools for solving complex real-world tasks. It addresses challenges like ambiguous user prompts, inaccurate tool selection, and inefficient tool scheduling by utilizing a task decomposer, a Thoughts-on-Graph paradigm, and an execution engine with a rich toolbox. The framework excels in tasks involving image, audio, and video processing, showcasing superior accuracy, efficiency, and versatility compared to existing methods.

Humanoid-Gym is a reinforcement learning framework designed for training locomotion skills for humanoid robots, focusing on zero-shot transfer from simulation to real-world environments. It integrates a sim-to-sim framework from Isaac Gym to Mujoco for verifying trained policies in different physical simulations. The codebase is verified with RobotEra's XBot-S and XBot-L humanoid robots. It offers comprehensive training guidelines, step-by-step configuration instructions, and execution scripts for easy deployment. The sim2sim support allows transferring trained policies to accurate simulated environments. The upcoming features include Denoising World Model Learning and Dexterous Hand Manipulation. Installation and usage guides are provided along with examples for training PPO policies and sim-to-sim transformations. The code structure includes environment and configuration files, with instructions on adding new environments. Troubleshooting tips are provided for common issues, along with a citation and acknowledgment section.

llm-compressor is an easy-to-use library for optimizing models for deployment with vllm. It provides a comprehensive set of quantization algorithms, seamless integration with Hugging Face models and repositories, and supports mixed precision, activation quantization, and sparsity. Supported algorithms include PTQ, GPTQ, SmoothQuant, and SparseGPT. Installation can be done via git clone and local pip install. Compression can be easily applied by selecting an algorithm and calling the oneshot API. The library also offers end-to-end examples for model compression. Contributions to the code, examples, integrations, and documentation are appreciated.

OASIS is a scalable, open-source social media simulator that integrates large language models with rule-based agents to realistically mimic the behavior of up to one million users on platforms like Twitter and Reddit. It facilitates the study of complex social phenomena such as information spread, group polarization, and herd behavior, offering a versatile tool for exploring diverse social dynamics and user interactions in digital environments. With features like scalability, dynamic environments, diverse action spaces, and integrated recommendation systems, OASIS provides a comprehensive platform for simulating social media interactions at a large scale.

KrillinAI is a video subtitle translation and dubbing tool based on AI large models, featuring speech recognition, intelligent sentence segmentation, professional translation, and one-click deployment of the entire process. It provides a one-stop workflow from video downloading to the final product, empowering cross-language cultural communication with AI. The tool supports multiple languages for input and translation, integrates features like automatic dependency installation, video downloading from platforms like YouTube and Bilibili, high-speed subtitle recognition, intelligent subtitle segmentation and alignment, custom vocabulary replacement, professional-level translation engine, and diverse external service selection for speech and large model services.

VideoTree is an official implementation for a query-adaptive and hierarchical framework for understanding long videos with LLMs. It dynamically extracts query-related information from input videos and builds a tree-based video representation for LLM reasoning. The tool requires Python 3.8 or above and leverages models like LaViLa and EVA-CLIP-8B for feature extraction. It also provides scripts for tasks like Adaptive Breath Expansion, Relevance-based Depth Expansion, and LLM Reasoning. The codebase is being updated to incorporate scripts/captions for NeXT-QA and IntentQA in the future.

llm-colosseum is a tool designed to evaluate Language Model Models (LLMs) in real-time by making them fight each other in Street Fighter III. The tool assesses LLMs based on speed, strategic thinking, adaptability, out-of-the-box thinking, and resilience. It provides a benchmark for LLMs to understand their environment and take context-based actions. Users can analyze the performance of different LLMs through ELO rankings and win rate matrices. The tool allows users to run experiments, test different LLM models, and customize prompts for LLM interactions. It offers installation instructions, test mode options, logging configurations, and the ability to run the tool with local models. Users can also contribute their own LLM models for evaluation and ranking.

LLM Consortium is a plugin for the `llm` package that implements a model consortium system with iterative refinement and response synthesis. It orchestrates multiple learned language models to collaboratively solve complex problems through structured dialogue, evaluation, and arbitration. The tool supports multi-model orchestration, iterative refinement, advanced arbitration, database logging, configurable parameters, hundreds of models, and the ability to save and load consortium configurations.

MFLUX is a line-by-line port of the FLUX implementation in the Huggingface Diffusers library to Apple MLX. It aims to run powerful FLUX models from Black Forest Labs locally on Mac machines. The codebase is minimal and explicit, prioritizing readability over generality and performance. Models are implemented from scratch in MLX, with tokenizers from the Huggingface Transformers library. Dependencies include Numpy and Pillow for image post-processing. Installation can be done using `uv tool` or classic virtual environment setup. Command-line arguments allow for image generation with specified models, prompts, and optional parameters. Quantization options for speed and memory reduction are available. LoRA adapters can be loaded for fine-tuning image generation. Controlnet support provides more control over image generation with reference images. Current limitations include generating images one by one, lack of support for negative prompts, and some LoRA adapters not working.

BlinkID iOS is a mobile SDK that enables developers to easily integrate ID scanning and data extraction capabilities into their iOS applications. The SDK supports scanning and processing various types of identity documents, such as passports, driver's licenses, and ID cards. It provides accurate and fast data extraction, including personal information and document details. With BlinkID iOS, developers can enhance their apps with secure and reliable ID verification functionality, improving user experience and streamlining identity verification processes.

An open-source mono-repository containing the MyCoder agent and CLI. It leverages Anthropic's Claude API for intelligent decision making, has a modular architecture with various tool categories, supports parallel execution with sub-agents, can modify code by writing itself, features a smart logging system for clear output, and is human-compatible using README.md, project files, and shell commands to build its own context.

STORM is a LLM system that writes Wikipedia-like articles from scratch based on Internet search. While the system cannot produce publication-ready articles that often require a significant number of edits, experienced Wikipedia editors have found it helpful in their pre-writing stage. **Try out our [live research preview](https://storm.genie.stanford.edu/) to see how STORM can help your knowledge exploration journey and please provide feedback to help us improve the system 🙏!**

XLang™ is a cutting-edge language designed for AI and IoT applications, offering exceptional dynamic and high-performance capabilities. It excels in distributed computing and seamless integration with popular languages like C++, Python, and JavaScript. Notably efficient, running 3 to 5 times faster than Python in AI and deep learning contexts. Features optimized tensor computing architecture for constructing neural networks through tensor expressions. Automates tensor data flow graph generation and compilation for specific targets, enhancing GPU performance by 6 to 10 times in CUDA environments.

Vitron is a unified pixel-level vision LLM designed for comprehensive understanding, generating, segmenting, and editing static images and dynamic videos. It addresses challenges in existing vision LLMs such as superficial instance-level understanding, lack of unified support for images and videos, and insufficient coverage across various vision tasks. The tool requires Python >= 3.8, Pytorch == 2.1.0, and CUDA Version >= 11.8 for installation. Users can deploy Gradio demo locally and fine-tune their models for specific tasks.

RoboMatrix is a skill-centric hierarchical framework for scalable robot task planning and execution in an open-world environment. It provides a structured approach to robot task execution using a combination of hardware components, environment configuration, installation procedures, and data collection methods. The framework is developed using the ROS2 framework on Ubuntu and supports robots from DJI's RoboMaster series. Users can follow the provided installation guidance to set up RoboMatrix and utilize it for various tasks such as data collection, task execution, and dataset construction. The framework also includes a supervised fine-tuning dataset and aims to optimize communication and release additional components in the future.

MorGana Form is a full-stack form builder project developed using Next.js, React, TypeScript, Ant Design, PostgreSQL, and other technologies. It allows users to quickly create and collect data through survey forms. The project structure includes components, hooks, utilities, pages, constants, Redux store, themes, types, server-side code, and component packages. Environment variables are required for database settings, NextAuth login configuration, and file upload services. Additionally, the project integrates an AI model for form generation using the Ali Qianwen model API.

PC Agent introduces a novel framework to empower autonomous digital agents through human cognition transfer. It consists of PC Tracker for data collection, Cognition Completion for transforming raw data, and a multi-agent system for decision-making and visual grounding. Users can set up the tool in Python environment, customize data collection with PC Tracker, process data into cognitive trajectories, and run the multi-agent system. The tool aims to enable AI to work autonomously while users sleep, providing a cognitive journey into the digital world.

The LLM Engineer's Handbook is an official repository containing a comprehensive guide on creating an end-to-end LLM-based system using best practices. It covers data collection & generation, LLM training pipeline, a simple RAG system, production-ready AWS deployment, comprehensive monitoring, and testing and evaluation framework. The repository includes detailed instructions on setting up local and cloud dependencies, project structure, installation steps, infrastructure setup, pipelines for data processing, training, and inference, as well as QA, tests, and running the project end-to-end.

Qiaoqiaoyun is a new generation zero-code product that combines an AI application development platform, AI knowledge base, and zero-code platform, helping enterprises quickly build personalized business applications in an AI way. Users can build personalized applications that meet business needs without any code. Qiaoqiaoyun has comprehensive application building capabilities, form engine, workflow engine, and dashboard engine, meeting enterprise's normal requirements. It is also an AI application development platform based on LLM large language model and RAG open-source knowledge base question-answering system.

AGiXT is a dynamic Artificial Intelligence Automation Platform engineered to orchestrate efficient AI instruction management and task execution across a multitude of providers. Our solution infuses adaptive memory handling with a broad spectrum of commands to enhance AI's understanding and responsiveness, leading to improved task completion. The platform's smart features, like Smart Instruct and Smart Chat, seamlessly integrate web search, planning strategies, and conversation continuity, transforming the interaction between users and AI. By leveraging a powerful plugin system that includes web browsing and command execution, AGiXT stands as a versatile bridge between AI models and users. With an expanding roster of AI providers, code evaluation capabilities, comprehensive chain management, and platform interoperability, AGiXT is consistently evolving to drive a multitude of applications, affirming its place at the forefront of AI technology.

aiexe is a cutting-edge command-line interface (CLI) and graphical user interface (GUI) tool that integrates powerful AI capabilities directly into your terminal or desktop. It is designed for developers, tech enthusiasts, and anyone interested in AI-powered automation. aiexe provides an easy-to-use yet robust platform for executing complex tasks with just a few commands. Users can harness the power of various AI models from OpenAI, Anthropic, Ollama, Gemini, and GROQ to boost productivity and enhance decision-making processes.

Claude.vim is a Vim plugin that integrates Claude, an AI pair programmer, into your Vim workflow. It allows you to chat with Claude about what to build or how to debug problems, and Claude offers opinions, proposes modifications, or even writes code. The plugin provides a chat/instruction-centric interface optimized for human collaboration, with killer features like access to chat history and vimdiff interface. It can refactor code, modify or extend selected pieces of code, execute complex tasks by reading documentation, cloning git repositories, and more. Note that it is early alpha software and expected to rapidly evolve.

Weave is a toolkit for developing Generative AI applications, built by Weights & Biases. With Weave, you can log and debug language model inputs, outputs, and traces; build rigorous, apples-to-apples evaluations for language model use cases; and organize all the information generated across the LLM workflow, from experimentation to evaluations to production. Weave aims to bring rigor, best-practices, and composability to the inherently experimental process of developing Generative AI software, without introducing cognitive overhead.

LLMStack is a no-code platform for building generative AI agents, workflows, and chatbots. It allows users to connect their own data, internal tools, and GPT-powered models without any coding experience. LLMStack can be deployed to the cloud or on-premise and can be accessed via HTTP API or triggered from Slack or Discord.

The VisionCraft API is a free API for using over 100 different AI models. From images to sound.

Kaito is an operator that automates the AI/ML inference model deployment in a Kubernetes cluster. It manages large model files using container images, avoids tuning deployment parameters to fit GPU hardware by providing preset configurations, auto-provisions GPU nodes based on model requirements, and hosts large model images in the public Microsoft Container Registry (MCR) if the license allows. Using Kaito, the workflow of onboarding large AI inference models in Kubernetes is largely simplified.

PyRIT is an open access automation framework designed to empower security professionals and ML engineers to red team foundation models and their applications. It automates AI Red Teaming tasks to allow operators to focus on more complicated and time-consuming tasks and can also identify security harms such as misuse (e.g., malware generation, jailbreaking), and privacy harms (e.g., identity theft). The goal is to allow researchers to have a baseline of how well their model and entire inference pipeline is doing against different harm categories and to be able to compare that baseline to future iterations of their model. This allows them to have empirical data on how well their model is doing today, and detect any degradation of performance based on future improvements.

Tabby is a self-hosted AI coding assistant, offering an open-source and on-premises alternative to GitHub Copilot. It boasts several key features: * Self-contained, with no need for a DBMS or cloud service. * OpenAPI interface, easy to integrate with existing infrastructure (e.g Cloud IDE). * Supports consumer-grade GPUs.

SPEAR (Simulator for Photorealistic Embodied AI Research) is a powerful tool for training embodied agents. It features 300 unique virtual indoor environments with 2,566 unique rooms and 17,234 unique objects that can be manipulated individually. Each environment is designed by a professional artist and features detailed geometry, photorealistic materials, and a unique floor plan and object layout. SPEAR is implemented as Unreal Engine assets and provides an OpenAI Gym interface for interacting with the environments via Python.

Magick is a groundbreaking visual AIDE (Artificial Intelligence Development Environment) for no-code data pipelines and multimodal agents. Magick can connect to other services and comes with nodes and templates well-suited for intelligent agents, chatbots, complex reasoning systems and realistic characters.