Adversarial Robustness Toolbox (ART) is a Python library for Machine Learning Security. ART provides tools that enable developers and researchers to defend and evaluate Machine Learning models and applications against the adversarial threats of Evasion, Poisoning, Extraction, and Inference. ART supports all popular machine learning frameworks (TensorFlow, Keras, PyTorch, MXNet, scikit-learn, XGBoost, LightGBM, CatBoost, GPy, etc.), all data types (images, tables, audio, video, etc.) and machine learning tasks (classification, object detection, speech recognition, generation, certification, etc.).

SGLang is a structured generation language designed for large language models (LLMs). It makes your interaction with LLMs faster and more controllable by co-designing the frontend language and the runtime system. The core features of SGLang include: - **A Flexible Front-End Language**: This allows for easy programming of LLM applications with multiple chained generation calls, advanced prompting techniques, control flow, multiple modalities, parallelism, and external interaction. - **A High-Performance Runtime with RadixAttention**: This feature significantly accelerates the execution of complex LLM programs by automatic KV cache reuse across multiple calls. It also supports other common techniques like continuous batching and tensor parallelism.

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.

TiDB is an open-source distributed SQL database that supports Hybrid Transactional and Analytical Processing (HTAP) workloads. It is MySQL compatible and features horizontal scalability, strong consistency, and high availability.

Moon is a monitoring and alerting platform suitable for multiple domains, supporting various application scenarios such as cloud-native, Internet of Things (IoT), and Artificial Intelligence (AI). It simplifies operational work of cloud-native monitoring, boasts strong IoT and AI support capabilities, and meets diverse monitoring needs across industries. Capable of real-time data monitoring, intelligent alerts, and fault response for various fields.

OVOS - Buildroot OS is a minimalistic Linux OS designed to bring the open source voice assistant ovos-core to embedded, low-spec headless, and small touchscreen devices. It includes a full 64-bit distribution with Linux kernel 6.1.x, Buildroot 2023.02.x, and OVOS framework utilizing ovos-docker containers. The supported hardware includes Raspberry Pi 3, 3b, 3b+, Raspberry Pi 4, x86_64 Intel-based computers, and Open Virtual Appliance. The project is inspired by Mycroft AI, Buildroot, and HassOS, offering a platform for building voice assistant solutions on various devices.

Postiz is an ultimate AI social media scheduling tool that offers everything you need to manage your social media posts, build an audience, capture leads, and grow your business. It allows you to schedule posts with AI features, measure work with analytics, collaborate with team members, and invite others to comment and schedule posts. The tech stack includes NX (Monorepo), NextJS (React), NestJS, Prisma, Redis, and Resend for email notifications.

Langfuse Python SDK is a software development kit that provides tools and functionalities for integrating with Langfuse's language processing services. It offers decorators for observing code behavior, low-level SDK for tracing, and wrappers for accessing Langfuse's public API. The SDK was recently rewritten in version 2, released on December 17, 2023, with detailed documentation available on the official website. It also supports integrations with OpenAI SDK, LlamaIndex, and LangChain for enhanced language processing capabilities.

Canvas is a DALL·E Playground for the Mac, allowing users to generate images with DALL·E 3 & DALL·E 2, edit images, create variations, copy, save, and share generated images. It is a simple, easy-to-use, free, and open-source native application for macOS 14.0 Sonoma or later. Users can download Canvas from the releases page on GitHub and require an OpenAI API key for access to the features.

Awesome-LLM is a curated list of resources related to large language models, focusing on papers, projects, frameworks, tools, tutorials, courses, opinions, and other useful resources in the field. It covers trending LLM projects, milestone papers, other papers, open LLM projects, LLM training frameworks, LLM evaluation frameworks, tools for deploying LLM, prompting libraries & tools, tutorials, courses, books, and opinions. The repository provides a comprehensive overview of the latest advancements and resources in the field of large language models.

LLM-Powered-RAG-System is a comprehensive repository containing frameworks, projects, components, evaluation tools, papers, blogs, and other resources related to Retrieval-Augmented Generation (RAG) systems powered by Large Language Models (LLMs). The repository includes various frameworks for building applications with LLMs, data frameworks, modular graph-based RAG systems, dense retrieval models, and efficient retrieval augmentation and generation frameworks. It also features projects such as personal productivity assistants, knowledge-based platforms, chatbots, question and answer systems, and code assistants. Additionally, the repository provides components for interacting with documents, databases, and optimization methods using ML and LLM technologies. Evaluation frameworks, papers, blogs, and other resources related to RAG systems are also included.

MaxKB is a knowledge base Q&A system based on the LLM large language model. MaxKB = Max Knowledge Base, which aims to become the most powerful brain of the enterprise.

MATLAB-Simulink-Challenge-Project-Hub is a repository aimed at contributing to the progress of engineering and science by providing challenge projects with real industry relevance and societal impact. The repository offers a wide range of projects covering various technology trends such as Artificial Intelligence, Autonomous Vehicles, Big Data, Computer Vision, and Sustainability. Participants can gain practical skills with MATLAB and Simulink while making a significant contribution to science and engineering. The projects are designed to enhance expertise in areas like Sustainability and Renewable Energy, Control, Modeling and Simulation, Machine Learning, and Robotics. By participating in these projects, individuals can receive official recognition for their problem-solving skills from technology leaders at MathWorks and earn rewards upon project completion.

Awesome-AI-Agents is a curated list of projects, frameworks, benchmarks, platforms, and related resources focused on autonomous AI agents powered by Large Language Models (LLMs). The repository showcases a wide range of applications, multi-agent task solver projects, agent society simulations, and advanced components for building and customizing AI agents. It also includes frameworks for orchestrating role-playing, evaluating LLM-as-Agent performance, and connecting LLMs with real-world applications through platforms and APIs. Additionally, the repository features surveys, paper lists, and blogs related to LLM-based autonomous agents, making it a valuable resource for researchers, developers, and enthusiasts in the field of AI.

Axolotl is a lightweight and efficient tool for managing and analyzing large datasets. It provides a user-friendly interface for data manipulation, visualization, and statistical analysis. With Axolotl, users can easily import, clean, and explore data to gain valuable insights and make informed decisions. The tool supports various data formats and offers a wide range of functions for data processing and modeling. Whether you are a data scientist, researcher, or business analyst, Axolotl can help streamline your data workflows and enhance your data analysis capabilities.

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.

Adversarial Robustness Toolbox (ART) is a Python library for Machine Learning Security. ART provides tools that enable developers and researchers to defend and evaluate Machine Learning models and applications against the adversarial threats of Evasion, Poisoning, Extraction, and Inference. ART supports all popular machine learning frameworks (TensorFlow, Keras, PyTorch, MXNet, scikit-learn, XGBoost, LightGBM, CatBoost, GPy, etc.), all data types (images, tables, audio, video, etc.) and machine learning tasks (classification, object detection, speech recognition, generation, certification, etc.).

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.