Safeguards Shield is a security and alignment toolkit designed to detect unwanted inputs and LLM outputs. It provides tools to optimize RAG pipelines for accuracy and ensure trustworthy AI needs are met. The SDK aims to make LLMs accurate and secure, unlocking value faster by unifying a set of tools.

Agent Evaluation is a generative AI-powered framework for testing virtual agents. It implements an LLM agent (evaluator) to orchestrate conversations with your own agent (target) and evaluate responses. It supports popular AWS services, allows concurrent multi-turn conversations, defines hooks for additional tasks, and can be used in CI/CD pipelines for faster delivery and stable production environments.

Laravel MCP Server SDK makes it easy to add MCP servers to your project and let AI talk to your apps. It provides tools for creating servers, tools, resources, prompts, and registering servers for web-based and local access. The package includes features for handling tool inputs, annotating tools, tool results, streaming tool responses, creating resources, creating prompts, and authentication using Laravel Passport. The MCP Inspector tool is available for testing and debugging servers.

TruLens provides a set of tools for developing and monitoring neural nets, including large language models. This includes both tools for evaluation of LLMs and LLM-based applications with _TruLens-Eval_ and deep learning explainability with _TruLens-Explain_. _TruLens-Eval_ and _TruLens-Explain_ are housed in separate packages and can be used independently.

Skyflo.ai is an AI agent designed for Cloud Native operations, providing seamless infrastructure management through natural language interactions. It serves as a safety-first co-pilot with a human-in-the-loop design. The tool offers flexible deployment options for both production and local Kubernetes environments, supporting various LLM providers and self-hosted models. Users can explore the architecture of Skyflo.ai and contribute to its development following the provided guidelines and Code of Conduct. The community engagement includes Discord, Twitter, YouTube, and GitHub Discussions.

Ocademy is an AI learning community dedicated to Python, Data Science, Machine Learning, Deep Learning, and MLOps. They promote equal opportunities for everyone to access AI through open-source educational resources. The repository contains curated AI courses, tutorials, books, tools, and resources for learning and creating Generative AI. It also offers an interactive book to help adults transition into AI. Contributors are welcome to join and contribute to the community by following guidelines. The project follows a code of conduct to ensure inclusivity and welcomes contributions from those passionate about Data Science and AI.

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.

Revornix is an information management tool designed for the AI era. It allows users to conveniently integrate all visible information and generates comprehensive reports at specific times. The tool offers cross-platform availability, all-in-one content aggregation, document transformation & vectorized storage, native multi-tenancy, localization & open-source features, smart assistant & built-in MCP, seamless LLM integration, and multilingual & responsive experience for users.

Kubeflow Trainer is a Kubernetes-native project for fine-tuning large language models (LLMs) and enabling scalable, distributed training of machine learning (ML) models across various frameworks. It allows integration with ML libraries like HuggingFace, DeepSpeed, or Megatron-LM to orchestrate ML training on Kubernetes. Develop LLMs effortlessly with the Kubeflow Python SDK and build Kubernetes-native Training Runtimes with Kubernetes Custom Resources APIs.

CosmosAIGraph is an AI-powered graph and RAG implementation of OmniRAG pattern, utilizing Azure Cosmos DB and other sources. It includes presentations, reference application documentation, FAQs, and a reference dataset of Python libraries pre-vectorized. The project focuses on Azure Cosmos DB for NoSQL and Apache Jena implementation for the in-memory RDF graph. It provides DockerHub images, with plans to add RBAC and Microsoft Entra ID/AAD authentication support, update AI model to gpt-4.5, and offer generic graph examples with a graph generation solution.

Prism is a Laravel package for integrating Large Language Models (LLMs) into applications. It simplifies text generation, multi-step conversations, and AI tools integration. Focus on developing exceptional AI applications without technical complexities.

Local Agent platform with generative AI models, RAG and tools to make AI helpful for everyone. Argo is a versatile tool that provides a user-friendly interface for leveraging AI capabilities. It offers a range of features and functionalities to assist users in various tasks related to artificial intelligence. The platform aims to democratize AI by simplifying complex processes and making them accessible to a wider audience. With Argo, users can easily deploy AI models, interact with generative AI technologies, and utilize a suite of tools designed to enhance their AI experience. Whether you are a beginner or an experienced AI practitioner, Argo provides a seamless environment for exploring and utilizing AI solutions.

Vento is an AI-driven machine automation platform that utilizes a Large Language Model (LLM) to automate the control of physical devices and machines. It features a natural language autopilot system for smart and industrial devices, providing a continuous decision loop for sensor states evaluation and actuator triggering. The platform offers a user-friendly UI for device onboarding, rule configuration, and real-time monitoring. Vento supports connected devices (IoT) based on ESP32 with ESPHome, allowing users to program, deploy, and manage IoT networks visually. Additionally, it provides AI assistance for creating rules and system management through automatic context transfer and prompt cascading.

hugegraph-ai aims to explore the integration of HugeGraph with artificial intelligence (AI) and provide comprehensive support for developers to leverage HugeGraph's AI capabilities in their projects. It includes modules for large language models, graph machine learning, and a Python client for HugeGraph. The project aims to address challenges like timeliness, hallucination, and cost-related issues by integrating graph systems with AI technologies.

Craftgen.ai is an innovative AI platform designed for both technical and non-technical users. It's built on a foundation of graph architecture for scalability and the Actor Model for efficient concurrent operations, tailored to both technical and non-technical users. A key aspect of Craftgen.ai is its modular AI approach, allowing users to assemble and customize AI components like building blocks to fit their specific needs. The platform's robustness is enhanced by its event-driven architecture, ensuring reliable data processing and featuring browser web technologies for universal access. Craftgen.ai excels in dynamic tool and workflow generation, with strong offline capabilities for secure environments and plans for desktop application integration. A unique and valuable feature of Craftgen.ai is its marketplace, where users can access a variety of pre-built AI solutions. This marketplace accelerates the deployment of AI tools but also fosters a community of sharing and innovation. Users can contribute to and leverage this repository of solutions, enhancing the platform's versatility and practicality. Craftgen.ai uses JSON schema for industry-standard alignment, enabling seamless integration with any API following the OpenAPI spec. This allows for a broad range of applications, from automating data analysis to streamlining content management. The platform is designed to bridge the gap between advanced AI technology and practical usability. It's a flexible, secure, and intuitive platform that empowers users, from developers seeking to create custom AI solutions to businesses looking to automate routine tasks. Craftgen.ai's goal is to make AI technology an integral, seamless part of everyday problem-solving and innovation, providing a platform where modular AI and a thriving marketplace converge to meet the diverse needs of its users.

AI Prompt Genius is a Chrome extension that allows you to curate a custom library of AI prompts. It is built using React web app and Tailwind CSS with DaisyUI components. The extension enables users to create and manage AI prompts for various purposes. It provides a user-friendly interface for organizing and accessing AI prompts efficiently. AI Prompt Genius is designed to enhance productivity and creativity by offering a personalized collection of prompts tailored to individual needs. Users can easily install the extension from the Chrome Web Store and start using it to generate AI prompts for different tasks.

Safeguards Shield is a security and alignment toolkit designed to detect unwanted inputs and LLM outputs. It provides tools to optimize RAG pipelines for accuracy and ensure trustworthy AI needs are met. The SDK aims to make LLMs accurate and secure, unlocking value faster by unifying a set of tools.

The GenAI repository contains pipelines that implement image and text generation tasks. The implementation uses OpenVINO capabilities to optimize the pipelines. Each sample covers a family of models and suggests certain modifications to adapt the code to specific needs. It includes the following pipelines: 1. Benchmarking script for large language models 2. Text generation C++ samples that support most popular models like LLaMA 2 3. Stable Diffuison (with LoRA) C++ image generation pipeline 4. Latent Consistency Model (with LoRA) C++ image generation pipeline

LightRAG is a PyTorch library designed for building and optimizing Retriever-Agent-Generator (RAG) pipelines. It follows principles of simplicity, quality, and optimization, offering developers maximum customizability with minimal abstraction. The library includes components for model interaction, output parsing, and structured data generation. LightRAG facilitates tasks like providing explanations and examples for concepts through a question-answering pipeline.

RAGHub is a community-driven project focused on cataloging new and emerging frameworks, projects, and resources in the Retrieval-Augmented Generation (RAG) ecosystem. It aims to help users stay ahead of changes in the field by providing a platform for the latest innovations in RAG. The repository includes information on RAG frameworks, evaluation frameworks, optimization frameworks, citation frameworks, engines, search reranker frameworks, projects, resources, and real-world use cases across industries and professions.

SkyRL is a full-stack RL library that provides components such as 'skyagent' for training long-horizon, real-world agents, 'skyrl-train' for modular RL training, and 'skyrl-gym' for a variety of tool-use tasks. It offers a library of math, coding, search, and SQL environments implemented in the Gymnasium API, optimized for multi-turn tool use LLMs on long-horizon, real-environment tasks.

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.