ort

Ort is an unofficial ONNX Runtime 1.17 wrapper for Rust based on the now inactive onnxruntime-rs. ONNX Runtime accelerates ML inference on both CPU and GPU.

CrewAI-GUI is a Node-Based Frontend tool designed to revolutionize AI workflow creation. It empowers users to design complex AI agent interactions through an intuitive drag-and-drop interface, export designs to JSON for modularity and reusability, and supports both GPT-4 API and Ollama for flexible AI backend. The tool ensures cross-platform compatibility, allowing users to create AI workflows on Windows, Linux, or macOS efficiently.

This is an open-source project for playing the game King of Glory with an artificial intelligence model. The first phase of the project has been completed, and future upgrades will be built upon this foundation. The second phase of the project has started, and progress is expected to proceed according to plan. For any questions, feel free to join the QQ exchange group: 687853827. The project aims to learn artificial intelligence and strictly prohibits cheating. Detailed installation instructions are available in the doc/README.md file. Environment installation video: (bilibili) Welcome to follow, like, tip, comment, and provide your suggestions.

Zotero MCP is an open-source project that integrates AI capabilities with Zotero using the Model Context Protocol. It consists of a Zotero plugin and an MCP server, enabling AI assistants to search, retrieve, and cite references from Zotero library. The project features a unified architecture with an integrated MCP server, eliminating the need for a separate server process. It provides features like intelligent search, detailed reference information, filtering by tags and identifiers, aiding in academic tasks such as literature reviews and citation management.

MCP for Unity is a tool that acts as a bridge, enabling AI assistants to interact with the Unity Editor via a local MCP Client. Users can instruct their LLM to manage assets, scenes, scripts, and automate tasks within Unity. The tool offers natural language control, powerful tools for asset management, scene manipulation, and automation of workflows. It is extensible and designed to work with various MCP Clients, providing a range of functions for precise text edits, script management, GameObject operations, and more.

AIPex is a revolutionary Chrome extension that transforms your browser into an intelligent automation platform. Using natural language commands and AI-powered intelligence, AIPex can automate virtually any browser task - from complex multi-step workflows to simple repetitive actions. It offers features like natural language control, AI-powered intelligence, multi-step automation, universal compatibility, smart data extraction, precision actions, form automation, visual understanding, developer-friendly with extensive API, and lightning-fast execution of automation tasks.

RKLLama is a server and client tool designed for running and interacting with LLM models optimized for Rockchip RK3588(S) and RK3576 platforms. It allows models to run on the NPU, with features such as running models on NPU, partial Ollama API compatibility, pulling models from Huggingface, API REST with documentation, dynamic loading/unloading of models, inference requests with streaming modes, simplified model naming, CPU model auto-detection, and optional debug mode. The tool supports Python 3.8 to 3.12 and has been tested on Orange Pi 5 Pro and Orange Pi 5 Plus with specific OS versions.

AskTube is an AI-powered YouTube video summarizer and QA assistant that utilizes Retrieval Augmented Generation (RAG) technology. It offers a comprehensive solution with Q&A functionality and aims to provide a user-friendly experience for local machine usage. The project integrates various technologies including Python, JS, Sanic, Peewee, Pytubefix, Sentence Transformers, Sqlite, Chroma, and NuxtJs/DaisyUI. AskTube supports multiple providers for analysis, AI services, and speech-to-text conversion. The tool is designed to extract data from YouTube URLs, store embedding chapter subtitles, and facilitate interactive Q&A sessions with enriched questions. It is not intended for production use but rather for end-users on their local machines.

ebook2audiobook is a CPU/GPU converter tool that converts eBooks to audiobooks with chapters and metadata using tools like Calibre, ffmpeg, XTTSv2, and Fairseq. It supports voice cloning and a wide range of languages. The tool is designed to run on 4GB RAM and provides a new v2.0 Web GUI interface for user-friendly interaction. Users can convert eBooks to text format, split eBooks into chapters, and utilize high-quality text-to-speech functionalities. Supported languages include Arabic, Chinese, English, French, German, Hindi, and many more. The tool can be used for legal, non-DRM eBooks only and should be used responsibly in compliance with applicable laws.

RobustMQ is a next-generation, high-performance, multi-protocol message queue built in Rust. It aims to create a unified messaging infrastructure tailored for modern cloud-native and AI systems. With features like high performance, distributed architecture, multi-protocol support, pluggable storage, cloud-native readiness, multi-tenancy, security features, observability, and user-friendliness, RobustMQ is designed to be production-ready and become a top-level Apache project in the message queue ecosystem by the second half of 2025.

FastServe-AI is a machine learning serving tool focused on GenAI & LLMs with simplicity as the top priority. It allows users to easily serve custom models by implementing the 'handle' method for 'FastServe'. The tool provides a FastAPI server for custom models and can be deployed using Lightning AI Studio. Users can install FastServe-AI via pip and run it to serve their own GPT-like LLM models in minutes.

LightEval is a lightweight LLM evaluation suite that Hugging Face has been using internally with the recently released LLM data processing library datatrove and LLM training library nanotron. We're releasing it with the community in the spirit of building in the open. Note that it is still very much early so don't expect 100% stability ^^' In case of problems or question, feel free to open an issue!

Sim is a platform that allows users to build and deploy AI agent workflows quickly and easily. It provides cloud-hosted and self-hosted options, along with support for local AI models. Users can set up the application using Docker Compose, Dev Containers, or manual setup with PostgreSQL and pgvector extension. The platform utilizes technologies like Next.js, Bun, PostgreSQL with Drizzle ORM, Better Auth for authentication, Shadcn and Tailwind CSS for UI, Zustand for state management, ReactFlow for flow editor, Fumadocs for documentation, Turborepo for monorepo management, Socket.io for real-time communication, and Trigger.dev for background jobs.

A powerful Go framework for building intelligent agent systems with large language models (LLMs), hierarchical planners, memory, telemetry, and a rich tool ecosystem. tRPC-Agent-Go enables the creation of autonomous or semi-autonomous agents that reason, call tools, collaborate with sub-agents, and maintain long-term state. The framework provides detailed documentation, examples, and tools for accelerating the development of AI applications.

LAYRA is the world's first visual-native AI automation engine that sees documents like a human, preserves layout and graphical elements, and executes arbitrarily complex workflows with full Python control. It empowers users to build next-generation intelligent systems with no limits or compromises. Built for Enterprise-Grade deployment, LAYRA features a modern frontend, high-performance backend, decoupled service architecture, visual-native multimodal document understanding, and a powerful workflow engine.

Zero is an open-source AI email solution that allows users to self-host their email app while integrating external services like Gmail. It aims to modernize and enhance emails through AI agents, offering features like open-source transparency, AI-driven enhancements, data privacy, self-hosting freedom, unified inbox, customizable UI, and developer-friendly extensibility. Built with modern technologies, Zero provides a reliable tech stack including Next.js, React, TypeScript, TailwindCSS, Node.js, Drizzle ORM, and PostgreSQL. Users can set up Zero using standard setup or Dev Container setup for VS Code users, with detailed environment setup instructions for Better Auth, Google OAuth, and optional GitHub OAuth. Database setup involves starting a local PostgreSQL instance, setting up database connection, and executing database commands for dependencies, tables, migrations, and content viewing.

The Google Cloud Vertex AI sample repository contains notebooks and community content that demonstrate how to develop and manage ML workflows using Google Cloud Vertex AI.

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.

Effort is an example implementation of the bucketMul algorithm, which allows for real-time adjustment of the number of calculations performed during inference of an LLM model. At 50% effort, it performs as fast as regular matrix multiplications on Apple Silicon chips; at 25% effort, it is twice as fast while still retaining most of the quality. Additionally, users have the option to skip loading the least important weights.

Ort is an unofficial ONNX Runtime 1.17 wrapper for Rust based on the now inactive onnxruntime-rs. ONNX Runtime accelerates ML inference on both CPU and GPU.

Model Hub V2 is a one-stop platform for model fine-tuning, deployment, and debugging without code, providing users with a visual interface to quickly validate the effects of fine-tuning various open-source models, facilitating rapid experimentation and decision-making, and lowering the threshold for users to fine-tune large models. For detailed instructions, please refer to the Feishu documentation.

This repository contains assets related to AI/ML workloads on Google Kubernetes Engine (GKE). Run optimized AI/ML workloads with Google Kubernetes Engine (GKE) platform orchestration capabilities. A robust AI/ML platform considers the following layers: Infrastructure orchestration that support GPUs and TPUs for training and serving workloads at scale Flexible integration with distributed computing and data processing frameworks Support for multiple teams on the same infrastructure to maximize utilization of resources

Ray is a unified framework for scaling AI and Python applications. It consists of a core distributed runtime and a set of AI libraries for simplifying ML compute, including Data, Train, Tune, RLlib, and Serve. Ray runs on any machine, cluster, cloud provider, and Kubernetes, and features a growing ecosystem of community integrations. With Ray, you can seamlessly scale the same code from a laptop to a cluster, making it easy to meet the compute-intensive demands of modern ML workloads.

Labelbox is a data-centric AI platform for enterprises to develop, optimize, and use AI to solve problems and power new products and services. Enterprises use Labelbox to curate data, generate high-quality human feedback data for computer vision and LLMs, evaluate model performance, and automate tasks by combining AI and human-centric workflows. The academic & research community uses Labelbox for cutting-edge AI research.

Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.

The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.

This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.

Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.

Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.

BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students

uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.

Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.