Higress is an open-source cloud-native API gateway built on the core of Istio and Envoy, based on Alibaba's internal practice of Envoy Gateway. It is designed for AI-native API gateway, serving AI businesses such as Tongyi Qianwen APP, Bailian Big Model API, and Machine Learning PAI platform. Higress provides capabilities to interface with LLM model vendors, AI observability, multi-model load balancing/fallback, AI token flow control, and AI caching. It offers features for AI gateway, Kubernetes Ingress gateway, microservices gateway, and security protection gateway, with advantages in production-level scalability, stream processing, extensibility, and ease of use.

AITuber-Kit is a tool that enables users to interact with AI characters, conduct AITuber live streams, and engage in external integration modes. Users can easily converse with AI characters using various LLM APIs, stream on YouTube with AI character reactions, and send messages to server apps via WebSocket. The tool provides settings for API keys, character configurations, voice synthesis engines, and more. It supports multiple languages and allows customization of VRM models and background images. AITuber-Kit follows the MIT license and offers guidelines for adding new languages to the project.

AIResume is an open-source resume creation platform that helps users easily create professional resumes, integrating AI technology to assist users in polishing their resumes. The project allows for template development using Vue 3, Vite, TypeScript, and Ant Design Vue. Users can edit resumes, export them as PDFs, switch between multiple resume templates, and collaborate on template development. AI features include resume refinement, deep optimization based on individual projects or experiences, and simulated interviews for user practice. Additional functionalities include theme color switching, high customization options, dark/light mode switching, real-time preview, drag-and-drop resume scaling, data export/import, data clearing, sample data prefilling, template market showcasing, and more.

A project that utilizes large models to help with Code Review on Gitlab, aimed at improving development efficiency. The project is customized for Gitlab and is developing a Multi-Agent plugin for collaborative review. It integrates various large models for code security issues and stays updated with the latest Code Review trends. The project architecture is designed to be powerful, flexible, and efficient, with easy integration of different models and high customization for developers.

uDesktopMascot is an open-source project for a desktop mascot application with a theme of 'freedom of creation'. It allows users to load and display VRM or GLB/FBX model files on the desktop, customize GUI colors and background images, and access various features through a menu screen. The application supports Windows 10/11 and macOS platforms.

GoMaxAI Pro is an AI-powered application for personal, team, and enterprise private operations. It supports various models like ChatGPT, Claude, Gemini, Kimi, Wenxin Yiyuan, Xunfei Xinghuo, Tsinghua Zhipu, Suno-v3.5, and Luma-video. The Pro version offers a new UI interface, member points system, management backend, homepage features, support for various content formats, AI video capabilities, SAAS multi-opening function, bug fixes, and more. It is built using web frontend with Vue3, mobile frontend with Uniapp, management frontend with Vue3, backend with Nodejs, and uses MySQL5.7(+) + Redis for data support. It can be deployed on Linux, Windows, or MacOS, with data storage options including local storage, Aliyun OSS, Tencent Cloud COS, and Chevereto image bed.

Douyin ChatGPT Bot is an AI-driven system for automatic replies on Douyin, including comment and private message replies. It offers features such as comment filtering, customizable robot responses, and automated account management. The system aims to enhance user engagement and brand image on the Douyin platform, providing a seamless experience for managing interactions with followers and potential customers.

KouriChat is a project that seamlessly integrates virtual and real interactions, providing eternal gentle bonds. It offers features like WeChat integration, immersive role-playing, intelligent conversation segmentation, emotion-based emojis, image generation, image recognition, voice messages, and more. The project is focused on technical research and learning exchanges, with a strong emphasis on ethical and legal guidelines. Users are required to take full responsibility for their actions, especially minors who should use the tool under supervision. The project architecture includes avatar configurations, data storage, handlers, AI service interfaces, a web UI, and utility libraries.

Agenta is an open-source LLM developer platform for prompt engineering, evaluation, human feedback, and deployment of complex LLM applications. It provides tools for prompt engineering and management, evaluation, human annotation, and deployment, all without imposing any restrictions on your choice of framework, library, or model. Agenta allows developers and product teams to collaborate in building production-grade LLM-powered applications in less time.

ChatGPT-PLUS is an open-source AI assistant solution based on AI large language model API, with a built-in operational management backend for easy deployment. It integrates multiple large language models from platforms like OpenAI, Azure, ChatGLM, Xunfei Xinghuo, and Wenxin Yanyan. Additionally, it includes MidJourney and Stable Diffusion AI drawing features. The system offers a complete open-source solution with ready-to-use frontend and backend applications, providing a seamless typing experience via Websocket. It comes with various pre-trained role applications such as Xiaohongshu writer, English translation master, Socrates, Confucius, Steve Jobs, and weekly report assistant to meet various chat and application needs. Users can enjoy features like Suno Wensheng music, integration with MidJourney/Stable Diffusion AI drawing, personal WeChat QR code for payment, built-in Alipay and WeChat payment functions, support for various membership packages and point card purchases, and plugin API integration for developing powerful plugins using large language model functions.

SwanLab is an open-source, lightweight AI experiment tracking tool that provides a platform for tracking, comparing, and collaborating on experiments, aiming to accelerate the research and development efficiency of AI teams by 100 times. It offers a friendly API and a beautiful interface, combining hyperparameter tracking, metric recording, online collaboration, experiment link sharing, real-time message notifications, and more. With SwanLab, researchers can document their training experiences, seamlessly communicate and collaborate with collaborators, and machine learning engineers can develop models for production faster.

KubeDoor is a microservice resource management platform developed using Python and Vue, based on K8S admission control mechanism. It supports unified remote storage, monitoring, alerting, notification, and display for multiple K8S clusters. The platform focuses on resource analysis and control during daily peak hours of microservices, ensuring consistency between resource request rate and actual usage rate.

Codemod platform is a tool that helps developers create, distribute, and run codemods in codebases of any size. The AI-powered, community-led codemods enable automation of framework upgrades, large refactoring, and boilerplate programming with speed and developer experience. It aims to make dream migrations a reality for developers by providing a platform for seamless codemod operations.

AnyLabeling is a tool for effortless data labeling with AI support from YOLO and Segment Anything. It combines features from LabelImg and Labelme with an improved UI and auto-labeling capabilities. Users can annotate images with polygons, rectangles, circles, lines, and points, as well as perform auto-labeling using YOLOv5 and Segment Anything. The tool also supports text detection, recognition, and Key Information Extraction (KIE) labeling, with multiple language options available such as English, Vietnamese, and Chinese.

The llms.txt hub is a centralized repository for llms.txt implementations and resources, facilitating interactions between LLM-powered tools and services with documentation and codebases. It standardizes documentation access, enhances AI model interpretation, improves AI response accuracy, and sets boundaries for AI content interaction across various projects and platforms.

EasyAi is a lightweight, beginner-friendly Java artificial intelligence algorithm framework. It can be seamlessly integrated into Java projects with Maven, requiring no additional environment configuration or dependencies. The framework provides pre-packaged modules for image object detection and AI customer service, as well as various low-level algorithm tools for deep learning, machine learning, reinforcement learning, heuristic learning, and matrix operations. Developers can easily develop custom micro-models tailored to their business needs.

Higress is an open-source cloud-native API gateway built on the core of Istio and Envoy, based on Alibaba's internal practice of Envoy Gateway. It is designed for AI-native API gateway, serving AI businesses such as Tongyi Qianwen APP, Bailian Big Model API, and Machine Learning PAI platform. Higress provides capabilities to interface with LLM model vendors, AI observability, multi-model load balancing/fallback, AI token flow control, and AI caching. It offers features for AI gateway, Kubernetes Ingress gateway, microservices gateway, and security protection gateway, with advantages in production-level scalability, stream processing, extensibility, and ease of use.

APIPark is an open-source AI Gateway and Developer Portal that enables users to easily manage, integrate, and deploy AI and API services. It provides robust API management features, including creation, monitoring, and access control, to help developers efficiently and securely develop and manage their APIs. The platform aims to solve challenges such as connecting to powerful AI models, managing complex AI & API call relationships, overseeing API creation and security, simplifying fault detection and troubleshooting, and enhancing the visibility and valuation of data assets.

LLMOps with Prompt flow is a template and guidance for building LLM-infused apps using Prompt flow. It provides centralized code hosting, lifecycle management, variant and hyperparameter experimentation, A/B deployment, many-to-many dataset/flow relationships, multiple deployment targets, comprehensive reporting, BYOF capabilities, configuration-based development, local prompt experimentation and evaluation, endpoint testing, and optional Human-in-loop validation. The tool is customizable to suit various application needs.

This repository provides code samples in Python, C#, REST, and JavaScript for vector support in Azure AI Search. It includes demos for various languages showcasing vectorization of data, creating indexes, and querying vector data. Additionally, it offers tools like Azure AI Search Lab for experimenting with AI-enabled search scenarios in Azure and templates for deploying custom chat-with-your-data solutions. The repository also features documentation on vector search, hybrid search, creating and querying vector indexes, and REST API references for Azure AI Search and Azure OpenAI Service.

The Intel® Geti™ SDK is a python package that enables teams to rapidly develop AI models by easing the complexities of model development and enhancing collaboration between teams. It provides tools to interact with an Intel® Geti™ server via the REST API, allowing for project creation, downloading, uploading, deploying for local inference with OpenVINO, setting project and model configuration, launching and monitoring training jobs, and media upload and prediction. The SDK also includes tutorial-style Jupyter notebooks demonstrating its usage.

Booster is a powerful inference accelerator designed for scaling large language models within production environments or for experimental purposes. It is built with performance and scaling in mind, supporting various CPUs and GPUs, including Nvidia CUDA, Apple Metal, and OpenCL cards. The tool can split large models across multiple GPUs, offering fast inference on machines with beefy GPUs. It supports both regular FP16/FP32 models and quantised versions, along with popular LLM architectures. Additionally, Booster features proprietary Janus Sampling for code generation and non-English languages.

xFasterTransformer is an optimized solution for Large Language Models (LLMs) on the X86 platform, providing high performance and scalability for inference on mainstream LLM models. It offers C++ and Python APIs for easy integration, along with example codes and benchmark scripts. Users can prepare models in a different format, convert them, and use the APIs for tasks like encoding input prompts, generating token ids, and serving inference requests. The tool supports various data types and models, and can run in single or multi-rank modes using MPI. A web demo based on Gradio is available for popular LLM models like ChatGLM and Llama2. Benchmark scripts help evaluate model inference performance quickly, and MLServer enables serving with REST and gRPC interfaces.

The Amazon Transcribe Live Call Analytics (LCA) with Agent Assist Sample Solution is designed to help contact centers assess and optimize caller experiences in real time. It leverages Amazon machine learning services like Amazon Transcribe, Amazon Comprehend, and Amazon SageMaker to transcribe and extract insights from contact center audio. The solution provides real-time supervisor and agent assist features, integrates with existing contact centers, and offers a scalable, cost-effective approach to improve customer interactions. The end-to-end architecture includes features like live call transcription, call summarization, AI-powered agent assistance, and real-time analytics. The solution is event-driven, ensuring low latency and seamless processing flow from ingested speech to live webpage updates.

This repository contains recipes for building and running containerized AI and LLM applications with Podman. It provides model servers that serve machine-learning models via an API, allowing developers to quickly prototype new AI applications locally. The recipes include components like model servers and AI applications for tasks such as chat, summarization, object detection, etc. Images for sample applications and models are available in `quay.io`, and bootable containers for AI training on Linux OS are enabled.

XLearning is a scheduling platform for big data and artificial intelligence, supporting various machine learning and deep learning frameworks. It runs on Hadoop Yarn and integrates frameworks like TensorFlow, MXNet, Caffe, Theano, PyTorch, Keras, XGBoost. XLearning offers scalability, compatibility, multiple deep learning framework support, unified data management based on HDFS, visualization display, and compatibility with code at native frameworks. It provides functions for data input/output strategies, container management, TensorBoard service, and resource usage metrics display. XLearning requires JDK >= 1.7 and Maven >= 3.3 for compilation, and deployment on CentOS 7.2 with Java >= 1.7 and Hadoop 2.6, 2.7, 2.8.