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VNTechies Blog is a platform dedicated to sharing open-source resources and providing knowledge and career guidance for the Cloud and DevOps community. The blog encourages contributions and support through donations. All content on the blog and repository is licensed under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Cloudflare Proxy EX is a tool that provides Cloudflare super proxy, OpenAI/ChatGPT proxy, Github acceleration, and online proxy services. It allows users to create a worker in Cloudflare website by copying the content from worker.js file, and add their domain name before any URL to use the tool. The tool is an improvement based on gaboolic's cloudflare-reverse-proxy, offering features like removing '/proxy/', handling redirection events, modifying headers, converting relative paths to absolute paths, and more. It aims to enhance proxy functionality and address issues faced by some websites. However, users are advised not to log in to any website through the online proxy due to potential security risks.

SuperAgentX is a lightweight open-source AI framework designed for multi-agent applications with Artificial General Intelligence (AGI) capabilities. It offers goal-oriented multi-agents with retry mechanisms, easy deployment through WebSocket, RESTful API, and IO console interfaces, streamlined architecture with no major dependencies, contextual memory using SQL + Vector databases, flexible LLM configuration supporting various Gen AI models, and extendable handlers for integration with diverse APIs and data sources. It aims to accelerate the development of AGI by providing a powerful platform for building autonomous AI agents capable of executing complex tasks with minimal human intervention.

VideoRefer Suite is a tool designed to enhance the fine-grained spatial-temporal understanding capabilities of Video Large Language Models (Video LLMs). It consists of three primary components: Model (VideoRefer) for perceiving, reasoning, and retrieval for user-defined regions at any specified timestamps, Dataset (VideoRefer-700K) for high-quality object-level video instruction data, and Benchmark (VideoRefer-Bench) to evaluate object-level video understanding capabilities. The tool can understand any object within a video.

LMDeploy is a toolkit for compressing, deploying, and serving LLM, developed by the MMRazor and MMDeploy teams. It has the following core features: * **Efficient Inference** : LMDeploy delivers up to 1.8x higher request throughput than vLLM, by introducing key features like persistent batch(a.k.a. continuous batching), blocked KV cache, dynamic split&fuse, tensor parallelism, high-performance CUDA kernels and so on. * **Effective Quantization** : LMDeploy supports weight-only and k/v quantization, and the 4-bit inference performance is 2.4x higher than FP16. The quantization quality has been confirmed via OpenCompass evaluation. * **Effortless Distribution Server** : Leveraging the request distribution service, LMDeploy facilitates an easy and efficient deployment of multi-model services across multiple machines and cards. * **Interactive Inference Mode** : By caching the k/v of attention during multi-round dialogue processes, the engine remembers dialogue history, thus avoiding repetitive processing of historical sessions.

Aim is an open-source, self-hosted ML experiment tracking tool designed to handle 10,000s of training runs. Aim provides a performant and beautiful UI for exploring and comparing training runs. Additionally, its SDK enables programmatic access to tracked metadata — perfect for automations and Jupyter Notebook analysis. **Aim's mission is to democratize AI dev tools 🎯**

Retinify is an advanced AI-powered stereo vision library designed for robotics, enabling real-time, high-precision 3D perception by leveraging GPU and NPU acceleration. It is open source under Apache-2.0 license, offers high precision 3D mapping and object recognition, runs computations on GPU for fast performance, accepts stereo images from any rectified camera setup, is cost-efficient using minimal hardware, and has minimal dependencies on CUDA Toolkit, cuDNN, and TensorRT. The tool provides a pipeline for stereo matching and supports various image data types independently of OpenCV.

Anx Reader is a meticulously designed e-book reader tailored for book enthusiasts. It boasts powerful AI functionalities and supports various e-book formats, enhancing the reading experience. With a modern interface, the tool aims to provide a seamless and enjoyable reading journey. It offers rich format support, seamless sync across devices, smart AI assistance, personalized reading experiences, professional reading analytics, a powerful note system, practical tools, and cross-platform support. The tool is continuously evolving with features like UI adaptation for tablets, page-turning animation, TTS voice reading, reading fonts, translation, and more in the pipeline.

Feast is an open source feature store for machine learning, providing a fast path to manage infrastructure for productionizing analytic data. It allows ML platform teams to make features consistently available, avoid data leakage, and decouple ML from data infrastructure. Feast abstracts feature storage from retrieval, ensuring portability across different model training and serving scenarios.

WenXin-Starter is a spring-boot-starter for Baidu's 'WenXin Workshop' large model, facilitating quick integration of Baidu's AI capabilities. It provides complete integration with WenXin Workshop's official API documentation, supports WenShengTu, built-in conversation memory, and supports conversation streaming. It also supports QPS control for individual models and queuing mechanism, with upcoming plugin support.

nonebot-plugin-marshoai is a chatbot plugin that utilizes the OpenAI standard format API, such as the GitHub Models API, to enable chat functionalities. The plugin features the character Marsho, a cute cat girl, for engaging conversations. It supports OneBot adapters and GitHub Models API, with limited validation for other adapters. Developed by Melobot.

ChatGPT Auto Refresh is a userscript that keeps ChatGPT sessions fresh by eliminating network errors and Cloudflare checks. It removes the 10-minute time limit from conversations when Chat History is disabled, ensuring a seamless experience. The tool is safe, lightweight, and a time-saver, allowing users to keep their sessions alive without constant copy/paste/refresh actions. It works even in background tabs, providing convenience and efficiency for users interacting with ChatGPT. The tool relies on the chatgpt.js library and is compatible with various browsers using Tampermonkey, making it accessible to a wide range of users.

WenXin-Starter is a spring-boot-starter for Baidu's "Wenxin Qianfan WENXINWORKSHOP" large model, which can help you quickly access Baidu's AI capabilities. It fully integrates the official API documentation of Wenxin Qianfan. Supports text-to-image generation, built-in dialogue memory, and supports streaming return of dialogue. Supports QPS control of a single model and supports queuing mechanism. Plugins will be added soon.

AirSwap Web is a peer-to-peer web frontend for AirSwap, an open developer community focused on decentralized trading systems. The repository utilizes React and NodeJS v16, with Yarn as the package manager. Designers and developers can contribute and earn through this platform, with detailed instructions available in the CONTRIBUTING file and the Discord server. The tool aims to facilitate decentralized trading and foster collaboration within the community.

The Model Context Protocol (MCP) Curriculum for Beginners is an open-source framework designed to standardize interactions between AI models and client applications. It offers a structured learning path with practical coding examples and real-world use cases in popular programming languages like C#, Java, JavaScript, Rust, Python, and TypeScript. Whether you're an AI developer, system architect, or software engineer, this guide provides comprehensive resources for mastering MCP fundamentals and implementation strategies.

VNTechies Blog is a platform dedicated to sharing open-source resources and providing knowledge and career guidance for the Cloud and DevOps community. The blog encourages contributions and support through donations. All content on the blog and repository is licensed under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

AirGo is a front and rear end separation, multi user, multi protocol proxy service management system, simple and easy to use. It supports vless, vmess, shadowsocks, and hysteria2.

Mosec is a high-performance and flexible model serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and the efficient online service API. * **Highly performant** : web layer and task coordination built with Rust 🦀, which offers blazing speed in addition to efficient CPU utilization powered by async I/O * **Ease of use** : user interface purely in Python 🐍, by which users can serve their models in an ML framework-agnostic manner using the same code as they do for offline testing * **Dynamic batching** : aggregate requests from different users for batched inference and distribute results back * **Pipelined stages** : spawn multiple processes for pipelined stages to handle CPU/GPU/IO mixed workloads * **Cloud friendly** : designed to run in the cloud, with the model warmup, graceful shutdown, and Prometheus monitoring metrics, easily managed by Kubernetes or any container orchestration systems * **Do one thing well** : focus on the online serving part, users can pay attention to the model optimization and business logic

The 'llm-code-interpreter' repository is a deprecated plugin that provides a code interpreter on steroids for ChatGPT by E2B. It gives ChatGPT access to a sandboxed cloud environment with capabilities like running any code, accessing Linux OS, installing programs, using filesystem, running processes, and accessing the internet. The plugin exposes commands to run shell commands, read files, and write files, enabling various possibilities such as running different languages, installing programs, starting servers, deploying websites, and more. It is powered by the E2B API and is designed for agents to freely experiment within a sandboxed environment.

Pezzo is a fully cloud-native and open-source LLMOps platform that allows users to observe and monitor AI operations, troubleshoot issues, save costs and latency, collaborate, manage prompts, and deliver AI changes instantly. It supports various clients for prompt management, observability, and caching. Users can run the full Pezzo stack locally using Docker Compose, with prerequisites including Node.js 18+, Docker, and a GraphQL Language Feature Support VSCode Extension. Contributions are welcome, and the source code is available under the Apache 2.0 License.

Learn Cloud Applied Generative AI Engineering (GenEng) is a course focusing on the application of generative AI technologies in various industries. The course covers topics such as the economic impact of generative AI, the role of developers in adopting and integrating generative AI technologies, and the future trends in generative AI. Students will learn about tools like OpenAI API, LangChain, and Pinecone, and how to build and deploy Large Language Models (LLMs) for different applications. The course also explores the convergence of generative AI with Web 3.0 and its potential implications for decentralized intelligence.

This repository contains shared codebase for two projects: gcloud-aio and gcloud-rest. gcloud-aio is built for Python 3's asyncio, while gcloud-rest is a threadsafe requests-based implementation. It provides clients for Google Cloud services like Auth, BigQuery, Datastore, KMS, PubSub, Storage, and Task Queue. Users can install the library using pip and refer to the documentation for usage details. Developers can contribute to the project by following the contribution guide.

Fluid is an open source Kubernetes-native Distributed Dataset Orchestrator and Accelerator for data-intensive applications, such as big data and AI applications. It implements dataset abstraction, scalable cache runtime, automated data operations, elasticity and scheduling, and is runtime platform agnostic. Key concepts include Dataset and Runtime. Prerequisites include Kubernetes version > 1.16, Golang 1.18+, and Helm 3. The tool offers features like accelerating remote file accessing, machine learning, accelerating PVC, preloading dataset, and on-the-fly dataset cache scaling. Contributions are welcomed, and the project is under the Apache 2.0 license with a vendor-neutral approach.

AIGES is a core component of the Athena Serving Framework, designed as a universal encapsulation tool for AI developers to deploy AI algorithm models and engines quickly. By integrating AIGES, you can deploy AI algorithm models and engines rapidly and host them on the Athena Serving Framework, utilizing supporting auxiliary systems for networking, distribution strategies, data processing, etc. The Athena Serving Framework aims to accelerate the cloud service of AI algorithm models and engines, providing multiple guarantees for cloud service stability through cloud-native architecture. You can efficiently and securely deploy, upgrade, scale, operate, and monitor models and engines without focusing on underlying infrastructure and service-related development, governance, and operations.