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.

Prompt Optimizer is a powerful AI prompt optimization tool that helps you write better AI prompts, improving AI output quality. It supports both web application and Chrome extension usage. The tool features intelligent optimization for prompt words, real-time testing to compare before and after optimization, integration with multiple mainstream AI models, client-side processing for security, encrypted local storage for data privacy, responsive design for user experience, and more.

The 'ailab' project is an experimental ground for code generation combining AI (especially coding agents) and Deno. It aims to manage configuration files defining coding rules and modes in Deno projects, enhancing the quality and efficiency of code generation by AI. The project focuses on defining clear rules and modes for AI coding agents, establishing best practices in Deno projects, providing mechanisms for type-safe code generation and validation, applying test-driven development (TDD) workflow to AI coding, and offering implementation examples utilizing design patterns like adapter pattern.

ZcChat is an AI desktop pet suitable for Galgame characters, featuring long-term memory, expressive actions, control over the computer, and voice functions. It utilizes Letta for AI long-term memory, Galgame-style character illustrations for more actions and expressions, and voice interaction with support for various voice synthesis tools like Vits. Users can configure characters, install Letta, set up voice synthesis and input, and control the pet to interact with the computer. The tool enhances visual and auditory experiences for users interested in AI desktop pets.

Nano is a Transformer-based autoregressive language model for personal enjoyment, research, modification, and alchemy. It aims to implement a specific and lightweight Transformer language model based on PyTorch, without relying on Hugging Face. Nano provides pre-training and supervised fine-tuning processes for models with 56M and 168M parameters, along with LoRA plugins. It supports inference on various computing devices and explores the potential of Transformer models in various non-NLP tasks. The repository also includes instructions for experiencing inference effects, installing dependencies, downloading and preprocessing data, pre-training, supervised fine-tuning, model conversion, and various other experiments.

FisherAI is a Chrome extension designed to improve learning efficiency. It supports automatic summarization, web and video translation, multi-turn dialogue, and various large language models such as gpt/azure/gemini/deepseek/mistral/groq/yi/moonshot. Users can enjoy flexible and powerful AI tools with FisherAI.

Nekro Agent is an AI chat plugin and proxy execution bot that is highly scalable, offers high freedom, and has minimal deployment requirements. It features context-aware chat for group/private chats, custom character settings, sandboxed execution environment, interactive image resource handling, customizable extension development interface, easy deployment with docker-compose, integration with Stable Diffusion for AI drawing capabilities, support for various file types interaction, hot configuration updates and command control, native multimodal understanding, visual application management control panel, CoT (Chain of Thought) support, self-triggered timers and holiday greetings, event notification understanding, and more. It allows for third-party extensions and AI-generated extensions, and includes features like automatic context trigger based on LLM, and a variety of basic commands for bot administrators.

GPT Academic is a powerful tool that leverages the capabilities of large language models (LLMs) to enhance academic research and writing. It provides a user-friendly interface that allows researchers, students, and professionals to interact with LLMs and utilize their abilities for various academic tasks. With GPT Academic, users can access a wide range of features and functionalities, including: * **Summarization and Paraphrasing:** GPT Academic can summarize complex texts, articles, and research papers into concise and informative summaries. It can also paraphrase text to improve clarity and readability. * **Question Answering:** Users can ask GPT Academic questions related to their research or studies, and the tool will provide comprehensive and well-informed answers based on its knowledge and understanding of the relevant literature. * **Code Generation and Explanation:** GPT Academic can generate code snippets and provide explanations for complex coding concepts. It can also help debug code and suggest improvements. * **Translation:** GPT Academic supports translation of text between multiple languages, making it a valuable tool for researchers working with international collaborations or accessing resources in different languages. * **Citation and Reference Management:** GPT Academic can help users manage their citations and references by automatically generating citations in various formats and providing suggestions for relevant references based on the user's research topic. * **Collaboration and Note-Taking:** GPT Academic allows users to collaborate on projects and take notes within the tool. They can share their work with others and access a shared workspace for real-time collaboration. * **Customizable Interface:** GPT Academic offers a customizable interface that allows users to tailor the tool to their specific needs and preferences. They can choose from a variety of themes, adjust the layout, and add or remove features to create a personalized workspace. Overall, GPT Academic is a versatile and powerful tool that can significantly enhance the productivity and efficiency of academic research and writing. It empowers users to leverage the capabilities of LLMs and unlock new possibilities for academic exploration and knowledge creation.

The 'meet-libai' project aims to promote and popularize the cultural heritage of the Chinese poet Li Bai by constructing a knowledge graph of Li Bai and training a professional AI intelligent body using large models. The project includes features such as data preprocessing, knowledge graph construction, question-answering system development, and visualization exploration of the graph structure. It also provides code implementations for large models and RAG retrieval enhancement.

ERNIE SDK repository contains two projects: ERNIE Bot Agent and ERNIE Bot. ERNIE Bot Agent is a large model intelligent agent development framework based on the Wenxin large model orchestration capability introduced by Baidu PaddlePaddle, combined with the rich preset platform functions of the PaddlePaddle Star River community. ERNIE Bot provides developers with convenient interfaces to easily call the Wenxin large model for text creation, general conversation, semantic vectors, and AI drawing basic functions.

HuaTuoAI is an artificial intelligence image classification system specifically designed for traditional Chinese medicine. It utilizes deep learning techniques, such as Convolutional Neural Networks (CNN), to accurately classify Chinese herbs and ingredients based on input images. The project aims to unlock the secrets of plants, depict the unknown realm of Chinese medicine using technology and intelligence, and perpetuate ancient cultural heritage.

Awesome-ChatTTS is an official recommended guide for ChatTTS beginners, compiling common questions and related resources. It provides a comprehensive overview of the project, including official introduction, quick experience options, popular branches, parameter explanations, voice seed details, installation guides, FAQs, and error troubleshooting. The repository also includes video tutorials, discussion community links, and project trends analysis. Users can explore various branches for different functionalities and enhancements related to ChatTTS.

Streamer-Sales is a large model for live streamers that can explain products based on their characteristics and inspire users to make purchases. It is designed to enhance sales efficiency and user experience, whether for online live sales or offline store promotions. The model can deeply understand product features and create tailored explanations in vivid and precise language, sparking user's desire to purchase. It aims to revolutionize the shopping experience by providing detailed and unique product descriptions to engage users effectively.

LotteryMaster is a tool designed to fetch lottery data, save it to Excel files, and provide analysis reports including number prediction, number recommendation, and number trends. It supports multiple platforms for access such as Web and mobile App. The tool integrates AI models like Qwen API and DeepSeek for generating analysis reports and trend analysis charts. Users can configure API parameters for controlling randomness, diversity, presence penalty, and maximum tokens. The tool also includes a frontend project based on uniapp + Vue3 + TypeScript for multi-platform applications. It provides a backend service running on Fastify with Node.js, Cheerio.js for web scraping, Pino for logging, xlsx for Excel file handling, and Jest for testing. The project is still in development and some features may not be fully implemented. The analysis reports are for reference only and do not constitute investment advice. Users are advised to use the tool responsibly and avoid addiction to gambling.

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.

Stake-auto-bot is a tool designed for automated staking in the cryptocurrency space. It allows users to set up automated processes for staking their digital assets, providing a convenient way to earn rewards and secure networks. The tool simplifies the staking process by automating the necessary steps, such as selecting validators, delegating tokens, and monitoring rewards. With Stake-auto-bot, users can optimize their staking strategies and maximize their returns with minimal effort.

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.