The oba live tool is a small tool for Douyin small shops and Kuaishou Baiying live broadcasts. It features multiple account management, intelligent message assistant, automatic product explanation, AI automatic reply, and AI intelligent assistant. The tool requires Windows 10 or above, Chrome or Edge browser, and a valid account for Douyin small shops or Kuaishou Baiying. Users can download the tool from the Releases page, connect to the control panel, set API keys for AI functions, and configure auto-reply prompts. The tool is licensed under the MIT license.

anki_packager is an intelligent tool for generating high-quality Anki flashcards for English vocabulary. It integrates multiple curated dictionaries, provides automated learning experiences, supports various features like Google TTS pronunciation and AI models for word summarization and story generation, offers convenient data import from other sources, ensures a good command-line interface, and can be run using Docker. Each flashcard includes detailed learning resources such as definitions, tenses, AI-generated roots for mnemonic aids, phrases, example sentences, word differentiations, and English explanations with AI-generated stories.

Paper-ai is a tool that helps you write papers using artificial intelligence. It provides features such as AI writing assistance, reference searching, and editing and formatting tools. With Paper-ai, you can quickly and easily create high-quality papers.

prose-polish is a tool for AI interaction through drag-and-drop cards, focusing on editing copy and manuscripts. It can recognize Markdown-formatted documents, automatically breaking them into paragraph cards. Users can create prefabricated prompt cards and quickly connect them to the manuscript for editing. The modified manuscript is still presented in card form, allowing users to drag it out as a new paragraph. To use it smoothly, users just need to remember one rule: 'Plug the plug into the socket!'

AI-Codereview-Gitlab is an automated code review tool based on large models, designed to help development teams conduct intelligent code reviews quickly during code merging or submission. It supports multiple large models including DeepSeek, ZhipuAI, OpenAI, and Ollama. The tool can automatically push review results to DingTalk, WeChat Work, and Feishu, generate daily reports based on GitLab commit records, and provide a visual dashboard to display code review records. The tool works by triggering webhook events on GitLab when users submit code, calling third-party large models to review the code, and recording the review results in corresponding Merge Requests or Commit Notes.

ONE is a modern web and AI agent development toolkit that empowers developers to build AI-powered applications with high performance, beautiful UI, AI integration, responsive design, type safety, and great developer experience. It is perfect for building modern web applications, from simple landing pages to complex AI-powered platforms.

Retro AIM Server is an instant messaging server that revives AOL Instant Messenger clients from the 2000s. It supports Windows AIM client versions 5.0-5.9, away messages, buddy icons, buddy list, chat rooms, instant messaging, user profiles, blocking/visibility toggle/idle notification, and warning. The Management API provides functionality for administering the server, including listing users, creating users, changing passwords, and listing active sessions.

ChatMemOllama is a personal WeChat public account chatbot that combines a local AI model (provided by Ollama) and mem0 memory management functionality. The project aims to provide an intelligent, personalized chat experience. It features a local AI model for conversation, memory management through mem0 for a coherent dialogue experience, support for multiple users simultaneously (with logic issues in the test version), and quick responses within 5 seconds to users with timeout prompts. It allows or prohibits other users from calling AI, with ongoing development tasks including debugging multiple user handling logic and keyword replies, and completed tasks such as basic conversation and tool calling. The ultimate goal is to wait for pre-task testing completion.

This project is a personal implementation and reproduction of a small-parameter Chinese LLM. It mainly refers to these two open source projects: https://github.com/charent/Phi2-mini-Chinese and https://github.com/DLLXW/baby-llama2-chinese. It includes the complete process of pre-training, SFT instruction fine-tuning, DPO, and PPO (to be done). I hope to share it with everyone and hope that everyone can work together to improve it!

HiveChat is an AI chat application designed for small and medium teams. It supports various models such as DeepSeek, Open AI, Claude, and Gemini. The tool allows easy configuration by one administrator for the entire team to use different AI models. It supports features like email or Feishu login, LaTeX and Markdown rendering, DeepSeek mind map display, image understanding, AI agents, cloud data storage, and integration with multiple large model service providers. Users can engage in conversations by logging in, while administrators can configure AI service providers, manage users, and control account registration. The technology stack includes Next.js, Tailwindcss, Auth.js, PostgreSQL, Drizzle ORM, and Ant Design.

YesImBot, also known as Athena, is a Koishi plugin designed to allow large AI models to participate in group chat discussions. It offers easy customization of the bot's name, personality, emotions, and other messages. The plugin supports load balancing multiple API interfaces for large models, provides immersive context awareness, blocks potentially harmful messages, and automatically fetches high-quality prompts. Users can adjust various settings for the bot and customize system prompt words. The ultimate goal is to seamlessly integrate the bot into group chats without detection, with ongoing improvements and features like message recognition, emoji sending, multimodal image support, and more.

GitHub Sentinel is an intelligent information retrieval and high-value content mining AI Agent designed for the era of large models (LLMs). It is aimed at users who need frequent and large-scale information retrieval, especially open source enthusiasts, individual developers, and investors. The main features include subscription management, update retrieval, notification system, report generation, multi-model support, scheduled tasks, graphical interface, containerization, continuous integration, and the ability to track and analyze the latest dynamics of GitHub open source projects and expand to other information channels like Hacker News for comprehensive information mining and analysis capabilities.

ShitCodify is an AI-powered tool that transforms normal, readable, and maintainable code into hard-to-understand, hard-to-maintain 'shit code'. It uses large language models like GPT-4 to analyze code and apply various 'anti-patterns' and bad practices to reduce code readability and maintainability while keeping the code functional.

QuantaLogic is a ReAct framework for building advanced AI agents that seamlessly integrates large language models with a robust tool system. It aims to bridge the gap between advanced AI models and practical implementation in business processes by enabling agents to understand, reason about, and execute complex tasks through natural language interaction. The framework includes features such as ReAct Framework, Universal LLM Support, Secure Tool System, Real-time Monitoring, Memory Management, and Enterprise Ready components.

HuggingLLM is a project that aims to introduce ChatGPT to a wider audience, particularly those interested in using the technology to create new products or applications. The project focuses on providing practical guidance on how to use ChatGPT-related APIs to create new features and applications. It also includes detailed background information and system design introductions for relevant tasks, as well as example code and implementation processes. The project is designed for individuals with some programming experience who are interested in using ChatGPT for practical applications, and it encourages users to experiment and create their own applications and demos.

Magic Resume is a modern online resume editor that makes creating professional resumes simple and fun. Built on Next.js and Framer Motion, it supports real-time preview and custom themes. Features include Next.js 14+ based construction, smooth animation effects (Framer Motion), custom theme support, responsive design, dark mode, export to PDF, real-time preview, auto-save, and local storage. The technology stack includes Next.js 14+, TypeScript, Framer Motion, Tailwind CSS, Shadcn/ui, and Lucide Icons.

The oba live tool is a small tool for Douyin small shops and Kuaishou Baiying live broadcasts. It features multiple account management, intelligent message assistant, automatic product explanation, AI automatic reply, and AI intelligent assistant. The tool requires Windows 10 or above, Chrome or Edge browser, and a valid account for Douyin small shops or Kuaishou Baiying. Users can download the tool from the Releases page, connect to the control panel, set API keys for AI functions, and configure auto-reply prompts. The tool is licensed under the MIT license.

The Sandbox AutoClicker is a bot designed for the crypto game The Sandbox, allowing users to automate various processes within the game. The tool offers features such as auto tuning, multi-account auto clicker, multi-threading, a convenient menu, and free proxies. It provides full optimization through a simple menu and is guaranteed to be safe for Windows systems, supporting versions 7/8/8.1/10/11 (x32/64).

Kirara AI is a chatbot that supports mainstream large language models and chat platforms. It provides features such as image sending, keyword-triggered replies, multi-account support, personality settings, and support for various chat platforms like QQ, Telegram, Discord, and WeChat. The tool also supports HTTP server for Web API, popular large models like OpenAI and DeepSeek, plugin mechanism, conditional triggers, admin commands, drawing models, voice replies, multi-turn conversations, cross-platform message sending, custom workflows, web management interface, and built-in Frpc intranet penetration.

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.