Gen-AI-Experiments is a structured collection of Jupyter notebooks and AI experiments designed to guide users through various AI tools, frameworks, and models. It offers valuable resources for both beginners and experienced practitioners, covering topics such as AI agents, model testing, RAG systems, real-world applications, and open-source tools. The repository includes folders with curated libraries, AI agents, experiments, LLM testing, open-source libraries, RAG experiments, and educhain experiments, each focusing on different aspects of AI development and application.

BMAD-METHOD™ is a universal AI agent framework that revolutionizes Agile AI-Driven Development. It offers specialized AI expertise across various domains, including software development, entertainment, creative writing, business strategy, and personal wellness. The framework introduces two key innovations: Agentic Planning, where dedicated agents collaborate to create detailed specifications, and Context-Engineered Development, which ensures complete understanding and guidance for developers. BMAD-METHOD™ simplifies the development process by eliminating planning inconsistency and context loss, providing a seamless workflow for creating AI agents and expanding functionality through expansion packs.

The AI Agent Factory is a spec-driven blueprint for building and monetizing digital FTEs. It empowers developers, entrepreneurs, and organizations to learn, build, and monetize intelligent AI agents, creating reliable digital FTEs that can be trusted, deployed, and scaled. The tool focuses on co-learning between humans and machines, emphasizing collaboration, clear specifications, and evolving together. It covers AI-assisted, AI-driven, and AI-native development approaches, guiding users through the AI development spectrum and organizational AI maturity levels. The core philosophy revolves around treating AI as a collaborative partner, using specification-first methodology, bilingual development, learning by doing, and ensuring transparency and reproducibility. The tool is suitable for beginners, professional developers, entrepreneurs, product leaders, educators, and tech leaders.

AudioMuse-AI is a deep learning-based tool for audio analysis and music generation. It provides a user-friendly interface for processing audio data and generating music compositions. The tool utilizes state-of-the-art machine learning algorithms to analyze audio signals and extract meaningful features for music generation. With AudioMuse-AI, users can explore the possibilities of AI in music creation and experiment with different styles and genres. Whether you are a music enthusiast, a researcher, or a developer, AudioMuse-AI offers a versatile platform for audio analysis and music generation.

This repository contains a curated list of awesome AI tools that can be used for various machine learning and artificial intelligence projects. It includes tools for data preprocessing, model training, evaluation, and deployment. The list is regularly updated with new tools and resources to help developers and data scientists in their AI projects.

This repository is dedicated to learning about Low-Code Full-Stack Agentic AI Development. It provides material for building modern AI-powered applications using a low-code full-stack approach. The main tools covered are UXPilot for UI/UX mockups, Lovable.dev for frontend applications, n8n for AI agents and workflows, Supabase for backend data storage, authentication, and vector search, and Model Context Protocol (MCP) for integration. The focus is on prompt and context engineering as the foundation for working with AI systems, enabling users to design, develop, and deploy AI-driven full-stack applications faster, smarter, and more reliably.

This repository contains Refact WebUI for fine-tuning and self-hosting of code models, which can be used inside Refact plugins for code completion and chat. Users can fine-tune open-source code models, self-host them, download and upload Lloras, use models for code completion and chat inside Refact plugins, shard models, host multiple small models on one GPU, and connect GPT-models for chat using OpenAI and Anthropic keys. The repository provides a Docker container for running the self-hosted server and supports various models for completion, chat, and fine-tuning. Refact is free for individuals and small teams under the BSD-3-Clause license, with custom installation options available for GPU support. The community and support include contributing guidelines, GitHub issues for bugs, a community forum, Discord for chatting, and Twitter for product news and updates.

EpicStaff is a powerful project management tool designed to streamline team collaboration and task management. It provides a user-friendly interface for creating and assigning tasks, tracking progress, and communicating with team members in real-time. With features such as task prioritization, deadline reminders, and file sharing capabilities, EpicStaff helps teams stay organized and productive. Whether you're working on a small project or managing a large team, EpicStaff is the perfect solution to keep everyone on the same page and ensure project success.

Agent-R1 is an open-source framework designed to accelerate research and development at the critical intersection of RL and Agent. It employs End-to-End reinforcement learning to train agents in specific environments. Developers define domain-specific tools and reward functions to extend Agent-R1 to unique use cases, eliminating the need for complex workflow engineering. Key features include multi-turn tool calling, multi-tool coordination, process rewards, custom tools and environments, support for multiple RL algorithms, and multi-modal support. It aims to make it easier for researchers and developers to create and explore agents in their own domains, collectively advancing the development of autonomous agents.

MemU is an open-source memory framework designed for AI companions, offering high accuracy, fast retrieval, and cost-effectiveness. It serves as an intelligent 'memory folder' that adapts to various AI companion scenarios. With MemU, users can create AI companions that remember them, learn their preferences, and evolve through interactions. The framework provides advanced retrieval strategies, 24/7 support, and is specialized for AI companions. MemU offers cloud, enterprise, and self-hosting options, with features like memory organization, interconnected knowledge graph, continuous self-improvement, and adaptive forgetting mechanism. It boasts high memory accuracy, fast retrieval, and low cost, making it suitable for building intelligent agents with persistent memory capabilities.

CushyStudio is a generative AI platform designed for creatives of any level to effortlessly create stunning images, videos, and 3D models. It offers CushyApps, a collection of visual tools tailored for different artistic tasks, and CushyKit, an extensive toolkit for custom apps development and task automation. Users can dive into the AI revolution, unleash their creativity, share projects, and connect with a vibrant community. The platform aims to simplify the AI art creation process and provide a user-friendly environment for designing interfaces, adding custom logic, and accessing various tools.

AgentForge is a low-code framework tailored for the rapid development, testing, and iteration of AI-powered autonomous agents and Cognitive Architectures. It is compatible with a range of LLM models and offers flexibility to run different models for different agents based on specific needs. The framework is designed for seamless extensibility and database-flexibility, making it an ideal playground for various AI projects. AgentForge is a beta-testing ground and future-proof hub for crafting intelligent, model-agnostic autonomous agents.

An open-source AI assistant for taking meeting notes that captures live meeting audio, transcribes it in real-time, and generates summaries while ensuring user privacy. Perfect for teams to focus on discussions while automatically capturing and organizing meeting content without external servers or complex infrastructure. Features include modern UI, real-time audio capture, speaker diarization, local processing for privacy, and more. The tool also offers a Rust-based implementation for better performance and native integration, with features like live transcription, speaker diarization, and a rich text editor for notes. Future plans include database connection for saving meeting minutes, improving summarization quality, and adding download options for meeting transcriptions and summaries. The backend supports multiple LLM providers through a unified interface, with configurations for Anthropic, Groq, and Ollama models. System architecture includes core components like audio capture service, transcription engine, LLM orchestrator, data services, and API layer. Prerequisites for setup include Node.js, Python, FFmpeg, and Rust. Development guidelines emphasize project structure, testing, documentation, type hints, and ESLint configuration. Contributions are welcome under the MIT License.

Flow-Like is an enterprise-grade workflow operating system built upon Rust for uncompromising performance, efficiency, and code safety. It offers a modular frontend for apps, a rich set of events, a node catalog, a powerful no-code workflow IDE, and tools to manage teams, templates, and projects within organizations. With typed workflows, users can create complex, large-scale workflows with clear data origins, transformations, and contracts. Flow-Like is designed to automate any process through seamless integration of LLM, ML-based, and deterministic decision-making instances.

LearnHouse is an open-source platform that allows anyone to easily provide world-class educational content. It supports various content types, including dynamic pages, videos, and documents. The platform is still in early development and should not be used in production environments. However, it offers several features, such as dynamic Notion-like pages, ease of use, multi-organization support, support for uploading videos and documents, course collections, user management, quizzes, course progress tracking, and an AI-powered assistant for teachers and students. LearnHouse is built using various open-source projects, including Next.js, TailwindCSS, Radix UI, Tiptap, FastAPI, YJS, PostgreSQL, LangChain, and React.

Cherry Studio is a desktop client that supports multiple LLM providers on Windows, Mac, and Linux. It offers diverse LLM provider support, AI assistants & conversations, document & data processing, practical tools integration, and enhanced user experience. The tool includes features like support for major LLM cloud services, AI web service integration, local model support, pre-configured AI assistants, document processing for text, images, and more, global search functionality, topic management system, AI-powered translation, and cross-platform support with ready-to-use features and themes for a better user experience.

Gen-AI-Experiments is a structured collection of Jupyter notebooks and AI experiments designed to guide users through various AI tools, frameworks, and models. It offers valuable resources for both beginners and experienced practitioners, covering topics such as AI agents, model testing, RAG systems, real-world applications, and open-source tools. The repository includes folders with curated libraries, AI agents, experiments, LLM testing, open-source libraries, RAG experiments, and educhain experiments, each focusing on different aspects of AI development and application.

ISEK is a decentralized agent network framework that enables building intelligent, collaborative agent-to-agent systems. It integrates the Google A2A protocol and ERC-8004 contracts for identity registration, reputation building, and cooperative task-solving, creating a self-organizing, decentralized society of agents. The platform addresses challenges in the agent ecosystem by providing an incentive system for users to pay for agent services, motivating developers to build high-quality agents and fostering innovation and quality in the ecosystem. ISEK focuses on decentralized agent collaboration and coordination, allowing agents to find each other, reason together, and act as a decentralized system without central control. The platform utilizes ERC-8004 for decentralized identity, reputation, and validation registries, establishing trustless verification and reputation management.

The AI Agent Factory is a spec-driven blueprint for building and monetizing digital FTEs. It empowers developers, entrepreneurs, and organizations to learn, build, and monetize intelligent AI agents, creating reliable digital FTEs that can be trusted, deployed, and scaled. The tool focuses on co-learning between humans and machines, emphasizing collaboration, clear specifications, and evolving together. It covers AI-assisted, AI-driven, and AI-native development approaches, guiding users through the AI development spectrum and organizational AI maturity levels. The core philosophy revolves around treating AI as a collaborative partner, using specification-first methodology, bilingual development, learning by doing, and ensuring transparency and reproducibility. The tool is suitable for beginners, professional developers, entrepreneurs, product leaders, educators, and tech leaders.

LiveBench is a benchmark tool designed for Language Model Models (LLMs) with a focus on limiting contamination through monthly new questions based on recent datasets, arXiv papers, news articles, and IMDb movie synopses. It provides verifiable, objective ground-truth answers for accurate scoring without an LLM judge. The tool offers 18 diverse tasks across 6 categories and promises to release more challenging tasks over time. LiveBench is built on FastChat's llm_judge module and incorporates code from LiveCodeBench and IFEval.

The Microsoft AI Chat Protocol SDK is a library for easily building AI Chat interfaces from services that follow the AI Chat Protocol API Specification. By agreeing on a standard API contract, AI backend consumption and evaluation can be performed easily and consistently across different services. It allows developers to develop AI chat interfaces, consume and evaluate AI inference backends, and incorporate HTTP middleware for logging and authentication.

VerifyWise is an open-source AI governance platform designed to help businesses harness the power of AI safely and responsibly. The platform ensures compliance and robust AI management without compromising on security. It offers additional products like MaskWise for data redaction, EvalWise for AI model evaluation, and FlagWise for security threat monitoring. VerifyWise simplifies AI governance for organizations, aiding in risk management, regulatory compliance, and promoting responsible AI practices. It features options for on-premises or private cloud hosting, open-source with AGPLv3 license, AI-generated answers for compliance audits, source code transparency, Docker deployment, user registration, role-based access control, and various AI governance tools like risk management, bias & fairness checks, evidence center, AI trust center, and more.

**Prompt flow** is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality.

DeepEval is a simple-to-use, open-source LLM evaluation framework specialized for unit testing LLM outputs. It incorporates various metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., and runs locally on your machine for evaluation. It provides a wide range of ready-to-use evaluation metrics, allows for creating custom metrics, integrates with any CI/CD environment, and enables benchmarking LLMs on popular benchmarks. DeepEval is designed for evaluating RAG and fine-tuning applications, helping users optimize hyperparameters, prevent prompt drifting, and transition from OpenAI to hosting their own Llama2 with confidence.

MegaDetector is an AI model that identifies animals, people, and vehicles in camera trap images (which also makes it useful for eliminating blank images). This model is trained on several million images from a variety of ecosystems. MegaDetector is just one of many tools that aims to make conservation biologists more efficient with AI. If you want to learn about other ways to use AI to accelerate camera trap workflows, check out our of the field, affectionately titled "Everything I know about machine learning and camera traps".

LeapfrogAI is a self-hosted AI platform designed to be deployed in air-gapped resource-constrained environments. It brings sophisticated AI solutions to these environments by hosting all the necessary components of an AI stack, including vector databases, model backends, API, and UI. LeapfrogAI's API closely matches that of OpenAI, allowing tools built for OpenAI/ChatGPT to function seamlessly with a LeapfrogAI backend. It provides several backends for various use cases, including llama-cpp-python, whisper, text-embeddings, and vllm. LeapfrogAI leverages Chainguard's apko to harden base python images, ensuring the latest supported Python versions are used by the other components of the stack. The LeapfrogAI SDK provides a standard set of protobuffs and python utilities for implementing backends and gRPC. LeapfrogAI offers UI options for common use-cases like chat, summarization, and transcription. It can be deployed and run locally via UDS and Kubernetes, built out using Zarf packages. LeapfrogAI is supported by a community of users and contributors, including Defense Unicorns, Beast Code, Chainguard, Exovera, Hypergiant, Pulze, SOSi, United States Navy, United States Air Force, and United States Space Force.

This Docker image for LLaVA (Large Language and Vision Assistant) provides a convenient way to run LLaVA locally or on RunPod. LLaVA is a powerful AI tool that combines natural language processing and computer vision capabilities. With this Docker image, you can easily access LLaVA's functionalities for various tasks, including image captioning, visual question answering, text summarization, and more. The image comes pre-installed with LLaVA v1.2.0, Torch 2.1.2, xformers 0.0.23.post1, and other necessary dependencies. You can customize the model used by setting the MODEL environment variable. The image also includes a Jupyter Lab environment for interactive development and exploration. Overall, this Docker image offers a comprehensive and user-friendly platform for leveraging LLaVA's capabilities.

The 'carrot' repository on GitHub provides a list of free and user-friendly ChatGPT mirror sites for easy access. The repository includes sponsored sites offering various GPT models and services. Users can find and share sites, report errors, and access stable and recommended sites for ChatGPT usage. The repository also includes a detailed list of ChatGPT sites, their features, and accessibility options, making it a valuable resource for ChatGPT users seeking free and unlimited GPT services.

TrustLLM is a comprehensive study of trustworthiness in LLMs, including principles for different dimensions of trustworthiness, established benchmark, evaluation, and analysis of trustworthiness for mainstream LLMs, and discussion of open challenges and future directions. Specifically, we first propose a set of principles for trustworthy LLMs that span eight different dimensions. Based on these principles, we further establish a benchmark across six dimensions including truthfulness, safety, fairness, robustness, privacy, and machine ethics. We then present a study evaluating 16 mainstream LLMs in TrustLLM, consisting of over 30 datasets. The document explains how to use the trustllm python package to help you assess the performance of your LLM in trustworthiness more quickly. For more details about TrustLLM, please refer to project website.

AI-YinMei is an AI virtual anchor Vtuber development tool (N card version). It supports fastgpt knowledge base chat dialogue, a complete set of solutions for LLM large language models: [fastgpt] + [one-api] + [Xinference], supports docking bilibili live broadcast barrage reply and entering live broadcast welcome speech, supports Microsoft edge-tts speech synthesis, supports Bert-VITS2 speech synthesis, supports GPT-SoVITS speech synthesis, supports expression control Vtuber Studio, supports painting stable-diffusion-webui output OBS live broadcast room, supports painting picture pornography public-NSFW-y-distinguish, supports search and image search service duckduckgo (requires magic Internet access), supports image search service Baidu image search (no magic Internet access), supports AI reply chat box [html plug-in], supports AI singing Auto-Convert-Music, supports playlist [html plug-in], supports dancing function, supports expression video playback, supports head touching action, supports gift smashing action, supports singing automatic start dancing function, chat and singing automatic cycle swing action, supports multi scene switching, background music switching, day and night automatic switching scene, supports open singing and painting, let AI automatically judge the content.