Diffusion Toolkit is an image metadata-indexer and viewer for AI-generated images. It helps you organize, search, and sort your ever-growing collection. Key features include: - Scanning images and storing prompts and other metadata (PNGInfo) - Searching for images using simple queries or filters - Viewing images and metadata easily - Tagging images with favorites, ratings, and NSFW flags - Sorting images by date created, aesthetic score, or rating - Auto-tagging NSFW images by keywords - Blurring images tagged as NSFW - Creating and managing albums - Viewing and searching prompts - Drag-and-drop functionality Diffusion Toolkit supports various image formats, including JPG/JPEG, PNG, WebP, and TXT metadata. It also supports metadata formats from popular AI image generators like AUTOMATIC1111, InvokeAI, NovelAI, Stable Diffusion, and more. You can use Diffusion Toolkit even on images without metadata and still enjoy features like rating and album management.

Thinc is a lightweight deep learning library that offers an elegant, type-checked, functional-programming API for composing models, with support for layers defined in other frameworks such as PyTorch, TensorFlow and MXNet. You can use Thinc as an interface layer, a standalone toolkit or a flexible way to develop new models.

A simple standalone viewer for reading prompt from Stable Diffusion generated image outside the webui. The tool supports macOS, Windows, and Linux, providing both GUI and CLI functionalities. Users can interact with the tool through drag and drop, copy prompt to clipboard, remove prompt from image, export prompt to text file, edit or import prompt to images, and more. It supports multiple formats including PNG, JPEG, WEBP, TXT, and various tools like A1111's webUI, Easy Diffusion, StableSwarmUI, Fooocus-MRE, NovelAI, InvokeAI, ComfyUI, Draw Things, and Naifu(4chan). Users can download the tool for different platforms and install it via Homebrew Cask or pip. The tool can be used to read, export, remove, and edit prompts from images, providing various modes and options for different tasks.

llm2sh is a command-line utility that leverages Large Language Models (LLMs) to translate plain-language requests into shell commands. It provides a convenient way to interact with your system using natural language. The tool supports multiple LLMs for command generation, offers a customizable configuration file, YOLO mode for running commands without confirmation, and is easily extensible with new LLMs and system prompts. Users can set up API keys for OpenAI, Claude, Groq, and Cerebras to use the tool effectively. llm2sh does not store user data or command history, and it does not record or send telemetry by itself, but the LLM APIs may collect and store requests and responses for their purposes.

HolmesGPT is an open-source DevOps assistant powered by OpenAI or any tool-calling LLM of your choice. It helps in troubleshooting Kubernetes, incident response, ticket management, automated investigation, and runbook automation in plain English. The tool connects to existing observability data, is compliance-friendly, provides transparent results, supports extensible data sources, runbook automation, and integrates with existing workflows. Users can install HolmesGPT using Brew, prebuilt Docker container, Python Poetry, or Docker. The tool requires an API key for functioning and supports OpenAI, Azure AI, and self-hosted LLMs.

The RAG ChatBot project combines Lama.cpp, Chroma, and Streamlit to build a Conversation-aware Chatbot and a Retrieval-augmented generation (RAG) ChatBot. The RAG Chatbot works by taking a collection of Markdown files as input and provides answers based on the context provided by those files. It utilizes a Memory Builder component to load Markdown pages, divide them into sections, calculate embeddings, and save them in an embedding database. The chatbot retrieves relevant sections from the database, rewrites questions for optimal retrieval, and generates answers using a local language model. It also remembers previous interactions for more accurate responses. Various strategies are implemented to deal with context overflows, including creating and refining context, hierarchical summarization, and async hierarchical summarization.

AirConnect-Synology is a minimal Synology package that allows users to use AirPlay to stream to UPnP/Sonos & Chromecast devices that do not natively support AirPlay. It is compatible with DSM 7.0 and DSM 7.1, and provides detailed information on installation, configuration, supported devices, troubleshooting, and more. The package automates the installation and usage of AirConnect on Synology devices, ensuring compatibility with various architectures and firmware versions. Users can customize the configuration using the airconnect.conf file and adjust settings for specific speakers like Sonos, Bose SoundTouch, and Pioneer/Phorus/Play-Fi.

Page Assist is an open-source Chrome Extension that provides a Sidebar and Web UI for your Local AI model. It allows you to interact with your model from any webpage.

DaoCloud Enterprise 5.0 Documentation provides detailed information on using DaoCloud, a Certified Kubernetes Service Provider. The documentation covers current and legacy versions, workflow control using GitOps, and instructions for opening a PR and previewing changes locally. It also includes naming conventions, writing tips, references, and acknowledgments to contributors. Users can find guidelines on writing, contributing, and translating pages, along with using tools like MkDocs, Docker, and Poetry for managing the documentation.

llama-zip is a command-line utility for lossless text compression and decompression. It leverages a user-provided large language model (LLM) as the probabilistic model for an arithmetic coder, achieving high compression ratios for structured or natural language text. The tool is not limited by the LLM's maximum context length and can handle arbitrarily long input text. However, the speed of compression and decompression is limited by the LLM's inference speed.

OmAgent is an open-source agent framework designed to streamline the development of on-device multimodal agents. It enables agents to empower various hardware devices, integrates speed-optimized SOTA multimodal models, provides SOTA multimodal agent algorithms, and focuses on optimizing the end-to-end computing pipeline for real-time user interaction experience. Key features include easy connection to diverse devices, scalability, flexibility, and workflow orchestration. The architecture emphasizes graph-based workflow orchestration, native multimodality, and device-centricity, allowing developers to create bespoke intelligent agent programs.

Cambrian-1 is a fully open project focused on exploring multimodal Large Language Models (LLMs) with a vision-centric approach. It offers competitive performance across various benchmarks with models at different parameter levels. The project includes training configurations, model weights, instruction tuning data, and evaluation details. Users can interact with Cambrian-1 through a Gradio web interface for inference. The project is inspired by LLaVA and incorporates contributions from Vicuna, LLaMA, and Yi. Cambrian-1 is licensed under Apache 2.0 and utilizes datasets and checkpoints subject to their respective original licenses.

TTS Generation WebUI is a comprehensive tool that provides a user-friendly interface for text-to-speech and voice cloning tasks. It integrates various AI models such as Bark, MusicGen, AudioGen, Tortoise, RVC, Vocos, Demucs, SeamlessM4T, and MAGNeT. The tool offers one-click installers, Google Colab demo, videos for guidance, and extra voices for Bark. Users can generate audio outputs, manage models, caches, and system space for AI projects. The project is open-source and emphasizes ethical and responsible use of AI technology.

SuperDuperDB is a Python framework for integrating AI models, APIs, and vector search engines directly with your existing databases, including hosting of your own models, streaming inference and scalable model training/fine-tuning. Build, deploy and manage any AI application without the need for complex pipelines, infrastructure as well as specialized vector databases, and moving our data there, by integrating AI at your data's source: - Generative AI, LLMs, RAG, vector search - Standard machine learning use-cases (classification, segmentation, regression, forecasting recommendation etc.) - Custom AI use-cases involving specialized models - Even the most complex applications/workflows in which different models work together SuperDuperDB is **not** a database. Think `db = superduper(db)`: SuperDuperDB transforms your databases into an intelligent platform that allows you to leverage the full AI and Python ecosystem. A single development and deployment environment for all your AI applications in one place, fully scalable and easy to manage.

The llama-recipes repository provides a scalable library for fine-tuning Llama 2, along with example scripts and notebooks to quickly get started with using the Llama 2 models in a variety of use-cases, including fine-tuning for domain adaptation and building LLM-based applications with Llama 2 and other tools in the LLM ecosystem. The examples here showcase how to run Llama 2 locally, in the cloud, and on-prem.

Torchtune is a PyTorch-native library for easily authoring, fine-tuning, and experimenting with LLMs. It provides native-PyTorch implementations of popular LLMs using composable and modular building blocks, easy-to-use and hackable training recipes for popular fine-tuning techniques, YAML configs for easily configuring training, evaluation, quantization, or inference recipes, and built-in support for many popular dataset formats and prompt templates to help you quickly get started with training.

Diffusion Toolkit is an image metadata-indexer and viewer for AI-generated images. It helps you organize, search, and sort your ever-growing collection. Key features include: - Scanning images and storing prompts and other metadata (PNGInfo) - Searching for images using simple queries or filters - Viewing images and metadata easily - Tagging images with favorites, ratings, and NSFW flags - Sorting images by date created, aesthetic score, or rating - Auto-tagging NSFW images by keywords - Blurring images tagged as NSFW - Creating and managing albums - Viewing and searching prompts - Drag-and-drop functionality Diffusion Toolkit supports various image formats, including JPG/JPEG, PNG, WebP, and TXT metadata. It also supports metadata formats from popular AI image generators like AUTOMATIC1111, InvokeAI, NovelAI, Stable Diffusion, and more. You can use Diffusion Toolkit even on images without metadata and still enjoy features like rating and album management.

Diffusion Toolkit is an image metadata-indexer and viewer for AI-generated images. It helps you organize, search, and sort your ever-growing collection. Key features include: - Scanning images and storing prompts and other metadata (PNGInfo) - Searching for images using simple queries or filters - Viewing images and metadata easily - Tagging images with favorites, ratings, and NSFW flags - Sorting images by date created, aesthetic score, or rating - Auto-tagging NSFW images by keywords - Blurring images tagged as NSFW - Creating and managing albums - Viewing and searching prompts - Drag-and-drop functionality Diffusion Toolkit supports various image formats, including JPG/JPEG, PNG, WebP, and TXT metadata. It also supports metadata formats from popular AI image generators like AUTOMATIC1111, InvokeAI, NovelAI, Stable Diffusion, and more. You can use Diffusion Toolkit even on images without metadata and still enjoy features like rating and album management.