Voicechat2 is a fast, fully local AI voice chat tool that uses WebSockets for communication. It includes a WebSocket server for remote access, default web UI with VAD and Opus support, and modular/swappable SRT, LLM, TTS servers. Users can customize components like SRT, LLM, and TTS servers, and run different models for voice-to-voice communication. The tool aims to reduce latency in voice communication and provides flexibility in server configurations.

Aphrodite is the official backend engine for PygmalionAI, serving as the inference endpoint for the website. It allows serving Hugging Face-compatible models with fast speeds. Features include continuous batching, efficient K/V management, optimized CUDA kernels, quantization support, distributed inference, and 8-bit KV Cache. The engine requires Linux OS and Python 3.8 to 3.12, with CUDA >= 11 for build requirements. It supports various GPUs, CPUs, TPUs, and Inferentia. Users can limit GPU memory utilization and access full commands via CLI.

Stable Diffusion web UI is a web interface for Stable Diffusion, implemented using Gradio library. It provides a user-friendly interface to access the powerful image generation capabilities of Stable Diffusion. With Stable Diffusion web UI, users can easily generate images from text prompts, edit and refine images using inpainting and outpainting, and explore different artistic styles and techniques. The web UI also includes a range of advanced features such as textual inversion, hypernetworks, and embeddings, allowing users to customize and fine-tune the image generation process. Whether you're an artist, designer, or simply curious about the possibilities of AI-generated art, Stable Diffusion web UI is a valuable tool that empowers you to create stunning and unique images.

Aphrodite is an inference engine optimized for serving HuggingFace-compatible models at scale. It leverages vLLM's Paged Attention technology to deliver high-performance model inference for multiple concurrent users. The engine supports continuous batching, efficient key/value management, optimized CUDA kernels, quantization support, distributed inference, and modern samplers. It can be easily installed and launched, with Docker support for deployment. Aphrodite requires Linux or Windows OS, Python 3.8 to 3.12, and CUDA >= 11. It is designed to utilize 90% of GPU VRAM but offers options to limit memory usage. Contributors are welcome to enhance the engine.

aiexe is a cutting-edge command-line interface (CLI) and graphical user interface (GUI) tool that integrates powerful AI capabilities directly into your terminal or desktop. It is designed for developers, tech enthusiasts, and anyone interested in AI-powered automation. aiexe provides an easy-to-use yet robust platform for executing complex tasks with just a few commands. Users can harness the power of various AI models from OpenAI, Anthropic, Ollama, Gemini, and GROQ to boost productivity and enhance decision-making processes.

Sarathi-Serve is the official OSDI'24 artifact submission for paper #444, focusing on 'Taming Throughput-Latency Tradeoff in LLM Inference'. It is a research prototype built on top of CUDA 12.1, designed to optimize throughput-latency tradeoff in Large Language Models (LLM) inference. The tool provides a Python environment for users to install and reproduce results from the associated experiments. Users can refer to specific folders for individual figures and are encouraged to cite the paper if they use the tool in their work.

R1-searcher is a tool designed to incentivize the search capability in large reasoning models (LRMs) via reinforcement learning. It enables LRMs to invoke web search and obtain external information during the reasoning process by utilizing a two-stage outcome-supervision reinforcement learning approach. The tool does not require instruction fine-tuning for cold start and is compatible with existing Base LLMs or Chat LLMs. It includes training code, inference code, model checkpoints, and a detailed technical report.

Scriberr is a self-hostable AI audio transcription app that utilizes open-source Whisper models from OpenAI for transcribing audio files locally on user's hardware. It offers fast transcription with customizable compute settings, local transcription on device, API endpoints for automation, and integration with other tools. Users can optionally summarize transcripts using ChatGPT or Ollama, with support for custom prompts. The app is mobile-ready, simple, and easy to use, with planned features including speaker diarization, audio recording, file actions, full text fuzzy search, tag-based organization, follow-along text with playback, edit summaries, export options, and support for other languages. Despite being in beta, Scriberr is functional and usable, albeit with some rough edges and minor bugs.

ztachip is a RISCV accelerator designed for vision and AI edge applications, offering up to 20-50x acceleration compared to non-accelerated RISCV implementations. It features an innovative tensor processor hardware to accelerate various vision tasks and TensorFlow AI models. ztachip introduces a new tensor programming paradigm for massive processing/data parallelism. The repository includes technical documentation, code structure, build procedures, and reference design examples for running vision/AI applications on FPGA devices. Users can build ztachip as a standalone executable or a micropython port, and run various AI/vision applications like image classification, object detection, edge detection, motion detection, and multi-tasking on supported hardware.

InfiniStore is an open-source high-performance KV store designed to support LLM Inference clusters. It provides high-performance and low-latency KV cache transfer and reuse among inference nodes. In addition to inference clusters, it can be used as a standalone KV store for integration with LLM training or inference services. InfiniStore is currently integrated with vLLM via LMCache and is in progress for integration with SGLang and other inference engines.

Horizon AI Boilerplate is an open-source Admin Dashboard template designed for Shadcn UI, NextJS, and Tailwind CSS. It provides over 30 dark/light frontend elements for creating Chat AI SaaS Apps quickly. The documentation is detailed and complex, guiding users through installation and usage. Users can start their local server with simple commands. The tool requires a valid OpenAI API key for ChatGPT functionality. Additionally, a Figma version is available for design purposes. The PRO version offers more components and pages. Users can report issues on GitHub and connect with the community via Discord. The tool credits open-source resources like Shadcn UI Library, NextJS Subscription Payments, and ChatBot UI by mckaywrigley.

Discover the journey of building a generative AI application using LangChain.js and Azure. This demo explores the development process from idea to production, using a RAG-based approach for a Q&A system based on YouTube video transcripts. The application allows to ask text-based questions about a YouTube video and uses the transcript of the video to generate responses. The code comes in two versions: local prototype using FAISS and Ollama with LLaMa3 model for completion and all-minilm-l6-v2 for embeddings, and Azure cloud version using Azure AI Search and GPT-4 Turbo model for completion and text-embedding-3-large for embeddings. Either version can be run as an API using the Azure Functions runtime.

Collection of client-side AI demos showcasing various AI applications using Chrome's built-in AI, Transformers.js, and Google's Gemma model through MediaPipe. Demos include weather description generation, summarization API, performance tips, utility functions, sentiment analysis, toxicity assessment, and streaming content using Server Sent Events.

This repository, llamafile-docker, automates the process of checking for new releases of Mozilla-Ocho/llamafile, building a Docker image with the latest version, and pushing it to Docker Hub. Users can download a pre-trained model in gguf format and use the Docker image to interact with the model via a server or CLI version. Contributions are welcome under the Apache 2.0 license.

Modus is an open-source, serverless framework for building APIs powered by WebAssembly. It simplifies integrating AI models, data, and business logic with sandboxed execution. Modus extracts metadata, compiles code with optimizations, caches compiled modules, prepares invocation plans, generates API schema, and activates endpoints. Users query the endpoint, and Modus loads compiled code into a sandboxed environment, runs code securely, queries data and AI models, and responds via API. It provides a production-ready scalable endpoint for AI-enabled apps, optimized for sub-second response times. Modus supports programming languages like AssemblyScript and Go, and can be hosted on Hypermode or any platform. Developed by Hypermode as an open-source project, Modus welcomes external contributions.

Pathway is a Python data processing framework for analytics and AI pipelines over data streams. It's the ideal solution for real-time processing use cases like streaming ETL or RAG pipelines for unstructured data. Pathway comes with an **easy-to-use Python API** , allowing you to seamlessly integrate your favorite Python ML libraries. Pathway code is versatile and robust: **you can use it in both development and production environments, handling both batch and streaming data effectively**. The same code can be used for local development, CI/CD tests, running batch jobs, handling stream replays, and processing data streams. Pathway is powered by a **scalable Rust engine** based on Differential Dataflow and performs incremental computation. Your Pathway code, despite being written in Python, is run by the Rust engine, enabling multithreading, multiprocessing, and distributed computations. All the pipeline is kept in memory and can be easily deployed with **Docker and Kubernetes**. You can install Pathway with pip: `pip install -U pathway` For any questions, you will find the community and team behind the project on Discord.

Omnia is a deployment tool designed to turn servers with RPM-based Linux images into functioning Slurm/Kubernetes clusters. It provides an Ansible playbook-based deployment for Slurm and Kubernetes on servers running an RPM-based Linux OS. The tool simplifies the process of setting up and managing clusters, making it easier for users to deploy and maintain their infrastructure.

Voicechat2 is a fast, fully local AI voice chat tool that uses WebSockets for communication. It includes a WebSocket server for remote access, default web UI with VAD and Opus support, and modular/swappable SRT, LLM, TTS servers. Users can customize components like SRT, LLM, and TTS servers, and run different models for voice-to-voice communication. The tool aims to reduce latency in voice communication and provides flexibility in server configurations.

llm-ui is a React library designed for LLMs, providing features such as removing broken markdown syntax, adding custom components to LLM output, smoothing out pauses in streamed output, rendering at native frame rate, supporting code blocks for every language with Shiki, and being headless to allow for custom styles. The library aims to enhance the user experience and flexibility when working with LLMs.

David UI is a free and open-source collection of customizable, production-ready UI components built with Tailwind CSS. It is designed to be developer-friendly and performance-focused, streamlining the creation of modern, visually appealing interfaces to help deliver high-quality user experiences faster.

The Aimeos GrapesJS CMS extension provides a simple to use but powerful page editor for creating content pages based on extensible components. It integrates seamlessly with Laravel applications and allows users to easily manage and display CMS content. The tool also supports Google reCAPTCHA v3 for enhanced security. Users can create and customize pages with various components and manage multi-language setups effortlessly. The extension simplifies the process of creating and managing content pages, making it ideal for developers and businesses looking to enhance their website's content management capabilities.

Cache-Augmented Generation (CAG) is an alternative paradigm to Retrieval-Augmented Generation (RAG) that eliminates real-time retrieval delays and errors by preloading all relevant resources into the model's context. CAG leverages extended context windows of large language models (LLMs) to generate responses directly, providing reduced latency, improved reliability, and simplified design. While CAG has limitations in knowledge size and context length, advancements in LLMs are addressing these issues, making CAG a practical and scalable alternative for complex applications.

KIVI is a plug-and-play 2bit KV cache quantization algorithm optimizing memory usage by quantizing key cache per-channel and value cache per-token to 2bit. It enables LLMs to maintain quality while reducing memory usage, allowing larger batch sizes and increasing throughput in real LLM inference workloads.

Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.

The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.

This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.

Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.

Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.

BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students

uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.

Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.