exo

Run your own AI cluster at home with everyday devices. Exo is experimental software that unifies existing devices into a powerful GPU, supporting wide model compatibility, dynamic model partitioning, automatic device discovery, ChatGPT-compatible API, and device equality. It does not use a master-worker architecture, allowing devices to connect peer-to-peer. Exo supports different partitioning strategies like ring memory weighted partitioning. Installation is recommended from source. Documentation includes example usage on multiple MacOS devices and information on inference engines and networking modules. Known issues include the iOS implementation lagging behind Python.

Iceburg CRM is a metadata driven CRM with AI abilities that allows users to quickly prototype any CRM. It offers features like metadata creations, import/export in multiple formats, field validation, themes, role permissions, calendar, audit logs, API, workflow, field level relationships, module level relationships, and more. Created with Vue 3 for the frontend, Laravel 10 for the backend, Tailwinds with DaisyUI plugin, and Inertia for routing. Users can install default, admin panel, core, custom, or AI versions. The tool supports AI Assist for module data suggestions and provides API endpoints for CRM modules, search, specific module data, record updates, and deletions. Iceburg CRM also includes themes, custom field types, calendar, datalets, workflow, roles and permissions, import/export functionality, and custom seeding options.

AIConfig is a framework that makes it easy to build generative AI applications for production. It manages generative AI prompts, models and model parameters as JSON-serializable configs that can be version controlled, evaluated, monitored and opened in a local editor for rapid prototyping. It allows you to store and iterate on generative AI behavior separately from your application code, offering a streamlined AI development workflow.

Fragments is an open-source tool that leverages Anthropic's Claude Artifacts, Vercel v0, and GPT Engineer. It is powered by E2B Sandbox SDK and Code Interpreter SDK, allowing secure execution of AI-generated code. The tool is based on Next.js 14, shadcn/ui, TailwindCSS, and Vercel AI SDK. Users can stream in the UI, install packages from npm and pip, and add custom stacks and LLM providers. Fragments enables users to build web apps with Python interpreter, Next.js, Vue.js, Streamlit, and Gradio, utilizing providers like OpenAI, Anthropic, Google AI, and more.

LoRAX is a framework that allows users to serve thousands of fine-tuned models on a single GPU, dramatically reducing the cost of serving without compromising on throughput or latency. It features dynamic adapter loading, heterogeneous continuous batching, adapter exchange scheduling, optimized inference, and is ready for production with prebuilt Docker images, Helm charts for Kubernetes, Prometheus metrics, and distributed tracing with Open Telemetry. LoRAX supports a number of Large Language Models as the base model including Llama, Mistral, and Qwen, and any of the linear layers in the model can be adapted via LoRA and loaded in LoRAX.

MetaAgent is a multi-agent collaboration platform designed to build, manage, and deploy multi-modal AI agents without the need for coding. Users can easily create AI agents by editing a yml file or using the provided UI. The platform supports features such as building LLM-based AI agents, multi-modal interactions with users using texts, audios, images, and videos, creating a company of agents for complex tasks like drawing comics, vector database and knowledge embeddings, and upcoming features like UI for creating and using AI agents, fine-tuning, and RLHF. The tool simplifies the process of creating and deploying AI agents for various tasks.

Taipy is an open-source Python library for easy, end-to-end application development, featuring what-if analyses, smart pipeline execution, built-in scheduling, and deployment tools.

Langrila is a library that provides an easy way to use API-based LLM (Large Language Models) with an emphasis on simple architecture for readability. It supports various AI models for chat and embedding tasks, as well as retrieval functionalities using Qdrant, Chroma, and Usearch. Langrila also includes modules for function calling, conversation memory management, and prompt templates. It enforces coding policies for simplicity, responsibility independence, and minimum module implementation. The library requires Python version 3.10 to 3.13 and additional dependencies like OpenAI, Gemini, Qdrant, Chroma, and Usearch for specific functionalities.

Avalon-LLM is a repository containing the official code for AvalonBench and the Avalon agent Strategist. AvalonBench evaluates Large Language Models (LLMs) playing The Resistance: Avalon, a board game requiring deductive reasoning, coordination, collaboration, and deception skills. Strategist utilizes LLMs to learn strategic skills through self-improvement, including high-level strategic evaluation and low-level execution guidance. The repository provides instructions for running AvalonBench, setting up Strategist, and conducting experiments with different agents in the game environment.

LLM Finetuning toolkit is a config-based CLI tool for launching a series of LLM fine-tuning experiments on your data and gathering their results. It allows users to control all elements of a typical experimentation pipeline - prompts, open-source LLMs, optimization strategy, and LLM testing - through a single YAML configuration file. The toolkit supports basic, intermediate, and advanced usage scenarios, enabling users to run custom experiments, conduct ablation studies, and automate fine-tuning workflows. It provides features for data ingestion, model definition, training, inference, quality assurance, and artifact outputs, making it a comprehensive tool for fine-tuning large language models.

Embodied Agents is a toolkit for integrating large multi-modal models into existing robot stacks with just a few lines of code. It provides consistency, reliability, scalability, and is configurable to any observation and action space. The toolkit is designed to reduce complexities involved in setting up inference endpoints, converting between different model formats, and collecting/storing datasets. It aims to facilitate data collection and sharing among roboticists by providing Python-first abstractions that are modular, extensible, and applicable to a wide range of tasks. The toolkit supports asynchronous and remote thread-safe agent execution for maximal responsiveness and scalability, and is compatible with various APIs like HuggingFace Spaces, Datasets, Gymnasium Spaces, Ollama, and OpenAI. It also offers automatic dataset recording and optional uploads to the HuggingFace hub.

Infinity is an AI-native database designed for LLM applications, providing incredibly fast full-text and vector search capabilities. It supports a wide range of data types, including vectors, full-text, and structured data, and offers a fused search feature that combines multiple embeddings and full text. Infinity is easy to use, with an intuitive Python API and a single-binary architecture that simplifies deployment. It achieves high performance, with 0.1 milliseconds query latency on million-scale vector datasets and up to 15K QPS.

ControlLLM is a framework that empowers large language models to leverage multi-modal tools for solving complex real-world tasks. It addresses challenges like ambiguous user prompts, inaccurate tool selection, and inefficient tool scheduling by utilizing a task decomposer, a Thoughts-on-Graph paradigm, and an execution engine with a rich toolbox. The framework excels in tasks involving image, audio, and video processing, showcasing superior accuracy, efficiency, and versatility compared to existing methods.

VideoKit is a full-featured user-generated content solution for Unity Engine, enabling video recording, camera streaming, microphone streaming, social sharing, and conversational interfaces. It is cross-platform, with C# source code available for inspection. Users can share media, save to camera roll, pick from camera roll, stream camera preview, record videos, remove background, caption audio, and convert text commands. VideoKit requires Unity 2022.3+ and supports Android, iOS, macOS, Windows, and WebGL platforms.

OSWorld is a benchmarking tool designed to evaluate multimodal agents for open-ended tasks in real computer environments. It provides a platform for running experiments, setting up virtual machines, and interacting with the environment using Python scripts. Users can install the tool on their desktop or server, manage dependencies with Conda, and run benchmark tasks. The tool supports actions like executing commands, checking for specific results, and evaluating agent performance. OSWorld aims to facilitate research in AI by providing a standardized environment for testing and comparing different agent baselines.

ChatterUI is a mobile app that allows users to manage chat files and character cards, and to interact with Large Language Models (LLMs). It supports multiple backends, including local, koboldcpp, text-generation-webui, Generic Text Completions, AI Horde, Mancer, Open Router, and OpenAI. ChatterUI provides a mobile-friendly interface for interacting with LLMs, making it easy to use them for a variety of tasks, such as generating text, translating languages, writing code, and answering questions.

OpenModelDB is a community-driven database of AI upscaling models, providing a centralized platform for users to access and compare various models. The repository contains a collection of models and model metadata, facilitating easy exploration and evaluation of different AI upscaling solutions. With a focus on enhancing the accessibility and usability of AI models, OpenModelDB aims to streamline the process of finding and selecting the most suitable models for specific tasks or projects.

Run your own AI cluster at home with everyday devices. Exo is experimental software that unifies existing devices into a powerful GPU, supporting wide model compatibility, dynamic model partitioning, automatic device discovery, ChatGPT-compatible API, and device equality. It does not use a master-worker architecture, allowing devices to connect peer-to-peer. Exo supports different partitioning strategies like ring memory weighted partitioning. Installation is recommended from source. Documentation includes example usage on multiple MacOS devices and information on inference engines and networking modules. Known issues include the iOS implementation lagging behind Python.

Spandrel is a library for loading and running pre-trained PyTorch models. It automatically detects the model architecture and hyperparameters from model files, and provides a unified interface for running models.

Open-DocLLM is an open-source project that addresses data extraction and processing challenges using OCR and LLM technologies. It consists of two main layers: OCR for reading document content and LLM for extracting specific content in a structured manner. The project offers a larger context window size compared to JP Morgan's DocLLM and integrates tools like Tesseract OCR and Mistral for efficient data analysis. Users can run the models on-premises using LLM studio or Ollama, and the project includes a FastAPI app for testing purposes.

Pipeline is a Python library designed for constructing computational flows for AI/ML models. It supports both development and production environments, offering capabilities for inference, training, and finetuning. The library serves as an interface to Mystic, enabling the execution of pipelines at scale and on enterprise GPUs. Users can also utilize this SDK with Pipeline Core on a private hosted cluster. The syntax for defining AI/ML pipelines is reminiscent of sessions in Tensorflow v1 and Flows in Prefect.

Prompt Panel is a tool designed to accelerate the adoption of AI agents by providing a platform where users can run large language models across any inference provider, create custom agent plugins, and use their own data safely. The tool allows users to break free from walled-gardens and have full control over their models, conversations, and logic. With Prompt Panel, users can pair their data with any language model, online or offline, and customize the system to meet their unique business needs without any restrictions.

LLMinator is a Gradio-based tool with an integrated chatbot designed to locally run and test Language Model Models (LLMs) directly from HuggingFace. It provides an easy-to-use interface made with Gradio, LangChain, and Torch, offering features such as context-aware streaming chatbot, inbuilt code syntax highlighting, loading any LLM repo from HuggingFace, support for both CPU and CUDA modes, enabling LLM inference with llama.cpp, and model conversion capabilities.

AI Edge Torch is a Python library that supports converting PyTorch models into a .tflite format for on-device applications on Android, iOS, and IoT devices. It offers broad CPU coverage with initial GPU and NPU support, closely integrating with PyTorch and providing good coverage of Core ATen operators. The library includes a PyTorch converter for model conversion and a Generative API for authoring mobile-optimized PyTorch Transformer models, enabling easy deployment of Large Language Models (LLMs) on mobile devices.

Weave is a toolkit for developing Generative AI applications, built by Weights & Biases. With Weave, you can log and debug language model inputs, outputs, and traces; build rigorous, apples-to-apples evaluations for language model use cases; and organize all the information generated across the LLM workflow, from experimentation to evaluations to production. Weave aims to bring rigor, best-practices, and composability to the inherently experimental process of developing Generative AI software, without introducing cognitive overhead.

LLMStack is a no-code platform for building generative AI agents, workflows, and chatbots. It allows users to connect their own data, internal tools, and GPT-powered models without any coding experience. LLMStack can be deployed to the cloud or on-premise and can be accessed via HTTP API or triggered from Slack or Discord.

The VisionCraft API is a free API for using over 100 different AI models. From images to sound.

Kaito is an operator that automates the AI/ML inference model deployment in a Kubernetes cluster. It manages large model files using container images, avoids tuning deployment parameters to fit GPU hardware by providing preset configurations, auto-provisions GPU nodes based on model requirements, and hosts large model images in the public Microsoft Container Registry (MCR) if the license allows. Using Kaito, the workflow of onboarding large AI inference models in Kubernetes is largely simplified.

PyRIT is an open access automation framework designed to empower security professionals and ML engineers to red team foundation models and their applications. It automates AI Red Teaming tasks to allow operators to focus on more complicated and time-consuming tasks and can also identify security harms such as misuse (e.g., malware generation, jailbreaking), and privacy harms (e.g., identity theft). The goal is to allow researchers to have a baseline of how well their model and entire inference pipeline is doing against different harm categories and to be able to compare that baseline to future iterations of their model. This allows them to have empirical data on how well their model is doing today, and detect any degradation of performance based on future improvements.

Tabby is a self-hosted AI coding assistant, offering an open-source and on-premises alternative to GitHub Copilot. It boasts several key features: * Self-contained, with no need for a DBMS or cloud service. * OpenAPI interface, easy to integrate with existing infrastructure (e.g Cloud IDE). * Supports consumer-grade GPUs.

SPEAR (Simulator for Photorealistic Embodied AI Research) is a powerful tool for training embodied agents. It features 300 unique virtual indoor environments with 2,566 unique rooms and 17,234 unique objects that can be manipulated individually. Each environment is designed by a professional artist and features detailed geometry, photorealistic materials, and a unique floor plan and object layout. SPEAR is implemented as Unreal Engine assets and provides an OpenAI Gym interface for interacting with the environments via Python.

Magick is a groundbreaking visual AIDE (Artificial Intelligence Development Environment) for no-code data pipelines and multimodal agents. Magick can connect to other services and comes with nodes and templates well-suited for intelligent agents, chatbots, complex reasoning systems and realistic characters.