The Agent OS is an experimental framework and runtime to build sophisticated, long running, and self-coding AI agents. We believe that the most important super-power of AI agents is to write and execute their own code to interact with the world. But for that to work, they need to run in a suitable environment—a place designed to be inhabited by agents. The Agent OS is designed from the ground up to function as a long-term computing substrate for these kinds of self-evolving agents.

LLM Agents is a small library designed to build agents controlled by large language models. It aims to provide a better understanding of how such agents work in a concise manner. The library allows agents to be instructed by prompts, use custom-built components as tools, and run in a loop of Thought, Action, Observation. The agents leverage language models to generate Thought and Action, while tools like Python REPL, Google search, and Hacker News search provide Observations. The library requires setting up environment variables for OpenAI API and SERPAPI API keys. Users can create their own agents by importing the library and defining tools accordingly.

Lumigator is an open-source platform developed by Mozilla.ai to help users select the most suitable language model for their specific needs. It supports the evaluation of summarization tasks using sequence-to-sequence models such as BART and BERT, as well as causal models like GPT and Mistral. The platform aims to make model selection transparent, efficient, and empowering by providing a framework for comparing LLMs using task-specific metrics to evaluate how well a model fits a project's needs. Lumigator is in the early stages of development and plans to expand support to additional machine learning tasks and use cases in the future.

Godot RL Agents is an open-source package that facilitates the integration of Machine Learning algorithms with games created in the Godot Engine. It provides interfaces for popular RL frameworks, support for memory-based agents, 2D and 3D games, AI sensors, and is licensed under MIT. Users can train agents in the Godot editor, create custom environments, export trained agents in ONNX format, and utilize advanced features like different RL training frameworks.

Sorcery is a SillyTavern extension that allows AI characters to interact with the real world by executing user-defined scripts at specific events in the chat. It is easy to use and does not require a specially trained function calling model. Sorcery can be used to control smart home appliances, interact with virtual characters, and perform various tasks in the chat environment. It works by injecting instructions into the system prompt and intercepting markers to run associated scripts, providing a seamless user experience.

EZKL is a library and command-line tool for doing inference for deep learning models and other computational graphs in a zk-snark (ZKML). It enables the following workflow: 1. Define a computational graph, for instance a neural network (but really any arbitrary set of operations), as you would normally in pytorch or tensorflow. 2. Export the final graph of operations as an .onnx file and some sample inputs to a .json file. 3. Point ezkl to the .onnx and .json files to generate a ZK-SNARK circuit with which you can prove statements such as: > "I ran this publicly available neural network on some private data and it produced this output" > "I ran my private neural network on some public data and it produced this output" > "I correctly ran this publicly available neural network on some public data and it produced this output" In the backend we use the collaboratively-developed Halo2 as a proof system. The generated proofs can then be verified with much less computational resources, including on-chain (with the Ethereum Virtual Machine), in a browser, or on a device.

Clippinator is a code assistant tool that helps users develop code autonomously by planning, writing, debugging, and testing projects. It consists of agents based on GPT-4 that work together to assist the user in coding tasks. The main agent, Taskmaster, delegates tasks to specialized subagents like Architect, Writer, Frontender, Editor, QA, and Devops. The tool provides project architecture, tools for file and terminal operations, browser automation with Selenium, linting capabilities, CI integration, and memory management. Users can interact with the tool to provide feedback and guide the coding process, making it a powerful tool when combined with human intervention.

ReVA (Reverse Engineering Assistant) is a project aimed at building a disassembler agnostic AI assistant for reverse engineering tasks. It utilizes a tool-driven approach, providing small tools to the user to empower them in completing complex tasks. The assistant is designed to accept various inputs, guide the user in correcting mistakes, and provide additional context to encourage exploration. Users can ask questions, perform tasks like decompilation, class diagram generation, variable renaming, and more. ReVA supports different language models for online and local inference, with easy configuration options. The workflow involves opening the RE tool and program, then starting a chat session to interact with the assistant. Installation includes setting up the Python component, running the chat tool, and configuring the Ghidra extension for seamless integration. ReVA aims to enhance the reverse engineering process by breaking down actions into small parts, including the user's thoughts in the output, and providing support for monitoring and adjusting prompts.

Lovelaice is an AI-powered assistant for your terminal and editor. It can run bash commands, search the Internet, answer general and technical questions, complete text files, chat casually, execute code in various languages, and more. Lovelaice is configurable with API keys and LLM models, and can be used for a wide range of tasks requiring bash commands or coding assistance. It is designed to be versatile, interactive, and helpful for daily tasks and projects.

Claudine is an AI agent designed to reason and act autonomously, leveraging the Anthropic API, Unix command line tools, HTTP, local hard drive data, and internet data. It can administer computers, analyze files, implement features in source code, create new tools, and gather contextual information from the internet. Users can easily add specialized tools. Claudine serves as a blueprint for implementing complex autonomous systems, with potential for customization based on organization-specific needs. The tool is based on the anthropic-kotlin-sdk and aims to evolve into a versatile command line tool similar to 'git', enabling branching sessions for different tasks.

ModelBench is a tool for running safety benchmarks against AI models and generating detailed reports. It is part of the MLCommons project and is designed as a proof of concept to aggregate measures, relate them to specific harms, create benchmarks, and produce reports. The tool requires LlamaGuard for evaluating responses and a TogetherAI account for running benchmarks. Users can install ModelBench from GitHub or PyPI, run tests using Poetry, and create benchmarks by providing necessary API keys. The tool generates static HTML pages displaying benchmark scores and allows users to dump raw scores and manage cache for faster runs. ModelBench is aimed at enabling users to test their own models and create tests and benchmarks.

AI Agents Masterclass is a repository dedicated to teaching developers how to use AI agents to transform businesses and create powerful software. It provides weekly videos with accompanying code folders, guiding users on setting up Python environments, using environment variables, and installing necessary packages to run the code. The focus is on Large Language Models that can interact with the outside world to perform tasks like drafting emails, booking appointments, and managing tasks, enabling users to create innovative applications with minimal coding effort.

This project aims to create a real-life version of GLaDOS, an aware, interactive, and embodied AI entity. It involves training a voice generator, developing a 'Personality Core,' implementing a memory system, providing vision capabilities, creating 3D-printable parts, and designing an animatronics system. The software architecture focuses on low-latency voice interactions, utilizing a circular buffer for data recording, text streaming for quick transcription, and a text-to-speech system. The project also emphasizes minimal dependencies for running on constrained hardware. The hardware system includes servo- and stepper-motors, 3D-printable parts for GLaDOS's body, animations for expression, and a vision system for tracking and interaction. Installation instructions cover setting up the TTS engine, required Python packages, compiling llama.cpp, installing an inference backend, and voice recognition setup. GLaDOS can be run using 'python glados.py' and tested using 'demo.ipynb'.

aiohomekit is a Python library that implements the HomeKit protocol for controlling HomeKit accessories using asyncio. It is primarily used with Home Assistant, targeting the same versions of Python and following their code standards. The library is still under development and does not offer API guarantees yet. It aims to match the behavior of real HAP controllers, even when not strictly specified, and works around issues like JSON formatting, boolean encoding, header sensitivity, and TCP packet splitting. aiohomekit is primarily tested with Phillips Hue and Eve Extend bridges via Home Assistant, but is known to work with many more devices. It does not support BLE accessories and is intended for client-side use only.

Quimera is an exploit-generator tool that utilizes large language models (LLMs) to uncover smart contract exploits in Foundry. It follows steps such as obtaining the smart contract's source code, creating a prompt for the exploit goal, generating or enhancing a Foundry test case, running the test, and analyzing the transaction trace for profitability. The tool is currently in an experimental prototype stage, focusing on optimizing settings, prompt creation, and exploring its capabilities. It has successfully rediscovered known exploits like APEMAGA, VISOR, FIRE, XAI, and Thunder-Loan using Gemini Pro 2.5 06-05.

Greenplum Database (GPDB) is an advanced, fully featured, open source data warehouse, based on PostgreSQL. It provides powerful and rapid analytics on petabyte scale data volumes. Uniquely geared toward big data analytics, Greenplum Database is powered by the world’s most advanced cost-based query optimizer delivering high analytical query performance on large data volumes.

AutoGPT is a revolutionary tool that empowers everyone to harness the power of AI. With AutoGPT, you can effortlessly build, test, and delegate tasks to AI agents, unlocking a world of possibilities. Our mission is to provide the tools you need to focus on what truly matters: innovation and creativity.

The Agent OS is an experimental framework and runtime to build sophisticated, long running, and self-coding AI agents. We believe that the most important super-power of AI agents is to write and execute their own code to interact with the world. But for that to work, they need to run in a suitable environment—a place designed to be inhabited by agents. The Agent OS is designed from the ground up to function as a long-term computing substrate for these kinds of self-evolving agents.

ChatDev IDE is a tool for building your AI agent, Whether it's NPCs in games or powerful agent tools, you can design what you want for this platform. It accelerates prompt engineering through **JavaScript Support** that allows implementing complex prompting techniques.

This library provides functionality required to build ReAct Agent using Large Language Models (LLMs).

NPi is an open-source platform providing Tool-use APIs to empower AI agents with the ability to take action in the virtual world. It is currently under active development, and the APIs are subject to change in future releases. NPi offers a command line tool for installation and setup, along with a GitHub app for easy access to repositories. The platform also includes a Python SDK and examples like Calendar Negotiator and Twitter Crawler. Join the NPi community on Discord to contribute to the development and explore the roadmap for future enhancements.

The 'ai-agents' repository is a collection of books and resources focused on developing AI agents, including topics such as GPT models, building AI agents from scratch, machine learning theory and practice, and basic methods and tools for data analysis. The repository provides detailed explanations and guidance for individuals interested in learning about and working with AI agents.

The 'llms' repository is a comprehensive guide on Large Language Models (LLMs), covering topics such as language modeling, applications of LLMs, statistical language modeling, neural language models, conditional language models, evaluation methods, transformer-based language models, practical LLMs like GPT and BERT, prompt engineering, fine-tuning LLMs, retrieval augmented generation, AI agents, and LLMs for computer vision. The repository provides detailed explanations, examples, and tools for working with LLMs.

The 'ai-app' repository is a comprehensive collection of tools and resources related to artificial intelligence, focusing on topics such as server environment setup, PyCharm and Anaconda installation, large model deployment and training, Transformer principles, RAG technology, vector databases, AI image, voice, and music generation, and AI Agent frameworks. It also includes practical guides and tutorials on implementing various AI applications. The repository serves as a valuable resource for individuals interested in exploring different aspects of AI technology.

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.