Open Interface is a self-driving software that automates computer tasks by sending user requests to a language model backend (e.g., GPT-4V) and simulating keyboard and mouse inputs to execute the steps. It course-corrects by sending current screenshots to the language models. The tool supports MacOS, Linux, and Windows, and requires setting up the OpenAI API key for access to GPT-4V. It can automate tasks like creating meal plans, setting up custom language model backends, and more. Open Interface is currently not efficient in accurate spatial reasoning, tracking itself in tabular contexts, and navigating complex GUI-rich applications. Future improvements aim to enhance the tool's capabilities with better models trained on video walkthroughs. The tool is cost-effective, with user requests priced between $0.05 - $0.20, and offers features like interrupting the app and primary display visibility in multi-monitor setups.

Coreply is an open-source Android app that provides texting suggestions while typing, enhancing the typing experience with intelligent, context-aware suggestions. It supports various texting apps and offers real-time AI suggestions, customizable LLM settings, and ensures no data collection. Users can install the app, configure it with an API key, and start receiving suggestions while typing in messaging apps. The tool supports different AI models from providers like OpenAI, Google AI Studio, Openrouter, Groq, and Codestral for chat completion and fill-in-the-middle tasks.

OpenLIT is an OpenTelemetry-native GenAI and LLM Application Observability tool. It's designed to make the integration process of observability into GenAI projects as easy as pie – literally, with just **a single line of code**. Whether you're working with popular LLM Libraries such as OpenAI and HuggingFace or leveraging vector databases like ChromaDB, OpenLIT ensures your applications are monitored seamlessly, providing critical insights to improve performance and reliability.

EvoAgentX is an open-source framework for building, evaluating, and evolving LLM-based agents or agentic workflows in an automated, modular, and goal-driven manner. It enables developers and researchers to move beyond static prompt chaining or manual workflow orchestration by introducing a self-evolving agent ecosystem. The framework includes features such as agent workflow autoconstruction, built-in evaluation, self-evolution engine, plug-and-play compatibility, comprehensive built-in tools, memory module support, and human-in-the-loop interactions.

Generative AI models have shown tremendous usefulness in increasing accessibility and automation of a wide range of tasks. This repository contains the `biochatter` Python package, a generic backend library for the connection of biomedical applications to conversational AI. It aims to provide a common framework for deploying, testing, and evaluating diverse models and auxiliary technologies in the biomedical domain. BioChatter is part of the BioCypher ecosystem, connecting natively to BioCypher knowledge graphs.

Mage is an open-source data pipeline tool for transforming and integrating data. It offers an easy developer experience, engineering best practices built-in, and data as a first-class citizen. Mage makes it easy to build, preview, and launch data pipelines, and provides observability and scaling capabilities. It supports data integrations, streaming pipelines, and dbt integration.

A sleek and powerful macOS client for Amazon Bedrock, bringing AI models to your desktop. It provides seamless interaction with multiple Amazon Bedrock models, real-time chat interface, easy model switching, support for various AI tasks, and native Dark Mode support. Built with SwiftUI for optimal performance and modern UI.

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.

vLLM Ascend plugin is a backend plugin designed to run vLLM on the Ascend NPU. It provides a hardware-pluggable interface that allows popular open-source models to run seamlessly on the Ascend NPU. The plugin is recommended within the vLLM community and adheres to the principles of hardware pluggability outlined in the RFC. Users can set up their environment with specific hardware and software prerequisites to utilize this plugin effectively.

SillyTavern is a user interface you can install on your computer (and Android phones) that allows you to interact with text generation AIs and chat/roleplay with characters you or the community create. SillyTavern is a fork of TavernAI 1.2.8 which is under more active development and has added many major features. At this point, they can be thought of as completely independent programs.

OpenRL is an open-source general reinforcement learning research framework that supports training for various tasks such as single-agent, multi-agent, offline RL, self-play, and natural language. Developed based on PyTorch, the goal of OpenRL is to provide a simple-to-use, flexible, efficient and sustainable platform for the reinforcement learning research community. It supports a universal interface for all tasks/environments, single-agent and multi-agent tasks, offline RL training with expert dataset, self-play training, reinforcement learning training for natural language tasks, DeepSpeed, Arena for evaluation, importing models and datasets from Hugging Face, user-defined environments, models, and datasets, gymnasium environments, callbacks, visualization tools, unit testing, and code coverage testing. It also supports various algorithms like PPO, DQN, SAC, and environments like Gymnasium, MuJoCo, Atari, and more.

ESP-AI provides a complete AI conversation solution for your development board, including IAT+LLM+TTS integration solutions for ESP32 series development boards. It can be injected into projects without affecting existing ones. By providing keys from platforms like iFlytek, Jiling, and local services, you can run the services without worrying about interactions between services or between development boards and services. The project's server-side code is based on Node.js, and the hardware code is based on Arduino IDE.

BeeAI Framework is a versatile tool for building production-ready multi-agent systems. It offers flexibility in orchestrating agents, seamless integration with various models and tools, and production-grade controls for scaling. The framework supports Python and TypeScript libraries, enabling users to implement simple to complex multi-agent patterns, connect with AI services, and optimize token usage and resource management.

Kuwa GenAI OS is an open, free, secure, and privacy-focused Generative-AI Operating System. It provides a multi-lingual turnkey solution for GenAI development and deployment on Linux and Windows. Users can enjoy features such as concurrent multi-chat, quoting, full prompt-list import/export/share, and flexible orchestration of prompts, RAGs, bots, models, and hardware/GPUs. The system supports various environments from virtual hosts to cloud, and it is open source, allowing developers to contribute and customize according to their needs.

The serverless-rag-demo repository showcases a solution for building a Retrieval Augmented Generation (RAG) system using Amazon Opensearch Serverless Vector DB, Amazon Bedrock, Llama2 LLM, and Falcon LLM. The solution leverages generative AI powered by large language models to generate domain-specific text outputs by incorporating external data sources. Users can augment prompts with relevant context from documents within a knowledge library, enabling the creation of AI applications without managing vector database infrastructure. The repository provides detailed instructions on deploying the RAG-based solution, including prerequisites, architecture, and step-by-step deployment process using AWS Cloudshell.

Cognee is an open-source framework designed for creating self-improving deterministic outputs for Large Language Models (LLMs) using graphs, LLMs, and vector retrieval. It provides a platform for AI engineers to enhance their models and generate more accurate results. Users can leverage Cognee to add new information, utilize LLMs for knowledge creation, and query the system for relevant knowledge. The tool supports various LLM providers and offers flexibility in adding different data types, such as text files or directories. Cognee aims to streamline the process of working with LLMs and improving AI models for better performance and efficiency.

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.

Danswer is an open-source Gen-AI Chat and Unified Search tool that connects to your company's docs, apps, and people. It provides a Chat interface and plugs into any LLM of your choice. Danswer can be deployed anywhere and for any scale - on a laptop, on-premise, or to cloud. Since you own the deployment, your user data and chats are fully in your own control. Danswer is MIT licensed and designed to be modular and easily extensible. The system also comes fully ready for production usage with user authentication, role management (admin/basic users), chat persistence, and a UI for configuring Personas (AI Assistants) and their Prompts. Danswer also serves as a Unified Search across all common workplace tools such as Slack, Google Drive, Confluence, etc. By combining LLMs and team specific knowledge, Danswer becomes a subject matter expert for the team. Imagine ChatGPT if it had access to your team's unique knowledge! It enables questions such as "A customer wants feature X, is this already supported?" or "Where's the pull request for feature Y?"

Semantic Kernel is an SDK that integrates Large Language Models (LLMs) like OpenAI, Azure OpenAI, and Hugging Face with conventional programming languages like C#, Python, and Java. Semantic Kernel achieves this by allowing you to define plugins that can be chained together in just a few lines of code. What makes Semantic Kernel _special_ , however, is its ability to _automatically_ orchestrate plugins with AI. With Semantic Kernel planners, you can ask an LLM to generate a plan that achieves a user's unique goal. Afterwards, Semantic Kernel will execute the plan for the user.

Floneum is a graph editor that makes it easy to develop your own AI workflows. It uses large language models (LLMs) to run AI models locally, without any external dependencies or even a GPU. This makes it easy to use LLMs with your own data, without worrying about privacy. Floneum also has a plugin system that allows you to improve the performance of LLMs and make them work better for your specific use case. Plugins can be used in any language that supports web assembly, and they can control the output of LLMs with a process similar to JSONformer or guidance.

MindsDB is a platform for customizing AI from enterprise data. You can create, serve, and fine-tune models in real-time from your database, vector store, and application data. MindsDB "enhances" SQL syntax with AI capabilities to make it accessible for developers worldwide. With MindsDB’s nearly 200 integrations, any developer can create AI customized for their purpose, faster and more securely. Their AI systems will constantly improve themselves — using companies’ own data, in real-time.

AiScript is a lightweight scripting language that runs on JavaScript. It supports arrays, objects, and functions as first-class citizens, and is easy to write without the need for semicolons or commas. AiScript runs in a secure sandbox environment, preventing infinite loops from freezing the host. It also allows for easy provision of variables and functions from the host.

Activepieces is an open source replacement for Zapier, designed to be extensible through a type-safe pieces framework written in Typescript. It features a user-friendly Workflow Builder with support for Branches, Loops, and Drag and Drop. Activepieces integrates with Google Sheets, OpenAI, Discord, and RSS, along with 80+ other integrations. The list of supported integrations continues to grow rapidly, thanks to valuable contributions from the community. Activepieces is an open ecosystem; all piece source code is available in the repository, and they are versioned and published directly to npmjs.com upon contributions. If you cannot find a specific piece on the pieces roadmap, please submit a request by visiting the following link: Request Piece Alternatively, if you are a developer, you can quickly build your own piece using our TypeScript framework. For guidance, please refer to the following guide: Contributor's Guide

Superagent is an open source framework that enables any developer to integrate production ready AI Assistants into any application in a matter of minutes.

AiScript is a lightweight scripting language that runs on JavaScript. It supports arrays, objects, and functions as first-class citizens, and is easy to write without the need for semicolons or commas. AiScript runs in a secure sandbox environment, preventing infinite loops from freezing the host. It also allows for easy provision of variables and functions from the host.

AskUI is a reliable, automated end-to-end automation tool that only depends on what is shown on your screen instead of the technology or platform you are running on.

The 'bots' repository is a collection of guides, tools, and example bots for programming bots to play video games. It provides resources on running bots live, installing the BotLab client, debugging bots, testing bots in simulated environments, and more. The repository also includes example bots for games like EVE Online, Tribal Wars 2, and Elvenar. Users can learn about developing bots for specific games, syntax of the Elm programming language, and tools for memory reading development. Additionally, there are guides on bot programming, contributing to BotLab, and exploring Elm syntax and core library.

Ain is a terminal HTTP API client designed for scripting input and processing output via pipes. It allows flexible organization of APIs using files and folders, supports shell-scripts and executables for common tasks, handles url-encoding, and enables sharing the resulting curl, wget, or httpie command-line. Users can put things that change in environment variables or .env-files, and pipe the API output for further processing. Ain targets users who work with many APIs using a simple file format and uses curl, wget, or httpie to make the actual calls.

LaVague is an open-source Large Action Model framework that uses advanced AI techniques to compile natural language instructions into browser automation code. It leverages Selenium or Playwright for browser actions. Users can interact with LaVague through an interactive Gradio interface to automate web interactions. The tool requires an OpenAI API key for default examples and offers a Playwright integration guide. Contributors can help by working on outlined tasks, submitting PRs, and engaging with the community on Discord. The project roadmap is available to track progress, but users should exercise caution when executing LLM-generated code using 'exec'.

Robocorp is a platform that allows users to create, deploy, and operate Python automations and AI actions. It provides an easy way to extend the capabilities of AI agents, assistants, and copilots with custom actions written in Python. Users can create and deploy tools, skills, loaders, and plugins that securely connect any AI Assistant platform to their data and applications. The Robocorp Action Server makes Python scripts compatible with ChatGPT and LangChain by automatically creating and exposing an API based on function declaration, type hints, and docstrings. It simplifies the process of developing and deploying AI actions, enabling users to interact with AI frameworks effortlessly.

Open Interface is a self-driving software that automates computer tasks by sending user requests to a language model backend (e.g., GPT-4V) and simulating keyboard and mouse inputs to execute the steps. It course-corrects by sending current screenshots to the language models. The tool supports MacOS, Linux, and Windows, and requires setting up the OpenAI API key for access to GPT-4V. It can automate tasks like creating meal plans, setting up custom language model backends, and more. Open Interface is currently not efficient in accurate spatial reasoning, tracking itself in tabular contexts, and navigating complex GUI-rich applications. Future improvements aim to enhance the tool's capabilities with better models trained on video walkthroughs. The tool is cost-effective, with user requests priced between $0.05 - $0.20, and offers features like interrupting the app and primary display visibility in multi-monitor setups.

AI-Case-Sorter-CS7.1 is a project focused on building a case sorter using machine vision and machine learning AI to sort cases by headstamp. The repository includes Arduino code and 3D models necessary for the project.