Open Computer Use is a secure cloud Linux computer powered by E2B Desktop Sandbox and controlled by open-source LLMs. It allows users to operate the computer via keyboard, mouse, and shell commands, live stream the display of the sandbox on the client computer, and pause or prompt the agent at any time. The tool is designed to work with any operating system and supports integration with various LLMs and providers following the OpenAI API specification.

eShopSupport is a sample .NET application showcasing common use cases and development practices for building AI solutions in .NET, specifically Generative AI. It demonstrates a customer support application for an e-commerce website using a services-based architecture with .NET Aspire. The application includes support for text classification, sentiment analysis, text summarization, synthetic data generation, and chat bot interactions. It also showcases development practices such as developing solutions locally, evaluating AI responses, leveraging Python projects, and deploying applications to the Cloud.

The 'llm-memorization' project is a tool designed to index, archive, and search conversations with a local LLM using a SQLite database enriched with automatically extracted keywords. It aims to provide personalized context at the start of a conversation by adding memory information to the initial prompt. The tool automates queries from local LLM conversational management libraries, offers a hybrid search function, enhances prompts based on posed questions, and provides an all-in-one graphical user interface for data visualization. It supports both French and English conversations and prompts for bilingual use.

VoiceStreamAI is a Python 3-based server and JavaScript client solution for near-realtime audio streaming and transcription using WebSocket. It employs Huggingface's Voice Activity Detection (VAD) and OpenAI's Whisper model for accurate speech recognition. The system features real-time audio streaming, modular design for easy integration of VAD and ASR technologies, customizable audio chunk processing strategies, support for multilingual transcription, and secure sockets support. It uses a factory and strategy pattern implementation for flexible component management and provides a unit testing framework for robust development.

LARS is an application that enables users to run Large Language Models (LLMs) locally on their devices, upload their own documents, and engage in conversations where the LLM grounds its responses with the uploaded content. The application focuses on Retrieval Augmented Generation (RAG) to increase accuracy and reduce AI-generated inaccuracies. LARS provides advanced citations, supports various file formats, allows follow-up questions, provides full chat history, and offers customization options for LLM settings. Users can force enable or disable RAG, change system prompts, and tweak advanced LLM settings. The application also supports GPU-accelerated inferencing, multiple embedding models, and text extraction methods. LARS is open-source and aims to be the ultimate RAG-centric LLM application.

Discover Whisper-TikTok, an innovative AI-powered tool that leverages the prowess of Edge TTS, OpenAI-Whisper, and FFMPEG to craft captivating TikTok videos. Whisper-TikTok effortlessly generates accurate transcriptions from audio files and integrates Microsoft Edge Cloud Text-to-Speech API for vibrant voiceovers. The program orchestrates the synthesis of videos using a structured JSON dataset, generating mesmerizing TikTok content in minutes.

This repository provides configuration and scripts for running Ollama LLM server on Apple Silicon Macs in headless mode, optimized for performance and resource usage. It includes features like automatic startup, system resource optimization, external network access, proper logging setup, and SSH-based remote management. Users can customize the Ollama service configuration and enable optional GPU memory optimization and Docker autostart for container applications. The installation process disables unnecessary system services, configures power management, and optimizes for background operation while maintaining Screen Sharing capability for remote management. Performance considerations focus on reducing memory usage, disabling GUI-related services, minimizing background processes, preventing sleep/hibernation, and optimizing for headless operation.

Agentok Studio is a tool built upon AG2, a powerful agent framework from Microsoft, offering intuitive visual tools to streamline the creation and management of complex agent-based workflows. It simplifies the process for creators and developers by generating native Python code with minimal dependencies, enabling users to create self-contained code that can be executed anywhere. The tool is currently under development and not recommended for production use, but contributions are welcome from the community to enhance its capabilities and functionalities.

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.

Single File Agents (SFA) is a collection of powerful single-file agents built on top of uv, a modern Python package installer and resolver. These agents aim to perform specific tasks efficiently, demonstrating precise prompt engineering and GenAI patterns. The repository contains agents built across major GenAI providers like Gemini, OpenAI, and Anthropic. Each agent is self-contained, minimal, and built on modern Python for fast and reliable dependency management. Users can run these scripts from their server or directly from a gist. The agents are patternful, emphasizing the importance of setting up effective prompts, tools, and processes for reusability.

Open CUAK (Computer Use Agent) is a platform for managing automation agents at scale, designed to run and manage thousands of automation agents with reliability. It allows for abundant productivity by ensuring scalability and profitability. The project aims to usher in a new era of work with equally distributed productivity, making it open-sourced for real businesses and real people. The core features include running operator-like automation workflows locally, vision-based automation, turning any browser into an operator-companion, utilizing a dedicated remote browser, and more.

STORM is a LLM system that writes Wikipedia-like articles from scratch based on Internet search. While the system cannot produce publication-ready articles that often require a significant number of edits, experienced Wikipedia editors have found it helpful in their pre-writing stage. **Try out our [live research preview](https://storm.genie.stanford.edu/) to see how STORM can help your knowledge exploration journey and please provide feedback to help us improve the system 🙏!**

KAITO is an operator that automates the AI/ML model inference or tuning workload in a Kubernetes cluster. It manages large model files using container images, provides preset configurations to avoid adjusting workload parameters based on GPU hardware, supports popular open-sourced inference runtimes, auto-provisions GPU nodes based on model requirements, and hosts large model images in the public Microsoft Container Registry. Using KAITO simplifies the workflow of onboarding large AI inference models in Kubernetes.

VerifyWise is an open-source AI governance platform designed to help businesses harness the power of AI safely and responsibly. The platform ensures compliance and robust AI management without compromising on security. It offers additional products like MaskWise for data redaction, EvalWise for AI model evaluation, and FlagWise for security threat monitoring. VerifyWise simplifies AI governance for organizations, aiding in risk management, regulatory compliance, and promoting responsible AI practices. It features options for on-premises or private cloud hosting, open-source with AGPLv3 license, AI-generated answers for compliance audits, source code transparency, Docker deployment, user registration, role-based access control, and various AI governance tools like risk management, bias & fairness checks, evidence center, AI trust center, and more.

llama.vscode is a local LLM-assisted text completion extension for Visual Studio Code. It provides auto-suggestions on input, allows accepting suggestions with shortcuts, and offers various features to enhance text completion. The extension is designed to be lightweight and efficient, enabling high-quality completions even on low-end hardware. Users can configure the scope of context around the cursor and control text generation time. It supports very large contexts and displays performance statistics for better user experience.

Slidev AI is a web app that leverages LLM (Large Language Model) technology to make creating Slidev-based online presentations elegant and effortless. It is designed to help engineers and academics quickly produce content-focused, minimalist PPTs that are easily shareable online. This project serves as a reference implementation for OpenMCP agent development, a production-ready presentation generation solution, and a template for creating domain-specific AI agents.

The Azure-Analytics-and-AI-Engagement repository provides packaged Industry Scenario DREAM Demos with ARM templates (Containing a demo web application, Power BI reports, Synapse resources, AML Notebooks etc.) that can be deployed in a customer’s subscription using the CAPE tool within a matter of few hours. Partners can also deploy DREAM Demos in their own subscriptions using DPoC.

Sorrentum is an open-source project that aims to combine open-source development, startups, and brilliant students to build machine learning, AI, and Web3 / DeFi protocols geared towards finance and economics. The project provides opportunities for internships, research assistantships, and development grants, as well as the chance to work on cutting-edge problems, learn about startups, write academic papers, and get internships and full-time positions at companies working on Sorrentum applications.

TiDB is an open-source distributed SQL database that supports Hybrid Transactional and Analytical Processing (HTAP) workloads. It is MySQL compatible and features horizontal scalability, strong consistency, and high availability.

Zep is an open-source platform for building and deploying large language model (LLM) applications. It provides a suite of tools and services that make it easy to integrate LLMs into your applications, including chat history memory, embedding, vector search, and data enrichment. Zep is designed to be scalable, reliable, and easy to use, making it a great choice for developers who want to build LLM-powered applications quickly and easily.

This repository codifies the Airflow cluster that is deployed at workflow.telemetry.mozilla.org (behind SSO) and commonly referred to as "WTMO" or simply "Airflow". Some links relevant to users and developers of WTMO: * The `dags` directory in this repository contains some custom DAG definitions * Many of the DAGs registered with WTMO don't live in this repository, but are instead generated from ETL task definitions in bigquery-etl * The Data SRE team maintains a WTMO Developer Guide (behind SSO)

Mojo is a new programming language that bridges the gap between research and production by combining Python syntax and ecosystem with systems programming and metaprogramming features. Mojo is still young, but it is designed to become a superset of Python over time.

PandasAI is a Python library that makes it easy to ask questions to your data in natural language. It helps you to explore, clean, and analyze your data using generative AI.

Databend is an open-source cloud data warehouse that serves as a cost-effective alternative to Snowflake. With its focus on fast query execution and data ingestion, it's designed for complex analysis of the world's largest datasets.

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.