This open-source project, also known as **Deep Learning System** or **AI System (AISys)**, aims to explore and learn about the system design of artificial intelligence and deep learning. The project is centered around the full-stack content of AI systems that ZOMI has accumulated,整理, and built during his work. The goal is to collaborate with all friends who are interested in AI open-source projects to jointly promote learning and discussion.

BaseAI is an AI framework designed for creating declarative and composable AI-powered LLM products. It enables the development of AI agent pipes locally, incorporating agentic tools and memory (RAG). The framework offers a learn guide for beginners to kickstart their journey with BaseAI. For detailed documentation, users can visit baseai.dev/docs. Contributions to BaseAI are encouraged, and interested individuals can refer to the Contributing Guide. The original authors of BaseAI include Ahmad Awais, Ashar Irfan, Saqib Ameen, Saad Irfan, and Ahmad Bilal. Security vulnerabilities can be reported privately via email to [email protected]. BaseAI aims to provide resources for learning AI agent development, utilizing agentic tools and memory.

The 'ai-demos' repository is a collection of example code from presentations focusing on building with AI and LLMs. It serves as a resource for developers looking to explore practical applications of artificial intelligence in their projects. The code snippets showcase various techniques and approaches to leverage AI technologies effectively. The repository aims to inspire and educate developers on integrating AI solutions into their applications.

The 'mslearn-ai-vision' repository contains lab files for Azure AI Vision modules. It provides hands-on exercises and resources for learning about AI vision capabilities on the Azure platform. The labs cover topics such as image recognition, object detection, and image classification using Azure's AI services. By following the lab exercises, users can gain practical experience in building and deploying AI vision solutions in the cloud.

AimRT is a basic runtime framework for modern robotics, developed in modern C++ with lightweight and easy deployment. It integrates research and development for robot applications in various deployment scenarios, providing debugging tools and observability support. AimRT offers a plug-in development interface compatible with ROS2, HTTP, Grpc, and other ecosystems for progressive system upgrades.

Open AI is a powerful tool for artificial intelligence research and development. It provides a wide range of machine learning models and algorithms, making it easier for developers to create innovative AI applications. With Open AI, users can explore cutting-edge technologies such as natural language processing, computer vision, and reinforcement learning. The platform offers a user-friendly interface and comprehensive documentation to support users in building and deploying AI solutions. Whether you are a beginner or an experienced AI practitioner, Open AI offers the tools and resources you need to accelerate your AI projects and stay ahead in the rapidly evolving field of artificial intelligence.

OmniChain is a tool for building efficient self-updating visual workflows using AI language models, enabling users to automate tasks, create chatbots, agents, and integrate with existing frameworks. It allows users to create custom workflows guided by logic processes, store and recall information, and make decisions based on that information. The tool enables users to create tireless robot employees that operate 24/7, access the underlying operating system, generate and run NodeJS code snippets, and create custom agents and logic chains. OmniChain is self-hosted, open-source, and available for commercial use under the MIT license, with no coding skills required.

Dust is a platform that provides customizable and secure AI assistants to amplify your team's potential. With Dust, you can build and deploy AI assistants that are tailored to your specific needs, without the need for extensive technical expertise. Dust's platform is easy to use and provides a variety of features to help you get started quickly, including a library of pre-built blocks, a developer platform, and an API reference.

AI_Spectrum is a versatile machine learning library that provides a wide range of tools and algorithms for building and deploying AI models. It offers a user-friendly interface for data preprocessing, model training, and evaluation. With AI_Spectrum, users can easily experiment with different machine learning techniques and optimize their models for various tasks. The library is designed to be flexible and scalable, making it suitable for both beginners and experienced data scientists.

This repository contains a collection of AI projects implemented in Python, primarily in Jupyter notebooks. The projects cover various aspects of artificial intelligence, including machine learning, deep learning, natural language processing, computer vision, and more. Each project is designed to showcase different AI techniques and algorithms, providing a hands-on learning experience for users interested in exploring the field of artificial intelligence.

A drill of scientific methods, processes, algorithms, and systems to build stories & models. An in-depth learning resource for humans. This repository is designed for individuals aiming to excel in the field of Data and AI, providing video sessions and text content for learning. It caters to those in leadership positions, professionals, and students, emphasizing the need for dedicated effort to achieve excellence in the tech field. The content covers various topics with a focus on practical application.

fAIr is an open AI-assisted mapping service developed by the Humanitarian OpenStreetMap Team (HOT) to improve mapping efficiency and accuracy for humanitarian purposes. It uses AI models, specifically computer vision techniques, to detect objects like buildings, roads, waterways, and trees from satellite and UAV imagery. The service allows OSM community members to create and train their own AI models for mapping in their region of interest and ensures models are relevant to local communities. Constant feedback loop with local communities helps eliminate model biases and improve model accuracy.

Runbooks is a repository that is no longer active. The project has been deprecated in favor of KubeAI, a platform designed to simplify the operationalization of AI on Kubernetes. For more information, please refer to the new repository at https://github.com/substratusai/kubeai.

CodeGPT is an extension for JetBrains IDEs that provides access to state-of-the-art large language models (LLMs) for coding assistance. It offers a range of features to enhance the coding experience, including code completions, a ChatGPT-like interface for instant coding advice, commit message generation, reference file support, name suggestions, and offline development support. CodeGPT is designed to keep privacy in mind, ensuring that user data remains secure and private.

This repository contains lab files for Azure AI Language modules. It provides hands-on exercises and resources for learning about various AI language technologies on the Azure platform. The labs cover topics such as natural language processing, text analytics, language understanding, and more. By following the exercises in this repository, users can gain practical experience in implementing AI language solutions using Azure services.

This repository is a comprehensive collection of cybersecurity-related references, scripts, tools, code, and other resources. It is carefully curated and maintained by Omar Santos. The repository serves as a supplemental material provider to several books, video courses, and live training created by Omar Santos. It encompasses over 10,000 references that are instrumental for both offensive and defensive security professionals in honing their skills.

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.

This open-source project, also known as **Deep Learning System** or **AI System (AISys)**, aims to explore and learn about the system design of artificial intelligence and deep learning. The project is centered around the full-stack content of AI systems that ZOMI has accumulated,整理, and built during his work. The goal is to collaborate with all friends who are interested in AI open-source projects to jointly promote learning and discussion.

SkyPilot is a framework for running LLMs, AI, and batch jobs on any cloud, offering maximum cost savings, highest GPU availability, and managed execution. SkyPilot abstracts away cloud infra burdens: - Launch jobs & clusters on any cloud - Easy scale-out: queue and run many jobs, automatically managed - Easy access to object stores (S3, GCS, R2) SkyPilot maximizes GPU availability for your jobs: * Provision in all zones/regions/clouds you have access to (the _Sky_), with automatic failover SkyPilot cuts your cloud costs: * Managed Spot: 3-6x cost savings using spot VMs, with auto-recovery from preemptions * Optimizer: 2x cost savings by auto-picking the cheapest VM/zone/region/cloud * Autostop: hands-free cleanup of idle clusters SkyPilot supports your existing GPU, TPU, and CPU workloads, with no code changes.

BentoML is an open-source model serving library for building performant and scalable AI applications with Python. It comes with everything you need for serving optimization, model packaging, and production deployment.

Council is an open-source platform designed for the rapid development and deployment of customized generative AI applications using teams of agents. It extends the LLM tool ecosystem by providing advanced control flow and scalable oversight for AI agents. Users can create sophisticated agents with predictable behavior by leveraging Council's powerful approach to control flow using Controllers, Filters, Evaluators, and Budgets. The framework allows for automated routing between agents, comparing, evaluating, and selecting the best results for a task. Council aims to facilitate packaging and deploying agents at scale on multiple platforms while enabling enterprise-grade monitoring and quality control.

LazyLLM is a low-code development tool for building complex AI applications with multiple agents. It assists developers in building AI applications at a low cost and continuously optimizing their performance. The tool provides a convenient workflow for application development and offers standard processes and tools for various stages of application development. Users can quickly prototype applications with LazyLLM, analyze bad cases with scenario task data, and iteratively optimize key components to enhance the overall application performance. LazyLLM aims to simplify the AI application development process and provide flexibility for both beginners and experts to create high-quality applications.

Spring AI Alibaba is an AI application framework for Java developers that seamlessly integrates with Alibaba Cloud QWen LLM services and cloud-native infrastructures. It provides features like support for various AI models, high-level AI agent abstraction, function calling, and RAG support. The framework aims to simplify the development, evaluation, deployment, and observability of AI native Java applications. It offers open-source framework and ecosystem integrations to support features like prompt template management, event-driven AI applications, and more.

AimRT is a basic runtime framework for modern robotics, developed in modern C++ with lightweight and easy deployment. It integrates research and development for robot applications in various deployment scenarios, providing debugging tools and observability support. AimRT offers a plug-in development interface compatible with ROS2, HTTP, Grpc, and other ecosystems for progressive system upgrades.

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.