The AI Engineering Hub is a repository that provides in-depth tutorials on LLMs and RAGs, real-world AI agent applications, and examples to implement, adapt, and scale in projects. It caters to beginners, practitioners, and researchers, offering resources for all skill levels to experiment and succeed in AI engineering.

PydanticAI is a Python agent framework designed to make it less painful to build production grade applications with Generative AI. It is built by the Pydantic Team and supports various AI models like OpenAI, Anthropic, Gemini, Ollama, Groq, and Mistral. PydanticAI seamlessly integrates with Pydantic Logfire for real-time debugging, performance monitoring, and behavior tracking of LLM-powered applications. It is type-safe, Python-centric, and offers structured responses, dependency injection system, and streamed responses. PydanticAI is in early beta, offering a Python-centric design to apply standard Python best practices in AI-driven projects.

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.

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.

The AI Tutor RAG System repository contains Jupyter notebooks supporting the RAG course, focusing on enhancing AI models with retrieval-based methods. It covers foundational and advanced concepts in retrieval-augmented generation, including data retrieval techniques, model integration with retrieval systems, and practical applications of RAG in real-world scenarios.

Koog is a Kotlin-based framework for building and running AI agents entirely in idiomatic Kotlin. It allows users to create agents that interact with tools, handle complex workflows, and communicate with users. Key features include pure Kotlin implementation, MCP integration, embedding capabilities, custom tool creation, ready-to-use components, intelligent history compression, powerful streaming API, persistent agent memory, comprehensive tracing, flexible graph workflows, modular feature system, scalable architecture, and multiplatform support.

Agentic is a lightweight and flexible Python library for building multi-agent systems. It provides a simple and intuitive API for creating and managing agents, defining their behaviors, and simulating interactions in a multi-agent environment. With Agentic, users can easily design and implement complex agent-based models to study emergent behaviors, social dynamics, and decentralized decision-making processes. The library supports various agent architectures, communication protocols, and simulation scenarios, making it suitable for a wide range of research and educational applications in the fields of artificial intelligence, machine learning, social sciences, and robotics.

This repository is a comprehensive collection of practical examples, tutorials, and recipes for building powerful LLM-powered applications. From simple chatbots to advanced AI agents, these projects serve as a guide for developers working with various AI frameworks and tools. Powered by Nebius AI Studio - your one-stop platform for building and deploying AI applications.

Awesome-AI-Security is a curated list of resources for AI security, including tools, research papers, articles, and tutorials. It aims to provide a comprehensive overview of the latest developments in securing AI systems and preventing vulnerabilities. The repository covers topics such as adversarial attacks, privacy protection, model robustness, and secure deployment of AI applications. Whether you are a researcher, developer, or security professional, this collection of resources will help you stay informed and up-to-date in the rapidly evolving field of AI security.

AI Manus is a general-purpose AI Agent system that supports running various tools and operations in a sandbox environment. It offers deployment with minimal dependencies, supports multiple tools like Terminal, Browser, File, Web Search, and messaging tools, allocates separate sandboxes for tasks, manages session history, supports stopping and interrupting conversations, file upload and download, and is multilingual. The system also provides user login and authentication. The project primarily relies on Docker for development and deployment, with model capability requirements and recommended Deepseek and GPT models.

The Alignment Handbook provides robust training recipes for continuing pretraining and aligning language models with human and AI preferences. It includes techniques such as continued pretraining, supervised fine-tuning, reward modeling, rejection sampling, and direct preference optimization (DPO). The handbook aims to fill the gap in public resources on training these models, collecting data, and measuring metrics for optimal downstream performance.

The ai-workshop-code repository contains code examples and tutorials for various artificial intelligence concepts and algorithms. It serves as a practical resource for individuals looking to learn and implement AI techniques in their projects. The repository covers a wide range of topics, including machine learning, deep learning, natural language processing, computer vision, and reinforcement learning. By exploring the code and following the tutorials, users can gain hands-on experience with AI technologies and enhance their understanding of how these algorithms work in practice.

Disciplined AI Software Development is a comprehensive repository that provides guidelines and best practices for developing AI software in a disciplined manner. It covers topics such as project organization, code structure, documentation, testing, and deployment strategies to ensure the reliability, scalability, and maintainability of AI applications. The repository aims to help developers and teams navigate the complexities of AI development by offering practical advice and examples to follow.

NodeTool is a platform designed for AI enthusiasts, developers, and creators, providing a visual interface to access a variety of AI tools and models. It simplifies access to advanced AI technologies, offering resources for content creation, data analysis, automation, and more. With features like a visual editor, seamless integration with leading AI platforms, model manager, and API integration, NodeTool caters to both newcomers and experienced users in the AI field.

VoltAgent is an open-source TypeScript framework designed for building and orchestrating AI agents. It simplifies the development of AI agent applications by providing modular building blocks, standardized patterns, and abstractions. Whether you're creating chatbots, virtual assistants, automated workflows, or complex multi-agent systems, VoltAgent handles the underlying complexity, allowing developers to focus on defining their agents' capabilities and logic. The framework offers ready-made building blocks, such as the Core Engine, Multi-Agent Systems, Workflow Engine, Extensible Packages, Tooling & Integrations, Data Retrieval & RAG, Memory management, LLM Compatibility, and a Developer Ecosystem. VoltAgent empowers developers to build sophisticated AI applications faster and more reliably, avoiding repetitive setup and the limitations of simpler tools.

FoundationaLLM is a platform designed for deploying, scaling, securing, and governing generative AI in enterprises. It allows users to create AI agents grounded in enterprise data, integrate REST APIs, experiment with various large language models, centrally manage AI agents and their assets, deploy scalable vectorization data pipelines, enable non-developer users to create their own AI agents, control access with role-based access controls, and harness capabilities from Azure AI and Azure OpenAI. The platform simplifies integration with enterprise data sources, provides fine-grain security controls, scalability, extensibility, and addresses the challenges of delivering enterprise copilots or AI agents.

The AI Engineering Hub is a repository that provides in-depth tutorials on LLMs and RAGs, real-world AI agent applications, and examples to implement, adapt, and scale in projects. It caters to beginners, practitioners, and researchers, offering resources for all skill levels to experiment and succeed in AI engineering.

Generative AI JS is a JavaScript library that provides tools for creating generative art and music using artificial intelligence techniques. It allows users to generate unique and creative content by leveraging machine learning models. The library includes functions for generating images, music, and text based on user input and preferences. With Generative AI JS, users can explore the intersection of art and technology, experiment with different creative processes, and create dynamic and interactive content for various applications.

Chrome AI is a Vercel AI provider for Chrome's built-in model (Gemini Nano). It allows users to create language models using Chrome's AI capabilities. The tool is under development and may contain errors and frequent changes. Users can install the ChromeAI provider module and use it to generate text, stream text, and generate objects. To enable AI in Chrome, users need to have Chrome version 127 or greater and turn on specific flags. The tool is designed for developers and researchers interested in experimenting with Chrome's built-in AI features.

ZetaForge is an open-source AI platform designed for rapid development of advanced AI and AGI pipelines. It allows users to assemble reusable, customizable, and containerized Blocks into highly visual AI Pipelines, enabling rapid experimentation and collaboration. With ZetaForge, users can work with AI technologies in any programming language, easily modify and update AI pipelines, dive into the code whenever needed, utilize community-driven blocks and pipelines, and share their own creations. The platform aims to accelerate the development and deployment of advanced AI solutions through its user-friendly interface and community support.

Atidraw is a web application that allows users to create, enhance, and share drawings using Cloudflare R2 and Cloudflare AI. It features intuitive drawing with signature_pad, AI-powered enhancements such as alt text generation and image generation with Stable Diffusion, global storage on Cloudflare R2, flexible authentication options, and high-performance server-side rendering on Cloudflare Pages. Users can deploy Atidraw with zero configuration on their Cloudflare account using NuxtHub.

The 'Free LLM API resources' repository provides a comprehensive list of services offering free access or credits for API-based LLM usage. It includes various providers with details on model names, limits, and notes. Users can find information on legitimate services and their respective usage restrictions to leverage LLM capabilities without incurring costs. The repository aims to assist developers and researchers in accessing AI models for experimentation, development, and learning purposes.

The 'Generative AI with JavaScript' repository is a comprehensive resource hub for JavaScript developers interested in delving into the world of Generative AI. It provides code samples, tutorials, and resources from a video series, offering best practices and tips to enhance AI skills. The repository covers the basics of generative AI, guides on building AI applications using JavaScript, from local development to deployment on Azure, and scaling AI models. It is a living repository with continuous updates, making it a valuable resource for both beginners and experienced developers looking to explore AI with JavaScript.

The react-native-ai repository allows users to run Large Language Models (LLM) locally in a React Native app using the Universal MLC LLM Engine with compatibility for Vercel AI SDK. Please note that this project is experimental and not ready for production. The repository is licensed under MIT and was created with create-react-native-library.

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.