AI Summer is a repository focused on providing workshops and resources for developing foundational skills in generative AI models and transformer models. The repository offers practical applications for inferencing and training, with a specific emphasis on understanding and utilizing advanced AI chat models like BingGPT. Participants are encouraged to engage in interactive programming environments, decide on projects to work on, and actively participate in discussions and breakout rooms. The workshops cover topics such as generative AI models, retrieval-augmented generation, building AI solutions, and fine-tuning models. The goal is to equip individuals with the necessary skills to work with AI technologies effectively and securely, both locally and in the cloud.

This repository introduces and helps organizations get started with building AI Apps and incorporating Large Language Models (LLMs) into them. The workshop covers topics such as prompt engineering, AI orchestration, and deploying AI apps. Participants will learn how to use Azure OpenAI, Langchain/ Semantic Kernel, Qdrant, and Azure AI Search to build intelligent applications.

Kai is an AI-enabled tool that simplifies the process of modernizing application source code to a new platform. It uses Large Language Models (LLMs) guided by static code analysis, along with data from Konveyor. This data provides insights into how the organization solved similar problems in the past, helping streamline and automate the code modernization process. Kai assists developers by providing suggestions and solutions to common problems through Retrieval Augmented Generation (RAG), working with LLMs using Konveyor analysis reports about the codebase and generating solutions based on previously solved examples.

LLMOps Duke AIPI is a course focused on operationalizing Large Language Models, teaching methodologies for developing applications using software development best practices with large language models. The course covers various topics such as generative AI concepts, setting up development environments, interacting with large language models, using local large language models, applied solutions with LLMs, extensibility using plugins and functions, retrieval augmented generation, introduction to Python web frameworks for APIs, DevOps principles, deploying machine learning APIs, LLM platforms, and final presentations. Students will learn to build, share, and present portfolios using Github, YouTube, and Linkedin, as well as develop non-linear life-long learning skills. Prerequisites include basic Linux and programming skills, with coursework available in Python or Rust. Additional resources and references are provided for further learning and exploration.

TI MINDMAP GPT is an AI-powered tool designed to assist cyber threat intelligence teams in quickly synthesizing and visualizing key information from various Threat Intelligence sources. The tool utilizes Large Language Models (LLMs) to transform lengthy content into concise, actionable summaries, going beyond mere text reduction to provide insightful encapsulations of crucial points and themes. Users can leverage their own LLM keys for personalized and efficient information processing, streamlining data analysis and enabling teams to focus on strategic decision-making.

AI2Apps is a visual IDE for building LLM-based AI agent applications, enabling developers to efficiently create AI agents through drag-and-drop, with features like design-to-development for rapid prototyping, direct packaging of agents into apps, powerful debugging capabilities, enhanced user interaction, efficient team collaboration, flexible deployment, multilingual support, simplified product maintenance, and extensibility through plugins.

SuperKnowa is a fast framework to build Enterprise RAG (Retriever Augmented Generation) Pipelines at Scale, powered by watsonx. It accelerates Enterprise Generative AI applications to get prod-ready solutions quickly on private data. The framework provides pluggable components for tackling various Generative AI use cases using Large Language Models (LLMs), allowing users to assemble building blocks to address challenges in AI-driven text generation. SuperKnowa is battle-tested from 1M to 200M private knowledge base & scaled to billions of retriever tokens.

doc2plan is a browser-based application that helps users create personalized learning plans by extracting content from documents. It features a Creator for manual or AI-assisted plan construction and a Viewer for interactive plan navigation. Users can extract chapters, key topics, generate quizzes, and track progress. The application includes AI-driven content extraction, quiz generation, progress tracking, plan import/export, assistant management, customizable settings, viewer chat with text-to-speech and speech-to-text support, and integration with various Retrieval-Augmented Generation (RAG) models. It aims to simplify the creation of comprehensive learning modules tailored to individual needs.

EngAce is a cutting-edge, generative AI-powered application revolutionizing Vietnamese English learning. It offers personalized learning experiences combining AI with comprehensive features. The repository contains source code, documentation, and resources for the app.

KitOps is a CNCF open standards project for packaging, versioning, and securely sharing AI/ML projects. It provides a unified solution for packaging, versioning, and managing assets in security-conscious enterprises, governments, and cloud operators. KitOps elevates AI artifacts to first-class, governed assets through ModelKits, which are tamper-proof, signable, and compatible with major container registries. The tool simplifies collaboration between data scientists, developers, and SREs, ensuring reliable and repeatable workflows for both development and operations. KitOps supports packaging for various types of models, including large language models, computer vision models, multi-modal models, predictive models, and audio models. It also facilitates compliance with the EU AI Act by offering tamper-proof, signable, and auditable ModelKits.

Arch is an intelligent Layer 7 gateway designed to protect, observe, and personalize LLM applications with APIs. It handles tasks like detecting and rejecting jailbreak attempts, calling backend APIs, disaster recovery, and observability. Built on Envoy Proxy, it offers features like function calling, prompt guardrails, traffic management, and standards-based observability. Arch aims to improve the speed, security, and personalization of generative AI applications.

Awesome AI Agent Failures is a community-curated repository documenting known failure modes for AI agents, real-world case studies, and techniques to avoid failures. It provides insights into common failure modes such as tool hallucination, response hallucination, goal misinterpretation, plan generation failures, incorrect tool use, verification & termination failures, and prompt injection. The repository also includes resources like research papers, industry resources, books, external resources, and related awesome lists to help AI engineers build more reliable AI agents by learning from production failures.

Stagehand is an AI web browsing framework that simplifies and extends web automation using three simple APIs: act, extract, and observe. It aims to provide a lightweight, configurable framework without complex abstractions, allowing users to automate web tasks reliably. The tool generates Playwright code based on atomic instructions provided by the user, enabling natural language-driven web automation. Stagehand is open source, maintained by the Browserbase team, and supports different models and model providers for flexibility in automation tasks.

**Advising App™** is a software solution created by Canyon GBS™ that includes a robust personal assistant designed to support student service professionals in their day-to-day roles. The assistant can help with research tasks, draft communication, language translation, content creation, student profile analysis, project planning, ideation, and much more. The software also includes a student service CRM designed to support the management of prospective and enrolled students. Key features of the CRM include record management, email and SMS, service management, caseload management, task management, interaction tracking, files and documents, and much more.

MonikA.I. submod is a project that enhances Monika After Story mod with various AI features. It utilizes multiple AI models for text generation, text-to-speech, speech-to-text, emotion detection, and NLI classification. Users can interact with Monika through chatbots, voice commands, and game actions. The project is compatible with MAS v0.12.15 and supports Windows, Linux, and MacOS. It offers a user-friendly installation process and detailed usage instructions for different AI functionalities.

Twinny is a free and open-source AI code completion plugin for Visual Studio Code and compatible editors. It integrates with various tools and frameworks, including Ollama, llama.cpp, oobabooga/text-generation-webui, LM Studio, LiteLLM, and Open WebUI. Twinny offers features such as fill-in-the-middle code completion, chat with AI about your code, customizable API endpoints, and support for single or multiline fill-in-middle completions. It is easy to install via the Visual Studio Code extensions marketplace and provides a range of customization options. Twinny supports both online and offline operation and conforms to the OpenAI API standard.

AI Summer is a repository focused on providing workshops and resources for developing foundational skills in generative AI models and transformer models. The repository offers practical applications for inferencing and training, with a specific emphasis on understanding and utilizing advanced AI chat models like BingGPT. Participants are encouraged to engage in interactive programming environments, decide on projects to work on, and actively participate in discussions and breakout rooms. The workshops cover topics such as generative AI models, retrieval-augmented generation, building AI solutions, and fine-tuning models. The goal is to equip individuals with the necessary skills to work with AI technologies effectively and securely, both locally and in the cloud.

CS7320-AI is a repository containing lecture materials, simple Python code examples, and assignments for the course CS 5/7320 Artificial Intelligence. The code examples cover various chapters of the textbook 'Artificial Intelligence: A Modern Approach' by Russell and Norvig. The repository focuses on basic AI concepts rather than advanced implementation techniques. It includes HOWTO guides for installing Python, working on assignments, and using AI with Python.

Dynamiq is an orchestration framework designed to streamline the development of AI-powered applications, specializing in orchestrating retrieval-augmented generation (RAG) and large language model (LLM) agents. It provides an all-in-one Gen AI framework for agentic AI and LLM applications, offering tools for multi-agent orchestration, document indexing, and retrieval flows. With Dynamiq, users can easily build and deploy AI solutions for various tasks.

Craftium is an open-source platform based on the Minetest voxel game engine and the Gymnasium and PettingZoo APIs, designed for creating fast, rich, and diverse single and multi-agent environments. It allows for connecting to Craftium's Python process, executing actions as keyboard and mouse controls, extending the Lua API for creating RL environments and tasks, and supporting client/server synchronization for slow agents. Craftium is fully extensible, extensively documented, modern RL API compatible, fully open source, and eliminates the need for Java. It offers a variety of environments for research and development in reinforcement learning.

Viglet Turing ES is an open source solution with Semantic Navigation and Chat bot features. It indexes all content in Solr as a search engine.

LLM-Learn-PK is a repository for testing various LLM and RAG tests. It serves as a learning platform where the creator experiments with different tests and learns in the process.

This repository is a collection of notes and code examples related to AI, covering topics such as Tokenization, Architectures, GGML, Llama.cpp, Position Embeddings, GPUs, Vector Databases, and Vision. It also includes in-progress work on Model Context Protocol (MCP) and Voice Activity Detection (VAD) for whisper.cpp. The repository offers exploration code for various AI-related concepts and tools like GGML, Llama.cpp, GPU technologies (CUDA, Kompute, Metal, OpenCL, ROCm, Vulkan), Word embeddings, Huggingface API, and Qdrant Vector Database in both Rust and Python.

CREDIT is an open software platform for training and deploying AI atmospheric prediction models. It offers fast models with flexible configuration options for input data and neural network architecture. The user-friendly interface enables quick setup and iteration. Developed by the MILES group and NSF National Center for Atmospheric Research, CREDIT combines advanced AI/ML with atmospheric science expertise. It provides a stable release with various models, training, and deployment options, with ongoing development. Detailed documentation is available for installation, training, deployment, config file interpretation, and API usage.

NanoLLM is a tool designed for optimized local inference for Large Language Models (LLMs) using HuggingFace-like APIs. It supports quantization, vision/language models, multimodal agents, speech, vector DB, and RAG. The tool aims to provide efficient and effective processing for LLMs on local devices, enhancing performance and usability for various AI applications.

This repository contains materials for the Microsoft Learn AI Fundamentals module. It covers the basics of artificial intelligence, machine learning, and data science. The content includes hands-on labs, interactive learning modules, and assessments to help learners understand key concepts and techniques in AI. Whether you are new to AI or looking to expand your knowledge, this module provides a comprehensive introduction to the fundamentals of AI.

Awesome AI Tools is a curated list of popular tools and resources for artificial intelligence enthusiasts. It includes a wide range of tools such as machine learning libraries, deep learning frameworks, data visualization tools, and natural language processing resources. Whether you are a beginner or an experienced AI practitioner, this repository aims to provide you with a comprehensive collection of tools to enhance your AI projects and research. Explore the list to discover new tools, stay updated with the latest advancements in AI technology, and find the right resources to support your AI endeavors.

The go2coding.github.io repository is a collection of resources for AI enthusiasts, providing information on AI products, open-source projects, AI learning websites, and AI learning frameworks. It aims to help users stay updated on industry trends, learn from community projects, access learning resources, and understand and choose AI frameworks. The repository also includes instructions for local and external deployment of the project as a static website, with details on domain registration, hosting services, uploading static web pages, configuring domain resolution, and a visual guide to the AI tool navigation website. Additionally, it offers a platform for AI knowledge exchange through a QQ group and promotes AI tools through a WeChat public account.

AI-Notes is a repository dedicated to practical applications of artificial intelligence and deep learning. It covers concepts such as data mining, machine learning, natural language processing, and AI. The repository contains Jupyter Notebook examples for hands-on learning and experimentation. It explores the development stages of AI, from narrow artificial intelligence to general artificial intelligence and superintelligence. The content delves into machine learning algorithms, deep learning techniques, and the impact of AI on various industries like autonomous driving and healthcare. The repository aims to provide a comprehensive understanding of AI technologies and their real-world applications.

Prompt Panel is a tool designed to accelerate the adoption of AI agents by providing a platform where users can run large language models across any inference provider, create custom agent plugins, and use their own data safely. The tool allows users to break free from walled-gardens and have full control over their models, conversations, and logic. With Prompt Panel, users can pair their data with any language model, online or offline, and customize the system to meet their unique business needs without any restrictions.

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.

AI Summer is a repository focused on providing workshops and resources for developing foundational skills in generative AI models and transformer models. The repository offers practical applications for inferencing and training, with a specific emphasis on understanding and utilizing advanced AI chat models like BingGPT. Participants are encouraged to engage in interactive programming environments, decide on projects to work on, and actively participate in discussions and breakout rooms. The workshops cover topics such as generative AI models, retrieval-augmented generation, building AI solutions, and fine-tuning models. The goal is to equip individuals with the necessary skills to work with AI technologies effectively and securely, both locally and in the cloud.