The IBM Power Systems AIX Collection provides modules to manage configurations and deployments of Power AIX systems, enabling workloads on Power platforms as part of an enterprise automation strategy through the Ansible ecosystem. It includes example best practices, requirements for AIX versions, Ansible, and Python, along with resources for documentation and contribution.

KDB.AI is a time-based vector database that allows developers to build scalable, reliable, and real-time applications by providing advanced search, recommendation, and personalization for Generative AI applications. It supports multiple index types, distance metrics, top-N and metadata filtered retrieval, as well as Python and REST interfaces. The repository contains samples demonstrating various use-cases such as temporal similarity search, document search, image search, recommendation systems, sentiment analysis, and more. KDB.AI integrates with platforms like ChatGPT, Langchain, and LlamaIndex. The setup steps require Unix terminal, Python 3.8+, and pip installed. Users can install necessary Python packages and run Jupyter notebooks to interact with the samples.

The Codebase Context Specification (CCS) project aims to standardize embedding contextual information within codebases to enhance understanding for both AI and human developers. It introduces a convention similar to `.env` and `.editorconfig` files but focused on documenting code for both AI and humans. By providing structured contextual metadata, collaborative documentation guidelines, and standardized context files, developers can improve code comprehension, collaboration, and development efficiency. The project includes a linter for validating context files and provides guidelines for using the specification with AI assistants. Tooling recommendations suggest creating memory systems, IDE plugins, AI model integrations, and agents for context creation and utilization. Future directions include integration with existing documentation systems, dynamic context generation, and support for explicit context overriding.

STRIDE GPT is an AI-powered threat modelling tool that leverages Large Language Models (LLMs) to generate threat models and attack trees for a given application based on the STRIDE methodology. Users provide application details, such as the application type, authentication methods, and whether the application is internet-facing or processes sensitive data. The model then generates its output based on the provided information. It features a simple and user-friendly interface, supports multi-modal threat modelling, generates attack trees, suggests possible mitigations for identified threats, and does not store application details. STRIDE GPT can be accessed via OpenAI API, Azure OpenAI Service, Google AI API, or Mistral API. It is available as a Docker container image for easy deployment.

AntSK is an AI knowledge base/agent built with .Net8+Blazor+SemanticKernel. It features a semantic kernel for accurate natural language processing, a memory kernel for continuous learning and knowledge storage, a knowledge base for importing and querying knowledge from various document formats, a text-to-image generator integrated with StableDiffusion, GPTs generation for creating personalized GPT models, API interfaces for integrating AntSK into other applications, an open API plugin system for extending functionality, a .Net plugin system for integrating business functions, real-time information retrieval from the internet, model management for adapting and managing different models from different vendors, support for domestic models and databases for operation in a trusted environment, and planned model fine-tuning based on llamafactory.

CSGHub Server is a part of the open source and reliable large model assets management platform - CSGHub. It focuses on management of models, datasets, and other LLM assets through REST API. Key features include creation and management of users and organizations, auto-tagging of model and dataset labels, search functionality, online preview of dataset files, content moderation for text and image, download of individual files, tracking of model and dataset activity data. The tool is extensible and customizable, supporting different git servers, flexible LFS storage system configuration, and content moderation options. The roadmap includes support for more Git servers, Git LFS, dataset online viewer, model/dataset auto-tag, S3 protocol support, model format conversion, and model one-click deploy. The project is licensed under Apache 2.0 and welcomes contributions.

Pathway is a Python data processing framework for analytics and AI pipelines over data streams. It's the ideal solution for real-time processing use cases like streaming ETL or RAG pipelines for unstructured data. Pathway comes with an **easy-to-use Python API** , allowing you to seamlessly integrate your favorite Python ML libraries. Pathway code is versatile and robust: **you can use it in both development and production environments, handling both batch and streaming data effectively**. The same code can be used for local development, CI/CD tests, running batch jobs, handling stream replays, and processing data streams. Pathway is powered by a **scalable Rust engine** based on Differential Dataflow and performs incremental computation. Your Pathway code, despite being written in Python, is run by the Rust engine, enabling multithreading, multiprocessing, and distributed computations. All the pipeline is kept in memory and can be easily deployed with **Docker and Kubernetes**. You can install Pathway with pip: `pip install -U pathway` For any questions, you will find the community and team behind the project on Discord.

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.

FeedGen is an open-source tool that uses Google Cloud's state-of-the-art Large Language Models (LLMs) to improve product titles, generate more comprehensive descriptions, and fill missing attributes in product feeds. It helps merchants and advertisers surface and fix quality issues in their feeds using Generative AI in a simple and configurable way. The tool relies on GCP's Vertex AI API to provide both zero-shot and few-shot inference capabilities on GCP's foundational LLMs. With few-shot prompting, users can customize the model's responses towards their own data, achieving higher quality and more consistent output. FeedGen is an Apps Script based application that runs as an HTML sidebar in Google Sheets, allowing users to optimize their feeds with ease.

Tara is a powerful node for ComfyUI that integrates Large Language Models (LLMs) to enhance and automate workflow processes. With Tara, you can create complex, intelligent workflows that refine and generate content, manage API keys, and seamlessly integrate various LLMs into your projects. It comprises nodes for handling OpenAI-compatible APIs, saving and loading API keys, composing multiple texts, and using predefined templates for OpenAI and Groq. Tara supports OpenAI and Grok models with plans to expand support to together.ai and Replicate. Users can install Tara via Git URL or ComfyUI Manager and utilize it for tasks like input guidance, saving and loading API keys, and generating text suitable for chaining in workflows.

GraphRAG Local Ollama is a repository that offers an adaptation of Microsoft's GraphRAG, customized to support local models downloaded using Ollama. It enables users to leverage local models with Ollama for large language models (LLMs) and embeddings, eliminating the need for costly OpenAPI models. The repository provides a simple setup process and allows users to perform question answering over private text corpora by building a graph-based text index and generating community summaries for closely-related entities. GraphRAG Local Ollama aims to improve the comprehensiveness and diversity of generated answers for global sensemaking questions over datasets.

This repository provides a deployment guide for utilizing Google Cloud's Generative AI tools in marketing scenarios. It includes step-by-step instructions, examples of crafting marketing materials, and supplementary Jupyter notebooks. The demos cover marketing insights, audience analysis, trendspotting, content search, content generation, and workspace integration. Users can access and visualize marketing data, analyze trends, improve search experience, and generate compelling content. The repository structure includes backend APIs, frontend code, sample notebooks, templates, and installation scripts.

LLM-Minutes-of-Meeting is a project showcasing NLP & LLM's capability to summarize long meetings and automate the task of delegating Minutes of Meeting(MoM) emails. It converts audio/video files to text, generates editable MoM, and aims to develop a real-time python web-application for meeting automation. The tool features keyword highlighting, topic tagging, export in various formats, user-friendly interface, and uses Celery for asynchronous processing. It is designed for corporate meetings, educational institutions, legal and medical fields, accessibility, and event coverage.

OpenDAN is an open source Personal AI OS that consolidates various AI modules for personal use. It empowers users to create powerful AI agents like assistants, tutors, and companions. The OS allows agents to collaborate, integrate with services, and control smart devices. OpenDAN offers features like rapid installation, AI agent customization, connectivity via Telegram/Email, building a local knowledge base, distributed AI computing, and more. It aims to simplify life by putting AI in users' hands. The project is in early stages with ongoing development and future plans for user and kernel mode separation, home IoT device control, and an official OpenDAN SDK release.

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.

Vikit.ai SDK is a software development kit that enables easy development of video generators using generative AI and other AI models. It serves as a langchain to orchestrate AI models and video editing tools. The SDK allows users to create videos from text prompts with background music and voice-over narration. It also supports generating composite videos from multiple text prompts. The tool requires Python 3.8+, specific dependencies, and tools like FFMPEG and ImageMagick for certain functionalities. Users can contribute to the project by following the contribution guidelines and standards provided.

The IBM Power Systems AIX Collection provides modules to manage configurations and deployments of Power AIX systems, enabling workloads on Power platforms as part of an enterprise automation strategy through the Ansible ecosystem. It includes example best practices, requirements for AIX versions, Ansible, and Python, along with resources for documentation and contribution.

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'.

DocsGPT is an open-source documentation assistant powered by GPT models. It simplifies the process of searching for information in project documentation by allowing developers to ask questions and receive accurate answers. With DocsGPT, users can say goodbye to manual searches and quickly find the information they need. The tool aims to revolutionize project documentation experiences and offers features like live previews, Discord community, guides, and contribution opportunities. It consists of a Flask app, Chrome extension, similarity search index creation script, and a frontend built with Vite and React. Users can quickly get started with DocsGPT by following the provided setup instructions and can contribute to its development by following the guidelines in the CONTRIBUTING.md file. The project follows a Code of Conduct to ensure a harassment-free community environment for all participants. DocsGPT is licensed under MIT and is built with LangChain.

Ollamac is a macOS app designed for interacting with Ollama models. It is optimized for macOS, allowing users to easily use any model from the Ollama library. The app features a user-friendly interface, chat archive for saving interactions, and real-time communication using HTTP streaming technology. Ollamac is open-source, enabling users to contribute to its development and enhance its capabilities. It requires macOS 14 or later and the Ollama system to be installed on the user's Mac with at least one Ollama model downloaded.

NPi is an open-source platform providing Tool-use APIs to empower AI agents with the ability to take action in the virtual world. It is currently under active development, and the APIs are subject to change in future releases. NPi offers a command line tool for installation and setup, along with a GitHub app for easy access to repositories. The platform also includes a Python SDK and examples like Calendar Negotiator and Twitter Crawler. Join the NPi community on Discord to contribute to the development and explore the roadmap for future enhancements.

DeFiChain is a blockchain platform dedicated to enabling decentralized finance with Bitcoin-grade security, strength, and immutability. It offers fast, intelligent, and transparent financial services accessible to everyone. DeFiChain has made significant modifications from Bitcoin Core, including moving to Proof-of-Stake, introducing a masternode model, supporting a community fund, anchoring to the Bitcoin blockchain, and enhancing decentralized financial transaction and opcode support. The platform is under active development with regular releases and contributions are welcomed.

doc-comments-ai is a tool designed to automatically generate code documentation using language models. It allows users to easily create documentation comment blocks for methods in various programming languages such as Python, Typescript, Javascript, Java, Rust, and more. The tool supports both OpenAI and local LLMs, ensuring data privacy and security. Users can generate documentation comments for methods in files, inline comments in method bodies, and choose from different models like GPT-3.5-Turbo, GPT-4, and Azure OpenAI. Additionally, the tool provides support for Treesitter integration and offers guidance on selecting the appropriate model for comprehensive documentation needs.

DevQualityEval is an evaluation benchmark and framework designed to compare and improve the quality of code generation of Language Model Models (LLMs). It provides developers with a standardized benchmark to enhance real-world usage in software development and offers users metrics and comparisons to assess the usefulness of LLMs for their tasks. The tool evaluates LLMs' performance in solving software development tasks and measures the quality of their results through a point-based system. Users can run specific tasks, such as test generation, across different programming languages to evaluate LLMs' language understanding and code generation capabilities.

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.