starlight-llms-txt is a tool designed to generate llms.txt files for training large language models on Starlight documentation websites. The project structure includes a Starlight plugin package in the packages/starlight-llms-txt/ directory and a documentation site in the docs/ directory for testing and demonstrating the plugin. The tool is licensed under MIT.

Describer is a tool that analyzes codebases using AI to generate architectural overviews, documentation, explanations, bug reports, and more. It scans all files in a directory and uses Google's Gemini AI to provide insights such as markdown architectural overviews, codebase summaries, code pattern analysis, codebase structure documentation, bug identification, and test idea generation. The tool respects .gitignore rules by default but allows users to include/exclude specific files or patterns for analysis.

Create TSI is a generative AI RAG toolkit that simplifies the process of creating AI Applications using LlamaIndex with low code. The toolkit leverages LLMs hosted by T-Systems on Open Telekom Cloud to generate bots, write agents, and customize them for specific use cases. It provides a Next.js-powered front-end for a chat interface, a Python FastAPI backend powered by llama-index package, and the ability to ingest and index user-supplied data for answering questions.

A Python script leveraging advanced language models to summarize webpages and youtube videos directly from URLs. It integrates with LangChain and ChatOllama for state-of-the-art summarization, providing detailed summaries for quick understanding of web-based documents. The tool offers a command-line interface for easy use and integration into workflows, with plans to add support for translating to different languages and streaming text output on gradio. It can also be used via a web UI using the gradio app. The script is dockerized for easy deployment and is open for contributions to enhance functionality and capabilities.

BESSER is a low-modeling low-code open-source platform funded by an FNR Pearl grant. It is built on B-UML, a Python-based interpretation of a 'Universal Modeling Language'. Users can specify their software application using B-UML and generate executable code for various applications like Django models or SQLAlchemy-compatible database structures. BESSER is available on PyPi and can be installed with pip. It supports popular Python IDEs and encourages contributions from the community.

This repository provides all the necessary items to build a Language Model from scratch, inspired by Karpathy's nanoGPT and Shakespeare generator. It includes data collection tools, data processing scripts, various models like BERT, GPT, and Seq-2-Seq, along with tokenizer and training files.

This repository contains the source code for the Apache Airflow website, including directories for archived documentation versions, landing pages, license templates, and the Sphinx theme. To work on the site locally, users need to install coreutils, Node.js, NPM, and HUGO, and run specific scripts provided in the repository. Contributors can refer to the contributor's guide for detailed instructions on how to contribute to the website.

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.

Bedrock Engineer is an autonomous software development agent application that utilizes Amazon Bedrock. It allows users to customize, create/edit files, execute commands, search the web, use a knowledge base, utilize multi-agents, generate images, and more. The tool provides an interactive chat interface with AI agents, file system operations, web search capabilities, project structure management, code analysis, code generation, data analysis, agent and tool customization, chat history management, and multi-language support. Users can select and customize agents, choose from various tools like file system operations, web search, Amazon Bedrock integration, and system command execution. Additionally, the tool offers features for website generation, connecting to design system data sources, AWS Step Functions ASL definition generation, diagram creation using natural language descriptions, and multi-language support.

The devdocs-to-llm repository is a work-in-progress tool that aims to convert documentation from DevDocs format to Long Language Model (LLM) format. This tool is designed to streamline the process of converting documentation for use with LLMs, making it easier for developers to leverage large language models for various tasks. By automating the conversion process, developers can quickly adapt DevDocs content for training and fine-tuning LLMs, enabling them to create more accurate and contextually relevant language models.

This repository contains a Rest-Backend for a Conversational Agent that allows embedding documents, semantic search, QA based on documents, and document processing with Large Language Models. It uses Aleph Alpha and OpenAI Large Language Models to generate responses to user queries, includes a vector database, and provides a REST API built with FastAPI. The project also features semantic search, secret management for API keys, installation instructions, and development guidelines for both backend and frontend components.

The Spring AI project provides a Spring-friendly API and abstractions for developing AI applications. It offers a portable client API for interacting with generative AI models, enabling developers to easily swap out implementations and access various models like OpenAI, Azure OpenAI, and HuggingFace. Spring AI also supports prompt engineering, providing classes and interfaces for creating and parsing prompts, as well as incorporating proprietary data into generative AI without retraining the model. This is achieved through Retrieval Augmented Generation (RAG), which involves extracting, transforming, and loading data into a vector database for use by AI models. Spring AI's VectorStore abstraction allows for seamless transitions between different vector database implementations.

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.

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.

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.

VectorVein is a no-code AI workflow software inspired by LangChain and langflow, aiming to combine the powerful capabilities of large language models and enable users to achieve intelligent and automated daily workflows through simple drag-and-drop actions. Users can create powerful workflows without the need for programming, automating all tasks with ease. The software allows users to define inputs, outputs, and processing methods to create customized workflow processes for various tasks such as translation, mind mapping, summarizing web articles, and automatic categorization of customer reviews.

starlight-llms-txt is a tool designed to generate llms.txt files for training large language models on Starlight documentation websites. The project structure includes a Starlight plugin package in the packages/starlight-llms-txt/ directory and a documentation site in the docs/ directory for testing and demonstrating the plugin. The tool is licensed under MIT.

GeekAI is an open-source AI assistant solution based on AI large language model API, featuring a complete system with ready-to-use front-end and back-end management, providing a seamless typing experience via Websocket. It integrates various pre-trained character applications like Xiaohongshu writing assistant, English translation master, Socrates, Confucius, Steve Jobs, and weekly report assistant. The tool supports multiple large language models from platforms like OpenAI, Azure, Wenxin Yanyan, Xunfei Xinghuo, and Tsinghua ChatGLM. Additionally, it includes MidJourney and Stable Diffusion AI drawing functionalities for creating various artworks such as text-based images, face swapping, and blending images. Users can utilize personal WeChat QR codes for payment without the need for enterprise payment channels, and the tool offers integrated payment options like Alipay and WeChat Pay with support for multiple membership packages and point card purchases. It also features a plugin API for developing powerful plugins using large language model functions, including built-in plugins for Weibo hot search, today's headlines, morning news, and AI drawing functions.

Amplication is a robust, open-source development platform designed to revolutionize the creation of scalable and secure .NET and Node.js applications. It automates backend applications development, ensuring consistency, predictability, and adherence to the highest standards with code that's built to scale. The user-friendly interface fosters seamless integration of APIs, data models, databases, authentication, and authorization. Built on a flexible, plugin-based architecture, Amplication allows effortless customization of the code and offers a diverse range of integrations. With a strong focus on collaboration, Amplication streamlines team-oriented development, making it an ideal choice for groups of all sizes, from startups to large enterprises. It enables users to concentrate on business logic while handling the heavy lifting of development. Experience the fastest way to develop .NET and Node.js applications with Amplication.

Plate is a rich-text editor framework designed for simplicity and efficiency. It consists of core plugin system, various plugin packages, primitive hooks and components, and pre-built components. Plate offers templates for different use cases like Notion-like template, Plate playground template, and Plate minimal template. Users can refer to the documentation for more information on Plate. Contributors are welcome to join the project by giving stars, making pull requests, or sharing plugins.

Transtation is an easy-to-use and powerful translation software for Android/Desktop based on Kotlin Multiplatform + Compose Multiplatform. It allows users to translate one item using multiple engines simultaneously, utilize advanced Large Language Models for translation, chat with LLMs for translation, translate long text, support plugin development, image translation, and screen translation. The application is designed for Chinese users and serves as a reference for learning Jetpack Compose or Compose Multiplatform. It features Kotlin Multiplatform, Compose Multiplatform, MVVM, Kotlin Coroutine, Flow, SqlDelight, synchronized translation with multiple engines, plugin development, and makes use of Kotlin language features like lazy loading, Coroutine, sealed classes, and reflection. The application gradually adapts to Android13 with features like setting application language separately and supporting Monet icon.

The ai-enhanced-audio-book repository contains AI-enhanced audio plugins developed using C++, JUCE, libtorch, RTNeural, and other libraries. It showcases neural networks learning to emulate guitar amplifiers through waveforms. Users can visit the official website for more information and obtain a copy of the book from the publisher Taylor and Francis/ Routledge/ Focal.

ChatGPT-WeChat is a personal assistant application that can be safely used on WeChat through enterprise WeChat without the risk of being banned. The project is open source and free, with no paid sections or external traffic operations except for advertising on the author's public account '积木成楼'. It supports various features such as secure usage on WeChat, multi-channel customer service message integration, proxy support, session management, rapid message response, voice and image messaging, drawing capabilities, private data storage, plugin support, and more. Users can also develop their own capabilities following the rules provided. The project is currently in development with stable versions available for use.

Coze Studio is an all-in-one AI agent development tool that offers the most convenient AI agent development environment, from development to deployment. It provides core technologies for AI agent development, complete app templates, and build frameworks. Coze Studio aims to simplify creating, debugging, and deploying AI agents through visual design and build tools, enabling powerful AI app development and customized business logic. The tool is developed using Golang for the backend, React + TypeScript for the frontend, and follows microservices architecture based on domain-driven design principles.

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.

AgentCloud is an open-source platform that enables companies to build and deploy private LLM chat apps, empowering teams to securely interact with their data. It comprises three main components: Agent Backend, Webapp, and Vector Proxy. To run this project locally, clone the repository, install Docker, and start the services. The project is licensed under the GNU Affero General Public License, version 3 only. Contributions and feedback are welcome from the community.

This framework generates fuzz targets for real-world `C`/`C++` projects with various Large Language Models (LLM) and benchmarks them via the `OSS-Fuzz` platform. It manages to successfully leverage LLMs to generate valid fuzz targets (which generate non-zero coverage increase) for 160 C/C++ projects. The maximum line coverage increase is 29% from the existing human-written targets.

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.

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.