Wa-OpenAI is a WhatsApp chatbot powered by OpenAI's ChatGPT and DALL-E models, allowing users to interact with AI for text generation and image creation. Users can easily integrate the bot into their WhatsApp conversations using commands like '/ai' and '/img'. The tool requires setting up an OpenAI API key and can be installed on RDP/Windows or Termux environments. It provides a convenient way to leverage AI capabilities within WhatsApp chats, offering a seamless experience for generating text and images.

Backend.AI Web UI is a user-friendly web and app interface designed to make AI accessible for end-users, DevOps, and SysAdmins. It provides features for session management, inference service management, pipeline management, storage management, node management, statistics, configurations, license checking, plugins, help & manuals, kernel management, user management, keypair management, manager settings, proxy mode support, service information, and integration with the Backend.AI Web Server. The tool supports various devices, offers a built-in websocket proxy feature, and allows for versatile usage across different platforms. Users can easily manage resources, run environment-supported apps, access a web-based terminal, use Visual Studio Code editor, manage experiments, set up autoscaling, manage pipelines, handle storage, monitor nodes, view statistics, configure settings, and more.

ORBIT (Open Retrieval-Based Inference Toolkit) is a middleware platform that provides a unified API for AI inference. It acts as a central gateway, allowing you to connect various local and remote AI models with your private data sources like SQL databases, vector stores, and local files. ORBIT uses a flexible adapter architecture to connect your data to AI models, creating specialized 'agents' for specific tasks. It supports scenarios like Knowledge Base Q&A and Chat with Your SQL Database, enabling users to interact with AI models seamlessly. The tool offers a RESTful API for programmatic access and includes features like authentication, API key management, system prompts, health monitoring, and file management. ORBIT is designed to streamline AI inference tasks and facilitate interactions between users and AI models.

Backend.AI is a streamlined, container-based computing cluster platform that hosts popular computing/ML frameworks and diverse programming languages, with pluggable heterogeneous accelerator support including CUDA GPU, ROCm GPU, TPU, IPU and other NPUs. It allocates and isolates the underlying computing resources for multi-tenant computation sessions on-demand or in batches with customizable job schedulers with its own orchestrator. All its functions are exposed as REST/GraphQL/WebSocket APIs.

PasteMax is a modern file viewer application designed for developers to easily navigate, search, and copy code from repositories. It provides features such as file tree navigation, token counting, search capabilities, selection management, sorting options, dark mode, binary file detection, and smart file exclusion. Built with Electron, React, and TypeScript, PasteMax is ideal for pasting code into ChatGPT or other language models. Users can download the application or build it from source, and customize file exclusions. Troubleshooting steps are provided for common issues, and contributions to the project are welcome under the MIT License.

AI Terminal is a Tauri + Angular terminal application with integrated AI capabilities, offering natural language command interpretation, an integrated AI assistant, command history and auto-completion, and cross-platform support (macOS, Windows, Linux). The modern UI is built with Tauri and Angular. The tool requires Node.js 18+, Rust and Cargo, and Ollama for AI features. Users can build a universal binary for macOS, install the tool using Homebrew, and use Ollama to download specific models. Contributions are welcome under the MIT License.

mcpd is a tool developed by Mozilla AI to declaratively manage Model Context Protocol (MCP) servers, enabling consistent interface for defining and running tools across different environments. It bridges the gap between local development and enterprise deployment by providing secure secrets management, declarative configuration, and seamless environment promotion. mcpd simplifies the developer experience by offering zero-config tool setup, language-agnostic tooling, version-controlled configuration files, enterprise-ready secrets management, and smooth transition from local to production environments.

AI Commits is a plugin for IntelliJ-based IDEs and Android Studio that generates commit messages using git diff and OpenAI. It offers features such as generating commit messages from diff using OpenAI API, computing diff only from selected files and lines in the commit dialog, creating custom prompts for commit message generation, using predefined variables and hints to customize prompts, choosing any of the models available in OpenAI API, setting OpenAI network proxy, and setting custom OpenAI compatible API endpoint.

PentAGI is an innovative tool for automated security testing that leverages cutting-edge artificial intelligence technologies. It is designed for information security professionals, researchers, and enthusiasts who need a powerful and flexible solution for conducting penetration tests. The tool provides secure and isolated operations in a sandboxed Docker environment, fully autonomous AI-powered agent for penetration testing steps, a suite of 20+ professional security tools, smart memory system for storing research results, web intelligence for gathering information, integration with external search systems, team delegation system, comprehensive monitoring and reporting, modern interface, API integration, persistent storage, scalable architecture, self-hosted solution, flexible authentication, and quick deployment through Docker Compose.

Melodisco is an AI music player that allows users to listen to music and manage playlists. It provides a user-friendly interface for music playback and organization. Users can deploy Melodisco with Vercel or Docker for easy setup. Local development instructions are provided for setting up the project environment. The project credits various tools and libraries used in its development, such as Next.js, Tailwind CSS, and Stripe. Melodisco is a versatile tool for music enthusiasts looking for an AI-powered music player with features like authentication, payment integration, and multi-language support.

Talk With Gemini is a web application that allows users to deploy their private Gemini application for free with one click. It supports Gemini Pro and Gemini Pro Vision models. The application features talk mode for direct communication with Gemini, visual recognition for understanding picture content, full Markdown support, automatic compression of chat records, privacy and security with local data storage, well-designed UI with responsive design, fast loading speed, and multi-language support. The tool is designed to be user-friendly and versatile for various deployment options and language preferences.

Aim is a command-line tool for downloading and uploading files with resume support. It supports various protocols including HTTP, FTP, SFTP, SSH, and S3. Aim features an interactive mode for easy navigation and selection of files, as well as the ability to share folders over HTTP for easy access from other devices. Additionally, it offers customizable progress indicators and output formats, and can be integrated with other commands through piping. Aim can be installed via pre-built binaries or by compiling from source, and is also available as a Docker image for platform-independent usage.

dbt-llm-agent is an LLM-powered agent designed for interacting with dbt projects. It offers features such as question answering, documentation generation, agentic model interpretation, Postgres integration with pgvector, dbt model selection, question tracking, and upcoming Slack integration. The agent utilizes dbt project parsing, PostgreSQL with pgvector, model selection syntax, large language models like GPT-4, and question tracking to provide its functionalities. Users can set up the agent by checking Python version, cloning the repository, installing dependencies, setting up PostgreSQL with pgvector, configuring environment variables, and initializing the database schema. The agent can be initialized in Cloud Mode, Local Mode, or Source Code Mode to load project metadata. Once set up, users can work with model documentation, ask questions, provide feedback, list models, get detailed model information, and contribute to the project.

Aiogram bot template is a boilerplate for creating Telegram bots using Aiogram framework. It provides a solid foundation for building robust and scalable bots with a focus on code organization, database integration, and localization.

model-compose is an open-source, declarative workflow orchestrator inspired by docker-compose. It lets you define and run AI model pipelines using simple YAML files. Effortlessly connect external AI services or run local AI models within powerful, composable workflows. Features include declarative design, multi-workflow support, modular components, flexible I/O routing, streaming mode support, and more. It supports running workflows locally or serving them remotely, Docker deployment, environment variable support, and provides a CLI interface for managing AI workflows.

AIGNE DocSmith is a powerful AI-driven documentation generation tool that automates the creation of detailed, structured, and multi-language documentation directly from source code. It intelligently analyzes codebase to generate a comprehensive document structure, populates content with high-quality AI-powered generation, supports seamless translation into 12+ languages, integrates with AIGNE Hub for large language models, offers Discuss Kit publishing, automatically updates documentation with source code changes, and allows for individual document optimization.

This repository contains notebooks, code samples, sample apps, and other resources that demonstrate how to use, develop and manage generative AI workflows using Generative AI on Google Cloud, powered by Vertex AI. For more Vertex AI samples, please visit the Vertex AI samples Github repository.

Aila Desktop Application is a powerful tool that integrates multiple leading AI models into a single desktop application. It allows users to interact with various AI models simultaneously, providing diverse responses and insights to their inquiries. With its user-friendly interface and customizable features, Aila empowers users to engage with AI seamlessly and efficiently. Whether you're a researcher, student, or professional, Aila can enhance your AI interactions and streamline your workflow.

This course has 18 lessons. Each lesson covers its own topic so start wherever you like! Lessons are labeled either "Learn" lessons explaining a Generative AI concept or "Build" lessons that explain a concept and code examples in both **Python** and **TypeScript** when possible. Each lesson also includes a "Keep Learning" section with additional learning tools. **What You Need** * Access to the Azure OpenAI Service **OR** OpenAI API - _Only required to complete coding lessons_ * Basic knowledge of Python or Typescript is helpful - *For absolute beginners check out these Python and TypeScript courses. * A Github account to fork this entire repo to your own GitHub account We have created a **Course Setup** lesson to help you with setting up your development environment. Don't forget to star (🌟) this repo to find it easier later. ## 🧠 Ready to Deploy? If you are looking for more advanced code samples, check out our collection of Generative AI Code Samples in both **Python** and **TypeScript**. ## 🗣️ Meet Other Learners, Get Support Join our official AI Discord server to meet and network with other learners taking this course and get support. ## 🚀 Building a Startup? Sign up for Microsoft for Startups Founders Hub to receive **free OpenAI credits** and up to **$150k towards Azure credits to access OpenAI models through Azure OpenAI Services**. ## 🙏 Want to help? Do you have suggestions or found spelling or code errors? Raise an issue or Create a pull request ## 📂 Each lesson includes: * A short video introduction to the topic * A written lesson located in the README * Python and TypeScript code samples supporting Azure OpenAI and OpenAI API * Links to extra resources to continue your learning ## 🗃️ Lessons | | Lesson Link | Description | Additional Learning | | :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ | | 00 | Course Setup | **Learn:** How to Setup Your Development Environment | Learn More | | 01 | Introduction to Generative AI and LLMs | **Learn:** Understanding what Generative AI is and how Large Language Models (LLMs) work. | Learn More | | 02 | Exploring and comparing different LLMs | **Learn:** How to select the right model for your use case | Learn More | | 03 | Using Generative AI Responsibly | **Learn:** How to build Generative AI Applications responsibly | Learn More | | 04 | Understanding Prompt Engineering Fundamentals | **Learn:** Hands-on Prompt Engineering Best Practices | Learn More | | 05 | Creating Advanced Prompts | **Learn:** How to apply prompt engineering techniques that improve the outcome of your prompts. | Learn More | | 06 | Building Text Generation Applications | **Build:** A text generation app using Azure OpenAI | Learn More | | 07 | Building Chat Applications | **Build:** Techniques for efficiently building and integrating chat applications. | Learn More | | 08 | Building Search Apps Vector Databases | **Build:** A search application that uses Embeddings to search for data. | Learn More | | 09 | Building Image Generation Applications | **Build:** A image generation application | Learn More | | 10 | Building Low Code AI Applications | **Build:** A Generative AI application using Low Code tools | Learn More | | 11 | Integrating External Applications with Function Calling | **Build:** What is function calling and its use cases for applications | Learn More | | 12 | Designing UX for AI Applications | **Learn:** How to apply UX design principles when developing Generative AI Applications | Learn More | | 13 | Securing Your Generative AI Applications | **Learn:** The threats and risks to AI systems and methods to secure these systems. | Learn More | | 14 | The Generative AI Application Lifecycle | **Learn:** The tools and metrics to manage the LLM Lifecycle and LLMOps | Learn More | | 15 | Retrieval Augmented Generation (RAG) and Vector Databases | **Build:** An application using a RAG Framework to retrieve embeddings from a Vector Databases | Learn More | | 16 | Open Source Models and Hugging Face | **Build:** An application using open source models available on Hugging Face | Learn More | | 17 | AI Agents | **Build:** An application using an AI Agent Framework | Learn More | | 18 | Fine-Tuning LLMs | **Learn:** The what, why and how of fine-tuning LLMs | Learn More |

Cog-comfyui allows users to run ComfyUI workflows on Replicate. ComfyUI is a visual programming tool for creating and sharing generative art workflows. With cog-comfyui, users can access a variety of pre-trained models and custom nodes to create their own unique artworks. The tool is easy to use and does not require any coding experience. Users simply need to upload their API JSON file and any necessary input files, and then click the "Run" button. Cog-comfyui will then generate the output image or video file.

Notes on AI state of the art, with a focus on generative and large language models. These are the "raw materials" for the https://lspace.swyx.io/ newsletter. This repo used to be called https://github.com/sw-yx/prompt-eng, but was renamed because Prompt Engineering is Overhyped. This is now an AI Engineering notes repo.

This repository contains example code to demonstrate how to connect MATLAB to the OpenAI™ Chat Completions API (which powers ChatGPT™) as well as OpenAI Images API (which powers DALL·E™). This allows you to leverage the natural language processing capabilities of large language models directly within your MATLAB environment.

xef.ai is a one-stop library designed to bring the power of modern AI to applications and services. It offers integration with Large Language Models (LLM), image generation, and other AI services. The library is packaged in two layers: core libraries for basic AI services integration and integrations with other libraries. xef.ai aims to simplify the transition to modern AI for developers by providing an idiomatic interface, currently supporting Kotlin. Inspired by LangChain and Hugging Face, xef.ai may transmit source code and user input data to third-party services, so users should review privacy policies and take precautions. Libraries are available in Maven Central under the `com.xebia` group, with `xef-core` as the core library. Developers can add these libraries to their projects and explore examples to understand usage.

CushyStudio is a generative AI platform designed for creatives of any level to effortlessly create stunning images, videos, and 3D models. It offers CushyApps, a collection of visual tools tailored for different artistic tasks, and CushyKit, an extensive toolkit for custom apps development and task automation. Users can dive into the AI revolution, unleash their creativity, share projects, and connect with a vibrant community. The platform aims to simplify the AI art creation process and provide a user-friendly environment for designing interfaces, adding custom logic, and accessing various tools.

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.