Moxin is an AI LLM client written in Rust to demonstrate the functionality of the Robius framework for multi-platform application development. It is currently in early stages of development and not fully functional. The tool supports building and running on macOS and Linux systems, with packaging options available for distribution. Users can install the required WasmEdge WASM runtime and dependencies to build and run Moxin. Packaging for distribution includes generating `.deb` Debian packages, AppImage, and pacman installation packages for Linux, as well as `.app` bundles and `.dmg` disk images for macOS. The macOS app is not signed, leading to a warning on installation, which can be resolved by removing the quarantine attribute from the installed app.

Moly is an AI LLM client written in Rust, showcasing the capabilities of the Makepad UI toolkit and Project Robius, a framework for multi-platform application development in Rust. It is currently in beta, allowing users to build and run Moly on macOS, Linux, and Windows. The tool provides packaging support for different platforms, such as `.app`, `.dmg`, `.deb`, AppImage, pacman, and `.exe` (NSIS). Users can easily set up WasmEdge using `moly-runner` and leverage `cargo` commands to build and run Moly. Additionally, Moly offers pre-built releases for download and supports packaging for distribution on Linux, Windows, and macOS.

Pieces CLI for Developers is a comprehensive command-line interface (CLI) tool designed to interact seamlessly with Pieces OS. It provides functionalities such as asset management, application interaction, and integration with various Pieces OS features. The tool is compatible with Windows 10 or greater, Mac, and Windows operating systems. Users can install the tool by running 'pip install pieces-cli' or 'brew install pieces-cli'. After installation, users can access the tool's functionalities through the terminal by using the 'pieces' command followed by subcommands and options. The tool supports various commands, which can be found in the documentation. Developers can contribute to the project by forking and cloning the repository, setting up a virtual environment, installing dependencies with poetry, and running test cases with pytest and coverage.

Anterion is an open-source AI software engineer that extends the capabilities of `SWE-agent` to plan and execute open-ended engineering tasks, with a frontend inspired by `OpenDevin`. It is designed to help users fix bugs and prototype ideas with ease. Anterion is equipped with easy deployment and a user-friendly interface, making it accessible to users of all skill levels.

AI for the command line, built for pipelines. LLM based AI is really good at interpreting the output of commands and returning the results in CLI friendly text formats like Markdown. Mods is a simple tool that makes it super easy to use AI on the command line and in your pipelines. Mods works with OpenAI, Groq, Azure OpenAI, and LocalAI To get started, install Mods and check out some of the examples below. Since Mods has built-in Markdown formatting, you may also want to grab Glow to give the output some _pizzazz_.

Termax is an LLM agent in your terminal that converts natural language to commands. It is featured by: - Personalized Experience: Optimize the command generation with RAG. - Various LLMs Support: OpenAI GPT, Anthropic Claude, Google Gemini, Mistral AI, and more. - Shell Extensions: Plugin with popular shells like `zsh`, `bash` and `fish`. - Cross Platform: Able to run on Windows, macOS, and Linux.

Tiledesk is an open-source live chat platform with integrated chatbots written in Node.js and Express. It is designed to be a multi-channel platform for web, Android, and iOS, and it can be used to increase sales or provide post-sales customer service. Tiledesk's chatbot technology allows for automation of conversations, and it also provides APIs and webhooks for connecting external applications. Additionally, it offers a marketplace for apps and features such as CRM, ticketing, and data export.

Garak is a free tool that checks if a Large Language Model (LLM) can be made to fail in a way that is undesirable. It probes for hallucination, data leakage, prompt injection, misinformation, toxicity generation, jailbreaks, and many other weaknesses. Garak's a free tool. We love developing it and are always interested in adding functionality to support applications.

ML-Bench is a tool designed to evaluate large language models and agents for machine learning tasks on repository-level code. It provides functionalities for data preparation, environment setup, usage, API calling, open source model fine-tuning, and inference. Users can clone the repository, load datasets, run ML-LLM-Bench, prepare data, fine-tune models, and perform inference tasks. The tool aims to facilitate the evaluation of language models and agents in the context of machine learning tasks on code repositories.

1.5-Pints is a repository that provides a recipe to pre-train models in 9 days, aiming to create AI assistants comparable to Apple OpenELM and Microsoft Phi. It includes model architecture, training scripts, and utilities for 1.5-Pints and 0.12-Pint developed by Pints.AI. The initiative encourages replication, experimentation, and open-source development of Pint by sharing the model's codebase and architecture. The repository offers installation instructions, dataset preparation scripts, model training guidelines, and tools for model evaluation and usage. Users can also find information on finetuning models, converting lit models to HuggingFace models, and running Direct Preference Optimization (DPO) post-finetuning. Additionally, the repository includes tests to ensure code modifications do not disrupt the existing functionality.

CodeSpin.AI is a set of open-source code generation tools that leverage large language models (LLMs) to automate coding tasks. With CodeSpin, you can generate code in various programming languages, including Python, JavaScript, Java, and C++, by providing natural language prompts. CodeSpin offers a range of features to enhance code generation, such as custom templates, inline prompting, and the ability to use ChatGPT as an alternative to API keys. Additionally, CodeSpin provides options for regenerating code, executing code in prompt files, and piping data into the LLM for processing. By utilizing CodeSpin, developers can save time and effort in coding tasks, improve code quality, and explore new possibilities in code generation.

DeepDanbooru is an anime-style girl image tag estimation system written in Python. It allows users to estimate images using a live demo site. The tool requires specific packages to be installed and provides a structured dataset for training projects. Users can create training projects, download tags, filter datasets, and start training to estimate tags for images. The tool uses a specific dataset structure and project structure to facilitate the training process.

Log10 is a one-line Python integration to manage your LLM data. It helps you log both closed and open-source LLM calls, compare and identify the best models and prompts, store feedback for fine-tuning, collect performance metrics such as latency and usage, and perform analytics and monitor compliance for LLM powered applications. Log10 offers various integration methods, including a python LLM library wrapper, the Log10 LLM abstraction, and callbacks, to facilitate its use in both existing production environments and new projects. Pick the one that works best for you. Log10 also provides a copilot that can help you with suggestions on how to optimize your prompt, and a feedback feature that allows you to add feedback to your completions. Additionally, Log10 provides prompt provenance, session tracking and call stack functionality to help debug prompt chains. With Log10, you can use your data and feedback from users to fine-tune custom models with RLHF, and build and deploy more reliable, accurate and efficient self-hosted models. Log10 also supports collaboration, allowing you to create flexible groups to share and collaborate over all of the above features.

gpt-cli is a command-line interface tool for interacting with various chat language models like ChatGPT, Claude, and others. It supports model customization, usage tracking, keyboard shortcuts, multi-line input, markdown support, predefined messages, and multiple assistants. Users can easily switch between different assistants, define custom assistants, and configure model parameters and API keys in a YAML file for easy customization and management.

Sandbox is an open-source cloud-based code editing environment with custom AI code autocompletion and real-time collaboration. It consists of a frontend built with Next.js, TailwindCSS, Shadcn UI, Clerk, Monaco, and Liveblocks, and a backend with Express, Socket.io, Cloudflare Workers, D1 database, R2 storage, Workers AI, and Drizzle ORM. The backend includes microservices for database, storage, and AI functionalities. Users can run the project locally by setting up environment variables and deploying the containers. Contributions are welcome following the commit convention and structure provided in the repository.

This repository contains Jupyter-based tutorials for NLP, ML, AI in Python for classes in Computational Linguistics, Natural Language Processing (NLP), Machine Learning (ML), and Artificial Intelligence (AI) at Indiana University.

Open Parse is a Python library for visually discerning document layouts and chunking them effectively. It is designed to fill the gap in open-source libraries for handling complex documents. Unlike text splitting, which converts a file to raw text and slices it up, Open Parse visually analyzes documents for superior LLM input. It also supports basic markdown for parsing headings, bold, and italics, and has high-precision table support, extracting tables into clean Markdown formats with accuracy that surpasses traditional tools. Open Parse is extensible, allowing users to easily implement their own post-processing steps. It is also intuitive, with great editor support and completion everywhere, making it easy to use and learn.

The MoonshotAI-Cookbook provides example code and guides for accomplishing common tasks with the MoonshotAI API. To run these examples, you'll need an MoonshotAI account and associated API key. Most code examples are written in Python, though the concepts can be applied in any language.

This repository is dedicated to the learning and exchange of resources for the School of Artificial Intelligence at Anhui University. Notes will be published on this website first: https://www.aoaoaoao.cn and will be synchronized to the repository regularly. You can also contact me at [email protected].

This repository provides a comprehensive guide to modern AI for beginners, covering both theoretical foundations and practical implementation. It emphasizes the importance of understanding both the mathematical principles and the code implementation of AI models. The repository includes resources on PyTorch, deep learning fundamentals, mathematical foundations, transformer-based LLMs, diffusion models, software engineering, and full-stack development. It also features tutorials on natural language processing with transformers, reinforcement learning, and practical deep learning for coders.

This repository is for the book 'Building AI Applications with ChatGPT APIs' published by Packt. It provides code examples and instructions for mastering ChatGPT, Whisper, and DALL-E APIs through building innovative AI projects. Readers will learn to develop AI applications using ChatGPT APIs, integrate them with frameworks like Flask and Django, create AI-generated art with DALL-E APIs, and optimize ChatGPT models through fine-tuning.

This repository contains a collection of sample applications and Jupyter Notebooks for hands-on experience with Pinecone vector databases and common AI patterns, tools, and algorithms. It includes production-ready examples for review and support, as well as learning-optimized examples for exploring AI techniques and building applications. Users can contribute, provide feedback, and collaborate to improve the resource.

LinGoose is a modular Go framework designed for building AI/LLM applications. It offers the flexibility to import only the necessary modules, abstracts features for customization, and provides a comprehensive solution for developing AI/LLM applications from scratch. The framework simplifies the process of creating intelligent applications by allowing users to choose preferred implementations or create their own. LinGoose empowers developers to leverage its capabilities to streamline the development of cutting-edge AI and LLM projects.

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.