Dir-assistant is a tool that allows users to interact with their current directory's files using local or API Language Models (LLMs). It supports various platforms and provides API support for major LLM APIs. Users can configure and customize their local LLMs and API LLMs using the tool. Dir-assistant also supports model downloads and configurations for efficient usage. It is designed to enhance file interaction and retrieval using advanced language models.

ComfyUI Desktop is a packaged desktop application that allows users to easily use ComfyUI with bundled features like ComfyUI source code, ComfyUI-Manager, and uv. It automatically installs necessary Python dependencies and updates with stable releases. The app comes with Electron, Chromium binaries, and node modules. Users can store ComfyUI files in a specified location and manage model paths. The tool requires Python 3.12+ and Visual Studio with Desktop C++ workload for Windows. It uses nvm to manage node versions and yarn as the package manager. Users can install ComfyUI and dependencies using comfy-cli, download uv, and build/launch the code. Troubleshooting steps include rebuilding modules and installing missing libraries. The tool supports debugging in VSCode and provides utility scripts for cleanup. Crash reports can be sent to help debug issues, but no personal data is included.

MLX LM is a Python package designed for generating text and fine-tuning large language models on Apple silicon using MLX. It offers integration with the Hugging Face Hub for easy access to thousands of LLMs, support for quantizing and uploading models to the Hub, low-rank and full model fine-tuning capabilities, and distributed inference and fine-tuning with `mx.distributed`. Users can interact with the package through command line options or the Python API, enabling tasks such as text generation, chatting with language models, model conversion, streaming generation, and sampling. MLX LM supports various Hugging Face models and provides tools for efficient scaling to long prompts and generations, including a rotating key-value cache and prompt caching. It requires macOS 15.0 or higher for optimal performance.

LLM-ollama is a plugin that provides access to models running on an Ollama server. It allows users to query the Ollama server for a list of models, register them with LLM, and use them for prompting, chatting, and embedding. The plugin supports image attachments, embeddings, JSON schemas, async models, model aliases, and model options. Users can interact with Ollama models through the plugin in a seamless and efficient manner.

OpenCommit is a tool that auto-generates meaningful commits using AI, allowing users to quickly create commit messages for their staged changes. It provides a CLI interface for easy usage and supports customization of commit descriptions, emojis, and AI models. Users can configure local and global settings, switch between different AI providers, and set up Git hooks for integration with IDE Source Control. Additionally, OpenCommit can be used as a GitHub Action to automatically improve commit messages on push events, ensuring all commits are meaningful and not generic. Payments for OpenAI API requests are handled by the user, with the tool storing API keys locally.

Reader is a tool that converts any URL to an LLM-friendly input with a simple prefix `https://r.jina.ai/`. It improves the output for your agent and RAG systems at no cost. Reader supports image reading, captioning all images at the specified URL and adding `Image [idx]: [caption]` as an alt tag. This enables downstream LLMs to interact with the images in reasoning, summarizing, etc. Reader offers a streaming mode, useful when the standard mode provides an incomplete result. In streaming mode, Reader waits a bit longer until the page is fully rendered, providing more complete information. Reader also supports a JSON mode, which contains three fields: `url`, `title`, and `content`. Reader is backed by Jina AI and licensed under Apache-2.0.

This repository provides an easy-to-use solution for running inference servers on Slurm-managed computing clusters using vLLM. All scripts in this repository run natively on the Vector Institute cluster environment. Users can deploy models as Slurm jobs, check server status and performance metrics, and shut down models. The repository also supports launching custom models with specific configurations. Additionally, users can send inference requests and set up an SSH tunnel to run inference from a local device.

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.

The `repo-to-text` tool converts a directory's structure and contents into a single text file. It generates a formatted text representation that includes the directory tree and file contents, making it easy to share code with LLMs for development and debugging. Users can customize the tool's behavior with various options and settings, including output directory specification, debug logging, and file inclusion/exclusion rules. The tool supports Docker usage for containerized environments and provides detailed instructions for installation, usage, settings configuration, and contribution guidelines. It is a versatile tool for converting repository contents into text format for easy sharing and documentation.

torchchat is a codebase showcasing the ability to run large language models (LLMs) seamlessly. It allows running LLMs using Python in various environments such as desktop, server, iOS, and Android. The tool supports running models via PyTorch, chatting, generating text, running chat in the browser, and running models on desktop/server without Python. It also provides features like AOT Inductor for faster execution, running in C++ using the runner, and deploying and running on iOS and Android. The tool supports popular hardware and OS including Linux, Mac OS, Android, and iOS, with various data types and execution modes available.

This repository codifies the Airflow cluster that is deployed at workflow.telemetry.mozilla.org (behind SSO) and commonly referred to as "WTMO" or simply "Airflow". Some links relevant to users and developers of WTMO: * The `dags` directory in this repository contains some custom DAG definitions * Many of the DAGs registered with WTMO don't live in this repository, but are instead generated from ETL task definitions in bigquery-etl * The Data SRE team maintains a WTMO Developer Guide (behind SSO)

Windows Agent Arena (WAA) is a scalable Windows AI agent platform designed for testing and benchmarking multi-modal, desktop AI agents. It provides researchers and developers with a reproducible and realistic Windows OS environment for AI research, enabling testing of agentic AI workflows across various tasks. WAA supports deploying agents at scale using Azure ML cloud infrastructure, allowing parallel running of multiple agents and delivering quick benchmark results for hundreds of tasks in minutes.

SambaNova AI Starter Kits is a collection of open-source examples and guides designed to facilitate the deployment of AI-driven use cases for developers and enterprises. The kits cover various categories such as Data Ingestion & Preparation, Model Development & Optimization, Intelligent Information Retrieval, and Advanced AI Capabilities. Users can obtain a free API key using SambaNova Cloud or deploy models using SambaStudio. Most examples are written in Python but can be applied to any programming language. The kits provide resources for tasks like text extraction, fine-tuning embeddings, prompt engineering, question-answering, image search, post-call analysis, and more.

The Artificial Intelligence Incident Database (AIID) is a collection of incidents involving the development and use of artificial intelligence (AI). The database is designed to help researchers, policymakers, and the public understand the potential risks and benefits of AI, and to inform the development of policies and practices to mitigate the risks and promote the benefits of AI. The AIID is a collaborative project involving researchers from the University of California, Berkeley, the University of Washington, and the University of Toronto.

Oxen is a data version control library, written in Rust. It's designed to be fast, reliable, and easy to use. Oxen can be used in a variety of ways, from a simple command line tool to a remote server to sync to, to integrations into other ecosystems such as python.

Sage is a tool that allows users to chat with any codebase, providing a chat interface for code understanding and integration. It simplifies the process of learning how a codebase works by offering heavily documented answers sourced directly from the code. Users can set up Sage locally or on the cloud with minimal effort. The tool is designed to be easily customizable, allowing users to swap components of the pipeline and improve the algorithms powering code understanding and generation.

Elia is a powerful terminal user interface designed for interacting with large language models. It allows users to chat with models like Claude 3, ChatGPT, Llama 3, Phi 3, Mistral, and Gemma. Conversations are stored locally in a SQLite database, ensuring privacy. Users can run local models through 'ollama' without data leaving their machine. Elia offers easy installation with pipx and supports various environment variables for different models. It provides a quick start to launch chats and manage local models. Configuration options are available to customize default models, system prompts, and add new models. Users can import conversations from ChatGPT and wipe the database when needed. Elia aims to enhance user experience in interacting with language models through a user-friendly interface.

ChatGPT Web Sea is an open-source project based on ChatGPT-web for secondary development. It supports all models that comply with the OpenAI interface standard, allows for model selection, configuration, and extension, and is compatible with OneAPI. The tool includes a Chinese ChatGPT tuning guide, supports file uploads, and provides model configuration options. Users can interact with the tool through a web interface, configure models, and perform tasks such as model selection, API key management, and chat interface setup. The project also offers Docker deployment options and instructions for manual packaging.

Dir-assistant is a tool that allows users to interact with their current directory's files using local or API Language Models (LLMs). It supports various platforms and provides API support for major LLM APIs. Users can configure and customize their local LLMs and API LLMs using the tool. Dir-assistant also supports model downloads and configurations for efficient usage. It is designed to enhance file interaction and retrieval using advanced language models.

KubeAI is a highly scalable AI platform that runs on Kubernetes, serving as a drop-in replacement for OpenAI with API compatibility. It can operate OSS model servers like vLLM and Ollama, with zero dependencies and additional OSS addons included. Users can configure models via Kubernetes Custom Resources and interact with models through a chat UI. KubeAI supports serving various models like Llama v3.1, Gemma2, and Qwen2, and has plans for model caching, LoRA finetuning, and image generation.

Renumics RAG is a retrieval-augmented generation assistant demo that utilizes LangChain and Streamlit. It provides a tool for indexing documents and answering questions based on the indexed data. Users can explore and visualize RAG data, configure OpenAI and Hugging Face models, and interactively explore questions and document snippets. The tool supports GPU and CPU setups, offers a command-line interface for retrieving and answering questions, and includes a web application for easy access. It also allows users to customize retrieval settings, embeddings models, and database creation. Renumics RAG is designed to enhance the question-answering process by leveraging indexed documents and providing detailed answers with sources.

LLM-Term is a Rust-based CLI tool that generates and executes terminal commands using OpenAI's language models or local Ollama models. It offers configurable model and token limits, works on both PowerShell and Unix-like shells, and provides a seamless user experience for generating commands based on prompts. Users can easily set up the tool, customize configurations, and leverage different models for command generation.

Gemini PHP is a PHP API client for interacting with the Gemini AI API. It allows users to generate content, chat, count tokens, configure models, embed resources, list models, get model information, troubleshoot timeouts, and test API responses. The client supports various features such as text-only input, text-and-image input, multi-turn conversations, streaming content generation, token counting, model configuration, and embedding techniques. Users can interact with Gemini's API to perform tasks related to natural language generation and text analysis.

Sdcb Chats is a powerful and flexible frontend for large language models, supporting multiple functions and platforms. Whether you want to manage multiple model interfaces or need a simple deployment process, Sdcb Chats can meet your needs. It supports dynamic management of multiple large language model interfaces, integrates visual models to enhance user interaction experience, provides fine-grained user permission settings for security, real-time tracking and management of user account balances, easy addition, deletion, and configuration of models, transparently forwards user chat requests based on the OpenAI protocol, supports multiple databases including SQLite, SQL Server, and PostgreSQL, compatible with various file services such as local files, AWS S3, Minio, Aliyun OSS, Azure Blob Storage, and supports multiple login methods including Keycloak SSO and phone SMS verification.

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.