ChatGPT Lite is a lightweight web interface developed using Next.js and the OpenAI Chat API. It allows users to deploy a custom ChatGPT interface supporting markdown, prompt storage, and multi-person chats. Users can create private web-based ChatGPT instances for friends without sharing API keys. The codebase is clear and expandable, making it an ideal starting point for AI projects.

ComfyUI is a highly-configurable, cloud-first AI-Dock container that allows users to run ComfyUI without bundled models or third-party configurations. Users can configure the container using provisioning scripts. The Docker image supports NVIDIA CUDA, AMD ROCm, and CPU platforms, with version tags for different configurations. Additional environment variables and Python environments are provided for customization. ComfyUI service runs on port 8188 and can be managed using supervisorctl. The tool also includes an API wrapper service and pre-configured templates for Vast.ai. The author may receive compensation for services linked in the documentation.

Stable Diffusion WebUI Docker Image allows users to run Automatic1111 WebUI in a docker container locally or in the cloud. The images do not bundle models or third-party configurations, requiring users to use a provisioning script for container configuration. It supports NVIDIA CUDA, AMD ROCm, and CPU platforms, with additional environment variables for customization and pre-configured templates for Vast.ai and Runpod.io. The service is password protected by default, with options for version pinning, startup flags, and service management using supervisorctl.

This AI-powered git commit plugin for VSCode streamlines your commit and push processes, eliminating the need for manual confirmation. With a focus on minimizing keystrokes, the plugin leverages LLM to generate commit messages and automate the entire process. Key features include AI-assisted git commit and push, eliminating the need for the 'git add .' command, and customizable OpenAI model selection. The plugin supports multiple languages, making it accessible to developers worldwide. Additionally, it offers advanced settings for specifying the OpenAI API key, base URL, and conventional commit format. Developers can contribute to the project by following the provided development instructions.

AQLM is the official PyTorch implementation for Extreme Compression of Large Language Models via Additive Quantization. It includes prequantized AQLM models without PV-Tuning and PV-Tuned models for LLaMA, Mistral, and Mixtral families. The repository provides inference examples, model details, and quantization setups. Users can run prequantized models using Google Colab examples, work with different model families, and install the necessary inference library. The repository also offers detailed instructions for quantization, fine-tuning, and model evaluation. AQLM quantization involves calibrating models for compression, and users can improve model accuracy through finetuning. Additionally, the repository includes information on preparing models for inference and contributing guidelines.

Bodhi App runs Open Source Large Language Models locally, exposing LLM inference capabilities as OpenAI API compatible REST APIs. It leverages llama.cpp for GGUF format models and huggingface.co ecosystem for model downloads. Users can run fine-tuned models for chat completions, create custom aliases, and convert Huggingface models to GGUF format. The CLI offers commands for environment configuration, model management, pulling files, serving API, and more.

LEADS is a lightweight embedded assisted driving system designed to simplify the development of instrumentation, control, and analysis systems for racing cars. It is written in Python and C/C++ with impressive performance. The system is customizable and provides abstract layers for component rearrangement. It supports hardware components like Raspberry Pi and Arduino, and can adapt to various hardware types. LEADS offers a modular structure with a focus on flexibility and lightweight design. It includes robust safety features, modern GUI design with dark mode support, high performance on different platforms, and powerful ESC systems for traction control and braking. The system also supports real-time data sharing, live video streaming, and AI-enhanced data analysis for driver training. LEADS VeC Remote Analyst enables transparency between the driver and pit crew, allowing real-time data sharing and analysis. The system is designed to be user-friendly, adaptable, and efficient for racing car development.

llm2sh is a command-line utility that leverages Large Language Models (LLMs) to translate plain-language requests into shell commands. It provides a convenient way to interact with your system using natural language. The tool supports multiple LLMs for command generation, offers a customizable configuration file, YOLO mode for running commands without confirmation, and is easily extensible with new LLMs and system prompts. Users can set up API keys for OpenAI, Claude, Groq, and Cerebras to use the tool effectively. llm2sh does not store user data or command history, and it does not record or send telemetry by itself, but the LLM APIs may collect and store requests and responses for their purposes.

ChatGPT Telegram Bot is a Telegram bot that provides a smooth AI experience. It supports both Azure OpenAI and native OpenAI, and offers real-time (streaming) response to AI, with a faster and smoother experience. The bot also has 15 preset bot identities that can be quickly switched, and supports custom bot identities to meet personalized needs. Additionally, it supports clearing the contents of the chat with a single click, and restarting the conversation at any time. The bot also supports native Telegram bot button support, making it easy and intuitive to implement required functions. User level division is also supported, with different levels enjoying different single session token numbers, context numbers, and session frequencies. The bot supports English and Chinese on UI, and is containerized for easy deployment.

mLoRA (Multi-LoRA Fine-Tune) is an open-source framework for efficient fine-tuning of multiple Large Language Models (LLMs) using LoRA and its variants. It allows concurrent fine-tuning of multiple LoRA adapters with a shared base model, efficient pipeline parallelism algorithm, support for various LoRA variant algorithms, and reinforcement learning preference alignment algorithms. mLoRA helps save computational and memory resources when training multiple adapters simultaneously, achieving high performance on consumer hardware.

AgentPoison is a repository that provides the official PyTorch implementation of the paper 'AgentPoison: Red-teaming LLM Agents via Memory or Knowledge Base Backdoor Poisoning'. It offers tools for red-teaming LLM agents by poisoning memory or knowledge bases. The repository includes trigger optimization algorithms, agent experiments, and evaluation scripts for Agent-Driver, ReAct-StrategyQA, and EHRAgent. Users can fine-tune motion planners, inject queries with triggers, and evaluate red-teaming performance. The codebase supports multiple RAG embedders and provides a unified dataset access for all three agents.

Construction-Hazard-Detection is an AI-driven tool focused on improving safety at construction sites by utilizing the YOLOv8 model for object detection. The system identifies potential hazards like overhead heavy loads and steel pipes, providing real-time analysis and warnings. Users can configure the system via a YAML file and run it using Docker. The primary dataset used for training is the Construction Site Safety Image Dataset enriched with additional annotations. The system logs are accessible within the Docker container for debugging, and notifications are sent through the LINE messaging API when hazards are detected.

MockingBird is a toolbox designed for Mandarin speech synthesis using PyTorch. It supports multiple datasets such as aidatatang_200zh, magicdata, aishell3, and data_aishell. The toolbox can run on Windows, Linux, and M1 MacOS, providing easy and effective speech synthesis with pretrained encoder/vocoder models. It is webserver ready for remote calling. Users can train their own models or use existing ones for the encoder, synthesizer, and vocoder. The toolbox offers a demo video and detailed setup instructions for installation and model training.

The Pipe is a multimodal-first tool for feeding files and web pages into vision-language models such as GPT-4V. It is best for LLM and RAG applications that require a deep understanding of tricky data sources. The Pipe is available as a hosted API at thepi.pe, or it can be set up locally.

runpod-worker-comfy is a serverless API tool that allows users to run any ComfyUI workflow to generate an image. Users can provide input images as base64-encoded strings, and the generated image can be returned as a base64-encoded string or uploaded to AWS S3. The tool is built on Ubuntu + NVIDIA CUDA and provides features like built-in checkpoints and VAE models. Users can configure environment variables to upload images to AWS S3 and interact with the RunPod API to generate images. The tool also supports local testing and deployment to Docker hub using Github Actions.

Can AI Code is a self-evaluating interview tool for AI coding models. It includes interview questions written by humans and tests taken by AI, inference scripts for common API providers and CUDA-enabled quantization runtimes, a Docker-based sandbox environment for validating untrusted Python and NodeJS code, and the ability to evaluate the impact of prompting techniques and sampling parameters on large language model (LLM) coding performance. Users can also assess LLM coding performance degradation due to quantization. The tool provides test suites for evaluating LLM coding performance, a webapp for exploring results, and comparison scripts for evaluations. It supports multiple interviewers for API and CUDA runtimes, with detailed instructions on running the tool in different environments. The repository structure includes folders for interviews, prompts, parameters, evaluation scripts, comparison scripts, and more.

ChatGPT Lite is a lightweight web interface developed using Next.js and the OpenAI Chat API. It allows users to deploy a custom ChatGPT interface supporting markdown, prompt storage, and multi-person chats. Users can create private web-based ChatGPT instances for friends without sharing API keys. The codebase is clear and expandable, making it an ideal starting point for AI projects.

assistant-ui is a set of React components for AI chat. It provides a collection of components that can be easily integrated into projects to create AI chat interfaces for Discord, websites, and demos. The components are designed to streamline the process of setting up AI chat functionality in React applications, making it easier for developers to incorporate AI chat features into their projects.

Discord AI Bot is a chatbot designed to interact with Ollama and AUTOMATIC1111 Stable Diffusion on Discord. The project is now archived due to lack of maintenance. Users can set up the bot by installing Node.js, Ollama, and a model, creating a Discord bot, and starting the bot with the necessary configurations. Additionally, Docker setup instructions are provided for easy deployment. The bot can be interacted with by mentioning it in Discord messages.

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.

Learn Prompting is a platform offering free resources, courses, and webinars to master prompt engineering and generative AI. It provides a Prompt Engineering Guide, courses on Generative AI, workshops, and the HackAPrompt competition. The platform also offers AI Red Teaming and AI Safety courses, research reports on prompting techniques, and welcomes contributions in various forms such as content suggestions, translations, artwork, and typo fixes. Users can locally develop the website using Visual Studio Code, Git, and Node.js, and run it in development mode to preview changes.

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.