assistant-ui

assistant-ui is a set of React components for AI chat, providing wide model provider support out of the box and the ability to integrate custom APIs. It includes integrations with Langchain, Vercel AI SDK, TailwindCSS, shadcn-ui, react-markdown, react-syntax-highlighter, React Hook Form, and more. The tool allows users to quickly create AI chat applications with pre-configured templates and easy setup steps.

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.

This repository provides code to deploy a chatbot powered by Multi-Model and Multi-RAG using AWS CDK on AWS. Users can experiment with various Large Language Models and Multimodal Language Models from different providers. The solution supports Amazon Bedrock, Amazon SageMaker self-hosted models, and third-party providers via API. It also offers additional resources like AWS Generative AI CDK Constructs and Project Lakechain for building generative AI solutions and document processing. The roadmap and authors are listed, along with contributors. The library is licensed under the MIT-0 License with information on changelog, code of conduct, and contributing guidelines. A legal disclaimer advises users to conduct their own assessment before using the content for production purposes.

Srt-AI-Voice-Assistant is a convenient tool that generates audio from uploaded .srt subtitle files by calling APIs such as Bert-VITS2 (HiyoriUI), GPT-SoVITS, and Microsoft TTS (online). The code is currently not perfect, and feedback on bugs or suggestions can be provided at https://github.com/YYuX-1145/Srt-AI-Voice-Assistant/issues. Recent updates include adding custom API functionality with a focus on security, support for Microsoft online TTS (requires key configuration), error handling improvements, automatic project path detection, compatibility with API-v1 for limited functionality, and significant feature updates supporting card synthesis.

The Google AI Go SDK enables developers to use Google's state-of-the-art generative AI models (like Gemini) to build AI-powered features and applications. It supports use cases like generating text from text-only input, generating text from text-and-images input (multimodal), building multi-turn conversations (chat), and embedding.

SuaveUI is an experimental Progressive Web App chat user interface designed for interacting with local AI models. It provides a platform for users to easily communicate with AI models in a chat-like environment. The tool is built using React for the user interface and Node.js for the backend. Users can run SuaveUI using Docker or by cloning the repository and running a server. The project is still in the early alpha stage and is being actively developed to enhance its functionality and features.

NanoLLM is a tool designed for optimized local inference for Large Language Models (LLMs) using HuggingFace-like APIs. It supports quantization, vision/language models, multimodal agents, speech, vector DB, and RAG. The tool aims to provide efficient and effective processing for LLMs on local devices, enhancing performance and usability for various AI applications.

IBM Generative AI Python SDK is a tool designed for the Tech Preview program for IBM Foundation Models Studio. It brings IBM Generative AI (GenAI) into Python programs, offering various operations and types. Users can start a trial version or request a demo via the provided link. The SDK was recently rewritten and released under V2 in 2024, with a migration guide available. Contributors are welcome to participate in the open-source project by contributing documentation, tests, bug fixes, and new functionality.

The `xaitk-saliency` package is an open source Explainable AI (XAI) framework for visual saliency algorithm interfaces and implementations, designed for analytics and autonomy applications. It provides saliency algorithms for various image understanding tasks such as image classification, image similarity, object detection, and reinforcement learning. The toolkit targets data scientists and developers who aim to incorporate visual saliency explanations into their workflow or product, offering both direct accessibility for experimentation and modular integration into systems and applications through Strategy and Adapter patterns. The package includes documentation, examples, and a demonstration tool for visual saliency generation in a user-interface.

Aippt is a commercial-grade AI tool for generating, parsing, and rendering PowerPoint presentations. It offers functionalities such as AI-powered PPT generation, PPT to JSON conversion, and JSON to PPT rendering. Users can experience online editing, upload PPT files for rendering, and download edited PPT files. The tool also supports commercial partnerships for custom industry solutions, native chart and animation support, user-defined templates, and competitive pricing. Aippt is available for commercial use with options for agency support and private deployment. The official website offers open APIs and an open platform for API/UI integration.

Aimeos Base abstraction layer is a tool designed to provide a solid foundation for building e-commerce applications. It offers a comprehensive set of functionalities and features that simplify the development process and enhance the performance of online stores. The abstraction layer abstracts common e-commerce functionalities, such as product management, order processing, and customer management, allowing developers to focus on business logic implementation rather than low-level technical details. With a strong emphasis on modularity and extensibility, Aimeos Base enables developers to create scalable and customizable e-commerce solutions that meet specific business requirements. The tool is well-documented and actively maintained by the Aimeos community, ensuring reliability and continuous improvement.

Talemate is a roleplay tool that allows users to interact with AI agents for dialogue, narration, summarization, direction, editing, world state management, character/scenario creation, text-to-speech, and visual generation. It supports multiple AI clients and APIs, offers long-term memory using ChromaDB, and provides tools for managing NPCs, AI-assisted character creation, and scenario creation. Users can customize prompts using Jinja2 templates and benefit from a modern, responsive UI. The tool also integrates with Runpod for enhanced functionality.

SyPB is a Counter-Strike 1.6 bot based on YaPB2.7.2. It provides a NPC system and an AMXX API for enhancing gameplay. The tool is designed for Windows users and can be downloaded from the provided link. SyPB aims to improve the gaming experience by offering advanced bot functionalities and integration with the AMXX API.

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.

OpenCat code running on BiBoard, a high-performance ESP32 quadruped robot development board. The board is mainly designed for developers and engineers working on multi-degree-of-freedom (MDOF) Multi-legged robots with up to 12 servos.

OpenModelDB is a community-driven database of AI upscaling models, providing a centralized platform for users to access and compare various models. The repository contains a collection of models and model metadata, facilitating easy exploration and evaluation of different AI upscaling solutions. With a focus on enhancing the accessibility and usability of AI models, OpenModelDB aims to streamline the process of finding and selecting the most suitable models for specific tasks or projects.

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.

**Prompt flow** is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality.

DeepEval is a simple-to-use, open-source LLM evaluation framework specialized for unit testing LLM outputs. It incorporates various metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., and runs locally on your machine for evaluation. It provides a wide range of ready-to-use evaluation metrics, allows for creating custom metrics, integrates with any CI/CD environment, and enables benchmarking LLMs on popular benchmarks. DeepEval is designed for evaluating RAG and fine-tuning applications, helping users optimize hyperparameters, prevent prompt drifting, and transition from OpenAI to hosting their own Llama2 with confidence.

MegaDetector is an AI model that identifies animals, people, and vehicles in camera trap images (which also makes it useful for eliminating blank images). This model is trained on several million images from a variety of ecosystems. MegaDetector is just one of many tools that aims to make conservation biologists more efficient with AI. If you want to learn about other ways to use AI to accelerate camera trap workflows, check out our of the field, affectionately titled "Everything I know about machine learning and camera traps".

LeapfrogAI is a self-hosted AI platform designed to be deployed in air-gapped resource-constrained environments. It brings sophisticated AI solutions to these environments by hosting all the necessary components of an AI stack, including vector databases, model backends, API, and UI. LeapfrogAI's API closely matches that of OpenAI, allowing tools built for OpenAI/ChatGPT to function seamlessly with a LeapfrogAI backend. It provides several backends for various use cases, including llama-cpp-python, whisper, text-embeddings, and vllm. LeapfrogAI leverages Chainguard's apko to harden base python images, ensuring the latest supported Python versions are used by the other components of the stack. The LeapfrogAI SDK provides a standard set of protobuffs and python utilities for implementing backends and gRPC. LeapfrogAI offers UI options for common use-cases like chat, summarization, and transcription. It can be deployed and run locally via UDS and Kubernetes, built out using Zarf packages. LeapfrogAI is supported by a community of users and contributors, including Defense Unicorns, Beast Code, Chainguard, Exovera, Hypergiant, Pulze, SOSi, United States Navy, United States Air Force, and United States Space Force.

This Docker image for LLaVA (Large Language and Vision Assistant) provides a convenient way to run LLaVA locally or on RunPod. LLaVA is a powerful AI tool that combines natural language processing and computer vision capabilities. With this Docker image, you can easily access LLaVA's functionalities for various tasks, including image captioning, visual question answering, text summarization, and more. The image comes pre-installed with LLaVA v1.2.0, Torch 2.1.2, xformers 0.0.23.post1, and other necessary dependencies. You can customize the model used by setting the MODEL environment variable. The image also includes a Jupyter Lab environment for interactive development and exploration. Overall, this Docker image offers a comprehensive and user-friendly platform for leveraging LLaVA's capabilities.

The 'carrot' repository on GitHub provides a list of free and user-friendly ChatGPT mirror sites for easy access. The repository includes sponsored sites offering various GPT models and services. Users can find and share sites, report errors, and access stable and recommended sites for ChatGPT usage. The repository also includes a detailed list of ChatGPT sites, their features, and accessibility options, making it a valuable resource for ChatGPT users seeking free and unlimited GPT services.

TrustLLM is a comprehensive study of trustworthiness in LLMs, including principles for different dimensions of trustworthiness, established benchmark, evaluation, and analysis of trustworthiness for mainstream LLMs, and discussion of open challenges and future directions. Specifically, we first propose a set of principles for trustworthy LLMs that span eight different dimensions. Based on these principles, we further establish a benchmark across six dimensions including truthfulness, safety, fairness, robustness, privacy, and machine ethics. We then present a study evaluating 16 mainstream LLMs in TrustLLM, consisting of over 30 datasets. The document explains how to use the trustllm python package to help you assess the performance of your LLM in trustworthiness more quickly. For more details about TrustLLM, please refer to project website.

AI-YinMei is an AI virtual anchor Vtuber development tool (N card version). It supports fastgpt knowledge base chat dialogue, a complete set of solutions for LLM large language models: [fastgpt] + [one-api] + [Xinference], supports docking bilibili live broadcast barrage reply and entering live broadcast welcome speech, supports Microsoft edge-tts speech synthesis, supports Bert-VITS2 speech synthesis, supports GPT-SoVITS speech synthesis, supports expression control Vtuber Studio, supports painting stable-diffusion-webui output OBS live broadcast room, supports painting picture pornography public-NSFW-y-distinguish, supports search and image search service duckduckgo (requires magic Internet access), supports image search service Baidu image search (no magic Internet access), supports AI reply chat box [html plug-in], supports AI singing Auto-Convert-Music, supports playlist [html plug-in], supports dancing function, supports expression video playback, supports head touching action, supports gift smashing action, supports singing automatic start dancing function, chat and singing automatic cycle swing action, supports multi scene switching, background music switching, day and night automatic switching scene, supports open singing and painting, let AI automatically judge the content.