MLX Chat is a simple UI / Web / Frontend for MLX mlx-lm using Streamlit. It provides a user-friendly interface to interact with the MLX language model, allowing users to easily generate text, translate languages, write different kinds of creative content, and more. The tool is designed to be accessible to users of all levels, from beginners to experienced programmers.

Stable Diffusion web UI is a web interface for Stable Diffusion, implemented using Gradio library. It provides a user-friendly interface to access the powerful image generation capabilities of Stable Diffusion. With Stable Diffusion web UI, users can easily generate images from text prompts, edit and refine images using inpainting and outpainting, and explore different artistic styles and techniques. The web UI also includes a range of advanced features such as textual inversion, hypernetworks, and embeddings, allowing users to customize and fine-tune the image generation process. Whether you're an artist, designer, or simply curious about the possibilities of AI-generated art, Stable Diffusion web UI is a valuable tool that empowers you to create stunning and unique images.

This tool is a fork of the 3D Gaussian Splatting code. It allows users to create a dataset ready to be trained with the Gaussian Splatting code. The dataset can be used for various experiments, such as creating orthogonal images, steganography, and lenticular effects. The tool also includes a visualizer that allows users to visualize the "painting" process during the Gaussian Splatting optimization.

This repository contains a simple Python Flask App utilizing the Google AI Gemini API to explore multi-modal capabilities. It provides a basic UI and Flask backend for easy integration and testing. The app allows users to interact with the AI model through chat messages, making it a great starting point for developers interested in AI-powered applications.

Kaito is an operator that automates the AI/ML inference model deployment in a Kubernetes cluster. It manages large model files using container images, avoids tuning deployment parameters to fit GPU hardware by providing preset configurations, auto-provisions GPU nodes based on model requirements, and hosts large model images in the public Microsoft Container Registry (MCR) if the license allows. Using Kaito, the workflow of onboarding large AI inference models in Kubernetes is largely simplified.

This repository contains a demo application for DepthAI, a tool that can load different networks, create pipelines, record video, and more. It provides documentation for installation and usage, including running programs through Docker. Users can explore DepthAI features via command line arguments or a clickable QT interface. Supported models include various AI models for tasks like face detection, human pose estimation, and object detection. The tool collects anonymous usage statistics by default, which can be disabled. Users can report issues to the development team for support and troubleshooting.

LLPhant is a comprehensive PHP Generative AI Framework that provides a simple and powerful way to build apps. It supports Symfony and Laravel and offers a wide range of features, including text generation, chatbots, text summarization, and more. LLPhant is compatible with OpenAI and Ollama and can be used to perform a variety of tasks, including creating semantic search, chatbots, personalized content, and text summarization.

MusicGPT is an application that allows running the latest music generation AI models locally in a performant way, supporting different music generation models transparently to the user. It can be interacted with through UI mode or CLI mode, generating music based on natural language prompts. The tool requires access to storage to save downloaded models and generated audios along with metadata. It is licensed under MIT License for the code and CC-BY-NC-4.0 License for the AI model weights.

A Python interface for creating battling Pokemon agents, 'poke-env' allows users to develop rule-based or Reinforcement Learning bots to battle on Pokemon Showdown. The tool provides an easy-to-use interface for agent creation and offers documentation, examples, and starting code for beginners. Users can install 'poke-env' via pip and set up a development server for testing. The project is inspired by an artificial intelligence class project and relies on data from Smogon forums' RMT section. It is licensed under MIT and can be cited using a provided BibTeX entry.

sdkit (stable diffusion kit) is an easy-to-use library for utilizing Stable Diffusion in AI Art projects. It includes features like ControlNets, LoRAs, Textual Inversion Embeddings, GFPGAN, CodeFormer for face restoration, RealESRGAN for upscaling, k-samplers, support for custom VAEs, NSFW filter, model-downloader, parallel GPU support, and more. It offers a model database, auto-scanning for malicious models, and various optimizations. The API consists of modules for loading models, generating images, filters, model merging, and utilities, all managed through the sdkit.Context object.

The LlamaEdge project makes it easy to run LLM inference apps and create OpenAI-compatible API services for the Llama2 series of LLMs locally. It provides a Rust+Wasm stack for fast, portable, and secure LLM inference on heterogeneous edge devices. The project includes source code for text generation, chatbot, and API server applications, supporting all LLMs based on the llama2 framework in the GGUF format. LlamaEdge is committed to continuously testing and validating new open-source models and offers a list of supported models with download links and startup commands. It is cross-platform, supporting various OSes, CPUs, and GPUs, and provides troubleshooting tips for common errors.

Engine Core is a project that demonstrates a pattern for enabling Large Language Models (LLMs) to undertake tasks with a dynamic system prompt and a collection of tool functions known as chat strategies. These strategies allow for the dynamic alteration of chat history, system prompts, and available tools on every run. The project includes example strategies such as demoStrategy, backendStrategy, and shellStrategy. Additionally, LLM integrations like Anthropic or OpenAI have been extracted into adapters to enable running the same app code and strategies while switching foundation models.

Marvin is a lightweight AI toolkit for building natural language interfaces that are reliable, scalable, and easy to trust. Each of Marvin's tools is simple and self-documenting, using AI to solve common but complex challenges like entity extraction, classification, and generating synthetic data. Each tool is independent and incrementally adoptable, so you can use them on their own or in combination with any other library. Marvin is also multi-modal, supporting both image and audio generation as well using images as inputs for extraction and classification. Marvin is for developers who care more about _using_ AI than _building_ AI, and we are focused on creating an exceptional developer experience. Marvin users should feel empowered to bring tightly-scoped "AI magic" into any traditional software project with just a few extra lines of code. Marvin aims to merge the best practices for building dependable, observable software with the best practices for building with generative AI into a single, easy-to-use library. It's a serious tool, but we hope you have fun with it. Marvin is open-source, free to use, and made with 💙 by the team at Prefect.

LOTUS (LLMs Over Tables of Unstructured and Structured Data) is a query engine that provides a declarative programming model and an optimized query engine for reasoning-based query pipelines over structured and unstructured data. It offers a simple and intuitive Pandas-like API with semantic operators for fast and easy LLM-powered data processing. The tool implements a semantic operator programming model, allowing users to write AI-based pipelines with high-level logic and leaving the rest of the work to the query engine. LOTUS supports various semantic operators like sem_map, sem_filter, sem_extract, sem_agg, sem_topk, sem_join, sem_sim_join, and sem_search, enabling users to perform tasks like mapping records, filtering data, aggregating records, and more. The tool also supports different model classes such as LM, RM, and Reranker for language modeling, retrieval, and reranking tasks respectively.

This repository provides a fullstack example of building a Retrieval Augmented Generation (RAG) app with Cloudflare. It utilizes Cloudflare Workers, Pages, D1, KV, R2, AI Gateway, and Workers AI. The app features streaming interactions to the UI, hybrid RAG with Full-Text Search and Vector Search, switchable providers using AI Gateway, per-IP rate limiting with Cloudflare's KV, OCR within Cloudflare Worker, and Smart Placement for workload optimization. The development setup requires Node, pnpm, and wrangler CLI, along with setting up necessary primitives and API keys. Deployment involves setting up secrets and deploying the app to Cloudflare Pages. The project implements a Hybrid Search RAG approach combining Full Text Search against D1 and Hybrid Search with embeddings against Vectorize to enhance context for the LLM.

OntoGPT is a Python package for extracting structured information from text using large language models, instruction prompts, and ontology-based grounding. It provides a command line interface and a minimal web app for easy usage. The tool has been evaluated on test data and is used in related projects like TALISMAN for gene set analysis. OntoGPT enables users to extract information from text by specifying relevant terms and provides the extracted objects as output.

这是一个程序员关于 ChatGPT 学习过程的记录，其中包括了 ChatGPT 的使用技巧、相关工具和资源的整理，以及一些个人见解和思考。 **使用技巧** * **充值 OpenAI API**：可以通过 https://beta.openai.com/account/api-keys 进行充值，支持信用卡和 PayPal。 * **使用专梯**：推荐使用稳定的专梯，可以有效提高 ChatGPT 的访问速度和稳定性。 * **使用魔法**：可以通过 https://my.x-air.app:666/#/register?aff=32853 访问 ChatGPT，无需魔法即可访问。 * **下载各种 apk**：可以通过 https://apkcombo.com 下载各种安卓应用的 apk 文件。 * **ChatGPT 官网**：ChatGPT 的官方网站是 https://ai.com。 * **Midjourney**：Midjourney 是一个生成式 AI 图像平台，可以通过 https://midjourney.com 访问。 * **文本转视频**：可以通过 https://www.d-id.com 将文本转换为视频。 * **国内大模型**：国内也有很多大模型，如阿里巴巴的通义千问、百度文心一言、讯飞星火、阿里巴巴通义听悟等。 * **查看 OpenAI 状态**：可以通过 https://status.openai.com/ 查看 OpenAI 的服务状态。 * **Canva 画图**：Canva 是一个在线平面设计平台，可以通过 https://www.canva.cn 进行画图。 **相关工具和资源** * **文字转语音**：可以通过 https://modelscope.cn/models?page=1&tasks=text-to-speech&type=audio 找到文字转语音的模型。 * **可好好玩玩的项目**： * https://github.com/sunner/ChatALL * https://github.com/labring/FastGPT * https://github.com/songquanpeng/one-api * **个人博客**： * https://baoyu.io/ * https://gorden-sun.notion.site/527689cd2b294e60912f040095e803c5?v=4f6cc12006c94f47aee4dc909511aeb5 * **srt 2 lrc 歌词**：可以通过 https://gotranscript.com/subtitle-converter 将 srt 格式的字幕转换为 lrc 格式的歌词。 * **5 种速率限制**：OpenAI API 有 5 种速率限制：RPM（每分钟请求数）、RPD（每天请求数）、TPM（每分钟 tokens 数量）、TPD（每天 tokens 数量）、IPM（每分钟图像数量）。 * **扣子平台**：coze.cn 是一个扣子平台，可以提供各种扣子。 * **通过云函数免费使用 GPT-3.5**：可以通过 https://juejin.cn/post/7353849549540589587 免费使用 GPT-3.5。 * **不蒜子 统计网页基数**：可以通过 https://busuanzi.ibruce.info/ 统计网页的基数。 * **视频总结和翻译网页**：可以通过 https://glarity.app/zh-CN 总结和翻译视频。 * **视频翻译和配音工具**：可以通过 https://github.com/jianchang512/pyvideotrans 翻译和配音视频。 * **文字生成音频**：可以通过 https://www.cnblogs.com/jijunjian/p/18118366 将文字生成音频。 * **memo ai**：memo.ac 是一个多模态 AI 平台，可以将视频链接、播客链接、本地音视频转换为文字，支持多语言转录后翻译，还可以将文字转换为新的音频。 * **视频总结工具**：可以通过 https://summarize.ing/ 总结视频。 * **可每天免费玩玩**：可以通过 https://www.perplexity.ai/ 每天免费玩玩。 * **Suno.ai**：Suno.ai 是一个 AI 语言模型，可以通过 https://bibigpt.co/ 访问。 * **CapCut**：CapCut 是一个视频编辑软件，可以通过 https://www.capcut.cn/ 下载。 * **Valla.ai**：Valla.ai 是一个多模态 AI 模型，可以通过 https://www.valla.ai/ 访问。 * **Viggle.ai**：Viggle.ai 是一个 AI 视频生成平台，可以通过 https://viggle.ai 访问。 * **使用免费的 GPU 部署文生图大模型**：可以通过 https://www.cnblogs.com/xuxiaona/p/18088404 部署文生图大模型。 * **语音转文字**：可以通过 https://speech.microsoft.com/portal 将语音转换为文字。 * **投资界的 ai**：可以通过 https://reportify.cc/ 了解投资界的 ai。 * **抓取小视频 app 的各种信息**：可以通过 https://github.com/NanmiCoder/MediaCrawler 抓取小视频 app 的各种信息。 * **马斯克 Grok1 开源**：马斯克的 Grok1 模型已经开源，可以通过 https://github.com/xai-org/grok-1 访问。 * **ChatALL**：ChatALL 是一个跨端支持的聊天机器人，可以通过 https://github.com/sunner/ChatALL 访问。 * **零一万物**：零一万物是一个 AI 平台，可以通过 https://www.01.ai/cn 访问。 * **智普**：智普是一个 AI 语言模型，可以通过 https://chatglm.cn/ 访问。 * **memo ai 下载**：可以通过 https://memo.ac/ 下载 memo ai。 * **ffmpeg 学习**：可以通过 https://www.ruanyifeng.com/blog/2020/01/ffmpeg.html 学习 ffmpeg。 * **自动生成文章小工具**：可以通过 https://www.cognition-labs.com/blog 生成文章。 * **简易商城**：可以通过 https://www.cnblogs.com/whuanle/p/18086537 搭建简易商城。 * **物联网**：可以通过 https://www.cnblogs.com/xuxiaona/p/18088404 学习物联网。 * **自定义表单、自定义列表、自定义上传和下载、自定义流程、自定义报表**：可以通过 https://www.cnblogs.com/whuanle/p/18086537 实现自定义表单、自定义列表、自定义上传和下载、自定义流程、自定义报表。 **个人见解和思考** * ChatGPT 是一个强大的工具，可以用来提高工作效率和创造力。 * ChatGPT 的使用门槛较低，即使是非技术人员也可以轻松上手。 * ChatGPT 的发展速度非常快，未来可能会对各个行业产生深远的影响。 * 我们应该理性看待 ChatGPT，既要看到它的优点，也要意识到它的局限性。 * 我们应该积极探索 ChatGPT 的应用场景，为社会创造价值。

A chat interface using open source models, eg OpenAssistant or Llama. It is a SvelteKit app and it powers the HuggingChat app on hf.co/chat.

ChatterUI is a mobile app that allows users to manage chat files and character cards, and to interact with Large Language Models (LLMs). It supports multiple backends, including local, koboldcpp, text-generation-webui, Generic Text Completions, AI Horde, Mancer, Open Router, and OpenAI. ChatterUI provides a mobile-friendly interface for interacting with LLMs, making it easy to use them for a variety of tasks, such as generating text, translating languages, writing code, and answering questions.

99AI is a commercializable AI web application based on NineAI 2.4.2 (no authorization, no backdoors, no piracy, integrated front-end and back-end integration packages, supports Docker rapid deployment). The uncompiled source code is temporarily closed. Compared with the stable version, the development version is faster.

Chat Nio is a next-generation AI one-stop solution that provides a rich and user-friendly interface for interacting with various AI models. It offers features such as AI chat conversation, rich format compatibility, markdown support, message menu support, multi-platform adaptation, dialogue memory, full-model file parsing, full-model DuckDuckGo online search, full-screen large text editing, model marketplace, preset support, site announcements, preference settings, internationalization support, and a rich admin system. Chat Nio also boasts a powerful channel management system that utilizes a self-developed channel distribution algorithm, supports multi-channel management, is compatible with multiple formats, allows for custom models, supports channel retries, enables balanced load within the same channel, and provides channel model mapping and user grouping. Additionally, Chat Nio offers forwarding API services that are compatible with multiple formats in the OpenAI universal format and support multiple model compatible layers. It also provides a custom build and install option for highly customizable deployments. Chat Nio is an open-source project licensed under the Apache License 2.0 and welcomes contributions from the community.

**Curated collection of papers and resources on how to unlock the reasoning ability of LLMs and MLLMs.** **Description in less than 400 words, no line breaks and quotation marks.** Large Language Models (LLMs) have revolutionized the NLP landscape, showing improved performance and sample efficiency over smaller models. However, increasing model size alone has not proved sufficient for high performance on challenging reasoning tasks, such as solving arithmetic or commonsense problems. This curated collection of papers and resources presents the latest advancements in unlocking the reasoning abilities of LLMs and Multimodal LLMs (MLLMs). It covers various techniques, benchmarks, and applications, providing a comprehensive overview of the field. **5 jobs suitable for this tool, in lowercase letters.** - content writer - researcher - data analyst - software engineer - product manager **Keywords of the tool, in lowercase letters.** - llm - reasoning - multimodal - chain-of-thought - prompt engineering **5 specific tasks user can use this tool to do, in less than 3 words, Verb + noun form, in daily spoken language.** - write a story - answer a question - translate a language - generate code - summarize a document

Chinese-LLaMA-Alpaca-2 is a large Chinese language model developed by Meta AI. It is based on the Llama-2 model and has been further trained on a large dataset of Chinese text. Chinese-LLaMA-Alpaca-2 can be used for a variety of natural language processing tasks, including text generation, question answering, and machine translation. Here are some of the key features of Chinese-LLaMA-Alpaca-2: * It is the largest Chinese language model ever trained, with 13 billion parameters. * It is trained on a massive dataset of Chinese text, including books, news articles, and social media posts. * It can be used for a variety of natural language processing tasks, including text generation, question answering, and machine translation. * It is open-source and available for anyone to use. Chinese-LLaMA-Alpaca-2 is a powerful tool that can be used to improve the performance of a wide range of natural language processing tasks. It is a valuable resource for researchers and developers working in the field of artificial intelligence.

Linly-Talker is an innovative digital human conversation system that integrates the latest artificial intelligence technologies, including Large Language Models (LLM) 🤖, Automatic Speech Recognition (ASR) 🎙️, Text-to-Speech (TTS) 🗣️, and voice cloning technology 🎤. This system offers an interactive web interface through the Gradio platform 🌐, allowing users to upload images 📷 and engage in personalized dialogues with AI 💬.

ChatFAQ is an open-source comprehensive platform for creating a wide variety of chatbots: generic ones, business-trained, or even capable of redirecting requests to human operators. It includes a specialized NLP/NLG engine based on a RAG architecture and customized chat widgets, ensuring a tailored experience for users and avoiding vendor lock-in.

AgentCloud is an open-source platform that enables companies to build and deploy private LLM chat apps, empowering teams to securely interact with their data. It comprises three main components: Agent Backend, Webapp, and Vector Proxy. To run this project locally, clone the repository, install Docker, and start the services. The project is licensed under the GNU Affero General Public License, version 3 only. Contributions and feedback are welcome from the community.

AnythingLLM is a full-stack application that enables you to turn any document, resource, or piece of content into context that any LLM can use as references during chatting. This application allows you to pick and choose which LLM or Vector Database you want to use as well as supporting multi-user management and permissions.

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.

Magick is a groundbreaking visual AIDE (Artificial Intelligence Development Environment) for no-code data pipelines and multimodal agents. Magick can connect to other services and comes with nodes and templates well-suited for intelligent agents, chatbots, complex reasoning systems and realistic characters.

Glide is a cloud-native LLM gateway that provides a unified REST API for accessing various large language models (LLMs) from different providers. It handles LLMOps tasks such as model failover, caching, key management, and more, making it easy to integrate LLMs into applications. Glide supports popular LLM providers like OpenAI, Anthropic, Azure OpenAI, AWS Bedrock (Titan), Cohere, Google Gemini, OctoML, and Ollama. It offers high availability, performance, and observability, and provides SDKs for Python and NodeJS to simplify integration.

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.

ONNX Runtime Generative AI is a library that provides the generative AI loop for ONNX models, including inference with ONNX Runtime, logits processing, search and sampling, and KV cache management. Users can call a high level `generate()` method, or run each iteration of the model in a loop. It supports greedy/beam search and TopP, TopK sampling to generate token sequences, has built in logits processing like repetition penalties, and allows for easy custom scoring.