ChatGPT-On-CS

ChatGPT-On-CS is an intelligent chatbot tool based on large models, supporting various platforms like WeChat, Taobao, Bilibili, Douyin, Weibo, and more. It can handle text, voice, and image inputs, access external resources through plugins, and customize enterprise AI applications based on proprietary knowledge bases. Users can set custom replies, utilize ChatGPT interface for intelligent responses, send images and binary files, and create personalized chatbots using knowledge base files. The tool also features platform-specific plugin systems for accessing external resources and supports enterprise AI applications customization.

FastGPT is a knowledge base Q&A system based on the LLM large language model, providing out-of-the-box data processing, model calling and other capabilities. At the same time, you can use Flow to visually arrange workflows to achieve complex Q&A scenarios!

ChatGPT Auto Refresh is a userscript that keeps ChatGPT sessions fresh by eliminating network errors and Cloudflare checks. It removes the 10-minute time limit from conversations when Chat History is disabled, ensuring a seamless experience. The tool is safe, lightweight, and a time-saver, allowing users to keep their sessions alive without constant copy/paste/refresh actions. It works even in background tabs, providing convenience and efficiency for users interacting with ChatGPT. The tool relies on the chatgpt.js library and is compatible with various browsers using Tampermonkey, making it accessible to a wide range of users.

AI-VTuber is a highly customizable AI VTuber project that integrates with Bilibili live streaming, uses Zhifu API as the language base model, and includes intent recognition, short-term and long-term memory, cognitive library building, song library creation, and integration with various voice conversion, voice synthesis, image generation, and digital human projects. It provides a user-friendly client for operations. The project supports virtual VTuber template construction, multi-person device template management, real-time switching of virtual VTuber templates, and offers various practical tools such as video/audio crawlers, voice recognition, voice separation, voice synthesis, voice conversion, AI drawing, and image background removal.

FisherAI is a Chrome extension designed to improve learning efficiency. It supports automatic summarization, web and video translation, multi-turn dialogue, and various large language models such as gpt/azure/gemini/deepseek/mistral/groq/yi/moonshot. Users can enjoy flexible and powerful AI tools with FisherAI.

Deploy langgenius/dify, an LLM based chat bot app on kubernetes with helm chart.

Lobe CLI Toolbox is an AI CLI Toolbox designed to enhance git commit and i18n workflow efficiency. It includes tools like Lobe Commit for generating Gitmoji-based commit messages and Lobe i18n for automating the i18n translation process. The toolbox also features Lobe label for automatically copying issues labels from a template repo. It supports features such as automatic splitting of large files, incremental updates, and customization options for the OpenAI model, API proxy, and temperature.

FluidFrames.RIFE is a Windows app powered by RIFE AI to create frame-generated and slowmotion videos. It is written in Python and utilizes external packages such as torch, onnxruntime-directml, customtkinter, OpenCV, moviepy, and Nuitka. The app features an elegant GUI, video frame generation at different speeds, video slow motion, video resizing, multiple GPU support, and compatibility with various video formats. Future versions aim to support different GPU types, enhance the GUI, include audio processing, optimize video processing speed, and introduce new features like saving AI-generated frames and supporting different RIFE AI models.

LLMFarm is an iOS and MacOS app designed to work with large language models (LLM). It allows users to load different LLMs with specific parameters, test the performance of various LLMs on iOS and macOS, and identify the most suitable model for their projects. The tool is based on ggml and llama.cpp by Georgi Gerganov and incorporates sources from rwkv.cpp by saharNooby, Mia by byroneverson, and LlamaChat by alexrozanski. LLMFarm features support for MacOS (13+) and iOS (16+), various inferences and sampling methods, Metal compatibility (not supported on Intel Mac), model setting templates, LoRA adapters support, LoRA finetune support, LoRA export as model support, and more. It also offers a range of inferences including LLaMA, GPTNeoX, Replit, GPT2, Starcoder, RWKV, Falcon, MPT, Bloom, and others. Additionally, it supports multimodal models like LLaVA, Obsidian, and MobileVLM. Users can customize inference options through JSON files and access supported models for download.

BraveGPT is a userscript that brings the power of ChatGPT to Brave Search. It allows users to engage with a conversational AI assistant directly within their search results, providing instant and personalized responses to their queries. BraveGPT is powered by GPT-4, the latest and most advanced language model from OpenAI, ensuring accurate and comprehensive answers. With BraveGPT, users can ask questions, get summaries, generate creative content, and more, all without leaving the Brave Search interface. The tool is easy to install and use, making it accessible to users of all levels. BraveGPT is a valuable addition to the Brave Search experience, enhancing its capabilities and providing users with a more efficient and informative search experience.

GoogleGPT is a browser extension that brings the power of ChatGPT to Google Search. With GoogleGPT, you can ask ChatGPT questions and get answers directly in your search results. You can also use GoogleGPT to generate text, translate languages, and more. GoogleGPT is compatible with all major browsers, including Chrome, Firefox, Edge, and Safari.

LLMFarm_core.swift is a Swift library designed to work with large language models (LLM). It enables users to load different LLMs with specific parameters. The library supports MacOS (13+) and iOS (16+), offering various inferences and sampling methods. It includes features such as Metal support (not compatible with Intel Mac), model setting templates, LoRA adapters support, and LoRA train support. The library is based on ggml and llama.cpp by Georgi Gerganov, with additional sources from rwkv.cpp by saharNooby and Mia by byroneverson.

chatgpt.js is a powerful JavaScript library that allows for super easy interaction w/ the ChatGPT DOM. * Feature-rich * Object-oriented * Easy-to-use * Lightweight (yet optimally performant)

This repository is a collection of papers on leveraging Large Language Models (LLMs) in Graph Tasks. It provides a comprehensive overview of how LLMs can enhance graph-related tasks by combining them with traditional Graph Neural Networks (GNNs). The integration of LLMs with GNNs allows for capturing both structural and contextual aspects of nodes in graph data, leading to more powerful graph learning. The repository includes summaries of various models that leverage LLMs to assist in graph-related tasks, along with links to papers and code repositories for further exploration.

ChatGPT Auto-Continue is a userscript that automatically continues generating ChatGPT responses when chats cut off. It relies on the powerful chatgpt.js library and is easy to install and use. Simply install Tampermonkey and ChatGPT Auto-Continue, and visit chat.openai.com as normal. Multi-reply conversations will automatically continue generating when cut-off!

DuckDuckGPT brings the magic of ChatGPT to DDG (powered by GPT-4!). DuckDuckGPT is a browser extension that allows you to use ChatGPT within DuckDuckGo. This means you can ask ChatGPT questions, get help with tasks, and generate creative content, all without leaving DuckDuckGo. DuckDuckGPT is easy to use. Once you have installed the extension, simply type your question into the DuckDuckGo search bar and hit enter. ChatGPT will then generate a response that will appear below the search results. DuckDuckGPT is a powerful tool that can help you with a wide variety of tasks. Here are just a few examples of what you can use it for: * Get help with research * Write essays and other creative content * Translate languages * Get coding help * Answer trivia questions * And much more! DuckDuckGPT is still in development, but it is already a very powerful tool. As GPT-4 continues to improve, DuckDuckGPT will only get better. So if you are looking for a way to make your DuckDuckGo searches more productive, be sure to give DuckDuckGPT a try.

ChatGPT-On-CS is an intelligent chatbot tool based on large models, supporting various platforms like WeChat, Taobao, Bilibili, Douyin, Weibo, and more. It can handle text, voice, and image inputs, access external resources through plugins, and customize enterprise AI applications based on proprietary knowledge bases. Users can set custom replies, utilize ChatGPT interface for intelligent responses, send images and binary files, and create personalized chatbots using knowledge base files. The tool also features platform-specific plugin systems for accessing external resources and supports enterprise AI applications customization.

ChatGPT-Plugins is a repository containing plugins for ChatGPT-Next-Web. These plugins provide additional functionalities and features to enhance the ChatGPT experience. Users can easily deploy these plugins using Vercel or HuggingFace. The repository includes README files in English and Vietnamese for user guidance.

OpenKF (Open Knowledge Flow) is an online intelligent customer service system. It is an open-source customer service system based on OpenIM, supporting LLM (Local Knowledgebase) customer service and multi-channel customer service. It is easy to integrate with third-party systems, deploy, and perform secondary development. The system provides features like login page, config page, dashboard page, platform page, and session page. Users can quickly get started with OpenKF by following the installation and run instructions. The architecture follows MVC design with a standardized directory structure. The community encourages involvement through community meetings, contributions, and development. OpenKF is licensed under the Apache 2.0 license.

FastWiki is an enterprise-level artificial intelligence customer service management system. It is a high-performance knowledge base system designed for large-scale information retrieval and intelligent search. Leveraging Microsoft's Semantic Kernel for deep learning and natural language processing, combined with .NET 8 and React framework, it provides an efficient, user-friendly, and scalable intelligent vector search platform. The system aims to offer an intelligent search solution that can understand and process complex queries, assisting users in quickly and accurately obtaining the needed information.

Awesome-LLM-RAG-Application is a repository that provides resources and information about applications based on Large Language Models (LLM) with Retrieval-Augmented Generation (RAG) pattern. It includes a survey paper, GitHub repo, and guides on advanced RAG techniques. The repository covers various aspects of RAG, including academic papers, evaluation benchmarks, downstream tasks, tools, and technologies. It also explores different frameworks, preprocessing tools, routing mechanisms, evaluation frameworks, embeddings, security guardrails, prompting tools, SQL enhancements, LLM deployment, observability tools, and more. The repository aims to offer comprehensive knowledge on RAG for readers interested in exploring and implementing LLM-based systems and products.

ChatGPT-On-CS is an intelligent chatbot tool based on large models, supporting various platforms like WeChat, Taobao, Bilibili, Douyin, Weibo, and more. It can handle text, voice, and image inputs, access external resources through plugins, and customize enterprise AI applications based on proprietary knowledge bases. Users can set custom replies, utilize ChatGPT interface for intelligent responses, send images and binary files, and create personalized chatbots using knowledge base files. The tool also features platform-specific plugin systems for accessing external resources and supports enterprise AI applications customization.

Call GPT is a voice application that utilizes Deepgram for Speech to Text, elevenlabs for Text to Speech, and OpenAI for GPT prompt completion. It allows users to chat with ChatGPT on the phone, providing better transcription, understanding, and speaking capabilities than traditional IVR systems. The app returns responses with low latency, allows user interruptions, maintains chat history, and enables GPT to call external tools. It coordinates data flow between Deepgram, OpenAI, ElevenLabs, and Twilio Media Streams, enhancing voice interactions.

A comprehensive repository of resources for Chinese large language models (LLMs), including data processing tools, fine-tuning frameworks, inference libraries, evaluation platforms, RAG engines, agent frameworks, books, courses, tutorials, and tips. The repository covers a wide range of tools and resources for working with LLMs, from data labeling and processing to model fine-tuning, inference, evaluation, and application development. It also includes resources for learning about LLMs through books, courses, and tutorials, as well as insights and strategies from building with LLMs.

Hailo TAPPAS is a set of full application examples that implement pipeline elements and pre-trained AI tasks. It demonstrates Hailo's system integration scenarios on predefined systems, aiming to accelerate time to market, simplify integration with Hailo's runtime SW stack, and provide a starting point for customers to fine-tune their applications. The tool supports both Hailo-15 and Hailo-8, offering various example applications optimized for different common hosts. TAPPAS includes pipelines for single network, two network, and multi-stream processing, as well as high-resolution processing via tiling. It also provides example use case pipelines like License Plate Recognition and Multi-Person Multi-Camera Tracking. The tool is regularly updated with new features, bug fixes, and platform support.

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.

Pixeltable is a Python library designed for ML Engineers and Data Scientists to focus on exploration, modeling, and app development without the need to handle data plumbing. It provides a declarative interface for working with text, images, embeddings, and video, enabling users to store, transform, index, and iterate on data within a single table interface. Pixeltable is persistent, acting as a database unlike in-memory Python libraries such as Pandas. It offers features like data storage and versioning, combined data and model lineage, indexing, orchestration of multimodal workloads, incremental updates, and automatic production-ready code generation. The tool emphasizes transparency, reproducibility, cost-saving through incremental data changes, and seamless integration with existing Python code and libraries.

Wave Apps is a directory of sample applications built on H2O Wave, allowing users to build AI apps faster. The apps cover various use cases such as explainable hotel ratings, human-in-the-loop credit risk assessment, mitigating churn risk, online shopping recommendations, and sales forecasting EDA. Users can download, modify, and integrate these sample apps into their own projects to learn about app development and AI model deployment.