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

AP-PLUGIN is an AI drawing plugin for the Yunzai series robot framework, allowing you to have a convenient AI drawing experience in the input box. It uses the open source Stable Diffusion web UI as the backend, deploys it for free, and generates a variety of images with richer functions.

This repository provides a tool for forwarding SMS and call notifications using various notification methods such as Telegram, PushDeer, Bark, DingTalk, Feishu, WeCom, Pushover, email, Gotify, Inotify, and SMTP protocol. It also allows controlling devices via SMS, scheduling base station positioning, querying data usage, reporting device status, power button operations, low power mode, message queue usage for sending notifications without freezing, automatic resend on notification failure, and support for master-slave mode for message forwarding.

AIDE-Plus is a comprehensive tool for Android app development, offering support for various Java syntax versions, Gradle and Maven build systems, ProGuard, AndroidX, CMake builds, APK/AAB generation, code coloring customization, data binding, and APK signing. It also provides features like AAPT2, D8, runtimeOnly, compileOnly, libgdxNatives, manifest merging, Shizuku installation support, and syntax auto-completion. The tool aims to streamline the development process and enhance the user experience by addressing common issues and providing advanced functionalities.

This project is an intelligent dialogue customer service tool based on a large model, which supports access to platforms such as WeChat, Qianniu, Bilibili, Douyin Enterprise, Douyin, Doudian, Weibo chat, Xiaohongshu professional account operation, Xiaohongshu, Zhihu, etc. You can choose GPT3.5/GPT4.0/ Lazy Treasure Box (more platforms will be supported in the future), which can process text, voice and pictures, and access external resources such as operating systems and the Internet through plug-ins, and support enterprise AI applications customized based on their own knowledge base.

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-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.

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.

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.

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.

RealScaler is a Windows app powered by RealESRGAN AI to enhance, upscale, and de-noise photos and videos. It provides an easy-to-use GUI for upscaling images and videos using multiple AI models. The tool supports automatic image tiling and merging to avoid GPU VRAM limitations, resizing images/videos before upscaling, interpolation between original and upscaled content, and compatibility with various image and video formats. RealScaler is written in Python and requires Windows 11/10, at least 8GB RAM, and a Directx12 compatible GPU with 4GB VRAM. Future versions aim to enhance performance, support more GPUs, offer a new GUI with Windows 11 style, include audio for upscaled videos, and provide features like metadata extraction and application from original to upscaled files.

VoAPI is a new high-value/high-performance AI model interface management and distribution system. It is a closed-source tool for personal learning use only, not for commercial purposes. Users must comply with upstream AI model service providers and legal regulations. The system offers a visually appealing interface with features such as independent development documentation page support, service monitoring page configuration support, and third-party login support. Users can manage user registration time, optimize interface elements, and support features like online recharge, model pricing display, and sensitive word filtering. VoAPI also provides support for various AI models and platforms, with the ability to configure homepage templates, model information, and manufacturer information.

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!

This is an offline Japanese translator for RPGMaker games based on Mtool and the Sakura model, capable of providing high-quality offline Japanese translations. It is recommended to use the Sakura-13B-Galgame translation model, and the currently supported versions are Sakura v0.8/v0.9/v0.10pre0.

This repository is a collection of research lectures and experience sharing posts from frontline researchers in the field of AI. It aims to help individuals upgrade their research skills and knowledge through insightful talks and experiences shared by experts. The content covers various topics such as evaluating research papers, choosing research directions, research methodologies, and tips for writing high-quality scientific papers. The repository also includes discussions on academic career paths, research ethics, and the emotional aspects of research work. Overall, it serves as a valuable resource for individuals interested in advancing their research capabilities in the field of AI.

BMW MD is a simple WhatsApp user BOT created by Ibrahim Tech. It allows users to scan pairing codes or QR codes to connect to WhatsApp and deploy the bot on Heroku. The bot can be used to perform various tasks such as sending messages, receiving messages, and managing contacts. It is released under the MIT License and contributions are welcome.

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

Next.js AI Chatbot is an open-source app template for building AI chatbots using Next.js, Vercel AI SDK, OpenAI, and Vercel KV. It includes features like Next.js App Router, React Server Components, Vercel AI SDK for streaming chat UI, support for various AI models, Tailwind CSS styling, Radix UI for headless components, chat history management, rate limiting, session storage with Vercel KV, and authentication with NextAuth.js. The template allows easy deployment to Vercel and customization of AI model providers.

The ChatGPT Telegram Bot is a powerful Telegram bot that utilizes various GPT models, including GPT3.5, GPT4, GPT4 Turbo, GPT4 Vision, DALL·E 3, Groq Mixtral-8x7b/LLaMA2-70b, and Claude2.1/Claude3 opus/sonnet API. It enables users to engage in efficient conversations and information searches on Telegram. The bot supports multiple AI models, online search with DuckDuckGo and Google, user-friendly interface, efficient message processing, document interaction, Markdown rendering, and convenient deployment options like Zeabur, Replit, and Docker. Users can set environment variables for configuration and deployment. The bot also provides Q&A functionality, supports model switching, and can be deployed in group chats with whitelisting. The project is open source under GPLv3 license.

This repository showcases how to build a simple LLM-based chatbot for answering questions based on documents using retrieval augmented generation (RAG) technique. It also provides guidance on deploying the chatbot using Podman or on the OpenShift Container Platform. The workshop associated with this repository introduces participants to LLMs & RAG concepts and demonstrates how to customize the chatbot for specific purposes. The software stack relies on open-source tools like streamlit, LlamaIndex, and local open LLMs via Ollama, making it accessible for GPU-constrained environments.

LangChat is an enterprise AIGC project solution in the Java ecosystem. It integrates AIGC large model functionality on top of the RBAC permission system to help enterprises quickly customize AI knowledge bases and enterprise AI robots. It supports integration with various large models such as OpenAI, Gemini, Ollama, Azure, Zhifu, Alibaba Tongyi, Baidu Qianfan, etc. The project is developed solely by TyCoding and is continuously evolving. It features multi-modality, dynamic configuration, knowledge base support, advanced RAG capabilities, function call customization, multi-channel deployment, workflows visualization, AIGC client application, and more.

The ai-sdk-chrome-ai repository is an open-source chatbot built with Next.js, the Vercel AI SDK, and the Chrome AI provider. It features Next.js App Router, Vercel AI SDK for interacting with the Gemini Nano model, shadcn/ui, Tailwind CSS styling, and Radix UI for headless component primitives. Users can deploy their own version of the chatbot to Vercel with one click and run it locally by installing dependencies and running the dev server. The repository provides a template for creating and customizing a chatbot powered by AI technology.

MinIO is a High Performance Object Storage released under GNU Affero General Public License v3.0. It is API compatible with Amazon S3 cloud storage service. Use MinIO to build high performance infrastructure for machine learning, analytics and application data workloads.

This repository contains assets related to AI/ML workloads on Google Kubernetes Engine (GKE). Run optimized AI/ML workloads with Google Kubernetes Engine (GKE) platform orchestration capabilities. A robust AI/ML platform considers the following layers: Infrastructure orchestration that support GPUs and TPUs for training and serving workloads at scale Flexible integration with distributed computing and data processing frameworks Support for multiple teams on the same infrastructure to maximize utilization of resources

Kong, or Kong API Gateway, is a cloud-native, platform-agnostic, scalable API Gateway distinguished for its high performance and extensibility via plugins. It also provides advanced AI capabilities with multi-LLM support. By providing functionality for proxying, routing, load balancing, health checking, authentication (and more), Kong serves as the central layer for orchestrating microservices or conventional API traffic with ease. Kong runs natively on Kubernetes thanks to its official Kubernetes Ingress Controller.

AI-in-a-Box is a curated collection of solution accelerators that can help engineers establish their AI/ML environments and solutions rapidly and with minimal friction, while maintaining the highest standards of quality and efficiency. It provides essential guidance on the responsible use of AI and LLM technologies, specific security guidance for Generative AI (GenAI) applications, and best practices for scaling OpenAI applications within Azure. The available accelerators include: Azure ML Operationalization in-a-box, Edge AI in-a-box, Doc Intelligence in-a-box, Image and Video Analysis in-a-box, Cognitive Services Landing Zone in-a-box, Semantic Kernel Bot in-a-box, NLP to SQL in-a-box, Assistants API in-a-box, and Assistants API Bot in-a-box.

This repository contains reference architectures and test cases for distributed model training with Amazon SageMaker Hyperpod, AWS ParallelCluster, AWS Batch, and Amazon EKS. The test cases cover different types and sizes of models as well as different frameworks and parallel optimizations (Pytorch DDP/FSDP, MegatronLM, NemoMegatron...).

The AWS Generative AI Constructs Library is an open-source extension of the AWS Cloud Development Kit (AWS CDK) that provides multi-service, well-architected patterns for quickly defining solutions in code to create predictable and repeatable infrastructure, called constructs. The goal of AWS Generative AI CDK Constructs is to help developers build generative AI solutions using pattern-based definitions for their architecture. The patterns defined in AWS Generative AI CDK Constructs are high level, multi-service abstractions of AWS CDK constructs that have default configurations based on well-architected best practices. The library is organized into logical modules using object-oriented techniques to create each architectural pattern model.

OpenVINO™ Model Server (OVMS) is a high-performance system for serving models. Implemented in C++ for scalability and optimized for deployment on Intel architectures, the model server uses the same architecture and API as TensorFlow Serving and KServe while applying OpenVINO for inference execution. Inference service is provided via gRPC or REST API, making deploying new algorithms and AI experiments easy.

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