Gemini Next Chat is an open-source, extensible high-performance Gemini chatbot framework that supports one-click free deployment of private Gemini web applications. It provides a simple interface with image recognition and voice conversation, supports multi-modal models, talk mode, visual recognition, assistant market, support plugins, conversation list, full Markdown support, privacy and security, PWA support, well-designed UI, fast loading speed, static deployment, and multi-language support.

RWKV Runner is a project designed to simplify the usage of large language models by automating various processes. It provides a lightweight executable program and is compatible with the OpenAI API. Users can deploy the backend on a server and use the program as a client. The project offers features like model management, VRAM configurations, user-friendly chat interface, WebUI option, parameter configuration, model conversion tool, download management, LoRA Finetune, and multilingual localization. It can be used for various tasks such as chat, completion, composition, and model inspection.

PySpur is a graph-based editor designed for LLM workflows, offering modular building blocks for easy workflow creation and debugging at node level. It allows users to evaluate final performance and promises self-improvement features in the future. PySpur is easy-to-hack, supports JSON configs for workflow graphs, and is lightweight with minimal dependencies, making it a versatile tool for workflow management in the field of AI and machine learning.

MLE-Agent is an intelligent companion designed for machine learning engineers and researchers. It features autonomous baseline creation, integration with Arxiv and Papers with Code, smart debugging, file system organization, comprehensive tools integration, and an interactive CLI chat interface for seamless AI engineering and research workflows.

ESP-AI provides a complete AI conversation solution for your development board, including IAT+LLM+TTS integration solutions for ESP32 series development boards. It can be injected into projects without affecting existing ones. By providing keys from platforms like iFlytek, Jiling, and local services, you can run the services without worrying about interactions between services or between development boards and services. The project's server-side code is based on Node.js, and the hardware code is based on Arduino IDE.

Whisper-WebUI is a Gradio-based browser interface for Whisper, serving as an Easy Subtitle Generator. It supports generating subtitles from various sources such as files, YouTube, and microphone. The tool also offers speech-to-text and text-to-text translation features, utilizing Facebook NLLB models and DeepL API. Users can translate subtitle files from other languages to English and vice versa. The project integrates faster-whisper for improved VRAM usage and transcription speed, providing efficiency metrics for optimized whisper models. Additionally, users can choose from different Whisper models based on size and language requirements.

Airshipper is a cross-platform Veloren launcher that allows users to update/download and start nightly builds of the game. It features a fancy UI with self-updating capabilities on Windows. Users can compile it from source and also have the option to install Airshipper-Server for advanced configurations. Note that Airshipper is still in development and may not be stable for all users.

Airflint is a tool designed to enforce best practices for all your Airflow Directed Acyclic Graphs (DAGs). It is currently in the alpha stage and aims to help users adhere to recommended practices when working with Airflow. Users can install Airflint from PyPI and integrate it into their existing Airflow environment to improve DAG quality. The tool provides rules for function-level imports and jinja template syntax usage, among others, to enhance the development process of Airflow DAGs.

ByteDance's Piano Transcription is a PyTorch implementation for transcribing piano recordings into MIDI files with pedals. This repository provides a simple GUI and packaging for Windows and Nix on Linux/macOS. It supports using GPU for inference and includes CLI usage. Users can upgrade the tool and report issues to the upstream project. The tool focuses on providing MIDI files, and any other improvements to transcription results should be directed to the original project.

TheoremExplainAgent is an AI system that generates long-form Manim videos to visually explain theorems, proving its deep understanding while uncovering reasoning flaws that text alone often hides. The codebase for the paper 'TheoremExplainAgent: Towards Multimodal Explanations for LLM Theorem Understanding' is available in this repository. It provides a tool for creating multimodal explanations for theorem understanding using AI technology.

Quark Engine is an AI-powered tool designed for analyzing Android APK files. It focuses on enhancing the detection process for auto-suggestion, enabling users to create detection workflows without coding. The tool offers an intuitive drag-and-drop interface for workflow adjustments and updates. Quark Agent, the core component, generates Quark Script code based on natural language input and feedback. The project is committed to providing a user-friendly experience for designing detection workflows through textual and visual methods. Various features are still under development and will be rolled out gradually.

The Agentic Radar is a security scanner designed to analyze and assess agentic systems for security and operational insights. It helps users understand how agentic systems function, identify potential vulnerabilities, and create security reports. The tool includes workflow visualization, tool identification, and vulnerability mapping, providing a comprehensive HTML report for easy reviewing and sharing. It simplifies the process of assessing complex workflows and multiple tools used in agentic systems, offering a structured view of potential risks and security frameworks.

E2B Sandbox is a secure sandboxed cloud environment made for AI agents and AI apps. Sandboxes allow AI agents and apps to have long running cloud secure environments. In these environments, large language models can use the same tools as humans do. For example: * Cloud browsers * GitHub repositories and CLIs * Coding tools like linters, autocomplete, "go-to defintion" * Running LLM generated code * Audio & video editing The E2B sandbox can be connected to any LLM and any AI agent or app.

VideoTuna is a codebase for text-to-video applications that integrates multiple AI video generation models for text-to-video, image-to-video, and text-to-image generation. It provides comprehensive pipelines in video generation, including pre-training, continuous training, post-training, and fine-tuning. The models in VideoTuna include U-Net and DiT architectures for visual generation tasks, with upcoming releases of a new 3D video VAE and a controllable facial video generation model.

The AI Toolkit by Ostris is a collection of tools for machine learning, specifically designed for image generation, LoRA (latent representations of attributes) extraction and manipulation, and model training. It provides a user-friendly interface and extensive documentation to make it accessible to both developers and non-developers. The toolkit is actively under development, with new features and improvements being added regularly. Some of the key features of the AI Toolkit include: - Batch Image Generation: Allows users to generate a batch of images based on prompts or text files, using a configuration file to specify the desired settings. - LoRA (lierla), LoCON (LyCORIS) Extractor: Facilitates the extraction of LoRA and LoCON representations from pre-trained models, enabling users to modify and manipulate these representations for various purposes. - LoRA Rescale: Provides a tool to rescale LoRA weights, allowing users to adjust the influence of specific attributes in the generated images. - LoRA Slider Trainer: Enables the training of LoRA sliders, which can be used to control and adjust specific attributes in the generated images, offering a powerful tool for fine-tuning and customization. - Extensions: Supports the creation and sharing of custom extensions, allowing users to extend the functionality of the toolkit with their own tools and scripts. - VAE (Variational Auto Encoder) Trainer: Facilitates the training of VAEs for image generation, providing users with a tool to explore and improve the quality of generated images. The AI Toolkit is a valuable resource for anyone interested in exploring and utilizing machine learning for image generation and manipulation. Its user-friendly interface, extensive documentation, and active development make it an accessible and powerful tool for both beginners and experienced users.

Flare is an open-source AI-powered decentralized social network client for Android/iOS/macOS, consolidating multiple social networks into one platform. It allows cross-posting content, ensures privacy, and plans to implement features like mixed timeline, AI-powered functions, and support for various platforms. The project is in active development and aims to provide a seamless social networking experience for users.

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.

WeClone is a tool that fine-tunes large language models using WeChat chat records. It utilizes approximately 20,000 integrated and effective data points, resulting in somewhat satisfactory outcomes that are occasionally humorous. The tool's effectiveness largely depends on the quantity and quality of the chat data provided. It requires a minimum of 16GB of GPU memory for training using the default chatglm3-6b model with LoRA method. Users can also opt for other models and methods supported by LLAMA Factory, which consume less memory. The tool has specific hardware and software requirements, including Python, Torch, Transformers, Datasets, Accelerate, and other optional packages like CUDA and Deepspeed. The tool facilitates environment setup, data preparation, data preprocessing, model downloading, parameter configuration, model fine-tuning, and inference through a browser demo or API service. Additionally, it offers the ability to deploy a WeChat chatbot, although users should be cautious due to the risk of account suspension by WeChat.

An AI Chatbot framework built in Python. It allows users to easily create Natural Language conversational scenarios with no coding efforts. The tool continuously learns from conversations to improve its capabilities. It can be integrated with various channels like Messenger and Slack. Users can create AI-powered chatbots without expertise in artificial intelligence.

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.