Sparka AI is a multi-provider AI chat tool that allows users to access various AI models like Claude, GPT-5, Gemini, and Grok through a single interface. It offers features such as document analysis, image generation, code execution, and research tools without the need for multiple subscriptions. The tool is open-source, production-ready, and provides capabilities for collaboration, secure authentication, attachment support, AI-powered image generation, syntax highlighting, resumable streams, chat branching, chat sharing, deep research, code execution, document creation, and web analytics. Built with modern technologies for scalability and performance, Sparka AI integrates with Vercel AI SDK, tRPC, Drizzle ORM, PostgreSQL, Redis, and AI SDK Gateway.

KitchenAI is an open-source toolkit designed to simplify AI development by serving as an AI backend and LLMOps solution. It aims to empower developers to focus on delivering results without being bogged down by AI infrastructure complexities. With features like simplifying AI integration, providing an AI backend, and empowering developers, KitchenAI streamlines the process of turning AI experiments into production-ready APIs. It offers built-in LLMOps features, is framework-agnostic and extensible, and enables faster time-to-production. KitchenAI is suitable for application developers, AI developers & data scientists, and platform & infra engineers, allowing them to seamlessly integrate AI into apps, deploy custom AI techniques, and optimize AI services with a modular framework. The toolkit eliminates the need to build APIs and infrastructure from scratch, making it easier to deploy AI code as production-ready APIs in minutes. KitchenAI also provides observability, tracing, and evaluation tools, and offers a Docker-first deployment approach for scalability and confidence.

The Eureka Framework is an open-source toolkit that leverages advanced Artificial Intelligence and Decentralized Science principles to revolutionize scientific discovery. It enables researchers, developers, and decentralized organizations to explore scientific papers, conduct AI-driven experiments, monetize research contributions, provide token-gated access to AI agents, and customize AI agents for specific research domains. The framework also offers features like a RESTful API, robust scheduler for task automation, and webhooks for real-time notifications, empowering users to automate research tasks, enhance productivity, and foster a committed research community.

Open-WebUI-Functions is a collection of Python-based functions that extend Open WebUI with custom pipelines, filters, and integrations. Users can interact with AI models, process data efficiently, and customize the Open WebUI experience. It includes features like custom pipelines, data processing filters, Azure AI support, N8N workflow integration, flexible configuration, secure API key management, and support for both streaming and non-streaming processing. The functions require an active Open WebUI instance, may need external AI services like Azure AI, and admin access for installation. Security features include automatic encryption of sensitive information like API keys. Pipelines include Azure AI Foundry, N8N, Infomaniak, and Google Gemini. Filters like Time Token Tracker measure response time and token usage. Integrations with Azure AI, N8N, Infomaniak, and Google are supported. Contributions are welcome, and the project is licensed under Apache License 2.0.

Monadic Chat is a locally hosted web application designed to create and utilize intelligent chatbots. It provides a Linux environment on Docker to GPT and other LLMs, enabling the execution of advanced tasks that require external tools. The tool supports voice interaction, image and video recognition and generation, and AI-to-AI chat, making it useful for using AI and developing various applications. It is available for Mac, Windows, and Linux (Debian/Ubuntu) with easy-to-use installers.

Lidar AI Solution is a highly optimized repository for self-driving 3D lidar, providing solutions for sparse convolution, BEVFusion, CenterPoint, OSD, and Conversion. It includes CUDA and TensorRT implementations for various tasks such as 3D sparse convolution, BEVFusion, CenterPoint, PointPillars, V2XFusion, cuOSD, cuPCL, and YUV to RGB conversion. The repository offers easy-to-use solutions, high accuracy, low memory usage, and quantization options for different tasks related to self-driving technology.

AI Coding Assistant is a free and open-source IntelliJ plugin that leverages cutting-edge Language Model APIs to enhance developers' coding experience. It seamlessly integrates with various leading LLM APIs, offers an intuitive toolbar UI, and allows granular control over API requests. With features like Code & Patch Chat, Planning with AI Agents, Markdown visualization, and versatile text processing capabilities, this tool aims to streamline coding workflows and boost productivity.

Riona-AI-Agent is a versatile AI chatbot designed to assist users in various tasks. It utilizes natural language processing and machine learning algorithms to understand user queries and provide accurate responses. The chatbot can be integrated into websites, applications, and messaging platforms to enhance user experience and streamline communication. With its customizable features and easy deployment, Riona-AI-Agent is suitable for businesses, developers, and individuals looking to automate customer support, provide information, and engage with users in a conversational manner.

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.

Ivy-Framework is a powerful tool for building internal applications with AI assistance using C# codebase. It provides a CLI for project initialization, authentication integrations, database support, LLM code generation, secrets management, container deployment, hot reload, dependency injection, state management, routing, and external widget framework. Users can easily create data tables for sorting, filtering, and pagination. The framework offers a seamless integration of front-end and back-end development, making it ideal for developing robust internal tools and dashboards.

Curiso AI is an infinite canvas platform that connects nodes and AI services to explore ideas without repetition. It empowers advanced users to unlock richer AI interactions. Features include multi OS support, infinite canvas, multiple AI provider integration, local AI inference provider integration, custom model support, model metrics, RAG support, local Transformers.js embedding models, inference parameters customization, multiple boards, vision model support, customizable interface, node-based conversations, and secure local encrypted storage. Curiso also offers a Solana token for exclusive access to premium features and enhanced AI capabilities.

Transformer Lab is an app that allows users to experiment with Large Language Models by providing features such as one-click download of popular models, finetuning across different hardware, RLHF and Preference Optimization, working with LLMs across different operating systems, chatting with models, using different inference engines, evaluating models, building datasets for training, calculating embeddings, providing a full REST API, running in the cloud, converting models across platforms, supporting plugins, embedded Monaco code editor, prompt editing, inference logs, all through a simple cross-platform GUI.

PocketPal AI is a versatile virtual assistant tool designed to streamline daily tasks and enhance productivity. It leverages artificial intelligence technology to provide personalized assistance in managing schedules, organizing information, setting reminders, and more. With its intuitive interface and smart features, PocketPal AI aims to simplify users' lives by automating routine activities and offering proactive suggestions for optimal time management and task prioritization.

Apt. is a free and open-source AI productivity tool designed to enhance user productivity while ensuring privacy and data security. It offers efficient AI solutions such as built-in ChatGPT, batch image and video processing, and more. Key features include free and open-source code, privacy protection through local deployment, offline operation, no installation needed, and multi-language support. Integrated AI models cover ChatGPT for intelligent conversations, image processing features like super-resolution and color restoration, and video processing capabilities including super-resolution and frame interpolation. Future plans include integrating more AI models. The tool provides user guides and technical support via email and various platforms, with a user-friendly interface for easy navigation.

This repository is dedicated to learning about Low-Code Full-Stack Agentic AI Development. It provides material for building modern AI-powered applications using a low-code full-stack approach. The main tools covered are UXPilot for UI/UX mockups, Lovable.dev for frontend applications, n8n for AI agents and workflows, Supabase for backend data storage, authentication, and vector search, and Model Context Protocol (MCP) for integration. The focus is on prompt and context engineering as the foundation for working with AI systems, enabling users to design, develop, and deploy AI-driven full-stack applications faster, smarter, and more reliably.

Cedar OS is an open-source framework that bridges the gap between AI agents and React applications, enabling the creation of AI-native applications where agents can interact with the application state like users. It focuses on providing intuitive and powerful ways for humans to interact with AI through features like full state integration, real-time streaming, voice-first design, and flexible architecture. Cedar OS offers production-ready chat components, agentic state management, context-aware mentions, voice integration, spells & quick actions, and fully customizable UI. It differentiates itself by offering a true AI-native architecture, developer-first experience, production-ready features, and extensibility. Built with TypeScript support, Cedar OS is designed for developers working on ambitious AI-native applications.

The Google Cloud Document AI Samples repository contains code samples and Community Samples demonstrating how to analyze, classify, and search documents using Google Cloud Document AI. It includes various projects showcasing different functionalities such as integrating with Google Drive, processing documents using Python, content moderation with Dialogflow CX, fraud detection, language extraction, paper summarization, tax processing pipeline, and more. The repository also provides access to test document files stored in a publicly-accessible Google Cloud Storage Bucket. Additionally, there are codelabs available for optical character recognition (OCR), form parsing, specialized processors, and managing Document AI processors. Community samples, like the PDF Annotator Sample, are also included. Contributions are welcome, and users can seek help or report issues through the repository's issues page. Please note that this repository is not an officially supported Google product and is intended for demonstrative purposes only.

The StepChat Free service provides high-speed streaming output, multi-turn dialogue support, online search support, long document interpretation, and image parsing. It offers zero-configuration deployment, multi-token support, and automatic session trace cleaning. It is fully compatible with the ChatGPT interface. Additionally, it provides seven other free APIs for various services. The repository includes a disclaimer about using reverse APIs and encourages users to avoid commercial use to prevent service pressure on the official platform. It offers online testing links, showcases different demos, and provides deployment guides for Docker, Docker-compose, Render, Vercel, and native deployments. The repository also includes information on using multiple accounts, optimizing Nginx reverse proxy, and checking the liveliness of refresh tokens.

The 'unilm' repository is a collection of tools, models, and architectures for Foundation Models and General AI, focusing on tasks such as NLP, MT, Speech, Document AI, and Multimodal AI. It includes various pre-trained models, such as UniLM, InfoXLM, DeltaLM, MiniLM, AdaLM, BEiT, LayoutLM, WavLM, VALL-E, and more, designed for tasks like language understanding, generation, translation, vision, speech, and multimodal processing. The repository also features toolkits like s2s-ft for sequence-to-sequence fine-tuning and Aggressive Decoding for efficient sequence-to-sequence decoding. Additionally, it offers applications like TrOCR for OCR, LayoutReader for reading order detection, and XLM-T for multilingual NMT.

searchGPT is an open-source project that aims to build a search engine based on Large Language Model (LLM) technology to provide natural language answers. It supports web search with real-time results, file content search, and semantic search from sources like the Internet. The tool integrates LLM technologies such as OpenAI and GooseAI, and offers an easy-to-use frontend user interface. The project is designed to provide grounded answers by referencing real-time factual information, addressing the limitations of LLM's training data. Contributions, especially from frontend developers, are welcome under the MIT License.

This repository contains tutorials for using Large Language Models (LLMs) in the U.S. Department of Defense. The tutorials utilize open-source frameworks and LLMs, allowing users to run them in their own cloud environments. The repository is maintained by the Defense Digital Service and welcomes contributions from users.

LARS is an application that enables users to run Large Language Models (LLMs) locally on their devices, upload their own documents, and engage in conversations where the LLM grounds its responses with the uploaded content. The application focuses on Retrieval Augmented Generation (RAG) to increase accuracy and reduce AI-generated inaccuracies. LARS provides advanced citations, supports various file formats, allows follow-up questions, provides full chat history, and offers customization options for LLM settings. Users can force enable or disable RAG, change system prompts, and tweak advanced LLM settings. The application also supports GPU-accelerated inferencing, multiple embedding models, and text extraction methods. LARS is open-source and aims to be the ultimate RAG-centric LLM application.

Eagle is a family of Vision-Centric High-Resolution Multimodal LLMs that enhance multimodal LLM perception using a mix of vision encoders and various input resolutions. The model features a channel-concatenation-based fusion for vision experts with different architectures and knowledge, supporting up to over 1K input resolution. It excels in resolution-sensitive tasks like optical character recognition and document understanding.

ERAG is an advanced system that combines lexical, semantic, text, and knowledge graph searches with conversation context to provide accurate and contextually relevant responses. This tool processes various document types, creates embeddings, builds knowledge graphs, and uses this information to answer user queries intelligently. It includes modules for interacting with web content, GitHub repositories, and performing exploratory data analysis using various language models.

Weave is a toolkit for developing Generative AI applications, built by Weights & Biases. With Weave, you can log and debug language model inputs, outputs, and traces; build rigorous, apples-to-apples evaluations for language model use cases; and organize all the information generated across the LLM workflow, from experimentation to evaluations to production. Weave aims to bring rigor, best-practices, and composability to the inherently experimental process of developing Generative AI software, without introducing cognitive overhead.

LLMStack is a no-code platform for building generative AI agents, workflows, and chatbots. It allows users to connect their own data, internal tools, and GPT-powered models without any coding experience. LLMStack can be deployed to the cloud or on-premise and can be accessed via HTTP API or triggered from Slack or Discord.

The VisionCraft API is a free API for using over 100 different AI models. From images to sound.

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.

PyRIT is an open access automation framework designed to empower security professionals and ML engineers to red team foundation models and their applications. It automates AI Red Teaming tasks to allow operators to focus on more complicated and time-consuming tasks and can also identify security harms such as misuse (e.g., malware generation, jailbreaking), and privacy harms (e.g., identity theft). The goal is to allow researchers to have a baseline of how well their model and entire inference pipeline is doing against different harm categories and to be able to compare that baseline to future iterations of their model. This allows them to have empirical data on how well their model is doing today, and detect any degradation of performance based on future improvements.

Tabby is a self-hosted AI coding assistant, offering an open-source and on-premises alternative to GitHub Copilot. It boasts several key features: * Self-contained, with no need for a DBMS or cloud service. * OpenAPI interface, easy to integrate with existing infrastructure (e.g Cloud IDE). * Supports consumer-grade GPUs.

SPEAR (Simulator for Photorealistic Embodied AI Research) is a powerful tool for training embodied agents. It features 300 unique virtual indoor environments with 2,566 unique rooms and 17,234 unique objects that can be manipulated individually. Each environment is designed by a professional artist and features detailed geometry, photorealistic materials, and a unique floor plan and object layout. SPEAR is implemented as Unreal Engine assets and provides an OpenAI Gym interface for interacting with the environments via Python.

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.