Python SDK for LiveKit enables developers to easily integrate real-time video, audio, and data features into their Python applications. By connecting to a LiveKit server, users can quickly build interactive live streaming or video call applications with minimal code. The SDK includes packages for real-time participant connection and access token generation, making it simple to create rooms and manage participants. With asyncio and aiohttp support, developers can seamlessly interact with the LiveKit server API and handle real-time communication tasks effortlessly.

The 'reolink_aio' Python package is designed to integrate Reolink devices (NVR/cameras) into your application. It implements Reolink IP NVR and camera API, allowing users to subscribe to Reolink ONVIF SWN events for real-time event notifications via webhook. The package provides functionalities to obtain and cache NVR or camera settings, capabilities, and states, as well as enable features like infrared lights, spotlight, and siren. Users can also subscribe to events, renew timers, and disconnect from the host device.

Pebblo enables developers to safely load data and promote their Gen AI app to deployment without worrying about the organization’s compliance and security requirements. The project identifies semantic topics and entities found in the loaded data and summarizes them on the UI or a PDF report.

Beyond LLM offers an all-in-one toolkit for experimentation, evaluation, and deployment of Retrieval-Augmented Generation (RAG) systems. It simplifies the process with automated integration, customizable evaluation metrics, and support for various Large Language Models (LLMs) tailored to specific needs. The aim is to reduce LLM hallucination risks and enhance reliability.

Build fast and accurate GenAI applications with GraphRAG SDK, a specialized toolkit for building Graph Retrieval-Augmented Generation (GraphRAG) systems. It integrates knowledge graphs, ontology management, and state-of-the-art LLMs to deliver accurate, efficient, and customizable RAG workflows. The SDK simplifies the development process by automating ontology creation, knowledge graph agent creation, and query handling, enabling users to interact and query their knowledge graphs effectively. It supports multi-agent systems and orchestrates agents specialized in different domains. The SDK is optimized for FalkorDB, ensuring high performance and scalability for large-scale applications. By leveraging knowledge graphs, it enables semantic relationships and ontology-driven queries that go beyond standard vector similarity, enhancing retrieval-augmented generation capabilities.

TorchRL is an open-source Reinforcement Learning (RL) library for PyTorch. It provides pytorch and **python-first** , low and high level abstractions for RL that are intended to be **efficient** , **modular** , **documented** and properly **tested**. The code is aimed at supporting research in RL. Most of it is written in python in a highly modular way, such that researchers can easily swap components, transform them or write new ones with little effort.

StableDiffusion.NET is a tool for creating images from text prompts using stable diffusion models. It allows users to build models with various configurations and options, supporting GPU acceleration for faster processing. The tool provides flexibility in choosing backends and integrating native libraries. Users can easily convert text prompts into images with default or custom parameters, and save the resulting images in PNG format. Additionally, users can extend the tool's functionality by writing custom extensions or installing pre-built extension sets like HPPH.System.Drawing and HPPH.SkiaSharp.

MLX-VLM is a package designed for running Vision LLMs on Mac systems using MLX. It provides a convenient way to install and utilize the package for processing large language models related to vision tasks. The tool simplifies the process of running LLMs on Mac computers, offering a seamless experience for users interested in leveraging MLX for vision-related projects.

Mobius is an AI infra platform including realtime computing and training. It is built on Ray, a distributed computing framework, and provides a number of features that make it well-suited for online machine learning tasks. These features include: * **Cross Language**: Mobius can run in multiple languages (only Python and Java are supported currently) with high efficiency. You can implement your operator in different languages and run them in one job. * **Single Node Failover**: Mobius has a special failover mechanism that only needs to rollback the failed node itself, in most cases, to recover the job. This is a huge benefit if your job is sensitive about failure recovery time. * **AutoScaling**: Mobius can generate a new graph with different configurations in runtime without stopping the job. * **Fusion Training**: Mobius can combine TensorFlow/Pytorch and streaming, then building an e2e online machine learning pipeline. Mobius is still under development, but it has already been used to power a number of real-world applications, including: * A real-time recommendation system for a major e-commerce company * A fraud detection system for a large financial institution * A personalized news feed for a major news organization If you are interested in using Mobius for your own online machine learning projects, you can find more information in the documentation.

LitData is a tool designed for blazingly fast, distributed streaming of training data from any cloud storage. It allows users to transform and optimize data in cloud storage environments efficiently and intuitively, supporting various data types like images, text, video, audio, geo-spatial, and multimodal data. LitData integrates smoothly with frameworks such as LitGPT and PyTorch, enabling seamless streaming of data to multiple machines. Key features include multi-GPU/multi-node support, easy data mixing, pause & resume functionality, support for profiling, memory footprint reduction, cache size configuration, and on-prem optimizations. The tool also provides benchmarks for measuring streaming speed and conversion efficiency, along with runnable templates for different data types. LitData enables infinite cloud data processing by utilizing the Lightning.ai platform to scale data processing with optimized machines.

Amadeus Python SDK provides a rich set of APIs for the travel industry. It allows users to make API calls for various travel-related tasks such as flight offers search, hotel bookings, trip purpose prediction, flight delay prediction, airport on-time performance, travel recommendations, and more. The SDK conveniently maps API paths to similar paths, making it easy to interact with the Amadeus APIs. Users can initialize the client with their API key and secret, make API calls, handle responses, and enable logging for debugging purposes. The SDK documentation includes detailed information about each SDK method, arguments, and return types.

aioapns is a Python library designed for sending push-notifications to iOS devices via Apple Push Notification Service. It provides an efficient client through asynchronous HTTP2 protocol for use with Python's asyncio framework. With features like internal connection pool, support for different types of connections, setting TTL and priority for notifications, and more, aioapns is a versatile tool for developers looking to send push notifications to iOS devices.

Ichigo is a local real-time voice AI tool that uses an early fusion technique to extend a text-based LLM to have native 'listening' ability. It is an open research experiment with improved multiturn capabilities and the ability to refuse processing inaudible queries. The tool is designed for open data, open weight, on-device Siri-like functionality, inspired by Meta's Chameleon paper. Ichigo offers a web UI demo and Gradio web UI for users to interact with the tool. It has achieved enhanced MMLU scores, stronger context handling, advanced noise management, and improved multi-turn capabilities for a robust user experience.

Deep Java Library (DJL) is an open-source, high-level, engine-agnostic Java framework for deep learning. It is designed to be easy to get started with and simple to use for Java developers. DJL provides a native Java development experience and allows users to integrate machine learning and deep learning models with their Java applications. The framework is deep learning engine agnostic, enabling users to switch engines at any point for optimal performance. DJL's ergonomic API interface guides users with best practices to accomplish deep learning tasks, such as running inference and training neural networks.

Scikit-LLM is a tool that seamlessly integrates powerful language models like ChatGPT into scikit-learn for enhanced text analysis tasks. It allows users to leverage large language models for various text analysis applications within the familiar scikit-learn framework. The tool simplifies the process of incorporating advanced language processing capabilities into machine learning pipelines, enabling users to benefit from the latest advancements in natural language processing.

GOAT (Great Onchain Agent Toolkit) is an open-source framework designed to simplify the process of making AI agents perform onchain actions by providing a provider-agnostic solution that abstracts away the complexities of interacting with blockchain tools such as wallets, token trading, and smart contracts. It offers a catalog of ready-made blockchain actions for agent developers and allows dApp/smart contract developers to develop plugins for easy access by agents. With compatibility across popular agent frameworks, support for multiple blockchains and wallet providers, and customizable onchain functionalities, GOAT aims to streamline the integration of blockchain capabilities into AI agents.

Python SDK for LiveKit enables developers to easily integrate real-time video, audio, and data features into their Python applications. By connecting to a LiveKit server, users can quickly build interactive live streaming or video call applications with minimal code. The SDK includes packages for real-time participant connection and access token generation, making it simple to create rooms and manage participants. With asyncio and aiohttp support, developers can seamlessly interact with the LiveKit server API and handle real-time communication tasks effortlessly.

Resonance is a framework designed to facilitate interoperability and messaging between services in your infrastructure and beyond. It provides AI capabilities and takes full advantage of asynchronous PHP, built on top of Swoole. With Resonance, you can: * Chat with Open-Source LLMs: Create prompt controllers to directly answer user's prompts. LLM takes care of determining user's intention, so you can focus on taking appropriate action. * Asynchronous Where it Matters: Respond asynchronously to incoming RPC or WebSocket messages (or both combined) with little overhead. You can set up all the asynchronous features using attributes. No elaborate configuration is needed. * Simple Things Remain Simple: Writing HTTP controllers is similar to how it's done in the synchronous code. Controllers have new exciting features that take advantage of the asynchronous environment. * Consistency is Key: You can keep the same approach to writing software no matter the size of your project. There are no growing central configuration files or service dependencies registries. Every relation between code modules is local to those modules. * Promises in PHP: Resonance provides a partial implementation of Promise/A+ spec to handle various asynchronous tasks. * GraphQL Out of the Box: You can build elaborate GraphQL schemas by using just the PHP attributes. Resonance takes care of reusing SQL queries and optimizing the resources' usage. All fields can be resolved asynchronously.

Aiogram bot template is a boilerplate for creating Telegram bots using Aiogram framework. It provides a solid foundation for building robust and scalable bots with a focus on code organization, database integration, and localization.

The official Node.js client for Pinecone, written in TypeScript. This client library provides a high-level interface for interacting with the Pinecone vector database service. With this client, you can create and manage indexes, upsert and query vector data, and perform other operations related to vector search and retrieval. The client is designed to be easy to use and provides a consistent and idiomatic experience for Node.js developers. It supports all the features and functionality of the Pinecone API, making it a comprehensive solution for building vector-powered applications in Node.js.

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.

Freeciv-web is an open-source turn-based strategy game that can be played in any HTML5 capable web-browser. It features in-depth gameplay, a wide variety of game modes and options. Players aim to build cities, collect resources, organize their government, and build an army to create the best civilization. The game offers both multiplayer and single-player modes, with a 2D version with isometric graphics and a 3D WebGL version available. The project consists of components like Freeciv-web, Freeciv C server, Freeciv-proxy, Publite2, and pbem for play-by-email support. Developers interested in contributing can check the GitHub issues and TODO file for tasks to work on.

Nextpy is a cutting-edge software development framework optimized for AI-based code generation. It provides guardrails for defining AI system boundaries, structured outputs for prompt engineering, a powerful prompt engine for efficient processing, better AI generations with precise output control, modularity for multiplatform and extensible usage, developer-first approach for transferable knowledge, and containerized & scalable deployment options. It offers 4-10x faster performance compared to Streamlit apps, with a focus on cooperation within the open-source community and integration of key components from various projects.

Airbadge is a Stripe addon for Auth.js that provides an easy way to create a SaaS site without writing any authentication or payment code. It integrates Stripe Checkout into the signup flow, offers over 50 OAuth options for authentication, allows route and UI restriction based on subscription, enables self-service account management, handles all Stripe webhooks, supports trials and free plans, includes subscription and plan data in the session, and is open source with a BSL license. The project also provides components for conditional UI display based on subscription status and helper functions to restrict route access. Additionally, it offers a billing endpoint with various routes for billing operations. Setup involves installing @airbadge/sveltekit, setting up a database provider for Auth.js, adding environment variables, configuring authentication and billing options, and forwarding Stripe events to localhost.

ChaKt is a multiplatform app built using Kotlin and Compose Multiplatform to demonstrate the use of Generative AI SDK for Kotlin Multiplatform to generate content using Google's Generative AI models. It features a simple chat based user interface and experience to interact with AI. The app supports mobile, desktop, and web platforms, and is built with Kotlin Multiplatform, Kotlin Coroutines, Compose Multiplatform, Generative AI SDK, Calf - File picker, and BuildKonfig. Users can contribute to the project by following the guidelines in CONTRIBUTING.md. The app is licensed under the MIT License.