videokit

Low-code, cross-platform media SDK for Unity Engine. Register at https://videokit.ai

Stars: 114

Visit

VideoKit is a full-featured user-generated content solution for Unity Engine, enabling video recording, camera streaming, microphone streaming, social sharing, and conversational interfaces. It is cross-platform, with C# source code available for inspection. Users can share media, save to camera roll, pick from camera roll, stream camera preview, record videos, remove background, caption audio, and convert text commands. VideoKit requires Unity 2022.3+ and supports Android, iOS, macOS, Windows, and WebGL platforms.

README:

VideoKit

VideoKit is the only full feature user-generated content solution for Unity Engine. VideoKit allows:

Video recording. Record MP4 videos, animated GIF images, WEBM videos, ProRes videos, waveform audio, JPEG image sequences, and more to come!
Camera streaming. Stream the camera preview with fine-grained control over focus, exposure, zoom, and more.
Microphone streaming. Stream microphone audio with control over the audio format and with echo cancellation.
Social Sharing. Share images and videos with the native share sheet, and save to the camera roll.
Conversational Interfaces. Build user interfaces with text-to-speech, speech-to-text, and more.
Cross-platform. Build once, deploy on Android, iOS, macOS, WebGL, and Windows.
Source Available. VideoKit is distributed with its C# source code available for inspection.

Installing VideoKit

Add the following items to your Unity project's Packages/manifest.json:

{
  "scopedRegistries": [
    {
      "name": "VideoKit",
      "url": "https://registry.npmjs.com",
      "scopes": ["ai.videokit"]
    },
    {
      "name": "Function",
      "url": "https://registry.npmjs.com",
      "scopes": ["ai.fxn"]
    }
  ],
  "dependencies": {
    "ai.videokit.videokit": "0.0.22",
  }
}

[!IMPORTANT] VideoKit is still in alpha. As such, the C# API is expected to change a lot between releases.

Retrieving your Access Key

To use VideoKit, you will need to generate an access key. First, head over to videokit.ai to create an account by logging in. Once you do, generate an access key:

Then add the key to your Unity project in Project Settings > VideoKit:

[!CAUTION] If your Unity project is open-source, make sure to add ProjectSettings/VideoKit.asset to your .gitignore file to keep your VideoKit access key private.

Using VideoKit

Here are a few things you can do with VideoKit:

Social Sharing

Share images, audio, and video files with the native share sheet with the MediaAsset.Share method:

Texture2D image = ...
ImageAsset asset = await MediaAsset.FromTexture(image);
string receiverAppId = await asset.Share();

Saving to the Camera Roll

Save images and videos to the camera roll with the MediaAsset.SaveToCameraRoll method:

Texture2D image = ...
ImageAsset asset = await MediaAsset.FromTexture(image);
bool saved = await asset.SaveToCameraRoll();

Picking from the Camera Roll

Pick images and videos from the camera roll with the MediaAsset.FromCameraRoll<T> method:

// This will present the native gallery UI
var asset = await MediaAsset.FromCameraRoll<ImageAsset>() as ImageAsset;
Texture2D image = await asset.ToTexture();
// Do stuff with `image`...

Camera Streaming

Stream the camera preview with the VideoKitCameraManager component:

Record Videos

Record MP4, HEVC, WEBM videos; animated GIF images; JPEG image sequences; and WAV audio files with the VideoKitRecorder component:

Human Texture

Remove the background from the camera preview with the VideoKitCameraManager component:

Speech-to-Text

Caption audio with the AudioAsset.Caption method:

AudioClip clip = ...;
var asset = await MediaAsset.FromAudioClip(clip);
var caption = await asset.Caption();
Debug.Log(caption);

Text Commands

Convert a natural language prompt into a struct with the TextAsset.To<T> method. This enables features like text commands, and can be combined with audio captioning for voice control:

using System.ComponentModel; // for `DescriptionAttribute`
using VideoKit.Assets;

struct Command { // Define this however you want

    [Description(@"The user's name")]
    public string name;

    [Description(@"The user's age")]
    public int age;
}

async void ParseCommand () {
    var prompt = "My name is Jake and I'm thirteen years old.";
    var asset = await MediaAsset.FromText(prompt);
    var command = await asset.To<Command>();
    // command = { "name": "Jake", "age": 13 }
}

Requirements

Unity 2022.3+

Supported Platforms

Android API Level 24+
iOS 14+
macOS 12+ (Apple Silicon and Intel)
Windows 10+ (64-bit only)
WebGL (requires Unity 6):
- Chrome 91+
- Firefox 90+
- Safari 16.4+

Resources

Thank you very much!

For Tasks:

Click tags to check more tools for each tasks

record videos share media stream camera remove background caption audio

For Jobs:

game developer app developer media content creator ar/vr developer ui/ux designer

Alternative AI tools for videokit

Similar Open Source Tools

videokit

github

: 114

redisvl

Redis Vector Library (RedisVL) is a Python client library for building AI applications on top of Redis. It provides a high-level interface for managing vector indexes, performing vector search, and integrating with popular embedding models and providers. RedisVL is designed to make it easy for developers to build and deploy AI applications that leverage the speed, flexibility, and reliability of Redis.

github

: 158

quivr

Quivr is a personal assistant powered by Generative AI, designed to be a second brain for users. It offers fast and efficient access to data, ensuring security and compatibility with various file formats. Quivr is open source and free to use, allowing users to share their brains publicly or keep them private. The marketplace feature enables users to share and utilize brains created by others, boosting productivity. Quivr's offline mode provides anytime, anywhere access to data. Key features include speed, security, OS compatibility, file compatibility, open source nature, public/private sharing options, a marketplace, and offline mode.

github

: 37.0k

SimplerLLM

SimplerLLM is an open-source Python library that simplifies interactions with Large Language Models (LLMs) for researchers and beginners. It provides a unified interface for different LLM providers, tools for enhancing language model capabilities, and easy development of AI-powered tools and apps. The library offers features like unified LLM interface, generic text loader, RapidAPI connector, SERP integration, prompt template builder, and more. Users can easily set up environment variables, create LLM instances, use tools like SERP, generic text loader, calling RapidAPI APIs, and prompt template builder. Additionally, the library includes chunking functions to split texts into manageable chunks based on different criteria. Future updates will bring more tools, interactions with local LLMs, prompt optimization, response evaluation, GPT Trainer, document chunker, advanced document loader, integration with more providers, Simple RAG with SimplerVectors, integration with vector databases, agent builder, and LLM server.

github

: 86

IntelliNode

IntelliNode is a javascript module that integrates cutting-edge AI models like ChatGPT, LLaMA, WaveNet, Gemini, and Stable diffusion into projects. It offers functions for generating text, speech, and images, as well as semantic search, multi-model evaluation, and chatbot capabilities. The module provides a wrapper layer for low-level model access, a controller layer for unified input handling, and a function layer for abstract functionality tailored to various use cases.

github

: 201

langserve

LangServe helps developers deploy `LangChain` runnables and chains as a REST API. This library is integrated with FastAPI and uses pydantic for data validation. In addition, it provides a client that can be used to call into runnables deployed on a server. A JavaScript client is available in LangChain.js.

github

: 1.9k

effective_llm_alignment

This is a super customizable, concise, user-friendly, and efficient toolkit for training and aligning LLMs. It provides support for various methods such as SFT, Distillation, DPO, ORPO, CPO, SimPO, SMPO, Non-pair Reward Modeling, Special prompts basket format, Rejection Sampling, Scoring using RM, Effective FAISS Map-Reduce Deduplication, LLM scoring using RM, NER, CLIP, Classification, and STS. The toolkit offers key libraries like PyTorch, Transformers, TRL, Accelerate, FSDP, DeepSpeed, and tools for result logging with wandb or clearml. It allows mixing datasets, generation and logging in wandb/clearml, vLLM batched generation, and aligns models using the SMPO method.

github

: 105

GraphRAG-SDK

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.

github

: 215

genaiscript

GenAIScript is a scripting environment designed to facilitate file ingestion, prompt development, and structured data extraction. Users can define metadata and model configurations, specify data sources, and define tasks to extract specific information. The tool provides a convenient way to analyze files and extract desired content in a structured format. It offers a user-friendly interface for working with data and automating data extraction processes, making it suitable for various data processing tasks.

github

: 2.2k

flow-prompt

Flow Prompt is a dynamic library for managing and optimizing prompts for large language models. It facilitates budget-aware operations, dynamic data integration, and efficient load distribution. Features include CI/CD testing, dynamic prompt development, multi-model support, real-time insights, and prompt testing and evolution.

github

: 68

pipecat

Pipecat is an open-source framework designed for building generative AI voice bots and multimodal assistants. It provides code building blocks for interacting with AI services, creating low-latency data pipelines, and transporting audio, video, and events over the Internet. Pipecat supports various AI services like speech-to-text, text-to-speech, image generation, and vision models. Users can implement new services and contribute to the framework. Pipecat aims to simplify the development of applications like personal coaches, meeting assistants, customer support bots, and more by providing a complete framework for integrating AI services.

github

: 4.3k

hugging-chat-api

Unofficial HuggingChat Python API for creating chatbots, supporting features like image generation, web search, memorizing context, and changing LLMs. Users can log in, chat with the ChatBot, perform web searches, create new conversations, manage conversations, switch models, get conversation info, use assistants, and delete conversations. The API also includes a CLI mode with various commands for interacting with the tool. Users are advised not to use the application for high-stakes decisions or advice and to avoid high-frequency requests to preserve server resources.

github

: 780

OpenAI

OpenAI is a Swift community-maintained implementation over OpenAI public API. It is a non-profit artificial intelligence research organization founded in San Francisco, California in 2015. OpenAI's mission is to ensure safe and responsible use of AI for civic good, economic growth, and other public benefits. The repository provides functionalities for text completions, chats, image generation, audio processing, edits, embeddings, models, moderations, utilities, and Combine extensions.

github

: 2.2k

embodied-agents

Embodied Agents is a toolkit for integrating large multi-modal models into existing robot stacks with just a few lines of code. It provides consistency, reliability, scalability, and is configurable to any observation and action space. The toolkit is designed to reduce complexities involved in setting up inference endpoints, converting between different model formats, and collecting/storing datasets. It aims to facilitate data collection and sharing among roboticists by providing Python-first abstractions that are modular, extensible, and applicable to a wide range of tasks. The toolkit supports asynchronous and remote thread-safe agent execution for maximal responsiveness and scalability, and is compatible with various APIs like HuggingFace Spaces, Datasets, Gymnasium Spaces, Ollama, and OpenAI. It also offers automatic dataset recording and optional uploads to the HuggingFace hub.

github

: 158

fragments

Fragments is an open-source tool that leverages Anthropic's Claude Artifacts, Vercel v0, and GPT Engineer. It is powered by E2B Sandbox SDK and Code Interpreter SDK, allowing secure execution of AI-generated code. The tool is based on Next.js 14, shadcn/ui, TailwindCSS, and Vercel AI SDK. Users can stream in the UI, install packages from npm and pip, and add custom stacks and LLM providers. Fragments enables users to build web apps with Python interpreter, Next.js, Vue.js, Streamlit, and Gradio, utilizing providers like OpenAI, Anthropic, Google AI, and more.

github

: 2.9k

preswald

Preswald is a full-stack platform for building, deploying, and managing interactive data applications in Python. It simplifies the process by combining ingestion, storage, transformation, and visualization into one lightweight SDK. With Preswald, users can connect to various data sources, customize app themes, and easily deploy apps locally. The platform focuses on code-first simplicity, end-to-end coverage, and efficiency by design, making it suitable for prototyping internal tools or deploying production-grade apps with reduced complexity and cost.

github

: 518

For similar tasks

videokit

github

: 114

react-native-vision-camera

VisionCamera is a powerful, high-performance Camera library for React Native. It features Photo and Video capture, QR/Barcode scanner, Customizable devices and multi-cameras ("fish-eye" zoom), Customizable resolutions and aspect-ratios (4k/8k images), Customizable FPS (30..240 FPS), Frame Processors (JS worklets to run facial recognition, AI object detection, realtime video chats, ...), Smooth zooming (Reanimated), Fast pause and resume, HDR & Night modes, Custom C++/GPU accelerated video pipeline (OpenGL).

github

: 7.8k

efficient-recorder

Efficient Recorder is a battery-life friendly tool designed to stream video, screen, mic, and system audio to any S3-compatible cloud storage service. It captures audio, screenshots, and webcam photos at configurable fps, utilizing low-energy volume detection for audio recording. The tool streams data to a configurable S3 endpoint or a custom server using MinIO. It aims to be storage and battery efficient, providing queued upload processing and minimal system resource overhead. The tool requires SoX for audio recording and webcam capture tools for operation. Users can specify various command line options for customization, such as enabling screenshot and webcam capture with specific intervals and image quality settings.

github

: 148

LLMs-Zero-to-Hero

LLMs-Zero-to-Hero is a repository dedicated to training large language models (LLMs) from scratch, covering topics such as dense models, MOE models, pre-training, supervised fine-tuning, direct preference optimization, reinforcement learning from human feedback, and deploying large models. The repository provides detailed learning notes for different chapters, code implementations, and resources for training and deploying LLMs. It aims to guide users from being beginners to proficient in building and deploying large language models.

github

: 54

CodeProject.AI-Server

CodeProject.AI Server is a standalone, self-hosted, fast, free, and open-source Artificial Intelligence microserver designed for any platform and language. It can be installed locally without the need for off-device or out-of-network data transfer, providing an easy-to-use solution for developers interested in AI programming. The server includes a HTTP REST API server, backend analysis services, and the source code, enabling users to perform various AI tasks locally without relying on external services or cloud computing. Current capabilities include object detection, face detection, scene recognition, sentiment analysis, and more, with ongoing feature expansions planned. The project aims to promote AI development, simplify AI implementation, focus on core use-cases, and leverage the expertise of the developer community.

github

: 645

BizyAir

BizyAir is a collection of ComfyUI nodes that help users overcome environmental and hardware limitations to generate high-quality content. It includes features such as ControlNet preprocessing, image background removal, photo-quality image generation, and animation super-resolution. Users can run ComfyUI anywhere without worrying about hardware requirements. Installation methods include using ComfyUI Manager, Comfy CLI, downloading standalone packages for Windows, or cloning the BizyAir repository into the custom_nodes subdirectory of ComfyUI.

github

: 455

For similar jobs

Protofy

Protofy is a full-stack, batteries-included low-code enabled web/app and IoT system with an API system and real-time messaging. It is based on Protofy (protoflow + visualui + protolib + protodevices) + Expo + Next.js + Tamagui + Solito + Express + Aedes + Redbird + Many other amazing packages. Protofy can be used to fast prototype Apps, webs, IoT systems, automations, or APIs. It is a ultra-extensible CMS with supercharged capabilities, mobile support, and IoT support (esp32 thanks to esphome).

github

: 227

generative-ai-dart

The Google Generative AI SDK for Dart enables developers to utilize cutting-edge Large Language Models (LLMs) for creating language applications. It provides access to the Gemini API for generating content using state-of-the-art models. Developers can integrate the SDK into their Dart or Flutter applications to leverage powerful AI capabilities. It is recommended to use the SDK for server-side API calls to ensure the security of API keys and protect against potential key exposure in mobile or web apps.

github

: 462

visionOS-examples

visionOS-examples is a repository containing accelerators for Spatial Computing. It includes examples such as Local Large Language Model, Chat Apple Vision Pro, WebSockets, Anchor To Head, Hand Tracking, Battery Life, Countdown, Plane Detection, Timer Vision, and PencilKit for visionOS. The repository showcases various functionalities and features for Apple Vision Pro, offering tools for developers to enhance their visionOS apps with capabilities like hand tracking, plane detection, and real-time cryptocurrency prices.

github

: 223

gemini-pro-vision-playground

Gemini Pro Vision Playground is a simple project aimed at assisting developers in utilizing the Gemini Pro Vision and Gemini Pro AI models for building applications. It provides a playground environment for experimenting with these models and integrating them into apps. The project includes instructions for setting up the Google AI API key and running the development server to visualize the results. Developers can learn more about the Gemini API documentation and Next.js framework through the provided resources. The project encourages contributions and feedback from the community.

github

: 75

Tiktok_Automation_Bot

TikTok Automation Bot is an Appium-based tool for automating TikTok account creation and video posting on real devices. It offers functionalities such as automated account creation and video posting, along with integrations like Crane tweak, SMSActivate service, and IPQualityScore service. The tool also provides device and automation management system, anti-bot system for human behavior modeling, and IP rotation system for different IP addresses. It is designed to simplify the process of managing TikTok accounts and posting videos efficiently.

github

: 122

general

General is a DART & Flutter library created by AZKADEV to speed up development on various platforms and CLI easily. It allows access to features such as camera, fingerprint, SMS, and MMS. The library is designed for Dart language and provides functionalities for app background, text to speech, speech to text, and more.

github

: 324

shards

Shards is a high-performance, multi-platform, type-safe programming language designed for visual development. It is a dataflow visual programming language that enables building full-fledged apps and games without traditional coding. Shards features automatic type checking, optimized shard implementations for high performance, and an intuitive visual workflow for beginners. The language allows seamless round-trip engineering between code and visual models, empowering users to create multi-platform apps easily. Shards also powers an upcoming AI-powered game creation system, enabling real-time collaboration and game development in a low to no-code environment.

github

: 70

AppFlowy

AppFlowy.IO is an open-source alternative to Notion, providing users with control over their data and customizations. It aims to offer functionality, data security, and cross-platform native experience to individuals, as well as building blocks and collaboration infra services to enterprises and hackers. The tool is built with Flutter and Rust, supporting multiple platforms and emphasizing long-term maintainability. AppFlowy prioritizes data privacy, reliable native experience, and community-driven extensibility, aiming to democratize the creation of complex workplace management tools.

github

: 59.3k