Search Results for "livekit-cli"
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Showing 7 open source projects for "livekit-cli"
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Cloud tools for web scraping and data extractionAutomate web data collection with cloud tools that handle anti-bot measures, browser rendering, and data transformation out of the box. Extract content from any website, push to vector databases for RAG workflows, or pipe directly into your apps via API. Schedule runs, set up webhooks, and connect to your existing stack. Free tier available, then scale as you need to.
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Desktop and Mobile Device Management SoftwareDesktop Central is a unified endpoint management (UEM) solution that helps in managing servers, laptops, desktops, smartphones, and tablets from a central location.
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cleanvideo-cli
CLI tool for removing watermarks from AI-generated videos using frame-
cleanvideo-cli is a command-line tool designed to remove visible watermarks from AI-generated videos. It works by analyzing video frames and reconstructing the underlying pixels in watermark regions, without cropping or blurring the original content. This project is intended for developers, researchers, and creators who need a lightweight utility for cleaning preview or draft videos before further processing. -
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Upscayl
Free and Open Source AI Image Upscaler for Linux, MacOS and Windows
...You can also download the flatpak version and double-click the flatpak file to install via Store but wait for the full release, we'll be pushing it to Flathub for easy access. Upscayl uses AI models to enhance your images by guessing what the details could be. It uses Real-ESRGAN (and more in the future) model to achieve this. The CLI tool is called real-esrgan-ncnn-vulkan and it's available on the Real-ESRGAN repository. -
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Promptr
Promptr is a CLI tool that lets you use plain English to instruct GPT3
Promptr is a CLI tool that lets you use plain English to instruct OpenAI LLM models to make changes to your codebase. Changes are applied directly to the files that you reference from your prompt. -
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CML
Continuous Machine Learning | CI/CD for ML
Continuous Machine Learning (CML) is an open-source CLI tool for implementing continuous integration & delivery (CI/CD) with a focus on MLOps. Use it to automate development workflows, including machine provisioning, model training and evaluation, comparing ML experiments across project history, and monitoring changing datasets. CML can help train and evaluate models, and then generate a visual report with results and metrics, automatically on every pull request. -
Run applications fast and securely in a fully managed environmentRun frontend and backend services, batch jobs, deploy websites and applications, and queue processing workloads without the need to manage infrastructure.
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Agent Skills
Skills for AI coding agents
Agent Skills by Vercel Labs is a curated collection of modular “skills” designed to extend the capabilities of AI coding agents by packaging human-ready instructions, workflows, and optional scripts that tell an agent how to perform specific development tasks. In this repository, each skill adheres to the Agent Skills specification, meaning they’re defined as folders with a SKILL.md file (containing task descriptions and step-by-step guidance) and can include helper scripts and reference... -
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Node ChatGPT API
A client implementation for ChatGPT and Bing AI
A client implementation for ChatGPT and Bing AI. Available as a Node.js module, REST API server, and CLI app. Support for the official ChatGPT model has been added! You can now use the gpt-3.5-turbo model with the official OpenAI API, using ChatGPTClient. This is the same model that ChatGPT uses, and it's the most powerful model available right now. Usage of this model is not free, however it is 10x cheaper than text-davinci-003. The default model used in ChatGPTClient is now gpt-3.5-turbo. ... -
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smartcrop.js
Content aware image cropping
...So true to the open source mantra of release early, release often, I'm releasing version 0.0.0 of smartcrop.js. Smartcrop.js implements an algorithm to find good crops for images. It can be used in the browser, in node or via a CLI. Smarcrop requires support for Promises, use a polyfill for unsupported browsers or set smartcrop.Promise to your favorite promise implementation (I recommend bluebird).
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