Python scraper based on AI🕷️ ScrapeGraphAI: You Only Scrape Once ScrapeGraphAI is a web scraping python library that uses LLM and direct graph logic to create scraping pipelines for websites, documents and XML files. Just say which information you want to extract and the library will do it for you! 🚀 Quick install The reference page for Scrapegraph-ai is available on the official page of pypy: pypi. pip install scrapegraphai you will also need to install Playwright for javascript-bas…
unofficial desktop version of oblivionOblivion Desktop - Unofficial Warp Client for Windows/Mac/Linux "Internet, for all or none!" Unofficial Desktop version of oblivion Oblivion provides secure, optimized internet access through a user-friendly Windows/Mac/Linux app using cloudflare warp technology Features Secure VPN: Custom WireGuard implementation in Go. User-Friendly: Simple, intuitive interface. Download OS Download …
Fully private LLM chatbot that runs entirely with a browser with no server needed. Supports Mistral and LLama 3.Secret Llama Entirely-in-browser, fully private LLM chatbot supporting Llama 3, Mistral and other open source models. Fully private = No conversation data ever leaves your computer Runs in the browser = No server needed and no install needed! Works offline Easy-to-use interface on par with ChatGPT, but for open source LLMs Big thanks to the inference engine provided by webllm. Join…
A Lightweight, Production-Ready Remix Stack for your next SaaS Application. 🛍️ Remix SaaS A Lightweight, Feature-Rich, and Production-Ready Remix Stack for your next SaaS application. Live Demo · Documentation · Twitter npx create-remix-saas@latest Live Demo We've created a simple demo that displays all template-provided features. Psst! Give the site a few seconds to load! (It's running on a free tier!) NoteRemix SaaS is an Open Source Template …
Bringing large-language models and chat to web browsers. Everything runs inside the browser with no server support.Web LLM | NPM Package | Get Started | Examples | Documentation | MLC LLM | Discord | WebLLM is a modular and customizable javascript package that directly brings language model chats directly onto web browsers with hardware acceleration. Everything runs inside the browser with no server support and is accelerated with WebGPU. WebLLM is fully compatible with OpenAI API. That is, you…
Create Magic Story! StoryDiffusion: Consistent Self-Attention for Long-Range Image and Video Generation [Paper] [Project Page] [🤗 Comic Generation Demo ] Official implementation of StoryDiffusion: Consistent Self-Attention for Long-Range Image and Video Generation. Demo Video 28a42f-2cf8-a5b-ec52-f3aaba486f.mp4 🌠 Key Features: StoryDiffusion can create a magic story by generating consistent images and videos. Our work mainly has two parts: …
Uncomplicated Observability for Python and beyond! 🪵🔥Pydantic Logfire — Uncomplicated Observability From the team behind Pydantic, Logfire is an observability platform built on the same belief as our open source library — that the most powerful tools can be easy to use. What sets Logfire apart: Simple and Powerful: Logfire's dashboard is simple relative to the power it provides, ensuring your entire engineering team will actually use it. Python-centric Insights: From rich display of P…
LM Studio in your terminal lms - Command Line Tool for LM Studio Built with lmstudio.js Installation lms ships with LM Studio 0.2.22 and newer. To set it up, run the built-in bootstrap command like so: Windows: cmd /c %USERPROFILE%/.cache/lm-studio/bin/lms.exe bootstrap Linux/macOS: ~/.cache/lm-studio/bin/lms bootstrap To check if the bootstrapping was successful, run the following in a 👉 new terminal window 👈: lms Usage You can use lms --help to see a list…
An efficient pure-PyTorch implementation of Kolmogorov-Arnold Network (KAN).An Efficient Implementation of Kolmogorov-Arnold Network This repository contains an efficient implementation of Kolmogorov-Arnold Network (KAN). The original implementation of KAN is available here. The performance issue of the original implementation is mostly because it needs to expand all intermediate variables to perform the different activation functions. For a layer with in_features input and out_features output,…