TypeScript client for the PDF Extract API
A light-weight module that brings Fetch API to node.js
A function to recursively extract files and their object paths within a value, replacing them with null in a deep clone without mutating the original value. FileList instances are treated as File instance arrays. Files are typically File and Blob instance
A light-weight module that brings window.fetch to node.js
extracts CSS into separate files
A light-weight module that brings Fetch API to node.js
Simple to use, blazing fast and thoroughly tested websocket client and server for Node.js
unzip a zip file into a directory using 100% javascript
GOV.UK Notify Node.js client
A Webpack plugin to optimize \ minimize CSS assets.
An isomorphic client library for the Azure Document Intelligence service.
Vanilla-extract integration for capsize
Creating Electron app packages
TypeScript definitions for apollo-upload-client
Babel plugin to extract translatable messages from source code into Lingui catalogs
PDF extraction and rendering across all JavaScript runtimes
A javascript/nodejs multipart/form-data parser which operates on raw data.
TypeScript client library for the Mistral AI API
A light-weight module that brings Fetch API to node.js
Cloud Text-to-Speech API client for Node.js
Cloud Speech Client Library for Node.js
A CSS Modules transform to extract local aliases for inline imports
Azure Content Understanding Rest Client
Cross Platform Smart Fetch Ponyfill
Provides access to the Alchemy text mining API - http://www.alchemyapi.com/
NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, paraphrasing, grammar and spelling correction, keywords and keyphrases extraction, chatbot, product description and ad generation, intent classification, text generation, image generation, code generation, question answering, automatic speech recognition, machine translation, language detection, semantic search, semantic similarity, speech synthesis, tokenization, POS tagging, embeddings, and dependency parsing. It is ready for production, served through a REST API. This is the Ruby client for the API. More details here: https://nlpcloud.com. Documentation: https://docs.nlpcloud.com.
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