13 dépôts
Tools that allow users to apply formatting or transformations to specific highlighted segments of text rather than the entire document.
Explore 13 awesome GitHub repositories matching data & databases · Selective Text Processors. Refine with filters or upvote what's useful.
Markdown Here is a browser extension that enables rich text composition within web-based editors that lack native formatting support. By transforming plain text markdown syntax into rendered HTML, it allows users to draft professional emails and documents using standard markup, including headers, tables, and footnotes, directly inside their browser. The tool distinguishes itself through a bidirectional transformation engine that supports both the conversion of markdown to HTML and the reversion of rendered content back into its original source code. This state-preserving functionality allows
Highlighted segments of text are isolated for selective transformation or reversion within a larger document.
TextMate is a programmable text editor designed for software development and project management. It functions as a highly customizable environment where users can define language-specific behaviors, syntax highlighting rules, and automated workflows to suit their individual development needs. The editor distinguishes itself through a modular, bundle-based extensibility model that allows for deep integration with system shell commands. By piping document buffers through external scripts and command-line tools, users can perform complex text transformations, automate file lifecycle tasks, and b
Allows swapping or cycling the order of characters, words, or lines within a selection.
Harper is a local English linter and grammar checker designed as an IDE writing assistant. It operates as a language server that provides real-time spelling and grammar analysis for markdown and code comments, processing all linguistic data on the local device to ensure privacy and eliminate cloud dependencies. The tool is specialized for technical documentation, featuring the ability to identify and ignore text within code fences and inline blocks to prevent false positives. It allows for personalized configuration through custom dictionaries and the use of suppression comments to exclude sp
Disables grammar checking for selected sections of text through the use of specific comments within the document.
chatGPTBox is a browser extension that integrates large language model chat interfaces and AI tools directly into the web browsing experience. It functions as an AI productivity toolkit and API client, allowing users to access AI assistants via a floating chat interface without leaving their active webpage. The project distinguishes itself by offering context-aware assistance and website-specific adaptations based on the current URL. It further enhances the browsing experience by displaying AI-generated responses alongside standard search engine results and providing a system to route chat re
Allows users to perform AI-powered translation, polishing, and code explanation on highlighted text.
Read Frog is an AI-powered immersive translation browser extension that functions as a bilingual reading assistant and text explanation tool. It connects to over 20 AI providers, including OpenAI and Anthropic, with configurable endpoints, API keys, and model settings, enabling translation and explanation of web content directly in the browser. The extension distinguishes itself through several integrated capabilities. It translates webpage content by placing translations directly next to the original text for side-by-side comparison, and can process content from PDFs, videos, and comics. It
Explains words, phrases, and sentences at a difficulty matching the reader's language proficiency level.
Obsidian Copilot is an AI assistant plugin for Obsidian that brings conversational AI directly into your note-taking vault. It allows you to chat with multiple large language models, create and execute custom prompts, and edit notes through natural conversation, all without leaving your workspace. The plugin distinguishes itself by offering complete model flexibility, supporting OpenAI, Anthropic, Google, local, and self-hosted models with no vendor lock-in. It stores all chat history, system prompts, and custom commands as plain Markdown files in your vault, ensuring full data ownership and
Applies AI-driven transformations like summarization and rewriting to selected text.
Ce projet est une fiche de référence en science des données et un guide d'étude en machine learning. Il fournit une collection curatée de formules, définitions et résumés de modèles conçus pour une consultation rapide lors du développement de projets et de la préparation aux entretiens techniques. La ressource est fournie sous forme de document éducatif PDF statique. Elle organise des frameworks techniques complexes et des concepts théoriques de machine learning dans un document portable à mise en page fixe pour assurer une présentation visuelle cohérente sur différents appareils. Le contenu couvre des références de concepts de machine learning et une synthèse des connaissances en science des données, spécifiquement adaptés pour la révision d'examens et la synthèse de frameworks théoriques.
Organizes theoretical machine learning concepts into discrete categories for targeted information retrieval and structured study.
React Email Editor is a drag-and-drop visual builder for creating responsive email templates, built as a React embeddable component. It also serves as an AI-powered email designer, a collaborative email design tool, and a React component library for composing emails programmatically with JSX. The editor represents designs as structured JSON and supports multi-format rendering for email clients, web pages, and PDF. What distinguishes this editor is its deep AI integration: users can generate full email templates from natural language, rewrite text with chosen intent, produce multiple text vari
Generates real-time AI suggestions for refining text, buttons, headings, and image alt text during editing.
Fengshenbang-LM est un écosystème de modèles de langage chinois et un framework de pré-entraînement conçu pour le développement et le réglage fin de grands modèles de langage à plusieurs milliards de paramètres. Il sert de pipeline de traitement du langage naturel et de plateforme d'IA cross-modale capable de générer du contenu à travers différentes modalités, y compris la génération texte-vers-image et la prédiction de structure protéique. Le projet fournit un adaptateur de modèle spécifique au domaine pour appliquer des modèles pré-entraînés à des industries spécialisées telles que la santé, la finance et le droit. Il utilise un système de configuration distribué et le sharding de données pour gérer l'entraînement de modèles à grande échelle sur plusieurs nœuds de calcul. Le framework couvre un large éventail de capacités, y compris le traitement du langage naturel chinois, la transformation automatique de texte et la génération de contenu multimodal. Il prend en charge en outre des tâches linguistiques générales telles que la traduction, la programmation et la classification de texte. Les flux de travail de prédiction et de réglage fin en aval sont gérés et exécutés via une interface en ligne de commande.
Uses AI to transform source text into different formats for translation and summarization.
VoiceInk is a system-wide speech-to-text dictation tool that converts spoken audio into text using local or cloud AI models. It functions as a local AI transcription engine and a context-aware voice assistant, allowing users to insert transcribed text directly into any active application on the operating system. The project distinguishes itself through the use of custom vocabulary management, which trains transcription engines to recognize industry-specific technical terms, professional terminology, and personal names. It further enhances output by using large language models to refine raw tr
Uses large language models to polish rough voice transcriptions into professional emails, chats, or social posts.
Local-File-Organizer is a local-first file classification system that uses on-device machine learning models to categorize documents and media into structured directories. It functions as an automated file classifier and asset manager that leverages local inference to sort files based on content, meaning, and metadata. The project emphasizes privacy by performing all data processing and analysis on the local device, eliminating the need to send sensitive files to external cloud services. It utilizes local models to analyze text and image content to generate descriptive filenames and thematic
Analyzes text content to generate summaries and thematic categories for automatic file organization.
Scramble is an artificial intelligence-powered browser extension designed to assist with text processing, editing, and writing directly within web pages. It functions as a text editor that allows users to highlight content on any webpage and transform it through summarization, correction, or rewriting. The tool distinguishes itself by providing a provider-agnostic abstraction layer, enabling users to connect to various local or cloud-based language models by configuring their own authentication keys and endpoints. It supports custom prompt engineering, allowing users to define and save person
Processes highlighted web content through selected prompts to rewrite, summarize, or format text.
La modélisation de sujets contextualisée est un framework qui intègre des architectures de deep learning avec des distributions statistiques de fréquence des mots pour extraire des thèmes cohérents à partir de grandes collections de documents. En combinant des embeddings basés sur des transformeurs pré-entraînés avec l'inférence variationnelle, le système identifie des modèles cachés dans le texte tout en maintenant l'interprétabilité des modèles génératifs traditionnels. La bibliothèque se distingue en mappant diverses langues dans un espace sémantique partagé, permettant la découverte et la classification de sujets à travers des jeux de données multilingues sans nécessiter de données d'entraînement spécifiques à la langue. Elle prend en charge la modélisation thématique supervisée, permettant aux utilisateurs d'incorporer des étiquettes de catégorie connues ou des retours humains pendant le processus d'entraînement pour orienter l'espace latent vers des résultats spécifiques. La boîte à outils fournit une suite complète d'utilitaires pour la préparation des données en langage naturel, incluant le nettoyage de texte et la transformation de corpus en formats doubles adaptés à la fois aux représentations vectorielles denses et à l'analyse de fréquence creuse. Ces capacités prennent en charge une gamme d'approches, y compris la découverte zero-shot et les flux de travail de classification itératifs avec intervention humaine.
Identifies hidden patterns and coherent topics by combining contextual embeddings with statistical modeling.