12 Repos
Tools that allow users to apply formatting or transformations to specific highlighted segments of text rather than the entire document.
Explore 12 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.
Dieses Projekt ist ein Data-Science-Referenzblatt und ein Machine-Learning-Studienleitfaden. Es bietet eine kuratierte Sammlung von Formeln, Definitionen und Modellzusammenfassungen, die für das schnelle Nachschlagen während der Projektentwicklung und der Vorbereitung auf technische Interviews konzipiert sind. Die Ressource wird als statische PDF-Bildungsressource bereitgestellt. Sie organisiert komplexe technische Frameworks und theoretische Machine-Learning-Konzepte in einem portablen Dokument mit festem Layout, um eine konsistente visuelle Darstellung auf verschiedenen Geräten zu gewährleisten. Der Inhalt umfasst Referenzen zu Machine-Learning-Konzepten und die Synthese von Data-Science-Wissen, die speziell auf die Prüfungsvorbereitung und die Synthese theoretischer Frameworks zugeschnitten sind.
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 is a Chinese language model ecosystem and pre-training framework designed for the development and fine-tuning of billion-parameter large language models. It serves as a natural language processing pipeline and cross-modal AI platform capable of generating content across different modalities, including text-to-image generation and protein structure prediction. The project provides a domain-specific model adapter for applying pretrained models to specialized industries such as healthcare, finance, and law. It utilizes a distributed configuration system and data sharding to manag
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.
Contextualized topic modeling is a framework that integrates deep learning architectures with statistical word frequency distributions to extract coherent themes from large document collections. By combining pre-trained transformer-based embeddings with variational inference, the system identifies hidden patterns in text while maintaining the interpretability of traditional generative models. The library distinguishes itself by mapping diverse languages into a shared semantic space, enabling topic discovery and classification across multilingual datasets without requiring language-specific tr
Identifies hidden patterns and coherent topics by combining contextual embeddings with statistical modeling.