Analysis updated 2026-05-18
Drop in a PDF textbook or handout to automatically extract its vocabulary words.
Provide a Google Gemini API key to auto-fill definitions, synonyms, and example sentences for each word.
Study with flashcards that test recall, recognition, spelling, and spoken pronunciation.
Export the extracted word list as a spreadsheet for use elsewhere.
| jerryxugit-2026/ziyang-vocab-master | cxq0517/htmltool2 | echosoar/local-trans | |
|---|---|---|---|
| Stars | 31 | 31 | 31 |
| Language | HTML | HTML | HTML |
| Setup difficulty | easy | easy | moderate |
| Complexity | 1/5 | 1/5 | 2/5 |
| Audience | general | vibe coder | developer |
Figures from each repo's GitHub metadata at analysis time.
Runs as a single HTML file with no server or account, a Google Gemini API key is only needed for the AI enrichment step.
Ziyang Vocab Master is a free vocabulary study tool created by a tenth-grade high school student in Beijing. The motivation is practical: most vocabulary apps force users to work from pre-built word lists, but students preparing for exams like the GRE or SAT, or studying from specific textbooks and teacher handouts, need to study their own custom lists. This tool lets you build a vocabulary database from any PDF you already have. The application is a single HTML file that runs entirely in your browser. No server, no account, and no installation are needed. All data stays on your own computer. It works in three steps. The first is a PDF extractor: you drop in a PDF and the tool automatically pulls out vocabulary words while filtering out common filler words like the and and. The resulting list can be exported as a spreadsheet. The second step is an AI enrichment stage: you provide a Google Gemini API key and the tool fills in each word's pronunciation in phonetic notation, its definition, word roots, synonyms, antonyms, and example sentences. It also fetches images from Pexels to give each word a visual memory aid. The third step is a flashcard review session. Cards cycle through four challenge types: recalling the word from a context clue, recognizing it in a sentence, spelling it correctly from memory, and speaking it aloud through a microphone. On macOS, right-clicking a word can open the system dictionary directly. The project is open source and free to use with no commercial intent. The author notes plans to add support for Korean, Ukrainian, Russian, Japanese, and Spanish in the future.
A free single-file browser tool that turns any PDF into an AI-enriched vocabulary list with flashcard review.
Mainly HTML. The stack also includes HTML, JavaScript, Google Gemini API.
Open source and free to use with no commercial intent stated by the author, check the repository for the exact license terms.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly general.
This repo across BitVibe Labs
Verify against the repo before relying on details.