manu69x

Corpus Hub contributor since 2026-10-26

manu69x's work was selected for the XERJ Corpus Hub, the open reference memory AI coding agents search before they write code. When an agent meets the same problem, it gets this implementation back as a worked example, with the author and the repository attached.

1corpus

1selected commit

33files

5,260lines

★ 1GitHub stars on repo

Totals across every corpus @manu69x appears in; a commit selected for two corpora counts once. Files and lines count the selected commits; each corpus indexes the whole repository at its pinned commit.

What an agent can do with the trans corpus

manu69x/trans: Local-first, LLM-assisted literary CAT platform (EN to IT): PDF import, entity & glossary knowledge base, human-approved translation with…

Look up how trans implements cat-tool, docker, fastapi, with answers cited to file and line.
Reuse a worked example: the commit “bilingual UI (Italian/English) with auto-detected locale” (33 files · TypeScript).
Answer from trans's real TypeScript source instead of memory (AI, prompts and agents).

Example questions

Where does trans handle “bilingual UI (Italian/English) with auto-detected locale”?
How does trans implement cat-tool?
What does frontend do in trans?

Paste it into your AI agent. It clones the repo at the pinned commit and indexes it on your machine.

Search the GitHub repository manu69x/trans with XERJ (https://hub.xerj.org/corpus/manu69x--trans).
Run these in a shell, in order, and check each result before the next:
1. xerj --help  (success: it prints usage). If xerj is missing: curl -fsSL https://xerj.org/get | sh
2. git clone https://github.com/manu69x/trans trans && git -C trans checkout 741056f99b8da76d5946ddd6dd7a0c94a86c72d1
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./trans --url http://127.0.0.1:9200 --prefix trans --progress plain
5. xerj autoindex map --url http://127.0.0.1:9200
Then answer my question from the indexed files and cite the ax_path of every hit. Query syntax: https://xerj.org/llms.txt
Licence: MIT. Keep the copyright notice and credit the authors.

corpus manu69x--trans · AI, prompts and agents
Related corpora: dunorth595--ai-agent-memory, dunorth595--ai-agent-chat, JeremyL691/SourceHero-AI, dziksu/synkinema
AI search and retrieval with XERJ · Case study: reference coding for agents

Selected work

GitHub ★ 1

manu69x/trans

Local-first, LLM-assisted literary CAT platform (EN to IT): PDF import, entity & glossary knowledge base, human-approved translation with immutable versions, DOCX/EPUB/PDF/XLIFF export. Fully offline against your own OpenAI-compatible LLM gateway

On GitHub: 10 commits · 311 files at the pinned commit · created 2026-10 · last push 2026-10-29

Languages: Python 75%, TypeScript 24%

741056f99b feat(i18n): bilingual UI (Italian/English) with auto-detected locale

selected commit: 33 files · 5,260 lines · TypeScript · frontend

The corpus is the whole repository at the pinned commit, not only the files of the selected commit.

live on the hub · licence clearedcorpus manu69x--transAIMITcat-tooldockerfastapillmlocal-firstnextjs agreed 2026-10-26

[![XERJ Corpus Hub contributor](https://hub.xerj.org/contributors/manu69x/badge.svg)](https://hub.xerj.org/contributors/manu69x)

Included with the author's permission (email, 2026-10-26), under each repository's own licence, with attribution. Own more repositories? Sign in with GitHub and add them. Want something removed? Reply to the email, withdraw it on /add, or open an issue on xerj-org/xerj.