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authorJiang Xin <worldhello.net@gmail.com>2026-02-15 14:06:19 +0800
committerJiang Xin <worldhello.net@gmail.com>2026-04-03 07:36:52 +0800
commitfc59ba0dfe134fbb51230d50f396f5efc9ba1721 (patch)
tree2450127bbed5f5336ab1f876f81a5279b39de23f /t/t4013/diff.format-patch_--stdout_initial..master^
parentb5690272f2457bb667542c57ae52c37768f295b6 (diff)
downloadgit-fc59ba0dfe134fbb51230d50f396f5efc9ba1721.tar.gz
git-fc59ba0dfe134fbb51230d50f396f5efc9ba1721.zip
l10n: docs: add translation instructions in AGENTS.md
Add a new "Translating po/XX.po" section to po/AGENTS.md with detailed workflow and procedures for AI agents to translate language-specific PO files. Users can invoke AI-assisted translation in coding tools with a prompt such as: "Translate the po/XX.po file by referring to @po/AGENTS.md" Translation results serve as drafts; human contributors must review and approve before submission. To address the low translation efficiency of some LLMs, batch translation replaces entry-by-entry translation. git-po-helper implements a gettext JSON format for translation files, replacing PO format during translation to enable batch processing. Evaluation with the Qwen model: git-po-helper agent-run --agent=qwen translate po/zh_CN.po Test translation (127 entries, 50 per batch): Initial state: 5998 translated, 91 fuzzy, 36 untranslated Final state: 6125 translated, 0 fuzzy, 0 untranslated Successfully translated: 127 entries (91 fuzzy + 36 untranslated) Success rate: 100% Benchmark results (3-run average): AI agent using gettext tools: | Metric | Value | |------------------|--------------------------------| | Avg. Num turns | 86 (176, 44, 40) | | Avg. Exec. Time | 20m44s (39m56s, 14m38s, 7m38s) | | Successful runs | 3/3 | AI agent using git-po-helper (JSON batch flow): | Metric | Value | |------------------|--------------------------------| | Avg. Num turns | 56 (68, 39, 63) | | Avg. Exec. Time | 19m8s (28m55s, 9m1s, 19m28s) | | Successful runs | 3/3 | The git-po-helper flow reduces the number of turns (86 → 56) with similar execution time; the bottleneck appears to be LLM processing rather than network interaction. Signed-off-by: Jiang Xin <worldhello.net@gmail.com>
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