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Overview

Project website app.immersivetranslate.com
Instructions for translators

Immersive Translate Document Translation
Project maintainers User avatar theowenyoung User avatar zhoulink90 User avatar marshmolly2b
Translation process
  • Translations can be made directly.
  • Translation suggestions can be made.
  • Translations are reviewed by dedicated reviewers.
  • Any authenticated user can contribute.
  • The translation uses monolingual files.
  • The translation base language is editable.
Source code repository git@github.com:immersive-translate/site.git
Repository branch main
Last remote commit update 更新 babeldoc glm 4.7 0d7efefe1
taoloading authored yesterday
Last commit in Weblate Translated using Weblate (Chinese (Traditional)) 3544c9bb2
User avatar wei83109 authored 6 months ago
Weblate repository https://weblate.immersivetranslate.com/git/immersive-document-translation/immersive-translate-site/
File mask app/src/i18n/*.json
Monolingual base language file app/src/i18n/en.json
15 hours ago

String statistics

Strings percent Hosted strings Words percent Hosted words Characters percent Hosted characters
Total 13,455 140,805 995,295
Source 897 9,387 66,353
Approved 0% 0 0% 0 0% 0
Waiting for review 92% 12,460 91% 129,192 91% 912,539
Translated 92% 12,460 91% 129,192 91% 912,539
Needs editing 1% 64 1% 1,807 1% 12,781
Read-only 0% 0 0% 0 0% 0
Failing checks 12% 1,728 21% 30,698 21% 214,734
Strings with suggestions 1% 12 1% 25 1% 199
Untranslated strings 6% 931 6% 9,806 7% 69,975
Last 12 months Previous

Activity in last 12 months

0 changes 154 changes 0 changes 220 changes 0 changes 5,090 changes 0 changes 292 changes 0 changes 7,720 changes 0 changes 1,278 changes 1,064 changes 911 changes 849 changes 841 changes 220 changes 1,418 changes 140 changes 690 changes 64 changes 1,027 changes 109 changes 794 changes
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Quick numbers

140 k
Hosted words
13,455
Hosted strings
92%
Translated
1
Contributors
and previous 30 days

Trends of last 30 days

+10%
Hosted words
+100%
+9%
Hosted strings
+100%
+1%
Translated
+92%
—
Contributors
+100%
User avatar None

Repository push failed

  1. Immersive Translate Site
  2. Immersive Translate Document App
 
To github.com:immersive-translate/site.git
 ! [rejected]            main -> weblate_i18n_main (non-fast-forward)
error: failed to push some refs to 'github.com:immersive-translate/site.git'
hint: Updates were rejected because a pushed branch tip is behind its remote
hint: counterpart. Check out this branch and integrate the remote changes
hint: (e.g. 'git pull ...') before pushing again.
hint: See the 'Note about fast-forwards' in 'git push --help' for details.
 (1)
15 hours ago
User avatar None

Repository push failed

  1. Immersive Translate Site
  2. Immersive Translate Document App
 
To github.com:immersive-translate/site.git
 ! [rejected]            main -> weblate_i18n_main (non-fast-forward)
error: failed to push some refs to 'github.com:immersive-translate/site.git'
hint: Updates were rejected because a pushed branch tip is behind its remote
hint: counterpart. Check out this branch and integrate the remote changes
hint: (e.g. 'git pull ...') before pushing again.
hint: See the 'Note about fast-forwards' in 'git push --help' for details.
 (1)
yesterday
User avatar None

Resource updated

  1. Immersive Translate Site
  2. Immersive Translate Document App
  3. Chinese (Traditional)
The “app/src/i18n/zh-TW.json” file was changed. yesterday
User avatar None

String updated in the repository

  1. Immersive Translate Site
  2. Immersive Translate Document App
  3. Chinese (Traditional)
GLM 4.7
智谱 4.67
yesterday
User avatar None

String updated in the repository

  1. Immersive Translate Site
  2. Immersive Translate Document App
  3. Chinese (Traditional)
We currently use a "translation quota" based billing method, detailed as follows:<br/><br/><ul><li>Translation quotas are charged based on the number of <b>Tokens</b> used during the translation process.</li><li>The <b>GLM-4-Flash-250414</b> model is available to all users, and every BabelDOC user receives a monthly quota of 500,000 Tokens for free model translations within BabelDOC. (Actual availability depends on the supply from upstream providers, and quotas are dynamically adjusted based on server load)</li><li>The <b>Qwen-Plus/DeepSeek-V3.2/Doubao-1.5-pro/Kimi+Qwen/Kimi+DeepSeek/GLM-4.7</b> models are exclusively for <b>Pro/Max</b> members, counted towards the members' general translation quota. Pro members enjoy up to <b>20 million Tokens</b> per month, while Max members enjoy up to <b>50 million Tokens</b> per month. Failed translations are not counted towards the quota.</li></ul><br/>At the start of a translation task, the system will deduct the general translation quota in advance based on "3000 Tokens × number of pages". Once the translation is complete, we will settle based on actual consumption, refunding any excess to your account or requesting additional tokens if there is a shortfall. If any system errors occur during the translation, all pre-deducted general translation quotas will be fully refunded to your account. When the automatic term extraction feature is not enabled, the pre-deduction per page is 3000 Tokens/page. When the automatic term extraction feature is enabled, the pre-deduction per page is 6000 Tokens/page.<br/><br/>From actual usage statistics, when automatic term extraction is enabled, the average consumption is about 7381.56 Tokens per page, with the P25–P75 range being 4215.42–9490.89 Tokens; when automatic term extraction is disabled, the average consumption is about 4702.98 Tokens per page, with the P25–P75 range being 2642.38–5797.40 Tokens. Here, P25 (the 25th percentile) indicates that 25% of the pages consume fewer Tokens than this value, and P75 (the 75th percentile) indicates that 75% of the pages consume fewer Tokens than this value. The P25–P75 range is used to describe the common consumption range for most pages, thereby reducing the impact of extreme samples on the overall assessment.
我們目前採用基於「翻譯額度」的計費方式，具體說明如下：

<ul><li>翻譯額度按照翻譯過程中使用的 <b> Token 數量 </b> 進行計費。</li><li><b> GLM-4-Flash-250414 </b> 模型所有用戶可用，所有 BabelDOC 用戶每月可獲得 50 萬 Token 額度，用來在 BabelDOC 中使用免費模型翻譯文件。（實際可用性取決於上游供應商的供應情況，額度根據伺服器負載動態調整）</li><li><b> Qwen-Plus/DeepSeek-V3.2/Doubao-1.5-pro/Kimi+Qwen/Kimi+DeepSeek/GLM-4.67 </b> 模型僅限 <b> Pro/Max </b> 會員使用，計入會員通用翻譯額度，Pro 會員每月可享受 <b> 高達 2000 萬 Token </b> 的翻譯額度，Max 會員每月可享受 <b> 高達 5000 萬 Token </b> 的翻譯額度。失敗的翻譯不計入翻譯額度。</li></ul>

在翻譯任務啟動時，系統將根據"3000 Token × 翻譯頁數"的計算方式預先扣除相應的通用翻譯額度。待翻譯完成後，我們將按實際消耗進行結算，多餘額度將退還至您的賬戶，不足部分則需補充。若翻譯過程中遇到任何系統錯誤，所有預扣的通用翻譯額度將自動全額返還至您的賬戶。當不啟用自動提取術語時，單頁預扣 Token 數為 3000 Token/頁。當啟用自動提取術語功能時，單頁預扣 Token 數為 6000 Token/頁。<br/><br/>從實際使用統計來看，啟用自動術語提取時，平均每頁約消耗 7381.56 Token，其中 P25–P75 區間為 4215.42–9490.89 Token；關閉自動術語提取時，平均每頁約消耗 4702.98 Token，P25–P75 區間為 2642.38–5797.40 Token。其中，P25（第 25 百分位）表示有 25% 的頁面 Token 消耗低於該值，P75（第 75 百分位）表示有 75% 的頁面 Token 消耗低於該值，P25–P75 區間可用於描述大多數頁面的常見消耗範圍，從而減少極端樣本對整體評估的干擾。
yesterday
User avatar None

String updated in the repository

  1. Immersive Translate Site
  2. Immersive Translate Document App
  3. Chinese (Traditional)
We currently use a "translation quota" based billing method, detailed as follows:<br/><br/><ul><li>Translation quotas are charged based on the number of <b>Tokens</b> used during the translation process.</li><li>The <b>GLM-4-Flash-250414</b> model is available to all users, and every BabelDOC user receives a monthly quota of 500,000 Tokens for free model translations within BabelDOC. (Actual availability depends on the supply from upstream suppliers, and quotas are dynamically adjusted based on server load)</li><li>Models such as <b>Qwen-Plus/DeepSeek-V3.2/Doubao-1.5-pro/GPT-5-mini/Gemini-2.5-Flash/Kimi+Qwen/Kimi+DeepSeek/GLM-4.7</b> are exclusively for <b>Pro/Max</b> members, counted towards the members' general translation quota. Pro members enjoy up to <b>20 million Tokens</b> per month, while Max members can enjoy up to <b>50 million Tokens</b> per month. Failed translations are not counted towards the translation quota.</li></ul><br/>At the start of a translation task, the system will deduct the general translation quota in advance based on the calculation of "3000 Tokens × number of pages". Once the translation is complete, we will settle based on actual consumption, refunding any excess to your account, or requiring additional if insufficient. If any system errors occur during the translation, all deducted general translation quotas will be fully refunded to your account. When the automatic term extraction feature is not enabled, the deduction per page is 3000 Tokens/page. When the automatic term extraction feature is enabled, the deduction per page is 6000 Tokens/page.<br/><br/>From actual usage statistics, when automatic term extraction is enabled, the average consumption is about 7381.56 Tokens per page, with the P25–P75 range being 4215.42–9490.89 Tokens; when automatic term extraction is disabled, the average consumption is about 4702.98 Tokens per page, with the P25–P75 range being 2642.38–5797.40 Tokens. Here, P25 (the 25th percentile) indicates that 25% of the pages consume fewer Tokens than this value, and P75 (the 75th percentile) indicates that 75% of the pages consume fewer Tokens than this value. The P25–P75 range is used to describe the common consumption range for most pages, thereby reducing the impact of extreme samples on the overall assessment.
我們目前採用基於「翻譯額度」的計費方式，具體說明如下：

<ul><li>翻譯額度按照翻譯過程中使用的 <b> Token 數量 </b> 進行計費。</li><li><b> GLM-4-Flash-250414 </b> 模型所有用戶可用，所有 BabelDOC 用戶每月可獲得 50 萬 Token 額度，用來在 BabelDOC 中使用免費模型翻譯文件。（實際可用性取決於上游供應商的供應情況，額度根據伺服器負載動態調整）</li><li><b> Qwen-Plus/DeepSeek-V3.2/Doubao-1.5-pro/GPT-5-mini/Gemini-2.5-Flash/Kimi+Qwen/Kimi+DeepSeek/GLM-4.67 </b> 模型僅限 <b> Pro/Max </b> 會員使用，計入會員通用翻譯額度，Pro 會員每月可享受 <b> 高達 2000 萬 Token </b> 的翻譯額度，Max 會員每月可享受 <b> 高達 5000 萬 Token </b> 的翻譯額度。失敗的翻譯不計入翻譯額度。</li></ul>

在翻譯任務啟動時，系統將根據"3000 Token × 翻譯頁數"的計算方式預先扣除相應的通用翻譯額度。待翻譯完成後，我們將按實際消耗進行結算，多餘額度將退還至您的賬戶，不足部分則需補充。若翻譯過程中遇到任何系統錯誤，所有預扣的通用翻譯額度將自動全額返還至您的賬戶。當不啟用自動提取術語時，單頁預扣 Token 數為 3000 Token/頁。當啟用自動提取術語功能時，單頁預扣 Token 數為 6000 Token/頁。<br/><br/>從實際使用統計來看，啟用自動術語提取時，平均每頁約消耗 7381.56 Token，其中 P25–P75 區間為 4215.42–9490.89 Token；關閉自動術語提取時，平均每頁約消耗 4702.98 Token，P25–P75 區間為 2642.38–5797.40 Token。其中，P25（第 25 百分位）表示有 25% 的頁面 Token 消耗低於該值，P75（第 75 百分位）表示有 75% 的頁面 Token 消耗低於該值，P25–P75 區間可用於描述大多數頁面的常見消耗範圍，從而減少極端樣本對整體評估的干擾。
yesterday
User avatar None

String updated in the repository

  1. Immersive Translate Site
  2. Immersive Translate Document App
  3. Chinese (Traditional)
All users currently have access to the GLM-4-Flash-250414 model for translation, while Pro users can also choose to use the Qwen-Plus/DeepSeek-V3.2/Doubao-1.5-pro/GPT-5-mini/Gemini-2.5-Flash/Kimi+Qwen/Kimi+DeepSeek/GLM-4.7 models for translation, subject to actual availability.

After comparison, we found that Kimi-K2-0905 is effective in extracting terminology, hence we are introducing the "Kimi + Qwen" and "Kimi + DeepSeek" translation services:

If you choose the "Kimi + Qwen" translation service and enable automatic terminology extraction, Kimi-K2-0905 will be used to extract terminology, and Qwen-Plus will be used to complete the text translation. All related consumption will be counted towards Qwen usage. (Limited time test)

If you choose the "Kimi + DeepSeek" translation service and enable automatic terminology extraction, Kimi-K2-0905 will be used to extract terminology, and DeepSeek-V3.2 will be used to complete the text translation. All related consumption will be counted towards DeepSeek usage. (Limited time test)

Since BabelDOC uses a backend translation architecture, all translation logic is executed on the server side, independent of the translation engine used by the plugin. Therefore, the range of translation engines available for BabelDOC differs from those available for immersive translation plugins, and BabelDOC only supports certain advanced translation models, not all advanced models are available.
所有用戶目前均可使用 GLM-4-Flash-250414 模型進行翻譯，而 Pro 用戶還可額外選擇使用 Qwen-Plus/DeepSeek-V3.2/Doubao-1.5-pro/GPT-5-mini/Gemini-2.5-Flash/Kimi+Qwen/Kimi+DeepSeek/GLM-4.67 模型（以實際可選模型為準）進行翻譯。

經過對比我們發現 Kimi-K2-0905 提取術語效果較好，因此推出“Kimi + Qwen”和“Kimi + DeepSeek”翻譯服務：

若選擇“Kimi + Qwen”翻譯服務，且啟用自動術語提取，則會使用 Kimi-K2-0905 提取術語，並使用 Qwen-Plus 完成文本翻譯。相關消耗均會計入 Qwen 消耗。（限時測試）

若選擇“Kimi + DeepSeek”翻譯服務，且啟用自動術語提取，則會使用 Kimi-K2-0905 提取術語，並使用 DeepSeek-V3.2 完成文本翻譯。相關消耗均會計入 DeepSeek 消耗。（限時測試）

由於 BabelDOC 採用後端翻譯架構，所有翻譯邏輯均在伺服器端執行，與插件所使用的翻譯引擎相互獨立。因此，BabelDOC 可選用的翻譯引擎範圍與沉浸式翻譯插件存在差異，BabelDOC 僅支持部分高級翻譯模型，並非所有高級模型均可使用。
yesterday
User avatar None

String updated in the repository

  1. Immersive Translate Site
  2. Immersive Translate Document App
  3. Chinese (Traditional)
All users can currently use the GLM-4-Flash-250414 model for translation free of charge, while Pro users can also choose to use the Qwen-Plus/DeepSeek-V3.2/Doubao-1.5-pro models for translation.
所有用戶目前均可使用 GLM-4-Flash-250414 模型進行翻譯，而 Pro 用戶還可額外選擇使用 Qwen-Plus/DeepSeek-V3.2/Doubao-1.5-pro/Kimi+Qwen/Kimi+DeepSeek/GLM-4.67 模型（以實際可選模型為準）進行翻譯。

經過對比我們發現 Kimi-K2-0905 提取術語效果較好，因此推出“Kimi + Qwen”和“Kimi + DeepSeek”翻譯服務：

若選擇“Kimi + Qwen”翻譯服務，且啟用自動術語提取，則會使用 Kimi-K2-0905 提取術語，並使用 Qwen-Plus 完成文本翻譯。相關消耗均會計入 Qwen 消耗。（限時測試）

若選擇“Kimi + DeepSeek”翻譯服務，且啟用自動術語提取，則會使用 Kimi-K2-0905 提取術語，並使用 DeepSeek-V3.2 完成文本翻譯。相關消耗均會計入 DeepSeek 消耗。（限時測試）

由於 BabelDOC 採用後端翻譯架構，所有翻譯邏輯均在伺服器端執行，與插件所使用的翻譯引擎相互獨立。因此，BabelDOC 可選用的翻譯引擎範圍與沉浸式翻譯插件存在差異，BabelDOC 僅支持部分高級翻譯模型，並非所有高級模型均可使用。
yesterday
User avatar None

String updated in the repository

  1. Immersive Translate Site
  2. Immersive Translate Document App
  3. Chinese (Traditional)
GLM 4.7
智谱 4.67
yesterday
User avatar None

Resource updated

  1. Immersive Translate Site
  2. Immersive Translate Document App
  3. Chinese (Traditional, Hong Kong)
The “app/src/i18n/zh-HK.json” file was changed. yesterday
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