`, or a `--provider` entry (see the Custom API Provider section).
- `--key`:
API key for the endpoint. Without the flag the key is read from `$BBM_API_KEY`, then from the format's own variable. Same flag as `--api_key`.
- `--api_format`:
The API the endpoint speaks. When omitted it is inferred: an `anthropic.com` host, or a model id containing `claude` with no `--api_base`, means `anthropic`; anything else means `openai`. Pass it when the guess is wrong, to reach a vendor without typing its address, or to pick an engine.
| format | key | notes |
|--------|-----|-------|
| `openai` (default) | required: `--key`, else `$BBM_API_KEY`, `$OPENAI_API_KEY`; not for a local address such as Ollama | any OpenAI-compatible endpoint: OpenAI itself, OpenRouter, Ollama and the rest, the address in `--api_base` |
| `anthropic` | required: `--key`, else `$BBM_API_KEY`, `$ANTHROPIC_API_KEY` | Anthropic itself, and gateways that speak the Messages API |
| `gemini` | required: `--key`, else `$BBM_API_KEY`, `$BBM_GOOGLE_GEMINI_KEY`, `$GEMINI_API_KEY` | the Gemini API, default `gemini-flash-latest`; paced by `--interval` |
| `qwen` | required: `--key`, else `$BBM_API_KEY`, `$BBM_QWEN_API_KEY`, `$DASHSCOPE_API_KEY` | Qwen-MT on DashScope, default `qwen-mt-turbo`; reads `--source_lang` |
| `groq` | required: `--key`, else `$BBM_API_KEY`, `$BBM_GROQ_API_KEY`, `$GROQ_API_KEY` | GroqCloud; `--model` required |
| `xai` | required: `--key`, else `$BBM_API_KEY`, `$BBM_XAI_API_KEY`, `$XAI_API_KEY` | xAI; `--model` required |
| `litellm` | none for a proxy on this machine, else `--key` or `$LITELLM_MASTER_KEY` | a LiteLLM proxy, `http://localhost:4000` unless `--api_base` says otherwise; `--model` required |
| `codex` | none: `codex login` (Codex CLI) | the local `codex app-server` sidecar on a ChatGPT/Codex plan, default `gpt-5.6-luna` |
| `orcarouter` | required: `--key` or `$BBM_ORCAROUTER_API_KEY` | OrcaRouter |
| `google` | none | Google Translate, free |
| `caiyun` | required: `--key` or `$BBM_CAIYUN_API_KEY` | Caiyun |
| `deepl` | required: `--key` or `$BBM_DEEPL_API_KEY` | DeepL (paid) |
| `deeplfree` | none | DeepL free tier |
| `tencent` | none | Tencent TranSmart, free |
| `customapi` | none | a `{text, source_lang, target_lang}` format API |
- `--interval`:
Seconds to wait between requests, e.g. `--interval 0.1` for 100ms. Only `--api_format gemini` paces itself with it; every other route ignores it. Default: `0.01`.
- `--test`:
Use `--test` option to preview the result if you haven't paid for the service. Note that there is a limit and it may take some time.
- `--language`:
Set the target language: a tag (`--language zh-hant`), a name (`--language "Traditional Chinese"`), or both at once — `--language "zh-hant:Traditional Chinese"`. The tag names the JSON structured-output field; the name is what the model is asked for. Default `zh-hans`. See also [available tags](https://github.com/yihong0618/bilingual_book_maker/wiki/Language-tags).
- `--source_lang`:
Source language. Stated, it appends a prompt line ("Translate from English"), and on `--api_format qwen` (whose request names a language pair) and `--api_format customapi` it rides in the request itself. Default: auto-detect.
- `--proxy`:
Use `--proxy` option to specify proxy server for internet access. Enter a string such as `http://127.0.0.1:7890`.
- `--resume`:
Use `--resume` option to manually resume the process after an interruption. Mutually
exclusive with `--parallel-workers`.
```shell
python3 make_book.py --book_name test_books/animal_farm.epub --api_format google --resume
```
- `--translate-tags`:
epub is made of html files. By default, we only translate contents in ``.
Use `--translate-tags` to specify tags need for translation. Use comma to separate multiple tags.
For example: `--translate-tags h1,h2,h3,p,div`
- `--plan-classify` (epub only), `--plan-dry-run`, `--plan-min-coverage`, `--max-batch-units`:
Plan mode: the whole book is partitioned and the model decides which tag signatures to translate. On by default for EPUBs; see [Plan mode](#plan-mode).
- `--exclude-translate-tags`:
Use `--exclude-translate-tags` to exclude content within specified HTML tags from translation. This is useful for preserving code blocks, preformatted text, or other special content. Use comma to separate multiple tags.
Default: `sup,code`.
For example: `--exclude-translate-tags code,pre`
**Tip**: Use `--exclude-translate-tags ""` to translate all content including code blocks (overrides the default exclusion).
- `--api_base`:
If you want to change api_base like using Cloudflare Workers, use `--api_base ` to support it.
**Note: the api url should be '`https://xxxx/v1`'. Quotation marks are required.**
- `--allow_navigable_strings`:
If you want to translate strings in an e-book that aren't labeled with any tags, you can use the `--allow_navigable_strings` parameter. This will add the strings to the translation queue.
- `--prompt`:
To tweak the prompt, use the `--prompt` parameter. The placeholders the `user` template may use are `{text}` (required), `{language}` and `{crlf}` (a newline, for the shapes — a JSON string, a table cell — that cannot carry one). Anything else in braces is refused before the run starts rather than raising mid-book; write `{{` and `}}` for a literal brace. It supports a few ways to configure the prompt:
- If you don't need to set the `system` role content, you can simply set it up like this: `--prompt "Translate {text} to {language}."` or `--prompt prompt_template_sample.txt`
- If you need to set the `system` role content, you can use the following format: `--prompt '{"user":"Translate {text} to {language}", "system": "You are a professional translator."}'` or `--prompt prompt_template.json`.
- A third key, `style`, is a standing instruction about how to write — register, tone, vocabulary. It is said **once where a window starts**, not repeated on every request.
- `--prompt` works on every LLM route, and on srt books too — there its sections sit on top of the subtitle loader's own prompt, section by section. Replacing the `user` template on an srt book means saying yourself that the block number and the timeline must come back unchanged; the run warns about it. The fixed machine-translation routes (google, deepl, caiyun, tencent, qwen, customapi) send text and nothing else, so they carry no prompt at all and the run says so at start.
- A `.md` file is read as the [PromptDown](https://github.com/btfranklin/promptdown) **block** form — the format is theirs, the reader is ours, so no extra package is installed: `--prompt prompt_md.prompt.md` (example at [./prompt_md.prompt.md](./prompt_md.prompt.md)). `## System Message`, an optional `## Style`, and a `## Conversation` whose `**User:**` turn is the template. The table form of a conversation is refused. Example:
```markdown
# Translation Prompt
## System Message
You are a professional translator who specializes in accurate translations.
## Conversation
**User:**
Please translate the following text into {language}:
{text}
```
- You can also set the `user` and `system` role prompt by setting environment variables: `BBM_CHATGPTAPI_USER_MSG_TEMPLATE` and `BBM_CHATGPTAPI_SYS_MSG`.
- An example JSON file can be found at [./prompt_template.json](./prompt_template.json).
- `--batch_size`:
Use the `--batch_size` parameter to specify the number of lines for batch translation (default is 10, currently only effective for txt files).
- `--accumulated_num`:
Wait for how many tokens have been accumulated before starting the translation.
For example, if you use `--accumulated_num 1600`, maybe openai will output 2200 tokens and maybe 200 tokens for other messages in the system messages user messages, 1600+2200+200=4000 — on some local models that is close to the limit. You have to choose your own value, there is no way to know if the limit is reached before sending.
In EPUB plan mode this is a per-request token budget: consecutive units of any length share one request up to `N` tokens. Pass `1` to turn grouping off — every unit is sent on its own.
- `--use_context`:
Translate with context.
- `--context_paragraph_limit`:
Use `--context_paragraph_limit` to set a limit on the number of context paragraphs when using the `--use_context` option. This applies to window mode only.
- `--use_context session`, `--context-compact-at`, `--no-context-compact`:
Session mode: one growing history instead of a re-sent window, compacted into a handoff report at the budget. See [Session mode](#session-mode).
- `--glossary` / `--terminology`:
A file of `term → translation` lines — one per line, `#` starts a note or a
comment, plain text.
Read by the openai- and codex-shaped routes for EPUB, Markdown, and PDF books.
A pinned term makes the translation say what you pinned, so pin only
renderings you can stand behind.
- `--glossary-auto on|off`:
Keep the renderings the handoff reports establish, so recurring names
stay unified across window seams. Session mode only, and off by
default: it relies on the model reporting its own renderings
accurately, which takes a capable model — most runs don't need it,
since the handoff summary already carries the recurring names.
- `--parallel-workers`:
Use `--parallel-workers` to process EPUB chapters or Markdown batches/sections in
parallel. Values greater than `1` spin up multiple workers (recommended: `2-4`) and
automatically fall back to sequential mode when there is only one unit of work. Other
input loaders currently accept this shared CLI option but do not parallelize their work.
- `--temperature`:
Sampling temperature for the openai and anthropic formats (the codex
format has none). For example: `--temperature 0.7`.
- `--block_size`:
Use `--block_size` to merge multiple paragraphs into one block. This may increase accuracy and speed up the process.
For example: `--block_size 5`.
- `--single_translate`:
Use `--single_translate` to output only the translated book without creating a bilingual version.
- `--no_disclosure`:
An epub output adds "Translated by gpt-5.6-luna, 2026." below the book intro; this flag leaves it out. It also turns off the translation metadata (`--translation-metadata`: the model, the date and the glossary).
- `--translation_style`:
Apply custom CSS to translated EPUB text, for example
`--translation_style "color: #808080; font-style: italic;"`.
- `--translation_color`:
Shorthand for setting only the translated EPUB text color, for example
`--translation_color "#1e90ff"`. If `--translation_style` is also present, the full style
takes precedence.
- `--pdf_layout {none,top-bottom,side-by-side,all}`:
Select additional bilingual PDF outputs for PDF inputs. The default `none` creates no
extra PDF; `all` attempts both top-bottom and side-by-side layouts. The bilingual TXT and
EPUB outputs are unaffected.
- `--to-epub`, `--pdf-ocr`, `--ocr-lang`, `--ocr-engine`, `--ocr-replace-layer`, `--pages`, `--device`, `--pdf-image-dpi` (PDF only):
Turn a PDF into a bilingual EPUB with a table of contents. See [PDF to bilingual EPUB](#pdf-to-bilingual-epub-experimental).
- `--sentence_mode`:
Translate EPUB text sentence by sentence instead of translating each paragraph as one
unit. It is incompatible with EPUB plan mode.
- `--batch` / `--batch-use`:
Two-stage translation through the ChatGPT Batch API. Currently **refused on EPUB
inputs**: the queue path is unreachable there, so such a run would translate live at
full price and then submit an empty batch job instead of writing the book. Also refused
on routes that do not implement the Batch API.
- `--quiet`:
Suppress EPUB progress bars and per-paragraph source/translation echoes while retaining
reports and errors. Recommended for log files and non-interactive agent runs.
- `--retranslate "$translated_filepath" "file_name_in_epub" "start_str" "end_str"`:
Retranslate from start_str to end_str's tag:
```shell
python3 "make_book.py" --book_name "test_books/animal_farm.epub" --retranslate 'test_books/animal_farm_bilingual.epub' 'index_split_002.html' 'in spite of the present book shortage which' 'This kind of thing is not a good symptom. Obviously'
```
To retranslate only the tag containing `start_str`, pass an empty fourth argument:
```shell
python3 "make_book.py" --book_name "test_books/animal_farm.epub" --retranslate 'test_books/animal_farm_bilingual.epub' 'index_split_002.html' 'in spite of the present book shortage which' ''
```
- `--no-thinking`:
Ask a reasoning model not to think before answering; on a paragraph of
prose it buys nothing and costs tokens and time.
```shell
python3 make_book.py --book_name test_books/animal_farm.epub --key ${openai_key} --no-thinking
```
- `--extra_body`:
Pass additional JSON parameters on the routes built on the OpenAI request
path — `openai` and the OpenAI-format custom providers — and on the
`anthropic` route. Provide a JSON object with the desired parameters.
Example:
```shell
python3 make_book.py --book_name test_books/animal_farm.epub --key ${openai_key} --extra_body '{"chat_template_kwargs": {"enable_thinking": false}}'
```
- `--extra_headers`:
Extra HTTP headers sent with every request, on the same routes. Values
must be strings.
```shell
python3 make_book.py --book_name test_books/animal_farm.epub --key ${openrouter_key} --api_base https://openrouter.ai/api/v1 --model anthropic/claude-haiku-4.5 --extra_headers '{"HTTP-Referer": "https://example.com", "X-Title": "bilingual_book_maker"}'
```
Common forms, for reference:
```shell
# openai route — disable a local/vLLM chat template's thinking block
--extra_body '{"chat_template_kwargs": {"enable_thinking": false}}'
# openai route (chat completions) — reasoning effort and a token ceiling,
# neither of which has its own flag (both model-dependent)
--extra_body '{"reasoning_effort": "low", "max_completion_tokens": 2000}'
# anthropic route — keep extended thinking off; for translation it mostly
# buys deviation from the source, not quality
--extra_body '{"thinking": {"type": "disabled"}}'
# OpenRouter attribution (shown on its dashboard)
--extra_headers '{"HTTP-Referer": "https://example.com", "X-Title": "bilingual_book_maker"}'
# a gateway's own auth or routing header (the value stays out of the logs)
--extra_headers '{"X-API-Key": "sk-gateway-..."}'
```
- `--provider`:
Use a custom provider defined in `bbm_providers.json`; `--model` picks a model at it. See the "Custom API Provider" section above.
- `--api_key`:
Same as `--key`.
### Examples
**Note if use `pip install bbook_maker` all commands can change to `bbook_maker args`**
```shell
# Test quickly
python3 make_book.py --book_name test_books/animal_farm.epub --key ${openai_key} --test --language zh-hans --use_context session
# Test quickly for src
python3 make_book.py --book_name test_books/Lex_Fridman_episode_322.srt --key ${openai_key} --test
# Or translate the whole book
python3 make_book.py --book_name test_books/animal_farm.epub --key ${openai_key} --language zh-hans --use_context session
# Gemini
python3 make_book.py --book_name test_books/animal_farm.epub --api_format gemini --key ${gemini_key} --model gemini-flash-latest
# Translate an EPUB with parallel chapter processing
python3 make_book.py --book_name test_books/animal_farm.epub --key ${openai_key} --parallel-workers 4
# Rotate across several models
python3 make_book.py --book_name test_books/animal_farm.epub --key ${openai_key} --model_list gpt-5-mini,gpt-4o-mini
# Set env OPENAI_API_KEY to leave out --key
export OPENAI_API_KEY=${your_api_key}
# Name a model and add context, translating to Japanese
python3 make_book.py --book_name test_books/animal_farm.epub --model gpt-4o --use_context --language ja
# Any OpenAI-compatible endpoint: base URL, key, and the model id it uses
python3 make_book.py --book_name test_books/animal_farm.epub --api_base "https://api.lingyiwanwu.com/v1" --key ${key} --model yi-34b-chat-0205 --use_context session
# DeepL, to Japanese
python3 make_book.py --book_name test_books/animal_farm.epub --api_format deepl --key ${deepl_key} --language ja
# Claude, to Japanese
python3 make_book.py --book_name test_books/animal_farm.epub --model claude-sonnet-4-6 --key ${claude_key} --language ja
# A custom translation API, to Japanese
python3 make_book.py --book_name test_books/animal_farm.epub --api_format customapi --api_base ${custom_api} --language ja
# A provider entry (e.g. SiliconFlow); the key comes from the entry's env_key
python3 make_book.py --book_name test_books/animal_farm.epub --provider siliconflow --language ja --use_context session
# Translate contents in and
python3 make_book.py --book_name test_books/animal_farm.epub --translate-tags div,p
# Plan mode: auto-discover translatable content (poetry, blockquotes, table cells,
# ...) and batch verse lines in stanza windows; preview the plan with --plan-dry-run
python3 make_book.py --book_name test_books/animal_farm.epub --plan-dry-run
python3 make_book.py --book_name test_books/animal_farm.epub --plan-classify all
# Tweaking the prompt
python3 make_book.py --book_name test_books/animal_farm.epub --prompt prompt_template_sample.txt
# or
python3 make_book.py --book_name test_books/animal_farm.epub --prompt prompt_template.json
# or
python3 make_book.py --book_name test_books/animal_farm.epub --prompt "Please translate \`{text}\` to {language}"
# translate txt file
python3 make_book.py --book_name test_books/the_little_prince.txt --test --language zh-hans
# aggregated translation txt file
python3 make_book.py --book_name test_books/the_little_prince.txt --test --batch_size 20
# Using Caiyun model to translate
# (the api currently only support: simplified chinese <-> english, simplified chinese <-> japanese)
# the official Caiyun has provided a test token (3975l6lr5pcbvidl6jl2)
# you can apply your own token by following this tutorial(https://bobtranslate.com/service/translate/caiyun.html)
python3 make_book.py --api_format caiyun --key 3975l6lr5pcbvidl6jl2 --book_name test_books/animal_farm.epub
# Set env BBM_CAIYUN_API_KEY to leave out --key
export BBM_CAIYUN_API_KEY=${your_api_key}
```
More understandable example
```shell
python3 make_book.py --book_name 'animal_farm.epub' --key sk-XXXXX --api_base 'https://xxxxx/v1' --use_context session
# Or python3 is not in your PATH
python make_book.py --book_name 'animal_farm.epub' --key sk-XXXXX --api_base 'https://xxxxx/v1' --use_context session
```
Microsoft Azure Endpoints
```shell
python3 make_book.py --book_name 'animal_farm.epub' --key XXXXX --api_base 'https://example-endpoint.openai.azure.com/openai/v1' --model 'deployment-name' --use_context session
# Or python3 is not in your PATH
python make_book.py --book_name 'animal_farm.epub' --key XXXXX --api_base 'https://example-endpoint.openai.azure.com/openai/v1' --model 'deployment-name' --use_context session
```
## Features
### Plan mode
An EPUB is translated through a plan by default: the book is split into units, the model decides by tag signature what to translate, so verse, lists and table cells are not missed, and neighbouring units share one request. `--plan-classify` chooses who decides: `auto` (the default), `agent` (you or your coding agent, through the plan file), `all` or `none`.
```shell
# preview what would be translated and what skipped (no key needed)
python3 make_book.py --book_name my_book.epub --plan-dry-run
# decide the plan yourself or with a coding agent, then rerun the same command to translate
python3 make_book.py --book_name my_book.epub --key ${key} --plan-classify agent
```
`--plan-dry-run` honours `--only_filelist` / `--exclude_filelist`. `--classify-model` lets another model classify, `jev` for the Jev classifier; `--classify-base-url`, `--classify-key` and `--classify-min-confidence` go with it. More: [Plan mode](https://github.com/yihong0618/bilingual_book_maker/wiki/Plan-mode), [Recommended settings for EPUB](https://github.com/yihong0618/bilingual_book_maker/wiki/Recommended-settings-for-EPUB).
### Session mode
`--use_context session` keeps one conversation for the whole book, so names and style stay consistent. The history is re-read at the cache price and, once it reaches `--context-compact-at` (default 8192 tokens), compacted into a short handoff report; `--no-context-compact` starts the next window empty instead. Best on endpoints with prompt caching. More: [Session mode](https://github.com/yihong0618/bilingual_book_maker/wiki/Session-mode).
### PDF to **bilingual** EPUB (experimental)
`--to-epub` turns a PDF into a reflowable bilingual EPUB with a table of contents: every paragraph followed by its translation, figures and display formulas kept as pictures. It needs the PDF extra, installed from a clone, and [Pandoc](https://pandoc.org/installing.html) 3.1.12 or newer; see [Installing the PDF extra](https://github.com/yihong0618/bilingual_book_maker/wiki/Installing-the-PDF-extra).
```shell
pip install ".[pdf]"
# two pages first; check the headings in paper_pages-1-2_book/source.md
python3 make_book.py --book_name paper.pdf --to-epub --pages 1-2 --key ${key} --use_context session
# then the whole file
python3 make_book.py --book_name paper.pdf --to-epub --key ${key} --use_context session
```
#### Scans (OCR)
`--pdf-ocr` reads pages that have no text layer. `--ocr-lang` names the languages to read (`iso:zh`, `iso:ja`, …), `--ocr-engine` picks the engine (`auto`, `rapidocr`, `ocrmac`, `easyocr`, `tesseract`), and `--ocr-replace-layer` reads every page again when the embedded text is wrong. More: [Which OCR engine](https://github.com/yihong0618/bilingual_book_maker/wiki/Which-OCR-engine).
```shell
python3 make_book.py --book_name scan.pdf --to-epub --pdf-ocr --ocr-lang iso:zh --key ${key}
```
#### Pages, figures and formulas
`--pages 12-30` (or `1,3,5-7`) translates only those pages, into `paper_pages-12-30_bilingual.epub`. Figures are drawn at 200 DPI; `--pdf-image-dpi 300` sharpens tiny labels. Display formulas are kept as pictures; `--no-formula-images` turns that off.
#### Layout and hardware
`--img-model MODEL` shows each page to a vision model that corrects what the layout detector got wrong, such as headings, captions and code; `--img-base-url` and `--img-key` point it at another endpoint. `--device` picks where the extraction models run (`auto`, `cpu`, `cuda`, `mps`, `xpu`).
More: [PDF to bilingual EPUB](https://github.com/yihong0618/bilingual_book_maker/wiki/PDF-to-bilingual-EPUB), [Recommended settings for PDF](https://github.com/yihong0618/bilingual_book_maker/wiki/Recommended-settings-for-PDF).
## Docker
You can use [Docker](https://www.docker.com/) if you don't want to deal with setting up the environment. Prebuilt images are published to GitHub Container Registry on every merge to `main` (as `latest`) and on every release tag:
```shell
docker pull ghcr.io/yihong0618/bilingual_book_maker:latest
```
Mount the folder containing your book at `/book` and pass the usual flags — the container accepts every `make_book.py` option, and the translated book is written back into the same folder:
```shell
# Linux / macOS
export folder_path=/path/to/your/books
export book_name=animal_farm.epub
export openai_key=sk-XXX
export language=zh-hans # see the language list in book_maker/utils.py
docker run --rm -v "${folder_path}":/book ghcr.io/yihong0618/bilingual_book_maker:latest --book_name "/book/${book_name}" --key "${openai_key}" --language "${language}"
```
```powershell
# Windows PowerShell
$folder_path="C:\Users\user\mybook"
$book_name="animal_farm.epub"
$openai_key="sk-xxx"
$language="zh-hans"
docker run --rm -v ${folder_path}:/book ghcr.io/yihong0618/bilingual_book_maker:latest --book_name "/book/$book_name" --key $openai_key --language $language
```
For example, a quick test needing no key at all, over the free Google route:
```shell
docker run --rm -v /home/user/my_books:/book ghcr.io/yihong0618/bilingual_book_maker:latest --book_name /book/animal_farm.epub --api_format google --test --test_num 1 --language zh-hant
```
The container runs as root, so writing into the mounted folder always works; on Linux the files it writes there belong to root (`chown` them afterwards, or add `--user $(id -u)`). API keys can also be passed as environment variables (`-e OPENAI_API_KEY=sk-XXX`) instead of `--key`.
The `pdf` tag adds Pandoc and the PDF packages for `--to-epub`, and runs to several gigabytes:
```shell
docker run --rm -v "${folder_path}":/book -v bbm-models:/root/.cache ghcr.io/yihong0618/bilingual_book_maker:pdf --book_name /book/paper.pdf --to-epub --key "${openai_key}" --use_context session
```
For a GPU, find your machine:
- Linux with an NVIDIA card: install the NVIDIA Container Toolkit and add `--gpus all`.
- Windows with an NVIDIA card: the same, through Docker Desktop's WSL2 backend.
- Mac (Apple silicon): Docker cannot reach the GPU; install the tool natively instead.
- arm64 Linux with an NVIDIA card: also add `--platform linux/amd64`.
More: [Docker](https://github.com/yihong0618/bilingual_book_maker/wiki/Docker).
To build the image yourself instead of pulling:
```shell
docker build --tag bilingual_book_maker .
docker run --rm -v /path/to/your/books:/book bilingual_book_maker --book_name /book/animal_farm.epub --key sk-XXX --language zh-hans
```
## Notes
1. API token from free trial has limit. If you want to speed up the process, consider paying for the service or use multiple OpenAI tokens
2. PR is welcome
# Thanks
- @[yetone](https://github.com/yetone)
# Contribution
- Any issues or PRs are welcome.
- TODOs in the issue can also be selected.
- Please run `black make_book.py`[^black] before submitting the code.
# Others better
- 书译 BookTranslator -> [Book Translator](https://www.booktranslator.app)
## Appreciation
Thank you, that's enough.
[^token]: You can get a token from [OpenAI](https://platform.openai.com/account/api-keys) or [Anthropic](https://console.anthropic.com/account/api-keys).
[^black]: https://github.com/psf/black