chatgpt subtitle translator
v2.16.2
ChatGPT has also demonstrated its capabilities as a robust translator, capable of handling not just common languages, but also unconventional forms of writing like emojis and word scrambling. However, it may not always produce a deterministic output and adhere to line-to-line correlation, potentially disrupting the timing of subtitles, even when instructed to follow precise instructions and setting the model temperature parameter to 0.
This utility uses the OpenAI ChatGPT API to translate text, with a specific focus on line-based translation, especially for SRT subtitles. The translator optimizes token usage by removing SRT overhead, grouping text into batches, resulting in arbitrary length translations without excessive token consumption while ensuring a one-to-one match between line input and output.
--experimental-structured-mode.--experimental-use-full-context (CLI only).Reference: https://github.com/openai/openai-quickstart-node#setup
>= 16.13.0 required. This README assumes bash shell environmentgit clone https://github.com/Cerlancism/chatgpt-subtitle-translator && cd chatgpt-subtitle-translatornpm installchmod +x cli/translator.mjs.example.env to .env
cp .env.example .env.env file
cli/translator.mjs --help
Usage: translator [options]
Translation tool based on ChatGPT API
Options:
--from <language>
Source language (default: "")
--to <language>
Target language (default: "English")
-i, --input <file>
Input source text with the content of this file, in .srt format or plain text
-o, --output <file>
Output file name, defaults to be based on input file name
-p, --plain-text <text>
Input source text with this plain text argument
-s, --system-instruction <instruction>
Override the prompt system instruction template Translate ${from} to ${to} with this plain text, ignoring --from and --to options
--initial-prompts <prompts>
Initial prompts for the translation in JSON (default: "[]")
--no-use-moderator
Don't use the OpenAI API Moderation endpoint
--moderation-model
(default: "omni-moderation-latest") https://platform.openai.com/docs/models/moderation
--no-prefix-number
Don't prefix lines with numerical indices
--no-line-matching
Don't enforce one to one line quantity input output matching
-l, --history-prompt-length <length>
Length of prompt history to retain for next request batch (default: 10)
-b, --batch-sizes <sizes>
Batch sizes of increasing order for translation prompt slices in JSON Array (default: "[10,100]")
The number of lines to include in each translation prompt, provided that they are estimated to within the token limit. In case of mismatched output line quantities, this number will be decreased step-by-step according to the values in the array, ultimately reaching one.
Larger batch sizes generally lead to more efficient token utilization and potentially better contextual translation. However, mismatched output line quantities or exceeding the token limit will cause token wastage, requiring resubmission of the batch with a smaller batch size.
--experimental-structured-mode [mode]
Enable structured response. (default: array, choices array, object)
--experimental-structured-mode array Structures the input and output into a plain array format. This option is more concise compared to base mode, though it uses slightly more tokens per batch.--experimental-structured-mode object Structures both the input and output into a dynamically generated object schema based on input values. This option is even more concise and uses fewer tokens, but requires smaller batch sizes and can be slow and unreliable. Due to its unreliability, it may lead to more resubmission retries, potentially wasting more tokens in the process.--experimental-use-full-context
Include the full context of translated data to work well with prompt caching.
The translated lines per user and assistant message pairs are sliced as defined by --history-prompt-length (by default --history-prompt-length 10), it is recommended to set this to the largest batch size (by default --batch-sizes "[10,100]"): --history-prompt-length 100.
Enabling this may risk running into the model's context window limit, typically 128K, but should be sufficient for most cases.
--log-level <level>
Log level (default: debug, choices: trace, debug, info, warn, error, silent)
--silent
Same as --log-level silent
--quiet
Same as --log-level silent
Additional Options for GPT:
-m, --model <model>"gpt-4o-mini") https://platform.openai.com/docs/api-reference/chat/create--stream-t, --temperature <temperature>0.3 to be more deterministic for translation (default: 1) https://platform.openai.com/docs/api-reference/chat/create#chat-create-temperature--top_p <top_p>--presence_penalty <presence_penalty>--frequency_penalty <frequency_penalty--logit_bias <logit_bias>cli/translator.mjs --plain-text "你好"Standard Output
Hello.
cli/translator.mjs --stream --to "Emojis" --temperature 0 --plain-text "$(curl 'https://api.chucknorris.io/jokes/0ECUwLDTTYSaeFCq6YMa5A' | jq .value)"Input Argument
Chuck Norris can walk with the animals, talk with the animals; grunt and squeak and squawk with the animals... and the animals, without fail, always say 'yessir Mr. Norris'.
Standard Output
????♂️??????????????️??️❗️??????=???????????????????=??.
cli/translator.mjs --stream --system-instruction "Scramble characters of words while only keeping the start and end letter" --no-prefix-number --no-line-matching --temperature 0 --plain-text "Chuck Norris can walk with the animals, talk with the animals;"Standard Output
Cuhck Nroris can wakl wtih the aiamnls, talk wtih the aiamnls;
cli/translator.mjs --stream --system-instruction "Unscramble characters back to English" --no-prefix-number --no-line-matching --temperature 0 --plain-text "Cuhck Nroris can wakl wtih the aiamnls, talk wtih the aiamnls;"Standard Output
Chuck Norris can walk with the animals, talk with the animals;
cli/translator.mjs --stream --temperature 0 --input test/data/test_cn.txtInput file: test/data/test_cn.txt
你好。
拜拜！
Standard Output
Hello.
Goodbye!
cli/translator.mjs --stream --temperature 0 --input test/data/test_ja_small.srtInput file: test/data/test_ja_small.srt
1
00:00:00,000 --> 00:00:02,000
おはようございます。
2
00:00:02,000 --> 00:00:05,000
お元気ですか？
3
00:00:05,000 --> 00:00:07,000
はい、元気です。
4
00:00:08,000 --> 00:00:12,000
今日は天気がいいですね。
5
00:00:12,000 --> 00:00:16,000
はい、とてもいい天気です。Output file: test/data/test_ja_small.srt.out_English.srt
1
00:00:00,000 --> 00:00:02,000
Good morning.
2
00:00:02,000 --> 00:00:05,000
How are you?
3
00:00:05,000 --> 00:00:07,000
Yes, I'm doing well.
4
00:00:08,000 --> 00:00:12,000
The weather is nice today, isn't it?
5
00:00:12,000 --> 00:00:16,000
Yes, it's very nice weather.System Instruction
Tokens: 5
Translate Japanese to English
| Input | Prompt | Transform | Output |
|---|---|---|---|
|
Tokens: |
Tokens: |
Tokens: |
Tokens: |
1
00:00:00,000 --> 00:00:02,000
おはようございます。
2
00:00:02,000 --> 00:00:05,000
お元気ですか？
3
00:00:05,000 --> 00:00:07,000
はい、元気です。
4
00:00:08,000 --> 00:00:12,000
今日は天気がいいですね。
5
00:00:12,000 --> 00:00:16,000
はい、とてもいい天気です。 |
|
|
1
00:00:00,000 --> 00:00:02,000
Good morning.
2
00:00:02,000 --> 00:00:05,000
How are you?
3
00:00:05,000 --> 00:00:07,000
Yes, I'm doing well.
4
00:00:08,000 --> 00:00:12,000
The weather is nice today, isn't it?
5
00:00:12,000 --> 00:00:16,000
Yes, it's very nice weather. |
TODO: More analysis
5 SRT lines:
test/data/test_ja_small.srt
299
362
276
30 SRT lines:
test/data/test_ja.srt
1625
6719
[5, 10], including up to 10 historical prompt context:1036
