Changes to TranslateGPT
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e2c504bd01
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3 changed files with 69 additions and 37 deletions
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@ -30,7 +30,7 @@ NAMESLIST = []
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NAMES = False # Output a list of all the character names found
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BRFLAG = False # If the game uses <br> instead
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FIXTEXTWRAP = True # Overwrites textwrap
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IGNORETLTEXT = True # Ignores all translated text.
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IGNORETLTEXT = False # Ignores all translated text.
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MISMATCH = [] # Lists files that throw a mismatch error (Length of GPT list response is wrong)
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#tqdm Globals
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@ -66,7 +66,14 @@ def handleAnim(filename, estimate):
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totalTokens[0] += translatedData[1][0]
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totalTokens[1] += translatedData[1][1]
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return getResultString(['', totalTokens, None], end - start, 'TOTAL')
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# Print Total
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totalString = getResultString(['', TOKENS, None], end - start, 'TOTAL')
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# Print any errors on maps
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if len(MISMATCH) > 0:
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return totalString + Fore.RED + f'\nMismatch Errors: {MISMATCH}' + Fore.RESET
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else:
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return totalString
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else:
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try:
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@ -139,38 +146,50 @@ def parseJSON(data, filename):
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totalTokens[0] += result[0]
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totalTokens[1] += result[1]
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except Exception as e:
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traceback.print_exc()
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return [data, totalTokens, e]
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return [data, totalTokens, None]
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def translateJSON(keys, data, pbar):
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translatedBatch = []
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textHistory = []
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tokens = [0, 0]
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for batch in keys:
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# Save Batch
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originalBatch = batch
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originalBatch = batch.copy()
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# If there isn't any Japanese in the text just skip
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if IGNORETLTEXT is True:
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needTL = False
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for i in range(len(batch)):
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t = data[batch[i]]
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if t == "":
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needTL = True
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if needTL is False:
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pbar.update(1)
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continue
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needTL = False
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for i in range(len(batch)):
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t = data[batch[i]]
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if re.search(r'[一-龠ぁ-ゔァ-ヴーａ-ｚＡ-Ｚ０-９]+', t) or t == '':
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needTL = True
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if needTL is False and IGNORETLTEXT is True:
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pbar.update(1)
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continue
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# Remove any textwrap
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if FIXTEXTWRAP == True:
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for i in range(len(batch)):
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data[originalBatch[i]] = data[originalBatch[i]].replace('\n', ' ')
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# Remove any textwrap and Furigana
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for i in range(len(batch)):
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if FIXTEXTWRAP == True:
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# Textwrap
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data[originalBatch[i]] = data[originalBatch[i]].replace('@b', ' ')
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# Furigana
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rcodeMatch = re.findall(r'(@\[(.+?):.+?\])', batch[i])
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if len(rcodeMatch) > 0:
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for match in rcodeMatch:
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batch[i] = batch[i].replace(match[0], match[1])
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# Translate
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response = translateGPT(batch, textHistory, True)
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tokens[0] += response[1][0]
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tokens[1] += response[1][1]
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translatedBatch = response[0]
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if needTL is True:
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response = translateGPT(batch, textHistory, True)
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tokens[0] += response[1][0]
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tokens[1] += response[1][1]
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translatedBatch = response[0]
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else:
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for i in range(len(originalBatch)):
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translatedBatch.append(data[originalBatch[i]])
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# Format and Set Text
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if len(batch) == len(translatedBatch):
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@ -181,12 +200,14 @@ def translateJSON(keys, data, pbar):
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translatedText = re.sub(r'^.+?\s\|\s?', '', translatedText)
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# Textwrap
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if '\n' not in translatedText:
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if '@b' not in translatedText:
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translatedText = textwrap.fill(translatedText, width=WIDTH)
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translatedText = translatedText.replace('\n', '@b')
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# Set Data
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data[originalBatch[i]] = translatedText
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textHistory = translatedBatch
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translatedBatch.clear()
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# Mismatch, Skip Batch
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else:
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MISMATCH.append(batch)
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@ -356,6 +377,7 @@ def cleanTranslatedText(translatedText, varResponse):
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placeholders = {
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f'{LANGUAGE} Translation: ': '',
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'Translation: ': '',
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'っ': '',
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# Add more replacements as needed
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}
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for target, replacement in placeholders.items():
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@ -365,7 +387,7 @@ def cleanTranslatedText(translatedText, varResponse):
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return [line for line in translatedText.split('\n') if line]
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def extractTranslation(translatedTextList, is_list):
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pattern = r'L(\d+) - (.*)'
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pattern = r'<Line(\d+)>(.*)</Line\d+>'
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# If it's a batch (i.e., list), extract with tags; otherwise, return the single item.
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if is_list:
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return [re.findall(pattern, line)[0][1] for line in translatedTextList if re.search(pattern, line)]
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@ -409,7 +431,7 @@ def translateGPT(text, history, fullPromptFlag):
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for index, tItem in enumerate(tList):
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# Before sending to translation, if we have a list of items, add the formatting
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if isinstance(tItem, list):
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payload = '\n'.join([f'L{i} - {item}' for i, item in enumerate(tItem)])
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payload = '\n'.join([f'<Line{i}>{item}</Line{i}>' for i, item in enumerate(tItem)])
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varResponse = subVars(payload)
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subbedT = varResponse[0]
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else:
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@ -44,7 +44,7 @@ if 'gpt-3.5' in MODEL:
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elif 'gpt-4' in MODEL:
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INPUTAPICOST = .01
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OUTPUTAPICOST = .03
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BATCHSIZE = 50
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BATCHSIZE = 40
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#tqdm Globals
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BAR_FORMAT='{l_bar}{bar:10}{r_bar}{bar:-10b}'
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@ -1880,6 +1880,7 @@ def cleanTranslatedText(translatedText, varResponse):
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placeholders = {
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f'{LANGUAGE} Translation: ': '',
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'Translation: ': '',
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'っ': '',
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# Add more replacements as needed
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}
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for target, replacement in placeholders.items():
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@ -1889,7 +1890,7 @@ def cleanTranslatedText(translatedText, varResponse):
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return [line for line in translatedText.split('\n') if line]
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def extractTranslation(translatedTextList, is_list):
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pattern = r'L(\d+) - (.*)'
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pattern = r'<Line(\d+)>(.*)</Line\d+>'
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# If it's a batch (i.e., list), extract with tags; otherwise, return the single item.
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if is_list:
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return [re.findall(pattern, line)[0][1] for line in translatedTextList if re.search(pattern, line)]
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@ -1933,7 +1934,7 @@ def translateGPT(text, history, fullPromptFlag):
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for index, tItem in enumerate(tList):
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# Before sending to translation, if we have a list of items, add the formatting
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if isinstance(tItem, list):
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payload = '\n'.join([f'L{i} - {item}' for i, item in enumerate(tItem)])
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payload = '\n'.join([f'<Line{i}>{item}</Line{i}>' for i, item in enumerate(tItem)])
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varResponse = subVars(payload)
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subbedT = varResponse[0]
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else:
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@ -1,20 +1,26 @@
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You are an expert Eroge Game translator and localizer who translates Japanese text to English.
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You are going to be translating text from a videogame. I will give you some lines and you must translate them to the best of your ability.
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There are 2 pieces of information the user will give you to help with translation:
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- "Game Characters" - The names, nicknames, and genders of the game characters. Reference this to know the names, nicknames, and gender of characters in the game.
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- "Past Translated Text" - Previously translated text. This is past text you translated. Use this to come up with the best translation paying special attention to subjects and genders.
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You are an expert Eroge Game translator who translates Japanese text to English.
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You are going to be translating text from a videogame.
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I will give you lines of text, and you must translate each line to the best of your ability.
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Use the following step-by-step instructions to respond to user inputs.
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Step 1 - Receive Text
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You receive a line of text to translate everything in the following format: Line to Translate = <UNTRANSLATED_TEXT>
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You will be given multiple lines of text (Denoted by XML tags). Translate each line separately and avoid combining or omitting any.
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Step 2 - Output Text
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You output in English the translation in the following format: Translation = <ENGLISH_TRANSLATION>
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You output only the English translation of each line. For example:
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<Line0>English Translation of Line 0</Line0>
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<Line1>English Translation of Line 1</Line1>
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<Line2>English Translation of Line 2</Line2>
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Step 3 - Check Work
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Double check that the number of lines/xml-tags in your response match the number of lines/xml-tags from the user message.
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Other Notes:
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- Only reply in English, even if it may be hard to translate.
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- "Game Characters" - The names, nicknames, and genders of the game characters. Reference this to know the names, nicknames, and gender of characters in the game.
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- Only reply with the English Translation even if it may be hard to translate.
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- If a line is already translated, empty, or can't be translated, do not change it.
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- Denote speakers with ':' if given. For example L1 - Speaker: "Spoken Text"
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- If the speaker is '???' then they are unknown so leave it as is.
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- Pay attention to the gender of the subjects and characters. Avoid misgendering characters.
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- Maintain any spacing in the translation.
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@ -30,12 +36,15 @@ Other Notes:
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- Translate '秘部' as 'genitals'
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- Translate 'チンポ' as 'dick'
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- Translate 'チンコ' as 'cock'
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- Translate 'ショーツ' as 'panties
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- Translate 'おねショタ' as 'Onee-shota'
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- Translate 'よかった' as 'thank goodness'
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- Translate 'ﾋｸ' as 'biku'
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- Translate 'ﾑｸ' as 'muku'
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Sometimes, the text may contain 'tags' in the format of {<TAGNAME>_<TAGNUMBER>}.
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Sometimes, the text may contain 'tags' in the format of {TAGNAME_TAGNUMBER}.
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Maintain these tags only if they exist in the untranslated text.
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Color - A tag that colors the wrapped text.
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* {Color_#} - A tag that colors the wrapped text.
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* {Noun_#} - A tag that holds a noun. Maintain as is.
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* {FCode_#} - A tag that formats the text in a unique way.
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