726 lines
24 KiB
Python
726 lines
24 KiB
Python
# Libraries
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import json, os, re, textwrap, threading, time, traceback, tiktoken, openai, csv
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from concurrent.futures import ThreadPoolExecutor, as_completed
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from pathlib import Path
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from colorama import Fore
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from dotenv import load_dotenv
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from retry import retry
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from tqdm import tqdm
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# Open AI
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load_dotenv()
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if os.getenv('api').replace(' ', '') != '':
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openai.base_url = os.getenv('api')
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openai.organization = os.getenv('org')
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openai.api_key = os.getenv('key')
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#Globals
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MODEL = os.getenv('model')
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TIMEOUT = int(os.getenv('timeout'))
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LANGUAGE = os.getenv('language').capitalize()
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PROMPT = Path('prompt.txt').read_text(encoding='utf-8')
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VOCAB = Path('vocab.txt').read_text(encoding='utf-8')
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THREADS = int(os.getenv('threads'))
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LOCK = threading.Lock()
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WIDTH = int(os.getenv('width'))
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LISTWIDTH = int(os.getenv('listWidth'))
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NOTEWIDTH = int(os.getenv('noteWidth'))
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MAXHISTORY = 10
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ESTIMATE = ''
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TOKENS = [0, 0]
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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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MISMATCH = [] # Lists files that thdata a mismatch error (Length of GPT list response is wrong)
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BRACKETNAMES = False
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TOTALLINES = 0
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PBAR = None
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# Pricing - Depends on the model https://openai.com/pricing
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# Batch Size - GPT 3.5 Struggles past 15 lines per request. GPT4 struggles past 50 lines per request
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# If you are getting a MISMATCH LENGTH error, lower the batch size.
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if 'gpt-3.5' in MODEL:
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INPUTAPICOST = .002
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OUTPUTAPICOST = .002
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BATCHSIZE = 10
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FREQUENCY_PENALTY = 0.2
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elif 'gpt-4' in MODEL:
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INPUTAPICOST = .005
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OUTPUTAPICOST = .015
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BATCHSIZE = 20
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FREQUENCY_PENALTY = 0.1
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#tqdm Globals
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BAR_FORMAT='{l_bar}{bar:10}{r_bar}{bar:-10b}'
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POSITION = 0
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LEAVE = False
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def handleEushully(filename, estimate):
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global ESTIMATE, TOKENS
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ESTIMATE = estimate
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if not ESTIMATE:
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with open('translated/' + filename, 'w+t', newline='', encoding='utf-8') as writeFile:
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# Translate
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start = time.time()
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translatedData = openFiles(filename, writeFile)
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# Print Result
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end = time.time()
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tqdm.write(getResultString(translatedData, end - start, filename))
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with LOCK:
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TOKENS[0] += translatedData[1][0]
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TOKENS[1] += translatedData[1][1]
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else:
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# Translate
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start = time.time()
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translatedData = openFilesEstimate(filename)
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# Print Result
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end = time.time()
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tqdm.write(getResultString(translatedData, end - start, filename))
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with LOCK:
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TOKENS[0] += translatedData[1][0]
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TOKENS[1] += translatedData[1][1]
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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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def openFiles(filename, writeFile):
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with open('files/' + filename, 'r', encoding='utf-8') as readFile, writeFile:
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translatedData = parseCSV(readFile, writeFile, filename)
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return translatedData
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def openFilesEstimate(filename):
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with open('files/' + filename, 'r', encoding='utf-8') as readFile:
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translatedData = parseCSV(readFile, '', filename)
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return translatedData
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def getResultString(translatedData, translationTime, filename):
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# File Print String
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totalTokenstring =\
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Fore.YELLOW +\
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'[Input: ' + str(translatedData[1][0]) + ']'\
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'[Output: ' + str(translatedData[1][1]) + ']'\
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'[Lines: ' + str(TOTALLINES) + ']'\
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'[Cost: ${:,.4f}'.format((translatedData[1][0] * .001 * INPUTAPICOST) +\
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(translatedData[1][1] * .001 * OUTPUTAPICOST)) + ']'
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timeString = Fore.BLUE + '[' + str(round(translationTime, 1)) + 's]'
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if translatedData[2] is None:
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# Success
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return filename + ': ' + totalTokenstring + timeString + Fore.GREEN + u' \u2713 ' + Fore.RESET
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else:
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# Fail
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try:
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raise translatedData[2]
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except Exception as e:
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traceback.print_exc()
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errorString = str(e) + Fore.RED
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return filename + ': ' + totalTokenstring + timeString + Fore.RED + u' \u2717 ' +\
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errorString + Fore.RESET
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def parseCSV(readFile, writeFile, filename):
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totalTokens = [0,0]
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totalLines = 0
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textHistory = []
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global LOCK
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# Get total for progress bar
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totalLines = len(readFile.readlines())
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readFile.seek(0)
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data = []
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reader = csv.reader(readFile, delimiter=',',)
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if not ESTIMATE:
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writer = csv.writer(writeFile, delimiter=',', quoting=csv.QUOTE_ALL)
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else:
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writer = ''
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# Write All Rows to Data
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for row in reader:
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data.append(row)
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with tqdm(bar_format=BAR_FORMAT, position=POSITION, total=totalLines, leave=LEAVE) as pbar:
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pbar.desc=filename
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pbar.total=totalLines
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try:
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if 'SC' == filename[0:2] or 'SP' == filename[0:2]:
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response = translateDialogue(data, pbar, writer, format, filename, [])
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totalTokens[0] = response[0]
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totalTokens[1] = response[1]
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elif 'UI' == filename[0:2]:
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response = translateUI(data, pbar, writer, format, filename, [])
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totalTokens[0] = response[0]
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totalTokens[1] = response[1]
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except Exception as e:
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traceback.print_exc()
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return [reader, totalTokens, None]
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def translateDialogue(data, pbar, writer, format, filename, translatedList):
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global LOCK, ESTIMATE, PBAR
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tokens = [0,0]
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stringList = [None] * 2
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i = 0
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try:
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# Set Variables
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speakerColumn = 0
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textSourceColumn = 1
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textTargetColumn = 3
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# Lists
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dialogueList = []
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setStringList = []
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# Parse Data
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while i in range(len(data)):
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# Dialogue
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if len(data[i][speakerColumn]) > 0 and data[i][speakerColumn][0].isupper() \
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or 'show-text' in data[i][speakerColumn] \
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or 'concat' in data[i][speakerColumn]:
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# Speaker
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speaker = ''
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if data[i][speakerColumn][0].isupper():
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if speakerColumn != None:
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response = getSpeaker(data[i][speakerColumn])
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tokens[0] += response[1][0]
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tokens[1] += response[1][1]
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speaker = response[0]
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# Dialogue
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jaString = data[i][textSourceColumn]
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# Remove Textwrap
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jaString = jaString.replace('\n', ' ')
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# Replace Unicode
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jaString = jaString.replace('\ue000', '...')
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# Pass 1
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if translatedList == []:
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# Add to list
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if speaker:
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dialogueList.append(f'[{speaker}]: {jaString}')
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else:
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dialogueList.append(f'[InnerVoice]: {jaString}')
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stringList[0] = dialogueList
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# Pass 2
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else:
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if translatedList[0]:
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# Grab and Pop
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translatedText = translatedList[0][0]
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translatedList[0].pop(0)
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# Set to None if empty list
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if len(translatedList[0]) <= 0:
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translatedList[0] = None
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# Remove speaker
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translatedText = re.sub(r'^\[(.+?)\]\s?[|:]\s?', '', translatedText)
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# Set Data
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data[i][textTargetColumn] = f'{translatedText}'
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# Set String Command
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if 'set-string' in data[i][speakerColumn]:
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jaString = data[i][textSourceColumn]
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# Pass 1
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if translatedList == []:
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setStringList.append(jaString)
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stringList[1] = setStringList
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# Pass 2
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else:
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if len(translatedList) > 1 and translatedList[1]:
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# Grab and Pop
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translatedText = translatedList[1][0]
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translatedList[1].pop(0)
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# Set to None if empty list
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if len(translatedList[1]) <= 0:
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translatedList[1] = -1
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# Textwrap
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translatedText = textwrap.fill(translatedText, WIDTH)
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# Set Data
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data[i][textTargetColumn] = f'{translatedText}'
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# Iterate
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i += 1
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# EOF
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stringList = [x for x in stringList if x is not None]
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if len(stringList) > 0:
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# Translate
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pbar.total = 0
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for i in range(len(stringList)):
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# Set Progress
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pbar.total += len(stringList[i])
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pbar.refresh()
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PBAR = pbar
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response = translateGPT(stringList[i], '', True)
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tokens[0] += response[1][0]
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tokens[1] += response[1][1]
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translatedList.append(response[0])
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# Set Strings
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if len(stringList) == len(translatedList):
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translateDialogue(data, pbar, writer, format, filename, translatedList)
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else:
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# Write all Data
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with LOCK:
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if not ESTIMATE:
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for row in data:
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writer.writerow(row)
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except Exception as e:
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traceback.print_exc()
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return tokens
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def translateUI(data, pbar, writer, format, filename, translatedList):
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global LOCK, ESTIMATE
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tokens = [0,0]
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stringList = [None] * 1
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i = 0
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try:
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# Lists
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textList = []
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# Parse Data
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while i in range(len(data)):
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# Text
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for j in range(len(data[i])):
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jaString = data[i][j]
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# If Japanese Text, Translate it.
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if not re.search(r'[一-龠ぁ-ゔァ-ヴーａ-ｚＡ-Ｚ０-９]+', jaString):
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continue
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# Replace Unicode
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jaString = jaString.replace('', '...')
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# Pass 1
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if translatedList == []:
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# Add to list
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textList.append(f'{jaString}')
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stringList[0] = textList
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# Pass 2
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else:
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if translatedList[0]:
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# Grab and Pop
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translatedText = translatedList[0][0]
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translatedList[0].pop(0)
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# Set to None if empty list
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if len(translatedList[0]) <= 0:
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translatedList[0] = None
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# Set Data
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if len(data[i]) > j + 1:
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data[i][j+1] = f'{translatedText}'
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# Iterate
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i += 1
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# EOF
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stringList = [x for x in stringList if x is not None]
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if len(stringList) > 0:
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# Translate
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pbar.total = 0
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for i in range(len(stringList)):
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# Set Progress
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pbar.total += len(stringList[i])
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pbar.refresh()
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response = translateGPT(stringList[i], '', True)
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tokens[0] += response[1][0]
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tokens[1] += response[1][1]
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translatedList.append(response[0])
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# Set Strings
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if len(stringList) == len(translatedList):
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translateUI(data, pbar, writer, format, filename, translatedList)
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# Write all Data
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with LOCK:
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if not ESTIMATE:
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for row in data:
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writer.writerow(row)
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except Exception as e:
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traceback.print_exc()
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return tokens
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# Save some money and enter the character before translation
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def getSpeaker(speaker):
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match speaker:
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case 'ファイン':
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return ['Fine', [0,0]]
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case '':
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return ['', [0,0]]
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case _:
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# Store Speaker
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if speaker not in str(NAMESLIST):
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response = translateGPT(speaker, 'Reply with only the '+ LANGUAGE +' translation of the NPC name.', False)
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response[0] = response[0].replace("'S", "'s")
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speakerList = [speaker, response[0]]
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NAMESLIST.append(speakerList)
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return response
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# Find Speaker
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else:
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for i in range(len(NAMESLIST)):
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if speaker == NAMESLIST[i][0]:
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return [NAMESLIST[i][1],[0,0]]
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return [speaker,[0,0]]
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def subVars(jaString):
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jaString = jaString.replace('\u3000', ' ')
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# Nested
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count = 0
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nestedList = re.findall(r'[\\]+[\w]+\[[\\]+[\w]+\[[0-9]+\]\]', jaString)
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nestedList = set(nestedList)
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if len(nestedList) != 0:
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for icon in nestedList:
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jaString = jaString.replace(icon, '[Nested_' + str(count) + ']')
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count += 1
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# Icons
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count = 0
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iconList = re.findall(r'[\\]+[iIkKwWaA]+\[[0-9]+\]', jaString)
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iconList = set(iconList)
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if len(iconList) != 0:
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for icon in iconList:
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jaString = jaString.replace(icon, '[Ascii_' + str(count) + ']')
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count += 1
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# Colors
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count = 0
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colorList = re.findall(r'[\\]+[cC]\[[0-9]+\]', jaString)
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colorList = set(colorList)
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if len(colorList) != 0:
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for color in colorList:
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jaString = jaString.replace(color, '[Color_' + str(count) + ']')
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count += 1
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# Names
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count = 0
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nameList = re.findall(r'[\\]+[nN]\[.+?\]+', jaString)
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nameList = set(nameList)
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if len(nameList) != 0:
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for name in nameList:
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jaString = jaString.replace(name, '[Noun_' + str(count) + ']')
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count += 1
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# Variables
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count = 0
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varList = re.findall(r'[\\]+[vV]\[[0-9]+\]', jaString)
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varList = set(varList)
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if len(varList) != 0:
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for var in varList:
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jaString = jaString.replace(var, '[Var_' + str(count) + ']')
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count += 1
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# Formatting
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count = 0
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formatList = re.findall(r'[\\]+[\w]+\[[a-zA-Z0-9\\\[\]\_,\s-]+\]', jaString)
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formatList = set(formatList)
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if len(formatList) != 0:
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for var in formatList:
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jaString = jaString.replace(var, '[FCode_' + str(count) + ']')
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count += 1
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# Put all lists in list and return
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allList = [nestedList, iconList, colorList, nameList, varList, formatList]
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return [jaString, allList]
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def resubVars(translatedText, allList):
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# Fix Spacing and ChatGPT Nonsense
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matchList = re.findall(r'\[\s?.+?\s?\]', translatedText)
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if len(matchList) > 0:
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for match in matchList:
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text = match.strip()
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translatedText = translatedText.replace(match, text)
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# Nested
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count = 0
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if len(allList[0]) != 0:
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for var in allList[0]:
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translatedText = translatedText.replace('[Nested_' + str(count) + ']', var)
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count += 1
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# Icons
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count = 0
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if len(allList[1]) != 0:
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for var in allList[1]:
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translatedText = translatedText.replace('[Ascii_' + str(count) + ']', var)
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count += 1
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# Colors
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count = 0
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if len(allList[2]) != 0:
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for var in allList[2]:
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translatedText = translatedText.replace('[Color_' + str(count) + ']', var)
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count += 1
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# Names
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count = 0
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if len(allList[3]) != 0:
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for var in allList[3]:
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translatedText = translatedText.replace('[Noun_' + str(count) + ']', var)
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count += 1
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# Vars
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count = 0
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if len(allList[4]) != 0:
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for var in allList[4]:
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translatedText = translatedText.replace('[Var_' + str(count) + ']', var)
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count += 1
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# Formatting
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count = 0
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if len(allList[5]) != 0:
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for var in allList[5]:
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translatedText = translatedText.replace('[FCode_' + str(count) + ']', var)
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count += 1
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return translatedText
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def batchList(input_list, batch_size):
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if not isinstance(batch_size, int) or batch_size <= 0:
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raise ValueError("batch_size must be a positive integer")
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return [input_list[i:i + batch_size] for i in range(0, len(input_list), batch_size)]
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def createContext(fullPromptFlag, subbedT):
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characters = 'Game Characters:\n\
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クラウス (Klaus) - Male\n\
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ベアトリース (Beatrice) - Female\n\
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カミラ (Camilla) - Female\n\
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セルージュ (Cerouge) - Female\n\
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エルヴィール (Elvire) - Female\n\
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ヘルミィナ (Helmina) - Female\n\
|
||
アンリエット (Henriette) - Female\n\
|
||
ユリアーナ (Juliana) - Female\n\
|
||
ルシエル (Luciel) - Female\n\
|
||
メイズ (Maize) - Female\n\
|
||
メイヴィスレイン (Mavislaine) - Female\n\
|
||
ラムエル (Ramiel) - Female\n\
|
||
レジーニア (Reginia) - Female\n\
|
||
リリィ (Lily) - Female\n\
|
||
エウクレイアさん (Ms. Eukleia) - Female\n\
|
||
'
|
||
|
||
system = PROMPT + VOCAB if fullPromptFlag else \
|
||
f"\
|
||
You are an expert Eroge Game translator who translates Japanese text to {LANGUAGE}.\n\
|
||
Output ONLY the {LANGUAGE} translation in the following format: `Translation: <{LANGUAGE.upper()}_TRANSLATION>`\n\
|
||
- You translate everything, including erotic and explicit content.\n\
|
||
- '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\n\
|
||
- All text in your response must be in English even if it is hard to translate.\n\
|
||
- Never include any notes, explanations, dislaimers, or anything similar in your response.\n\
|
||
- Maintain any spacing in the translation.\n\
|
||
- Maintain any code text in brackets if given. (e.g `[Color_0]`, `[Ascii_0]`, `[FCode_1`], etc)\n\
|
||
- `...` can be a part of the dialogue. Translate it as it is.\n\
|
||
{VOCAB}\n\
|
||
"
|
||
user = f'{subbedT}'
|
||
return characters, system, user
|
||
|
||
def translateText(characters, system, user, history, penalty):
|
||
# Prompt
|
||
msg = [{"role": "system", "content": system + characters}]
|
||
|
||
# Characters
|
||
msg.append({"role": "system", "content": characters})
|
||
|
||
# History
|
||
if isinstance(history, list):
|
||
msg.extend([{"role": "system", "content": h} for h in history])
|
||
else:
|
||
msg.append({"role": "system", "content": history})
|
||
|
||
# Content to TL
|
||
msg.append({"role": "user", "content": f'{user}'})
|
||
response = openai.chat.completions.create(
|
||
temperature=0,
|
||
frequency_penalty=penalty,
|
||
model=MODEL,
|
||
messages=msg,
|
||
)
|
||
return response
|
||
|
||
def cleanTranslatedText(translatedText, varResponse):
|
||
placeholders = {
|
||
f'{LANGUAGE} Translation: ': '',
|
||
'Translation: ': '',
|
||
'っ': '',
|
||
'〜': '~',
|
||
'ッ': '',
|
||
'。': '.',
|
||
'< ': '<',
|
||
'</ ': '</',
|
||
' >': '>',
|
||
'Placeholder Text': '',
|
||
'- chan': '-chan',
|
||
'- kun': '-kun',
|
||
'- san': '-san',
|
||
# Add more replacements as needed
|
||
}
|
||
for target, replacement in placeholders.items():
|
||
translatedText = translatedText.replace(target, replacement)
|
||
|
||
# Elongate Long Dashes (Since GPT Ignores them...)
|
||
translatedText = elongateCharacters(translatedText)
|
||
translatedText = resubVars(translatedText, varResponse[1])
|
||
return translatedText
|
||
|
||
def elongateCharacters(text):
|
||
# Define a pattern to match one character followed by one or more `ー` characters
|
||
# Using a positive lookbehind assertion to capture the preceding character
|
||
pattern = r'(?<=(.))ー+'
|
||
|
||
# Define a replacement function that elongates the captured character
|
||
def repl(match):
|
||
char = match.group(1) # The character before the ー sequence
|
||
count = len(match.group(0)) - 1 # Number of ー characters
|
||
return char * count # Replace ー sequence with the character repeated
|
||
|
||
# Use re.sub() to replace the pattern in the text
|
||
return re.sub(pattern, repl, text)
|
||
|
||
def extractTranslation(translatedTextList, is_list):
|
||
pattern = r'`?<Line\d+>([\\]*.*?[\\]*?)<\/?Line\d+>`?'
|
||
# If it's a batch (i.e., list), extract with tags; otherwise, return the single item.
|
||
if is_list:
|
||
matchList = re.findall(pattern, translatedTextList)
|
||
return matchList
|
||
else:
|
||
matchList = re.findall(pattern, translatedTextList)
|
||
return matchList[0][0] if matchList else translatedTextList
|
||
|
||
def countTokens(characters, system, user, history):
|
||
inputTotalTokens = 0
|
||
outputTotalTokens = 0
|
||
enc = tiktoken.encoding_for_model('gpt-4')
|
||
|
||
# Input
|
||
if isinstance(history, list):
|
||
for line in history:
|
||
inputTotalTokens += len(enc.encode(line))
|
||
else:
|
||
inputTotalTokens += len(enc.encode(history))
|
||
inputTotalTokens += len(enc.encode(system))
|
||
inputTotalTokens += len(enc.encode(characters))
|
||
inputTotalTokens += len(enc.encode(user))
|
||
|
||
# Output
|
||
outputTotalTokens += round(len(enc.encode(user))*3)
|
||
|
||
return [inputTotalTokens, outputTotalTokens]
|
||
|
||
def combineList(tlist, text):
|
||
if isinstance(text, list):
|
||
return [t for sublist in tlist for t in sublist]
|
||
return tlist[0]
|
||
|
||
@retry(exceptions=Exception, tries=5, delay=5)
|
||
def translateGPT(text, history, fullPromptFlag):
|
||
global PBAR
|
||
|
||
mismatch = False
|
||
totalTokens = [0, 0]
|
||
if isinstance(text, list):
|
||
tList = batchList(text, BATCHSIZE)
|
||
else:
|
||
tList = [text]
|
||
|
||
for index, tItem in enumerate(tList):
|
||
# Before sending to translation, if we have a list of items, add the formatting
|
||
if isinstance(tItem, list):
|
||
payload = '\n'.join([f'`<Line{i}>{item}</Line{i}>`' for i, item in enumerate(tItem)])
|
||
payload = re.sub(r'(<Line\d+)(><)(\/Line\d+>)', r'\1>Placeholder Text<\3', payload)
|
||
varResponse = subVars(payload)
|
||
subbedT = varResponse[0]
|
||
else:
|
||
varResponse = subVars(tItem)
|
||
subbedT = varResponse[0]
|
||
|
||
# Things to Check before starting translation
|
||
if not re.search(r'[一-龠ぁ-ゔァ-ヴーａ-ｚＡ-Ｚ０-９]+', subbedT):
|
||
if PBAR is not None:
|
||
PBAR.update(len(tItem))
|
||
continue
|
||
|
||
# Create Message
|
||
characters, system, user = createContext(fullPromptFlag, subbedT)
|
||
|
||
# Calculate Estimate
|
||
if ESTIMATE:
|
||
estimate = countTokens(characters, system, user, history)
|
||
totalTokens[0] += estimate[0]
|
||
totalTokens[1] += estimate[1]
|
||
continue
|
||
|
||
# Translating
|
||
response = translateText(characters, system, user, history, 0.02)
|
||
translatedText = response.choices[0].message.content
|
||
totalTokens[0] += response.usage.prompt_tokens
|
||
totalTokens[1] += response.usage.completion_tokens
|
||
|
||
# Formatting
|
||
translatedText = cleanTranslatedText(translatedText, varResponse)
|
||
if isinstance(tItem, list):
|
||
extractedTranslations = extractTranslation(translatedText, True)
|
||
tList[index] = extractedTranslations
|
||
if len(tItem) != len(extractedTranslations):
|
||
# Mismatch. Try Again
|
||
response = translateText(characters, system, user, history, 0.2)
|
||
translatedText = response.choices[0].message.content
|
||
totalTokens[0] += response.usage.prompt_tokens
|
||
totalTokens[1] += response.usage.completion_tokens
|
||
|
||
# Formatting
|
||
translatedText = cleanTranslatedText(translatedText, varResponse)
|
||
if isinstance(tItem, list):
|
||
extractedTranslations = extractTranslation(translatedText, True)
|
||
tList[index] = extractedTranslations
|
||
if len(tItem) != len(extractedTranslations):
|
||
mismatch = True # Just here for breakpoint
|
||
|
||
# Create History
|
||
with LOCK:
|
||
if PBAR is not None:
|
||
PBAR.update(len(tItem))
|
||
if not mismatch:
|
||
history = extractedTranslations[-10:] # Update history if we have a list
|
||
else:
|
||
history = text[-10:]
|
||
else:
|
||
# Ensure we're passing a single string to extractTranslation
|
||
extractedTranslations = extractTranslation(translatedText, False)
|
||
tList[index] = extractedTranslations
|
||
|
||
finalList = combineList(tList, text)
|
||
return [finalList, totalTokens]
|