474 lines
No EOL
16 KiB
Python
474 lines
No EOL
16 KiB
Python
# Libraries
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import json, os, re, textwrap, threading, time, traceback, tiktoken, openai
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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.api_base = 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 = 70
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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 = 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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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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# 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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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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def handleAnim(filename, estimate):
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global ESTIMATE
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totalTokens = [0,0]
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ESTIMATE = estimate
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if estimate:
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start = time.time()
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translatedData = openFiles(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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totalTokens[0] += translatedData[1][0]
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totalTokens[1] += translatedData[1][1]
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# Print Total
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totalString = getResultString(['', totalTokens, 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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with open('translated/' + filename, 'w', encoding='UTF-8') as outFile:
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start = time.time()
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translatedData = openFiles(filename)
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# Print Result
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end = time.time()
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json.dump(translatedData[0], outFile, ensure_ascii=False, indent=4)
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tqdm.write(getResultString(translatedData, end - start, filename))
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with LOCK:
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totalTokens[0] += translatedData[1][0]
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totalTokens[1] += translatedData[1][1]
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except Exception as e:
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return 'Fail'
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return getResultString(['', totalTokens, None], end - start, 'TOTAL')
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def openFiles(filename):
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with open('files/' + filename, 'r', encoding='UTF-8-sig') as f:
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data = json.load(f)
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# Map Files
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if '.json' in filename:
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translatedData = parseJSON(data, filename)
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else:
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raise NameError(filename + ' Not Supported')
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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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'[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] == 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 parseJSON(data, filename):
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keys = list(data.keys())
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batches = [keys[i:i + BATCHSIZE] for i in range(0, len(keys), BATCHSIZE)]
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totalTokens = [0, 0]
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totalLines = 0
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totalLines = len(batches)
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global LOCK
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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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result = translateJSON(batches, data, pbar)
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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.copy()
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# If there isn't any Japanese in the text just skip
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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 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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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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for i in range(len(translatedBatch)):
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# Remove added speaker
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translatedText = translatedBatch[i]
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translatedText = re.sub(r'^.+?\s\|\s?', '', translatedText)
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# Textwrap
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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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pbar.update(1)
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continue
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pbar.update(1)
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return tokens
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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]+\[.+?\]', 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:\
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篠崎 誠一 == Shinozaki Seiichi - Male\
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宮前 遥奈 == Miyamae Haruna - Female\
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榛名 悠真 == Haruna Yuuma - Male\
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浪川 時宗 == Namikawa Tokimune - Male\
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高嶋 美雪 == Takashima Miyuki - Female'
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system = PROMPT if fullPromptFlag else \
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f'Output ONLY the {LANGUAGE} translation in the following format: `Translation: <{LANGUAGE.upper()}_TRANSLATION>`'
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user = f'{subbedT}'
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return characters, system, user
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def translateText(characters, system, user, history):
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# Prompt
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msg = [{"role": "system", "content": system}]
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# Characters
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msg.append({"role": "user", "content": characters})
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# History
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if isinstance(history, list):
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msg.extend([{"role": "user", "content": h} for h in history])
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else:
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msg.append({"role": "user", "content": history})
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# Content to TL
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msg.append({"role": "user", "content": user})
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response = openai.ChatCompletion.create(
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temperature=0,
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frequency_penalty=0,
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presence_penalty=0,
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model=MODEL,
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messages=msg,
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request_timeout=TIMEOUT,
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)
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return response
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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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translatedText = translatedText.replace(target, replacement)
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translatedText = resubVars(translatedText, varResponse[1])
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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'<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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else:
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matchList = re.findall(pattern, translatedTextList)
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return matchList[0][1] if matchList else translatedTextList
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def countTokens(characters, system, user, history):
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inputTotalTokens = 0
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outputTotalTokens = 0
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enc = tiktoken.encoding_for_model(MODEL)
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# Input
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if isinstance(history, list):
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for line in history:
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inputTotalTokens += len(enc.encode(line))
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else:
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inputTotalTokens += len(enc.encode(history))
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inputTotalTokens += len(enc.encode(system))
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inputTotalTokens += len(enc.encode(characters))
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inputTotalTokens += len(enc.encode(user))
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# Output
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outputTotalTokens += round(len(enc.encode(user))/1.7)
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return [inputTotalTokens, outputTotalTokens]
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def combineList(tlist, text):
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if isinstance(text, list):
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return [t for sublist in tlist for t in sublist]
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return tlist[0]
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@retry(exceptions=Exception, tries=5, delay=5)
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def translateGPT(text, history, fullPromptFlag):
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totalTokens = [0, 0]
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if isinstance(text, list):
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tList = batchList(text, BATCHSIZE)
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else:
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tList = [text]
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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'<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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varResponse = subVars(tItem)
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subbedT = varResponse[0]
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# Things to Check before starting translation
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if not re.search(r'[一-龠ぁ-ゔァ-ヴーａ-ｚＡ-Ｚ０-９]+', subbedT):
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continue
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# Create Message
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characters, system, user = createContext(fullPromptFlag, subbedT)
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# Calculate Estimate
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if ESTIMATE:
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estimate = countTokens(characters, system, user, history)
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totalTokens[0] += estimate[0]
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totalTokens[1] += estimate[1]
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continue
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# Translating
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response = translateText(characters, system, user, history)
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translatedText = response.choices[0].message.content
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totalTokens[0] += response.usage.prompt_tokens
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totalTokens[1] += response.usage.completion_tokens
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# Formatting
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translatedTextList = cleanTranslatedText(translatedText, varResponse)
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if isinstance(tItem, list):
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extractedTranslations = extractTranslation(translatedTextList, True)
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tList[index] = extractedTranslations
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history = extractedTranslations[-10:] # Update history if we have a list
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else:
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# Ensure we're passing a single string to extractTranslation
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extractedTranslations = extractTranslation('\n'.join(translatedTextList), False)
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tList[index] = extractedTranslations
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finalList = combineList(tList, text)
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return [finalList, totalTokens] |