# Libraries import os import re import textwrap import threading import time import traceback import tiktoken import openai from pathlib import Path from colorama import Fore from dotenv import load_dotenv from retry import retry from tqdm import tqdm # Open AI load_dotenv() if os.getenv('api').replace(' ', '') != '': openai.base_url = os.getenv('api') openai.organization = os.getenv('org') openai.api_key = os.getenv('key') #Globals MODEL = os.getenv('model') TIMEOUT = int(os.getenv('timeout')) LANGUAGE = os.getenv('language').capitalize() PROMPT = Path('prompt.txt').read_text(encoding='utf-8') VOCAB = Path('vocab.txt').read_text(encoding='utf-8') THREADS = int(os.getenv('threads')) LOCK = threading.Lock() WIDTH = int(os.getenv('width')) LISTWIDTH = int(os.getenv('listWidth')) NOTEWIDTH = 70 MAXHISTORY = 10 ESTIMATE = '' TOKENS = [0, 0] NAMESLIST = [] NAMES = False # Output a list of all the character names found BRFLAG = False # If the game uses
instead FIXTEXTWRAP = True # Overwrites textwrap IGNORETLTEXT = False # Ignores all translated text. MISMATCH = [] # Lists files that throw a mismatch error (Length of GPT list response is wrong) #tqdm Globals BAR_FORMAT='{l_bar}{bar:10}{r_bar}{bar:-10b}' POSITION = 0 LEAVE = False # Pricing - Depends on the model https://openai.com/pricing # Batch Size - GPT 3.5 Struggles past 15 lines per request. GPT4 struggles past 50 lines per request # If you are getting a MISMATCH LENGTH error, lower the batch size. if 'gpt-3.5' in MODEL: INPUTAPICOST = .002 OUTPUTAPICOST = .002 BATCHSIZE = 10 elif 'gpt-4' in MODEL: INPUTAPICOST = .005 OUTPUTAPICOST = .015 BATCHSIZE = 40 def handleRegex(filename, estimate): global ESTIMATE ESTIMATE = estimate if ESTIMATE: start = time.time() translatedData = openFiles(filename) # Print Result end = time.time() tqdm.write(getResultString(translatedData, end - start, filename)) with LOCK: TOKENS[0] += translatedData[1][0] TOKENS[1] += translatedData[1][1] # Print Total totalString = getResultString(['', TOKENS, None], end - start, 'TOTAL') # Print any errors on maps if len(MISMATCH) > 0: return totalString + Fore.RED + f'\nMismatch Errors: {MISMATCH}' + Fore.RESET else: return totalString else: try: with open('translated/' + filename, 'w', encoding='cp932', errors='ignore') as outFile: start = time.time() translatedData = openFiles(filename) # Print Result end = time.time() outFile.writelines(translatedData[0]) tqdm.write(getResultString(translatedData, end - start, filename)) with LOCK: TOKENS[0] += translatedData[1][0] TOKENS[1] += translatedData[1][1] except Exception: traceback.print_exc() return 'Fail' return getResultString(['', TOKENS, None], end - start, 'TOTAL') def getResultString(translatedData, translationTime, filename): # File Print String totalTokenstring =\ Fore.YELLOW +\ '[Input: ' + str(translatedData[1][0]) + ']'\ '[Output: ' + str(translatedData[1][1]) + ']'\ '[Cost: ${:,.4f}'.format((translatedData[1][0] * .001 * INPUTAPICOST) +\ (translatedData[1][1] * .001 * OUTPUTAPICOST)) + ']' timeString = Fore.BLUE + '[' + str(round(translationTime, 1)) + 's]' if translatedData[2] == None: # Success return filename + ': ' + totalTokenstring + timeString + Fore.GREEN + u' \u2713 ' + Fore.RESET else: # Fail try: raise translatedData[2] except Exception as e: traceback.print_exc() errorString = str(e) + Fore.RED return filename + ': ' + totalTokenstring + timeString + Fore.RED + u' \u2717 ' +\ errorString + Fore.RESET def openFiles(filename): with open('files/' + filename, 'r', encoding='shift_jis') as readFile: translatedData = parseRegex(readFile, filename) # Delete lines marked for deletion finalData = [] for line in translatedData[0]: if line != '\\d\n': finalData.append(line) translatedData[0] = finalData return translatedData def parseRegex(readFile, filename): totalTokens = [0,0] # Read File into data data = readFile.readlines() # Create Progress Bar with tqdm(bar_format=BAR_FORMAT, position=POSITION, leave=LEAVE) as pbar: pbar.desc=filename try: result = translateRegex(data, pbar, filename, []) totalTokens[0] += result[0] totalTokens[1] += result[1] except Exception as e: traceback.print_exc() return [data, totalTokens, e] return [data, totalTokens, None] def translateRegex(data, pbar, filename, translatedList): stringList = [] currentGroup = [] tokens = [0,0] speaker = '' voice = False global LOCK, ESTIMATE i = 0 while i < len(data): voice = False speaker = '' if 'actorID' in data[i]: # Lines match = re.search(r'label[\\]+\":[\\]+\"(.*?)\"', data[i]) if match == None: match = re.search(r'label[\\]+\":[\\]+\"(.*?)\"', data[i]) if match != None and match.group(1) != '': originalString = match.group(1) # Pass 1 if translatedList == []: # Grab Consecutive Strings jaString = match.group(1) # Remove any textwrap jaString = jaString.replace('\n', ' ') # Add String stringList.append(jaString.strip()) # Pass 2 else: # Get Text if translatedList: # Grab and Pop translatedText = translatedList[0] translatedList.pop(0) # Set to None if empty list if len(translatedList) <= 0: translatedList = None # Textwrap translatedText = textwrap.fill(translatedText, width=WIDTH) # Set Data data[i] = data[i].replace(originalString, translatedText) i += 1 # Nothing relevant. Skip Line. else: i += 1 else: i += 1 # EOF if len(stringList) > 0: # Set Progress pbar.total = len(stringList) pbar.refresh() # Translate response = translateGPT(stringList, 'Reply with the English TL of the NPC Name', True, pbar, filename) tokens[0] += response[1][0] tokens[1] += response[1][1] translatedList = response[0] # Set Strings if len(stringList) == len(translatedList): translateRegex(data, pbar, filename, translatedList) # Mismatch else: with LOCK: if filename not in MISMATCH: MISMATCH.append(filename) return tokens # Save some money and enter the character before translation def getSpeaker(speaker, pbar, filename): match speaker: case 'ファイン': return ['Fine', [0,0]] case '': return ['', [0,0]] case _: # Store Speaker if speaker not in str(NAMESLIST): response = translateGPT(speaker, 'Reply with only the '+ LANGUAGE +' translation of the NPC name.', False, pbar, filename) response[0] = response[0].replace("'S", "'s") speakerList = [speaker, response[0]] NAMESLIST.append(speakerList) return response # Find Speaker else: for i in range(len(NAMESLIST)): if speaker == NAMESLIST[i][0]: return [NAMESLIST[i][1],[0,0]] return [speaker,[0,0]] def subVars(jaString): jaString = jaString.replace('\u3000', ' ') # Nested count = 0 nestedList = re.findall(r'[\\]+[\w]+\[[\\]+[\w]+\[[0-9]+\]\]', jaString) nestedList = set(nestedList) if len(nestedList) != 0: for icon in nestedList: jaString = jaString.replace(icon, '[Nested_' + str(count) + ']') count += 1 # Icons count = 0 iconList = re.findall(r'[\\]+[iIkKwWaA]+\[[0-9]+\]', jaString) iconList = set(iconList) if len(iconList) != 0: for icon in iconList: jaString = jaString.replace(icon, '[Ascii_' + str(count) + ']') count += 1 # Colors count = 0 colorList = re.findall(r'[\\]+[cC]\[[0-9]+\]', jaString) colorList = set(colorList) if len(colorList) != 0: for color in colorList: jaString = jaString.replace(color, '[Color_' + str(count) + ']') count += 1 # Names count = 0 nameList = re.findall(r'[\\]+[nN]\[.+?\]+', jaString) nameList = set(nameList) if len(nameList) != 0: for name in nameList: jaString = jaString.replace(name, '[Noun_' + str(count) + ']') count += 1 # Variables count = 0 varList = re.findall(r'[\\]+[vV]\[[0-9]+\]', jaString) varList = set(varList) if len(varList) != 0: for var in varList: jaString = jaString.replace(var, '[Var_' + str(count) + ']') count += 1 # Formatting count = 0 formatList = re.findall(r'[\\]+[\w]+\[[a-zA-Z0-9\\\[\]\_,\s-]+\]', jaString) formatList = set(formatList) if len(formatList) != 0: for var in formatList: jaString = jaString.replace(var, '[FCode_' + str(count) + ']') count += 1 # Put all lists in list and return allList = [nestedList, iconList, colorList, nameList, varList, formatList] return [jaString, allList] def resubVars(translatedText, allList): # Fix Spacing and ChatGPT Nonsense matchList = re.findall(r'\[\s?.+?\s?\]', translatedText) if len(matchList) > 0: for match in matchList: text = match.strip() translatedText = translatedText.replace(match, text) # Nested count = 0 if len(allList[0]) != 0: for var in allList[0]: translatedText = translatedText.replace('[Nested_' + str(count) + ']', var) count += 1 # Icons count = 0 if len(allList[1]) != 0: for var in allList[1]: translatedText = translatedText.replace('[Ascii_' + str(count) + ']', var) count += 1 # Colors count = 0 if len(allList[2]) != 0: for var in allList[2]: translatedText = translatedText.replace('[Color_' + str(count) + ']', var) count += 1 # Names count = 0 if len(allList[3]) != 0: for var in allList[3]: translatedText = translatedText.replace('[Noun_' + str(count) + ']', var) count += 1 # Vars count = 0 if len(allList[4]) != 0: for var in allList[4]: translatedText = translatedText.replace('[Var_' + str(count) + ']', var) count += 1 # Formatting count = 0 if len(allList[5]) != 0: for var in allList[5]: translatedText = translatedText.replace('[FCode_' + str(count) + ']', var) count += 1 return translatedText def batchList(input_list, batch_size): if not isinstance(batch_size, int) or batch_size <= 0: raise ValueError("batch_size must be a positive integer") return [input_list[i:i + batch_size] for i in range(0, len(input_list), batch_size)] def createContext(fullPromptFlag, subbedT): characters = 'Game Characters:\n\ フィリア (Philia) - Female\n\ アルネット (Annett) - Female\n\ ラピュセナ (Rapusena) - Female\n\ リッカ (Rikka) - Female\n\ アンデリビア (Andelivia) - Female\n\ リリアブルム (Liliabloom) - Female\n\ カルナ (Karna) - Female\n\ ラフィング=スピア (Laughing Spear) - Female\n\ ノーラ (Nora) - 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 {LANGUAGE} 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): # 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=0.1, frequency_penalty=0.1, model=MODEL, messages=msg, ) return response def cleanTranslatedText(translatedText, varResponse): placeholders = { f'{LANGUAGE} Translation: ': '', 'Translation: ': '', 'っ': '', '〜': '~', 'ッ': '', '。': '.', 'Placeholder Text': '' # 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'`?<[Ll]ine\d+>([\\]*.*?[\\]*?)<\/?[Ll]ine\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))*2) 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, pbar, filename): 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'`{item}`' for i, item in enumerate(tItem)]) payload = re.sub(r'(<)(\/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): 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) 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) if len(tItem) != len(extractedTranslations): # Mismatch. Try Again response = translateText(characters, system, user, history) 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) if len(tItem) == len(extractedTranslations): tList[index] = extractedTranslations else: MISMATCH.append(filename) else: tList[index] = extractedTranslations # Create History history = tList[index] # Update history if we have a list pbar.update(len(tList[index])) else: # Ensure we're passing a single string to extractTranslation extractedTranslations = extractTranslation(translatedText, False) tList[index] = extractedTranslations finalList = combineList(tList, text) return [finalList, totalTokens]