# Libraries import json, os, re, textwrap, threading, time, traceback, tiktoken, openai, csv from concurrent.futures import ThreadPoolExecutor, as_completed 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 = int(os.getenv('noteWidth')) 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 = True # Ignores all translated text. MISMATCH = [] # Lists files that thdata a mismatch error (Length of GPT list response is wrong) BRACKETNAMES = 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 FREQUENCY_PENALTY = 0.2 elif 'gpt-4' in MODEL: INPUTAPICOST = .005 OUTPUTAPICOST = .015 BATCHSIZE = 40 FREQUENCY_PENALTY = 0.1 #tqdm Globals BAR_FORMAT='{l_bar}{bar:10}{r_bar}{bar:-10b}' POSITION = 0 LEAVE = False PBAR = None def handleCSV(filename, estimate): global ESTIMATE, TOKENS ESTIMATE = estimate if not ESTIMATE: with open('translated/' + filename, 'w+t', newline='', encoding='utf-8-sig') as writeFile: # Translate start = time.time() translatedData = openFiles(filename, writeFile) # Print Result end = time.time() tqdm.write(getResultString(translatedData, end - start, filename)) with LOCK: TOKENS[0] += translatedData[1][0] TOKENS[1] += translatedData[1][1] else: # Translate start = time.time() translatedData = openFilesEstimate(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 def openFiles(filename, writeFile): with open('files/' + filename, 'r', encoding='utf-8-sig') as readFile, writeFile: translatedData = parseCSV(readFile, writeFile, filename) return translatedData def openFilesEstimate(filename): with open('files/' + filename, 'r', encoding='utf-8-sig') as readFile: translatedData = parseCSV(readFile, '', filename) return translatedData 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] is 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 parseCSV(readFile, writeFile, filename): totalTokens = [0,0] totalLines = 0 textHistory = [] global LOCK format = '' while format == '': format = input('\n\nSelect the CSV Format:\n\n1. Translator++') match format: case '1': format = '1' # Get total for progress bar totalLines = len(readFile.readlines()) readFile.seek(0) reader = csv.reader(readFile, delimiter=',') if not ESTIMATE: writer = csv.writer(writeFile, delimiter=',', quotechar='\"') else: writer = '' with tqdm(bar_format=BAR_FORMAT, position=POSITION, total=totalLines, leave=LEAVE) as pbar: pbar.desc=filename pbar.total=totalLines # Grab All Rows data = [] for row in reader: data.append(row) try: response = translateCSV(data, pbar, writer, filename, None, format) totalTokens[0] = response[0] totalTokens[1] = response[1] except Exception as e: traceback.print_exc() return [data, totalTokens, None] def translateCSV(data, pbar, writer, filename, translatedList, format): global LOCK, ESTIMATE, PBAR PBAR = pbar translatedText = '' totalTokens = [0,0] i = 0 stringList = [] try: # Translate while i < len(data): match format: # T++ Format: Japanese Text on column 1. English on Column 2 case '1': # Get String if data[i][1] == "": jaString = data[i][0] # Remove Textwrap jaString = jaString.replace('\n', ' ') # Pass 1 if not translatedList: stringList.append(jaString) # Pass 2 else: # Grab and Pop translatedText = translatedList[0] translatedList.pop(0) # Add Wordwrap translatedText = textwrap.fill(translatedText, WIDTH) # Set Data data[i][1] = translatedText # Iterate i += 1 # EOF if len(stringList) > 0: # Set Progress pbar.total = len(stringList) pbar.refresh() # Translate response = translateGPT(stringList, '', True) totalTokens[0] += response[1][0] totalTokens[1] += response[1][1] translatedList = response[0] # Set Strings if len(stringList) == len(translatedList): translateCSV(data, pbar, writer, filename, translatedList, format) # Mismatch else: with LOCK: if filename not in MISMATCH: MISMATCH.append(filename) # Write all Data with LOCK: if not ESTIMATE: for row in data: writer.writerow(row) except Exception: traceback.print_exc() # Write all Data with LOCK: if not ESTIMATE: for row in data: writer.writerow(row) return totalTokens return totalTokens # Save some money and enter the character before translation def getSpeaker(speaker): 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 the '+ LANGUAGE +' translation of the NPC name.', False) response[0] = response[0].title() response[0] = response[0].replace("'S", "'s") # Retry if name doesn't translate for some reason if re.search(r'([a-zA-Z??])', response[0]) == None: response = translateGPT(speaker, 'Reply with the '+ LANGUAGE +' translation of the NPC name.', False) response[0] = response[0].title() 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'([\\]+c\[\d+\][\\]+c|[\\]+c\[\d+\])', 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\ レナリス (Renalith) - Female\n\ スクルー (Sukuru) - Female\n\ シスターミサ (Sister Misa) - Female\n\ オリン (Orin) - Female\n\ プローテ (Prote) - Female\n\ 夜霧 (Night Fog) - Female\n\ ワウ (Wao) - Female\n\ ファンナ (Fanna) - Female\n\ 精霊主スクルド (Spirit God Skuld) - Female\n\ エキドナ (Echnida) - Female\n\ マルス (Mars) - Male\n\ ラヴィー (Lavi) - Unknown\n\ 魅音 (Mion) - Female\n\ ヴィオラ (Viola) - Female\n\ リンメイ (Lin Mei) - Female\n\ リネット (Lynette) - Female\n\ チェロル (Cheryl) - Female\n\ カルーア姫 (Princess Karua) - Female\n\ 田姫 (Tajirme) - Female\n\ リュート (Luto) - Male\n\ ホルン (Horn) - Female\n\ ルメラ (Lumera) - Female\n\ 末嬉 (Sueki) - Female\n\ モニカ姫 (Princess Monica) - Female\n\ エメルーラ (Emerald) - Female\n\ フンシス (Funsis) - Male \n\ バゼット (Bazzet) - 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'```json\n{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, response_format={ "type": "json_object" }, 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): try: line_dict = json.loads(translatedTextList) # If it's a batch (i.e., list), extract with tags; otherwise, return the single item. if is_list: string_list = list(line_dict.values()) return string_list except Exception as e: print(e) return 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 = {f"Line{i+1}": string for i, string in enumerate(tItem)} payload = json.dumps(payload, indent=4, ensure_ascii=False) 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 # Check Translation 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, 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) if len(tItem) != len(extractedTranslations): mismatch = True # Just here for breakpoint # Set if no mismatch if mismatch == False: tList[index] = extractedTranslations history = extractedTranslations[-10:] # Update history if we have a list else: history = text[-10:] mismatch = False # Update Loading Bar with LOCK: if PBAR is not None: PBAR.update(len(tItem)) else: # Ensure we're passing a single string to extractTranslation extractedTranslations = extractTranslation(translatedText, False) tList[index] = extractedTranslations finalList = combineList(tList, text) return [finalList, totalTokens]