from concurrent.futures import ThreadPoolExecutor, as_completed import json import os from pathlib import Path import re import sys import textwrap import threading import time import traceback import tiktoken from colorama import Fore from dotenv import load_dotenv import openai from retry import retry from tqdm import tqdm #Globals load_dotenv() openai.organization = os.getenv('org') openai.api_key = os.getenv('key') APICOST = .002 # Depends on the model https://openai.com/pricing PROMPT = Path('prompt.txt').read_text(encoding='utf-8') THREADS = 20 LOCK = threading.Lock() WIDTH = 75 LISTWIDTH = 75 MAXHISTORY = 10 ESTIMATE = '' TOTALCOST = 0 TOKENS = 0 TOTALTOKENS = 0 #tqdm Globals BAR_FORMAT='{l_bar}{bar:10}{r_bar}{bar:-10b}' POSITION=0 LEAVE=False # Flags CODE401 = True CODE102 = True CODE122 = False CODE101 = False CODE355655 = False CODE357 = False CODE356 = False CODE320 = False CODE111 = False def handleLune(filename, estimate): global ESTIMATE, TOKENS, TOTALTOKENS, TOTALCOST ESTIMATE = estimate if estimate: start = time.time() translatedData = openFiles(filename) # Print Result end = time.time() tqdm.write(getResultString(translatedData, end - start, filename)) with LOCK: TOTALCOST += translatedData[1] * .001 * APICOST TOTALTOKENS += translatedData[1] else: with open('translated/' + filename, 'w', encoding='shiftjis') 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: TOTALCOST += translatedData[1] * .001 * APICOST TOTALTOKENS += translatedData[1] return getResultString(['', TOTALTOKENS, None], end - start, 'TOTAL') def openFiles(filename): with open('files/' + filename, 'r', encoding='shiftjis') as f: translatedData = parseText(f, filename) return translatedData def getResultString(translatedData, translationTime, filename): # File Print String tokenString = Fore.YELLOW + '[' + str(translatedData[1]) + \ ' Tokens/${:,.4f}'.format(translatedData[1] * .001 * APICOST) + ']' timeString = Fore.BLUE + '[' + str(round(translationTime, 1)) + 's]' if translatedData[2] == None: # Success return filename + ': ' + tokenString + timeString + Fore.GREEN + u' \u2713 ' + Fore.RESET else: # Fail try: raise translatedData[2] except Exception as e: errorString = str(e) + Fore.RED return filename + ': ' + tokenString + timeString + Fore.RED + u' \u2717 ' +\ errorString + Fore.RESET def parseText(data, filename): totalTokens = 0 totalLines = 0 global LOCK # Get total for progress bar linesList = data.readlines() totalLines = len(linesList) with tqdm(bar_format=BAR_FORMAT, position=POSITION, total=totalLines, leave=LEAVE) as pbar: pbar.desc=filename pbar.total=totalLines try: response = translateText(linesList, pbar) except Exception as e: traceback.print_exc() return [linesList, 0, e] return [response[0], response[1], None] def translateText(data, pbar): textHistory = [] maxHistory = MAXHISTORY tokens = 0 speaker = '' speakerFlag = False currentGroup = [] syncIndex = 0 ### Translation for i in range(len(data)): if syncIndex > i: i = syncIndex # Finish if at end if i+1 > len(data): return [data, tokens] # Remove newlines jaString = data[i] jaString = jaString.replace('\n', '') # Reset Speaker if '00000000' == jaString: i += 1 speaker = '' jaString = data[i] # Grab and Translate Speaker elif '00003000' == jaString or '00002000' == jaString: i += 1 jaString = data[i].replace('\n', '') # Known Speakers namesList = [ "John", "Bob", "Tom", "女教師" ] if jaString in namesList: jaString = jaString.replace('女教師', 'Female Teacher') # Translate Speaker response = translateGPT(jaString, 'Reply with only the english translation of the NPC name', True) tokens += response[1] speaker = response[0].strip('.') data[i] = speaker + '\n' # Set index to line i += 1 else: continue # Translate finalJAString = data[i] if speaker != '': response = translateGPT(f'{speaker}: {finalJAString}', 'Previous Text for Context: ' + ' '.join(textHistory), True) else: response = translateGPT(finalJAString, 'Previous Text for Context: ' + ' '.join(textHistory), True) tokens += response[1] translatedText = response[0] # Remove added speaker and quotes translatedText = re.sub(r'^.+?:\s', '', translatedText) # TextHistory is what we use to give GPT Context, so thats appended here. if speaker != '': textHistory.append(speaker + ': ' + translatedText) elif speakerFlag == False: textHistory.append('\"' + translatedText + '\"') # Keep textHistory list at length maxHistory if len(textHistory) > maxHistory: textHistory.pop(0) currentGroup = [] # Textwrap translatedText = textwrap.fill(translatedText, width=40) translatedText = translatedText.replace('\n', '\\n') # Set Data data[i] = translatedText + '\n' syncIndex = i + 1 pbar.update() return [data, tokens] def subVars(jaString): jaString = jaString.replace('\u3000', ' ') # Icons count = 0 iconList = re.findall(r'[\\]+[iIkKwW]+\[[0-9]+\]', 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, '[N_' + 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 if '笑えるよね.' in jaString: print('t') formatList = re.findall(r'[\\]+CL', 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 = [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.replace(' ', '') translatedText = translatedText.replace(match, text) # Icons count = 0 if len(allList[0]) != 0: for var in allList[0]: translatedText = translatedText.replace('[Ascii_' + str(count) + ']', var) count += 1 # Colors count = 0 if len(allList[1]) != 0: for var in allList[1]: translatedText = translatedText.replace('[Color_' + str(count) + ']', var) count += 1 # Names count = 0 if len(allList[2]) != 0: for var in allList[2]: translatedText = translatedText.replace('[N_' + str(count) + ']', var) count += 1 # Vars count = 0 if len(allList[3]) != 0: for var in allList[3]: translatedText = translatedText.replace('[Var_' + str(count) + ']', var) count += 1 # Formatting count = 0 if len(allList[4]) != 0: for var in allList[4]: translatedText = translatedText.replace('[FCode_' + str(count) + ']', var) count += 1 # Remove Color Variables Spaces # if '\\c' in translatedText: # translatedText = re.sub(r'\s*(\\+c\[[1-9]+\])\s*', r' \1', translatedText) # translatedText = re.sub(r'\s*(\\+c\[0+\])', r'\1', translatedText) return translatedText @retry(exceptions=Exception, tries=5, delay=5) def translateGPT(t, history, fullPromptFlag): # If ESTIMATE is True just count this as an execution and return. if ESTIMATE: enc = tiktoken.encoding_for_model("gpt-3.5-turbo") tokens = len(enc.encode(t)) * 2 + len(enc.encode(history)) + len(enc.encode(PROMPT)) return (t, tokens) # Sub Vars varResponse = subVars(t) subbedT = varResponse[0] # If there isn't any Japanese in the text just skip if not re.search(r'[一-龠]+|[ぁ-ゔ]+|[ァ-ヴ]+|[\uFF00-\uFFEF]', subbedT): return(t, 0) """Translate text using GPT""" context = '```\ Game Characters:\ Character: 如月亜里愛 == Kisaragi Aria - Nickname: Aria - Gender: Female\ Character: 愛洲美彌子 == Aisu Miyako - Gender: Female\ Character: 喜遊名心 == Cocoa Kiyuna - Gender: Female\ Character: 柵瀬愛色 == Ai Sakurai - Gender: Female\ Character: 陰平小鞠 == Komari Kagehira - Gender: Female\ Character: 訓覇一縷 == Ichiru Kurube - Gender: Female\ Character: 緋皇月 == Luna Hisube - Gender: Female\ Character: 刑事 == Detective - Gender: Male\ ```' if fullPromptFlag: system = PROMPT user = 'Line to Translate = ' + subbedT else: system = 'Output ONLY the english translation in the following format: `Translation: `' user = 'Line to Translate = ' + subbedT response = openai.ChatCompletion.create( temperature=0, frequency_penalty=0.2, presence_penalty=0.2, model="gpt-3.5-turbo", messages=[ {"role": "system", "content": system}, {"role": "user", "content": context}, {"role": "user", "content": history}, {"role": "user", "content": user} ], request_timeout=30, ) # Save Translated Text translatedText = response.choices[0].message.content tokens = response.usage.total_tokens # Resub Vars translatedText = resubVars(translatedText, varResponse[1]) # Remove Placeholder Text translatedText = translatedText.replace('English Translation: ', '') translatedText = translatedText.replace('Translation: ', '') translatedText = translatedText.replace('Line to Translate = ', '') translatedText = translatedText.replace('Translation = ', '') translatedText = translatedText.replace('Translate = ', '') translatedText = translatedText.replace('English Translation:', '') translatedText = translatedText.replace('Translation:', '') translatedText = translatedText.replace('Line to Translate =', '') translatedText = translatedText.replace('Translation =', '') translatedText = translatedText.replace('Translate =', '') translatedText = re.sub(r'\n\nPast Translated Text:.*', '', translatedText, 0, re.DOTALL) translatedText = re.sub(r'Note:.*', '', translatedText) translatedText = translatedText.replace('っ', '') # Return Translation if len(translatedText) > 15 * len(t) or "I'm sorry, but I'm unable to assist with that translation" in translatedText: raise Exception else: return [translatedText, tokens]