383 lines
12 KiB
Python
383 lines
12 KiB
Python
import json
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import os
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from pathlib import Path
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import re
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import sys
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import textwrap
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import threading
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import time
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import traceback
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import tiktoken
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from colorama import Fore
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from dotenv import load_dotenv
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import openai
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from retry import retry
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from tqdm import tqdm
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#Globals
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load_dotenv()
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openai.organization = os.getenv('org')
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openai.api_key = os.getenv('key')
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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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INPUTAPICOST = .002 # Depends on the model https://openai.com/pricing
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OUTPUTAPICOST = .002
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PROMPT = Path('prompt.txt').read_text(encoding='utf-8')
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THREADS = int(os.getenv('threads')) # Controls how many threads are working on a single file (May have to drop this)
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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 = 50
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MAXHISTORY = 10
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ESTIMATE = ''
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totalTokens = [0, 0]
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NAMESLIST = []
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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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BRFLAG = False # If the game uses <br> instead
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FIXTEXTWRAP = True
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IGNORETLTEXT = False
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def handleLune(filename, estimate):
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global ESTIMATE, totalTokens
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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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return getResultString(['', totalTokens, None], end - start, 'TOTAL')
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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)
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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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totalTokens = [0, 0]
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totalLines = 0
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totalLines = len(data)
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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(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(data, pbar):
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textHistory = []
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maxHistory = MAXHISTORY
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tokens = [0, 0]
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speaker = 'None'
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for item in data:
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# Speaker
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if 'name' in item:
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if item['name'] not in [None, '-']:
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response = translateGPT(item['name'], 'Reply with only the '+ LANGUAGE +' translation of the NPC name', False)
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speaker = response[0]
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tokens[0] += response[1][0]
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tokens[1] += response[1][1]
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item['name'] = speaker
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else:
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speaker = 'None'
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# Text
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if 'message' in item:
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if item['message'] != None:
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jaString = item['message']
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# Remove any textwrap
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if FIXTEXTWRAP == True:
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jaString = jaString.replace('\n', ' ')
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# Translate
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if jaString != '':
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response = translateGPT(f'{speaker} | {jaString}', textHistory, True)
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tokens[0] += response[1][0]
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tokens[1] += response[1][1]
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translatedText = response[0]
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textHistory.append('\"' + translatedText + '\"')
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else:
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translatedText = jaString
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textHistory.append('\"' + translatedText + '\"')
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# Remove added speaker
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translatedText = re.sub(r'^.+?\s\|\s?', '', translatedText)
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# Textwrap
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translatedText = textwrap.fill(translatedText, width=WIDTH)
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# Set Data
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item['message'] = translatedText
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# Keep textHistory list at length maxHistory
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if len(textHistory) > maxHistory:
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textHistory.pop(0)
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currentGroup = []
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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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# Icons
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count = 0
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iconList = re.findall(r'[\\]+[iIkKwW]+\[[0-9]+\]', 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, '[N_' + 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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if '笑えるよね.' in jaString:
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print('t')
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formatList = re.findall(r'[\\]+CL', 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 = [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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# Icons
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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('[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[1]) != 0:
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for var in allList[1]:
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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[2]) != 0:
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for var in allList[2]:
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translatedText = translatedText.replace('[N_' + 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[3]) != 0:
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for var in allList[3]:
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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[4]) != 0:
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for var in allList[4]:
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translatedText = translatedText.replace('[FCode_' + str(count) + ']', var)
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count += 1
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# Remove Color Variables Spaces
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# if '\\c' in translatedText:
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# translatedText = re.sub(r'\s*(\\+c\[[1-9]+\])\s*', r' \1', translatedText)
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# translatedText = re.sub(r'\s*(\\+c\[0+\])', r'\1', translatedText)
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return translatedText
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@retry(exceptions=Exception, tries=5, delay=5)
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def translateGPT(t, history, fullPromptFlag):
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# If ESTIMATE is True just count this as an execution and return.
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if ESTIMATE:
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enc = tiktoken.encoding_for_model(MODEL)
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historyRaw = ''
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if isinstance(history, list):
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for line in history:
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historyRaw += line
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else:
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historyRaw = history
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inputTotalTokens = len(enc.encode(historyRaw)) + len(enc.encode(PROMPT))
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outputTotalTokens = len(enc.encode(t)) * 2 # Estimating 2x the size of the original text
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totalTokens = [inputTotalTokens, outputTotalTokens]
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return (t, totalTokens)
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# Sub Vars
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varResponse = subVars(t)
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subbedT = varResponse[0]
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# If there isn't any Japanese in the text just skip
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if not re.search(r'[一-龠]+|[ぁ-ゔ]+|[ァ-ヴ]+|[\uFF00-\uFFEF]', subbedT):
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return(t, [0,0])
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# Characters
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context = '```\
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Game Characters:\
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Character: ソル == Sol - Gender: Female\
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Character: ェニ先生 == Eni-sensei - Gender: Female\
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Character: 神泉 理央 == Kamiizumi Rio - Gender: Female\
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Character: 吉祥寺 アリサ == Kisshouji Arisa - Gender: Female\
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```'
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# Prompt
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if fullPromptFlag:
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system = PROMPT
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user = 'Line to Translate = ' + subbedT
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else:
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system = 'Output ONLY the '+ LANGUAGE +' translation in the following format: `Translation: <'+ LANGUAGE.upper() +'_TRANSLATION>`'
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user = 'Line to Translate = ' + subbedT
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# Create Message List
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msg = []
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msg.append({"role": "system", "content": system})
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msg.append({"role": "user", "content": context})
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if isinstance(history, list):
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for line in history:
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msg.append({"role": "user", "content": line})
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else:
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msg.append({"role": "user", "content": history})
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msg.append({"role": "user", "content": user})
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response = openai.ChatCompletion.create(
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temperature=0.1,
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frequency_penalty=0.2,
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presence_penalty=0.2,
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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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# Save Translated Text
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translatedText = response.choices[0].message.content
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totalTokens = [response.usage.prompt_tokens, response.usage.completion_tokens]
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# Resub Vars
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translatedText = resubVars(translatedText, varResponse[1])
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# Remove Placeholder Text
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translatedText = translatedText.replace(LANGUAGE +' Translation: ', '')
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translatedText = translatedText.replace('Translation: ', '')
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translatedText = translatedText.replace('Line to Translate = ', '')
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translatedText = translatedText.replace('Translation = ', '')
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translatedText = translatedText.replace('Translate = ', '')
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translatedText = translatedText.replace(LANGUAGE +' Translation:', '')
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translatedText = translatedText.replace('Translation:', '')
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translatedText = translatedText.replace('Line to Translate =', '')
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translatedText = translatedText.replace('Translation =', '')
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translatedText = translatedText.replace('Translate =', '')
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translatedText = re.sub(r'Note:.*', '', translatedText)
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translatedText = translatedText.replace('っ', '')
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# Return Translation
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if len(translatedText) > 15 * len(t) or "I'm sorry, but I'm unable to assist with that translation" in translatedText:
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raise Exception
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else:
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return [translatedText, totalTokens]
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