294 lines
No EOL
10 KiB
Python
294 lines
No EOL
10 KiB
Python
from concurrent.futures import ThreadPoolExecutor, as_completed
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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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APICOST = .002 # Depends on the model https://openai.com/pricing
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PROMPT = Path('prompt.txt').read_text(encoding='utf-8')
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THREADS = 20
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LOCK = threading.Lock()
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WIDTH = 75
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LISTWIDTH = 75
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MAXHISTORY = 10
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ESTIMATE = ''
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TOTALCOST = 0
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TOKENS = 0
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TOTALTOKENS = 0
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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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# Flags
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CODE401 = True
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CODE102 = True
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CODE122 = False
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CODE101 = False
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CODE355655 = False
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CODE357 = False
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CODE356 = False
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CODE320 = False
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CODE111 = False
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def handleTextfile(filename, estimate):
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global ESTIMATE, TOKENS, TOTALTOKENS, TOTALCOST
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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(['', TOKENS, None], end - start, filename))
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with LOCK:
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TOTALCOST += TOKENS * .001 * APICOST
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TOTALTOKENS += TOKENS
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TOKENS = 0
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return getResultString(['', TOTALTOKENS, None], end - start, 'TOTAL')
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else:
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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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outFile.writelines(translatedData[0])
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tqdm.write(getResultString(translatedData, end - start, filename))
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with LOCK:
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TOTALCOST += translatedData[1] * .001 * APICOST
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TOTALTOKENS += translatedData[1]
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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') as f:
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translatedData = parseText(f, filename)
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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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tokenString = Fore.YELLOW + '[' + str(translatedData[1]) + \
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' Tokens/${:,.4f}'.format(translatedData[1] * .001 * APICOST) + ']'
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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 + ': ' + tokenString + 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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errorString = str(e) + Fore.RED
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return filename + ': ' + tokenString + timeString + Fore.RED + u' \u2717 ' +\
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errorString + Fore.RESET
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def parseText(data, filename):
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totalTokens = 0
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totalLines = 0
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global LOCK
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# Get total for progress bar
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linesList = data.readlines()
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totalLines = len(linesList)
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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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response = translateText(linesList, pbar)
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except Exception as e:
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traceback.print_exc()
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return [linesList, 0, e]
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return [response[0], response[1], None]
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def translateText(data, pbar):
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textHistory = []
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maxHistory = MAXHISTORY
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tokens = 0
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speaker = ''
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speakerFlag = False
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currentGroup = []
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syncIndex = 0
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for i in range(len(data)):
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if i != syncIndex:
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continue
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match = re.findall(r'm\[[0-9]+\] = \"(.*)\"', data[i])
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if len(match) > 0:
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jaString = match[0]
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### Translate
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# Remove any textwrap
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jaString = re.sub(r'\\n', ' ', jaString)
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# Grab Speaker
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speakerMatch = re.findall(r's\[[0-9]+\] = \"(.+?)[／\"]', data[i-1])
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if len(speakerMatch) > 0:
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# If there isn't any Japanese in the text just skip
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if re.search(r'[一-龠]+|[ぁ-ゔ]+|[ァ-ヴー]+', jaString) and '_' not in speakerMatch[0]:
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speaker = ''
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else:
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speaker = ''
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else:
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speaker = ''
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# Grab rest of the messages
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currentGroup.append(jaString)
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start = i
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data[i] = re.sub(r'(m\[[0-9]+\]) = \"(.+)\"', rf'\1 = ""', data[i])
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while (len(data) > i+1 and re.search(r'm\[[0-9]+\] = \"(.*)\"', data[i+1]) != None):
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i+=1
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match = re.findall(r'm\[[0-9]+\] = \"(.*)\"', data[i])
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currentGroup.append(match[0])
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data[i] = re.sub(r'(m\[[0-9]+\]) = \"(.+)\"', rf'\1 = ""', data[i])
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finalJAString = ' '.join(currentGroup)
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# Translate
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if speaker != '':
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response = translateGPT(f'{speaker}: {finalJAString}', 'Previous Text for Context: ' + ' '.join(textHistory), True)
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else:
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response = translateGPT(finalJAString, 'Previous Text for Context: ' + ' '.join(textHistory), True)
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tokens += response[1]
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translatedText = response[0]
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# Remove added speaker and quotes
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translatedText = re.sub(r'^.+?:\s', '', translatedText)
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# TextHistory is what we use to give GPT Context, so thats appended here.
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# rawTranslatedText = re.sub(r'[\\<>]+[a-zA-Z]+\[[a-zA-Z0-9]+\]', '', translatedText)
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if speaker != '':
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textHistory.append(speaker + ': ' + translatedText)
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elif speakerFlag == False:
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textHistory.append('\"' + 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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# Textwrap
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translatedText = translatedText.replace('\"', '\\"')
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translatedText = textwrap.fill(translatedText, width=WIDTH)
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# Write
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textList = translatedText.split("\n")
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for t in textList:
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data[start] = re.sub(r'(m\[[0-9]+\]) = \"(.*)\"', rf'\1 = "{t}"', data[start])
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start+=1
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syncIndex = i + 1
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pbar.update()
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return [data, tokens]
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def subVars(jaString):
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varRegex = r'\\+[a-zA-Z]+\[[0-9a-zA-Z\\\[\]]+\]+|[\\]+[#|]+|\\+[\\\[\]\.<>a-zA-Z0-9]+'
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count = 0
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varList = re.findall(varRegex, jaString)
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if len(varList) != 0:
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for var in varList:
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jaString = jaString.replace(var, '<x' + str(count) + '>')
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count += 1
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return [jaString, varList]
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def resubVars(translatedText, varList):
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count = 0
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if len(varList) != 0:
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for var in varList:
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translatedText = translatedText.replace('<x' + 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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with LOCK:
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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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global TOKENS
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enc = tiktoken.encoding_for_model("gpt-3.5-turbo-0613")
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TOKENS += len(enc.encode(t)) * 2 + len(enc.encode(history)) + len(enc.encode(PROMPT))
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return (t, 0)
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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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return (t,0)
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if not re.search(r'[一-龠]+|[ぁ-ゔ]+|[ァ-ヴー]+', subbedT):
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return(t, 0)
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"""Translate text using GPT"""
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context = 'Eroge Names Context: 夏樹 明人 == Natsuki Akito | Male, 朝露 砂夜子 == Asatsuyu Sayoko | Female, 神野 藍 == Jinno Ai | Female, 神野 菫 | Jinno Sumire | Female, 夏樹 海夕里 == Natsuki Miyuri | Female, 水森 陽太 == Mizumori Youta | Male, 夏樹 和人 == Natsuki Kazuto | Male, 野崎 博也 == Nozaki Hiroya | Male, 大菊 ジュン == Oogiku Jun | Male, 酒井 絹代 == Sakai Kinuyo | Female, 酒井 豊 == Sakai Yutaka | Male, 竜生 春義 == Tatsuki Haruyoshi | Male, 竜生 潤 == Tatsuki Jun | Male, 吉沢 英玄 == Yoshizawa Eigen | Male, 吉沢 武雄 == Yoshizawa Takeo | Male'
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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 = 'You are an expert translator who translates everything to English. Reply with only the English Translation of the text.'
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user = 'Line to Translate: ' + subbedT
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response = openai.ChatCompletion.create(
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temperature=0,
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frequency_penalty=1,
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model="gpt-3.5-turbo",
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messages=[
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{"role": "system", "content": system},
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{"role": "user", "content": context},
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{"role": "user", "content": history},
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{"role": "user", "content": user}
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],
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request_timeout=30,
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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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tokens = response.usage.total_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('English 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('English Translation:', '')
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translatedText = translatedText.replace('Translation:', '')
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translatedText = translatedText.replace('Line to Translate:', '')
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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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return [t, response.usage.total_tokens]
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else:
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return [translatedText, tokens] |