317 lines
No EOL
11 KiB
Python
317 lines
No EOL
11 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 = 10 # For GPT4 rate limit will be hit if you have more than 1 thread.
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LOCK = threading.Lock()
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WIDTH = 60
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LISTWIDTH = 60
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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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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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# Flags
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NAMES = True # Output a list of all the character names found
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BRFLAG = False # If the game uses <br> instead
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FIXTEXTWRAP = False
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def handleTyrano(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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if NAMES == True:
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tqdm.write(str(NAMESLIST))
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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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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, outFile)
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# Print Result
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outFile.writelines(translatedData[0])
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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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TOTALCOST += translatedData[1] * .001 * APICOST
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TOTALTOKENS += translatedData[1]
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except Exception as e:
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traceback.print_exc()
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return 'Fail'
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return getResultString(['', TOTALTOKENS, None], end - start, 'TOTAL')
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def openFiles(filename, outFile):
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with open('files/' + filename, 'r', encoding='utf-8') as readFile:
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translatedData = parseTyrano(readFile, outFile, filename)
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# Delete lines marked for deletion
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finalData = []
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for line in translatedData[0]:
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if line != '\\d\n':
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finalData.append(line)
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translatedData[0] = finalData
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return translatedData
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def parseTyrano(readFile, outFile, 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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data = readFile.readlines()
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totalLines = len(data)
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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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totalTokens += translateTyrano(data, outFile, pbar)
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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 translateTyrano(data, outFile, pbar):
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textHistory = []
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maxHistory = MAXHISTORY
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tokens = 0
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currentGroup = []
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syncIndex = 0
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global LOCK, ESTIMATE
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for i in range(len(data)):
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if syncIndex > i:
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i = syncIndex
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# Speaker
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if '#' in data[i]:
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matchList = re.findall(r'#(.+)', data[i])
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if len(matchList) != 0:
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response = translateGPT(matchList[0], 'Reply with only the english translation of the NPC name', True)
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speaker = response[0]
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tokens += response[1]
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data[i] = '#' + speaker + '\n'
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else:
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speaker = ''
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# Lines
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elif '[p]' in data[i]:
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matchList = re.findall(r'(.+?)\[p\]', data[i])
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if len(matchList) > 0:
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matchList[0] = matchList[0].replace('「', '')
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matchList[0] = matchList[0].replace('」', '')
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currentGroup.append(matchList[0])
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if len(data) > i+1:
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while '[p]' in data[i+1]:
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data[i] = '\d\n'
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i += 1
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matchList = re.findall(r'(.+?)\[p\]', data[i])
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if len(matchList) > 0:
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matchList[0] = matchList[0].replace('「', '')
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matchList[0] = matchList[0].replace('」', '')
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currentGroup.append(matchList[0])
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# Join up 401 groups for better translation.
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if len(currentGroup) > 0:
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finalJAString = ''.join(currentGroup)
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oldjaString = finalJAString
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#Check Speaker
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if speaker == '':
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response = translateGPT(finalJAString, 'Previous Dialogue: ' + '\n\n'.join(textHistory), True)
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tokens += response[1]
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translatedText = response[0]
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textHistory.append('\"' + translatedText + '\"')
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else:
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response = translateGPT(speaker + ': ' + finalJAString, 'Previous Dialogue: ' + '\n\n'.join(textHistory), True)
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tokens += response[1]
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translatedText = response[0]
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textHistory.append('\"' + translatedText + '\"')
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# Remove added speaker
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translatedText = translatedText.replace(speaker + ': ', '')
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# Set Data
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translatedText = translatedText.replace('\"', '')
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# Format Text
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matchList = re.findall(r'(.+?[\.\?\!]+)', translatedText)
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translatedText = re.sub(r'(.+?[\.\?\!]+)', '', translatedText)
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if len(matchList) > 0:
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del data[i]
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for line in matchList:
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data.insert(i, line.strip() + '[p]\n')
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i+=1
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else:
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print ('SUS')
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if translatedText != '':
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data[i] = translatedText.strip() + '[p]\n'
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currentGroup = []
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pbar.update(1)
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if len(data) > i+1:
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syncIndex = i+1
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else:
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break
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return tokens
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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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traceback.print_exc()
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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 subVars(jaString):
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varRegex = r'\\+[a-zA-Z]+\[[0-9a-zA-Z\\\[\]]+\]+|[\\]+[#a-zA-Z]+|[\\.<>]+'
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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, '[v' + 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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# Fix Spacing and ChatGPT Nonsense
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matchList = re.findall(r'@\s?[0-9]+?', translatedText)
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if len(matchList) > 0:
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for match in matchList:
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text = match.replace(' ', '')
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translatedText = translatedText.replace(match, text)
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if len(varList) != 0:
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for var in varList:
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translatedText = translatedText.replace('@' + 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")
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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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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: 桐嶋 香織 == Kaori Kirishima | Female, 肉山 猛 == Takeshi Nikuyama'
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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=0.2,
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presence_penalty=0.2,
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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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translatedText = re.sub(r'\n\nPast Translated Text:.*', '', translatedText, 0, re.DOTALL)
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translatedText = re.sub(r'Note:.*', '', translatedText)
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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] |