579 lines
No EOL
20 KiB
Python
579 lines
No EOL
20 KiB
Python
# Libraries
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import json, os, re, textwrap, threading, time, traceback, tiktoken, openai, csv
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from concurrent.futures import ThreadPoolExecutor, as_completed
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from pathlib import Path
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from colorama import Fore
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from dotenv import load_dotenv
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from retry import retry
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from tqdm import tqdm
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# Open AI
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load_dotenv()
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if os.getenv('api').replace(' ', '') != '':
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openai.api_base = os.getenv('api')
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openai.organization = os.getenv('org')
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openai.api_key = os.getenv('key')
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#Globals
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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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PROMPT = Path('prompt.txt').read_text(encoding='utf-8')
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THREADS = int(os.getenv('threads'))
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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 = int(os.getenv('noteWidth'))
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MAXHISTORY = 10
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ESTIMATE = ''
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TOKENS = [0, 0]
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NAMESLIST = []
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NAMES = False # 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 = True # Overwrites textwrap
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IGNORETLTEXT = True # Ignores all translated text.
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MISMATCH = [] # Lists files that thdata a mismatch error (Length of GPT list response is wrong)
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BRACKETNAMES = False
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# Pricing - Depends on the model https://openai.com/pricing
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# Batch Size - GPT 3.5 Struggles past 15 lines per request. GPT4 struggles past 50 lines per request
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# If you are getting a MISMATCH LENGTH error, lower the batch size.
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if 'gpt-3.5' in MODEL:
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INPUTAPICOST = .002
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OUTPUTAPICOST = .002
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BATCHSIZE = 10
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FREQUENCY_PENALTY = 0.2
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elif 'gpt-4' in MODEL:
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INPUTAPICOST = .01
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OUTPUTAPICOST = .03
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BATCHSIZE = 40
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FREQUENCY_PENALTY = 0.1
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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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def handleCSV(filename, estimate):
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global ESTIMATE, TOKENS
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ESTIMATE = estimate
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with open('translated/' + filename, 'w+t', newline='', encoding='utf-8') as writeFile:
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# Translate
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start = time.time()
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translatedData = openFiles(filename, writeFile)
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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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TOKENS[0] += translatedData[1][0]
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TOKENS[1] += translatedData[1][1]
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# Print Total
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totalString = getResultString(['', TOKENS, None], end - start, 'TOTAL')
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# Print any errors on maps
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if len(MISMATCH) > 0:
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return totalString + Fore.RED + f'\nMismatch Errors: {MISMATCH}' + Fore.RESET
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else:
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return totalString
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def openFiles(filename, writeFile):
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with open('files/' + filename, 'r', encoding='utf-8') as readFile, writeFile:
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translatedData = parseCSV(readFile, writeFile, 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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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] is 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 parseCSV(readFile, writeFile, filename):
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totalTokens = [0,0]
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totalLines = 0
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textHistory = []
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global LOCK
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format = ''
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while format == '':
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format = input('\n\nSelect the CSV Format:\n\n1. Translator++\n2. Translate All (Depreciated)\n')
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match format:
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case '1':
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format = '1'
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case '2':
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format = '2'
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# Get total for progress bar
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totalLines = len(readFile.readlines())
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readFile.seek(0)
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reader = csv.reader(readFile, delimiter=',',)
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writer = csv.writer(writeFile, delimiter=',', quotechar='\"')
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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 = translateCSV(reader, pbar, writer, textHistory, format)
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totalTokens[0] = response[0]
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totalTokens[1] = response[1]
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except Exception as e:
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traceback.print_exc()
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return [reader, totalTokens, None]
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def translateCSV(reader, pbar, writer, textHistory, format):
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translatedText = ''
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maxHistory = MAXHISTORY
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totalTokens = [0,0]
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global LOCK, ESTIMATE
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data = []
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batch = []
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i = 0
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try:
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# Grab All Rows
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for row in reader:
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data.append(row)
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# Batch
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while i < len(data):
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if len(batch) < BATCHSIZE:
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if 'Original Text' not in data[i]:
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batch.append(data[i])
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pbar.update(1)
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i += 1
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else:
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match format:
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# T++ Format: Japanese Text on column 1. English on Column 2
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case '1':
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# Put in Payload
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payload = []
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for row in batch:
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if row[1] == "":
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jaString = row[0]
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else:
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jaString = row[1]
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# Remove Textwrap
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jaString = jaString.replace('\n', ' ')
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payload.append(jaString)
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# Translate
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response = translateGPT(payload, textHistory, True)
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translatedTextList = response[0]
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totalTokens[0] = response[1][0]
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totalTokens[1] = response[1][1]
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# MISMATCH
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if len(translatedTextList) != len(payload):
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pbar.write(f'Mismatch Error: {i-len(batch)}-{i}')
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batch.clear()
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continue
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# Set Data
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j = i - BATCHSIZE
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for row in translatedTextList:
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row = row.replace('"', '\\"')
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row = row.replace(',', '\,')
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data[j][1] = row
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j += 1
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batch.clear()
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# Translate Everything
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case '2':
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for i in range(len(data)):
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# This will allow you to ignore certain columns
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if i not in [1]:
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continue
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jaString = data[i]
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matchList = re.findall(r':name\[(.+?),.+?\](.+?[」）\"。]+)', jaString)
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# Start Translation
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for match in matchList:
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speaker = match[0]
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text = match[1]
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# Translate Speaker
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response = translateGPT (speaker, 'Reply with the '+ LANGUAGE +' translation of the NPC name.', True)
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translatedSpeaker = response[0]
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totalTokens += response[1][0]
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totalTokens += response[1][1]
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# Translate Line
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jaText = re.sub(r'([\u3000-\uffef])\1{3,}', r'\1\1\1', text)
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response = translateGPT(translatedSpeaker + ': ' + jaText, 'Previous Translated Text: ' + '|'.join(textHistory), True)
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translatedText = response[0]
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totalTokens[0] += response[1][0]
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totalTokens[1] += response[1][1]
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# TextHistory is what we use to give GPT Context, so thats appended here.
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textHistory.append(translatedText)
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# Remove Speaker from translated text
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translatedText = re.sub(r'.+?: ', '', translatedText)
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# Set Data
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translatedSpeaker = translatedSpeaker.replace('\"', '')
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translatedText = translatedText.replace('\"', '')
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translatedText = translatedText.replace('「', '')
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translatedText = translatedText.replace('」', '')
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data[i] = data[i].replace('\n', ' ')
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# Textwrap
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translatedText = textwrap.fill(translatedText, width=WIDTH)
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translatedText = '「' + translatedText + '」'
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data[i] = re.sub(rf':name\[({re.escape(speaker)}),', f':name[{translatedSpeaker},', data[i])
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data[i] = data[i].replace(text, translatedText)
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# Keep History at fixed length.
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with LOCK:
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if len(textHistory) > maxHistory:
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textHistory.pop(0)
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with LOCK:
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if not ESTIMATE:
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writer.writerow(data)
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pbar.update(1)
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# Leftovers
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if format == '1':
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# Put in Payload
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payload = []
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for row in batch:
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if row[1] == "":
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jaString = row[0]
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else:
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jaString = row[1]
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# Remove Textwrap
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jaString = jaString.replace('\n', ' ')
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payload.append(jaString)
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# Translate
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response = translateGPT(payload, textHistory, True)
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translatedTextList = response[0]
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totalTokens[0] = response[1][0]
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totalTokens[1] = response[1][1]
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# MISMATCH
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if len(translatedTextList) != len(payload):
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pbar.write(f'Mismatch Error: {i-BATCHSIZE}-{i}')
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batch.clear()
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# Set Data
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j = i - len(batch)
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for row in translatedTextList:
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row = row.replace('"', '\\"')
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row = row.replace(',', '\,')
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data[j][1] = row
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j += 1
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batch.clear()
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# Write all Data
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with LOCK:
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if not ESTIMATE:
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for row in data:
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writer.writerow(row)
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except Exception as e:
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traceback.print_exc()
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return totalTokens
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def subVars(jaString):
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jaString = jaString.replace('\u3000', ' ')
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# Nested
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count = 0
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nestedList = re.findall(r'[\\]+[\w]+\[[\\]+[\w]+\[[0-9]+\]\]', jaString)
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nestedList = set(nestedList)
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if len(nestedList) != 0:
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for icon in nestedList:
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jaString = jaString.replace(icon, '{Nested_' + str(count) + '}')
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count += 1
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# Icons
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count = 0
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iconList = re.findall(r'[\\]+[iIkKwWaA]+\[[0-9]+\]', 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, '{Noun_' + 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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formatList = re.findall(r'[\\]+[\w]+\[.+?\]', 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 = [nestedList, 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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# Nested
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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('{Nested_' + str(count) + '}', var)
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count += 1
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# Icons
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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('{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[2]) != 0:
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for var in allList[2]:
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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[3]) != 0:
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for var in allList[3]:
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translatedText = translatedText.replace('{Noun_' + 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[4]) != 0:
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for var in allList[4]:
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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[5]) != 0:
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for var in allList[5]:
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translatedText = translatedText.replace('{FCode_' + str(count) + '}', var)
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count += 1
|
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|
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return translatedText
|
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|
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def batchList(input_list, batch_size):
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if not isinstance(batch_size, int) or batch_size <= 0:
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raise ValueError("batch_size must be a positive integer")
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return [input_list[i:i + batch_size] for i in range(0, len(input_list), batch_size)]
|
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def createContext(fullPromptFlag, subbedT):
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characters = 'Game Characters:\n\
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ミオリ (Miori) - Female\n\
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'
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system = PROMPT if fullPromptFlag else \
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f"\
|
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You are an expert Eroge Game translator who translates Japanese text to English.\n\
|
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You are going to be translating text from a videogame.\n\
|
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I will give you lines of text, and you must translate each line to the best of your ability.\n\
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- Translate 'マンコ' as 'pussy'\n\
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- Translate 'おまんこ' as 'pussy'\n\
|
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- Translate 'お尻' as 'butt'\n\
|
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- Translate '尻' as 'ass'\n\
|
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- Translate 'お股' as 'crotch'\n\
|
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- Translate '秘部' as 'genitals'\n\
|
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- Translate 'チンポ' as 'dick'\n\
|
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- Translate 'チンコ' as 'cock'\n\
|
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- Translate 'ショーツ' as 'panties\n\
|
||
- Translate 'おねショタ' as 'Onee-shota'\n\
|
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- Translate 'よかった' as 'thank goodness'\n\
|
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Output ONLY the {LANGUAGE} translation in the following format: `Translation: <{LANGUAGE.upper()}_TRANSLATION>`\
|
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"
|
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user = f'{subbedT}'
|
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return characters, system, user
|
||
|
||
def translateText(characters, system, user, history):
|
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# Prompt
|
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msg = [{"role": "system", "content": system + characters}]
|
||
|
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# Characters
|
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msg.append({"role": "system", "content": characters})
|
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|
||
# History
|
||
if isinstance(history, list):
|
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msg.extend([{"role": "assistant", "content": h} for h in history])
|
||
else:
|
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msg.append({"role": "assistant", "content": history})
|
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|
||
# Content to TL
|
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msg.append({"role": "user", "content": f'{user}'})
|
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response = openai.chat.completions.create(
|
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temperature=0.1,
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frequency_penalty=0.1,
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presence_penalty=0.1,
|
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model=MODEL,
|
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messages=msg,
|
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)
|
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return response
|
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|
||
def cleanTranslatedText(translatedText, varResponse):
|
||
placeholders = {
|
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f'{LANGUAGE} Translation: ': '',
|
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'Translation: ': '',
|
||
'っ': '',
|
||
'〜': '~',
|
||
'ー': '-',
|
||
'ッ': '',
|
||
'。': '.',
|
||
'Placeholder Text': ''
|
||
# Add more replacements as needed
|
||
}
|
||
for target, replacement in placeholders.items():
|
||
translatedText = translatedText.replace(target, replacement)
|
||
|
||
translatedText = resubVars(translatedText, varResponse[1])
|
||
return [line for line in translatedText.replace('\\n', '\n').split('\n') if line]
|
||
|
||
def extractTranslation(translatedTextList, is_list):
|
||
pattern = r'`?<Line(\d+)>([\\]*.*?[\\]*?)<\/?Line\d+>`?'
|
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# If it's a batch (i.e., list), extract with tags; otherwise, return the single item.
|
||
if is_list:
|
||
return [re.findall(pattern, line)[0][1] for line in translatedTextList if re.search(pattern, line)]
|
||
else:
|
||
matchList = re.findall(pattern, translatedTextList)
|
||
return matchList[0][1] if matchList else translatedTextList
|
||
|
||
def countTokens(characters, system, user, history):
|
||
inputTotalTokens = 0
|
||
outputTotalTokens = 0
|
||
enc = tiktoken.encoding_for_model(MODEL)
|
||
|
||
# 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))/1.5)
|
||
|
||
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):
|
||
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 = '\n'.join([f'`<Line{i}>{item}</Line{i}>`' for i, item in enumerate(tItem)])
|
||
payload = payload.replace('``', '`Placeholder Text`')
|
||
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):
|
||
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)
|
||
translatedText = response.choices[0].message.content
|
||
totalTokens[0] += response.usage.prompt_tokens
|
||
totalTokens[1] += response.usage.completion_tokens
|
||
|
||
# Formatting
|
||
translatedTextList = cleanTranslatedText(translatedText, varResponse)
|
||
if isinstance(tItem, list):
|
||
extractedTranslations = extractTranslation(translatedTextList, True)
|
||
tList[index] = extractedTranslations
|
||
if len(tItem) != len(translatedTextList):
|
||
mismatch = True # Just here so breakpoint can be set
|
||
history = extractedTranslations[-10:] # Update history if we have a list
|
||
else:
|
||
# Ensure we're passing a single string to extractTranslation
|
||
extractedTranslations = extractTranslation('\n'.join(translatedTextList), False)
|
||
tList[index] = extractedTranslations
|
||
|
||
finalList = combineList(tList, text)
|
||
return [finalList, totalTokens] |