748 lines
27 KiB
Python
748 lines
27 KiB
Python
# Libraries
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import json
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import os
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import re
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import util.dazedwrap as dazedwrap
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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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import openai
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import csv
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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.base_url = 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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VOCAB = Path("vocab.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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# Regex - Need to change this if you want to translate from/to other languages. Default is Japanese Regex
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LANGREGEX = r"[一-龠ぁ-ゔァ-ヴーａ-ｚＡ-Ｚ０-９\uFF61-\uFF9F]+"
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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 = 3.00
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OUTPUTAPICOST = 5.00
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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 = 2.0
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OUTPUTAPICOST = 8.00
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BATCHSIZE = 30
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FREQUENCY_PENALTY = 0.05
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elif "deepseek" in MODEL:
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INPUTAPICOST = 0.27
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OUTPUTAPICOST = 1.10
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BATCHSIZE = 30
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FREQUENCY_PENALTY = 0.05
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else:
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INPUTAPICOST = float(os.getenv("input_cost"))
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OUTPUTAPICOST = float(os.getenv("output_cost"))
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BATCHSIZE = int(os.getenv("batchsize"))
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FREQUENCY_PENALTY = float(os.getenv("frequency_penalty"))
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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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PBAR = None
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ENCODING = "utf8"
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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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if not ESTIMATE:
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with open("translated/" + filename, "w+t", newline="", encoding=ENCODING, errors="xmlcharrefreplace") 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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else:
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# Translate
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start = time.time()
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translatedData = openFilesEstimate(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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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=ENCODING) as readFile, writeFile:
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translatedData = parseCSV(readFile, writeFile, filename)
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return translatedData
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def openFilesEstimate(filename):
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with open("files/" + filename, "r", encoding="utf8") as readFile:
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translatedData = parseCSV(readFile, "", 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 + "[Input: " + str(translatedData[1][0]) + "]"
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"[Output: "
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+ str(translatedData[1][1])
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+ "]" "[Cost: ${:,.4f}".format(((translatedData[1][0] / 1000000) * INPUTAPICOST) + ((translatedData[1][1] / 1000000) * OUTPUTAPICOST))
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+ "]"
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)
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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 + " \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 + " \u2717 " + 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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global LOCK
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# Read from tmp files
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if os.path.isfile("csv.tmp"):
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with open("csv.tmp") as tmpFile:
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format = tmpFile.readline()
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else:
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format = ""
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# Choices
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while format not in ["1", "2", "3", "4"]:
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format = input("\n\nSelect the CSV Format:\n\n1. Translator++\n2. Single\n3. Multiple\n4. Speaker&Text\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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case "3":
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format = "3"
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case "4":
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format = "4"
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# Write to file for later use
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with open("csv.tmp", "w", encoding="utf-8") as tmpFile:
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tmpFile.write(f"{format}")
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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="\t")
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if not ESTIMATE:
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writer = csv.writer(
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writeFile,
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delimiter="\t",
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)
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else:
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writer = ""
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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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# Grab All Rows
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data = []
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for row in reader:
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data.append(row)
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try:
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response = translateCSV(data, pbar, writer, filename, None, format)
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totalTokens[0] = response[0]
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totalTokens[1] = response[1]
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except Exception:
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traceback.print_exc()
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return [data, totalTokens, None]
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def translateCSV(data, pbar, writer, filename, translatedList, format):
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global LOCK, ESTIMATE, PBAR
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PBAR = pbar
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translatedText = ""
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totalTokens = [0, 0]
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i = 0
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stringList = []
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try:
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# Translate
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while i < len(data):
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match format:
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# T++ Format: Source Text on column 1. TL Target on Column 2
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case "1":
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# Get String
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if i != 0:
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if data[i][1] == "":
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jaString = data[i][0]
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else:
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jaString = data[i][1]
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# Remove Textwrap
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jaString = jaString.replace("\\n", " ")
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# Pass 1
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if not translatedList:
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stringList.append(jaString)
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# Pass 2
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else:
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# Grab and Pop
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translatedText = translatedList[0]
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translatedList.pop(0)
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# Add Wordwrap
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translatedText = dazedwrap.wrapText(translatedText, WIDTH)
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translatedText = translatedText.replace("\n", "\\n")
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# Set Data
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data[i][1] = translatedText
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# Iterate
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i += 1
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# Target Format
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case "2":
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# Set Values
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sourceColumn = 0
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targetColumn = 1
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# Check if Translated
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jaString = data[i][sourceColumn]
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# Remove Textwrap
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jaString = jaString.replace("\\n", " ")
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# Pass 1
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if not translatedList:
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stringList.append(jaString)
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# Pass 2
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else:
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# Grab and Pop
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translatedText = translatedList[0]
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translatedList.pop(0)
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# Add Wordwrap
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translatedText = dazedwrap.wrapText(translatedText, WIDTH)
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translatedText = translatedText.replace("\n", "\\n")
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# Set Data
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data[i][targetColumn] = translatedText
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# Iterate
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i += 1
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# In Place Format
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case "3":
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# Set columns to translate. Leave empty to translate all.
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targetColumns = [0]
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# False - Place translation in source column
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# True - Place translation in next column
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targetNextRow = False
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# Skip 1st Row
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skipFirstRow = True
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for j in range(len(data[i])):
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if skipFirstRow and i == 0:
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continue
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if j in targetColumns and data[i][j]:
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# Check if Translated
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jaString = data[i][j]
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# Remove Textwrap
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jaString = jaString.replace("\n", " ")
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# Pass 1
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if not translatedList:
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stringList.append(jaString)
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# Pass 2
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else:
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# Grab and Pop
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translatedText = translatedList[0]
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translatedList.pop(0)
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# Add Wordwrap
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translatedText = dazedwrap.wrapText(translatedText, WIDTH)
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# Set Data
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if targetNextRow:
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data[i][j + 1] = translatedText
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else:
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data[i][j] = translatedText
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# Iterate
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i += 1
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# Speaker & Text Format
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case "4":
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# Set columns to translate. Leave empty to translate all.
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speakerColumn = 2
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textColumn = 9
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speaker = ""
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if len(data[i]) > textColumn and data[i][textColumn]:
|
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# Speaker
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if data[i][speakerColumn]:
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speakerResponse = getSpeaker(data[i][speakerColumn])
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totalTokens[0] += speakerResponse[1][0]
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totalTokens[1] += speakerResponse[1][1]
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speaker = speakerResponse[0]
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data[i][speakerColumn] = speaker
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# Get Text
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jaString = data[i][textColumn]
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|
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# Remove Textwrap
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jaString = jaString.replace("\\n", " ")
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# Remove Furigana
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jaString = re.sub(r"＜(.*)＝.*＞", r"\1", jaString)
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|
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# Pass 1
|
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if not translatedList:
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# Append Speaker
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if speaker:
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jaString = f"[{speaker}]: {jaString}"
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# Append to List
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stringList.append(jaString)
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|
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# Pass 2
|
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else:
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# Grab and Pop
|
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translatedText = translatedList[0]
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translatedList.pop(0)
|
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|
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# Remove speaker
|
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if speaker:
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translatedText = re.sub(r"^\[?(.+?)\]?\s?[|:]\s?", "", translatedText)
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|
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# Add Wordwrap
|
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translatedText = dazedwrap.wrapText(translatedText, WIDTH)
|
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translatedText = translatedText.replace("\n", "\\n")
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|
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# Check for more than 3 newlines (Shoujo Ramune)
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newline_count = translatedText.count("\\n")
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if newline_count >= 3:
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parts = translatedText.split("\\n", 3)
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data[i][textColumn] = parts[0] + "\\n" + parts[1] + "\\n" + parts[2]
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new_row = data[i].copy()
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new_row[textColumn] = parts[3]
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new_row[0] = str(int(new_row[0]) + 1) # Add 1 to the line number
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data.insert(i + 1, new_row)
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i += 1
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else:
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data[i][textColumn] = translatedText
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# Iterate
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i += 1
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|
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# EOF
|
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if len(stringList) > 0:
|
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# Set Progress
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||
pbar.total = len(stringList)
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pbar.refresh()
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|
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# Translate
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response = translateGPT(stringList, "", True)
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totalTokens[0] += response[1][0]
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totalTokens[1] += response[1][1]
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translatedList = response[0]
|
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|
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# Set Strings
|
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if len(stringList) == len(translatedList):
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translateCSV(data, pbar, writer, filename, translatedList, format)
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|
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# Mismatch
|
||
else:
|
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with LOCK:
|
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if filename not in MISMATCH:
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MISMATCH.append(filename)
|
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|
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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)
|
||
|
||
except Exception:
|
||
traceback.print_exc()
|
||
|
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# Write all Data
|
||
with LOCK:
|
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if not ESTIMATE:
|
||
for row in data:
|
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writer.writerow(row)
|
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return totalTokens
|
||
|
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return totalTokens
|
||
|
||
|
||
# Save some money and enter the character before translation
|
||
def getSpeaker(speaker):
|
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match speaker:
|
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case "ファイン":
|
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return ["Fine", [0, 0]]
|
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case "":
|
||
return ["", [0, 0]]
|
||
case _:
|
||
# Find Speaker
|
||
for i in range(len(NAMESLIST)):
|
||
if speaker == NAMESLIST[i][0]:
|
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return [NAMESLIST[i][1], [0, 0]]
|
||
|
||
# If there isn't any Japanese in the text just skip
|
||
if not re.search(LANGREGEX, speaker):
|
||
return [speaker, [0, 0]]
|
||
|
||
# Translate and Store Speaker
|
||
response = translateGPT(
|
||
f"{speaker}",
|
||
"Reply with the " + LANGUAGE + " translation of the NPC name.",
|
||
True,
|
||
)
|
||
response[0] = response[0].title()
|
||
response[0] = response[0].replace("'S", "'s")
|
||
response[0] = response[0].replace("Speaker: ", "")
|
||
|
||
# Retry if name doesn't translate for some reason
|
||
if re.search(r"([a-zA-Z？?])", response[0]) == None:
|
||
response = translateGPT(
|
||
f"{speaker}",
|
||
"Reply with the " + LANGUAGE + " translation of the NPC name.",
|
||
False,
|
||
)
|
||
response[0] = response[0].title()
|
||
response[0] = response[0].replace("'S", "'s")
|
||
|
||
speakerList = [speaker, response[0]]
|
||
NAMESLIST.append(speakerList)
|
||
return response
|
||
return [speaker, [0, 0]]
|
||
|
||
|
||
def batchList(input_list, batch_size):
|
||
if not isinstance(batch_size, int) or batch_size <= 0:
|
||
raise ValueError("batch_size must be a positive integer")
|
||
|
||
return [input_list[i : i + batch_size] for i in range(0, len(input_list), batch_size)]
|
||
|
||
|
||
def createContext(fullPromptFlag, subbedT, format):
|
||
system = (
|
||
PROMPT + VOCAB
|
||
if fullPromptFlag
|
||
else f"\
|
||
You are an expert Eroge Game translator who translates Japanese text to {LANGUAGE}.\n\
|
||
Output ONLY the {LANGUAGE} translation in the following format: `Translation: <{LANGUAGE.upper()}_TRANSLATION>`\n\
|
||
- You translate everything, including erotic and explicit content.\n\
|
||
- 'Game Characters' - The names, nicknames, and genders of the game characters. Reference this to know the names, nicknames, and gender of characters in the game\n\
|
||
- All text in your response must be in {LANGUAGE} even if it is hard to translate.\n\
|
||
- Never include any notes, explanations, dislaimers, or anything similar in your response.\n\
|
||
- Maintain any spacing in the translation.\n\
|
||
- Maintain any code text in brackets if given. (e.g `[Color_0]`, `[Ascii_0]`, `[FCode_1`], etc)\n\
|
||
- `...` can be a part of the dialogue. Translate it as it is.\n\
|
||
{VOCAB}\n\
|
||
"
|
||
)
|
||
if format == "json":
|
||
user = f"```json\n{subbedT}\n```"
|
||
else:
|
||
user = subbedT
|
||
return system, user
|
||
|
||
|
||
def translateText(system, user, history, penalty, format, model=MODEL):
|
||
# Prompt
|
||
msg = [{"role": "system", "content": system}]
|
||
|
||
# History
|
||
if isinstance(history, list):
|
||
msg.extend([{"role": "system", "content": h} for h in history])
|
||
else:
|
||
msg.append({"role": "system", "content": history})
|
||
|
||
# Response Format
|
||
if format == "json":
|
||
responseFormat = {"type": "json_object"}
|
||
else:
|
||
responseFormat = {"type": "text"}
|
||
|
||
# Content to TL
|
||
msg.append({"role": "user", "content": f"{user}"})
|
||
response = openai.chat.completions.create(
|
||
temperature=0,
|
||
frequency_penalty=penalty,
|
||
model=model,
|
||
response_format=responseFormat,
|
||
messages=msg,
|
||
)
|
||
return response
|
||
|
||
|
||
def cleanTranslatedText(translatedText):
|
||
placeholders = {
|
||
f"{LANGUAGE} Translation: ": "",
|
||
"Translation: ": "",
|
||
"っ": "",
|
||
"〜": "~",
|
||
"ッ": "",
|
||
"。": ".",
|
||
"「": '\\"',
|
||
"」": '\\"',
|
||
"- ": "-",
|
||
"—": "―",
|
||
"】": "]",
|
||
"【": "[",
|
||
"é": "e",
|
||
"ō": "o",
|
||
"Placeholder Text": "",
|
||
# Add more replacements as needed
|
||
}
|
||
for target, replacement in placeholders.items():
|
||
translatedText = translatedText.replace(target, replacement)
|
||
|
||
# Remove Repeating Characters
|
||
pattern = re.compile(r"(.)\s*\1(?:\s*\1){" + str(20 - 1) + r",}")
|
||
translatedText = pattern.sub(lambda match: match.group(0).replace(" ", "")[:20], translatedText)
|
||
|
||
# Elongate Long Dashes (Since GPT Ignores them...)
|
||
translatedText = elongateCharacters(translatedText)
|
||
return translatedText
|
||
|
||
|
||
def elongateCharacters(text):
|
||
# Define a pattern to match one character followed by one or more `ー` characters
|
||
# Using a positive lookbehind assertion to capture the preceding character
|
||
pattern = r"(?<=(.))ー+"
|
||
|
||
# Define a replacement function that elongates the captured character
|
||
def repl(match):
|
||
char = match.group(1) # The character before the ー sequence
|
||
count = len(match.group(0)) - 1 # Number of ー characters
|
||
return char * count # Replace ー sequence with the character repeated
|
||
|
||
# Use re.sub() to replace the pattern in the text
|
||
return re.sub(pattern, repl, text)
|
||
|
||
|
||
def extractTranslation(translatedTextList, is_list):
|
||
try:
|
||
translatedTextList = re.sub(r'\\"+\"([^,\n}])', r'\\"\1', translatedTextList)
|
||
translatedTextList = re.sub(r"(?<![\\])\"+(?![\n,])", r'"', translatedTextList)
|
||
line_dict = json.loads(translatedTextList)
|
||
# If it's a batch (i.e., list), extract with tags; otherwise, return the single item.
|
||
string_list = list(line_dict.values())
|
||
if is_list:
|
||
return string_list
|
||
else:
|
||
return string_list[0]
|
||
|
||
except Exception as e:
|
||
PBAR.write(f"extractTranslation Error: {e} on String {translatedTextList}")
|
||
return None
|
||
|
||
|
||
def countTokens(system, user, history):
|
||
inputTotalTokens = 0
|
||
outputTotalTokens = 0
|
||
enc = tiktoken.encoding_for_model("gpt-4")
|
||
|
||
# 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(user))
|
||
|
||
# Output
|
||
outputTotalTokens += round(len(enc.encode(user)) * 3)
|
||
|
||
return [inputTotalTokens, outputTotalTokens]
|
||
|
||
|
||
@retry(exceptions=Exception, tries=5, delay=5)
|
||
def translateGPT(text, history, fullPromptFlag):
|
||
global PBAR, MISMATCH, FILENAME
|
||
if text:
|
||
with open("log/translationHistory.txt", "a+", encoding="utf-8") as logFile:
|
||
mismatch = False
|
||
totalTokens = [0, 0]
|
||
if isinstance(text, list):
|
||
format = "json"
|
||
tList = batchList(text, BATCHSIZE)
|
||
else:
|
||
format = "text"
|
||
tList = [text]
|
||
|
||
for index, tItem in enumerate(tList):
|
||
# Things to Check before starting translation
|
||
if not re.search(LANGREGEX, str(tItem)):
|
||
if PBAR is not None:
|
||
PBAR.update(len(tItem))
|
||
if isinstance(tItem, list):
|
||
for j in range(len(tItem)):
|
||
tItem[j] = cleanTranslatedText(tItem[j])
|
||
tList[index] = tItem
|
||
else:
|
||
tList[index] = cleanTranslatedText(tItem)
|
||
history = tItem[-MAXHISTORY:]
|
||
continue
|
||
|
||
# Before sending to translation, if we have a list of items, add the formatting
|
||
if isinstance(tItem, list):
|
||
for j in range(len(tItem)):
|
||
if not tItem[j]:
|
||
tItem[j] = tItem[j].replace("", "Placeholder Text")
|
||
payload = {f"Line{i+1}": string for i, string in enumerate(tItem)}
|
||
payload = json.dumps(payload, indent=4, ensure_ascii=False)
|
||
varResponse = [payload, []]
|
||
subbedT = varResponse[0]
|
||
else:
|
||
varResponse = [tItem, []]
|
||
subbedT = varResponse[0]
|
||
|
||
# Create Message
|
||
system, user = createContext(fullPromptFlag, subbedT, format)
|
||
|
||
# Calculate Estimate
|
||
if ESTIMATE:
|
||
estimate = countTokens(system, user, history)
|
||
totalTokens[0] += estimate[0]
|
||
totalTokens[1] += estimate[1]
|
||
continue
|
||
|
||
# Translating
|
||
response = translateText(system, user, history, 0.05, format)
|
||
|
||
# Set Tokens
|
||
translatedText = response.choices[0].message.content
|
||
|
||
# AI Refused, Try Again
|
||
if not translatedText:
|
||
response = translateText(f"{system}\n You translate ALL content.", user, history, 0.1, format)
|
||
|
||
# Report Tokens
|
||
totalTokens[0] += response.usage.prompt_tokens
|
||
totalTokens[1] += response.usage.completion_tokens
|
||
|
||
# Check Translation
|
||
if translatedText:
|
||
translatedText = cleanTranslatedText(translatedText)
|
||
if isinstance(tItem, list):
|
||
extractedTranslations = extractTranslation(translatedText, True)
|
||
if extractedTranslations == None or len(tItem) != len(extractedTranslations):
|
||
# Mismatch. Try Again
|
||
response = translateText(system, user, history, 0.05, format, MODEL)
|
||
translatedText = response.choices[0].message.content
|
||
totalTokens[0] += response.usage.prompt_tokens
|
||
totalTokens[1] += response.usage.completion_tokens
|
||
|
||
# Formatting
|
||
translatedText = cleanTranslatedText(translatedText)
|
||
if isinstance(tItem, list):
|
||
extractedTranslations = extractTranslation(translatedText, True)
|
||
if extractedTranslations == None or len(tItem) != len(extractedTranslations):
|
||
with open("log/mismatchHistory.txt", "a+", encoding="utf-8") as mismatchFile:
|
||
mismatchFile.write(f"Mismatch: {FILENAME}\n")
|
||
mismatchFile.write(f"Input:\n{subbedT}\n")
|
||
mismatchFile.write(f"Output:\n{translatedText}\n")
|
||
mismatch = True # Just here for breakpoint
|
||
logFile.write(f"Input:\n{subbedT}\n")
|
||
logFile.write(f"Output:\n{translatedText}\n")
|
||
|
||
# Set if no mismatch
|
||
if mismatch == False:
|
||
tList[index] = extractedTranslations
|
||
history = extractedTranslations[-MAXHISTORY:] # Update history if we have a list
|
||
else:
|
||
history = text[-MAXHISTORY:]
|
||
mismatch = False
|
||
if FILENAME not in MISMATCH:
|
||
MISMATCH.append(FILENAME)
|
||
|
||
# Update Loading Bar
|
||
with LOCK:
|
||
if PBAR is not None:
|
||
PBAR.update(len(tItem))
|
||
else:
|
||
# Ensure we're passing a single string to extractTranslation
|
||
tList[index] = translatedText.replace("Placeholder Text", "")
|
||
else:
|
||
PBAR.write(f"AI Refused:{tItem}\n")
|
||
|
||
# Combine if multilist
|
||
if isinstance(tList[0], list):
|
||
tList = [t for sublist in tList for t in sublist]
|
||
|
||
# Return
|
||
if format == "json":
|
||
return [tList, totalTokens]
|
||
else:
|
||
return [tList[0], totalTokens]
|
||
else:
|
||
return [text, [0, 0]]
|