706 lines
24 KiB
Python
706 lines
24 KiB
Python
# Libraries
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import os
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import re
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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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import openai
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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 = 70
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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 = False # Overwrites textwrap
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IGNORETLTEXT = False # Ignores all translated text.
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MISMATCH = [] # Lists files that throw a mismatch error (Length of GPT list response is wrong)
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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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# 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 = 0.002
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OUTPUTAPICOST = 0.002
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BATCHSIZE = 10
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elif "gpt-4" in MODEL:
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INPUTAPICOST = 0.01
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OUTPUTAPICOST = 0.03
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BATCHSIZE = 10
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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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def handleKansen(filename, estimate):
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global ESTIMATE
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ESTIMATE = estimate
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if ESTIMATE:
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start = time.time()
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translatedData = openFiles(filename)
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# Print Result
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end = time.time()
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tqdm.write(getResultString(translatedData, end - start, filename))
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with LOCK:
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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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else:
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try:
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with open("translated/" + filename, "w", encoding="shift_jis", errors="ignore") as outFile:
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start = time.time()
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translatedData = openFiles(filename)
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# Print Result
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end = time.time()
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outFile.writelines(translatedData[0])
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tqdm.write(getResultString(translatedData, end - start, filename))
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with LOCK:
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TOKENS[0] += translatedData[1][0]
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TOKENS[1] += translatedData[1][1]
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except Exception:
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traceback.print_exc()
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return "Fail"
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return getResultString(["", TOKENS, None], end - start, "TOTAL")
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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] * 0.001 * INPUTAPICOST) + (translatedData[1][1] * 0.001 * 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] == 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 openFiles(filename):
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with open("files/" + filename, "r", encoding="cp932") as readFile:
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translatedData = parseTyrano(readFile, 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, filename):
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totalTokens = [0, 0]
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totalLines = 0
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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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result = translateTyrano(data, pbar, totalLines)
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totalTokens[0] += result[0]
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totalTokens[1] += result[1]
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except Exception as e:
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traceback.print_exc()
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return [data, totalTokens, e]
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return [data, totalTokens, None]
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def translateTyrano(data, pbar, totalLines):
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textHistory = []
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batch = []
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currentGroup = []
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maxHistory = MAXHISTORY
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tokens = [0, 0]
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speaker = ""
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insertBool = False
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global LOCK, ESTIMATE
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i = 0
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batchStartIndex = 0
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while i < len(data):
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# Speaker
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if "[ns]" in data[i]:
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matchList = re.findall(r"\[ns\](.+?)\[", data[i])
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if len(matchList) != 0:
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response = getSpeaker(matchList[0])
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speaker = response[0]
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tokens[0] += response[1][0]
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tokens[1] += response[1][1]
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data[i] = "[ns]" + speaker + "[nse]\n"
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else:
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speaker = ""
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# Choices
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elif "[sel" in data[i]:
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matchList = re.findall(r'\[sel.+text="(.+?)".+', data[i])
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if len(matchList) != 0:
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originalText = matchList[0]
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if len(textHistory) > 0:
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response = translateGPT(
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matchList[0],
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"Keep your translation as brief as possible. Previous text for context: "
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+ textHistory[len(textHistory) - 1]
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+ "\n\nReply in the style of a dialogue option.",
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False,
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)
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else:
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response = translateGPT(
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matchList[0],
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"\n\nReply in the style of a dialogue option.",
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False,
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)
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translatedText = response[0]
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tokens[0] += response[1][0]
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tokens[1] += response[1][1]
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# Remove characters that may break scripts
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charList = [".", '"', "\\n"]
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for char in charList:
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translatedText = translatedText.replace(char, "")
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# Escape all '
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translatedText = translatedText.replace("\\", "")
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# translatedText = translatedText.replace("'", "\\\'")
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# Set Data
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translatedText = data[i].replace(originalText, translatedText)
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data[i] = translatedText
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# Lines
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matchList = re.findall(r"(.+?)\[[rpcms_sel]+\]$", data[i])
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if len(matchList) > 0:
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if "hisout" in matchList[0]:
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i += 1
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continue
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currentGroup.append(matchList[0])
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if len(data) > i + 1:
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while "[r]" in data[i + 1]:
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if insertBool is True:
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data[i] = r"\d\n"
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pbar.update(1)
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i += 1
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matchList = re.findall(r"(.+?)\[r\]", data[i])
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if len(matchList) > 0:
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currentGroup.append(matchList[0])
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while "[pcms]" in data[i + 1]:
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if insertBool is True:
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data[i] = r"\d\n"
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pbar.update(1)
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i += 1
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matchList = re.findall(r"(.+?)\[pcms\]", data[i])
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if len(matchList) > 0:
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currentGroup.append(matchList[0])
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while "[pcms_sel]" in data[i + 1]:
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if insertBool is True:
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data[i] = r"\d\n"
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pbar.update(1)
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i += 1
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matchList = re.findall(r"(.+?)\[pcms_sel\]", data[i])
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if len(matchList) > 0:
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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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# Remove any textwrap
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if FIXTEXTWRAP == True:
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finalJAString = finalJAString.replace("[r]", " ")
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# Remove Extra Stuff bad for translation.
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finalJAString = finalJAString.replace("ﾞ", "")
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finalJAString = finalJAString.replace("・", ".")
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finalJAString = finalJAString.replace("‶", "")
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finalJAString = finalJAString.replace("”", "")
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finalJAString = finalJAString.replace("―", "-")
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finalJAString = finalJAString.replace("…", "...")
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finalJAString = re.sub(r"(\.{3}\.+)", "...", finalJAString)
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finalJAString = finalJAString.replace(" ", " ")
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# Furigana Removal
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matchList = re.findall(r"(\[ruby\stext=.+text=\"(.+)\"\])", finalJAString)
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if len(matchList) > 0:
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finalJAString = finalJAString.replace(matchList[0][0], matchList[0][1])
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# Add Speaker (If there is one)
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if speaker != "":
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finalJAString = f"{speaker}: {finalJAString}"
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# [Passthrough 1] Pulling From File
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if insertBool is False:
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# Append to List and Clear Values
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batch.append(finalJAString)
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speaker = ""
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# Translate Batch if Full
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if len(batch) == BATCHSIZE:
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# Translate
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response = translateGPT(batch, textHistory, True)
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tokens[0] += response[1][0]
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tokens[1] += response[1][1]
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translatedBatch = response[0]
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textHistory = translatedBatch[-10:]
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# Set Values
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if len(batch) == len(translatedBatch):
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i = batchStartIndex
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insertBool = True
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# Mismatch
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else:
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pbar.write(f"Mismatch: {batchStartIndex} - {i}")
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MISMATCH.append(batch)
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batchStartIndex = i
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batch.clear()
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i += 1
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if insertBool is True:
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pbar.update(1)
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currentGroup = []
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# [Passthrough 2] Setting Data
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else:
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# Get Text
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translatedText = translatedBatch[0]
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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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# Remove added speaker
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translatedText = re.sub(r"^.+?:\s", "", translatedText)
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# Textwrap
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translatedText = textwrap.fill(translatedText, width=WIDTH)
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textList = translatedText.split("\n")
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# Set Text
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data[i] = r"\d\n"
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for line in textList:
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# Wordwrap Text
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if "[r]" not in line:
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line = textwrap.fill(line, width=WIDTH)
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line = line.replace("\n", "[r]")
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# Set
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data.insert(i, line.strip() + "[r]\n")
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i += 1
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data[i - 1] = data[i - 1].replace("[r]", "[pcms]")
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translatedBatch.pop(0)
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speaker = ""
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currentGroup = []
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# If Batch is empty. Move on.
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if len(translatedBatch) == 0:
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insertBool = False
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batchStartIndex = i
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batch.clear()
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# Nothing relevant. Skip Line.
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else:
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i += 1
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if insertBool is True:
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pbar.update(1)
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# Translate Batch if not empty and EOF
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if len(batch) != 0 and i >= len(data):
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# Translate
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response = translateGPT(batch, textHistory, True)
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tokens[0] += response[1][0]
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tokens[1] += response[1][1]
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translatedBatch = response[0]
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textHistory = translatedBatch[-10:]
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# Set Values
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if len(batch) == len(translatedBatch):
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i = batchStartIndex
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insertBool = True
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# Mismatch
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else:
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pbar.write(f"Mismatch: {batchStartIndex} - {i}")
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MISMATCH.append(batch)
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batchStartIndex = i
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batch.clear()
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currentGroup = []
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return tokens
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# Save some money and enter the character before translation
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def getSpeaker(speaker):
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match speaker:
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case "央":
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return ["Akira", [0, 0]]
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case "累":
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return ["Rui", [0, 0]]
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case "梨里":
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return ["Riri", [0, 0]]
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case "純":
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return ["Jun", [0, 0]]
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case "美鈴":
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return ["Misuzu", [0, 0]]
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case "須田":
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return ["Suda", [0, 0]]
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case "高橋":
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return ["Takahashi", [0, 0]]
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case "勇二":
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return ["Yuuji", [0, 0]]
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case _:
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return translateGPT(
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speaker,
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"Reply with only the " + LANGUAGE + " translation of the NPC name.",
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False,
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)
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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
|
||
count = 0
|
||
if len(allList[4]) != 0:
|
||
for var in allList[4]:
|
||
translatedText = translatedText.replace("{Var_" + str(count) + "}", var)
|
||
count += 1
|
||
|
||
# Formatting
|
||
count = 0
|
||
if len(allList[5]) != 0:
|
||
for var in allList[5]:
|
||
translatedText = translatedText.replace("{FCode_" + str(count) + "}", var)
|
||
count += 1
|
||
|
||
return translatedText
|
||
|
||
|
||
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):
|
||
characters = "Game Characters:\n\
|
||
渋江 央 (Shibue Akira) - Male\n\
|
||
蘆名 累 (Ashina Rui) - Female\n\
|
||
清原 梨里 (Kiyohara Riri) - Female\n\
|
||
五十嵐 純 (Igarashi Jun) - Female\n\
|
||
子野日 美鈴 (Nenohi Misuzu) - Female\n\
|
||
須田 (Suda) - Male\n\
|
||
高橋 (Takahashi) - Female\n\
|
||
勇二 (Yuuji) - Male\n\
|
||
"
|
||
|
||
system = (
|
||
PROMPT + VOCAB
|
||
if fullPromptFlag
|
||
else f"\
|
||
You are an expert Eroge Game translator who translates Japanese text to {LANGUAGE}.\n\
|
||
You are going to be translating text from a videogame.\n\
|
||
I will give you lines of text, and you must translate each line to the best of your ability.\n\
|
||
{VOCAB}\n\
|
||
Output ONLY the {LANGUAGE} translation in the following format: `Translation: <{LANGUAGE.upper()}_TRANSLATION>`\
|
||
"
|
||
)
|
||
user = f"{subbedT}"
|
||
return characters, system, user
|
||
|
||
|
||
def translateText(characters, system, user, history):
|
||
# Prompt
|
||
msg = [{"role": "system", "content": system + characters}]
|
||
|
||
# Characters
|
||
msg.append({"role": "system", "content": characters})
|
||
|
||
# History
|
||
if isinstance(history, list):
|
||
msg.extend([{"role": "system", "content": h} for h in history])
|
||
else:
|
||
msg.append({"role": "system", "content": history})
|
||
|
||
# Content to TL
|
||
msg.append({"role": "user", "content": f"{user}"})
|
||
response = openai.chat.completions.create(
|
||
temperature=0.1,
|
||
frequency_penalty=0.1,
|
||
presence_penalty=0.1,
|
||
model=MODEL,
|
||
messages=msg,
|
||
)
|
||
return response
|
||
|
||
|
||
def cleanTranslatedText(translatedText, varResponse):
|
||
placeholders = {
|
||
f"{LANGUAGE} Translation: ": "",
|
||
"Translation: ": "",
|
||
"っ": "",
|
||
"〜": "~",
|
||
"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+>`?"
|
||
# 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("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(characters))
|
||
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):
|
||
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
|
||
|
||
# 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]
|