574 lines
20 KiB
Python
574 lines
20 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 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 = True # 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 = 50
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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 handleAnim(filename, estimate):
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global ESTIMATE
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totalTokens = [0, 0]
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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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totalTokens[0] += translatedData[1][0]
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totalTokens[1] += translatedData[1][1]
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# Print Total
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totalString = getResultString(["", totalTokens, 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="UTF-8") as outFile:
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start = time.time()
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translatedData = openFiles(filename)
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# Print Result
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end = time.time()
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json.dump(translatedData[0], outFile, ensure_ascii=False, indent=4)
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tqdm.write(getResultString(translatedData, end - start, filename))
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with LOCK:
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totalTokens[0] += translatedData[1][0]
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totalTokens[1] += translatedData[1][1]
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except Exception:
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return "Fail"
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return getResultString(["", totalTokens, None], end - start, "TOTAL")
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def openFiles(filename):
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with open("files/" + filename, "r", encoding="UTF-8-sig") as f:
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data = json.load(f)
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# Map Files
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if ".json" in filename:
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translatedData = parseJSON(data, filename)
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else:
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raise NameError(filename + " Not Supported")
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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] * 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 parseJSON(data, filename):
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keys = list(data.keys())
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batches = [keys[i : i + BATCHSIZE] for i in range(0, len(keys), BATCHSIZE)]
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totalTokens = [0, 0]
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totalLines = 0
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totalLines = len(batches)
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global LOCK
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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 = translateJSON(batches, data, pbar)
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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 translateJSON(keys, data, pbar):
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translatedBatch = []
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textHistory = []
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tokens = [0, 0]
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for batch in keys:
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# Save Batch
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originalBatch = batch.copy()
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# If there isn't any Japanese in the text just skip
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needTL = False
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for i in range(len(batch)):
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t = data[batch[i]]
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if re.search(r"[一-龠ぁ-ゔァ-ヴーａ-ｚＡ-Ｚ０-９]+", t) or t == "":
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needTL = True
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if needTL is False and IGNORETLTEXT is True:
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pbar.update(1)
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continue
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# Remove any textwrap and Furigana
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for i in range(len(batch)):
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if FIXTEXTWRAP == True:
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# Textwrap
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data[originalBatch[i]] = data[originalBatch[i]].replace("@b", " ")
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# Furigana
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rcodeMatch = re.findall(r"(@\[(.+?):.+?\])", batch[i])
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if len(rcodeMatch) > 0:
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for match in rcodeMatch:
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batch[i] = batch[i].replace(match[0], match[1])
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# Translate
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if needTL is True:
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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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else:
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for i in range(len(originalBatch)):
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translatedBatch.append(data[originalBatch[i]])
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# Format and Set Text
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if len(batch) == len(translatedBatch):
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for i in range(len(translatedBatch)):
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# Remove added speaker
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translatedText = translatedBatch[i]
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translatedText = re.sub(r"^.+?\s\|\s?", "", translatedText)
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# Textwrap
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if "@n" in translatedText:
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match = re.search(r".*@n(.*)", translatedText)
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if match != None:
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tlText = match.group(1)
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tlText = textwrap.fill(tlText, width=WIDTH)
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tlText = tlText.replace("\n", "@b")
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translatedText = translatedText.replace(match.group(1), tlText)
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elif "@b" not in translatedText:
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translatedText = textwrap.fill(translatedText, width=WIDTH)
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translatedText = translatedText.replace("\n", "@b")
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# Set Data
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data[originalBatch[i]] = translatedText
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textHistory = translatedBatch
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translatedBatch.clear()
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# Mismatch, Skip Batch
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else:
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MISMATCH.append(batch)
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pbar.update(1)
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continue
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pbar.update(1)
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return tokens
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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]+\[[a-zA-Z0-9\\\[\]\_,\s-]+\]", 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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return translatedText
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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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達也 (Tatsuya) - Male\n\
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香織 (Kaori) - Female\n\
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岩瀬 (Iwase)\n\
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万蔵 (Manzou) - Male\n\
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結奈 (Yuuna) - Female\n\
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茅部 (Kayabe)\n\
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"
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system = (
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PROMPT + VOCAB
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if fullPromptFlag
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else f"\
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You are an expert Eroge Game translator who translates Japanese text to {LANGUAGE}.\n\
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Output ONLY the {LANGUAGE} translation in the following format: `Translation: <{LANGUAGE.upper()}_TRANSLATION>`\n\
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- You translate everything, including erotic and explicit content.\n\
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- '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\
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- All text in your response must be in {LANGUAGE} even if it is hard to translate.\n\
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- Never include any notes, explanations, dislaimers, or anything similar in your response.\n\
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- Maintain any spacing in the translation.\n\
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- Maintain any code text in brackets if given. (e.g `[Color_0]`, `[Ascii_0]`, `[FCode_1`], etc)\n\
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- `...` can be a part of the dialogue. Translate it as it is.\n\
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{VOCAB}\n\
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"
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)
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user = f"{subbedT}"
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return characters, system, user
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def translateText(characters, system, user, history, penalty):
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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
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if isinstance(history, list):
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msg.extend([{"role": "system", "content": h} for h in history])
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else:
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msg.append({"role": "system", "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,
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frequency_penalty=penalty,
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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):
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placeholders = {
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f"{LANGUAGE} Translation: ": "",
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"Translation: ": "",
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"っ": "",
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"〜": "~",
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"ッ": "",
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"。": ".",
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"Placeholder Text": "",
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"é": "e",
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"—": "-",
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"ū": "u",
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# Add more replacements as needed
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}
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for target, replacement in placeholders.items():
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translatedText = translatedText.replace(target, replacement)
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# Elongate Long Dashes (Since GPT Ignores them...)
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translatedText = elongateCharacters(translatedText)
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translatedText = resubVars(translatedText, varResponse[1])
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return translatedText
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def elongateCharacters(text):
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# Define a pattern to match one character followed by one or more `ー` characters
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# Using a positive lookbehind assertion to capture the preceding character
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pattern = r"(?<=(.))ー+"
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# Define a replacement function that elongates the captured character
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def repl(match):
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char = match.group(1) # The character before the ー sequence
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count = len(match.group(0)) - 1 # Number of ー characters
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return char * count # Replace ー sequence with the character repeated
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# Use re.sub() to replace the pattern in the text
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return re.sub(pattern, repl, text)
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def extractTranslation(translatedTextList, is_list):
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pattern = r"`?<[Ll]ine\d+>([\\]*.*?[\\]*?)<\/?[Ll]ine\d+>`?"
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# If it's a batch (i.e., list), extract with tags; otherwise, return the single item.
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if is_list:
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matchList = re.findall(pattern, translatedTextList)
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return matchList
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else:
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matchList = re.findall(pattern, translatedTextList)
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return matchList[0][0] if matchList else translatedTextList
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def countTokens(characters, system, user, history):
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inputTotalTokens = 0
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outputTotalTokens = 0
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enc = tiktoken.encoding_for_model("gpt-4")
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# Input
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if isinstance(history, list):
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for line in history:
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inputTotalTokens += len(enc.encode(line))
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else:
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inputTotalTokens += len(enc.encode(history))
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inputTotalTokens += len(enc.encode(system))
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inputTotalTokens += len(enc.encode(characters))
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inputTotalTokens += len(enc.encode(user))
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# Output
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outputTotalTokens += round(len(enc.encode(user)) * 3)
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return [inputTotalTokens, outputTotalTokens]
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@retry(exceptions=Exception, tries=5, delay=5)
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def translateGPT(text, history, fullPromptFlag):
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mismatch = False
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totalTokens = [0, 0]
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if isinstance(text, list):
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tList = batchList(text, BATCHSIZE)
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else:
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tList = [text]
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for index, tItem in enumerate(tList):
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# Before sending to translation, if we have a list of items, add the formatting
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if isinstance(tItem, list):
|
||
payload = "\n".join([f"`<Line{i}>{item}</Line{i}>`" for i, item in enumerate(tItem)])
|
||
payload = re.sub(r"(<Line\d+)(><)(\/Line\d+>)", r"\1>Placeholder Text<\3", payload)
|
||
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, 0.02)
|
||
translatedText = response.choices[0].message.content
|
||
totalTokens[0] += response.usage.prompt_tokens
|
||
totalTokens[1] += response.usage.completion_tokens
|
||
|
||
# Formatting
|
||
translatedText = cleanTranslatedText(translatedText, varResponse)
|
||
if isinstance(tItem, list):
|
||
extractedTranslations = extractTranslation(translatedText, True)
|
||
tList[index] = extractedTranslations
|
||
if len(tItem) != len(extractedTranslations):
|
||
# Mismatch. Try Again
|
||
response = translateText(characters, system, user, history, 0.1)
|
||
translatedText = response.choices[0].message.content
|
||
totalTokens[0] += response.usage.prompt_tokens
|
||
totalTokens[1] += response.usage.completion_tokens
|
||
|
||
# Formatting
|
||
translatedText = cleanTranslatedText(translatedText, varResponse)
|
||
if isinstance(tItem, list):
|
||
extractedTranslations = extractTranslation(translatedText, True)
|
||
tList[index] = extractedTranslations
|
||
if len(tItem) != len(extractedTranslations):
|
||
mismatch = True # Just here for breakpoint
|
||
|
||
# Create History
|
||
if not mismatch:
|
||
history = extractedTranslations[-10:] # Update history if we have a list
|
||
else:
|
||
history = text[-10:]
|
||
else:
|
||
# Ensure we're passing a single string to extractTranslation
|
||
extractedTranslations = extractTranslation(translatedText, 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]
|