354 lines
11 KiB
Python
354 lines
11 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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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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from util.translation import TranslationConfig, translateAI as sharedtranslateAI
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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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FILENAME = None
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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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# 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 = 1.25
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OUTPUTAPICOST = 10.00
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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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# Initialize Translation Config
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TRANSLATION_CONFIG = TranslationConfig(
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model=MODEL,
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language=LANGUAGE,
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prompt=PROMPT,
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vocab=VOCAB,
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langRegex=LANGREGEX,
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batchSize=BATCHSIZE,
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maxHistory=MAXHISTORY,
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estimateMode=False # Will be set dynamically based on ESTIMATE
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)
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LEAVE = False
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def handleRenpy(filename, estimate):
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global ESTIMATE
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global FILENAME
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FILENAME = filename
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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="utf8", 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] / 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] == 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="utf8") as readFile:
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translatedData = parseRenpy(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 parseRenpy(readFile, filename):
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global PBAR
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totalTokens = [0, 0]
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# Read File into data
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data = readFile.readlines()
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# Create Progress Bar
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with tqdm(bar_format=BAR_FORMAT, position=POSITION, leave=LEAVE) as pbar:
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pbar.desc = filename
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PBAR = pbar
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try:
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result = translateRenpy(data, [])
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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 translateRenpy(data, translatedList):
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stringList = []
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currentGroup = []
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tokens = [0, 0]
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speaker = ""
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voice = False
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global LOCK, ESTIMATE, FILENAME, PBAR
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i = 0
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while i < len(data):
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voice = False
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speaker = ""
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lineRegexNoSpeaker = r'^\s\s\s\s"(.*)"'
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lineRegexSpeaker = r'^\s\s\s\s(.+?)\s"(.*)"'
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# Grab Line
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match = re.search(lineRegexSpeaker, data[i])
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if match:
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response = getSpeaker(match.group(1))
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jaString = match.group(2)
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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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else:
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match = re.search(lineRegexNoSpeaker, data[i])
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if match:
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jaString = match.group(1)
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# Valid Line
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if match and "voice" not in data[i]:
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originalString = jaString
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# Pass 1
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if translatedList == []:
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# Remove any textwrap
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jaString = jaString.replace("\\n", " ")
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# Add String
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if speaker:
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stringList.append(f"[{speaker}]: {jaString.strip()}")
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else:
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stringList.append(jaString.strip())
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# Pass 2
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else:
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# Get Text
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if translatedList:
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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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# Set to None if empty list
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if len(translatedList) <= 0:
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translatedList = None
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# Remove speaker
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if speaker != "":
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matchSpeakerList = re.findall(r"^\[?(.+?)\]?\s?[|:]\s?", translatedText)
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translatedText = re.sub(r"^\[?(.+?)\]?\s?[|:]\s?", "", translatedText)
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# Escape Quotes
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translatedText = re.sub(r'[\\]*(")', '\\"', translatedText)
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translatedText = re.sub(r"[\\]*(')", "\\'", translatedText)
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# Textwrap
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translatedText = dazedwrap.wrapText(translatedText, width=WIDTH)
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translatedText = translatedText.replace("\n", "\\n")
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# Set Data
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data[i] = data[i].replace(originalString, translatedText)
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i += 1
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else:
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i += 1
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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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# Translate
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response = translateAI(stringList, "Reply with the English TL of the NPC Name", True)
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tokens[0] += response[1][0]
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tokens[1] += response[1][1]
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translatedList = response[0]
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# Set Strings
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if len(stringList) == len(translatedList):
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translateRenpy(data, translatedList)
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# Mismatch
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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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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 "ファイン":
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return ["Fine", [0, 0]]
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case "":
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return ["", [0, 0]]
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case _:
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# Find Speaker
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for i in range(len(NAMESLIST)):
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if speaker == NAMESLIST[i][0]:
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return [NAMESLIST[i][1], [0, 0]]
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# Translate and Store Speaker
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response = translateAI(
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f"{speaker}",
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"Reply with the " + LANGUAGE + " translation of the NPC name.",
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False,
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)
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response[0] = response[0].title()
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response[0] = response[0].replace("'S", "'s")
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response[0] = response[0].replace("Speaker: ", "")
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# Retry if name doesn't translate for some reason
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if re.search(r"([a-zA-Z？?])", response[0]) == None:
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response = translateAI(
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f"{speaker}",
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"Reply with the " + LANGUAGE + " translation of the NPC name.",
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False,
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)
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response[0] = response[0].title()
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response[0] = response[0].replace("'S", "'s")
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speakerList = [speaker, response[0]]
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NAMESLIST.append(speakerList)
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return response
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return [speaker, [0, 0]]
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def translateAI(text, history, fullPromptFlag):
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"""
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Legacy wrapper function for the new shared translation utility.
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This maintains compatibility with existing code while using the new shared implementation.
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"""
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global PBAR, MISMATCH, FILENAME
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# Update config estimate mode based on global ESTIMATE
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TRANSLATION_CONFIG.estimateMode = bool(ESTIMATE)
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# Call the new shared translation function
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return sharedtranslateAI(
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text=text,
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history=history,
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fullPromptFlag=fullPromptFlag,
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config=TRANSLATION_CONFIG,
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filename=FILENAME,
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pbar=PBAR,
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lock=LOCK,
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mismatchList=MISMATCH
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)
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