374 lines
12 KiB
Python
374 lines
12 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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PBAR = None
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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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# 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-5" 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 handleLune(filename, estimate):
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global FILENAME, ESTIMATE, totalTokens
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ESTIMATE = estimate
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FILENAME = filename
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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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return getResultString(["", TOKENS, None], end - start, "TOTAL")
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else:
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try:
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with open("translated/" + filename, "w", encoding="utf-8", newline="\n") 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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TOKENS[0] += translatedData[1][0]
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TOKENS[1] += translatedData[1][1]
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except Exception:
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return "Fail"
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return getResultString(["", TOKENS, 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] / 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 parseJSON(data, filename):
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totalTokens = [0, 0]
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totalLines = 0
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totalLines = len(data)
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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(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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return [data, totalTokens, e]
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return [data, totalTokens, None]
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def translateJSON(data, pbar):
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global PBAR
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PBAR = pbar
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textHistory = []
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batch = []
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maxHistory = MAXHISTORY
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tokens = [0, 0]
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speaker = "None"
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insertBool = False
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i = 0
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batchStartIndex = 0
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while i < len(data):
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item = data[i]
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# Speaker
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if "name" in item:
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if item["name"] not in [None, "-"]:
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response = getSpeaker(item["name"])
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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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item["name"] = speaker
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else:
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speaker = "None"
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# Text
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if "message" in item:
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for text in [
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"text",
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"text2",
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"help1",
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"help2",
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"help3",
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"like",
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"message",
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"me",
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]:
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if text in item:
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if item[text] != None:
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jaString = item[text]
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# Remove any textwrap
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if FIXTEXTWRAP == True:
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finalJAString = jaString.replace("\n", " ")
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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 = translateAI(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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if insertBool is False:
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pbar.update(1)
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i += 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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# Remove added speaker
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translatedText = re.sub(r"^.+?:\s", "", translatedText)
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# Textwrap
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translatedText = dazedwrap.wrapText(translatedText, width=WIDTH)
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# Set Text
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item[text] = translatedText
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translatedBatch.pop(0)
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speaker = ""
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currentGroup = []
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i += 1
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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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else:
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i += 1
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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 = translateAI(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 "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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