DazedTL/modules/wolf2.py

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# Libraries
import json
import io
import os
import re
import util.dazedwrap as dazedwrap
import threading
import time
import traceback
import tiktoken
from pathlib import Path
from colorama import Fore
from dotenv import load_dotenv
from retry import retry
from tqdm import tqdm
from util.translation import TranslationConfig, translateAI as sharedtranslateAI, getPricingConfig, calculateCost
import tempfile
# OpenAI initialization centralized in util/translation.py
# Globals
MODEL = os.getenv("model")
TIMEOUT = int(os.getenv("timeout"))
LANGUAGE = os.getenv("language").capitalize()
PROMPT = Path("prompt.txt").read_text(encoding="utf-8")
VOCAB = Path("vocab.txt").read_text(encoding="utf-8")
LOCK = threading.Lock()
WIDTH = int(os.getenv("width"))
LISTWIDTH = int(os.getenv("listWidth"))
NOTEWIDTH = 70
MAXHISTORY = 10
ESTIMATE = ""
TOKENS = [0, 0]
NAMESLIST = []
NAMES = False # Output a list of all the character names found
BRFLAG = False # If the game uses <br> instead
FIXTEXTWRAP = True # Overwrites textwrap
IGNORETLTEXT = False # Ignores all translated text.
MISMATCH = [] # Lists files that throw a mismatch error (Length of GPT list response is wrong)
FILENAME = "" # Current file being processed, used by translateAI wrapper
# tqdm Globals
BAR_FORMAT = "{l_bar}{bar:10}{r_bar}{bar:-10b}"
POSITION = 0
LEAVE = False
# Regex - Need to change this if you want to translate from/to other languages. Default is Japanese Regex
LANGREGEX = r"[一-龠ぁ-ゔァ-ヴーa---\uFF61-\uFF9F]+"
# Get pricing configuration based on the model
PRICING_CONFIG = getPricingConfig(MODEL)
INPUTAPICOST = PRICING_CONFIG["inputAPICost"]
OUTPUTAPICOST = PRICING_CONFIG["outputAPICost"]
BATCHSIZE = PRICING_CONFIG["batchSize"]
FREQUENCY_PENALTY = PRICING_CONFIG["frequencyPenalty"]
# Initialize Translation Config
TRANSLATION_CONFIG = TranslationConfig(
model=MODEL,
language=LANGUAGE,
prompt=PROMPT,
vocab=VOCAB,
langRegex=LANGREGEX,
batchSize=BATCHSIZE,
maxHistory=MAXHISTORY,
estimateMode=False # Will be set dynamically based on ESTIMATE
)
LEAVE = False
def handleWOLF2(filename, estimate):
global ESTIMATE, FILENAME
ESTIMATE = estimate
FILENAME = filename
if ESTIMATE:
start = time.time()
translatedData = openFiles(filename)
# Print Result
end = time.time()
tqdm.write(getResultString(translatedData, end - start, filename))
with LOCK:
TOKENS[0] += translatedData[1][0]
TOKENS[1] += translatedData[1][1]
# Print Total
totalString = getResultString(["", TOKENS, None], end - start, "TOTAL")
# Print any errors on maps
if len(MISMATCH) > 0:
return totalString + Fore.RED + f"\nMismatch Errors: {MISMATCH}" + Fore.RESET
else:
return totalString
else:
try:
with open("translated/" + filename, "w", encoding="shift_jis", errors="ignore") as outFile:
start = time.time()
translatedData = openFiles(filename)
# Print Result
end = time.time()
outFile.writelines(translatedData[0])
tqdm.write(getResultString(translatedData, end - start, filename))
with LOCK:
TOKENS[0] += translatedData[1][0]
TOKENS[1] += translatedData[1][1]
except Exception:
traceback.print_exc()
return "Fail"
return getResultString(["", TOKENS, None], end - start, "TOTAL")
def getResultString(translatedData, translationTime, filename):
# File Print String
cost = calculateCost(translatedData[1][0], translatedData[1][1], MODEL)
totalTokenstring = (
Fore.YELLOW + "[Input: " + str(translatedData[1][0]) + "]"
"[Output: "
+ str(translatedData[1][1])
+ "]" "[Cost: ${:,.4f}".format(cost)
+ "]"
)
timeString = Fore.BLUE + "[" + str(round(translationTime, 1)) + "s]"
if translatedData[2] == None:
# Success
return filename + ": " + totalTokenstring + timeString + Fore.GREEN + " \u2713 " + Fore.RESET
else:
# Fail
try:
raise translatedData[2]
except Exception as e:
traceback.print_exc()
errorString = str(e) + Fore.RED
return filename + ": " + totalTokenstring + timeString + Fore.RED + " \u2717 " + errorString + Fore.RESET
def openFiles(filename):
# Use a robust reader to handle cp932/Shift_JIS variants and occasional bad bytes
def read_file_lines_with_fallback(path: str):
encodings = ["cp932", "shift_jis", "utf-8-sig", "utf-8"]
for enc in encodings:
try:
with open(path, "r", encoding=enc) as f:
return f.readlines()
except UnicodeDecodeError:
continue
# Last resort: ignore undecodable bytes under cp932
with open(path, "rb") as f:
raw = f.read()
try:
text = raw.decode("cp932", errors="ignore")
except Exception:
text = raw.decode("latin-1", errors="ignore")
return text.splitlines(keepends=True)
path = os.path.join("files", filename)
lines = read_file_lines_with_fallback(path)
# Keep parseWOLF API by wrapping lines in a file-like object
with io.StringIO("".join(lines)) as readFile:
translatedData = parseWOLF(readFile, filename)
# Delete lines marked for deletion
finalData = []
for line in translatedData[0]:
if line != "\\d\n":
finalData.append(line)
translatedData[0] = finalData
return translatedData
def parseWOLF(readFile, filename):
totalTokens = [0, 0]
# Read File into data
data = readFile.readlines()
# Create Progress Bar
with tqdm(bar_format=BAR_FORMAT, position=POSITION, leave=LEAVE) as pbar:
pbar.desc = filename
try:
result = translateWOLF(data, [], pbar, filename)
totalTokens[0] += result[0]
totalTokens[1] += result[1]
except Exception as e:
traceback.print_exc()
return [data, totalTokens, e]
return [data, totalTokens, None]
def save_progress_lines(lines, filename, encoding="shift_jis"):
"""Atomically save current line-based translation progress."""
try:
if ESTIMATE:
return
os.makedirs("translated", exist_ok=True)
tmp_fd, tmp_path = tempfile.mkstemp(prefix=f"{filename}.", suffix=".tmp", dir="translated")
try:
with os.fdopen(tmp_fd, "w", encoding=encoding, newline="\n", errors="ignore") as tmp_file:
tmp_file.writelines(lines)
os.replace(tmp_path, os.path.join("translated", filename))
finally:
if os.path.exists(tmp_path):
try:
os.remove(tmp_path)
except OSError:
pass
except Exception:
traceback.print_exc()
def saveCheckLines(lines, filename, tokens=None, encoding="shift_jis"):
try:
if tokens is not None:
if not (isinstance(tokens, (list, tuple)) and len(tokens) >= 2 and (tokens[0] or tokens[1])):
return
save_progress_lines(lines, filename, encoding=encoding)
except Exception:
traceback.print_exc()
def translateWOLF(data, translatedList, pbar, filename):
stringList = []
currentGroup = []
tokens = [0, 0]
speaker = ""
global LOCK, ESTIMATE, PBAR
PBAR = pbar
i = 0
while i < len(data):
# Speaker
matchList = re.findall(r"^([^/]*)", data[i])
if len(matchList) != 0:
response = getSpeaker(matchList[0])
speaker = response[0]
tokens[0] += response[1][0]
tokens[1] += response[1][1]
data[i] = data[i].replace(matchList[0], f"{speaker}")
saveCheckLines(data, filename)
i += 1
else:
speaker = ""
# Options
if "//選択肢" in data[i]:
i += 1
choiceList = []
initialIndex = i
while "//" in data[i] and "の場合" not in data[i]:
choiceList.append(re.search(r"\/\/(.*)", data[i]).group(1))
i += 1
# Translate
response = translateAI(choiceList, "This will be a dialogue option")
tokens[0] += response[1][0]
tokens[1] += response[1][1]
choiceListTL = response[0]
# Set Data
if len(choiceList) == len(choiceListTL):
# Set Data
i = initialIndex
while "//" in data[i] and "の場合" not in data[i]:
choiceListTL[0] = choiceListTL[0].replace(", ", "")
data[i] = f"//{choiceListTL[0]}\n"
choiceListTL.pop(0)
i += 1
saveCheckLines(data, filename)
# Mismatch
else:
with LOCK:
if filename not in MISMATCH:
MISMATCH.append(filename)
# Lines
if r"/" not in data[i] and "@" not in data[i] and data[i] != "\n":
# Pass 1
if translatedList == []:
# Grab Consecutive Strings
currentGroup.append(data[i])
i += 1
while i < len(data) and r"/" not in data[i] and "@" not in data[i] and data[i] != "\n":
currentGroup.append(data[i])
i += 1
# Join up 401 groups for better translation.
if len(currentGroup) > 0:
jaString = "".join(currentGroup)
currentGroup = []
# Remove any textwrap
jaString = jaString.replace("\n", " ")
# Add Speaker (If there is one)
if speaker != "":
jaString = f"[{speaker}]: {jaString}"
# Add String
stringList.append(jaString)
i += 1
# Pass 2
else:
# Insert Strings
while i < len(data) and r"/" not in data[i] and "@" not in data[i] and data[i] != "\n":
data.pop(i)
# Get Text
translatedText = translatedList[0]
translatedList.pop(0)
if len(translatedList) <= 0:
translatedList = None
# Remove speaker
matchSpeakerList = re.findall(r"^(\[.+?\]\s?[|:]\s?)\s?", translatedText)
if len(matchSpeakerList) > 0:
translatedText = translatedText.replace(matchSpeakerList[0], "")
# Textwrap
translatedText = dazedwrap.wrapText(translatedText, width=WIDTH)
# Set Data
data.insert(i, f"{translatedText}\n")
saveCheckLines(data, filename)
i += 1
# Nothing relevant. Skip Line.
else:
i += 1
# EOF
if len(stringList) > 0:
# Set Progress
pbar.total = len(stringList)
pbar.refresh()
# Translate
response = translateAI(stringList, "")
tokens[0] += response[1][0]
tokens[1] += response[1][1]
translatedList = response[0]
# Set Strings
if len(stringList) == len(translatedList):
translateWOLF(data, translatedList, pbar, filename)
# Mismatch
else:
with LOCK:
if filename not in MISMATCH:
MISMATCH.append(filename)
return tokens
# Save some money and enter the character before translation
def getSpeaker(speaker):
match speaker:
case "ファイン":
return ["Fine", [0, 0]]
case "":
return ["", [0, 0]]
case _:
# Find Speaker
for i in range(len(NAMESLIST)):
if speaker == NAMESLIST[i][0]:
return [NAMESLIST[i][1], [0, 0]]
# Translate and Store Speaker
response = translateAI(
f"{speaker}",
"Reply with the " + LANGUAGE + " translation of the NPC name.",
False,
)
response[0] = response[0].title()
response[0] = response[0].replace("'S", "'s")
response[0] = response[0].replace("Speaker: ", "")
# Retry if name doesn't translate for some reason
if re.search(r"([a-zA-Z?])", response[0]) == None:
response = translateAI(
f"{speaker}",
"Reply with the " + LANGUAGE + " translation of the NPC name.",
False,
)
response[0] = response[0].title()
response[0] = response[0].replace("'S", "'s")
speakerList = [speaker, response[0]]
NAMESLIST.append(speakerList)
return response
return [speaker, [0, 0]]
def translateAI(text, history, history_ctx=None):
"""
Legacy wrapper function for the new shared translation utility.
This maintains compatibility with existing code while using the new shared implementation.
"""
global PBAR, MISMATCH, FILENAME
# Update config estimate mode based on global ESTIMATE
TRANSLATION_CONFIG.estimateMode = bool(ESTIMATE)
# Call the new shared translation function
return sharedtranslateAI(
text=text,
history=history,
config=TRANSLATION_CONFIG,
filename=FILENAME,
pbar=PBAR,
lock=LOCK,
mismatchList=MISMATCH
)