127 lines
4.6 KiB
Python
127 lines
4.6 KiB
Python
from concurrent.futures import ThreadPoolExecutor
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from colorama import Fore
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from dotenv import load_dotenv
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from tqdm import tqdm
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import os
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import re
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import textwrap
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import json
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import time
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import openai
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#Globals
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load_dotenv()
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openai.organization = os.getenv('org')
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openai.api_key = os.getenv('key')
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pipe = '###'
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THREADS = 5
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def main():
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# Open File (Threads)
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with ThreadPoolExecutor(max_workers=THREADS, thread_name_prefix='handle') as executor:
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for filename in os.listdir("files"):
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if filename.endswith('json'):
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executor.submit(handle, filename)
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def handle(filename):
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with open('translated/' + filename, 'w', encoding='UTF-8') as outFile:
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with open('files/' + filename, 'r', encoding='UTF-8') as f:
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try:
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# Map Files
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if 'Map' in filename:
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# Start Timer
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start = time.time()
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# Start Translation
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translatedData = parseMap(json.load(f), filename)
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json.dump(translatedData, outFile, ensure_ascii=False)
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# Print Results
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end = time.time()
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print(f.name + ':', end=' ')
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print(Fore.GREEN + str(round(end - start, 1)) + 's ' + u'\u2713' + Fore.RESET)
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except Exception as e:
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end = time.time()
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print(f.name + ':', end=' ')
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print(Fore.RED + str(round(end - start, 1)) + 's ' + u'\u2717 ' + str(e) + Fore.RESET)
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def parseMap(data, filename):
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with ThreadPoolExecutor(max_workers=THREADS, thread_name_prefix='parseMap') as executor:
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events = data['events']
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for event in events:
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if event is not None:
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for page in event['pages']:
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future = executor.submit(searchCodes, page, filename)
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# Verify if an exception was thrown
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try:
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future.result()
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except Exception as e:
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raise e
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return data
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def searchCodes(page, filename):
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translatedText = ''
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currentGroup = []
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textHistory = []
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try:
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for i in tqdm(range(len(page['list'])), leave=False, position=0, desc=filename):
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time.sleep(0.001)
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if page['list'][i]['code'] == 401:
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currentGroup.append(page['list'][i]['parameters'][0])
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while (page['list'][i+1]['code'] == 401):
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del page['list'][i]
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currentGroup.append(page['list'][i]['parameters'][0])
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else:
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if len(currentGroup) > 0:
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text = ''.join(currentGroup)
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text = text.replace('\\n', '')
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translatedText = translateGPT(text, ' '.join(textHistory))
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textHistory.append(translatedText)
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translatedText = textwrap.fill(translatedText, width=50)
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page['list'][i-1]['parameters'][0] = translatedText
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if len(textHistory) > 10:
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textHistory.pop(0)
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currentGroup = []
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except IndexError:
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pass
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# Append leftover groups
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if len(currentGroup) > 0:
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translatedText = translateGPT(''.join(currentGroup), ' '.join(textHistory))
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translatedText = textwrap.fill(translatedText, width=50)
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page['list'][i]['parameters'][0] = translatedText
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currentGroup = []
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def translateGPT(t, history):
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pattern = r'[一-龠]+|[ぁ-ゔ]+|[ァ-ヴー]+'
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if not re.search(pattern, t):
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return t
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"""Translate text using GPT"""
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system = "Context: " + history + "\n\n###\n\n You are a professional Japanese visual novel translator,\
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editor, and localizer. You always manages to carry all of the little nuances of the original Japanese text to your output,\
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while still making it a prose masterpiece, and localizing it in a way that an average American would understand.\
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The 'Context' at the top is previously translated text for the work.\
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You translate Onomatopoeia literally.\
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When I give you something to translate, answer with just the translation.\
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Translation Examples:\
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\\n<ルイ>そう、私はルイよ。= \\n<Rui> Yes, I'm Rui.\
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\\nそう、私はルイよ。= \\nYes, I'm Rui."
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response = openai.ChatCompletion.create(
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temperature=0,
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model="gpt-3.5-turbo",
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messages=[
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{"role": "system", "content": system},
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{"role": "user", "content": t}
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]
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)
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return response.choices[0].message.content
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main()
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