208 lines
6.9 KiB
Python
208 lines
6.9 KiB
Python
import os
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import functools
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import re
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import pickle
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import time
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CACHE_FOLDER = "gpt_log"
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if not os.path.exists(CACHE_FOLDER):
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os.makedirs(CACHE_FOLDER)
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def lru_file_cache(maxsize=128, ttl=None, filename=None):
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"""
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Decorator that caches a function's return value after being called with given arguments.
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It uses a Least Recently Used (LRU) cache strategy to limit the size of the cache.
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maxsize: Maximum size of the cache. Defaults to 128.
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ttl: Time-to-Live of the cache. If a value hasn't been accessed for `ttl` seconds, it will be evicted from the cache.
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filename: Name of the file to store the cache in. If not supplied, the function name + ".cache" will be used.
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"""
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cache_path = os.path.join(CACHE_FOLDER, f"{filename}.cache") if filename is not None else None
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def decorator_function(func):
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cache = {}
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_cache_info = {
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"hits": 0,
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"misses": 0,
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"maxsize": maxsize,
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"currsize": 0,
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"ttl": ttl,
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"filename": cache_path,
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}
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@functools.wraps(func)
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def wrapper_function(*args, **kwargs):
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key = str((args, frozenset(kwargs)))
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if key in cache:
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if _cache_info["ttl"] is None or (cache[key][1] + _cache_info["ttl"]) >= time.time():
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_cache_info["hits"] += 1
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print(f'Warning, reading cache, last read {(time.time()-cache[key][1])//60} minutes ago'); time.sleep(2)
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cache[key][1] = time.time()
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return cache[key][0]
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else:
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del cache[key]
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result = func(*args, **kwargs)
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cache[key] = [result, time.time()]
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_cache_info["misses"] += 1
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_cache_info["currsize"] += 1
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if _cache_info["currsize"] > _cache_info["maxsize"]:
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oldest_key = None
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for k in cache:
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if oldest_key is None:
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oldest_key = k
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elif cache[k][1] < cache[oldest_key][1]:
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oldest_key = k
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del cache[oldest_key]
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_cache_info["currsize"] -= 1
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if cache_path is not None:
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with open(cache_path, "wb") as f:
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pickle.dump(cache, f)
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return result
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def cache_info():
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return _cache_info
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wrapper_function.cache_info = cache_info
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if cache_path is not None and os.path.exists(cache_path):
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with open(cache_path, "rb") as f:
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cache = pickle.load(f)
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_cache_info["currsize"] = len(cache)
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return wrapper_function
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return decorator_function
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def contains_chinese(string):
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"""
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Returns True if the given string contains Chinese characters, False otherwise.
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"""
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chinese_regex = re.compile(u'[\u4e00-\u9fff]+')
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return chinese_regex.search(string) is not None
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def extract_chinese_characters(file_path):
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syntax = []
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with open(file_path, 'r', encoding='utf-8') as f:
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content = f.read()
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import ast
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root = ast.parse(content)
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for node in ast.walk(root):
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if isinstance(node, ast.Name):
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if contains_chinese(node.id):
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print(node.id)
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syntax.append(node)
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return syntax
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def extract_chinese_characters_from_directory(directory_path):
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chinese_characters = []
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for root, dirs, files in os.walk(directory_path):
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for file in files:
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if file.endswith('.py'):
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file_path = os.path.join(root, file)
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chinese_characters.extend(extract_chinese_characters(file_path))
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return chinese_characters
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directory_path = './'
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chinese_characters = extract_chinese_characters_from_directory(directory_path)
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word_to_translate = {}
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for d in chinese_characters:
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word_to_translate[d['word']] = "TRANS"
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def break_dictionary(d, n):
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items = list(d.items())
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num_dicts = (len(items) + n - 1) // n
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return [{k: v for k, v in items[i*n:(i+1)*n]} for i in range(num_dicts)]
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N_EACH_REQ = 50
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word_to_translate_split = break_dictionary(word_to_translate, N_EACH_REQ)
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LANG = "English"
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@lru_file_cache(maxsize=10, ttl=1e40, filename="translation_cache")
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def trans(words):
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# from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
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# from toolbox import get_conf, ChatBotWithCookies
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# proxies, WEB_PORT, LLM_MODEL, CONCURRENT_COUNT, AUTHENTICATION, CHATBOT_HEIGHT, LAYOUT, API_KEY = \
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# get_conf('proxies', 'WEB_PORT', 'LLM_MODEL', 'CONCURRENT_COUNT', 'AUTHENTICATION', 'CHATBOT_HEIGHT', 'LAYOUT', 'API_KEY')
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# llm_kwargs = {
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# 'api_key': API_KEY,
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# 'llm_model': LLM_MODEL,
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# 'top_p':1.0,
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# 'max_length': None,
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# 'temperature':0.0,
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# }
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# plugin_kwargs = {}
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# chatbot = ChatBotWithCookies(llm_kwargs)
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# history = []
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# for gpt_say in request_gpt_model_in_new_thread_with_ui_alive(
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# inputs=words, inputs_show_user=words,
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# llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
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# sys_prompt=f"Translate following words to {LANG}, replace `TRANS` with translated result."
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# ):
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# gpt_say = gpt_say[1][0][1]
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# return gpt_say
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return '{}'
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translated_result = {}
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for d in word_to_translate_split:
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res = trans(str(d))
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try:
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# convert translated result back to python dictionary
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res_dict = eval(res)
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except:
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print('Unexpected output.')
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translated_result.update(res_dict)
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print('All Chinese characters:', chinese_characters)
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# =================== create copy =====================
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def copy_source_code():
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"""
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一键更新协议：备份和下载
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"""
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from toolbox import get_conf
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import shutil
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import os
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import requests
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import zipfile
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try: shutil.rmtree(f'./multi-language/{LANG}/')
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except: pass
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os.makedirs(f'./multi-language', exist_ok=True)
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backup_dir = f'./multi-language/{LANG}/'
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shutil.copytree('./', backup_dir, ignore=lambda x, y: ['multi-language', 'gpt_log', '.git', 'private_upload'])
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copy_source_code()
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for d in chinese_characters:
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d['file'] = f'./multi-language/{LANG}/' + d['file']
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if d['word'] in translated_result:
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d['trans'] = translated_result[d['word']]
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else:
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d['trans'] = None
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chinese_characters = sorted(chinese_characters, key=lambda x: len(x['word']), reverse=True)
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for d in chinese_characters:
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if d['trans'] is None:
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continue
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with open(d['file'], 'r', encoding='utf-8') as f:
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content = f.read()
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content.replace(d['word'], d['trans'])
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substring = d['trans']
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substring_start_index = content.find(substring)
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substring_end_index = substring_start_index + len(substring) - 1
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if content[substring_start_index].isalpha() or content[substring_start_index].isdigit():
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content = content[:substring_start_index+1]
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