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import os | |
import json | |
import functools | |
import re | |
import pickle | |
import time | |
CACHE_FOLDER = "gpt_log" | |
blacklist = ['multi-language', 'gpt_log', '.git', 'private_upload', 'multi_language.py'] | |
LANG = "TraditionalChinese" | |
TransPrompt = f"Replace each json value `#` with translated results in Traditional Chinese, e.g., \"原始文本\":\"翻譯後文字\". Keep Json format. Do not answer #." | |
# LANG = "Japanese" | |
# TransPrompt = f"Replace each json value `#` with translated results in Japanese, e.g., \"原始文本\":\"テキストの翻訳\". Keep Json format. Do not answer #." | |
# LANG = "English" | |
# TransPrompt = f"Replace each json value `#` with translated results in English, e.g., \"原始文本\":\"TranslatedText\". Keep Json format. Do not answer #." | |
if not os.path.exists(CACHE_FOLDER): | |
os.makedirs(CACHE_FOLDER) | |
def lru_file_cache(maxsize=128, ttl=None, filename=None): | |
""" | |
Decorator that caches a function's return value after being called with given arguments. | |
It uses a Least Recently Used (LRU) cache strategy to limit the size of the cache. | |
maxsize: Maximum size of the cache. Defaults to 128. | |
ttl: Time-to-Live of the cache. If a value hasn't been accessed for `ttl` seconds, it will be evicted from the cache. | |
filename: Name of the file to store the cache in. If not supplied, the function name + ".cache" will be used. | |
""" | |
cache_path = os.path.join(CACHE_FOLDER, f"{filename}.cache") if filename is not None else None | |
def decorator_function(func): | |
cache = {} | |
_cache_info = { | |
"hits": 0, | |
"misses": 0, | |
"maxsize": maxsize, | |
"currsize": 0, | |
"ttl": ttl, | |
"filename": cache_path, | |
} | |
def wrapper_function(*args, **kwargs): | |
key = str((args, frozenset(kwargs))) | |
if key in cache: | |
if _cache_info["ttl"] is None or (cache[key][1] + _cache_info["ttl"]) >= time.time(): | |
_cache_info["hits"] += 1 | |
print(f'Warning, reading cache, last read {(time.time()-cache[key][1])//60} minutes ago'); time.sleep(2) | |
cache[key][1] = time.time() | |
return cache[key][0] | |
else: | |
del cache[key] | |
result = func(*args, **kwargs) | |
cache[key] = [result, time.time()] | |
_cache_info["misses"] += 1 | |
_cache_info["currsize"] += 1 | |
if _cache_info["currsize"] > _cache_info["maxsize"]: | |
oldest_key = None | |
for k in cache: | |
if oldest_key is None: | |
oldest_key = k | |
elif cache[k][1] < cache[oldest_key][1]: | |
oldest_key = k | |
del cache[oldest_key] | |
_cache_info["currsize"] -= 1 | |
if cache_path is not None: | |
with open(cache_path, "wb") as f: | |
pickle.dump(cache, f) | |
return result | |
def cache_info(): | |
return _cache_info | |
wrapper_function.cache_info = cache_info | |
if cache_path is not None and os.path.exists(cache_path): | |
with open(cache_path, "rb") as f: | |
cache = pickle.load(f) | |
_cache_info["currsize"] = len(cache) | |
return wrapper_function | |
return decorator_function | |
def contains_chinese(string): | |
""" | |
Returns True if the given string contains Chinese characters, False otherwise. | |
""" | |
chinese_regex = re.compile(u'[\u4e00-\u9fff]+') | |
return chinese_regex.search(string) is not None | |
def split_list(lst, n_each_req): | |
""" | |
Split a list into smaller lists, each with a maximum number of elements. | |
:param lst: the list to split | |
:param n_each_req: the maximum number of elements in each sub-list | |
:return: a list of sub-lists | |
""" | |
result = [] | |
for i in range(0, len(lst), n_each_req): | |
result.append(lst[i:i + n_each_req]) | |
return result | |
def map_to_json(map, language): | |
dict_ = read_map_from_json(language) | |
dict_.update(map) | |
with open(f'docs/translate_{language.lower()}.json', 'w', encoding='utf8') as f: | |
json.dump(dict_, f, indent=4, ensure_ascii=False) | |
def read_map_from_json(language): | |
if os.path.exists(f'docs/translate_{language.lower()}.json'): | |
with open(f'docs/translate_{language.lower()}.json', 'r', encoding='utf8') as f: | |
res = json.load(f) | |
res = {k:v for k, v in res.items() if v is not None and contains_chinese(k)} | |
return res | |
return {} | |
def advanced_split(splitted_string, spliter, include_spliter=False): | |
splitted_string_tmp = [] | |
for string_ in splitted_string: | |
if spliter in string_: | |
splitted = string_.split(spliter) | |
for i, s in enumerate(splitted): | |
if include_spliter: | |
if i != len(splitted)-1: | |
splitted[i] += spliter | |
splitted[i] = splitted[i].strip() | |
for i in reversed(range(len(splitted))): | |
if not contains_chinese(splitted[i]): | |
splitted.pop(i) | |
splitted_string_tmp.extend(splitted) | |
else: | |
splitted_string_tmp.append(string_) | |
splitted_string = splitted_string_tmp | |
return splitted_string_tmp | |
cached_translation = {} | |
cached_translation = read_map_from_json(language=LANG) | |
def trans(word_to_translate, language, special=False): | |
if len(word_to_translate) == 0: return {} | |
from crazy_functions.crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency | |
from toolbox import get_conf, ChatBotWithCookies | |
proxies, WEB_PORT, LLM_MODEL, CONCURRENT_COUNT, AUTHENTICATION, CHATBOT_HEIGHT, LAYOUT, API_KEY = \ | |
get_conf('proxies', 'WEB_PORT', 'LLM_MODEL', 'CONCURRENT_COUNT', 'AUTHENTICATION', 'CHATBOT_HEIGHT', 'LAYOUT', 'API_KEY') | |
llm_kwargs = { | |
'api_key': API_KEY, | |
'llm_model': LLM_MODEL, | |
'top_p':1.0, | |
'max_length': None, | |
'temperature':0.4, | |
} | |
import random | |
N_EACH_REQ = random.randint(16, 32) | |
word_to_translate_split = split_list(word_to_translate, N_EACH_REQ) | |
inputs_array = [str(s) for s in word_to_translate_split] | |
inputs_show_user_array = inputs_array | |
history_array = [[] for _ in inputs_array] | |
if special: # to English using CamelCase Naming Convention | |
sys_prompt_array = [f"Translate following names to English with CamelCase naming convention. Keep original format" for _ in inputs_array] | |
else: | |
sys_prompt_array = [f"Translate following sentences to {LANG}. E.g., You should translate sentences to the following format ['translation of sentence 1', 'translation of sentence 2']. Do NOT answer with Chinese!" for _ in inputs_array] | |
chatbot = ChatBotWithCookies(llm_kwargs) | |
gpt_say_generator = request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency( | |
inputs_array, | |
inputs_show_user_array, | |
llm_kwargs, | |
chatbot, | |
history_array, | |
sys_prompt_array, | |
) | |
while True: | |
try: | |
gpt_say = next(gpt_say_generator) | |
print(gpt_say[1][0][1]) | |
except StopIteration as e: | |
result = e.value | |
break | |
translated_result = {} | |
for i, r in enumerate(result): | |
if i%2 == 1: | |
try: | |
res_before_trans = eval(result[i-1]) | |
res_after_trans = eval(result[i]) | |
if len(res_before_trans) != len(res_after_trans): | |
raise RuntimeError | |
for a,b in zip(res_before_trans, res_after_trans): | |
translated_result[a] = b | |
except: | |
# try: | |
# res_before_trans = word_to_translate_split[(i-1)//2] | |
# res_after_trans = [s for s in result[i].split("', '")] | |
# for a,b in zip(res_before_trans, res_after_trans): | |
# translated_result[a] = b | |
# except: | |
print('GPT输出格式错误,稍后可能需要再试一次') | |
res_before_trans = eval(result[i-1]) | |
for a in res_before_trans: | |
translated_result[a] = None | |
return translated_result | |
def trans_json(word_to_translate, language, special=False): | |
if len(word_to_translate) == 0: return {} | |
from crazy_functions.crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency | |
from toolbox import get_conf, ChatBotWithCookies | |
proxies, WEB_PORT, LLM_MODEL, CONCURRENT_COUNT, AUTHENTICATION, CHATBOT_HEIGHT, LAYOUT, API_KEY = \ | |
get_conf('proxies', 'WEB_PORT', 'LLM_MODEL', 'CONCURRENT_COUNT', 'AUTHENTICATION', 'CHATBOT_HEIGHT', 'LAYOUT', 'API_KEY') | |
llm_kwargs = { | |
'api_key': API_KEY, | |
'llm_model': LLM_MODEL, | |
'top_p':1.0, | |
'max_length': None, | |
'temperature':0.1, | |
} | |
import random | |
N_EACH_REQ = random.randint(16, 32) | |
random.shuffle(word_to_translate) | |
word_to_translate_split = split_list(word_to_translate, N_EACH_REQ) | |
inputs_array = [{k:"#" for k in s} for s in word_to_translate_split] | |
inputs_array = [ json.dumps(i, ensure_ascii=False) for i in inputs_array] | |
inputs_show_user_array = inputs_array | |
history_array = [[] for _ in inputs_array] | |
sys_prompt_array = [TransPrompt for _ in inputs_array] | |
chatbot = ChatBotWithCookies(llm_kwargs) | |
gpt_say_generator = request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency( | |
inputs_array, | |
inputs_show_user_array, | |
llm_kwargs, | |
chatbot, | |
history_array, | |
sys_prompt_array, | |
) | |
while True: | |
try: | |
gpt_say = next(gpt_say_generator) | |
print(gpt_say[1][0][1]) | |
except StopIteration as e: | |
result = e.value | |
break | |
translated_result = {} | |
for i, r in enumerate(result): | |
if i%2 == 1: | |
try: | |
translated_result.update(json.loads(result[i])) | |
except: | |
print(result[i]) | |
print(result) | |
return translated_result | |
def step_1_core_key_translate(): | |
def extract_chinese_characters(file_path): | |
syntax = [] | |
with open(file_path, 'r', encoding='utf-8') as f: | |
content = f.read() | |
import ast | |
root = ast.parse(content) | |
for node in ast.walk(root): | |
if isinstance(node, ast.Name): | |
if contains_chinese(node.id): syntax.append(node.id) | |
if isinstance(node, ast.Import): | |
for n in node.names: | |
if contains_chinese(n.name): syntax.append(n.name) | |
elif isinstance(node, ast.ImportFrom): | |
for n in node.names: | |
if contains_chinese(n.name): syntax.append(n.name) | |
for k in node.module.split('.'): | |
if contains_chinese(k): syntax.append(k) | |
return syntax | |
def extract_chinese_characters_from_directory(directory_path): | |
chinese_characters = [] | |
for root, dirs, files in os.walk(directory_path): | |
if any([b in root for b in blacklist]): | |
continue | |
for file in files: | |
if file.endswith('.py'): | |
file_path = os.path.join(root, file) | |
chinese_characters.extend(extract_chinese_characters(file_path)) | |
return chinese_characters | |
directory_path = './' | |
chinese_core_names = extract_chinese_characters_from_directory(directory_path) | |
chinese_core_keys = [name for name in chinese_core_names] | |
chinese_core_keys_norepeat = [] | |
for d in chinese_core_keys: | |
if d not in chinese_core_keys_norepeat: chinese_core_keys_norepeat.append(d) | |
need_translate = [] | |
cached_translation = read_map_from_json(language=LANG) | |
cached_translation_keys = list(cached_translation.keys()) | |
for d in chinese_core_keys_norepeat: | |
if d not in cached_translation_keys: | |
need_translate.append(d) | |
need_translate_mapping = trans(need_translate, language=LANG, special=True) | |
map_to_json(need_translate_mapping, language=LANG) | |
cached_translation = read_map_from_json(language=LANG) | |
cached_translation = dict(sorted(cached_translation.items(), key=lambda x: -len(x[0]))) | |
chinese_core_keys_norepeat_mapping = {} | |
for k in chinese_core_keys_norepeat: | |
chinese_core_keys_norepeat_mapping.update({k:cached_translation[k]}) | |
chinese_core_keys_norepeat_mapping = dict(sorted(chinese_core_keys_norepeat_mapping.items(), key=lambda x: -len(x[0]))) | |
# =============================================== | |
# copy | |
# =============================================== | |
def copy_source_code(): | |
from toolbox import get_conf | |
import shutil | |
import os | |
try: shutil.rmtree(f'./multi-language/{LANG}/') | |
except: pass | |
os.makedirs(f'./multi-language', exist_ok=True) | |
backup_dir = f'./multi-language/{LANG}/' | |
shutil.copytree('./', backup_dir, ignore=lambda x, y: blacklist) | |
copy_source_code() | |
# =============================================== | |
# primary key replace | |
# =============================================== | |
directory_path = f'./multi-language/{LANG}/' | |
for root, dirs, files in os.walk(directory_path): | |
for file in files: | |
if file.endswith('.py'): | |
file_path = os.path.join(root, file) | |
syntax = [] | |
# read again | |
with open(file_path, 'r', encoding='utf-8') as f: | |
content = f.read() | |
for k, v in chinese_core_keys_norepeat_mapping.items(): | |
content = content.replace(k, v) | |
with open(file_path, 'w', encoding='utf-8') as f: | |
f.write(content) | |
def step_2_core_key_translate(): | |
# ================================================================================================= | |
# step2 | |
# ================================================================================================= | |
def load_string(strings, string_input): | |
string_ = string_input.strip().strip(',').strip().strip('.').strip() | |
if string_.startswith('[Local Message]'): | |
string_ = string_.replace('[Local Message]', '') | |
string_ = string_.strip().strip(',').strip().strip('.').strip() | |
splitted_string = [string_] | |
# -------------------------------------- | |
splitted_string = advanced_split(splitted_string, spliter=",", include_spliter=False) | |
splitted_string = advanced_split(splitted_string, spliter="。", include_spliter=False) | |
splitted_string = advanced_split(splitted_string, spliter=")", include_spliter=False) | |
splitted_string = advanced_split(splitted_string, spliter="(", include_spliter=False) | |
splitted_string = advanced_split(splitted_string, spliter="(", include_spliter=False) | |
splitted_string = advanced_split(splitted_string, spliter=")", include_spliter=False) | |
splitted_string = advanced_split(splitted_string, spliter="<", include_spliter=False) | |
splitted_string = advanced_split(splitted_string, spliter=">", include_spliter=False) | |
splitted_string = advanced_split(splitted_string, spliter="[", include_spliter=False) | |
splitted_string = advanced_split(splitted_string, spliter="]", include_spliter=False) | |
splitted_string = advanced_split(splitted_string, spliter="【", include_spliter=False) | |
splitted_string = advanced_split(splitted_string, spliter="】", include_spliter=False) | |
splitted_string = advanced_split(splitted_string, spliter="?", include_spliter=False) | |
splitted_string = advanced_split(splitted_string, spliter=":", include_spliter=False) | |
splitted_string = advanced_split(splitted_string, spliter=":", include_spliter=False) | |
splitted_string = advanced_split(splitted_string, spliter=",", include_spliter=False) | |
splitted_string = advanced_split(splitted_string, spliter="#", include_spliter=False) | |
splitted_string = advanced_split(splitted_string, spliter="\n", include_spliter=False) | |
splitted_string = advanced_split(splitted_string, spliter=";", include_spliter=False) | |
splitted_string = advanced_split(splitted_string, spliter="`", include_spliter=False) | |
splitted_string = advanced_split(splitted_string, spliter=" ", include_spliter=False) | |
splitted_string = advanced_split(splitted_string, spliter="- ", include_spliter=False) | |
splitted_string = advanced_split(splitted_string, spliter="---", include_spliter=False) | |
# -------------------------------------- | |
for j, s in enumerate(splitted_string): # .com | |
if '.com' in s: continue | |
if '\'' in s: continue | |
if '\"' in s: continue | |
strings.append([s,0]) | |
def get_strings(node): | |
strings = [] | |
# recursively traverse the AST | |
for child in ast.iter_child_nodes(node): | |
node = child | |
if isinstance(child, ast.Str): | |
if contains_chinese(child.s): | |
load_string(strings=strings, string_input=child.s) | |
elif isinstance(child, ast.AST): | |
strings.extend(get_strings(child)) | |
return strings | |
string_literals = [] | |
directory_path = f'./multi-language/{LANG}/' | |
for root, dirs, files in os.walk(directory_path): | |
for file in files: | |
if file.endswith('.py'): | |
file_path = os.path.join(root, file) | |
syntax = [] | |
with open(file_path, 'r', encoding='utf-8') as f: | |
content = f.read() | |
# comments | |
comments_arr = [] | |
for code_sp in content.splitlines(): | |
comments = re.findall(r'#.*$', code_sp) | |
for comment in comments: | |
load_string(strings=comments_arr, string_input=comment) | |
string_literals.extend(comments_arr) | |
# strings | |
import ast | |
tree = ast.parse(content) | |
res = get_strings(tree, ) | |
string_literals.extend(res) | |
[print(s) for s in string_literals] | |
chinese_literal_names = [] | |
chinese_literal_names_norepeat = [] | |
for string, offset in string_literals: | |
chinese_literal_names.append(string) | |
chinese_literal_names_norepeat = [] | |
for d in chinese_literal_names: | |
if d not in chinese_literal_names_norepeat: chinese_literal_names_norepeat.append(d) | |
need_translate = [] | |
cached_translation = read_map_from_json(language=LANG) | |
cached_translation_keys = list(cached_translation.keys()) | |
for d in chinese_literal_names_norepeat: | |
if d not in cached_translation_keys: | |
need_translate.append(d) | |
up = trans_json(need_translate, language=LANG, special=False) | |
map_to_json(up, language=LANG) | |
cached_translation = read_map_from_json(language=LANG) | |
cached_translation = dict(sorted(cached_translation.items(), key=lambda x: -len(x[0]))) | |
# =============================================== | |
# literal key replace | |
# =============================================== | |
directory_path = f'./multi-language/{LANG}/' | |
for root, dirs, files in os.walk(directory_path): | |
for file in files: | |
if file.endswith('.py'): | |
file_path = os.path.join(root, file) | |
syntax = [] | |
# read again | |
with open(file_path, 'r', encoding='utf-8') as f: | |
content = f.read() | |
for k, v in cached_translation.items(): | |
if v is None: continue | |
if '"' in v: | |
v = v.replace('"', "`") | |
if '\'' in v: | |
v = v.replace('\'', "`") | |
content = content.replace(k, v) | |
with open(file_path, 'w', encoding='utf-8') as f: | |
f.write(content) | |
if file.strip('.py') in cached_translation: | |
file_new = cached_translation[file.strip('.py')] + '.py' | |
file_path_new = os.path.join(root, file_new) | |
with open(file_path_new, 'w', encoding='utf-8') as f: | |
f.write(content) | |
os.remove(file_path) | |
step_1_core_key_translate() | |
step_2_core_key_translate() |