GPT-Academic-with-B3n-AI / multi_language.py
qingxu98's picture
version 3.6
17d0a32
"""
Translate this project to other languages (experimental, please open an issue if there is any bug)
Usage:
1. modify config.py, set your LLM_MODEL and API_KEY(s) to provide access to OPENAI (or any other LLM model provider)
2. modify LANG (below ↓)
LANG = "English"
3. modify TransPrompt (below ↓)
TransPrompt = f"Replace each json value `#` with translated results in English, e.g., \"原始文本\":\"TranslatedText\". Keep Json format. Do not answer #."
4. Run `python multi_language.py`.
Note: You need to run it multiple times to increase translation coverage because GPT makes mistakes sometimes.
(You can also run `CACHE_ONLY=True python multi_language.py` to use cached translation mapping)
5. Find the translated program in `multi-language\English\*`
P.S.
- The translation mapping will be stored in `docs/translation_xxxx.json`, you can revised mistaken translation there.
- If you would like to share your `docs/translation_xxxx.json`, (so that everyone can use the cached & revised translation mapping), please open a Pull Request
- If there is any translation error in `docs/translation_xxxx.json`, please open a Pull Request
- Welcome any Pull Request, regardless of language
"""
import os
import json
import functools
import re
import pickle
import time
from toolbox import get_conf
CACHE_ONLY = os.environ.get('CACHE_ONLY', False)
CACHE_FOLDER = get_conf('PATH_LOGGING')
blacklist = ['multi-language', CACHE_FOLDER, '.git', 'private_upload', 'multi_language.py', 'build', '.github', '.vscode', '__pycache__', 'venv']
# 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,
}
@functools.wraps(func)
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 answers with unexpected format, some words may not be translated, but you can try again later to increase translation coverage.')
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():
LANG_STD = 'std'
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)
# if node.module is None: print(node.module)
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
print(files)
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_STD)
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)
if CACHE_ONLY:
need_translate_mapping = {}
else:
need_translate_mapping = trans(need_translate, language=LANG_STD, special=True)
map_to_json(need_translate_mapping, language=LANG_STD)
cached_translation = read_map_from_json(language=LANG_STD)
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)
if CACHE_ONLY:
up = {}
else:
up = trans_json(need_translate, language=LANG, special=False)
map_to_json(up, language=LANG)
cached_translation = read_map_from_json(language=LANG)
LANG_STD = 'std'
cached_translation.update(read_map_from_json(language=LANG_STD))
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()
print('Finished, checkout generated results at ./multi-language/')