| """ |
| 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 = "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: |
| 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: |
| |
| |
| |
| |
| |
| |
| 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) |
| |
| 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]))) |
|
|
| |
| |
| |
| 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() |
|
|
| |
| |
| |
| 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() |
| |
| 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(): |
|
|
| |
| |
| |
|
|
| 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): |
| if '.com' in s: continue |
| if '\'' in s: continue |
| if '\"' in s: continue |
| strings.append([s,0]) |
|
|
|
|
| def get_strings(node): |
| strings = [] |
| |
| 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_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) |
|
|
| |
| 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]))) |
|
|
| |
| |
| |
| 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() |
| |
| 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/') |