|<\/p><\/div>$')
pattern_markdown_p = re.compile(r'^
|<\/div>$')
def thread_write_chat(chatbot, history):
"""
对话记录写入数据库
"""
private_key = toolbox.get_conf('private_key')[0]
chat_title = chatbot[0][1].split()
i_say = pattern_markdown.sub('', chatbot[-1][0])
gpt_result = history
if private_key in chat_title:
SqliteHandle(f'ai_private_{chat_title[-2]}').inset_prompt({i_say: gpt_result})
else:
SqliteHandle(f'ai_common_{chat_title[-2]}').inset_prompt({i_say: gpt_result})
base_path = os.path.dirname(__file__)
prompt_path = os.path.join(base_path, 'users_data')
def reuse_chat(result, chatbot, history, pro_numb):
"""复用对话记录"""
if result is None or result == []:
return chatbot, history, gr.update(), gr.update(), ''
else:
if pro_numb:
chatbot += result
history += [pattern_markdown.sub('', _) for i in result for _ in i]
else:
chatbot.append(result[-1])
history += [pattern_markdown.sub('', _) for i in result[-2:] for _ in i]
print(chatbot[-1][0])
i_say = pattern_markdown.sub('', chatbot[-1][0])
return chatbot, history, i_say, gr.Tabs.update(selected='chatbot'), ''
def num_tokens_from_string(listing: list, encoding_name: str = 'cl100k_base') -> int:
"""Returns the number of tokens in a text string."""
count_tokens = 0
for i in listing:
encoding = tiktoken.get_encoding(encoding_name)
count_tokens += len(encoding.encode(i))
return count_tokens
def spinner_chatbot_loading(chatbot):
loading = [''.join(['.' * random.randint(1, 5)])]
# 将元组转换为列表并修改元素
loading_msg = copy.deepcopy(chatbot)
temp_list = list(loading_msg[-1])
if pattern_markdown.match(temp_list[1]):
temp_list[1] = pattern_markdown.sub('', temp_list[1]) + f'{random.choice(loading)}'
else:
temp_list[1] = pattern_markdown_p.sub('', temp_list[1]) + f'{random.choice(loading)}'
# 将列表转换回元组并替换原始元组
loading_msg[-1] = tuple(temp_list)
return loading_msg
def refresh_load_data(chat, history, prompt):
"""
Args:
chat: 聊天组件
history: 对话记录
prompt: prompt dataset组件
Returns:
预期是每次刷新页面，加载最新
"""
is_all = toolbox.get_conf('prompt_list')[0]['key'][0]
data = prompt_retrieval(is_all=[is_all])
prompt.samples = data
return prompt.update(samples=data, visible=True), prompt, chat, history
def txt_converter_json(input_string):
try:
if input_string.startswith("{") and input_string.endswith("}"):
# 尝试将字符串形式的字典转换为字典对象
dict_object = ast.literal_eval(input_string)
else:
# 尝试将字符串解析为JSON对象
dict_object = json.loads(input_string)
formatted_json_string = json.dumps(dict_object, indent=4, ensure_ascii=False)
return formatted_json_string
except (ValueError, SyntaxError):
return input_string
class YamlHandle:
def __init__(self, file=os.path.join(prompt_path, 'ai_common.yaml')):
if not os.path.exists(file):
Shell(f'touch {file}').read()
self.file = file
self._load = self.load()
def load(self) -> dict:
with open(file=self.file, mode='r') as f:
data = yaml.safe_load(f)
return data
def update(self, key, value):
date = self._load
if not date:
date = {}
date[key] = value
with open(file=self.file, mode='w') as f:
yaml.dump(date, f, allow_unicode=True)
return date
def dump_dict(self, new_dict):
date = self._load
if not date:
date = {}
date.update(new_dict)
with open(file=self.file, mode='w') as f:
yaml.dump(date, f, allow_unicode=True)
return date
class JsonHandle:
def __init__(self, file):
if os.path.exists(file):
with open(file=file, mode='r') as self.file_obj:
pass
else:
self.file_obj = io.StringIO() # 创建空白文本对象
self.file_obj.write('{}') # 向文本对象写入有有效 JSON 格式的数据
self.file_obj.seek(0) # 将文本对象的光标重置到开头
def load(self):
data = json.load(self.file_obj)
return data
if __name__ == '__main__':
result = [['214214', '5657'], ['fasfaf', '41241'],['kkkgh', '1`31`3'],]
ff = [pattern_markdown.sub('', _) for i in result[-2:] for _ in i]
print(ff)