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# flake8: noqa E501
import re
from typing import Dict
import json
from builder_prompt import BuilderPromptGenerator
from builder_prompt_zh import ZhBuilderPromptGenerator
from config_utils import parse_configuration
from help_tools import LogoGeneratorTool, config_conversion
from modelscope_agent import prompt_generator_register
from modelscope_agent.agent import AgentExecutor
from modelscope_agent.agent_types import AgentType
from modelscope_agent.llm import LLMFactory
from modelscope_agent.prompt import MessagesGenerator
from modelscope_agent.utils.logger import agent_logger as logger
prompts = {
'BuilderPromptGenerator': BuilderPromptGenerator,
'ZhBuilderPromptGenerator': ZhBuilderPromptGenerator,
}
prompt_generator_register(prompts)
SYSTEM = 'You are a helpful assistant.'
LOGO_TOOL_NAME = 'logo_designer'
ANSWER = 'Answer'
CONFIG = 'Config'
ASSISTANT_PROMPT = """{}: <answer>\n{}: <config>\nRichConfig: <rich_config>""".format(
ANSWER, CONFIG)
UPDATING_CONFIG_STEP = '🚀Updating Config...'
CONFIG_UPDATED_STEP = '✅Config Updated!'
UPDATING_LOGO_STEP = '🚀Updating Logo...'
LOGO_UPDATED_STEP = '✅Logo Updated!'
def init_builder_chatbot_agent(uuid_str):
# build model
builder_cfg, model_cfg, _, _, _, _ = parse_configuration(uuid_str)
# additional tool
additional_tool_list = {LOGO_TOOL_NAME: LogoGeneratorTool()}
tool_cfg = {LOGO_TOOL_NAME: {'is_remote_tool': True}}
# build llm
logger.info(
uuid=uuid_str, message=f'using builder model {builder_cfg.model}')
llm = LLMFactory.build_llm(builder_cfg.model, model_cfg)
llm.set_agent_type(AgentType.Messages)
# build prompt
# prompt generator
prompt_generator = 'BuilderPromptGenerator'
language = builder_cfg.get('language', 'en')
if language == 'zh':
prompt_generator = 'ZhBuilderPromptGenerator'
# build agent
agent = BuilderChatbotAgent(
llm,
tool_cfg,
agent_type=AgentType.Messages,
additional_tool_list=additional_tool_list,
prompt_generator=prompt_generator,
uuid=uuid_str)
agent.set_available_tools([LOGO_TOOL_NAME])
return agent
class BuilderChatbotAgent(AgentExecutor):
def __init__(self, llm, tool_cfg, agent_type, additional_tool_list,
**kwargs):
super().__init__(
llm,
tool_cfg,
agent_type=agent_type,
additional_tool_list=additional_tool_list,
tool_retrieval=False,
**kwargs)
# used to reconstruct assistant message when builder config is updated
self._last_assistant_structured_response = {}
def stream_run(self,
task: str,
remote: bool = True,
print_info: bool = False,
append_files: list = [],
uuid_str: str = '') -> Dict:
# retrieve tools
tool_list = self.retrieve_tools(task)
self.prompt_generator.init_prompt(task, tool_list, [])
function_list = []
llm_result, exec_result = '', ''
idx = 0
while True:
idx += 1
llm_artifacts = self.prompt_generator.generate(
llm_result, exec_result)
if print_info:
logger.info(
uuid=uuid_str,
message=f'LLM inputs in round {idx}',
content={'llm_artifacts': llm_artifacts})
llm_result = ''
try:
parser_obj = AnswerParser()
for s in self.llm.stream_generate(llm_artifacts=llm_artifacts):
llm_result += s
answer, finish = parser_obj.parse_answer(llm_result)
if answer == '':
continue
result = {'llm_text': answer}
if finish:
result.update({'step': UPDATING_CONFIG_STEP})
yield result
if print_info:
logger.info(
uuid=uuid_str,
message=f'LLM output in round {idx}',
content={'llm_result': llm_result})
except Exception as e:
yield {'error': 'llm result is not valid'}
try:
re_pattern_config = re.compile(
pattern=r'Config: ([\s\S]+)\nRichConfig')
res = re_pattern_config.search(llm_result)
if res is None:
return
config = res.group(1).strip()
self._last_assistant_structured_response['config_str'] = config
rich_config = llm_result[llm_result.rfind('RichConfig:')
+ len('RichConfig:'):].strip()
try:
answer = json.loads(rich_config)
except Exception:
logger.error(uuid=uuid_str, error='parse RichConfig error')
return
self._last_assistant_structured_response[
'rich_config_dict'] = answer
builder_cfg = config_conversion(answer, uuid_str=uuid_str)
yield {'exec_result': {'result': builder_cfg}}
yield {'step': CONFIG_UPDATED_STEP}
except ValueError as e:
logger.error(uuid=uuid_str, error=str(e))
yield {'error content=[{}]'.format(llm_result)}
return
# record the llm_result result
_ = self.prompt_generator.generate(
{
'role': 'assistant',
'content': llm_result
}, '')
messages = self.prompt_generator.history
if 'logo_prompt' in answer and len(messages) > 4 and (
answer['logo_prompt'] not in messages[-3]['content']):
# draw logo
yield {'step': UPDATING_LOGO_STEP}
params = {
'user_requirement': answer['logo_prompt'],
'uuid_str': uuid_str
}
tool = self.tool_list[LOGO_TOOL_NAME]
try:
exec_result = tool(**params, remote=remote)
yield {'exec_result': exec_result}
yield {'step': LOGO_UPDATED_STEP}
return
except Exception as e:
exec_result = f'Action call error: {LOGO_TOOL_NAME}: {params}. \n Error message: {e}'
yield {'error': exec_result}
self.prompt_generator.reset()
return
else:
return
def update_config_to_history(self, config: Dict):
""" update builder config to message when user modify configuration
Args:
config info read from builder config file
"""
if len(
self.prompt_generator.history
) > 0 and self.prompt_generator.history[-1]['role'] == 'assistant':
answer = self._last_assistant_structured_response['answer_str']
simple_config = self._last_assistant_structured_response[
'config_str']
rich_config_dict = {
k: config[k]
for k in ['name', 'description', 'prompt_recommend']
}
rich_config_dict[
'logo_prompt'] = self._last_assistant_structured_response[
'rich_config_dict']['logo_prompt']
rich_config_dict['instructions'] = config['instruction'].split(';')
rich_config = json.dumps(rich_config_dict, ensure_ascii=False)
new_content = ASSISTANT_PROMPT.replace('<answer>', answer).replace(
'<config>', simple_config).replace('<rich_config>',
rich_config)
self.prompt_generator.history[-1]['content'] = new_content
def beauty_output(response: str, step_result: str):
flag_list = [
CONFIG_UPDATED_STEP, UPDATING_CONFIG_STEP, LOGO_UPDATED_STEP,
UPDATING_LOGO_STEP
]
if step_result in flag_list:
end_str = ''
for item in flag_list:
if response.endswith(item):
end_str = item
if end_str == '':
response = f'{response}\n{step_result}'
elif end_str in [CONFIG_UPDATED_STEP, LOGO_UPDATED_STEP]:
response = f'{response}\n{step_result}'
else:
response = response[:-len('\n' + end_str)]
response = f'{response}\n{step_result}'
return response
class AnswerParser(object):
def __init__(self):
self._history = ''
def parse_answer(self, llm_result: str):
finish = False
answer_prompt = ANSWER + ': '
if len(llm_result) >= len(answer_prompt):
start_pos = llm_result.find(answer_prompt)
end_pos = llm_result.find(f'\n{CONFIG}')
if start_pos >= 0:
if end_pos > start_pos:
result = llm_result[start_pos + len(answer_prompt):end_pos]
finish = True
else:
result = llm_result[start_pos + len(answer_prompt):]
else:
result = llm_result
else:
result = ''
new_result = result[len(self._history):]
self._history = result
return new_result, finish
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