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feat(knext): add kag_agent #319

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@mfz-ant mfz-ant commented Jul 5, 2024

add kag_agent

await asyncio.create_task(self.is_question_deps_ready(question))
rewrited_question = self.rewrite_question.forward(question)
info_dict = {
'status': f'重写问题',
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please add index tags to support Chinese and English selections.

rewrited_question = self.rewrite_question.forward(question)
info_dict = {
'status': f'重写问题',
'log_info': f'原问题: {question.question}. 重写后的问题: {rewrited_question}\n{str(question)}',
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same comments as above

async def solve_problem_impl(self, question: Question, **kwargs):
info_dict = {
'status': 'start solve_problem_impl',
'log_info': f'current question depth: {question.get_current_depth()}\n{str(question)}'
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please add index tags to support Chinese and English selections.

parts = _output_string.split("llm_output:") # 分割一次
result = parts[-1] if len(parts) > 1 else _output_string
# parse \n
parts_2 = result.split('依赖关系是:')
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add index tags to support Chinese and English selections.

def _process_dep(_input_list):
dep_dict = {}
for dep in _input_list:
res = dep.split("依赖")
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add index tags to support Chinese and English selections.

name='po_pairs')
s_grouped_df.rename(columns={"s": "entity"}, inplace=True)

# 使用'o'列进行分组,并将其他列转换为元组,然后聚合到list中
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add comments in English.

name = name.strip()
rep_name = re.sub(r'[^a-zA-Z0-9]', '_', name)
md5_hash = hashlib.md5()
# 更新 hash 对象,传入字符串的二进制形式
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add comments in English.

md5_hash = hashlib.md5()
# 更新 hash 对象,传入字符串的二进制形式
md5_hash.update(name.encode('utf-8'))
# 获取十六进制的 MD5 值
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add comments in English.

WORKSPACE = os.path.join(CWD, 'workspace')
if not os.path.exists(WORKSPACE):
os.makedirs(WORKSPACE)
DATA_DIR = '/Users/lisiyuan/Codes/FromLLMtoAgent/data/musique-main/data'
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your personal data dir?

return agent


def create_divide_and_conquer_agent_v2(musique_data, get_llm_fn, get_embed_fn, prompt_template_dir, intermediate_dir, debug_mode):
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what is the difference between create_divide_and_conquer_agent_v1 and create_divide_and_conquer_agent_v2?

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2 participants