98 lines
3.0 KiB
Python
98 lines
3.0 KiB
Python
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from pydantic import BaseModel
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from loguru import logger
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from .general_schema import *
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class Message(BaseModel):
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chat_index: str = None
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role_name: str
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role_type: str
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role_prompt: str = None
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input_query: str = None
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origin_query: str = None
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# 模型最终返回
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role_content: str = None
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role_contents: List[str] = []
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step_content: str = None
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step_contents: List[str] = []
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chain_content: str = None
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chain_contents: List[str] = []
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# 模型结果解析
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plans: List[str] = None
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code_content: str = None
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code_filename: str = None
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tool_params: str = None
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tool_name: str = None
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parsed_output: dict = {}
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spec_parsed_output: dict = {}
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parsed_output_list: List[Dict] = []
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# 执行结果
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action_status: str = ActionStatus.DEFAUILT
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agent_index: int = None
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code_answer: str = None
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tool_answer: str = None
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observation: str = None
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figures: Dict[str, str] = {}
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# 辅助信息
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tools: List[BaseTool] = []
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task: Task = None
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db_docs: List['Doc'] = []
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code_docs: List['CodeDoc'] = []
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search_docs: List['Doc'] = []
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agents: List = []
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# 执行输入
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phase_name: str = None
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chain_name: str = None
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do_search: bool = False
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doc_engine_name: str = None
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code_engine_name: str = None
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cb_search_type: str = None
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search_engine_name: str = None
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top_k: int = 3
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score_threshold: float = 1.0
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do_doc_retrieval: bool = False
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do_code_retrieval: bool = False
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do_tool_retrieval: bool = False
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history_node_list: List[str] = []
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def to_tuple_message(self, return_all: bool = True, content_key="role_content"):
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role_content = self.to_str_content(False, content_key)
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if return_all:
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return (self.role_name, role_content)
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else:
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return (role_content)
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def to_dict_message(self, return_all: bool = True, content_key="role_content"):
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role_content = self.to_str_content(False, content_key)
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if return_all:
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return {"role": self.role_name, "content": role_content}
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else:
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return vars(self)
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def to_str_content(self, return_all: bool = True, content_key="role_content"):
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if content_key == "role_content":
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role_content = self.role_content or self.input_query
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elif content_key == "step_content":
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role_content = self.step_content or self.role_content or self.input_query
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else:
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role_content = self.role_content or self.input_query
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if return_all:
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return f"{self.role_name}: {role_content}"
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else:
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return role_content
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def is_system_role(self,):
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return self.role_type == "system"
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def __str__(self) -> str:
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# key_str = '\n'.join([k for k, v in vars(self).items()])
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# logger.debug(f"{key_str}")
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return "\n".join([": ".join([k, str(v)]) for k, v in vars(self).items()])
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