import json from typing import Union, Dict, List, Sequence from knext.client.operator import OperatorClient from knext.common.runnable import Input, Output from knext.component.builder.base import SPGExtractor from knext.operator.spg_record import SPGRecord from knext import rest from knext.operator.op import PromptOp, ExtractOp # try: from nn4k.invoker.base import LLMInvoker, NNInvoker # noqa: F403 # except ImportError: # pass class LLMBasedExtractor(SPGExtractor): """A Process Component that transforming unstructured data into structured data. Examples: extract = UserDefinedExtractor( output_fields=["id", 'riskMark', 'useCert'] ).set_operator("DemoExtractOp") """ """All output column names after knowledge extraction processing.""" output_fields: List[str] """Knowledge extract operator of this component.""" llm: NNInvoker """PromptOps""" prompt_ops: List[PromptOp] @property def input_types(self) -> Input: return Dict[str, str] @property def output_types(self) -> Output: return Union[Dict[str, str], SPGRecord] @property def input_keys(self): return None @property def output_keys(self): return self.output_fields def invoke(self, input: Input) -> Sequence[Output]: raise NotImplementedError(f"{self.__class__.__name__} does not support being invoked separately.") def submit(self): raise NotImplementedError(f"{self.__class__.__name__} does not support being submitted separately.") def to_rest(self): """Transforms `LLMBasedExtractor` to REST model `ExtractNodeConfig`.""" params = {} params["model_config"] = json.dumps(self.llm._nn_config) api_client = OperatorClient()._rest_client.api_client params["prompt_config"] = json.dumps([api_client.sanitize_for_serialization(op.to_rest()) for op in self.prompt_ops]) from knext.operator.builtin.online_runner import _BuiltInOnlineExtractor extract_op = _BuiltInOnlineExtractor(params) print(extract_op.eval({"input": "甲状腺结节是指在甲状腺内的肿块,可随吞咽动作随甲状腺而上下移动,是临床常见的病症,可由多种病因引起。临床上有多种甲状腺疾病,如甲状腺退行性变、炎症、自身免疫以及新生物等都可以表现为结节。甲状腺结节可以单发,也可以多发,多发结节比单发结节的发病率高,但单发结节甲状腺癌的发生率较高。患者通常可以选择在普外科,甲状腺外科,内分泌科,头颈外科挂号就诊。有些患者可以触摸到自己颈部前方的结节。在大多情况下,甲状腺结节没有任何症状,甲状腺功能也是正常的。甲状腺结节进展为其它甲状腺疾病的概率只有1%。有些人会感觉到颈部疼痛、咽喉部异物感,或者存在压迫感。当甲状腺结节发生囊内自发性出血时,疼痛感会更加强烈。治疗方面,一般情况下可以用放射性碘治疗,复方碘口服液(Lugol液)等,或者服用抗甲状腺药物来抑制甲状腺激素的分泌。目前常用的抗甲状腺药物是硫脲类化合物,包括硫氧嘧啶类的丙基硫氧嘧啶(PTU)和甲基硫氧嘧啶(MTU)及咪唑类的甲硫咪唑和卡比马唑。"})) exit() config = rest.ExtractNodeConfig( output_fields=self.output_fields, operator_config=extract_op.to_rest() ) return rest.Node(**super().to_dict(), node_config=config) @classmethod def from_rest(cls, node: rest.Node): pass class UserDefinedExtractor(SPGExtractor): """A Process Component that transforming unstructured data into structured data. Examples: extract = UserDefinedExtractor( output_fields=["id", 'riskMark', 'useCert'] ).set_operator("DemoExtractOp") """ """All output column names after knowledge extraction processing.""" output_fields: List[str] """Knowledge extract operator of this component.""" extract_op: ExtractOp @property def input_types(self) -> Input: return Dict[str, str] @property def output_types(self) -> Output: return Union[Dict[str, str], SPGRecord] @property def input_keys(self): return None @property def output_keys(self): return self.output_fields def set_operator(self, op_name: str, params: Dict[str, str] = None): """Sets knowledge extract operator to this component.""" self.extract_op = ExtractOp.by_name(op_name)(params) return self def invoke(self, input: Input) -> Sequence[Output]: raise NotImplementedError(f"{self.__class__.__name__} does not support being invoked separately.") def submit(self): raise NotImplementedError(f"{self.__class__.__name__} does not support being submitted separately.") def to_rest(self): """Transforms `UserDefinedExtractor` to REST model `ExtractNodeConfig`.""" operator_config = self.extract_op.to_rest() config = rest.UserDefinedExtractNodeConfig( output_fields=self.output_fields, operator_config=operator_config ) return rest.Node(**super().to_dict(), node_config=config) @classmethod def from_rest(cls, node: rest.Node): return cls()