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import json
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from typing import Union, Dict, List, Sequence
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from knext.client.operator import OperatorClient
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from knext.common.runnable import Input, Output
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from knext.component.builder.base import SPGExtractor
from knext.operator.spg_record import SPGRecord
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from knext import rest
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from knext.operator.op import PromptOp, ExtractOp
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# try:
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from nn4k.invoker.base import LLMInvoker, NNInvoker # noqa: F403
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# except ImportError:
# pass
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class LLMBasedExtractor(SPGExtractor):
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"""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."""
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llm: NNInvoker
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"""PromptOps"""
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prompt_ops: List[PromptOp]
@property
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def input_types(self) -> Input:
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return Dict[str, str]
@property
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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]:
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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.")
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def to_rest(self):
"""Transforms `LLMBasedExtractor` to REST model `ExtractNodeConfig`."""
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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()
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config = rest.ExtractNodeConfig(
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output_fields=self.output_fields, operator_config=extract_op.to_rest()
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)
return rest.Node(**super().to_dict(), node_config=config)
@classmethod
def from_rest(cls, node: rest.Node):
pass
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class UserDefinedExtractor(SPGExtractor):
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"""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
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def input_types(self) -> Input:
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return Dict[str, str]
@property
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def output_types(self) -> Output:
return Union[Dict[str, str], SPGRecord]
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@property
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def input_keys(self):
return None
@property
def output_keys(self):
return self.output_fields
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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
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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.")
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def to_rest(self):
"""Transforms `UserDefinedExtractor` to REST model `ExtractNodeConfig`."""
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operator_config = self.extract_op.to_rest()
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config = rest.UserDefinedExtractNodeConfig(
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output_fields=self.output_fields, operator_config=operator_config
)
return rest.Node(**super().to_dict(), node_config=config)
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@classmethod
def from_rest(cls, node: rest.Node):
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return cls()