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41 lines
1.1 KiB
Python
41 lines
1.1 KiB
Python
from typing import Any, Dict, List, Optional
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from pydantic import BaseModel
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class Answer(BaseModel):
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answer: Optional[str]
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question: Optional[str]
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score: Optional[float] = None
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probability: Optional[float] = None
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context: Optional[str]
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offset_start: int
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offset_end: int
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offset_start_in_doc: Optional[int]
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offset_end_in_doc: Optional[int]
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document_id: Optional[str] = None
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meta: Optional[Dict[str, str]]
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class AnswersToIndividualQuestion(BaseModel):
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question: str
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answers: List[Optional[Answer]]
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@staticmethod
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def to_elastic_response_dsl(data: Dict[str, Any]):
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result_dsl = {'hits': {'hits': [], 'total': {'value': len(data["answers"])}}}
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for answer in data["answers"]:
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record = {"_source": {k: v for k, v in dict(answer).items()}}
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record["_id"] = record["_source"].pop("document_id", None)
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record["_score"] = record["_source"].pop("score", None)
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result_dsl['hits']['hits'].append(record)
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return result_dsl
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class Answers(BaseModel):
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results: List[AnswersToIndividualQuestion]
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