You've already forked RekomenciBackend
gitgernit
67 lines
2.2 KiB
Python
67 lines
2.2 KiB
Python
from collections.abc import Sequence
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from decimal import Decimal
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from typing import cast
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from httpx import AsyncClient
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from template_project.application.common.data_structure import to_data_structure
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from template_project.application.resume.entity import ResumeId
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@to_data_structure
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class SuitableVacancyDs:
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vacancy_id: str
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from_salary: Decimal
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to_salary: Decimal
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key_skills: list[str]
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resume_similarity: float
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@to_data_structure
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class GenerateResumePredictionResponse:
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salary_from: Decimal
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salary_to: Decimal
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recommended_skills: list[str]
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class MlApiGateway:
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def __init__(self, client: AsyncClient) -> None:
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self._client = client
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async def generate_embedding(self, text: str) -> list[float]:
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response = await self._client.post("/get_embedding", json={"text": text}, timeout=100)
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return cast(list[float], response.json()["embedding"])
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async def generate_resume_prediction(
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self,
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resume_id: ResumeId,
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key_skills: list[str],
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suitable_vacancies: Sequence[SuitableVacancyDs],
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) -> GenerateResumePredictionResponse:
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response = await self._client.post(
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"/predict",
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json={
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"resume_id": str(resume_id),
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"key_skills": key_skills,
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"vacancies": [
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{
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"vacancy_id": str(suitable_vacancy.vacancy_id),
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"from_salary": str(suitable_vacancy.from_salary),
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"to_salary": str(suitable_vacancy.to_salary),
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"key_skills": suitable_vacancy.key_skills,
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"resume_similarity": suitable_vacancy.resume_similarity,
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}
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for suitable_vacancy in suitable_vacancies
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],
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},
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timeout=100,
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)
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response.raise_for_status()
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response_json = response.json()
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return GenerateResumePredictionResponse(
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salary_from=Decimal(str(response_json["salary_from"])),
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salary_to=Decimal(str(response_json["salary_to"])),
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recommended_skills=response_json["recommended_skills"],
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)
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