You've already forked RekomenciBackend
ivankirpichnikov
122 lines
4.1 KiB
Python
122 lines
4.1 KiB
Python
from decimal import Decimal
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from dishka import FromDishka
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from dishka.integrations.fastapi import DishkaRoute
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from fastapi import APIRouter
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from pydantic import BaseModel, Field
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from template_project.application.resume.entity import ResumeId
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from template_project.ml.interactors.predict_salary import (
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PredictSalaryInteractor,
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PredictSalaryRequest,
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VacancyInput,
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)
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router = APIRouter(route_class=DishkaRoute, tags=["Prediction"])
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class VacancyInputModel(BaseModel):
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vacancy_id: str = Field(description="Vacancy ID", examples=["vacancy_123"])
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from_salary: Decimal = Field(description="Minimum salary", examples=[Decimal(100000)])
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to_salary: Decimal = Field(description="Maximum salary", examples=[Decimal(150000)])
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key_skills: list[str] = Field(description="List of key skills", examples=[["Python", "FastAPI", "PostgreSQL"]])
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resume_similarity: float = Field(
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ge=0.0, le=1.0, description="Resume similarity score (0.0 to 1.0)", examples=[0.85]
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)
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model_config = {
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"json_schema_extra": {
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"example": {
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"vacancy_id": "vacancy_123",
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"from_salary": "100000",
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"to_salary": "150000",
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"key_skills": ["Python", "FastAPI", "PostgreSQL"],
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"resume_similarity": 0.85,
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}
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}
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}
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class PredictSalaryRequestModel(BaseModel):
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resume_id: ResumeId = Field(description="Resume ID", examples=["01234567-89ab-cdef-0123-456789abcdef"])
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key_skills: list[str] = Field(
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min_length=1, description="List of key skills from resume", examples=[["Python", "FastAPI", "PostgreSQL"]]
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)
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vacancies: list[VacancyInputModel] = Field(
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min_length=1, description="List of relevant vacancies", examples=[[]]
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)
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model_config = {
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"json_schema_extra": {
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"example": {
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"resume_id": "01234567-89ab-cdef-0123-456789abcdef",
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"key_skills": ["Python", "FastAPI", "PostgreSQL"],
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"vacancies": [
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{
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"vacancy_id": "vacancy_123",
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"from_salary": "100000",
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"to_salary": "150000",
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"key_skills": ["Python", "FastAPI", "PostgreSQL", "Docker"],
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"resume_similarity": 0.85,
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}
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],
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}
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}
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}
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class PredictSalaryResponseModel(BaseModel):
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salary_from: Decimal = Field(description="Minimum predicted salary", examples=[Decimal(100000)])
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salary_to: Decimal = Field(description="Maximum predicted salary", examples=[Decimal(150000)])
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recommended_skills: list[str] = Field(
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description="Top 3 recommended skills", examples=[["Kubernetes", "Redis", "Docker"]]
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)
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model_config = {
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"json_schema_extra": {
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"example": {
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"salary_from": "100000",
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"salary_to": "150000",
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"recommended_skills": ["Kubernetes", "Redis", "Docker"],
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}
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}
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}
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@router.post(
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"/predict_salary",
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summary="Predict salary",
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description="Predict salary range and recommend skills based on resume and relevant vacancies",
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responses={
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200: {"description": "Salary prediction generated successfully", "model": PredictSalaryResponseModel},
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},
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)
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async def predict_salary(
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request: PredictSalaryRequestModel,
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interactor: FromDishka[PredictSalaryInteractor],
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) -> PredictSalaryResponseModel:
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vacancy_inputs = [
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VacancyInput(
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vacancy_id=vacancy.vacancy_id,
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from_salary=vacancy.from_salary,
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to_salary=vacancy.to_salary,
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key_skills=vacancy.key_skills,
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resume_similarity=vacancy.resume_similarity,
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)
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for vacancy in request.vacancies
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]
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predict_request = PredictSalaryRequest(
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resume_id=request.resume_id,
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key_skills=request.key_skills,
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vacancies=vacancy_inputs,
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)
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response = await interactor.execute(predict_request)
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return PredictSalaryResponseModel(
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salary_from=response.salary_from,
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salary_to=response.salary_to,
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recommended_skills=response.recommended_skills,
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)
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