add pipline

src/template_project/application/common/entity.py

@@ -1,7 +1,7 @@
 from collections.abc import Hashable
-from dataclasses import dataclass, replace
+from dataclasses import dataclass
 from datetime import datetime
-from typing import Self, cast, dataclass_transform, override
+from typing import cast, dataclass_transform, override
 from uuid import UUID
 
 from template_project.application.common.errors import EntityAlreadyDeletedError
@@ -22,9 +22,6 @@ class Entity[EntityId: UUID](Hashable):
         if self.deleted_at is not None:
             raise EntityAlreadyDeletedError(entity_name=self.__class__.__name__)
 
-    def __copy__(self) -> Self:
-        return replace(self)
-
     @override
     def __eq__(self, other: object) -> bool:
         if isinstance(other, Entity):

src/template_project/application/resume/entity.py

@@ -80,6 +80,23 @@ class ResumePrediction(Entity[ResumePredictionId]):
     to_salary: Decimal
     recommended_skills: list[str]
 
+    @classmethod
+    def factory(
+        cls,
+        resume_id: ResumeId,
+        from_salary: Decimal,
+        to_salary: Decimal,
+        recommended_skills: list[str],
+    ) -> Self:
+        return cls(
+            id=ResumePredictionId(uuid7()),
+            created_at=datetime.now(tz=UTC),
+            resume_id=resume_id,
+            from_salary=from_salary,
+            to_salary=to_salary,
+            recommended_skills=recommended_skills,
+        )
+
 
 @to_entity
 class ResumeExperience(Entity[ResumeExperienceId]):

src/template_project/application/resume/interactors/resume_embedding.py

@@ -3,20 +3,21 @@ from collections.abc import Callable
 from Levenshtein import ratio
 
 from template_project.application.common.unit_of_work import UnitOfWork
-from template_project.application.resume.entity import Resume, ResumeEmbedding, ResumePrediction
+from template_project.application.resume.entity import Resume, ResumeEmbedding
+from template_project.application.resume.resume_prediction_generator import ResumePredictionGenerator
 from template_project.application.resume.vector_generator import ResumeEmbeddingVectorGenerator
 from template_project.application.vacancy.data_gateway import VacancyDataGateway
-from template_project.application.vacancy.entity import Vacancy
+from template_project.application.vacancy.data_structure import SuitableVacancy
 
 
 def suitable_vacancies_key(
     resume: Resume,
-) -> Callable[[Vacancy], bool]:
-    def wrapper(vacancy: Vacancy) -> bool:
+) -> Callable[[SuitableVacancy], tuple[bool, bool]]:
+    def wrapper(suitable_vacancy: SuitableVacancy) -> tuple[bool, bool]:
         count_skills = 0
         ratio_skill_sum = 0.0
         for resum_key_skill in resume.key_skills:
-            for suitable_resume_key_skill in vacancy.key_skills:
+            for suitable_resume_key_skill in suitable_vacancy.vacancy.key_skills:
                 ratio_skill = ratio(resum_key_skill, suitable_resume_key_skill)
                 if ratio_skill != 0:
                     count_skills += 1
@@ -27,26 +28,28 @@ def suitable_vacancies_key(
         except ZeroDivisionError:
             matching_skills = 0
 
-        return resume.experience_type == vacancy.experience_type and matching_skills >= 50
+        return resume.experience_type == suitable_vacancy.vacancy.experience_type, matching_skills >= 50
 
     return wrapper
 
 
-class ResumeEmbeddingPipeline:
+class ResumeEmbeddingInteractor:
     def __init__(
         self,
         unit_of_work: UnitOfWork,
         vacancy_data_gateway: VacancyDataGateway,
         vector_generator: ResumeEmbeddingVectorGenerator,
+        resume_prediction_generator: ResumePredictionGenerator,
     ) -> None:
         self.unit_of_work = unit_of_work
-        self.vacancy_data_gateway = vacancy_data_gateway
         self.vector_generator = vector_generator
+        self.vacancy_data_gateway = vacancy_data_gateway
+        self.resume_prediction_generator = resume_prediction_generator
 
     async def run(
         self,
         resume: Resume,
-    ) -> ResumePrediction:
+    ) -> None:
         vector = await self.vector_generator.generate(
             position=resume.position,
             about_me=resume.about_me,
@@ -62,13 +65,12 @@ class ResumeEmbeddingPipeline:
         suitable_vacancies_filtered = sorted(
             suitable_vacancies,
             key=suitable_vacancies_key(resume),
+        )[:50]
+
+        resume_prediction = await self.resume_prediction_generator.generate(
+            resume=resume,
+            suituble_vacancies=suitable_vacancies_filtered,
         )
 
-        suitable_vacancies = suitable_vacancies_filtered[:50]
-
-        # TODO: тут надо сделать отправку в ИИ
-
-        await self.unit_of_work.add(resume_embedding)
+        await self.unit_of_work.add(resume_embedding, resume_prediction)
         await self.unit_of_work.commit()
-
-        raise NotImplementedError

src/template_project/application/resume/resume_prediction.py

@@ -1 +0,0 @@
-# class ResumePredicition

src/template_project/application/resume/resume_prediction_generator.py

@@ -0,0 +1,16 @@
+from abc import abstractmethod
+from collections.abc import Sequence
+from typing import Protocol
+
+from template_project.application.resume.entity import Resume, ResumePrediction
+from template_project.application.vacancy.data_structure import SuitableVacancy
+
+
+class ResumePredictionGenerator(Protocol):
+    @abstractmethod
+    async def generate(
+        self,
+        resume: Resume,
+        suituble_vacancies: Sequence[SuitableVacancy],
+    ) -> ResumePrediction:
+        raise NotImplementedError

src/template_project/application/vacancy/data_gateway.py

@@ -2,10 +2,10 @@ from abc import abstractmethod
 from collections.abc import Sequence
 from typing import Protocol
 
-from template_project.application.vacancy.entity import Vacancy
+from template_project.application.vacancy.data_structure import SuitableVacancy
 
 
 class VacancyDataGateway(Protocol):
     @abstractmethod
-    async def get_suitable(self, vector: list[float]) -> Sequence[Vacancy]:
+    async def get_suitable(self, vector: list[float]) -> Sequence[SuitableVacancy]:
         raise NotImplementedError

src/template_project/application/vacancy/data_structure.py

@@ -0,0 +1,8 @@
+from template_project.application.common.data_structure import to_data_structure
+from template_project.application.vacancy.entity import Vacancy
+
+
+@to_data_structure
+class SuitableVacancy:
+    vacancy: Vacancy
+    resume_similarity: float