feat(): prediction pipeline

src/template_project/adapters/data_gateways/resume.py

@@ -26,7 +26,6 @@ from template_project.application.resume.entity import (
     ResumePrediction,
     ResumeProject,
 )
-from template_project.application.resume.errors import ResumeNotFoundError
 from template_project.application.user.entity import UserId
 
 
@@ -35,12 +34,8 @@ class DefaultResumeDataGateway(ResumeDataGateway):
         self._session = session
 
     @override
-    async def load(self, resume_id: ResumeId) -> Resume:
-        resume = await self._session.get(Resume, resume_id)
-        if resume is None:
-            raise ResumeNotFoundError(resume_id=resume_id)
-
-        return resume
+    async def load_by_resume_id(self, resume_id: ResumeId) -> Resume | None:
+        return await self._session.get(Resume, resume_id)
 
     @override
     async def list_by_user_id(self, user_id: UserId, limit: int, offset: int) -> Sequence[Resume]:
@@ -64,11 +59,15 @@ class DefaultResumeDataGateway(ResumeDataGateway):
     async def get_history(self, resume_id: ResumeId) -> Sequence[Resume]:
         # TODO: N+1
         history: list[Resume] = []
-        current_resume = await self.load(resume_id)
+        current_resume = await self.load_by_resume_id(resume_id)
+        if current_resume is None:
+            return history
         history.append(current_resume)
 
         while current_resume.down_resume_id is not None:
-            current_resume = await self.load(current_resume.down_resume_id)
+            current_resume = await self.load_by_resume_id(current_resume.down_resume_id)
+            if current_resume is None:
+                break
             history.append(current_resume)
 
         return history

src/template_project/adapters/data_gateways/tables.py

@@ -70,6 +70,34 @@ class StringArrayType(TypeDecorator[list[str]]):
         return []
 
 
+class ExperienceTypeType(TypeDecorator[ExperienceType]):
+    impl: Any = String
+    cache_ok: bool | None = True
+
+    @override
+    def process_bind_param(self, value: Any, dialect: Any) -> Any:
+        if value is None:
+            return None
+        if isinstance(value, ExperienceType):
+            return value.value
+        if isinstance(value, str):
+            return value
+        return None
+
+    @override
+    def process_result_value(self, value: Any, dialect: Any) -> ExperienceType:
+        if value is None:
+            raise ValueError("experience_type cannot be None")
+        if isinstance(value, ExperienceType):
+            return value
+        if isinstance(value, str):
+            try:
+                return ExperienceType(value)
+            except ValueError:
+                raise ValueError(f"Invalid experience_type value: {value}")
+        raise ValueError(f"Cannot convert {type(value)} to ExperienceType")
+
+
 user_table: Final = Table(
     "users",
     meta_data,
@@ -138,7 +166,7 @@ resume_table: Final = Table(
     Column("location", String, nullable=False),
     Column("about_me", String, nullable=False),
     Column("key_skills", StringArrayType(), nullable=False, server_default=text("'[]'::jsonb")),
-    Column("experience_type", String, nullable=False),
+    Column("experience_type", ExperienceTypeType(), nullable=False),
     Column("down_resume_id", UUID, ForeignKey("resume.id", ondelete="CASCADE"), nullable=True, default=None),
     Column("up_resume_id", UUID, ForeignKey("resume.id", ondelete="CASCADE"), nullable=True, default=None),
 )
@@ -241,6 +269,7 @@ mapper_registry.map_imperatively(
     resume_table,
     properties={
         "key_skills": resume_table.c.key_skills,
+        "experience_type": resume_table.c.experience_type,
     },
 )
 mapper_registry.map_imperatively(ResumeEmbedding, resume_embedding_table)

src/template_project/adapters/data_gateways/vacancy.py

@@ -20,6 +20,8 @@ class DefaultVacancyDataGateway(VacancyDataGateway):
             select(Vacancy, label("resume_similarity", vacancy_embedding_table.c.vector.cosine_distance(vector)))
             .join(VacancyEmbedding, vacancy_embedding_table.c.vacancy_id == vacancy_table.c.id)
             .where(vacancy_embedding_table.c.vector.cosine_distance(vector) > 0.5)
+            .order_by(vacancy_embedding_table.c.vector.cosine_distance(vector).asc())
+            .limit(100)
         )
         result = await self._session.execute(statement)
         return [