Поменяли на email и еще че то сделали, но на самом деле просто комичу, чтобы если вдруг что то сломается вернуиться обратно

database.py

@@ -1,6 +1,9 @@
 from typing import Optional
 from sqlalchemy.ext.asyncio import create_async_engine, async_sessionmaker
 from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column
+from sqlalchemy import Column, DateTime
+from sqlalchemy.sql import func
+from datetime import datetime
 
 engine = create_async_engine("sqlite+aiosqlite:///questions.db")
 new_session = async_sessionmaker(engine, expire_on_commit=False)
@@ -12,10 +15,11 @@ class QuestionOrm(Model):
     __tablename__ = "questions"
 
     id: Mapped[int] = mapped_column(primary_key=True)
-    id_user: Mapped[int]
+    email_user: Mapped[str]
     type_question: Mapped[bool]
     question: Mapped[str]
     answer: Mapped[Optional[str]]
+    question_time: Mapped[datetime] = mapped_column(DateTime, server_default=func.now())
 
 async def create_tables():
     async with engine.begin() as conn:

model.py

@@ -8,11 +8,11 @@ from keras.src.utils import pad_sequences
 model = tf.keras.models.load_model('.//neural_network/models/model/best_model_lstm_negative.keras')
 
 # Загрузка токенизатора
-with open('neural_network/models/tokenization/tokenizer_lstm_lstm_negative.pickle', 'rb') as handle:
+with open('.//neural_network/tokenization/tokenizer_negative.pickle', 'rb') as handle:
     tokenizer = pickle.load(handle)
 
 # Загрузка названий классов
-with open('neural_network/models/classification/class_names_lstm_negative.txt', 'r', encoding='utf-8') as file:
+with open('.//neural_network/classification/class_names_negative.txt', 'r', encoding='utf-8') as file:
     class_names = [line.strip() for line in file.readlines()]
 
 def preprocess_text(text: str):

repository.py

@@ -1,10 +1,11 @@
-from sqlalchemy import select
+from sqlalchemy import select, delete
+from sqlalchemy.orm import joinedload
+from datetime import datetime
 
 from database import new_session, QuestionOrm
 from schemas import SQuestionAdd, SQuestion
 from model import predict_answer
 
-
 class QuestionRepository:
     @classmethod
     async def add_one(cls, data: SQuestionAdd) -> int:
@@ -15,8 +16,19 @@ class QuestionRepository:
             answer = predict_answer(question_dict["question"])
 
             question_dict["answer"] = answer
+            question_dict["question_time"] = datetime.now()
             question = QuestionOrm(**question_dict)
             session.add(question)
+
+            # Проверка количества записей для email_user
+            query = select(QuestionOrm).where(QuestionOrm.email_user == data.email_user)
+            result = await session.execute(query)
+            user_questions = result.scalars().all()
+            if len(user_questions) > 10:
+                # Удаление самой старой записи
+                oldest_question = min(user_questions, key=lambda q: q.question_time)
+                await session.delete(oldest_question)
+
             await session.flush()
             await session.commit()
             return question.id

schemas.py

@@ -1,14 +1,16 @@
 from typing import Optional
 from pydantic import BaseModel, ConfigDict
+from datetime import datetime
 
 class SQuestionAdd(BaseModel):
-    id_user: int
+    email_user: str
     type_question: bool
     question: str
 
 class SQuestion(SQuestionAdd):
     id: int
     answer: Optional[str] = None
+    question_time: datetime
 
     model_config = ConfigDict(from_attributes=True)