feat: house price prediction model integration

backend/app/dtos/house/house_create_request.py

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+from pydantic import BaseModel, Field
+
+
+class HouseCreateRequest(BaseModel):
+    address: str = Field(
+        ...,
+        min_length=1,
+        max_length=255,
+        description="House address",
+        examples=["123 Main St"],
+    )
+    city: str = Field(
+        ..., description="City where the house is located", examples=["Springfield"]
+    )
+    country: str = Field(
+        ..., description="Country where the house is located", examples=["USA"]
+    )
+    price: float = Field(..., description="Price of the house", examples=[250000.00])
+    description: str = Field(
+        ...,
+        description="Description of the house",
+        examples=["A beautiful 3-bedroom house"],
+    )
+    square_feet: float = Field(
+        ...,
+        description="Square footage of the house",
+        examples=[1500.00],
+    )
+    bedrooms: int = Field(
+        ..., description="Number of bedrooms in the house", examples=[3]
+    )
+    bathrooms: float = Field(
+        ..., description="Number of bathrooms in the house", examples=[2.5]
+    )

backend/app/dtos/house/house_create_response.py

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+from pydantic import BaseModel
+
+
+class HouseCreateResponse(BaseModel):
+    id: str

backend/app/dtos/house/house_features.py

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+from pydantic import BaseModel, Field
+from typing import Optional
+
+class HouseFeatures(BaseModel):
+    square_feet: float = Field(..., description="Total square feet of the house")
+    bedrooms: int = Field(..., description="Number of bedrooms")
+    bathrooms: float = Field(..., description="Number of bathrooms")
+    number_of_floors: Optional[int] = Field(default=None, description="Number of floors")

backend/app/dtos/house/house_predict_request.py

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+from pydantic import BaseModel
+
+
+class HousePricePredictionRequest(BaseModel):
+    square_feet: float
+    bedrooms: int
+    bathrooms: float

backend/app/dtos/house/house_predict_response.py

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+from pydantic import BaseModel
+
+
+class HousePricePredictionResponse(BaseModel):
+    predicted_price: float

backend/app/dtos/house/house_response.py

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+from pydantic import BaseModel
+
+
+class HouseResponse(BaseModel):
+    id: str
+    description: str
+    address: str
+    city: str
+    country: str
+    price: float

backend/app/dtos/house/houses_list_response.py

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+from pydantic import BaseModel
+
+from backend.app.dtos.house.house_response import HouseResponse
+
+class HousesListResponse(BaseModel):
+    houses: list[HouseResponse]

backend/app/dtos/owner/owner_detail_response.py

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+from pydantic import BaseModel
+
+
+class OwnerDetailResponse(BaseModel):
+    id: str
+    user_id: str
+    email: str

backend/app/dtos/owner/owner_list_response.py

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+from pydantic import BaseModel
+
+
+class OwnerResponse(BaseModel):
+    id: str
+    user_id: str
+
+
+class OwnerListResponse(BaseModel):
+    owners: list[OwnerResponse]

backend/app/dtos/user/user_list_response.py

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+from pydantic import BaseModel
+
+from backend.app.dtos.user.user_response import UserResponse
+
+class UserListResponse(BaseModel):
+    users: list[UserResponse]

backend/app/dtos/user/user_response.py

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+from pydantic import BaseModel
+
+
+class UserResponse(BaseModel):
+    id: str
+    email: str