models.py

from typing import List, Optional, Literal
from pydantic import BaseModel, Field
from instructor import Field as InstructorField

class Location(BaseModel):
    name: str
    lat: float
    lon: float
    relevance: str

class ZoomRange(BaseModel):
    range: List[int] = Field(..., description="Start and end years")
    explanation: str

class StyleConfig(BaseModel):
    level: str
    options: List[str] = Field(..., description="Available style options")
    explanation: str

class TemporalZoom(BaseModel):
    level: Literal["century", "decade", "year"]
    range: List[int] = Field(..., description="Start and end years")
    explanation: str

class GeographicalZoom(BaseModel):
    level: Literal["continent", "country", "city"]
    locations: List[Location]
    explanation: str = ""

class StyleZoom(BaseModel):
    level: Literal["movement", "sub_movement", "specific"]
    options: List[str]
    explanation: str

class AxisImpact(BaseModel):
    geographical: Optional[str] = None
    temporal: Optional[str] = None
    style: Optional[str] = None

class TemporalConfig(BaseModel):
    component: Literal["st.slider"]
    current_zoom: TemporalZoom
    available_zooms: dict[Literal["in", "out"], ZoomRange]
    impacted_by: AxisImpact

class GeographicalConfig(BaseModel):
    component: Literal["st.map"]
    current_zoom: GeographicalZoom
    available_zooms: dict[Literal["in", "out"], dict[Literal["locations", "explanation"], str | List[Location]]]
    impacted_by: AxisImpact

class StyleConfig(BaseModel):
    component: Literal["st.multiselect", "st.selectbox"]
    current_zoom: StyleZoom

class Analysis(BaseModel):
    query_focus: str
    historical_context: str

class ArtResponse(BaseModel):
    """Art history exploration response with contextual zoom configurations"""
    analysis: Analysis
    axis_configurations: dict[
        Literal["temporal", "geographical", "style"],
        TemporalConfig | GeographicalConfig | StyleConfig
    ]

    @classmethod
    def from_llm(cls, query: str, current_zoom_states: dict) -> "ArtResponse":
        """Factory method to create response from LLM output"""
        # This would be implemented with instructor
        pass