from __future__ import annotations

from datetime import datetime
from typing import Literal
from uuid import UUID

from pydantic import BaseModel, Field

from app.schemas.operations import VectorSelectionBBox


class AssistantChatMessage(BaseModel):
    role: Literal["user", "assistant"]
    content: str = Field(min_length=1, max_length=4_000)


class AssistantQueryRequest(BaseModel):
    question: str = Field(min_length=2, max_length=2_000)
    model: str | None = Field(default=None, max_length=255)
    bbox: VectorSelectionBBox | None = None
    area_id: UUID | None = None
    history: list[AssistantChatMessage] = Field(default_factory=list, max_length=8)


class AssistantModelRead(BaseModel):
    name: str
    size_bytes: int | None = None
    parameter_size: str | None = None
    quantization_level: str | None = None
    capabilities: list[str] = Field(default_factory=list)


class AssistantModelList(BaseModel):
    items: list[AssistantModelRead]
    total: int
    default_model: str | None = None


class AssistantStatus(BaseModel):
    enabled: bool
    reachable: bool
    status: str
    base_url: str
    default_model: str | None = None
    model_count: int = 0
    limitation_message: str


class AssistantContextMetric(BaseModel):
    theme: str
    label: str
    value: float
    unit: str
    source: str
    dataset_id: UUID
    observed_at: datetime | None = None
    is_estimate: bool = False


class AssistantTemporalSeries(BaseModel):
    temporal_series_key: str
    label: str
    source: str
    first_year: int
    last_year: int
    observation_count: int


class AssistantQueryResponse(BaseModel):
    answer: str
    model: str
    scope_label: str
    context_metrics: list[AssistantContextMetric]
    temporal_series: list[AssistantTemporalSeries]
    source_dataset_ids: list[UUID]
    warnings: list[str]
    generated_at: datetime