from __future__ import annotations

from typing import Literal

from pydantic import BaseModel, Field


class EmailData(BaseModel):
    subject: str
    body: str


class ClassifyRequest(BaseModel):
    email_data: EmailData
    provider: Literal["openai", "anthropic"] | None = None
    model: str | None = None
    base_url: str | None = None
    api_key: str | None = Field(default=None, exclude=True)
    temperature: float | None = None
    from_address: str | None = None
    received_at: str | None = None


class ClassificationDetails(BaseModel):
    summary: str | None = None
    suggested_title: str | None = None
    suggested_notes: str | None = None
    deadline: str | None = None
    people: list[str] = Field(default_factory=list)
    organizations: list[str] = Field(default_factory=list)
    attachments_referenced: list[str] = Field(default_factory=list)
    next_steps: list[str] = Field(default_factory=list)
    key_points: list[str] = Field(default_factory=list)
    source_signals: list[str] = Field(default_factory=list)
    dedupe_key: str | None = None


class DedupeResult(BaseModel):
    status: Literal["new", "duplicate", "updated"]
    seen_count: int = 1
    matched_on: Literal["none", "subject", "fingerprint"] = "none"
    subject_key: str
    fingerprint: str


class ClassificationResult(BaseModel):
    needs_action: bool
    category: Literal["action_required", "question", "fyi", "newsletter", "promotional", "automated", "alert", "uncategorized"]
    priority: Literal["high", "medium", "low"]
    task_description: str | None = None
    reasoning: str
    confidence: float
    details: ClassificationDetails | None = None
    dedupe: DedupeResult | None = None