"""Pure domain models — no framework imports (no FastAPI, SQLAlchemy, httpx, etc.)."""

from dataclasses import dataclass, field
from datetime import datetime, timezone
from typing import Optional


@dataclass
class RuleDocument:
    """A rule from the knowledge base with metadata."""

    rule_id: str
    title: str
    section: str
    content: str
    source_file: str
    parent_rule: Optional[str] = None
    page_ref: Optional[str] = None

    def to_metadata(self) -> dict[str, str]:
        """Flat dict suitable for vector store metadata (no None values)."""
        return {
            "rule_id": self.rule_id,
            "title": self.title,
            "section": self.section,
            "parent_rule": self.parent_rule or "",
            "page_ref": self.page_ref or "",
            "source_file": self.source_file,
        }


@dataclass
class RuleSearchResult:
    """A rule returned from semantic search with a similarity score."""

    rule_id: str
    title: str
    content: str
    section: str
    similarity: float

    def __post_init__(self):
        if not (0.0 <= self.similarity <= 1.0):
            raise ValueError(
                f"similarity must be between 0.0 and 1.0, got {self.similarity}"
            )


@dataclass
class Conversation:
    """A chat session between a user and the bot."""

    id: str
    user_id: str
    channel_id: str
    created_at: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
    last_activity: datetime = field(default_factory=lambda: datetime.now(timezone.utc))


@dataclass
class ChatMessage:
    """A single message in a conversation."""

    id: str
    conversation_id: str
    content: str
    is_user: bool
    parent_id: Optional[str] = None
    created_at: datetime = field(default_factory=lambda: datetime.now(timezone.utc))


@dataclass
class LLMResponse:
    """Structured response from the LLM."""

    answer: str
    cited_rules: list[str] = field(default_factory=list)
    confidence: float = 0.5
    needs_human: bool = False


@dataclass
class ChatResult:
    """Final result returned by ChatService to inbound adapters."""

    response: str
    conversation_id: str
    message_id: str
    cited_rules: list[str]
    confidence: float
    needs_human: bool
    parent_message_id: Optional[str] = None