leocrm/app/plugins/builtins/unified_search/providers/conversation_provider.py

"""Conversation search provider — queries comm_conversations table."""

from __future__ import annotations

import logging
import uuid
from typing import Any

from sqlalchemy import text
from sqlalchemy.ext.asyncio import AsyncSession

from app.plugins.builtins.unified_search.base_provider import BaseSearchProvider

logger = logging.getLogger(__name__)


class ConversationSearchProvider(BaseSearchProvider):
    """Search provider for CommConversation entities."""

    entity_type = "conversation"

    async def _search_fts_filtered(
        self,
        db: AsyncSession,
        tsquery: str,
        tenant_id: uuid.UUID,
        limit: int,
        visible_ids: set[uuid.UUID] | None,
    ) -> list[dict[str, Any]]:
        """Full-text search on comm_conversations.title and last_msg_preview."""
        if visible_ids is not None:
            sql = text(
                """
                SELECT c.*, ts_rank(
                    to_tsvector('pg_catalog.german',
                        coalesce(c.title, '') || ' ' || coalesce(c.last_msg_preview, '')
                    ),
                    to_tsquery('pg_catalog.german', :q)
                ) AS rank
                FROM comm_conversations c
                WHERE c.tenant_id = :tid
                  AND c.deleted_at IS NULL
                  AND to_tsvector('pg_catalog.german',
                      coalesce(c.title, '') || ' ' || coalesce(c.last_msg_preview, '')
                  ) @@ to_tsquery('pg_catalog.german', :q)
                  AND c.id = ANY(:visible_ids)
                ORDER BY rank DESC
                LIMIT :lim
                """
            )
            result = await db.execute(
                sql,
                {
                    "q": tsquery,
                    "tid": tenant_id,
                    "lim": limit,
                    "visible_ids": list(visible_ids),
                },
            )
        else:
            sql = text(
                """
                SELECT c.*, ts_rank(
                    to_tsvector('pg_catalog.german',
                        coalesce(c.title, '') || ' ' || coalesce(c.last_msg_preview, '')
                    ),
                    to_tsquery('pg_catalog.german', :q)
                ) AS rank
                FROM comm_conversations c
                WHERE c.tenant_id = :tid
                  AND c.deleted_at IS NULL
                  AND to_tsvector('pg_catalog.german',
                      coalesce(c.title, '') || ' ' || coalesce(c.last_msg_preview, '')
                  ) @@ to_tsquery('pg_catalog.german', :q)
                ORDER BY rank DESC
                LIMIT :lim
                """
            )
            result = await db.execute(
                sql,
                {"q": tsquery, "tid": tenant_id, "lim": limit},
            )
        rows = result.mappings().all()
        return [dict(r) for r in rows]

    async def _search_vector_filtered(
        self,
        db: AsyncSession,
        embedding: list[float],
        tenant_id: uuid.UUID,
        limit: int,
        visible_ids: set[uuid.UUID] | None,
    ) -> list[dict[str, Any]]:
        """Semantic search — comm_conversations table has no embedding column yet."""
        return []

    async def get_embedding_text(
        self, db: AsyncSession, entity_id: uuid.UUID, tenant_id: uuid.UUID
    ) -> str:
        """Get text for embedding generation."""
        sql = text(
            """
            SELECT title, last_msg_preview
            FROM comm_conversations
            WHERE id = :eid AND tenant_id = :tid
            """
        )
        result = await db.execute(sql, {"eid": entity_id, "tid": tenant_id})
        row = result.mappings().first()
        if not row:
            return ""
        parts = [
            row.get("title", ""),
            row.get("last_msg_preview", ""),
        ]
        return " ".join(str(p) for p in parts if p)

    def to_search_result(self, entity: object) -> dict[str, Any]:
        """Convert conversation to search result dict."""
        if isinstance(entity, dict):
            title = entity.get("title", "") or ""
            preview = entity.get("last_msg_preview", "") or ""
            entity_id = str(entity.get("id", ""))
            is_direct = entity.get("is_direct", False)
        else:
            title = getattr(entity, "title", "") or ""
            preview = getattr(entity, "last_msg_preview", "") or ""
            entity_id = str(getattr(entity, "id", ""))
            is_direct = getattr(entity, "is_direct", False)
        return {
            "entity_type": self.entity_type,
            "entity_id": entity_id,
            "title": title,
            "snippet": preview[:200],
            "score": 0.0,
            "data": {"is_direct": is_direct},
        }