"""richer full-text search document (title + keywords + search terms + description)

Revision ID: 0032_search_document
Revises: 0031_title_fts
Create Date: 2026-06-30

Broadens the feed's full-text search from the title alone to a weighted search document, so the
local search behaves more like YouTube's — finding videos by the uploader's own keywords or by
the search query that surfaced them, not only by words in the title:

- `keywords`      — the creator's snippet.tags (already fetched with the snippet we request, so
                    zero extra quota), stored space-joined.
- `search_terms`  — distinct live-search queries that surfaced the video (across all users),
                    appended by the search route. Folds YouTube's relevance judgement into local
                    search: a video YT returned for a query becomes findable by it locally.

These plus a truncated description feed a STORED generated `search_vector` column, weighted
title (A) > keywords+search_terms (B) > description (C) so ts_rank ranks title hits highest. A
plain GIN index on the column guarantees the planner uses it (no expression/param matching). The
title-only expression index from 0031 is dropped (superseded). Existing rows get title +
description indexed immediately; keywords/search_terms fill in as videos are (re-)enriched and
searched. Uses the `unaccent_simple` config from 0031 (accent-insensitive).
"""
from typing import Sequence, Union

import sqlalchemy as sa
from alembic import op

revision: str = "0032_search_document"
down_revision: Union[str, None] = "0031_title_fts"
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None

_SEARCH_VECTOR_EXPR = (
    "setweight(to_tsvector('public.unaccent_simple', coalesce(title, '')), 'A') || "
    "setweight(to_tsvector('public.unaccent_simple', coalesce(keywords, '') || ' ' || "
    "coalesce(search_terms, '')), 'B') || "
    "setweight(to_tsvector('public.unaccent_simple', left(coalesce(description, ''), 1000)), 'C')"
)


def upgrade() -> None:
    op.add_column("videos", sa.Column("keywords", sa.Text(), nullable=True))
    op.add_column("videos", sa.Column("search_terms", sa.Text(), nullable=True))
    # Replace the title-only index with a generated weighted search_vector + its GIN index.
    op.execute("DROP INDEX IF EXISTS ix_videos_title_fts")
    op.execute(
        f"ALTER TABLE videos ADD COLUMN search_vector tsvector "
        f"GENERATED ALWAYS AS ({_SEARCH_VECTOR_EXPR}) STORED"
    )
    op.execute(
        "CREATE INDEX ix_videos_search_vector ON videos USING gin (search_vector)"
    )


def downgrade() -> None:
    op.execute("DROP INDEX IF EXISTS ix_videos_search_vector")
    op.drop_column("videos", "search_vector")
    op.drop_column("videos", "search_terms")
    op.drop_column("videos", "keywords")
    # Recreate the title-only FTS index from 0031.
    op.execute(
        "CREATE INDEX ix_videos_title_fts ON videos "
        "USING gin (to_tsvector('public.unaccent_simple', coalesce(title, '')))"
    )