feat(feed): broaden search to a weighted document (title + keywords + queries + description)

Makes the local search behave more like YouTube's — finding videos by the
uploader's own keywords or the query that surfaced them, not only words in the
title. A DB-generated, weighted search_vector (migration 0032) replaces the
title-only FTS index:
- keywords: the creator's snippet.tags (free — already in the snippet we fetch),
  stored on enrich.
- search_terms: distinct live-search queries that surfaced the video (across all
  users), appended by the search route — folds YouTube's relevance into local
  search (a video YT returned for a query becomes findable by it even without a
  title match), the user's own idea.
- description (truncated) for broad recall on the existing catalog.
Weighted title(A) > keywords+queries(B) > description(C) so ts_rank keeps title
hits on top. A plain GIN index on the generated column guarantees index use (no
expression/param matching). Verified on localdev: recall 146->213 for one query;
7 'eurovision' hits via the document but not the title; index scan confirmed.
This commit is contained in:
npeter83 2026-06-30 02:00:38 +02:00
parent 20bcdf5ecb
commit 4395afc210
5 changed files with 115 additions and 11 deletions

View file

@ -234,6 +234,9 @@ def apply_video_details(video: Video, item: dict) -> None:
video.view_count = int(stats["viewCount"]) if stats.get("viewCount") else None
video.like_count = int(stats["likeCount"]) if stats.get("likeCount") else None
video.category_id = int(snippet["categoryId"]) if snippet.get("categoryId") else None
# Creator keyword tags (free with the snippet we already fetch) → search document.
tags = snippet.get("tags")
video.keywords = " ".join(tags) if tags else None
video.topic_categories = topics.get("topicCategories")
video.default_language = snippet.get("defaultLanguage") or snippet.get(
"defaultAudioLanguage"