fix(similarity): address code review - column-only queries, configurable batch size, WCAG touch targets

- Use column-only query in embeddings overview to reduce memory for 100K+ files
- Add embedding_backfill_batch_size config setting (default 50)
- Fix WCAG touch target on backfill button (min-height/min-width 44px)
- Add inline comment explaining 3 chars/token truncation estimate
- Import settings in compute_embedding task for configurable batch size

Co-authored-by: christianlouis <361235+christianlouis@users.noreply.github.com>

app/utils/similarity.py

@@ -59,8 +59,8 @@ def generate_embedding(text: str, model: str | None = None) -> list[float]:
         model = settings.embedding_model
 
     # Truncate to stay within the model's context window.
-    # Use a conservative estimate of ~3 characters per token so that the
-    # resulting text fits comfortably within ``embedding_max_tokens``.
+    # Conservative 3 chars/token estimate (actual ratio varies by language;
+    # English averages ~4 chars/token but 3 gives a safety margin).
     max_chars = settings.embedding_max_tokens * 3
     if len(text) > max_chars:
         logger.debug(