Keep every file inside the rules the repo already wrote down

The 500-line rule and the one-line-comment rule were enforced only from
memory, so they drifted. bench/filesize_check.py now checks the budget on
every tracked source file, and it passes.

Split, with behaviour proven unchanged by comparing each moved function body
against HEAD byte for byte (53 training bodies, 21 benchmark bodies, 0
differences):

  db.py        503 -> 396   store_search.py     105
  bench/run.py 609 -> 351   query_set.py         80, report.py 211
  benchmarks.py 619 -> 424  benchmark_scoring.py 262
  training.py 1630 ->  94   training_{common,encode,metrics,datasets,lora,retrieval}

TrainingService stays as a thin facade for the CLI; the facade's parameter
lists are pinned against the module functions by inspect, which is what
catches a leaked self.

Deleted the eight top-level functions no file called, after fixing the scan
that had reported 201 false positives by skipping the defining file. The
v1/v2/v3 sweep found nothing to delete and says so: every remaining version
tag is an on-disk format marker, a migration step, a fixture name, or a
third-party model name.

Collapsed 39 multi-line comment blocks (86 lines) to one line each, keeping
the measured facts and error strings that justify the code.

269 tests pass; ruff clean; mypy 24 errors in 9 files against a 24-in-6
baseline, net zero; pyright 4, the same four HEAD measures.

backend/src/ely_eye/clip_encoder.py

@@ -65,8 +65,7 @@ class ClipEncoder:
         if self._tokenizer is None:
             from transformers import BertTokenizer
 
-            # The export is BERT-style (vocab.txt, [CLS]=101); transformers 5 unified the fast and
-            # slow tokenizers, so the name the CLIP docs use is an alias for this one.
+            # The export is BERT-style (vocab.txt, [CLS]=101); transformers 5 aliases the fast and slow tokenizers, so this is the name the CLIP docs mean.
             self._tokenizer = BertTokenizer.from_pretrained(str(self.model_dir))
         return self._tokenizer