fix(preflight): label diversity respects the label's SQL type

[saadqbal]

Rides the reland path (#150 → #149 → develop). Bugbot flagged this on my parallel reland #151 (which targeted the now-superseded ux branch); this carries the same fix onto feat/preflight-parity so the develop-bound reland doesn't re-introduce it.

Bug: CheckLabelDiversity collapsed numeric-looking labels ("1"/"1.0") for every tabular_classification dataset. The in-cluster LabelDiversityValidator._label_read_kwargs pins dtype=str for string-family schema types (VARCHAR/CHAR/TEXT/STRING) — so those labels stay distinct; only numeric types get pandas numeric inference. A user-declared VARCHAR label with numeric-looking classes was wrongly rejected at preflight.

Fix: derive the drop-NA / collapse-numeric flags from the label's declared SQL type at the dispatch site; image/text (untyped) unchanged. Adds leaf + dispatch tests; parity suite green. Aligns the Go side with the golden generator, which already types columns VARCHAR.

Rolls up under #145/#147.

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Note

Low Risk
Localized preflight validation parity fix with targeted tests; no auth, upload, or cluster behavior changes.

Overview
Fixes preflight label diversity for tabular_classification so it matches in-cluster LabelDiversityValidator behavior (data-ingestors #252).

CheckLabelDiversity no longer uses a single “tabular schema” mode. It takes dropNASentinels and collapseNumeric instead, applying NA-sentinel skipping and "1"/"1.0" collapse only when the ingestor would. For PreflightDataset, those flags come from the label column’s declared SQL type via new helpers labelSchemaType and isStringSQLType: string types (VARCHAR/CHAR/TEXT/STRING) keep numeric-looking labels distinct; numeric types still collapse. Image and text classification keep untyped reads (false, false).

Tests cover leaf flag behavior and PreflightDataset dispatch (VARCHAR passes, FLOAT rejects on the same CSV).

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[LukasWodka]

👋 Heads-up — Code review queue is at 35 / 30

Above the WIP limit. The team convention is to review existing PRs before opening new work.

Open PRs currently in Code review (oldest first):

• averaging-service#156 — feat(strategies): FedMedian Byzantine-robust aggregation (CLI: a mistyped subcommand (e.g. dataset pus) prints help and exits 0 instead of erroring #75) · author: @shujaatTracebloc · reviewer: @divyasinghds
• averaging-service#157 — feat(strategies): FedTrimmedAvg Byzantine-robust aggregation (CLI: a mistyped subcommand (e.g. dataset pus) prints help and exits 0 instead of erroring #75) · author: @shujaatTracebloc · reviewer: @divyasinghds
• averaging-service#158 — feat(strategies): Krum / MultiKrum Byzantine-robust selection (CLI: a mistyped subcommand (e.g. dataset pus) prints help and exits 0 instead of erroring #75) · author: @shujaatTracebloc · reviewer: @divyasinghds
• averaging-service#159 — feat(strategies): FedProx aggregation strategy (dataset push: --category help lists 5 of 9 categories, and unknown-vs-empty category errors give two different lists (one leaks unsupported segmentation) #74) · author: @shujaatTracebloc · reviewer: @divyasinghds
• averaging-service#160 — feat(strategies): FedOpt family — FedAdam / FedYogi / FedAdagrad (dataset push: --category help lists 5 of 9 categories, and unknown-vs-empty category errors give two different lists (one leaks unsupported segmentation) #74) · author: @shujaatTracebloc · reviewer: @divyasinghds
• backend#927 — feat(validators): schema check for tabular/text/token classification (#924 G2) · author: @divyasinghds · no reviewer assigned
• backend#931 — feat(validators): generic all-category checks + validation matrix (#924 Phase 0/G12) · author: @divyasinghds · reviewer: @saqlainsyed007
• backend#934 — feat(validators): column-level tabular/text schema diagnostics (#924 G3/G4) · author: @divyasinghds · no reviewer assigned
• backend#935 — feat(validators): time-series & survival temporal checks (#924 G8/G9) · author: @divyasinghds · reviewer: @saqlainsyed007
• backend#936 — feat(validators): text/NLP language + alignable-text checks (#924 G10) · author: @divyasinghds · reviewer: @saqlainsyed007

Pull from review before opening new work. (This is a nudge from the kanban WIP check, not a block.)