feat(model-manager): identify UNet-only SDXL LoRAs (e.g. slider LoRAs)

[Pfannkuchensack]

Summary

Self-attention-only SDXL LoRAs (e.g. Civitai "slider" LoRAs) patch only the UNet and contain no cross-attention (attn2) or text-encoder (lora_te*) keys. lora_token_vector_length() reads the base's context dimension from exactly those keys, so it returns None for such LoRAs and identification fails with "unrecognized token vector length None".

Add a structural fallback: SDXL's UNet has a deep transformer stack (up to 10 transformer blocks) in its lower-resolution attention blocks, so transformer_blocks indices reach >= 2, whereas SD1.x/SD2.x only ever have a single transformer block (index 0) per attention. _state_dict_looks_like_sdxl_unet_lora() detects SDXL from that structure alone. The regex is anchored on the UNet down/up/mid-block + attentions grouping so it won't false-positive on DiT LoRAs (FLUX/Qwen/Z-Image) that also use transformer_blocks.

The fallback only runs after the normal token-vector detection returns None, so existing LoRAs are unaffected. Wired into both the LyCORIS and Diffusers base configs.

Related Issues / Discussions

Closes #7709

QA Instructions

1. Grab a UNet-only SDXL "slider" LoRA whose keys are all lora_unet_..._attn1_... (no attn2/lora_te*), e.g. Dramatic Lighting Slider.
2. On main, installing/scanning it fails to identify with "unrecognized token vector length None".
3. On this branch, install it via the model manager and confirm it is identified as LoRA / StableDiffusionXL / LyCORIS.
4. Use the LoRA in an SDXL generation and confirm it applies correctly.
5. Regression: install a normal SDXL LoRA (with cross-attention + text-encoder keys) and an SD1.5 LoRA and confirm their bases are still detected correctly (unchanged path).

Automated coverage: tests/backend/model_manager/configs/test_sdxl_slider_lora_identification.py — unit tests for the structural heuristic (positive: self-attention-only slider + diffusers dot-format; negative: SD1.5 shallow stack, Qwen, FLUX, empty/non-string keys) plus end-to-end identification through the LyCORIS configs (SDXL matches, SD1/SD2 reject).

uv run --extra cuda --extra test python -m pytest tests/backend/model_manager/configs/ tests/backend/patches/lora_conversions/ --no-cov -q

Merge Plan

Standard merge — no DB schema or redux changes.

Checklist

• The PR has a short but descriptive title, suitable for a changelog
• Tests added / updated (if applicable)
• ❗Changes to a redux slice have a corresponding migration
• Documentation added / updated (if applicable)
• Updated What's New copy (if doing a release after this PR)