docs: sync all documentation with current codebase

- remove GenerationRequest and generate_with_request references (class deleted)
- document cuda>flash>torch default priority and FlashAttnBackend
- add ASTR_BACKEND env var to backend docs, TorchNativeBackend (default) → (fallback)
- fix JsonlStore transform routing → DatasetFactory ownership
- fix CudaBackend fallback chain description (FlashAttn → TorchNative)
- add FlashAttnBackend to architecture strategy table
- add router_stats to DecoderOutput/FFNOutput TypedDict diagrams
- add decode_o_part/ml_part/decode_out to KVCache diagram
- add --append_eos/--no-append_eos to IFD evaluation parameter table
- update get-started CUDA kernel note (no longer requires explicit attn_backend activation)
- fix python -m scripts.tools.server (no __init__.py) → direct script call

docs/guides/evaluation.md

@@ -214,6 +214,7 @@ python scripts/eval/evaluate_ifd.py \
 | `--sentinel_text` | `\n` | Prefix for unconditional pass (`""` → bos/pad fallback) |
 | `--per_token` | False | Include per-token IFD breakdown |
 | `--max_samples` | None | Random subsample per file |
+| `--append_eos` / `--no-append_eos` | `True` | Append (or skip) EOS token to instruction/response |
 
 **How it works**: Two forward passes per batch — (1) conditional: packed BFD sequence with context + response, (2) unconditional: response prefixed with a sentinel. IFD = mean_conditional_loss / mean_unconditional_loss. IFD > 1 means the instruction makes the response harder to predict (higher quality data).