feat(data): add Hermes function-calling dataset preset

Register NousResearch/hermes-function-calling-v1 (func_calling config) in the
shared dataset registry. Since vllm-project#777 that registry is the single source of
presets, so the entry serves both pipelines: off-policy `prepare-data` and the
on-policy regeneration script's `--dataset`.

Hermes func_calling is a function-calling SFT dataset (Apache-2.0) already in
ShareGPT from/value form, so it needs no normalizer (like the existing sharegpt
preset). Each row is a single user request followed by a multi-step agentic
trajectory: system -> human -> gpt -> tool -> gpt in the common case. Tool calls
and results are text-encoded (<tool_call>/<tool_response>) inline; the parallel
`tools` column carries the JSON schemas as a JSON string.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01LRRGNt2T9ktWyFRboNUZNU
Signed-off-by: Ranran Haoran Zhang <ranzhang@redhat.com>

Author: WindChimeRan

docs/cli/response_regeneration.md

@@ -124,6 +124,7 @@ The text presets from the shared dataset registry (`DATASET_CONFIGS` in `specula
 | `magpie`            | `Magpie-Align/Magpie-Llama-3.1-Pro-300K-Filtered` | `train`       |
 | `nemotron`          | `nvidia/Llama-Nemotron-Post-Training-Dataset`     | `chat`        |
 | `open-perfectblend` | `mlabonne/open-perfectblend`                      | `train`       |
+| `hermes-fc`         | `NousResearch/hermes-function-calling-v1`         | `train`       |
 
 The registry's multimodal preset, `sharegpt4v_coco`, is **off-policy only** and `--dataset` rejects it. Its turns carry image content parts, which the Chat Completions API rejects, and the pre-tokenized output row has nowhere to keep pixel data. Use it with `prepare-data`.
 

src/speculators/data_generation/configs.py

@@ -151,4 +151,11 @@ def _normalize_sharegpt4v_coco(example: dict) -> dict:
         hf_path="mlabonne/open-perfectblend",
         split="train",
     ),
+    # Multi-turn function-calling SFT
+    "hermes-fc": DatasetConfig(
+        name="hermes-fc",
+        hf_path="NousResearch/hermes-function-calling-v1",
+        subset="func_calling",
+        split="train",
+    ),
 }