Synthetic supervised-fine-tuning data for a retriever-agnostic, tool-calling shopping assistant
(target model: LiquidAI/LFM2.5-230M, 230M). Every grounded answer is written from search-tool results
only (RAG-as-a-tool), and tool/argument names are procedurally randomized per example so the
model learns to read the injected schema rather than memorize a fixed toolset.
Compositional generation:… See the full description on the dataset page:
https://huggingface.co/datasets/lazos/frontend-agent-sft.
