tuxevil/Home-Assistant-Requests-V5.1-Native-Strict

Home Assistant Requests V5.1 Native Strict

Private research dataset for supervised fine-tuning and regression testing of a small Home Assistant native tool-calling model.

Contract: ha-native-tool-calling-v2.

Frozen snapshot

Tokenizer audit:

• —model: unsloth/Qwen3-4B-Instruct-2507
• —revision: 992063681dc2f7de4ee976110199552935cad284
• —MAX_SEQ_LENGTH=4096
• —overlength rows: 0
• —render failures: 0

All 20 Home Assistant native tools are represented. Test contains 52 GetLiveContext cases, at least 20 positive cases per tool, 102 direct/no-tool cases, and 22 multi-call cases.

Files

• —train.jsonl, validation.jsonl, test.jsonl: frozen training/evaluation splits.
• —metadata.json: sources, coverage, tool counts, and readiness report.
• —audit.json: contract, duplicate, leakage, entity-cap, secret, and hash audit.
• —token_audit.json: full tokenizer/template length and supervised-token audit.
• —provenance.json: immutable revisions, input/output hashes, code hashes, and exact build command.

Sources and licensing

This is a mixed-license derivative dataset. Preserve source attribution and applicable notices when redistributing derivatives.

1. 1.tuxevil/Home-Assistant-Requests-V5-Native, revision fbf847bb63cfb2e49a36435412d610ac8993e8fc, derived from acon96/Home-Assistant-Requests-V2 — MIT.
2. 2.enfuse/joint-intent-slot-smarthome, revision 39056ca057ae92d71fb7a272f7960567e55dca70 — Apache-2.0. Used in train only through a deterministic strict mapper.
3. 3.home-assistant/intents, revision 35466626accc5699203fc20a1af470ff173a7893 — CC-BY-4.0. Attribution: Home Assistant intents contributors.
4. 4.Deterministic internal deficit-only fixtures generated for missing readiness classes. No teacher LLM or paid API generated these fixtures.

The repository-level metadata uses license: other because no single SPDX license describes the combined corpus.

Construction policy

• —Maximum eight exposed entities per row.
• —Tool names and schemas are frozen from Home Assistant Core branch 2026.7.4.
• —Tool arguments must satisfy their supplied schema and refer only to exposed entities/areas.
• —Invalid, hidden-target, conflicting, unsupported, or non-native examples are rejected.
• —Enfuse data is train-only.
• —Official Home Assistant conformance rows are allocated test first, then validation, then train, without row reuse.
• —Final global isolation removes normalized user-text and structured semantic-signature collisions in priority order: test → validation → train.
• —Coverage fixtures only fill measured deficits and receive unique split-specific utterances.

Verified gates

audit.json reports:

• —contract errors: 0
• —duplicate example IDs: 0
• —cross-split semantic overlap: 0
• —cross-split normalized user overlap: 0
• —secret-pattern hits: 0
• —maximum exposed entities: 8
• —training readiness: true

token_audit.json reports zero overlength rows and zero render failures over all 4,969 rows.

Limitations

• —Split isolation prevents leakage created by this build. It cannot prove that a pretrained base model never saw public Home Assistant or Enfuse text during pretraining.
• —Official conformance sentences are useful deterministic holdouts, not a guarantee of out-of-distribution generalization.
• —Deficit fixtures are synthetic deterministic coverage data and may be stylistically narrower than real voice traffic.
• —Passing dataset gates does not promote a model to production. Adapter, merged FP16, Q5, Ollama, and physical Home Assistant smoke gates remain mandatory.
• —Q5 artifacts produced from this dataset remain research-only-pending-ollama-gate until tested against an authorized physical entity.

Reproducibility

See provenance.json for exact revisions, SHA-256 hashes, code hashes, tokenizer versions, and complete build command. Consumers should pin the Hugging Face dataset repository to an immutable commit SHA rather than main.