Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
json
Languages:
multilingual
Size:
1K - 10K
License:
| license: other | |
| license_name: mixed-mit-apache-2.0-cc-by-4.0 | |
| task_categories: | |
| - text-generation | |
| language: | |
| - multilingual | |
| tags: | |
| - home-assistant | |
| - tool-calling | |
| - function-calling | |
| - smart-home | |
| - qwen3 | |
| pretty_name: Home Assistant Requests V5.1 Native Strict | |
| size_categories: | |
| - 1K<n<10K | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: train.jsonl | |
| - split: validation | |
| path: validation.jsonl | |
| - split: test | |
| path: test.jsonl | |
| # Home Assistant Requests V5.2 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 | |
| | Split | Rows | Direct speech | Multi-call | Maximum rendered tokens | | |
| |---|---:|---:|---:|---:| | |
| | train | 3,806 | 340 | 78 | 3,098 | | |
| | validation | 530 | 52 | 4 | 2,874 | | |
| | test | 633 | 102 | 22 | 2,925 | | |
| 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. `tuxevil/Home-Assistant-Requests-V5-Native`, revision `fbf847bb63cfb2e49a36435412d610ac8993e8fc`, derived from `acon96/Home-Assistant-Requests-V2` — MIT. | |
| 2. `enfuse/joint-intent-slot-smarthome`, revision `39056ca057ae92d71fb7a272f7960567e55dca70` — Apache-2.0. Used in train only through a deterministic strict mapper. | |
| 3. `home-assistant/intents`, revision `35466626accc5699203fc20a1af470ff173a7893` — CC-BY-4.0. Attribution: Home Assistant intents contributors. | |
| 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`. | |