| --- |
| license: mit |
| language: [en] |
| task_categories: [text-generation] |
| pretty_name: LocalAgent Dispatch Data |
| tags: [tool-calling, function-calling, agent, dispatch, synthetic, routing] |
| configs: |
| - config_name: paraphrase |
| data_files: |
| - {split: train, path: paraphrase_train.jsonl} |
| - {split: eval, path: paraphrase_eval.jsonl} |
| - config_name: contextual |
| data_files: |
| - {split: train, path: contextual_train.jsonl} |
| - {split: eval, path: contextual_eval.jsonl} |
| - config_name: scenarios_single |
| data_files: |
| - {split: train, path: scenarios_single_train.jsonl} |
| - {split: eval, path: scenarios_single_eval.jsonl} |
| - config_name: scenarios_episodes |
| data_files: |
| - {split: train, path: scenarios_episodes_train.jsonl} |
| - {split: eval, path: scenarios_episodes_eval.jsonl} |
| - config_name: freeform |
| data_files: |
| - {split: train, path: freeform_train.jsonl} |
| - {split: eval, path: freeform_eval.jsonl} |
| --- |
| |
| # LocalAgent Dispatch Data |
|
|
| Synthetic data for training/evaluating a **generable tool-dispatch** model over a 50-tool surface |
| (route head → dense selector → pointer-copy). A static snapshot of the deterministic generators in |
| [LocalAgent](https://github.com/sangbumchoi/localagent) (`src/localagent/data/`). Train/eval are |
| **disjoint in both phrasing and slot values**. Companion model + demo: |
| [danelcsb/localagent-tiny-30m-byte](https://huggingface.co/danelcsb/localagent-tiny-30m-byte) · |
| [Space](https://huggingface.co/spaces/danelcsb/localagent-webgpu). |
|
|
| ## Configs |
|
|
| | config | rows (train/eval) | what it is | |
| |---|---|---| |
| | `paraphrase` | 1000 / 1000 | many natural phrasings per tool (all 50 tools), single-turn | |
| | `contextual` | 230 / 230 | **referent-conditioned**: same instruction → different tool by referent ("Open status.host.io"→`open_url`, "Open 'Chrome'"→`open_app`, "Open docs/intro.md"→`read_file`) | |
| | `scenarios_single` | 60 / 40 | clarify / **abstain** (over-trigger negatives, no tool) / parallel (≥2 calls) | |
| | `scenarios_episodes` | 60 / 60 | multi-turn episodes: workflow / chained / error-recovery | |
| | `freeform` | 86 / 45 | hand-written natural queries — **train** (86) + out-of-distribution **eval** (45) | |
|
|
| ## Schema |
|
|
| Single-turn (`paraphrase`, `contextual`, `scenarios_single`): |
| ```json |
| {"prompt": "...", "kind": "tool|text", "category": "...", "tool": "<name|>", |
| "target": "{\"arguments\":{...},\"name\":\"...\"}", "calls": [{...}]?} |
| ``` |
| - `kind="text"` (clarify/abstain) → no tool; `target` is the natural-language reply. |
| - `calls` present for parallel turns (≥2 tool calls). Tool-call arg values are **literal substrings |
| of `prompt`** (so a copy/pointer mechanism can ground them). |
|
|
| Episodes (`scenarios_episodes`): `{"category": "...", "turns": [{"role", "content", "tool_calls": |
| [{"name","arguments"}], "tool_response"}]}`. Copy-args in follow-up calls appear verbatim in a prior |
| `tool_response`. |
|
|
| `freeform`: `{"prompt": "...", "tool": "<gold tool>"}`. |
|
|
| ## Usage |
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("danelcsb/localagent-dispatch-data", "paraphrase", split="train") |
| ``` |
|
|
| Regenerate deterministically from source: `python scripts/export_dataset.py` in the LocalAgent repo. |
|
|
