The dataset teaches a small language model to respond to a single puppet-theater beat with one compact JSON object. It is intended for hackathon prototyping, schema following, and local adapter experiments, not as a general storytelling or chat dataset.

Schema

Each row is chat-style JSONL:

{
  "id": "actor-sft-v0-000001",
  "source_mix": ["synthetic_v0", "deterministic_templates", "ai_puppet_theater_runtime_schema"],
  "row_type": "prop_inspection",
  "messages": [
    {"role": "system", "content": "You are an Actor agent in AI Puppet Theater..."},
    {"role": "user", "content": "premise: ...\nshow_state JSON: ...\nactor JSON: ...\ndirector_instruction: ..."},
    {"role": "assistant", "content": "{\"intent\":\"inspect_prop\",\"line\":\"...\"}"}
  ]
}

The assistant content is a serialized JSON object with exactly:

{
  "intent": "inspect_prop",
  "line": "This rubber duck squeaks exactly like a guilty witness.",
  "emotion": "investigative",
  "gesture": "leans toward the glowing prop",
  "stage_effect": "prop_table_glow",
  "memory_update": "Noted that the rubber duck behaved like evidence.",
  "tool_request": {
    "tool": "inspect_prop",
    "args": {"prop": "rubber duck"},
    "reason": "The prop may reveal a stage clue."
  }
}

memory_update may be null. tool_request may be null.

Allowed tools:

inspect_prop with args: {"prop": "..."}
consult_stage_oracle with args: {"question": "..."}
change_lighting with args: {"mood": "..."} to match the current AI Puppet Theater runtime

Versions

v0

actor_sft_v0 is the first-pass schema and behavior-contract dataset. It is the source for the MiniCPM5 Actor LoRA adapter used in the hackathon demo and downstream GGUF conversion.

v1

actor_sft_v1 is a targeted hardening experiment with more oracle, prop, lighting, and memory rows. It improved local validation tooling and schema audit coverage, but the v1 adapter experiment did not outperform v0 on full eval at the time this card was written.

The published LoRA and GGUF artifacts are based on the v0 Actor adapter path.

Generation

Rows are generated by deterministic templates in the AI Puppet Theater repo. The generator uses fixed seeds, multiple premises, actor profiles, props, moods, stage effects, line templates, memory-update templates, and Director instructions.

Optional local seed ingestion exists for TheatreLM/RPGPT-style rows, but raw external rows are not committed here. If optional seeds are used, they only seed premise, persona, setting, memory, prop, and Director-instruction material. Assistant completions remain generated in the validated Actor JSON schema.

Potential optional seed sources:

Intended Use

Fine-tuning small models to emit Actor-agent JSON for AI Puppet Theater.
Testing structured output, tool request shape, short theatrical lines, and demo-safe puppet responses.
Hackathon prototyping and reproducible dataset generation.

Limitations

Synthetic and template-driven; it does not teach rich long-form theater writing.
Memory arcs are shallow and row-local.
Director planning is out of scope; this dataset is Actor-only.
Runtime still needs JSON validation, sanitization, and deterministic fallback.
Demo-safe filters are simple and do not replace manual review.
This dataset is not intended for general chat, broad instruction following, or safety-critical use.

Related Artifacts

Space: AI Puppet Theater
Dataset: AI-Puppet-Theater-Actor-SFT
Base model: openbmb/MiniCPM5-1B
LoRA adapter: AI-Puppet-Theater-MiniCPM5-Actor-LoRA
GGUF model: AI-Puppet-Theater-MiniCPM5-Actor-GGUF
Product blog: AI Puppet Theater: From Premise to Puppet Show
Fine-tuning blog: Teaching a 1B Model to Speak Puppet JSON
Demo video: YouTube walkthrough

License

This dataset is released under Apache-2.0.

The published dataset rows are generated from AI Puppet Theater deterministic templates and runtime schemas. Optional TheatreLM/RPGPT-style seed ingestion is documented for local generation experiments, but raw external rows are not committed in this published dataset.