🎼 Scene Context Composer

The name is a little lie in your favor: 🎼 Scene Context Composer doesn't call an API, doesn't spawn a local LLM, and doesn't need a key. It rolls a scene. Give it a genre, a tone, and a seed, and it procedurally assembles a full context - subject, situation, tone modifier, atmosphere, and a framing phrase - from JSON data files that ship in the pack. If you've been eyeing the LLM prompt-enhancer trend and thought "I just want something coherent without babysitting a model," this is the no-dependencies end of that spectrum.

It's the v2 of this pack's context system, and it shows. Where the Picker (its sibling, same pack) is the simple upstream companion, the Composer is the standalone writer. The README is explicit that it's renderer-agnostic by construction - the text it emits feeds any text-conditioned model, which matters because the pack's other headline node targets Ideogram 4's structured-prompt format specifically.

How it works

The data lives in scene_context/ - shared with the Picker, single source of truth - and the whole thing is deterministic template sampling from that JSON. The mechanics, grounded in the source:

• Genre flavors the pool. Your genre narrows which settings are even eligible. Add genre2 for a union mashup - settings matching either are in play, so "sci_fi" + "fantasy" rolls venues from both worlds.
• Setting is two-tier. Pick an archetype like "on a nautical vessel" and it filters venues by facet tags, then rolls within that pool. Pick a specific venue name like pirate_ship and it pins that outright - the author's escape hatch, deliberately unconstrained (a fantasy cruise ship is a legitimate ask).
• The double filter is the interesting bit. Tone is a selection axis, not seasoning: each tone declares which situation capability tags it's compatible with (violent_capable, calm_capable, …), and Setting and Tone jointly narrow the situation pool. A tone that matches nothing just falls back to the full list - flavor yields to structure.
• Composition is a first-class axis. Framing phrases key off the situation's scene_type_bias - face_off, gathering, atmospheric, and friends - with a generic fallback pool so unknown biases still get something reasonable.

The inputs and outputs that matter

You actually set: genre, genre2 (leave at none until you want a mashup), tone (🎲 random, violent, charming, satirical, eerie, mundane), setting (archetype or specific venue, or 🎲 to roll by genre), composition (🎲 random follows the situation's bias; none emits no framing), and seed. That's it - everything else is handled.

Outputs are where the value hides:

• context_text - the prose: subject, situation, tone modifier, atmosphere flourish.
• render_prompt - context_text plus the composition phrase. This is the model-ready one.
• components_json - every piece separately, for remixing or logging.
• seed_used - the actual seed, so you can wire it into a sampler and reproduce the roll.

Install

Same as any custom node, and this one is refreshingly light:

cd ComfyUI/custom_nodes/
git clone https://github.com/elliefox-ai/comfyui-scene-generator.git ComfyUI-EllieFoxAI-scene-gen

Then restart ComfyUI and look under SceneGen in the node menu. Or just search "comfyui-scene-generator" in ComfyUI Manager. There is no requirements.txt and no model download - the README's "no additional Python dependencies beyond what ComfyUI already provides" is actually true, which is rare enough to say out loud.

Where people get burned

This pack has almost no community footprint yet (a corpus search for "scene generator" in r/comfyui turns up single digits), so you're early - expect to debug by reading. Two grounded gotchas: the text it writes is natural-language prose for LLM-encoded models, so if you feed it to a tag-trained checkpoint like Illustrious or Pony, don't expect it to sing. And if a workflow you downloaded asks for Outpaint Controller or PromptPeek, those moved to sibling packs (comfyui-elliefoxai-canvas, comfyui-elliefoxai-diagnostics) - this repo only carries the four SceneGen nodes. For reproducibility, run seed_used into your sampler seed rather than letting it roll free; the whole point of the deterministic design is that one seed drives the story.