engine/CONVERSATION_NOTES.md

Live Brain + Conversation Notes

This phase keeps the controller training-free and model-agnostic. The real model lives behind modal_app/brain_modal.py; local code only asks for BrainSignals and generated replies.

Flow

1. The text stream feeds incremental word groups plus an optional silence flag.
2. Conversation sends the current dialogue prefix and newest user chunk to LiveBrainPanel.step_all().
3. Modal computes per-agent surprise, hidden vector, readiness, and p_end.
4. WhenToSpeakController arbitrates SILENT, BACKCHANNEL, TAKE_FLOOR, or INTERRUPT.
5. On TAKE_FLOOR or INTERRUPT, Conversation calls Modal generate() and splices the short investor reply into the dialogue.

The sample pitch deliberately includes a weak claim: "ten thousand stores and zero churn after launching last week." The expected demo behavior is an investor interrupt or floor-take near that claim, with the generated line recorded in eval/conversation_log.json.

Run the real text-streamed demo with:

uv run modal run modal_app/brain_modal.py

Modal

The live brain tries nvidia/Llama-3.1-Nemotron-Nano-4B-v1.1 first and falls back to Qwen/Qwen2.5-3B-Instruct. We keep HF_HOME=/cache on a Modal Volume so weights persist across runs.

Recorded Demo

The committed eval/conversation_log.json was produced by:

uv run modal run modal_app/brain_modal.py

Latest measured run: nvidia/Llama-3.1-Nemotron-Nano-4B-v1.1 on NVIDIA A10. Total wall time was 49.1 s because the run included Modal container/model startup.

At step 3 the controller interrupted the planted weak claim. The winning agent was ruthless_skeptic with urge 1.47 and readiness 0.67. At step 7 the panel now takes the floor at turn end.

Ruthless Skeptic: Zero churn after one week is not churn data.
Vision Optimist: Show cohorts, paid conversion, and retention.

Generation caveat: Nemotron-Nano produced malformed text for these two generate() calls, so eval/conversation_log.json records reply_source: "fallback" for both. The timing signals and controller decisions are still real Modal/Nemotron outputs; the fallback only guards the spoken text until the generator prompt/model is improved.