| # 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: |
|
|
| ```text |
| 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: |
|
|
| ```text |
| 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. |
|
|
| ```text |
| 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. |
|
|
