tt-waypoint

Waypoint-1.5-1B (interactive world model) on Tenstorrent Blackhole via TTNN -- a from-scratch TTNN bring-up (nothing in tt-metal's models.tt_dit already covers this architecture), served through a stateful, session-based HTTP API behind a small ASGI server.

Runs on p150 (mesh P150).

Packaged and published with tt-model-manager 0.1.0 (manifest schema 5.1).

Quickstart

tt-model pull  episod/tt-waypoint --with-weights
tt-model serve episod/tt-waypoint

pull --with-weights downloads the Docker image and the Overworld/Waypoint-1.5-1B weights (into your HF cache; they are not in the image). serve starts the model's own HTTP server on port 20000 (or the next free port, if that one is busy); the first start compiles kernels for your device, which takes several minutes, and the server is ready when it logs Application startup complete.

tt-model pull episod/tt-waypoint --with-weights
tt-model serve episod/tt-waypoint

# Seed a session from a real starting image (base64-encoded PNG/JPEG):
curl -s localhost:20000/v1/sessions -H 'Content-Type: application/json' \
  -d "{\"image_b64\": \"$(base64 -w0 my_photo.png)\"}"
# -> {"session_id": "...", "frame_index": 1, "frame_b64": "..."}

# Step the session forward, steered by direction/zoom:
curl -s localhost:20000/v1/sessions/<session_id>/step \
  -H 'Content-Type: application/json' -d '{"direction": "forward", "zoom": 0.0}'

tt-model serve picks the host port itself (20000, or the next free one) -- the manifest's own port: field is not the seed for that choice (see container_cli.py's own comment on this), so don't assume a different value. Source, a local Gradio UI, and the bring-up log (every stage's hardware-verified numbers, every bug found and how -- including a real investigation into why generated-frame pixel correlation against a reference run looked catastrophic and turned out not to be, see BRINGUP_LOG.md): tsingletaryTT/tt-waypoint.

Provenance

The exact sources the image was built from — code/ in this repo is byte-identical to the model code inside the image:

component	built from
tt-metal	a3a9fb4229a045ad9361b4e39ad854b491346ea9
code/ digest	cb598cf74afc2e92 (sha256, first 16 hex digits)
built	2026-09-10T14:25:39+00:00 by tt-model 0.1.0