Dreamverse Development

Dreamverse lives under apps/dreamverse/ as a product app inside the FastVideo monorepo. Backend code uses the local FastVideo workspace package; frontend tooling remains standalone under apps/dreamverse/web/.

Backend tests

Run backend tests excluding GPU-marked cases from the FastVideo repository root:

uv run --locked --package dreamverse --extra test pytest apps/dreamverse/dreamverse/tests/ -m 'not gpu' -q

Collection can still touch FastVideo streaming imports that probe for an active GPU driver, so the corresponding CI job runs on a GPU even with GPU-marked tests excluded.

Backend launch

Launch the migrated backend through the installed console commands:

dreamverse-server --port 8009
dreamverse-mock-server --port 8009

If dreamverse-server is missing, install FastVideo with the dreamverse extra from the checkout:

UV_TORCH_BACKEND=cu126 uv pip install -e ".[dreamverse]"  # use cu130 on CUDA 13

Frontend build and tests

Run frontend commands from the standalone web app:

cd apps/dreamverse/web
npm ci
npm run build
npm test

Playwright is intentionally run against a live backend as part of the local GPU manual verification flow, not in the Phase 3 migration gate.

Local GPU verification

Choose an available physical GPU for full-stack smoke tests. For example, CUDA_VISIBLE_DEVICES=4 makes physical GPU 4 appear as logical GPU 0 inside the process.

For a managed backend-and-frontend redeploy with readiness checks and logs, use the repo-local skill helper:

./.agents/skills/dreamverse-deploy/scripts/dreamverse-deploy.sh 4 8009 5299

The helper's legacy frontend default is 5274, so the example passes the web app's current port, 5299, explicitly. It writes logs under /tmp/opencode/dreamverse-deploy. The equivalent manual backend launch is:

CUDA_VISIBLE_DEVICES=4 dreamverse-server --host 0.0.0.0 --port 8009

In another shell, verify the service:

curl -s http://localhost:8009/healthz

The full Playwright suite expects /healthz, /readyz, /status, /prompt-system-config, and /curated-presets from the Dreamverse backend.

Production-equivalent GPU prerequisites

For the production-equivalent NVFP4 path, install these dependencies in the FastVideo .venv before GPU smoke tests:

uv pip install --python .venv/bin/python \
  flashinfer-python flash-attn cerebras-cloud-sdk openai \
  --no-build-isolation

Package	Why
`flashinfer-python`	Required for NVFP4 quantization. Without it, model load fails with `ImportError: NVFP4 quantization requires flashinfer`.
`flash-attn`	Optional but recommended; without it attention falls back to Torch SDPA (functional but slower).
`cerebras-cloud-sdk`	Required by the migrated prompt enhancer for the default `cerebras` provider.
`openai`	Required by the prompt enhancer's OpenAI-compatible providers + downstream rewrites.

B200 / sm_100a + gcc-15 conda toolchain (flashinfer JIT workaround)

On hosts where the conda toolchain ships gcc-15 (which nvcc rejects with #error -- unsupported GNU version! gcc versions later than 14 are not supported!), set these env vars before launching anything that triggers flashinfer's JIT kernel build:

export CC=/usr/bin/gcc-13
export CXX=/usr/bin/g++-13
export CUDAHOSTCXX=/usr/bin/g++-13
export NVCC_PREPEND_FLAGS="-ccbin /usr/bin/gcc-13 -allow-unsupported-compiler"

dreamverse-server does not set these; keep them in the launching shell when starting it directly. The repo-local dreamverse-deploy skill exports them for managed local launches.

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