Deploy just the OVRTX rendering API standalone via Docker Compose so one or more agent CLIs / services can point at it as a shared rendering endpoint. Use when user wants to run OVRTX standalone, deploy a shared rendering service, separate the rendering endpoint from an agent service, expose OVRTX to multiple callers, or set RENDER_ENDPOINT to a dedicated render host. Trigger phrases include "deploy ovrtx", "run ovrtx standalone", "shared rendering service", "ovrtx rendering docker", "render endpoint deploy", "ovrtx docker compose", "standalone rendering".
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Deploy just the OVRTX rendering API standalone via Docker Compose so one or more agent CLIs / services can point at it as a shared rendering endpoint. Use when user wants to run OVRTX standalone, deploy a shared rendering service, separate the rendering endpoint from an agent service, expose OVRTX to multiple callers, or set RENDER_ENDPOINT to a dedicated render host. Trigger phrases include "deploy ovrtx", "run ovrtx standalone", "shared rendering service", "ovrtx rendering docker", "render endpoint deploy", "ovrtx docker compose", "standalone rendering".
Requires Docker daemon, Docker Compose, NVIDIA Container Toolkit, NVIDIA GPU with about 16GB+ VRAM or a validated AWS GPU instance, free host port 8001 by default, and OVRTX readiness with gpu_initialized=true.
Deploy OVRTX Rendering API Standalone
Bring up just the OVRTX rendering API without the rest of an agent service stack. Useful when:
Multiple agent CLIs (or services) need to share a single rendering host.
The rendering GPU box is separate from the machine running the CLI / agent service.
You want to iterate on the agent pipeline without rebooting the rendering container each time.
apps/ovrtx_rendering_api/ ships the Dockerfile, service code, and standalone
docker-compose.yml. Use that compose file for shared render-service
deployments so the command is not semantically tied to material or physics.
When to Use
Use when the user wants a standalone OVRTX rendering API without a Material or Physics service stack.
Use when multiple agent CLIs or services should share one rendering endpoint.
Use when the render GPU host is separate from the machine running the agent CLI or service.
Use service-specific Docker deploy skills when the user wants the bundled sidecar managed with that service stack.
Limitations
The default standalone stack owns host port 8001. Stop overlapping Texture, Material, Physics, or prior OVRTX stacks before startup.
OVRTX is not ready on HTTP 200 alone; report ready only when /health contains gpu_initialized: true.
First build, shader warm-up, and first render can take several minutes. Return logs and health commands instead of holding an agent session open indefinitely.
For Brev/AWS validation smoke paths, keep OVRTX_RENDER_MODE=pt; do not switch to rt2 as a workaround for hangs.
Prerequisites
Docker Compose: docker compose version
NVIDIA GPU with ~16 GB+ VRAM: nvidia-smi
NVIDIA Container Toolkit: docker run --rm --gpus all nvidia/cuda:12.0-base nvidia-smi
No VLM provider key is required — OVRTX itself does not call a VLM.
Instructions
Confirm Docker, Compose, GPU, NVIDIA Container Toolkit, and port availability before starting OVRTX.
Start the standalone OVRTX compose stack from the repo root.
Poll /health and report readiness only when gpu_initialized is true.
Export RENDER_ENDPOINT for any caller that should use the shared endpoint.
Return endpoint, health state, log commands, stop commands, and caller environment variables using the output format below.
Start Standalone OVRTX
Run the standalone OVRTX compose file from the repo root:
OVRTX_RENDER_MODE=pt docker compose -f apps/ovrtx_rendering_api/docker-compose.yml up --build
If you need a different host port:
OVRTX_HOST_PORT=8010 OVRTX_RENDER_MODE=pt docker compose -f apps/ovrtx_rendering_api/docker-compose.yml up --build
First build takes ~10 minutes (OVRTX builds from source). First render takes
several minutes because shader work is cached only after the first render. For
Brev smoke tests, keep OVRTX_RENDER_MODE=pt and use
OVRTX_DAEMON_RENDER_TIMEOUT=900.
Validated AWS render candidates:
g7e.2xlarge / RTX PRO Server 6000: preferred fast validation path when
budget allows. /health and /render passed; cold warm-up completed within
the 900 second timeout.
g6e.xlarge / L40S: cheaper validated fallback. /health and /render
passed with OVRTX_NUM_SENSOR_UPDATES=1, but cold warm-up can be much slower
than RTX PRO Server 6000.
You may temporarily set OVRTX_NUM_SENSOR_UPDATES=1 to reduce cold-start work,
then restore the service default before quality-sensitive agent runs.
By default the compose file publishes host port 8001 to container port
8000. Health check succeeds once the GPU has warmed up
(gpu_initialized: true).
This is functionally equivalent for smoke testing, but Compose is preferred for
repeatable shared-service deployments because it carries the health check,
restart policy, logging policy, debug volume, and GPU reservation.
Point agent CLIs / services at it
Once the health check passes, export RENDER_ENDPOINT in the environment of the machine running the agent CLI or service:
export RENDER_ENDPOINT=http://localhost:8001 # same hostexport RENDER_ENDPOINT=http://render-host.lan:8001 # remote host
For Material Agent using backend: remote against OVRTX, also set:
export MA_RENDERING_USE_DATA_URI=true
That keeps the NVCF-compatible renderer client on the direct data-URI path
instead of uploading prepared stages through S3.
Then invoke agent CLIs / services that use backend: remote rendering:
material-agent run apps/material_agent/configs/unified_example.yaml
physics-agent run apps/physics_agent/configs/lightbulb.yaml # set render.backend: remote before using a shared endpoint
texture-agent run apps/texture_agent/configs/texture_example.yaml
apps/physics_agent/configs/lightbulb.yaml is public and defaults to local OVRTX rendering. Copy it or edit it for your run, then set the render backend to remote before pointing it at a shared RENDER_ENDPOINT.
For an agent service deployed via Docker Compose alongside the rendering host, set RENDER_ENDPOINT=http://render-host.lan:8001 in the agent service's .env.
Check Health
python - <<'PY'
import json
from urllib.request import urlopen
try:
with urlopen("http://localhost:8001/health", timeout=10) as response:
health = json.load(response)
except Exception as exc:
print(f"OVRTX unreachable: {exc}")
raise SystemExit(1)
print(json.dumps(health))
if health.get("status") == "unhealthy":
print("OVRTX unhealthy")
raise SystemExit(1)
if health.get("gpu_initialized") is True:
print("OVRTX ready")
else:
print("OVRTX warming")
PY
Until GPU warm-up completes, gpu_initialized is false. Agent CLIs / services that depend on the endpoint will block on their own retry logic until warm-up finishes.
For Brev-hosted runs, delete the workspace after the smoke or pipeline run
unless the operator explicitly keeps it. Brev auth can expire during long
build, warm-up, or smoke-test windows; if deletion is blocked, re-login and
repeat brev delete. If the instance is still reachable by SSH, power it off
first to stop compute spend while Brev workspace cleanup catches up.
Rebuild
docker compose -f apps/ovrtx_rendering_api/docker-compose.yml up --build --force-recreate
GPU Assignment
To pin OVRTX to a specific GPU, edit the relevant agent service's docker-compose.yml:
ovrtx-rendering-api:deploy:resources:reservations:devices:-driver:nvidiadevice_ids: ['0'] # specific GPU by IDcapabilities: [gpu]
Or raise count to reserve multiple GPUs (OVRTX uses the first one in the assigned set).
Environment Variables
Configurable via shell environment variables before docker compose up:
Variable
Default
Description
OVRTX_LOG_LEVEL
warn
Log verbosity (trace, debug, info, warn, error)
OVRTX_NUM_SENSOR_UPDATES
500
Sensor update count before capture; lower only for smoke tests
OVRTX_RENDER_MODE
pt
Render mode. Brev/AWS validation smoke paths must stay on pt; do not use rt2 as a workaround for hangs
Output Format
When handing control back to the user, report:
RENDER_ENDPOINT: http://localhost:8001 or the configured remote host/port.
OVRTX_HEALTH: healthy only when /health contains "gpu_initialized":true; otherwise warming or unhealthy.
CALLER_ENV: RENDER_ENDPOINT=... and MA_RENDERING_USE_DATA_URI=true when relevant for Material Agent remote rendering.
Any GPU/toolkit blockers, port conflicts, or host-driver issues.
Troubleshooting
gpu_initialized: false after several minutes
Cause: Shader compilation is slow on first boot (cold cache) or the GPU is being shared with another process. Check nvidia-smi for VRAM pressure.
Solution: Wait up to ~5 minutes on cold start. If it persists, make sure no other CUDA process is holding VRAM on the same GPU.
Some Brev L40S provider images can have NVIDIA compute libraries but not the
NVIDIA GL/Vulkan libraries required by OVRTX. Install the matching
libnvidia-gl package and regenerate CDI before recreating the container:
If the daemon reaches readiness but the first Brev/AWS validation render still
hangs, do not switch to rt2 as a workaround. Keep OVRTX_RENDER_MODE=pt, use
a 900 second render timeout for smoke testing, and capture daemon logs. AWS g7e.2xlarge / RTX PRO Server
6000 and AWS g6e.xlarge / L40S both completed full /health plus /render
smoke. Prefer RTX PRO Server 6000 for fast validation loops; use L40S when
cost matters more than cold-start latency.
Port 8001 already in use
Cause: Another process (e.g., another agent service's OVRTX sidecar, or a prior run) is using 8001.
Solution: Stop the other container, or set OVRTX_HOST_PORT before starting
the standalone compose file. OVRTX listens on container port 8000; the host
port is the left side of the mapping.
OVRTX_HOST_PORT=8010 OVRTX_RENDER_MODE=pt docker compose -f apps/ovrtx_rendering_api/docker-compose.yml up --build
Agent CLI fails with connection refused
Cause: OVRTX container still warming up, or RENDER_ENDPOINT is unset / pointing at the wrong host.
Solution: Poll /health first and confirm gpu_initialized: true before invoking the CLI; verify RENDER_ENDPOINT with echo $RENDER_ENDPOINT.
