Hartmut/HartOMat
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

feat: add workflow rollout gate signals

Browse Source
This commit is contained in:
Hartmut Nörenberg
2026-04-08 21:44:02 +02:00
parent 8c9648d5dc
commit fe46dabfc5
4 changed files with 1624 additions and 101 deletions
Download Patch File Download Diff File Expand all files Collapse all files
backend/app/domains/rendering/dispatch_service.py
+218 -14
View File
@@ -17,6 +17,28 @@ import logging
logger = logging.getLogger(__name__)
def _build_rollout_signal(
*,
gate_status: str,
ready: bool,
reasons: list[str],
workflow_def_id=None,
output_type_id=None,
verdict: str | None = None,
) -> dict:
return {
"rollout_gate_status": gate_status,
"rollout_gate_verdict": verdict,
"rollout_gate_reasons": reasons,
"workflow_rollout_ready": ready,
"workflow_rollout_status": "ready_for_rollout" if ready else "hold_legacy_authoritative",
"output_type_rollout_ready": ready,
"output_type_rollout_status": "ready_for_rollout" if ready else "hold_legacy_authoritative",
"rollout_workflow_definition_id": str(workflow_def_id) if workflow_def_id is not None else None,
"rollout_output_type_id": str(output_type_id) if output_type_id is not None else None,
}
def dispatch_render_with_workflow(order_line_id: str) -> dict:
"""Dispatch a render for the given order line.
@@ -33,6 +55,7 @@ def dispatch_render_with_workflow(order_line_id: str) -> dict:
from app.domains.orders.models import OrderLine
from app.domains.rendering.models import OutputType, WorkflowDefinition
from app.domains.rendering.workflow_config_utils import (
canonicalize_workflow_config,
extract_runtime_workflow,
get_workflow_execution_mode,
)
@@ -67,7 +90,16 @@ def dispatch_render_with_workflow(order_line_id: str) -> dict:
"order_line %s: no workflow_definition_id, using legacy dispatch",
order_line_id,
)
return _legacy_dispatch(order_line_id)
legacy_result = _legacy_dispatch(order_line_id)
legacy_result.update(
_build_rollout_signal(
gate_status="legacy_only",
ready=False,
reasons=["No workflow definition is linked; legacy dispatch remains authoritative."],
output_type_id=getattr(output_type, "id", None),
)
)
return legacy_result
# Load the linked WorkflowDefinition
wf_def: WorkflowDefinition | None = session.execute(
@@ -84,13 +116,45 @@ def dispatch_render_with_workflow(order_line_id: str) -> dict:
order_line_id,
output_type.workflow_definition_id,
)
return _legacy_dispatch(order_line_id)
legacy_result = _legacy_dispatch(order_line_id)
legacy_result.update(
_build_rollout_signal(
gate_status="workflow_unavailable",
ready=False,
reasons=["Linked workflow definition is missing or inactive; legacy dispatch remains authoritative."],
workflow_def_id=output_type.workflow_definition_id,
output_type_id=output_type.id,
)
)
return legacy_result
execution_mode = get_workflow_execution_mode(wf_def.config, default="legacy")
try:
canonical_config = canonicalize_workflow_config(wf_def.config)
except Exception as exc:
logger.warning(
"order_line %s: workflow_definition_id %s has invalid config (%s), "
"falling back to legacy dispatch",
order_line_id,
wf_def.id,
exc,
)
legacy_result = _legacy_dispatch(order_line_id)
legacy_result.update(
_build_rollout_signal(
gate_status="workflow_invalid",
ready=False,
reasons=[f"Workflow definition config is invalid: {exc}."],
workflow_def_id=wf_def.id,
output_type_id=output_type.id,
)
)
return legacy_result
execution_mode = get_workflow_execution_mode(canonical_config, default="legacy")
def _prepare_graph_context(target_mode: str):
workflow_context = prepare_workflow_context(
wf_def.config,
canonical_config,
context_id=order_line_id,
execution_mode=target_mode,
)
@@ -122,7 +186,18 @@ def dispatch_render_with_workflow(order_line_id: str) -> dict:
wf_def.id,
exc,
)
return _legacy_dispatch(order_line_id)
legacy_result = _legacy_dispatch(order_line_id)
legacy_result["fallback_from"] = "workflow_graph"
legacy_result.update(
_build_rollout_signal(
gate_status="graph_preparation_failed",
ready=False,
reasons=[f"Graph runtime preparation failed: {exc}."],
workflow_def_id=wf_def.id,
output_type_id=output_type.id,
)
)
return legacy_result
run = None
try:
@@ -136,7 +211,18 @@ def dispatch_render_with_workflow(order_line_id: str) -> dict:
wf_def.id,
exc,
)
return _legacy_dispatch(order_line_id)
legacy_result = _legacy_dispatch(order_line_id)
legacy_result["fallback_from"] = "workflow_graph"
legacy_result.update(
_build_rollout_signal(
gate_status="graph_run_creation_failed",
ready=False,
reasons=[f"Graph workflow run creation failed: {exc}."],
workflow_def_id=wf_def.id,
output_type_id=output_type.id,
)
)
return legacy_result
try:
dispatch_result = execute_graph_workflow(session, workflow_context)
@@ -154,15 +240,35 @@ def dispatch_render_with_workflow(order_line_id: str) -> dict:
fallback_result = _legacy_dispatch(order_line_id)
fallback_result["fallback_from"] = "workflow_graph"
fallback_result["workflow_run_id"] = str(run.id)
fallback_result.update(
_build_rollout_signal(
gate_status="graph_execution_failed",
ready=False,
reasons=[f"Graph workflow execution failed: {exc}."],
workflow_def_id=wf_def.id,
output_type_id=output_type.id,
)
)
return fallback_result
return {
result = {
"backend": "workflow_graph",
"execution_mode": "graph",
"workflow_run_id": str(run.id),
"celery_task_id": dispatch_result.task_ids[0] if dispatch_result.task_ids else None,
"task_ids": dispatch_result.task_ids,
}
result.update(
_build_rollout_signal(
gate_status="graph_authoritative",
ready=True,
verdict="pass",
reasons=["Workflow graph dispatch is authoritative for this output type."],
workflow_def_id=wf_def.id,
output_type_id=output_type.id,
)
)
return result
if execution_mode == "shadow":
legacy_result = _legacy_dispatch(order_line_id)
@@ -180,6 +286,18 @@ def dispatch_render_with_workflow(order_line_id: str) -> dict:
legacy_result["execution_mode"] = "shadow"
legacy_result["shadow_status"] = "skipped"
legacy_result["shadow_error"] = str(exc)
legacy_result.update(
_build_rollout_signal(
gate_status="shadow_skipped",
ready=False,
reasons=[
"Shadow workflow preparation failed; legacy dispatch remains authoritative.",
f"Preparation error: {exc}.",
],
workflow_def_id=wf_def.id,
output_type_id=output_type.id,
)
)
return legacy_result
run = None
@@ -197,6 +315,18 @@ def dispatch_render_with_workflow(order_line_id: str) -> dict:
legacy_result["execution_mode"] = "shadow"
legacy_result["shadow_status"] = "failed"
legacy_result["shadow_error"] = str(exc)
legacy_result.update(
_build_rollout_signal(
gate_status="shadow_run_creation_failed",
ready=False,
reasons=[
"Shadow workflow run could not be created; legacy dispatch remains authoritative.",
f"Run creation error: {exc}.",
],
workflow_def_id=wf_def.id,
output_type_id=output_type.id,
)
)
return legacy_result
try:
@@ -216,15 +346,39 @@ def dispatch_render_with_workflow(order_line_id: str) -> dict:
legacy_result["shadow_status"] = "failed"
legacy_result["shadow_error"] = str(exc)
legacy_result["shadow_workflow_run_id"] = str(run.id)
legacy_result.update(
_build_rollout_signal(
gate_status="shadow_execution_failed",
ready=False,
reasons=[
"Shadow workflow execution failed; legacy dispatch remains authoritative.",
f"Execution error: {exc}.",
],
workflow_def_id=wf_def.id,
output_type_id=output_type.id,
)
)
return legacy_result
legacy_result["execution_mode"] = "shadow"
legacy_result["shadow_status"] = "dispatched"
legacy_result["shadow_workflow_run_id"] = str(run.id)
legacy_result["shadow_task_ids"] = dispatch_result.task_ids
legacy_result.update(
_build_rollout_signal(
gate_status="pending_shadow_verdict",
ready=False,
reasons=[
"Legacy dispatch remains authoritative until the shadow workflow comparison returns pass.",
"A pass verdict is required before workflow-first rollout is ready.",
],
workflow_def_id=wf_def.id,
output_type_id=output_type.id,
)
)
return legacy_result
workflow_type, params = extract_runtime_workflow(wf_def.config)
workflow_type, params = extract_runtime_workflow(canonical_config)
if workflow_type is None or workflow_type == "custom":
logger.warning(
"order_line %s: workflow_definition_id %s has no supported preset runtime, "
@@ -232,7 +386,17 @@ def dispatch_render_with_workflow(order_line_id: str) -> dict:
order_line_id,
wf_def.id,
)
return _legacy_dispatch(order_line_id)
legacy_result = _legacy_dispatch(order_line_id)
legacy_result.update(
_build_rollout_signal(
gate_status="workflow_runtime_unsupported",
ready=False,
reasons=["Workflow definition has no supported preset runtime; legacy dispatch remains authoritative."],
workflow_def_id=wf_def.id,
output_type_id=output_type.id,
)
)
return legacy_result
logger.info(
"order_line %s: dispatching via WorkflowDefinition %s (type=%s)",
@@ -243,7 +407,7 @@ def dispatch_render_with_workflow(order_line_id: str) -> dict:
try:
workflow_context = prepare_workflow_context(
wf_def.config,
canonical_config,
context_id=order_line_id,
execution_mode="legacy",
)
@@ -255,7 +419,17 @@ def dispatch_render_with_workflow(order_line_id: str) -> dict:
wf_def.id,
exc,
)
return _legacy_dispatch(order_line_id)
legacy_result = _legacy_dispatch(order_line_id)
legacy_result.update(
_build_rollout_signal(
gate_status="workflow_preparation_failed",
ready=False,
reasons=[f"Workflow runtime preparation failed: {exc}."],
workflow_def_id=wf_def.id,
output_type_id=output_type.id,
)
)
return legacy_result
# For turntable workflows: resolve step_path + output_dir from the order line at runtime
if workflow_type == "turntable" and ("step_path" not in params or "output_dir" not in params):
@@ -299,7 +473,17 @@ def dispatch_render_with_workflow(order_line_id: str) -> dict:
wf_def.id,
exc,
)
return _legacy_dispatch(order_line_id)
legacy_result = _legacy_dispatch(order_line_id)
legacy_result.update(
_build_rollout_signal(
gate_status="workflow_run_creation_failed",
ready=False,
reasons=[f"Workflow run creation failed: {exc}."],
workflow_def_id=wf_def.id,
output_type_id=output_type.id,
)
)
return legacy_result
from app.domains.rendering.workflow_builder import dispatch_workflow
@@ -317,15 +501,35 @@ def dispatch_render_with_workflow(order_line_id: str) -> dict:
order_line_id,
wf_def.id,
)
return _legacy_dispatch(order_line_id)
legacy_result = _legacy_dispatch(order_line_id)
legacy_result.update(
_build_rollout_signal(
gate_status="workflow_dispatch_failed",
ready=False,
reasons=[f"Workflow dispatch failed: {exc}."],
workflow_def_id=wf_def.id,
output_type_id=output_type.id,
)
)
return legacy_result
return {
result = {
"backend": "workflow",
"workflow_type": workflow_type,
"execution_mode": "legacy",
"workflow_run_id": str(run.id),
"celery_task_id": celery_task_id,
}
result.update(
_build_rollout_signal(
gate_status="workflow_legacy_runtime",
ready=False,
reasons=["Workflow definition is active, but execution still uses the legacy runtime path."],
workflow_def_id=wf_def.id,
output_type_id=output_type.id,
)
)
return result
def _legacy_dispatch(order_line_id: str) -> dict:
backend/app/domains/rendering/workflow_comparison_service.py
+86 -15
View File
@@ -10,11 +10,16 @@ from PIL import Image, ImageChops, ImageStat
from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession
from app.config import settings
from app.core.render_paths import resolve_result_path, result_path_to_storage_key
from app.domains.media.models import MediaAsset
from app.domains.orders.models import OrderLine
from app.domains.rendering.models import WorkflowRun
from app.domains.rendering.schemas import WorkflowComparisonArtifactOut, WorkflowRunComparisonOut
ROLLOUT_PASS_MAX_MEAN_PIXEL_DELTA = 0.0
ROLLOUT_WARN_MAX_MEAN_PIXEL_DELTA = 0.02
@dataclass(slots=True)
class _ArtifactComparison:
@@ -36,18 +41,78 @@ class _ArtifactComparison:
sha256=self.sha256,
mime_type=self.mime_type,
image_width=self.image_width,
image_height=self.image_height,
image_height=self.image_height,
)
def evaluate_rollout_gate(
*,
authoritative_output: _ArtifactComparison,
observer_output: _ArtifactComparison,
exact_match: bool | None,
dimensions_match: bool | None,
mean_pixel_delta: float | None,
) -> dict[str, object]:
thresholds = {
"pass_max_mean_pixel_delta": ROLLOUT_PASS_MAX_MEAN_PIXEL_DELTA,
"warn_max_mean_pixel_delta": ROLLOUT_WARN_MAX_MEAN_PIXEL_DELTA,
}
reasons: list[str] = []
if not authoritative_output.exists:
verdict = "fail"
reasons.append("Authoritative legacy output is missing; keep legacy fallback active.")
elif not observer_output.exists:
verdict = "fail"
reasons.append("Observer workflow output is missing; rollout cannot be approved.")
elif exact_match:
verdict = "pass"
reasons.append("Observer output matches the authoritative legacy output byte-for-byte.")
elif dimensions_match is False:
verdict = "fail"
reasons.append("Observer output dimensions differ from the authoritative legacy output.")
elif mean_pixel_delta is None:
verdict = "fail"
reasons.append("Observer output could not be pixel-compared against the authoritative output.")
elif mean_pixel_delta <= ROLLOUT_PASS_MAX_MEAN_PIXEL_DELTA:
verdict = "pass"
reasons.append("Observer output is visually identical within the pass threshold.")
elif mean_pixel_delta <= ROLLOUT_WARN_MAX_MEAN_PIXEL_DELTA:
verdict = "warn"
reasons.append(
"Observer output differs slightly from the authoritative output but remains within the warn threshold."
)
else:
verdict = "fail"
reasons.append(
"Observer output exceeds the allowed parity threshold; keep legacy fallback active."
)
if mean_pixel_delta is not None and not exact_match:
reasons.append(
f"Mean pixel delta {mean_pixel_delta:.6f}; "
f"pass<={ROLLOUT_PASS_MAX_MEAN_PIXEL_DELTA:.6f}, "
f"warn<={ROLLOUT_WARN_MAX_MEAN_PIXEL_DELTA:.6f}."
)
rollout_ready = verdict == "pass"
rollout_status = "ready_for_rollout" if rollout_ready else "hold_legacy_authoritative"
return {
"verdict": verdict,
"ready": rollout_ready,
"status": rollout_status,
"reasons": reasons,
"thresholds": thresholds,
"workflow_rollout_ready": rollout_ready,
"workflow_rollout_status": rollout_status,
"output_type_rollout_ready": rollout_ready,
"output_type_rollout_status": rollout_status,
}
def _normalize_storage_key(path: str | None) -> str | None:
if not path:
return None
normalized = path.replace("\\", "/")
marker = "/uploads/"
if marker in normalized:
return normalized.split(marker, 1)[1]
return normalized.lstrip("/")
return result_path_to_storage_key(path)
def _build_artifact(path: str | None) -> _ArtifactComparison:
@@ -63,7 +128,8 @@ def _build_artifact(path: str | None) -> _ArtifactComparison:
image_height=None,
)
file_path = Path(path)
resolved_path = resolve_result_path(path)
file_path = resolved_path or Path(path)
exists = file_path.exists()
mime_type, _ = mimetypes.guess_type(str(file_path))
@@ -136,10 +202,8 @@ async def _load_shadow_asset_by_workflow_run(
if asset is None:
return None
storage_key = asset.storage_key.lstrip("/")
if storage_key.startswith("app/uploads/"):
return f"/{storage_key}"
return f"/app/uploads/{storage_key}"
resolved = resolve_result_path(asset.storage_key)
return str(resolved) if resolved is not None else None
def _find_shadow_file(order_line: OrderLine, workflow_run: WorkflowRun) -> str | None:
@@ -147,9 +211,13 @@ def _find_shadow_file(order_line: OrderLine, workflow_run: WorkflowRun) -> str |
candidate_roots: list[Path] = []
if order_line.result_path:
candidate_roots.append(Path(order_line.result_path).parent)
resolved_result = resolve_result_path(order_line.result_path)
if resolved_result is not None:
candidate_roots.append(resolved_result.parent)
candidate_roots.append(Path("/app/uploads/renders") / str(order_line.id))
upload_root = Path(settings.upload_dir)
candidate_roots.append(upload_root / "renders" / str(order_line.id))
candidate_roots.append(upload_root / "step_files" / "renders")
seen_roots: set[Path] = set()
candidates: list[Path] = []
@@ -215,6 +283,9 @@ async def build_workflow_run_comparison(
if exact_match:
status = "matched"
summary = "Observer output matches the authoritative legacy output byte-for-byte."
elif mean_pixel_delta == 0.0 and dimensions_match:
status = "matched"
summary = "Observer output matches the authoritative legacy output visually, but file metadata differs."
else:
status = "different"
if dimensions_match is False:
backend/tests/domains/test_workflow_dispatch_service.py
+1109 -13
View File
File diff suppressed because it is too large Load Diff
scripts/test_render_pipeline.py
+211 -59
View File
@@ -53,6 +53,9 @@ passed = []
failed = []
warnings = []
ROLLOUT_PASS_MAX_MEAN_PIXEL_DELTA = 0.0
ROLLOUT_WARN_MAX_MEAN_PIXEL_DELTA = 0.02
# ---------------------------------------------------------------------------
# Helpers
@@ -83,6 +86,55 @@ def section(title: str):
print(f"{BLUE}{'='*60}{RESET}")
def evaluate_rollout_gate_from_comparison(comparison: dict) -> dict:
reasons: list[str] = []
mean_pixel_delta = comparison.get("mean_pixel_delta")
exact_match = comparison.get("exact_match")
dimensions_match = comparison.get("dimensions_match")
status = comparison.get("status")
authoritative_exists = bool(comparison.get("authoritative_output", {}).get("exists"))
observer_exists = bool(comparison.get("observer_output", {}).get("exists"))
if not authoritative_exists:
verdict = "fail"
reasons.append("Authoritative legacy output is missing.")
elif not observer_exists:
verdict = "fail"
reasons.append("Observer workflow output is missing.")
elif exact_match:
verdict = "pass"
reasons.append("Observer output matches the authoritative legacy output byte-for-byte.")
elif dimensions_match is False:
verdict = "fail"
reasons.append("Observer output dimensions differ from the authoritative legacy output.")
elif mean_pixel_delta is None:
verdict = "fail"
reasons.append(f"Workflow comparison did not produce a pixel delta (status={status}).")
elif mean_pixel_delta <= ROLLOUT_PASS_MAX_MEAN_PIXEL_DELTA:
verdict = "pass"
reasons.append("Observer output is visually identical within the pass threshold.")
elif mean_pixel_delta <= ROLLOUT_WARN_MAX_MEAN_PIXEL_DELTA:
verdict = "warn"
reasons.append("Observer output differs slightly but remains within the warn threshold.")
else:
verdict = "fail"
reasons.append("Observer output exceeds the rollout parity threshold.")
if mean_pixel_delta is not None and not exact_match:
reasons.append(
f"Mean pixel delta {mean_pixel_delta:.6f}; "
f"pass<={ROLLOUT_PASS_MAX_MEAN_PIXEL_DELTA:.6f}, "
f"warn<={ROLLOUT_WARN_MAX_MEAN_PIXEL_DELTA:.6f}."
)
return {
"verdict": verdict,
"ready": verdict == "pass",
"reasons": reasons,
}
class APIClient:
def __init__(self, host: str, email: str, password: str):
self.host = host.rstrip("/")
@@ -93,7 +145,7 @@ class APIClient:
def _login(self, email: str, password: str):
resp = self.session.post(
f"{self.host}/api/auth/login",
data={"username": email, "password": password},
json={"email": email, "password": password},
)
resp.raise_for_status()
data = resp.json()
@@ -110,6 +162,44 @@ class APIClient:
return self.session.delete(f"{self.host}/api{path}", **kwargs)
def build_graph_still_config() -> dict:
return {
"version": 1,
"ui": {"preset": "still_graph", "execution_mode": "graph"},
"nodes": [
{
"id": "setup",
"step": "order_line_setup",
"params": {},
"ui": {"label": "Order Line Setup", "position": {"x": 0, "y": 100}},
},
{
"id": "template",
"step": "resolve_template",
"params": {},
"ui": {"label": "Resolve Template", "position": {"x": 220, "y": 100}},
},
{
"id": "render",
"step": "blender_still",
"params": {},
"ui": {"type": "renderNode", "label": "Still Render", "position": {"x": 440, "y": 100}},
},
{
"id": "output",
"step": "output_save",
"params": {},
"ui": {"type": "outputNode", "label": "Save Output", "position": {"x": 660, "y": 100}},
},
],
"edges": [
{"from": "setup", "to": "template"},
{"from": "template", "to": "render"},
{"from": "render", "to": "output"},
],
}
# ---------------------------------------------------------------------------
# Test: Render health endpoint
# ---------------------------------------------------------------------------
@@ -174,24 +264,34 @@ def test_step_upload(client: APIClient, step_file: Path) -> str | None:
cad_file_id = data["cad_file_id"]
ok(f"STEP uploaded → cad_file_id={cad_file_id[:8]}... status={data.get('status')}")
# Poll for completed processing
# Poll the existing CAD endpoints. There is no GET /api/cad/{id}; the most
# reliable readiness signal is /objects returning 200 with processing_status.
info(f"Waiting for CAD processing (timeout={CAD_PROCESSING_TIMEOUT}s)...")
deadline = time.time() + CAD_PROCESSING_TIMEOUT
last_status = None
while time.time() < deadline:
resp = client.get(f"/cad/{cad_file_id}")
if resp.status_code == 200:
cad = resp.json()
resp_objects = client.get(f"/cad/{cad_file_id}/objects")
if resp_objects.status_code == 200:
cad = resp_objects.json()
status = cad.get("processing_status")
if status != last_status:
info(f" CAD status: {status}")
last_status = status
if status == "completed":
ok(f"CAD processing completed (thumbnail rendered)")
ok("CAD processing completed (parsed objects available)")
return cad_file_id
if status == "failed":
fail(f"CAD processing FAILED: {cad.get('error_message', 'unknown error')}")
return None
resp_thumb = client.get(f"/cad/{cad_file_id}/thumbnail")
if resp_thumb.status_code == 200:
if last_status != "completed":
info(" CAD status: completed")
last_status = "completed"
ok("CAD processing completed (thumbnail available)")
return cad_file_id
time.sleep(POLL_INTERVAL_SECONDS)
fail(f"CAD processing timed out after {CAD_PROCESSING_TIMEOUT}s (last status: {last_status})")
@@ -207,17 +307,14 @@ def test_order_render(
cad_file_id: str,
output_type_ids: list[str],
test_label: str,
*,
use_graph_dispatch: bool = False,
) -> bool:
"""Create a minimal order, submit, dispatch renders, wait for completion."""
section(f"3. Order Render — {test_label}")
info(f"Output types: {len(output_type_ids)}")
# Get a product that uses this CAD file
resp = client.get(f"/cad/{cad_file_id}")
if resp.status_code != 200:
fail(f"CAD file lookup failed: {resp.status_code}")
return False
# Find or create a product linked to this CAD file
product_id = None
resp_products = client.get("/products/?limit=100")
@@ -245,46 +342,41 @@ def test_order_render(
product_id = resp_create.json()["id"]
ok(f"Created test product: {product_id[:8]}...")
# Build output_type_selections for one product
ot_selections = [{"product_id": product_id, "output_type_id": ot_id} for ot_id in output_type_ids]
# Create order via wizard endpoint
resp_order = client.post("/orders/product-order", json={
"product_id": product_id,
"output_type_selections": [
{"output_type_id": ot_id}
for ot_id in output_type_ids
],
})
resp_order = client.post(
"/orders",
json={
"notes": f"Render pipeline integration test: {test_label}",
"items": [],
"lines": [
{"product_id": product_id, "output_type_id": ot_id}
for ot_id in output_type_ids
],
},
)
if resp_order.status_code not in (200, 201):
# Fallback: try to find existing submitted order
warn(f"Product order wizard not available ({resp_order.status_code}), looking for existing order lines...")
return _test_existing_renders(client, product_id, output_type_ids)
fail(f"Order creation failed: {resp_order.status_code} {resp_order.text[:300]}")
return False
order = resp_order.json()
order_id = order["id"]
ok(f"Order created: {order.get('order_number')} (id={order_id[:8]}...)")
return _submit_and_wait(client, order_id, output_type_ids)
return _submit_and_wait(
client,
order,
output_type_ids,
use_graph_dispatch=use_graph_dispatch,
)
def _test_existing_renders(client: APIClient, product_id: str, output_type_ids: list[str]) -> bool:
"""Find existing order lines for a product and wait for completion."""
resp = client.get(f"/orders/?limit=20")
if resp.status_code != 200:
fail("Could not list orders")
return False
orders = resp.json()
if isinstance(orders, dict):
orders = orders.get("items", [])
for order in orders:
if order.get("status") in ("submitted", "processing", "rendering"):
return _submit_and_wait(client, order["id"], output_type_ids)
warn("No suitable existing orders found for render test")
return True # non-blocking warning
def _submit_and_wait(client: APIClient, order_id: str, output_type_ids: list[str]) -> bool:
def _submit_and_wait(
client: APIClient,
order: dict,
output_type_ids: list[str],
*,
use_graph_dispatch: bool = False,
) -> bool:
order_id = order["id"]
# Submit
resp_sub = client.post(f"/orders/{order_id}/submit")
if resp_sub.status_code not in (200, 201, 204):
@@ -296,14 +388,34 @@ def _submit_and_wait(client: APIClient, order_id: str, output_type_ids: list[str
else:
ok("Order submitted")
# Dispatch renders
resp_disp = client.post(f"/orders/{order_id}/dispatch-renders")
if resp_disp.status_code not in (200, 201, 204):
fail(f"Dispatch renders failed: {resp_disp.status_code} {resp_disp.text[:200]}")
return False
dispatch_data = resp_disp.json() if resp_disp.content else {}
dispatched = dispatch_data.get("dispatched", "?")
ok(f"Renders dispatched ({dispatched} lines)")
dispatch_run_id = None
if use_graph_dispatch:
lines = order.get("lines", [])
if len(lines) != 1:
fail("Graph mode currently expects exactly one order line per test order")
return False
line_id = lines[0]["id"]
resp_disp = client.post(
"/workflows/dispatch",
json={
"context_id": line_id,
"config": build_graph_still_config(),
},
)
if resp_disp.status_code not in (200, 201):
fail(f"Workflow draft dispatch failed: {resp_disp.status_code} {resp_disp.text[:300]}")
return False
dispatch_data = resp_disp.json()
dispatch_run_id = dispatch_data["workflow_run"]["id"]
ok(f"Graph workflow dispatched (run={dispatch_run_id[:8]}..., tasks={dispatch_data.get('dispatched', '?')})")
else:
resp_disp = client.post(f"/orders/{order_id}/dispatch-renders")
if resp_disp.status_code not in (200, 201, 204):
fail(f"Dispatch renders failed: {resp_disp.status_code} {resp_disp.text[:200]}")
return False
dispatch_data = resp_disp.json() if resp_disp.content else {}
dispatched = dispatch_data.get("dispatched", "?")
ok(f"Renders dispatched ({dispatched} lines)")
# Poll for order completion
info(f"Waiting for renders to complete (timeout={RENDER_TIMEOUT_SECONDS}s per OT)...")
@@ -323,10 +435,20 @@ def _submit_and_wait(client: APIClient, order_id: str, output_type_ids: list[str
info(f" {summary}")
last_summary = summary
if order_status == "completed":
ok(f"Order completed — all {len(lines)} render(s) done")
# Check individual line results
all_success = True
terminal_states = {"completed", "failed", "cancelled"}
line_states = [state for state in statuses if state]
if line_states and all(state in terminal_states for state in line_states):
all_success = all(state == "completed" for state in line_states)
if order_status == "completed":
ok(f"Order completed — all {len(lines)} render(s) done")
elif all_success:
ok(
f"All {len(lines)} render line(s) completed "
f"(order status remains {order_status})"
)
else:
fail(f"Order reached terminal line states with order={order_status}")
for line in lines:
rs = line.get("render_status")
ot_name = line.get("output_type_name") or line.get("output_type", {}).get("name", "?")
@@ -334,13 +456,30 @@ def _submit_and_wait(client: APIClient, order_id: str, output_type_ids: list[str
ok(f" Line [{ot_name}]: completed")
elif rs == "failed":
fail(f" Line [{ot_name}]: FAILED")
all_success = False
else:
warn(f" Line [{ot_name}]: {rs}")
if all_success and dispatch_run_id:
resp_cmp = client.get(f"/workflows/runs/{dispatch_run_id}/comparison")
if resp_cmp.status_code == 200:
comparison = resp_cmp.json()
rollout_gate = evaluate_rollout_gate_from_comparison(comparison)
verdict = rollout_gate["verdict"]
if verdict == "pass":
ok(" Rollout gate PASS — graph output is ready for workflow-first rollout")
elif verdict == "warn":
warn(" Rollout gate WARN — keep legacy authoritative and review drift")
else:
warn(" Rollout gate FAIL — keep legacy authoritative")
info(f" Comparison status: {comparison.get('status')}, verdict={verdict}")
for reason in rollout_gate["reasons"]:
info(f" {reason}")
else:
warn(f" Comparison lookup failed: {resp_cmp.status_code}")
return all_success
if order_status == "failed":
fail(f"Order FAILED — check render logs")
fail("Order FAILED — check render logs")
return False
time.sleep(POLL_INTERVAL_SECONDS)
@@ -377,6 +516,7 @@ def main():
parser.add_argument("--health", action="store_true", help="Only run health check")
parser.add_argument("--sample", action="store_true", help="Quick sample test (1 STEP, 1 OT)")
parser.add_argument("--full", action="store_true", help="Full test (all output types)")
parser.add_argument("--graph", action="store_true", help="Dispatch sample/full renders via /api/workflows/dispatch")
parser.add_argument("--step", default=str(SAMPLE_STEP), help="Path to STEP file")
args = parser.parse_args()
@@ -431,7 +571,13 @@ def main():
output_types[0],
)
info(f"Sample test using output type: {ot['name']}")
test_order_render(client, cad_file_id, [ot["id"]], f"Sample [{ot['name']}]")
test_order_render(
client,
cad_file_id,
[ot["id"]],
f"Sample [{ot['name']}]",
use_graph_dispatch=args.graph,
)
elif args.full:
# Test each output type individually
@@ -439,7 +585,13 @@ def main():
if ot.get("is_animation"):
warn(f"Skipping animation output type: {ot['name']} (too slow for full test)")
continue
test_order_render(client, cad_file_id, [ot["id"]], ot["name"])
test_order_render(
client,
cad_file_id,
[ot["id"]],
ot["name"],
use_graph_dispatch=args.graph,
)
_print_summary()
sys.exit(0 if not failed else 1)