fix: close Python workflow client review

This commit is contained in:
lda
2026-08-31 23:38:03 +07:00 Verified
parent 4f946a35ef
commit 5e3d0b6524
15 changed files with 200 additions and 224 deletions
@@ -1301,7 +1301,13 @@ artifact = await graph.save(version=1)
run = await artifact.run({})
```
State explicitly that drafts are not part of `wf_client` but remain registered in the server until the separate draft opt-out plan is executed. Update `docs/current_roadmap.md` to mark the Python-client slice complete only after every verification step below passes.
Drafts are not part of `wf_client`. The shipped server composition uses
`drafts=False` by default, which excludes draft storage, domain modules, and RPC
registration; real legacy draft consumers opt in explicitly with `drafts=True`.
The earlier plan assumption that draft methods would remain registered pending a
separate opt-out slice is historical. Update `docs/current_roadmap.md` to mark
the Python-client slice complete only after every verification step below
passes.
- [ ] **Step 6: Run focused and cross-layer verification**
@@ -633,12 +633,11 @@ capability, expose secrets, or fetch an unbounded trace.
authoring compiles a complete workflow and saves it through the existing
artifact-from-plan operation.
Making draft support uninitialized by default is a separate server-composition
slice. Today `WorkflowApi` constructs draft modules unconditionally, durable
context validation requires a draft store, and the JSON-RPC app always
registers draft methods. That follow-up must make draft storage, domain modules,
and RPC registration opt-in without weakening artifact, deployment, or run
durability.
Draft support is uninitialized by default across storage, domain modules, and
JSON-RPC registration. Normal composition uses `drafts=False`; callers that
still operate the legacy draft workspace surface must opt in explicitly with
`drafts=True`. This keeps artifact, deployment, and run durability independent
from draft storage.
## Testing Strategy