* feat(gateway): accept conversation references in run context and report the capability
LangGraph SDK clients build a fixed run body and drop unknown top-level
fields, so they cannot send the conversation_references field from #5399.
RunCreateRequest now lifts context.conversation_references into the
top-level field before validation, so it keeps the same bounds and error
locations, and drops it from context, so it never reaches the merged run
context or the checkpointed configurable. Sending both is a 422.
GET /api/features reports conversation_references {enabled, max_references}
with the same "tool is configured" predicate as run admission, so a client
can hide an entry point on deployments without the tool.
Related to #5398.
* fix(gateway): report the field type error for a malformed top-level reference list
A malformed top-level conversation_references sent alongside a context
list now fails with the field's own type error instead of the conflict
message. The tool-configured predicate reads tool.use directly, and the
features test doubles carry that attribute like every real ToolConfig.
* fix(gateway): treat every list-like top-level reference value as a conflict
Pydantic's lax mode coerces tuples, sets, frozensets and deques into the
list[str] field, so a direct Python caller passing one of those together
with context.conversation_references now reports the conflict instead of
slipping both grants through. Unreachable over HTTP, where JSON has no
such types.
* fix(gateway): ask pydantic whether a top-level reference value is list-like
Enumerating list-like types cannot track pydantic's lax acceptance set
(generators, UserList, dict key views also coerce into list[str]). The
conflict guard now validates the top-level value with a TypeAdapter for
list[Any]: whatever pydantic would coerce reports the conflict when it is
non-empty, and whatever it rejects still surfaces the field's own type
error. Regression tests cover deque, UserList, dict keys and a generator,
plus rejected scalars.
* fix(gateway): probe top-level references with the field's own annotation
The conflict guard now validates the top-level value with the exact item
annotation the field uses, so its acceptance set is the field's rather than
a superset: an item the field rejects (an empty string, a non-string, the
ints of a range or dict view) surfaces the field's own item error instead
of a conflict. The annotation is shared through one alias so the two cannot
drift.
* fix(gateway): materialise a one-shot iterator before probing top-level references
The item-validating probe could consume a generator while collecting an
item error, after which the field re-validated the exhausted iterator,
coerced it to [] and let the request through with the key still in
context. Iterators are now read once into a list that both the probe and
the field validate, so a bad item is reported at its index and a valid
generator is kept.
* fix(gateway): materialise every once-walkable iterable before probing references
Pydantic coerces any iterable into the list field, and an object whose
__iter__ hands out a generator once is not an Iterator instance, so the
previous gate let it reach the probe and be consumed. The lift now reads
every iterable except lists, tuples and the shapes the field rejects as a
whole (str, bytes, dict) into a list first, so the probe and the field
always validate the same items.
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Co-authored-by: Totoro-qaq <279883115+Totoro-qaq@users.noreply.github.com>
* feat(conversation): continue reading a cut message by offset
A referenced message longer than 4,000 characters was cut, and its
suffix could not be read back. Cut messages now carry a continuation
(message_seq, offset). read_conversation(thread_id, message_seq, offset)
returns the next part of that one message, sized to the same
tool-output budget as pages. The read scans only the requested row
under the existing visibility rules and rechecks ownership. Offsets
follow the source's current text; an offset past the end is rejected.
Related to #5398.
* docs(conversation): say continuations ignore limit
A continuation always returns one part of one message, so limit does not apply there. The tool schema now says so instead of discarding it silently.
Related to #5398.
* fix(conversation): stop instead of looping when no text fits the budget
With a read_conversation tool-output budget below the envelope size, the fitted text was empty and the continuation repeated the requested offset, so an agent would repeat the identical call forever. Page and continuation reads now return output_budget_too_small with no continuation.
Related to #5398.
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Co-authored-by: Totoro-qaq <279883115+Totoro-qaq@users.noreply.github.com>
Document that read permission expiry and source deletion do not erase
text already copied into the destination conversation, and that reads
follow the source's current visible history. Truncated results now tell
the agent to acknowledge the omission and ask for the missing material
before claiming every requirement is covered.
Pages were filled to 20,000 text characters by cutting the last message
that did not fit, and that suffix could never be paged back. They could
also exceed the default 12,000-character tool-output budget, which
externalized the page to a file. Pages are now sized by their serialized
length against the read_conversation tool-output budget; a message that
does not fit starts the next page intact, so only a message over 4,000
characters (or one whose escaped JSON alone exceeds the budget) is cut.
Co-authored-by: Totoro-qaq <279883115+Totoro-qaq@users.noreply.github.com>
Co-authored-by: Claude Opus 5 <noreply@anthropic.com>
