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Build(deps): Update langgraph-prebuilt requirement from <1.0.9 to <1.1.1 in /topic/machine-learning/langchain#1687

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Build(deps): Update langgraph-prebuilt requirement from <1.0.9 to <1.1.1 in /topic/machine-learning/langchain#1687
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dependabot/pip/topic/machine-learning/langchain/langgraph-prebuilt-lt-1.1.1

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@dependabot dependabot Bot commented on behalf of github May 12, 2026

Updates the requirements on langgraph-prebuilt to permit the latest version.

Release notes

Sourced from langgraph-prebuilt's releases.

langgraph==1.1.0

Changes since 1.0.10

  • release(langgraph): 1.1 (#7102)
  • fix: replay behavior for parent + subgraphs! (#7038)
  • feat: type safe stream/invoke w/ proper output type coercion (#6961)

Type-Safe Streaming & Invoke

LangGraph 1.1 introduces version="v2" — a new opt-in streaming format that brings full type safety to stream(), astream(), invoke(), and ainvoke().

What's changing

v1 (default, unchanged): stream() yields bare tuples like (stream_mode, data) or just data. invoke() returns a plain dict. Interrupts are mixed into the output dict under "__interrupt__".

v2 (opt-in): stream() yields strongly-typed StreamPart dicts with type, ns, data, and (for values) interrupts fields. invoke() returns a GraphOutput object with .value and .interrupts attributes. When your state schema is a Pydantic model or dataclass, outputs are automatically coerced to the correct type.

invoke() / ainvoke() with version="v2"

from langgraph.types import GraphOutput
result = graph.invoke({"input": "hello"}, version="v2")
result is a GraphOutput, not a dict
assert isinstance(result, GraphOutput)
result.value       # your output — dict, Pydantic model, or dataclass
result.interrupts  # tuple[Interrupt, ...], empty if none occurred

With a non-"values" stream mode, invoke(..., stream_mode="updates", version="v2") returns list[StreamPart] instead of list[tuple].

stream() / astream() with version="v2"

for part in graph.stream({"input": "hello"}, version="v2"):
    if part["type"] == "values":
        part["data"]        # OutputT — full state
        part["interrupts"]  # tuple[Interrupt, ...]
    elif part["type"] == "updates":
        part["data"]        # dict[str, Any]
    elif part["type"] == "messages":
        part["data"]        # tuple[BaseMessage, dict]
    elif part["type"] == "custom":
        part["data"]        # Any
    elif part["type"] == "tasks":
        part["data"]        # TaskPayload | TaskResultPayload
    elif part["type"] == "debug":
        part["data"]        # DebugPayload

... (truncated)

Commits
  • 3330ccd release(langgraph): 1.1 (#7102)
  • 4ef6169 feat(cli): add distributed runtime support to langgraph cli (#7096)
  • 27da1d3 chore(deps): bump the all-dependencies group across 1 directory with 3 update...
  • 9c2deac fix: replay behavior for parent + subgraphs! (#7038)
  • 2638ff7 release(cli): 0.4.15 (#7095)
  • 6511797 feat(cli): add langgraph deploy (#7004)
  • 6a19a5a chore: Add cache (#7092)
  • f4a18e0 chore(deps): bump the all-dependencies group in /libs/langgraph with 3 update...
  • d5b6124 chore(deps): bump the all-dependencies group across 1 directory with 2 update...
  • f7d94d2 chore(deps): bump the all-dependencies group in /libs/cli with 2 updates (#7075)
  • Additional commits viewable in compare view

@dependabot dependabot Bot added dependencies Concerns of dependencies. python Pull requests that update Python code labels May 12, 2026
Updates the requirements on [langgraph-prebuilt](https://github.com/langchain-ai/langgraph) to permit the latest version.
- [Release notes](https://github.com/langchain-ai/langgraph/releases)
- [Commits](langchain-ai/langgraph@v0.0.3...1.1.0)

---
updated-dependencies:
- dependency-name: langgraph-prebuilt
  dependency-version: 1.1.0
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot dependabot Bot force-pushed the dependabot/pip/topic/machine-learning/langchain/langgraph-prebuilt-lt-1.1.1 branch from 0cdda3f to 03ade22 Compare May 31, 2026 22:59
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