Update OpenAPI spec from LangGraph API v0.5.23

This PR improves the consistency of interrupt streaming. 

- when streaming with stream_mode values, the stream chunk now contains
the entire state alongside the interrupt:

```python
class State(TypedDict):
    robot_input: str
# at this point in time robot_input is already set to  "beep boop i am a robot"
app.stream(..., stream_mode="values")
# before
{"__interrupt__": (Interrupt(value="interrupt",))}}
# after
{"robot_input": "beep boop i am a robot", "__interrupt__": (Interrupt(value="interrupt"))}
```

- when streaming with stream_mode=["values", "updates"], interrupts are
surfaced in both an update stream chunk and the value stream chunk, when
previously we keep interrupt in values only if we request values mode
only

```python
class State(TypedDict):
    robot_input: str
# at this point in time robot_input is already set to  "beep boop i am a robot"
app.stream(..., stream_mode=["values", "updates"])
# before (interrupt would only emit on update chunk, there would be no values chunk)
("updates", {"__interrupt__": (Interrupt(value="interrupt",))}})
# after
("updates", {"__interrupt__": (Interrupt(value="interrupt",))}})
("values", {"robot_input": "beep boop i am a robot", "__interrupt__": (Interrupt(value="interrupt"))})
```

For housekeeping: this PR improves on this revert:
https://github.com/langchain-ai/langgraph/pull/6141

docs/_scripts/notebook_hooks.py

@@ -81,7 +81,7 @@ REDIRECT_MAP = {
     # cloud redirects
     "cloud/index.md": "https://docs.langchain.com/oss/python/langgraph/overview",
     "cloud/how-tos/index.md": "https://docs.langchain.com/langsmith/home",
-    "cloud/concepts/api.md": "https://docs.langchain.com/langsmith/langgraph-server",
+    "cloud/concepts/api.md": "https://docs.langchain.com/langsmith/agent-server",
     "cloud/concepts/cloud.md": "https://docs.langchain.com/langsmith/cloud",
     "cloud/faq/studio.md": "https://docs.langchain.com/langsmith/studio",
     "cloud/how-tos/human_in_the_loop_edit_state.md": "https://docs.langchain.com/langsmith/add-human-in-the-loop",
@@ -111,8 +111,8 @@ REDIRECT_MAP = {
     "tutorials/introduction.ipynb": "https://docs.langchain.com/oss/python/langgraph/overview",
     "agents/deployment.md": "https://docs.langchain.com/oss/python/langgraph/local-server",
     # deployment redirects
-    "how-tos/deploy-self-hosted.md": "https://docs.langchain.com/langsmith/hosting",
-    "concepts/self_hosted.md": "https://docs.langchain.com/langsmith/hosting",
+    "how-tos/deploy-self-hosted.md": "https://docs.langchain.com/langsmith/platform-setup",
+    "concepts/self_hosted.md": "https://docs.langchain.com/langsmith/platform-setup",
     "tutorials/deployment.md": "https://docs.langchain.com/langsmith/deployments",
     # assistant redirects
     "cloud/how-tos/assistant_versioning.md": "https://docs.langchain.com/langsmith/configuration-cloud",
@@ -129,16 +129,30 @@ REDIRECT_MAP = {
     "how-tos/human_in_the_loop/edit-graph-state.ipynb": "https://docs.langchain.com/oss/python/langgraph/use-time-travel",
 
     # LGP mintlify migration redirects
+    "examples/index.md": "https://docs.langchain.com/oss/python/learn",
+    "guides/index.md": "https://docs.langchain.com/oss/python/langgraph/overview",
+    "concepts/index.md": "https://docs.langchain.com/oss/python/langgraph/overview",
+    "tutorials/index.md": "https://docs.langchain.com/oss/python/learn",
+    "llms-txt-overview.md": "https://docs.langchain.com/llms.txt",
+    "tutorials/rag/langgraph_adaptive_rag.md": "https://docs.langchain.com/oss/python/langgraph/agentic-rag",
+    "tutorials/multi_agent/multi-agent-collaboration.ipynb": "https://docs.langchain.com/oss/python/langchain/multi-agent",
+    "how-tos/create-react-agent-manage-message-history.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory",
+    "how-tos/many-tools.ipynb": "https://docs.langchain.com/oss/python/langchain/tools",
+    "tutorials/customer-support/customer-support.ipynb": "https://docs.langchain.com/oss/python/langgraph/agentic-rag",
+    "how-tos/react-agent-structured-output.ipynb": "https://docs.langchain.com/oss/python/langchain/agents#structured-output",
+    "tutorials/code_assistant/langgraph_code_assistant.ipynb": "https://docs.langchain.com/oss/python/langgraph/agentic-rag",
+    "tutorials/multi_agent/hierarchical_agent_teams.ipynb": "https://docs.langchain.com/oss/python/langchain/supervisor",
     "tutorials/auth/getting_started.md": "https://docs.langchain.com/langsmith/auth",
     "tutorials/auth/resource_auth.md": "https://docs.langchain.com/langsmith/resource-auth",
     "tutorials/auth/add_auth_server.md": "https://docs.langchain.com/langsmith/add-auth-server",
     "how-tos/use-remote-graph.md": "https://docs.langchain.com/langsmith/use-remote-graph",
     "how-tos/autogen-integration.md": "https://docs.langchain.com/langsmith/autogen-integration",
+    "how-tos/human_in_the_loop/wait-user-input.ipynb": "https://docs.langchain.com/oss/python/langgraph/interrupts",
     "cloud/how-tos/use_stream_react.md": "https://docs.langchain.com/langsmith/use-stream-react",
     "cloud/how-tos/generative_ui_react.md": "https://docs.langchain.com/langsmith/generative-ui-react",
     "concepts/langgraph_platform.md": "https://docs.langchain.com/langsmith/deployments",
     "concepts/langgraph_components.md": "https://docs.langchain.com/langsmith/components",
-    "concepts/langgraph_server.md": "https://docs.langchain.com/langsmith/langgraph-server",
+    "concepts/langgraph_server.md": "https://docs.langchain.com/langsmith/agent-server",
     "concepts/langgraph_data_plane.md": "https://docs.langchain.com/langsmith/data-plane",
     "concepts/langgraph_control_plane.md": "https://docs.langchain.com/langsmith/control-plane",
     "concepts/langgraph_cli.md": "https://docs.langchain.com/langsmith/cli",
@@ -201,7 +215,7 @@ REDIRECT_MAP = {
     "cloud/deployment/egress.md": "https://docs.langchain.com/langsmith/env-var",
     "cloud/how-tos/streaming.md": "https://docs.langchain.com/langsmith/streaming",
     "cloud/reference/api/api_ref.md": "https://docs.langchain.com/langsmith/server-api-ref",
-    "cloud/reference/langgraph_server_changelog.md": "https://docs.langchain.com/langsmith/langgraph-server-changelog",
+    "cloud/reference/langgraph_server_changelog.md": "https://docs.langchain.com/langsmith/agent-server-changelog",
     "cloud/reference/api/api_ref_control_plane.md": "https://docs.langchain.com/langsmith/api-ref-control-plane",
     "cloud/reference/cli.md": "https://docs.langchain.com/langsmith/cli",
     "cloud/reference/env_var.md": "https://docs.langchain.com/langsmith/env-var",
@@ -219,12 +233,15 @@ REDIRECT_MAP = {
     "tutorials/get-started/6-time-travel.md": "https://docs.langchain.com/oss/python/langgraph/quickstart",
     "tutorials/langsmith/local-server.md": "https://docs.langchain.com/oss/python/langgraph/local-server",
     "tutorials/workflows.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
+    "tutorials/plan-and-execute/plan-and-execute.ipynb": "https://docs.langchain.com/oss/python/langchain/middleware/built-in#to-do-list",
+    "tutorials/langgraph-platform/local-server/local-server.md": "https://docs.langchain.com/langsmith/local-server",
     "concepts/agentic_concepts.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
     "guides/index.md": "https://docs.langchain.com/oss/python/langchain/overview",
     "agents/overview.md": "https://docs.langchain.com/oss/python/langchain/agents",
     "agents/run_agents.md": "https://docs.langchain.com/oss/python/langgraph/quickstart",
     "concepts/low_level.md": "https://docs.langchain.com/oss/python/langgraph/graph-api",
     "how-tos/graph-api.md": "https://docs.langchain.com/oss/python/langgraph/graph-api",
+    "how-tos/react-agent-from-scratch.ipynb": "https://docs.langchain.com/oss/python/langchain/quickstart",
     "concepts/functional_api.md": "https://docs.langchain.com/oss/python/langgraph/functional-api",
     "how-tos/use-functional-api.md": "https://docs.langchain.com/oss/python/langgraph/functional-api",
     "concepts/pregel.md": "https://docs.langchain.com/oss/python/langgraph/pregel",
@@ -282,8 +299,8 @@ REDIRECT_MAP = {
     "reference/supervisor.md": "https://reference.langchain.com/python/langgraph/supervisor/",
     "reference/swarm.md": "https://reference.langchain.com/python/langgraph/swarm/",
     "reference/mcp.md": "https://reference.langchain.com/python/langgraph/mcp/",
-    "cloud/reference/sdk/python_sdk_ref.md": "https://reference.langchain.com/python/platform/python_sdk/",
-    "reference/remote_graph.md": "https://reference.langchain.com/python/platform/remote_graph/",
+    "cloud/reference/sdk/python_sdk_ref.md": "https://reference.langchain.com/python/langsmith/deployment/sdk/",
+    "reference/remote_graph.md": "https://reference.langchain.com/python/langsmith/deployment/remote_graph/",
 
     # additional exclude-search entries from mkdocs.yml
     "additional-resources/index.md": "https://docs.langchain.com/oss/python/langchain/overview",
@@ -294,8 +311,8 @@ REDIRECT_MAP = {
     "cloud/deployment/custom_docker.md": "https://docs.langchain.com/langsmith/custom-docker",
     "cloud/deployment/egress.md": "https://docs.langchain.com/langsmith/env-var",
     "cloud/deployment/graph_rebuild.md": "https://docs.langchain.com/langsmith/graph-rebuild",
-    "cloud/deployment/self_hosted_control_plane.md": "https://docs.langchain.com/langsmith/hosting",
-    "cloud/deployment/self_hosted_data_plane.md": "https://docs.langchain.com/langsmith/hosting",
+    "cloud/deployment/self_hosted_control_plane.md": "https://docs.langchain.com/langsmith/platform-setup",
+    "cloud/deployment/self_hosted_data_plane.md": "https://docs.langchain.com/langsmith/platform-setup",
     "cloud/deployment/semantic_search.md": "https://docs.langchain.com/langsmith/semantic-search",
     "cloud/deployment/setup_javascript.md": "https://docs.langchain.com/langsmith/setup-javascript",
     "cloud/deployment/setup_pyproject.md": "https://docs.langchain.com/langsmith/setup-pyproject",
@@ -331,7 +348,7 @@ REDIRECT_MAP = {
     "cloud/reference/api/api_ref.md": "https://docs.langchain.com/langsmith/server-api-ref",
     "cloud/reference/cli.md": "https://docs.langchain.com/langsmith/cli",
     "cloud/reference/env_var.md": "https://docs.langchain.com/langsmith/env-var",
-    "cloud/reference/langgraph_server_changelog.md": "https://docs.langchain.com/langsmith/langgraph-server-changelog",
+    "cloud/reference/langgraph_server_changelog.md": "https://docs.langchain.com/langsmith/agent-server-changelog",
     "cloud/reference/sdk/js_ts_sdk_ref.md": "https://reference.langchain.com/javascript/modules/langsmith.html",
     "concepts/application_structure.md": "https://docs.langchain.com/langsmith/application-structure",
     "concepts/assistants.md": "https://docs.langchain.com/langsmith/assistants",
@@ -345,9 +362,9 @@ REDIRECT_MAP = {
     "concepts/langgraph_control_plane.md": "https://docs.langchain.com/langsmith/control-plane",
     "concepts/langgraph_data_plane.md": "https://docs.langchain.com/langsmith/data-plane",
     "concepts/langgraph_platform.md": "https://docs.langchain.com/langsmith/home",
-    "concepts/langgraph_self_hosted_control_plane.md": "https://docs.langchain.com/langsmith/hosting",
-    "concepts/langgraph_self_hosted_data_plane.md": "https://docs.langchain.com/langsmith/hosting",
-    "concepts/langgraph_server.md": "https://docs.langchain.com/langsmith/langgraph-server",
+    "concepts/langgraph_self_hosted_control_plane.md": "https://docs.langchain.com/langsmith/platform-setup",
+    "concepts/langgraph_self_hosted_data_plane.md": "https://docs.langchain.com/langsmith/platform-setup",
+    "concepts/langgraph_server.md": "https://docs.langchain.com/langsmith/agent-server",
     "concepts/langgraph_standalone_container.md": "https://docs.langchain.com/langsmith/docker",
     "concepts/langgraph_studio.md": "https://docs.langchain.com/langsmith/studio",
     "concepts/plans.md": "https://docs.langchain.com/langsmith/home",
@@ -793,6 +810,17 @@ def on_post_build(config):
     # Track which paths have explicit redirects
     redirected_paths = set()
 
+    # Collect all existing HTML files in the site
+    all_html_files = set()
+    for root, dirs, files in os.walk(site_dir):
+        for file in files:
+            if file.endswith(".html"):
+                # Get relative path from site_dir
+                html_path = os.path.relpath(os.path.join(root, file), site_dir)
+                # Normalize path separators to forward slashes
+                html_path = html_path.replace(os.sep, "/")
+                all_html_files.add(html_path)
+
     # Process explicit redirects from REDIRECT_MAP
     for page_old, page_new in REDIRECT_MAP.items():
         # Convert .ipynb to .md for path calculation
@@ -847,6 +875,24 @@ def on_post_build(config):
 
             _write_html(site_dir, old_html_path, new_html_path)
 
+    # Create catch-all redirects for any HTML files not explicitly redirected
+    catchall_url = "https://docs.langchain.com/oss/python/langgraph/overview"
+    for html_file in all_html_files:
+        # Skip if this file is already explicitly redirected
+        if html_file in redirected_paths:
+            continue
+
+        # Skip the root index.html (we handle that separately)
+        if html_file == "index.html":
+            continue
+
+        # Skip reference documentation (keep those accessible)
+        if html_file.startswith("reference/"):
+            continue
+
+        # Create redirect for this unmapped file
+        _write_html(site_dir, html_file, catchall_url)
+
     # Create root index.html redirect
     root_redirect_html = """<!doctype html>
 <html lang="en">

libs/checkpoint-postgres/LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2024 LangChain, Inc.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

libs/checkpoint-postgres/langgraph/checkpoint/postgres/__init__.py

@@ -97,7 +97,7 @@ class PostgresSaver(BasePostgresSaver):
                 strict=False,
             ):
                 cur.execute(migration)
-                cur.execute(f"INSERT INTO checkpoint_migrations (v) VALUES ({v})")
+                cur.execute("INSERT INTO checkpoint_migrations (v) VALUES (%s)", (v,))
         if self.pipe:
             self.pipe.sync()
 

libs/checkpoint-postgres/langgraph/checkpoint/postgres/aio.py

@@ -102,7 +102,9 @@ class AsyncPostgresSaver(BasePostgresSaver):
                 strict=False,
             ):
                 await cur.execute(migration)
-                await cur.execute(f"INSERT INTO checkpoint_migrations (v) VALUES ({v})")
+                await cur.execute(
+                    "INSERT INTO checkpoint_migrations (v) VALUES (%s)", (v,)
+                )
         if self.pipe:
             await self.pipe.sync()
 

libs/checkpoint-postgres/langgraph/checkpoint/postgres/base.py

@@ -81,7 +81,7 @@ MIGRATIONS = [
     """
     CREATE INDEX CONCURRENTLY IF NOT EXISTS checkpoint_writes_thread_id_idx ON checkpoint_writes(thread_id);
     """,
-    """ALTER TABLE checkpoint_writes ADD COLUMN task_path TEXT NOT NULL DEFAULT '';""",
+    """ALTER TABLE checkpoint_writes ADD COLUMN IF NOT EXISTS task_path TEXT NOT NULL DEFAULT '';""",
 ]
 
 SELECT_SQL = """

libs/checkpoint-postgres/langgraph/checkpoint/postgres/shallow.py

@@ -77,7 +77,7 @@ MIGRATIONS = [
     CREATE INDEX CONCURRENTLY IF NOT EXISTS checkpoint_writes_thread_id_idx ON checkpoint_writes(thread_id);
     """,
     """
-    ALTER TABLE checkpoint_writes ADD COLUMN task_path TEXT NOT NULL DEFAULT '';
+    ALTER TABLE checkpoint_writes ADD COLUMN IF NOT EXISTS task_path TEXT NOT NULL DEFAULT '';
     """,
 ]
 
@@ -252,7 +252,7 @@ class ShallowPostgresSaver(BasePostgresSaver):
                 strict=False,
             ):
                 cur.execute(migration)
-                cur.execute(f"INSERT INTO checkpoint_migrations (v) VALUES ({v})")
+                cur.execute("INSERT INTO checkpoint_migrations (v) VALUES (%s)", (v,))
         if self.pipe:
             self.pipe.sync()
 
@@ -614,7 +614,9 @@ class AsyncShallowPostgresSaver(BasePostgresSaver):
                 strict=False,
             ):
                 await cur.execute(migration)
-                await cur.execute(f"INSERT INTO checkpoint_migrations (v) VALUES ({v})")
+                await cur.execute(
+                    "INSERT INTO checkpoint_migrations (v) VALUES (%s)", (v,)
+                )
         if self.pipe:
             await self.pipe.sync()
 

libs/checkpoint-postgres/langgraph/store/postgres/base.py

@@ -91,7 +91,12 @@ WHERE expires_at IS NOT NULL;
 VECTOR_MIGRATIONS: Sequence[Migration] = [
     Migration(
         """
-CREATE EXTENSION IF NOT EXISTS vector;
+DO $$
+BEGIN
+    IF NOT EXISTS (SELECT 1 FROM pg_extension WHERE extname = 'vector') THEN
+        CREATE EXTENSION vector;
+    END IF;
+END $$;
 """,
     ),
     Migration(

libs/checkpoint-postgres/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-checkpoint-postgres"
-version = "3.0.0"
+version = "3.0.1"
 description = "Library with a Postgres implementation of LangGraph checkpoint saver."
 authors = []
 requires-python = ">=3.10"
@@ -19,7 +19,10 @@ dependencies = [
 ]
 
 [project.urls]
-Repository = "https://www.github.com/langchain-ai/langgraph"
+Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/checkpoint-postgres"
+Twitter = "https://x.com/LangChainAI"
+Slack = "https://www.langchain.com/join-community"
+Reddit = "https://www.reddit.com/r/LangChain/"
 
 [dependency-groups]
 test = [

libs/checkpoint-postgres/uv.lock

@@ -281,7 +281,7 @@ test = [
 
 [[package]]
 name = "langgraph-checkpoint-postgres"
-version = "3.0.0"
+version = "3.0.1"
 source = { editable = "." }
 dependencies = [
     { name = "langgraph-checkpoint" },

libs/checkpoint-sqlite/LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2024 LangChain, Inc.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

libs/checkpoint-sqlite/pyproject.toml

@@ -18,7 +18,10 @@ dependencies = [
 ]
 
 [project.urls]
-Repository = "https://www.github.com/langchain-ai/langgraph"
+Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/checkpoint-sqlite"
+Twitter = "https://x.com/LangChainAI"
+Slack = "https://www.langchain.com/join-community"
+Reddit = "https://www.reddit.com/r/LangChain/"
 
 [dependency-groups]
 test = [

libs/checkpoint/pyproject.toml

@@ -17,7 +17,10 @@ dependencies = [
 ]
 
 [project.urls]
-Repository = "https://www.github.com/langchain-ai/langgraph"
+Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/checkpoint"
+Twitter = "https://x.com/LangChainAI"
+Slack = "https://www.langchain.com/join-community"
+Reddit = "https://www.reddit.com/r/LangChain/"
 
 [dependency-groups]
 test = [

libs/cli/pyproject.toml

@@ -25,7 +25,10 @@ inmem = [
 ]
 
 [project.urls]
-Repository = "https://www.github.com/langchain-ai/langgraph"
+Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/cli"
+Twitter = "https://x.com/LangChainAI"
+Slack = "https://www.langchain.com/join-community"
+Reddit = "https://www.reddit.com/r/LangChain/"
 
 [project.scripts]
 langgraph = "langgraph_cli.cli:cli"

libs/langgraph/.claude/settings.local.json

@@ -1,16 +0,0 @@
-{
-  "permissions": {
-    "allow": [
-      "Bash(rg:*)",
-      "Bash(python:*)",
-      "Bash(grep:*)",
-      "Bash(sed:*)",
-      "Bash(awk:*)",
-      "Bash(uv run mypy:*)",
-      "Bash(uv run:*)",
-      "Bash(make test:*)",
-      "Bash(make test_parallel:*)"
-    ],
-    "deny": []
-  }
-}

libs/langgraph/langgraph/func/__init__.py

@@ -151,13 +151,13 @@ def task(
 
 
         @task
-        def add_one(a: int) -> int:
+        def add_one_task(a: int) -> int:
             return a + 1
 
 
         @entrypoint()
         def add_one(numbers: list[int]) -> list[int]:
-            futures = [add_one(n) for n in numbers]
+            futures = [add_one_task(n) for n in numbers]
             results = [f.result() for f in futures]
             return results
 
@@ -173,13 +173,13 @@ def task(
 
 
         @task
-        async def add_one(a: int) -> int:
+        async def add_one_task(a: int) -> int:
             return a + 1
 
 
         @entrypoint()
         async def add_one(numbers: list[int]) -> list[int]:
-            futures = [add_one(n) for n in numbers]
+            futures = [add_one_task(n) for n in numbers]
             return asyncio.gather(*futures)
 
 

libs/langgraph/langgraph/graph/message.py

@@ -30,6 +30,7 @@ __all__ = (
     "add_messages",
     "MessagesState",
     "MessageGraph",
+    "REMOVE_ALL_MESSAGES",
 )
 
 Messages = list[MessageLikeRepresentation] | MessageLikeRepresentation

libs/langgraph/langgraph/graph/state.py

@@ -110,12 +110,20 @@ def _get_node_name(node: StateNode[Any, ContextT]) -> str:
 
 class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
     """A graph whose nodes communicate by reading and writing to a shared state.
-    The signature of each node is State -> Partial<State>.
+
+    The signature of each node is `State -> Partial<State>`.
 
     Each state key can optionally be annotated with a reducer function that
     will be used to aggregate the values of that key received from multiple nodes.
     The signature of a reducer function is `(Value, Value) -> Value`.
 
+    !!! warning
+
+        `StateGraph` is a builder class and cannot be used directly for execution.
+        You must first call `.compile()` to create an executable graph that supports
+        methods like `invoke()`, `stream()`, `astream()`, and `ainvoke()`. See the
+        `CompiledStateGraph` documentation for more details.
+
     Args:
         state_schema: The schema class that defines the state.
         context_schema: The schema class that defines the runtime context.
@@ -289,7 +297,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
         destinations: dict[str, str] | tuple[str, ...] | None = None,
         **kwargs: Unpack[DeprecatedKwargs],
     ) -> Self:
-        """Add a new node to the state graph, input schema is inferred as the state schema.
+        """Add a new node to the `StateGraph`, input schema is inferred as the state schema.
         Will take the name of the function/runnable as the node name.
         """
         ...
@@ -307,7 +315,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
         destinations: dict[str, str] | tuple[str, ...] | None = None,
         **kwargs: Unpack[DeprecatedKwargs],
     ) -> Self:
-        """Add a new node to the state graph, input schema is specified.
+        """Add a new node to the `StateGraph`, input schema is specified.
         Will take the name of the function/runnable as the node name.
         """
         ...
@@ -326,7 +334,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
         destinations: dict[str, str] | tuple[str, ...] | None = None,
         **kwargs: Unpack[DeprecatedKwargs],
     ) -> Self:
-        """Add a new node to the state graph, input schema is inferred as the state schema."""
+        """Add a new node to the `StateGraph`, input schema is inferred as the state schema."""
         ...
 
     @overload
@@ -343,7 +351,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
         destinations: dict[str, str] | tuple[str, ...] | None = None,
         **kwargs: Unpack[DeprecatedKwargs],
     ) -> Self:
-        """Add a new node to the state graph, input schema is specified."""
+        """Add a new node to the `StateGraph`, input schema is specified."""
         ...
 
     def add_node(
@@ -359,7 +367,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
         destinations: dict[str, str] | tuple[str, ...] | None = None,
         **kwargs: Unpack[DeprecatedKwargs],
     ) -> Self:
-        """Add a new node to the state graph.
+        """Add a new node to the `StateGraph`.
 
         Args:
             node: The function or runnable this node will run.
@@ -416,7 +424,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
             ```
 
         Returns:
-            Self: The instance of the state graph, allowing for method chaining.
+            Self: The instance of the `StateGraph`, allowing for method chaining.
         """
         if (retry := kwargs.get("retry", MISSING)) is not MISSING:
             warnings.warn(
@@ -571,7 +579,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
             ValueError: If the start key is `'END'` or if the start key or end key is not present in the graph.
 
         Returns:
-            Self: The instance of the state graph, allowing for method chaining.
+            Self: The instance of the `StateGraph`, allowing for method chaining.
         """
         if self.compiled:
             logger.warning(
@@ -676,7 +684,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
             ValueError: If the sequence contains duplicate node names.
 
         Returns:
-            Self: The instance of the state graph, allowing for method chaining.
+            Self: The instance of the `StateGraph`, allowing for method chaining.
         """
         if len(nodes) < 1:
             raise ValueError("Sequence requires at least one node.")
@@ -809,7 +817,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
         debug: bool = False,
         name: str | None = None,
     ) -> CompiledStateGraph[StateT, ContextT, InputT, OutputT]:
-        """Compiles the state graph into a `CompiledStateGraph` object.
+        """Compiles the `StateGraph` into a `CompiledStateGraph` object.
 
         The compiled graph implements the `Runnable` interface and can be invoked,
         streamed, batched, and run asynchronously.
@@ -826,7 +834,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
             name: The name to use for the compiled graph.
 
         Returns:
-            CompiledStateGraph: The compiled state graph.
+            CompiledStateGraph: The compiled `StateGraph`.
         """
         # assign default values
         interrupt_before = interrupt_before or []

libs/langgraph/langgraph/pregel/_algo.py

@@ -258,9 +258,11 @@ def apply_writes(
         next_version = None
     else:
         next_version = get_next_version(
-            max(checkpoint["channel_versions"].values())
-            if checkpoint["channel_versions"]
-            else None,
+            (
+                max(checkpoint["channel_versions"].values())
+                if checkpoint["channel_versions"]
+                else None
+            ),
             None,
         )
 
@@ -491,6 +493,11 @@ def prepare_next_tasks(
 PUSH_TRIGGER = (PUSH,)
 
 
+class _TaskIDFn(Protocol):
+    def __call__(self, namespace: bytes, *parts: str | bytes) -> str:
+        pass
+
+
 def prepare_single_task(
     task_path: tuple[Any, ...],
     task_id_checksum: str | None,
@@ -520,250 +527,50 @@ def prepare_single_task(
     task_id_func = _xxhash_str if checkpoint["v"] > 1 else _uuid5_str
 
     if task_path[0] == PUSH and isinstance(task_path[-1], Call):
-        # (PUSH, parent task path, idx of PUSH write, id of parent task, Call)
-        task_path_t = cast(tuple[str, tuple, int, str, Call], task_path)
-        call = task_path_t[-1]
-        proc_ = get_runnable_for_task(call.func)
-        name = proc_.name
-        if name is None:
-            raise ValueError("`call` functions must have a `__name__` attribute")
-        # create task id
-        triggers: Sequence[str] = PUSH_TRIGGER
-        checkpoint_ns = f"{parent_ns}{NS_SEP}{name}" if parent_ns else name
-        task_id = task_id_func(
-            checkpoint_id_bytes,
-            checkpoint_ns,
-            str(step),
-            name,
-            PUSH,
-            task_path_str(task_path[1]),
-            str(task_path[2]),
+        return prepare_push_task_functional(
+            cast(tuple[str, tuple, int, str, Call], task_path),
+            task_id_checksum,
+            checkpoint=checkpoint,
+            checkpoint_id_bytes=checkpoint_id_bytes,
+            pending_writes=pending_writes,
+            channels=channels,
+            managed=managed,
+            config=config,
+            step=step,
+            stop=stop,
+            for_execution=for_execution,
+            store=store,
+            checkpointer=checkpointer,
+            manager=manager,
+            cache_policy=cache_policy,
+            retry_policy=retry_policy,
+            parent_ns=parent_ns,
+            task_id_func=task_id_func,
+        )
+
+    elif task_path[0] == PUSH:
+        return prepare_push_task_send(
+            cast(tuple[str, tuple], task_path),
+            task_id_checksum,
+            checkpoint=checkpoint,
+            checkpoint_id_bytes=checkpoint_id_bytes,
+            pending_writes=pending_writes,
+            channels=channels,
+            managed=managed,
+            config=config,
+            step=step,
+            processes=processes,
+            stop=stop,
+            for_execution=for_execution,
+            store=store,
+            checkpointer=checkpointer,
+            manager=manager,
+            cache_policy=cache_policy,
+            retry_policy=retry_policy,
+            parent_ns=parent_ns,
+            task_id_func=task_id_func,
         )
-        task_checkpoint_ns = f"{checkpoint_ns}:{task_id}"
-        # we append True to the task path to indicate that a call is being
-        # made, so we should not return interrupts from this task (responsibility lies with the parent)
-        task_path = (*task_path[:3], True)
-        metadata = {
-            "langgraph_step": step,
-            "langgraph_node": name,
-            "langgraph_triggers": triggers,
-            "langgraph_path": task_path,
-            "langgraph_checkpoint_ns": task_checkpoint_ns,
-        }
-        if task_id_checksum is not None:
-            assert task_id == task_id_checksum, f"{task_id} != {task_id_checksum}"
-        if for_execution:
-            writes: deque[tuple[str, Any]] = deque()
-            cache_policy = call.cache_policy or cache_policy
-            if cache_policy:
-                args_key = cache_policy.key_func(*call.input[0], **call.input[1])
-                cache_key: CacheKey | None = CacheKey(
-                    (
-                        CACHE_NS_WRITES,
-                        (identifier(call.func) or "__dynamic__"),
-                    ),
-                    xxh3_128_hexdigest(
-                        args_key.encode() if isinstance(args_key, str) else args_key,
-                    ),
-                    cache_policy.ttl,
-                )
-            else:
-                cache_key = None
-            scratchpad = _scratchpad(
-                config[CONF].get(CONFIG_KEY_SCRATCHPAD),
-                pending_writes,
-                task_id,
-                xxh3_128_hexdigest(task_checkpoint_ns.encode()),
-                config[CONF].get(CONFIG_KEY_RESUME_MAP),
-                step,
-                stop,
-            )
-            runtime = cast(
-                Runtime, configurable.get(CONFIG_KEY_RUNTIME, DEFAULT_RUNTIME)
-            )
-            runtime = runtime.override(store=store)
-            return PregelExecutableTask(
-                name,
-                call.input,
-                proc_,
-                writes,
-                patch_config(
-                    merge_configs(config, {"metadata": metadata}),
-                    run_name=name,
-                    callbacks=call.callbacks
-                    or (manager.get_child(f"graph:step:{step}") if manager else None),
-                    configurable={
-                        CONFIG_KEY_TASK_ID: task_id,
-                        # deque.extend is thread-safe
-                        CONFIG_KEY_SEND: writes.extend,
-                        CONFIG_KEY_READ: partial(
-                            local_read,
-                            scratchpad,
-                            channels,
-                            managed,
-                            PregelTaskWrites(task_path, name, writes, triggers),
-                        ),
-                        CONFIG_KEY_CHECKPOINTER: (
-                            checkpointer or configurable.get(CONFIG_KEY_CHECKPOINTER)
-                        ),
-                        CONFIG_KEY_CHECKPOINT_MAP: {
-                            **configurable.get(CONFIG_KEY_CHECKPOINT_MAP, {}),
-                            parent_ns: checkpoint["id"],
-                        },
-                        CONFIG_KEY_CHECKPOINT_ID: None,
-                        CONFIG_KEY_CHECKPOINT_NS: task_checkpoint_ns,
-                        CONFIG_KEY_SCRATCHPAD: scratchpad,
-                        CONFIG_KEY_RUNTIME: runtime,
-                    },
-                ),
-                triggers,
-                call.retry_policy or retry_policy,
-                cache_key,
-                task_id,
-                task_path,
-            )
-        else:
-            return PregelTask(task_id, name, task_path)
-    elif task_path[0] == PUSH:
-        if len(task_path) == 2:
-            # SEND tasks, executed in superstep n+1
-            # (PUSH, idx of pending send)
-            idx = cast(int, task_path[1])
-            if not channels[TASKS].is_available():
-                return
-            sends: Sequence[Send] = channels[TASKS].get()
-            if idx < 0 or idx >= len(sends):
-                return
-            packet = sends[idx]
-            if not isinstance(packet, Send):
-                logger.warning(
-                    f"Ignoring invalid packet type {type(packet)} in pending sends"
-                )
-                return
 
-            if packet.node not in processes:
-                logger.warning(
-                    f"Ignoring unknown node name {packet.node} in pending sends"
-                )
-                return
-            # find process
-            proc = processes[packet.node]
-            proc_node = proc.node
-            if proc_node is None:
-                return
-            # create task id
-            triggers = PUSH_TRIGGER
-            checkpoint_ns = (
-                f"{parent_ns}{NS_SEP}{packet.node}" if parent_ns else packet.node
-            )
-            task_id = task_id_func(
-                checkpoint_id_bytes,
-                checkpoint_ns,
-                str(step),
-                packet.node,
-                PUSH,
-                str(idx),
-            )
-        else:
-            logger.warning(f"Ignoring invalid PUSH task path {task_path}")
-            return
-        task_checkpoint_ns = f"{checkpoint_ns}:{task_id}"
-        # we append False to the task path to indicate that a call is not being made
-        # so we should return interrupts from this task
-        task_path = (*task_path[:3], False)
-        metadata = {
-            "langgraph_step": step,
-            "langgraph_node": packet.node,
-            "langgraph_triggers": triggers,
-            "langgraph_path": task_path,
-            "langgraph_checkpoint_ns": task_checkpoint_ns,
-        }
-        if task_id_checksum is not None:
-            assert task_id == task_id_checksum, f"{task_id} != {task_id_checksum}"
-        if for_execution:
-            if proc.metadata:
-                metadata.update(proc.metadata)
-            writes = deque()
-            cache_policy = proc.cache_policy or cache_policy
-            if cache_policy:
-                args_key = cache_policy.key_func(packet.arg)
-                cache_key = CacheKey(
-                    (
-                        CACHE_NS_WRITES,
-                        (identifier(proc) or "__dynamic__"),
-                        packet.node,
-                    ),
-                    xxh3_128_hexdigest(
-                        args_key.encode() if isinstance(args_key, str) else args_key,
-                    ),
-                    cache_policy.ttl,
-                )
-            else:
-                cache_key = None
-            scratchpad = _scratchpad(
-                config[CONF].get(CONFIG_KEY_SCRATCHPAD),
-                pending_writes,
-                task_id,
-                xxh3_128_hexdigest(task_checkpoint_ns.encode()),
-                config[CONF].get(CONFIG_KEY_RESUME_MAP),
-                step,
-                stop,
-            )
-            runtime = cast(
-                Runtime, configurable.get(CONFIG_KEY_RUNTIME, DEFAULT_RUNTIME)
-            )
-            runtime = runtime.override(
-                store=store, previous=checkpoint["channel_values"].get(PREVIOUS, None)
-            )
-            additional_config: RunnableConfig = {
-                "metadata": metadata,
-                "tags": proc.tags,
-            }
-            return PregelExecutableTask(
-                packet.node,
-                packet.arg,
-                proc_node,
-                writes,
-                patch_config(
-                    merge_configs(config, additional_config),
-                    run_name=packet.node,
-                    callbacks=(
-                        manager.get_child(f"graph:step:{step}") if manager else None
-                    ),
-                    configurable={
-                        CONFIG_KEY_TASK_ID: task_id,
-                        # deque.extend is thread-safe
-                        CONFIG_KEY_SEND: writes.extend,
-                        CONFIG_KEY_READ: partial(
-                            local_read,
-                            scratchpad,
-                            channels,
-                            managed,
-                            PregelTaskWrites(task_path, packet.node, writes, triggers),
-                        ),
-                        CONFIG_KEY_CHECKPOINTER: (
-                            checkpointer or configurable.get(CONFIG_KEY_CHECKPOINTER)
-                        ),
-                        CONFIG_KEY_CHECKPOINT_MAP: {
-                            **configurable.get(CONFIG_KEY_CHECKPOINT_MAP, {}),
-                            parent_ns: checkpoint["id"],
-                        },
-                        CONFIG_KEY_CHECKPOINT_ID: None,
-                        CONFIG_KEY_CHECKPOINT_NS: task_checkpoint_ns,
-                        CONFIG_KEY_SCRATCHPAD: scratchpad,
-                        CONFIG_KEY_RUNTIME: runtime,
-                    },
-                ),
-                triggers,
-                proc.retry_policy or retry_policy,
-                cache_key,
-                task_id,
-                task_path,
-                writers=proc.flat_writers,
-                subgraphs=proc.subgraphs,
-            )
-        else:
-            return PregelTask(task_id, packet.node, task_path)
     elif task_path[0] == PULL:
         # (PULL, node name)
         name = cast(str, task_path[1])
@@ -834,7 +641,7 @@ def prepare_single_task(
                 if node := proc.node:
                     if proc.metadata:
                         metadata.update(proc.metadata)
-                    writes = deque()
+                    writes: deque[tuple[str, Any]] = deque()
                     cache_policy = proc.cache_policy or cache_policy
                     if cache_policy:
                         args_key = cache_policy.key_func(val)
@@ -845,9 +652,11 @@ def prepare_single_task(
                                 name,
                             ),
                             xxh3_128_hexdigest(
-                                args_key.encode()
-                                if isinstance(args_key, str)
-                                else args_key,
+                                (
+                                    args_key.encode()
+                                    if isinstance(args_key, str)
+                                    else args_key
+                                ),
                             ),
                             cache_policy.ttl,
                         )
@@ -870,7 +679,9 @@ def prepare_single_task(
                         node,
                         writes,
                         patch_config(
-                            merge_configs(config, additional_config),
+                            merge_configs(
+                                config, cast(RunnableConfig, additional_config)
+                            ),
                             run_name=name,
                             callbacks=(
                                 manager.get_child(f"graph:step:{step}")
@@ -919,6 +730,297 @@ def prepare_single_task(
                 return PregelTask(task_id, name, task_path[:3])
 
 
+def prepare_push_task_functional(
+    task_path: tuple[str, tuple, int, str, Call],
+    # (PUSH, parent task path, idx of PUSH write, id of parent task, Call)
+    task_id_checksum: str | None,
+    *,
+    checkpoint: Checkpoint,
+    checkpoint_id_bytes: bytes,
+    pending_writes: list[PendingWrite],
+    channels: Mapping[str, BaseChannel],
+    managed: ManagedValueMapping,
+    config: RunnableConfig,
+    step: int,
+    stop: int,
+    for_execution: bool,
+    store: BaseStore | None = None,
+    checkpointer: BaseCheckpointSaver | None = None,
+    manager: None | ParentRunManager | AsyncParentRunManager = None,
+    cache_policy: CachePolicy | None = None,
+    retry_policy: Sequence[RetryPolicy] = (),
+    parent_ns: str,
+    # namespace: bytes, *parts: str | bytes
+    task_id_func: _TaskIDFn,
+) -> PregelTask | PregelExecutableTask:
+    """Prepare a push task with an attached caller. Used for the functional API."""
+    configurable = config.get(CONF, {})
+
+    call = task_path[-1]
+    proc_ = get_runnable_for_task(call.func)
+    name = proc_.name
+    if name is None:
+        raise ValueError("`call` functions must have a `__name__` attribute")
+    # create task id
+    triggers: Sequence[str] = PUSH_TRIGGER
+    checkpoint_ns = f"{parent_ns}{NS_SEP}{name}" if parent_ns else name
+    task_id = task_id_func(
+        checkpoint_id_bytes,
+        checkpoint_ns,
+        str(step),
+        name,
+        PUSH,
+        task_path_str(task_path[1]),
+        str(task_path[2]),
+    )
+    task_checkpoint_ns = f"{checkpoint_ns}:{task_id}"
+    # we append True to the task path to indicate that a call is being
+    # made, so we should not return interrupts from this task (responsibility lies with the parent)
+    in_progress_task_path = (*task_path[:3], True)
+    metadata = {
+        "langgraph_step": step,
+        "langgraph_node": name,
+        "langgraph_triggers": triggers,
+        "langgraph_path": in_progress_task_path,
+        "langgraph_checkpoint_ns": task_checkpoint_ns,
+    }
+    if task_id_checksum is not None:
+        assert task_id == task_id_checksum, f"{task_id} != {task_id_checksum}"
+    if for_execution:
+        writes: deque[tuple[str, Any]] = deque()
+        cache_policy = call.cache_policy or cache_policy
+        if cache_policy:
+            args_key = cache_policy.key_func(*call.input[0], **call.input[1])
+            cache_key: CacheKey | None = CacheKey(
+                (
+                    CACHE_NS_WRITES,
+                    (identifier(call.func) or "__dynamic__"),
+                ),
+                xxh3_128_hexdigest(
+                    args_key.encode() if isinstance(args_key, str) else args_key,
+                ),
+                cache_policy.ttl,
+            )
+        else:
+            cache_key = None
+        scratchpad = _scratchpad(
+            configurable.get(CONFIG_KEY_SCRATCHPAD),
+            pending_writes,
+            task_id,
+            xxh3_128_hexdigest(task_checkpoint_ns.encode()),
+            configurable.get(CONFIG_KEY_RESUME_MAP),
+            step,
+            stop,
+        )
+        runtime = cast(Runtime, configurable.get(CONFIG_KEY_RUNTIME, DEFAULT_RUNTIME))
+        runtime = runtime.override(store=store)
+        return PregelExecutableTask(
+            name,
+            call.input,
+            proc_,
+            writes,
+            patch_config(
+                merge_configs(config, {"metadata": metadata}),
+                run_name=name,
+                callbacks=call.callbacks
+                or (manager.get_child(f"graph:step:{step}") if manager else None),
+                configurable={
+                    CONFIG_KEY_TASK_ID: task_id,
+                    # deque.extend is thread-safe
+                    CONFIG_KEY_SEND: writes.extend,
+                    CONFIG_KEY_READ: partial(
+                        local_read,
+                        scratchpad,
+                        channels,
+                        managed,
+                        PregelTaskWrites(in_progress_task_path, name, writes, triggers),
+                    ),
+                    CONFIG_KEY_CHECKPOINTER: (
+                        checkpointer or configurable.get(CONFIG_KEY_CHECKPOINTER)
+                    ),
+                    CONFIG_KEY_CHECKPOINT_MAP: {
+                        **configurable.get(CONFIG_KEY_CHECKPOINT_MAP, {}),
+                        parent_ns: checkpoint["id"],
+                    },
+                    CONFIG_KEY_CHECKPOINT_ID: None,
+                    CONFIG_KEY_CHECKPOINT_NS: task_checkpoint_ns,
+                    CONFIG_KEY_SCRATCHPAD: scratchpad,
+                    CONFIG_KEY_RUNTIME: runtime,
+                },
+            ),
+            triggers,
+            call.retry_policy or retry_policy,
+            cache_key,
+            task_id,
+            in_progress_task_path,
+        )
+    else:
+        return PregelTask(task_id, name, in_progress_task_path)
+
+
+def prepare_push_task_send(
+    task_path: tuple[str, tuple],
+    # (PUSH, parent task path)
+    task_id_checksum: str | None,
+    *,
+    checkpoint: Checkpoint,
+    checkpoint_id_bytes: bytes,
+    pending_writes: list[PendingWrite],
+    channels: Mapping[str, BaseChannel],
+    managed: ManagedValueMapping,
+    config: RunnableConfig,
+    step: int,
+    stop: int,
+    for_execution: bool,
+    store: BaseStore | None = None,
+    checkpointer: BaseCheckpointSaver | None = None,
+    manager: None | ParentRunManager | AsyncParentRunManager = None,
+    cache_policy: CachePolicy | None = None,
+    retry_policy: Sequence[RetryPolicy] = (),
+    parent_ns: str,
+    task_id_func: _TaskIDFn,
+    processes: Mapping[str, PregelNode],
+) -> PregelTask | PregelExecutableTask | None:
+    if len(task_path) == 2:
+        # SEND tasks, executed in superstep n+1
+        # (PUSH, idx of pending send)
+        idx = cast(int, task_path[1])
+        if not channels[TASKS].is_available():
+            return
+        sends: Sequence[Send] = channels[TASKS].get()
+        if idx < 0 or idx >= len(sends):
+            return
+        packet = sends[idx]
+        if not isinstance(packet, Send):
+            logger.warning(
+                f"Ignoring invalid packet type {type(packet)} in pending sends"
+            )
+            return
+
+        if packet.node not in processes:
+            logger.warning(f"Ignoring unknown node name {packet.node} in pending sends")
+            return
+        # find process
+        proc = processes[packet.node]
+        proc_node = proc.node
+        if proc_node is None:
+            return
+        # create task id
+        triggers = PUSH_TRIGGER
+        checkpoint_ns = (
+            f"{parent_ns}{NS_SEP}{packet.node}" if parent_ns else packet.node
+        )
+        task_id = task_id_func(
+            checkpoint_id_bytes,
+            checkpoint_ns,
+            str(step),
+            packet.node,
+            PUSH,
+            str(idx),
+        )
+    else:
+        logger.warning(f"Ignoring invalid PUSH task path {task_path}")
+        return
+    configurable = config.get(CONF, {})
+    task_checkpoint_ns = f"{checkpoint_ns}:{task_id}"
+    # we append False to the task path to indicate that a call is not being made
+    # so we should return interrupts from this task
+    translated_task_path = (*task_path[:3], False)
+    metadata = {
+        "langgraph_step": step,
+        "langgraph_node": packet.node,
+        "langgraph_triggers": triggers,
+        "langgraph_path": translated_task_path,
+        "langgraph_checkpoint_ns": task_checkpoint_ns,
+    }
+    if task_id_checksum is not None:
+        assert task_id == task_id_checksum, f"{task_id} != {task_id_checksum}"
+    if for_execution:
+        if proc.metadata:
+            metadata.update(proc.metadata)
+        writes: deque[tuple[str, Any]] = deque()
+        cache_policy = proc.cache_policy or cache_policy
+        if cache_policy:
+            args_key = cache_policy.key_func(packet.arg)
+            cache_key = CacheKey(
+                (
+                    CACHE_NS_WRITES,
+                    (identifier(proc) or "__dynamic__"),
+                    packet.node,
+                ),
+                xxh3_128_hexdigest(
+                    args_key.encode() if isinstance(args_key, str) else args_key,
+                ),
+                cache_policy.ttl,
+            )
+        else:
+            cache_key = None
+        scratchpad = _scratchpad(
+            config[CONF].get(CONFIG_KEY_SCRATCHPAD),
+            pending_writes,
+            task_id,
+            xxh3_128_hexdigest(task_checkpoint_ns.encode()),
+            config[CONF].get(CONFIG_KEY_RESUME_MAP),
+            step,
+            stop,
+        )
+        runtime = cast(Runtime, configurable.get(CONFIG_KEY_RUNTIME, DEFAULT_RUNTIME))
+        runtime = runtime.override(
+            store=store, previous=checkpoint["channel_values"].get(PREVIOUS, None)
+        )
+        additional_config: RunnableConfig = {
+            "metadata": metadata,
+            "tags": proc.tags,
+        }
+        return PregelExecutableTask(
+            packet.node,
+            packet.arg,
+            proc_node,
+            writes,
+            patch_config(
+                merge_configs(config, additional_config),
+                run_name=packet.node,
+                callbacks=(
+                    manager.get_child(f"graph:step:{step}") if manager else None
+                ),
+                configurable={
+                    CONFIG_KEY_TASK_ID: task_id,
+                    # deque.extend is thread-safe
+                    CONFIG_KEY_SEND: writes.extend,
+                    CONFIG_KEY_READ: partial(
+                        local_read,
+                        scratchpad,
+                        channels,
+                        managed,
+                        PregelTaskWrites(
+                            translated_task_path, packet.node, writes, triggers
+                        ),
+                    ),
+                    CONFIG_KEY_CHECKPOINTER: (
+                        checkpointer or configurable.get(CONFIG_KEY_CHECKPOINTER)
+                    ),
+                    CONFIG_KEY_CHECKPOINT_MAP: {
+                        **configurable.get(CONFIG_KEY_CHECKPOINT_MAP, {}),
+                        parent_ns: checkpoint["id"],
+                    },
+                    CONFIG_KEY_CHECKPOINT_ID: None,
+                    CONFIG_KEY_CHECKPOINT_NS: task_checkpoint_ns,
+                    CONFIG_KEY_SCRATCHPAD: scratchpad,
+                    CONFIG_KEY_RUNTIME: runtime,
+                },
+            ),
+            triggers,
+            proc.retry_policy or retry_policy,
+            cache_key,
+            task_id,
+            translated_task_path,
+            writers=proc.flat_writers,
+            subgraphs=proc.subgraphs,
+        )
+    else:
+        return PregelTask(task_id, packet.node, translated_task_path)
+
+
 def checkpoint_null_version(
     checkpoint: Checkpoint,
 ) -> V | None:

libs/langgraph/langgraph/pregel/_loop.py

@@ -459,9 +459,6 @@ class PregelLoop:
     def tick(self) -> bool:
         """Execute a single iteration of the Pregel loop.
 
-        Args:
-            input_keys: The key(s) to read input from.
-
         Returns:
             True if more iterations are needed.
         """
@@ -769,6 +766,7 @@ class PregelLoop:
             ]
             self.checkpoint["channel_values"][TASKS] = sanitized_tasks
         # bail if no checkpointer
+
         if do_checkpoint and self._checkpointer_put_after_previous is not None:
             self.prev_checkpoint_config = (
                 self.checkpoint_config
@@ -938,8 +936,15 @@ class PregelLoop:
                 stream_modes = self.stream.modes if self.stream else []
                 if "updates" in stream_modes:
                     self._emit("updates", lambda: iter(interrupts))
-                elif "values" in stream_modes:
-                    self._emit("values", lambda: iter(interrupts))
+                if "values" in stream_modes:
+                    current_values = read_channels(self.channels, self.output_keys)
+                    # self.output_keys is a sequence, stream chunk contains entire state and interrupts
+                    if isinstance(current_values, dict):
+                        current_values[INTERRUPT] = interrupts[0][INTERRUPT]
+                        self._emit("values", lambda: iter([current_values]))
+                    # self.output_keys is a string, stream chunk contains only interrupts
+                    else:
+                        self._emit("values", lambda: iter(interrupts))
             elif writes[0][0] != ERROR:
                 self._emit(
                     "updates",

libs/langgraph/langgraph/pregel/main.py

@@ -1702,7 +1702,9 @@ class Pregel(
             # we use the task id generated by prepare_next_tasks
             node_to_task_ids: dict[str, deque[str]] = defaultdict(deque)
             if saved is not None and saved.pending_writes is not None:
-                # tasks for this checkpoint
+                # we call prepare_next_tasks to discover the task IDs that
+                # would have been generated, so we can reuse them and
+                # properly populate task.result in state history
                 next_tasks = prepare_next_tasks(
                     checkpoint,
                     saved.pending_writes,
@@ -1721,32 +1723,6 @@ class Pregel(
                 for t in next_tasks.values():
                     node_to_task_ids[t.name].append(t.id)
 
-                # apply null writes
-                if null_writes := [
-                    w[1:] for w in saved.pending_writes or [] if w[0] == NULL_TASK_ID
-                ]:
-                    apply_writes(
-                        checkpoint,
-                        channels,
-                        [PregelTaskWrites((), INPUT, null_writes, [])],
-                        checkpointer.get_next_version,
-                        self.trigger_to_nodes,
-                    )
-                # apply writes
-                for tid, k, v in saved.pending_writes:
-                    if k in (ERROR, INTERRUPT):
-                        continue
-                    if tid not in next_tasks:
-                        continue
-                    next_tasks[tid].writes.append((k, v))
-                if tasks := [t for t in next_tasks.values() if t.writes]:
-                    apply_writes(
-                        checkpoint,
-                        channels,
-                        tasks,
-                        checkpointer.get_next_version,
-                        self.trigger_to_nodes,
-                    )
             valid_updates: list[tuple[str, dict[str, Any] | None, str | None]] = []
             if len(updates) == 1:
                 values, as_node, task_id = updates[0]
@@ -2167,7 +2143,9 @@ class Pregel(
             # we use the task id generated by prepare_next_tasks
             node_to_task_ids: dict[str, deque[str]] = defaultdict(deque)
             if saved is not None and saved.pending_writes is not None:
-                # tasks for this checkpoint
+                # we call prepare_next_tasks to discover the task IDs that
+                # would have been generated, so we can reuse them and
+                # properly populate task.result in state history
                 next_tasks = prepare_next_tasks(
                     checkpoint,
                     saved.pending_writes,
@@ -2186,31 +2164,6 @@ class Pregel(
                 for t in next_tasks.values():
                     node_to_task_ids[t.name].append(t.id)
 
-                # apply null writes
-                if null_writes := [
-                    w[1:] for w in saved.pending_writes or [] if w[0] == NULL_TASK_ID
-                ]:
-                    apply_writes(
-                        checkpoint,
-                        channels,
-                        [PregelTaskWrites((), INPUT, null_writes, [])],
-                        checkpointer.get_next_version,
-                        self.trigger_to_nodes,
-                    )
-                for tid, k, v in saved.pending_writes:
-                    if k in (ERROR, INTERRUPT):
-                        continue
-                    if tid not in next_tasks:
-                        continue
-                    next_tasks[tid].writes.append((k, v))
-                if tasks := [t for t in next_tasks.values() if t.writes]:
-                    apply_writes(
-                        checkpoint,
-                        channels,
-                        tasks,
-                        checkpointer.get_next_version,
-                        self.trigger_to_nodes,
-                    )
             valid_updates: list[tuple[str, dict[str, Any] | None, str | None]] = []
             if len(updates) == 1:
                 values, as_node, task_id = updates[0]
@@ -2401,7 +2354,7 @@ class Pregel(
             validate_keys(output_keys, self.channels)
         interrupt_before = interrupt_before or self.interrupt_before_nodes
         interrupt_after = interrupt_after or self.interrupt_after_nodes
-        if not isinstance(stream_mode, list):
+        if isinstance(stream_mode, str):
             stream_modes = {stream_mode}
         else:
             stream_modes = set(stream_mode)
@@ -2478,11 +2431,12 @@ class Pregel(
                     Will be emitted as 2-tuples `(LLM token, metadata)`.
                 - `"checkpoints"`: Emit an event when a checkpoint is created, in the same format as returned by `get_state()`.
                 - `"tasks"`: Emit events when tasks start and finish, including their results and errors.
+                - `"debug"`: Emit debug events with as much information as possible for each step.
 
                 You can pass a list as the `stream_mode` parameter to stream multiple modes at once.
                 The streamed outputs will be tuples of `(mode, data)`.
 
-                See [LangGraph streaming guide](https://langchain-ai.github.io/langgraph/how-tos/streaming/) for more details.
+                See [LangGraph streaming guide](https://docs.langchain.com/oss/python/langgraph/streaming) for more details.
             print_mode: Accepts the same values as `stream_mode`, but only prints the output to the console, for debugging purposes. Does not affect the output of the graph in any way.
             output_keys: The keys to stream, defaults to all non-context channels.
             interrupt_before: Nodes to interrupt before, defaults to all nodes in the graph.
@@ -2499,7 +2453,7 @@ class Pregel(
                 where `namespace` is a tuple with the path to the node where a subgraph is invoked,
                 e.g. `("parent_node:<task_id>", "child_node:<task_id>")`.
 
-                See [LangGraph streaming guide](https://langchain-ai.github.io/langgraph/how-tos/streaming/) for more details.
+                See [LangGraph streaming guide](https://docs.langchain.com/oss/python/langgraph/streaming) for more details.
 
         Yields:
             The output of each step in the graph. The output shape depends on the `stream_mode`.
@@ -2744,12 +2698,14 @@ class Pregel(
                 - `"custom"`: Emit custom data from inside nodes or tasks using `StreamWriter`.
                 - `"messages"`: Emit LLM messages token-by-token together with metadata for any LLM invocations inside nodes or tasks.
                     Will be emitted as 2-tuples `(LLM token, metadata)`.
+                - `"checkpoints"`: Emit an event when a checkpoint is created, in the same format as returned by `get_state()`.
+                - `"tasks"`: Emit events when tasks start and finish, including their results and errors.
                 - `"debug"`: Emit debug events with as much information as possible for each step.
 
                 You can pass a list as the `stream_mode` parameter to stream multiple modes at once.
                 The streamed outputs will be tuples of `(mode, data)`.
 
-                See [LangGraph streaming guide](https://langchain-ai.github.io/langgraph/how-tos/streaming/) for more details.
+                See [LangGraph streaming guide](https://docs.langchain.com/oss/python/langgraph/streaming) for more details.
             print_mode: Accepts the same values as `stream_mode`, but only prints the output to the console, for debugging purposes. Does not affect the output of the graph in any way.
             output_keys: The keys to stream, defaults to all non-context channels.
             interrupt_before: Nodes to interrupt before, defaults to all nodes in the graph.
@@ -2766,7 +2722,7 @@ class Pregel(
                 where `namespace` is a tuple with the path to the node where a subgraph is invoked,
                 e.g. `("parent_node:<task_id>", "child_node:<task_id>")`.
 
-                See [LangGraph streaming guide](https://langchain-ai.github.io/langgraph/how-tos/streaming/) for more details.
+                See [LangGraph streaming guide](https://docs.langchain.com/oss/python/langgraph/streaming) for more details.
 
         Yields:
             The output of each step in the graph. The output shape depends on the `stream_mode`.
@@ -3148,31 +3104,30 @@ class Pregel(
         durability: Durability | None = None,
         **kwargs: Any,
     ) -> dict[str, Any] | Any:
-        """Asynchronously invoke the graph on a single input.
+        """Asynchronously run the graph with a single input and config.
 
         Args:
-            input: The input data for the computation. It can be a dictionary or any other type.
-            config: The configuration for the computation.
+            input: The input data for the graph. It can be a dictionary or any other type.
+            config: The configuration for the graph run.
             context: The static context to use for the run.
                 !!! version-added "Added in version 0.6.0"
-            stream_mode: The stream mode for the computation.
+            stream_mode: The stream mode for the graph run.
             print_mode: Accepts the same values as `stream_mode`, but only prints the output to the console, for debugging purposes. Does not affect the output of the graph in any way.
-            output_keys: The output keys to include in the result.
-            interrupt_before: The nodes to interrupt before.
-            interrupt_after: The nodes to interrupt after.
+            output_keys: The output keys to retrieve from the graph run.
+            interrupt_before: The nodes to interrupt the graph run before.
+            interrupt_after: The nodes to interrupt the graph run after.
             durability: The durability mode for the graph execution, defaults to `"async"`.
                 Options are:
 
                 - `"sync"`: Changes are persisted synchronously before the next step starts.
                 - `"async"`: Changes are persisted asynchronously while the next step executes.
                 - `"exit"`: Changes are persisted only when the graph exits.
-            **kwargs: Additional keyword arguments.
+            **kwargs: Additional keyword arguments to pass to the graph run.
 
         Returns:
-            The result of the computation. If `stream_mode` is `"values"`, it returns the latest value.
-            If `stream_mode` is `"chunks"`, it returns a list of chunks.
+            The output of the graph run. If `stream_mode` is `"values"`, it returns the latest output.
+            If `stream_mode` is not `"values"`, it returns a list of output chunks.
         """
-
         output_keys = output_keys if output_keys is not None else self.output_channels
 
         latest: dict[str, Any] | Any = None

libs/langgraph/langgraph/runtime.py

@@ -111,7 +111,7 @@ class Runtime(Generic[ContextT]):
             stream_writer=other.stream_writer
             if other.stream_writer is not _no_op_stream_writer
             else self.stream_writer,
-            previous=other.previous or self.previous,
+            previous=self.previous if other.previous is None else other.previous,
         )
 
     def override(

libs/langgraph/langgraph/typing.py

@@ -31,13 +31,13 @@ ContextT_contra = TypeVar(
 )
 
 InputT = TypeVar("InputT", bound=StateLike, default=StateT)
-"""Type variable used to represent the input to a state graph.
+"""Type variable used to represent the input to a `StateGraph`.
 
 Defaults to `StateT`.
 """
 
 OutputT = TypeVar("OutputT", bound=StateLike, default=StateT)
-"""Type variable used to represent the output of a state graph.
+"""Type variable used to represent the output of a `StateGraph`.
 
 Defaults to `StateT`.
 """

libs/langgraph/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph"
-version = "1.0.2"
+version = "1.0.3"
 description = "Building stateful, multi-actor applications with LLMs"
 authors = []
 requires-python = ">=3.10"
@@ -32,8 +32,15 @@ dependencies = [
     "pydantic>=2.7.4",
 ]
 
+
 [project.urls]
-Repository = "https://www.github.com/langchain-ai/langgraph"
+Homepage = "https://docs.langchain.com/oss/python/langgraph/overview"
+Documentation = "https://reference.langchain.com/python/langgraph/"
+Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/langgraph"
+Changelog = "https://github.com/langchain-ai/langgraph/releases"
+Twitter = "https://x.com/LangChainAI"
+Slack = "https://www.langchain.com/join-community"
+Reddit = "https://www.reddit.com/r/LangChain/"
 
 [dependency-groups]
 test = [

libs/langgraph/tests/test_pregel.py

@@ -8422,23 +8422,55 @@ def test_null_resume_disallowed_with_multiple_interrupts(
     }
 
 
-def test_interrupt_stream_mode_values():
-    """Test that interrupts are surfaced when steam_mode='values'"""
+def test_interrupt_stream_mode_values(sync_checkpointer: BaseCheckpointSaver):
+    """Test that interrupts are surfaced on 'values' stream mode"""
 
     class State(TypedDict):
+        robot_input: str
         human_input: str
 
+    def robot_input_node(state: State) -> State:
+        return {"robot_input": "beep boop i am a robot"}
+
     def human_input_node(state: State) -> Command:
         human_input = interrupt("interrupt")
         return Command(update={"human_input": human_input})
 
     builder = StateGraph(State)
+    builder.add_node(robot_input_node)
     builder.add_node(human_input_node)
-    builder.add_edge(START, "human_input_node")
-    app = builder.compile()
+    builder.add_edge(START, "robot_input_node")
+    builder.add_edge("robot_input_node", "human_input_node")
+    app = builder.compile(checkpointer=sync_checkpointer)
+    config = {"configurable": {"thread_id": str(uuid.uuid4())}}
 
-    result = [*app.stream(State(), stream_mode="values")]
-    assert "__interrupt__" in result[-1]
+    result = [*app.stream(State(), config, stream_mode=["updates", "values"])]
+    assert len(result) == 4
+    assert result == [
+        ("updates", {"robot_input_node": {"robot_input": "beep boop i am a robot"}}),
+        ("values", {"robot_input": "beep boop i am a robot"}),
+        ("updates", {"__interrupt__": (Interrupt(value="interrupt", id=AnyStr()),)}),
+        (
+            "values",
+            {
+                "robot_input": "beep boop i am a robot",
+                "__interrupt__": (Interrupt(value="interrupt", id=AnyStr()),),
+            },
+        ),
+    ]
+    resume_result = [
+        *app.stream(
+            Command(resume="i am a human"), config, stream_mode=["updates", "values"]
+        )
+    ]
+    assert resume_result == [
+        ("values", {"robot_input": "beep boop i am a robot"}),
+        ("updates", {"human_input_node": {"human_input": "i am a human"}}),
+        (
+            "values",
+            {"robot_input": "beep boop i am a robot", "human_input": "i am a human"},
+        ),
+    ]
 
 
 def test_supersteps_populate_task_results(
@@ -8805,3 +8837,43 @@ def test_overwrite_parallel_error(
         InvalidUpdateError, match="Can receive only one Overwrite value per super-step."
     ):
         graph.invoke({"messages": ["START"]}, config)
+
+
+def test_fork_does_not_apply_pending_writes(
+    sync_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Test that forking with update_state does not apply pending writes from original execution."""
+
+    class State(TypedDict):
+        value: Annotated[int, operator.add]
+
+    def node_a(state: State) -> State:
+        return {"value": 10}
+
+    def node_b(state: State) -> State:
+        return {"value": 100}
+
+    graph = (
+        StateGraph(State)
+        .add_node("node_a", node_a)
+        .add_node("node_b", node_b)
+        .add_edge(START, "node_a")
+        .add_edge("node_a", "node_b")
+        .compile(checkpointer=sync_checkpointer)
+    )
+
+    thread1 = {"configurable": {"thread_id": "1"}}
+    graph.invoke({"value": 1}, thread1)
+
+    history = list(graph.get_state_history(thread1))
+    checkpoint_before_a = next(s for s in history if s.next == ("node_a",))
+
+    fork_config = graph.update_state(
+        checkpoint_before_a.config, {"value": 20}, as_node="node_a"
+    )
+
+    # Continue from fork (should run node_b)
+    result = graph.invoke(None, fork_config)
+
+    # Should be: 1 (input) + 20 (forked node_a) + 100 (node_b) = 121
+    assert result == {"value": 121}

libs/langgraph/tests/test_pregel_async.py

@@ -9196,6 +9196,64 @@ async def test_astream_waiter_cleanup_on_cancel(
     assert all(t.done() for t in recorded_tasks)
 
 
+@NEEDS_CONTEXTVARS
+async def test_interrupt_stream_mode_values(async_checkpointer: BaseCheckpointSaver):
+    """Test that interrupts are surfaced on 'values' stream mode"""
+
+    class State(TypedDict):
+        robot_input: str
+        human_input: str
+
+    def robot_input_node(state: State) -> State:
+        return {"robot_input": "beep boop i am a robot"}
+
+    def human_input_node(state: State) -> Command:
+        human_input = interrupt("interrupt")
+        return Command(update={"human_input": human_input})
+
+    builder = StateGraph(State)
+    builder.add_node(robot_input_node)
+    builder.add_node(human_input_node)
+    builder.add_edge(START, "robot_input_node")
+    builder.add_edge("robot_input_node", "human_input_node")
+    app = builder.compile(checkpointer=async_checkpointer)
+    config = {"configurable": {"thread_id": str(uuid.uuid4())}}
+
+    result = [
+        (mode, e)
+        async for mode, e in app.astream(
+            State(), config, stream_mode=["updates", "values"]
+        )
+    ]
+    assert len(result) == 4
+    assert result == [
+        ("updates", {"robot_input_node": {"robot_input": "beep boop i am a robot"}}),
+        ("values", {"robot_input": "beep boop i am a robot"}),
+        ("updates", {"__interrupt__": (Interrupt(value="interrupt", id=AnyStr()),)}),
+        (
+            "values",
+            {
+                "robot_input": "beep boop i am a robot",
+                "__interrupt__": (Interrupt(value="interrupt", id=AnyStr()),),
+            },
+        ),
+    ]
+    resume_result = [
+        (mode, e)
+        async for mode, e in app.astream(
+            Command(resume="i am a human"), config, stream_mode=["updates", "values"]
+        )
+    ]
+    assert resume_result == [
+        ("values", {"robot_input": "beep boop i am a robot"}),
+        ("updates", {"human_input_node": {"human_input": "i am a human"}}),
+        (
+            "values",
+            {"robot_input": "beep boop i am a robot", "human_input": "i am a human"},
+        ),
+    ]
+
+
 async def test_supersteps_populate_task_results(
     async_checkpointer: BaseCheckpointSaver,
 ) -> None:
@@ -9249,3 +9307,41 @@ async def test_supersteps_populate_task_results(
 
     assert bulk_start_result == ref_start_result == {"num": 1, "text": "one"}
     assert bulk_double_result == ref_double_result == {"num": 2, "text": "oneone"}
+
+
+async def test_fork_does_not_apply_pending_writes(
+    async_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Test that forking with aupdate_state does not apply pending writes from original execution."""
+
+    class State(TypedDict):
+        value: Annotated[int, operator.add]
+
+    def node_a(state: State) -> State:
+        return {"value": 10}
+
+    def node_b(state: State) -> State:
+        return {"value": 100}
+
+    graph = (
+        StateGraph(State)
+        .add_node("node_a", node_a)
+        .add_node("node_b", node_b)
+        .add_edge(START, "node_a")
+        .add_edge("node_a", "node_b")
+        .compile(checkpointer=async_checkpointer)
+    )
+
+    thread1 = {"configurable": {"thread_id": "1"}}
+    await graph.ainvoke({"value": 1}, thread1)
+
+    history = [c async for c in graph.aget_state_history(thread1)]
+    checkpoint_before_a = next(s for s in history if s.next == ("node_a",))
+
+    fork_config = await graph.aupdate_state(
+        checkpoint_before_a.config, {"value": 20}, as_node="node_a"
+    )
+    result = await graph.ainvoke(None, fork_config)
+
+    # 1 (input) + 20 (forked node_a) + 100 (node_b) = 121
+    assert result == {"value": 121}

libs/langgraph/uv.lock

@@ -1345,7 +1345,7 @@ wheels = [
 
 [[package]]
 name = "langgraph"
-version = "1.0.2"
+version = "1.0.3"
 source = { editable = "." }
 dependencies = [
     { name = "langchain-core" },
@@ -1571,7 +1571,7 @@ test = [
 
 [[package]]
 name = "langgraph-checkpoint-postgres"
-version = "3.0.0"
+version = "3.0.1"
 source = { editable = "../checkpoint-postgres" }
 dependencies = [
     { name = "langgraph-checkpoint" },
@@ -1710,7 +1710,7 @@ test = [
 
 [[package]]
 name = "langgraph-prebuilt"
-version = "1.0.2"
+version = "1.0.5"
 source = { editable = "../prebuilt" }
 dependencies = [
     { name = "langchain-core" },
@@ -1794,6 +1794,7 @@ requires-dist = [
 dev = [
     { name = "codespell" },
     { name = "mypy" },
+    { name = "pydantic", specifier = ">=2.12.4" },
     { name = "pytest" },
     { name = "pytest-asyncio" },
     { name = "pytest-mock" },

libs/prebuilt/.claude/settings.local.json

@@ -0,0 +1,21 @@
+{
+  "permissions": {
+    "allow": [
+      "Bash(make test:*)",
+      "Bash(uv run pytest:*)",
+      "Bash(LANGGRAPH_TEST_FAST=0 make start-services:*)",
+      "Bash(LANGGRAPH_TEST_FAST=0 uv run:*)",
+      "Bash(EXIT_CODE=$?)",
+      "Bash(make stop-services:*)",
+      "Bash(exit $EXIT_CODE)",
+      "Read(//Users/sydney_runkle/oss/langgraph/**)",
+      "Bash(python3:*)",
+      "Bash(find:*)",
+      "Bash(python -m pytest:*)",
+      "Bash(python:*)",
+      "Read(//tmp/**)"
+    ],
+    "deny": [],
+    "ask": []
+  }
+}

libs/prebuilt/langgraph/prebuilt/chat_agent_executor.py

@@ -63,7 +63,7 @@ class AgentState(TypedDict):
 
 
 @deprecated(
-    "AgentStatePydantic has been moved to `langchain.agents`. Please update your import to `from langchain.agents import AgentStatePydantic`.",
+    "AgentStatePydantic has been deprecated in favor of AgentState in `langchain.agents`.",
     category=LangGraphDeprecatedSinceV10,
 )
 class AgentStatePydantic(BaseModel):
@@ -78,11 +78,11 @@ with warnings.catch_warnings():
     warnings.filterwarnings(
         "ignore",
         category=LangGraphDeprecatedSinceV10,
-        message="AgentState has been moved to langchain.agents.*",
+        message="AgentState has been moved to `langchain.agents`.*",
     )
 
     @deprecated(
-        "AgentStateWithStructuredResponse has been moved to `langchain.agents`. Please update your import to `from langchain.agents import AgentStateWithStructuredResponse`.",
+        "AgentStateWithStructuredResponse has been deprecated in favor of AgentState in `langchain.agents`.",
         category=LangGraphDeprecatedSinceV10,
     )
     class AgentStateWithStructuredResponse(AgentState):
@@ -95,11 +95,11 @@ with warnings.catch_warnings():
     warnings.filterwarnings(
         "ignore",
         category=LangGraphDeprecatedSinceV10,
-        message="AgentStatePydantic has been moved to langchain.agents.*",
+        message="AgentStatePydantic has been deprecated in favor of AgentState in `langchain.agents`.",
     )
 
     @deprecated(
-        "AgentStateWithStructuredResponsePydantic has been moved to `langchain.agents`. Please update your import to `from langchain.agents import AgentStateWithStructuredResponsePydantic`.",
+        "AgentStateWithStructuredResponsePydantic has been deprecated in favor of AgentState in `langchain.agents`.",
         category=LangGraphDeprecatedSinceV10,
     )
     class AgentStateWithStructuredResponsePydantic(AgentStatePydantic):

libs/prebuilt/langgraph/prebuilt/tool_node.py

@@ -142,6 +142,25 @@ class ToolCallRequest:
     state: Any
     runtime: ToolRuntime
 
+    def __setattr__(self, name: str, value: Any) -> None:
+        """Raise deprecation warning when setting attributes directly.
+
+        Direct attribute assignment is deprecated. Use the `override()` method instead.
+        """
+        import warnings
+
+        # Allow setting attributes during initialization
+        if not hasattr(self, "__dataclass_fields__") or not hasattr(self, name):
+            object.__setattr__(self, name, value)
+        else:
+            warnings.warn(
+                f"Setting attribute '{name}' on ToolCallRequest is deprecated. "
+                "Use the override() method instead to create a new instance with modified values.",
+                DeprecationWarning,
+                stacklevel=2,
+            )
+            object.__setattr__(self, name, value)
+
     def override(
         self, **overrides: Unpack[_ToolCallRequestOverrides]
     ) -> ToolCallRequest:
@@ -202,8 +221,9 @@ Examples:
 
     ```python
     def handler(request, execute):
-        request.tool_call["args"]["value"] *= 2
-        return execute(request)
+        modified_call = {**request.tool_call, "args": {**request.tool_call["args"], "value": request.tool_call["args"]["value"] * 2}}
+        modified_request = request.override(tool_call=modified_call)
+        return execute(modified_request)
     ```
 
     Retry on error (execute multiple times):
@@ -479,9 +499,7 @@ def _infer_handled_types(handler: Callable[..., str]) -> tuple[type[Exception],
 
 def _filter_validation_errors(
     validation_error: ValidationError,
-    tool_to_state_args: dict[str, str | None],
-    tool_to_store_arg: str | None,
-    tool_to_runtime_arg: str | None,
+    injected_args: _InjectedArgs | None,
 ) -> list[ErrorDetails]:
     """Filter validation errors to only include LLM-controlled arguments.
 
@@ -496,25 +514,28 @@ def _filter_validation_errors(
 
     Args:
         validation_error: The Pydantic ValidationError raised during tool invocation.
-        tool_to_state_args: Mapping of state argument names to state field names.
-        tool_to_store_arg: Name of the store argument, if any.
-        tool_to_runtime_arg: Name of the runtime argument, if any.
+        injected_args: The _InjectedArgs structure containing all injected arguments,
+            or None if there are no injected arguments.
 
     Returns:
         List of ErrorDetails containing only errors for LLM-controlled arguments,
         with system-injected argument values removed from the input field.
     """
-    injected_args = set(tool_to_state_args.keys())
-    if tool_to_store_arg:
-        injected_args.add(tool_to_store_arg)
-    if tool_to_runtime_arg:
-        injected_args.add(tool_to_runtime_arg)
+    # Collect all injected argument names
+    injected_arg_names: set[str] = set()
+    if injected_args:
+        if injected_args.state:
+            injected_arg_names.update(injected_args.state.keys())
+        if injected_args.store:
+            injected_arg_names.add(injected_args.store)
+        if injected_args.runtime:
+            injected_arg_names.add(injected_args.runtime)
 
     filtered_errors: list[ErrorDetails] = []
     for error in validation_error.errors():
         # Check if error location contains any injected argument
         # error['loc'] is a tuple like ('field_name',) or ('field_name', 'nested_field')
-        if error["loc"] and error["loc"][0] not in injected_args:
+        if error["loc"] and error["loc"][0] not in injected_arg_names:
             # Create a copy of the error dict to avoid mutating the original
             error_copy: dict[str, Any] = {**error}
 
@@ -522,7 +543,7 @@ def _filter_validation_errors(
             if isinstance(error_copy.get("input"), dict):
                 input_dict = error_copy["input"]
                 input_copy = {
-                    k: v for k, v in input_dict.items() if k not in injected_args
+                    k: v for k, v in input_dict.items() if k not in injected_arg_names
                 }
                 error_copy["input"] = input_copy
 
@@ -532,6 +553,60 @@ def _filter_validation_errors(
     return filtered_errors
 
 
+@dataclass
+class _InjectedArgs:
+    """Internal structure for tracking injected arguments for a tool.
+
+    This data structure is built once during ToolNode initialization by analyzing
+    the tool's signature and args schema, then reused during execution for efficient
+    injection without repeated reflection.
+
+    The structure maps from tool parameter names to their injection sources, enabling
+    the ToolNode to know exactly which arguments need to be injected and where to
+    get their values from.
+
+    Attributes:
+        state: Mapping from tool parameter names to state field names for injection.
+            Keys are tool parameter names, values are either:
+            - str: Name of the state field to extract and inject
+            - None: Inject the entire state object
+            Empty dict if no state injection is needed.
+        store: Name of the tool parameter where the store should be injected,
+            or None if no store injection is needed.
+        runtime: Name of the tool parameter where the runtime should be injected,
+            or None if no runtime injection is needed.
+
+    Example:
+        For a tool with signature:
+        ```python
+        def my_tool(
+            x: int,
+            messages: Annotated[list, InjectedState("messages")],
+            full_state: Annotated[dict, InjectedState()],
+            store: Annotated[BaseStore, InjectedStore()],
+            runtime: ToolRuntime,
+        ) -> str:
+            ...
+        ```
+
+        The resulting `_InjectedArgs` would be:
+        ```python
+        _InjectedArgs(
+            state={
+                "messages": "messages",  # Extract state["messages"]
+                "full_state": None,      # Inject entire state
+            },
+            store="store",               # Inject into "store" parameter
+            runtime="runtime",           # Inject into "runtime" parameter
+        )
+        ```
+    """
+
+    state: dict[str, str | None]
+    store: str | None
+    runtime: str | None
+
+
 class ToolNode(RunnableCallable):
     """A node for executing tools in LangGraph workflows.
 
@@ -676,9 +751,7 @@ class ToolNode(RunnableCallable):
         """
         super().__init__(self._func, self._afunc, name=name, tags=tags, trace=False)
         self._tools_by_name: dict[str, BaseTool] = {}
-        self._tool_to_state_args: dict[str, dict[str, str | None]] = {}
-        self._tool_to_store_arg: dict[str, str | None] = {}
-        self._tool_to_runtime_arg: dict[str, str | None] = {}
+        self._injected_args: dict[str, _InjectedArgs] = {}
         self._handle_tool_errors = handle_tool_errors
         self._messages_key = messages_key
         self._wrap_tool_call = wrap_tool_call
@@ -689,9 +762,8 @@ class ToolNode(RunnableCallable):
             else:
                 tool_ = tool
             self._tools_by_name[tool_.name] = tool_
-            self._tool_to_state_args[tool_.name] = _get_state_args(tool_)
-            self._tool_to_store_arg[tool_.name] = _get_store_arg(tool_)
-            self._tool_to_runtime_arg[tool_.name] = _get_runtime_arg(tool_)
+            # Build injected args mapping once during initialization in a single pass
+            self._injected_args[tool_.name] = _get_all_injected_args(tool_)
 
     @property
     def tools_by_name(self) -> dict[str, BaseTool]:
@@ -844,12 +916,8 @@ class ToolNode(RunnableCallable):
                 response = tool.invoke(call_args, config)
             except ValidationError as exc:
                 # Filter out errors for injected arguments
-                filtered_errors = _filter_validation_errors(
-                    exc,
-                    self._tool_to_state_args.get(call["name"], {}),
-                    self._tool_to_store_arg.get(call["name"]),
-                    self._tool_to_runtime_arg.get(call["name"]),
-                )
+                injected = self._injected_args.get(call["name"])
+                filtered_errors = _filter_validation_errors(exc, injected)
                 # Use original call["args"] without injected values for error reporting
                 raise ToolInvocationError(
                     call["name"], exc, call["args"], filtered_errors
@@ -1001,12 +1069,8 @@ class ToolNode(RunnableCallable):
                 response = await tool.ainvoke(call_args, config)
             except ValidationError as exc:
                 # Filter out errors for injected arguments
-                filtered_errors = _filter_validation_errors(
-                    exc,
-                    self._tool_to_state_args.get(call["name"], {}),
-                    self._tool_to_store_arg.get(call["name"]),
-                    self._tool_to_runtime_arg.get(call["name"]),
-                )
+                injected = self._injected_args.get(call["name"])
+                filtered_errors = _filter_validation_errors(exc, injected)
                 # Use original call["args"] without injected values for error reporting
                 raise ToolInvocationError(
                     call["name"], exc, call["args"], filtered_errors
@@ -1199,86 +1263,6 @@ class ToolNode(RunnableCallable):
             return input["state"]
         return input
 
-    def _inject_state(
-        self,
-        tool_call: ToolCall,
-        state: list[AnyMessage] | dict[str, Any] | BaseModel,
-    ) -> ToolCall:
-        state_args = self._tool_to_state_args[tool_call["name"]]
-
-        if state_args and isinstance(state, list):
-            required_fields = list(state_args.values())
-            if (
-                len(required_fields) == 1 and required_fields[0] == self._messages_key
-            ) or required_fields[0] is None:
-                state = {self._messages_key: state}
-            else:
-                err_msg = (
-                    f"Invalid input to ToolNode. Tool {tool_call['name']} requires "
-                    f"graph state dict as input."
-                )
-                if any(state_field for state_field in state_args.values()):
-                    required_fields_str = ", ".join(f for f in required_fields if f)
-                    err_msg += f" State should contain fields {required_fields_str}."
-                raise ValueError(err_msg)
-
-        if isinstance(state, dict):
-            tool_state_args = {
-                tool_arg: state[state_field] if state_field else state
-                for tool_arg, state_field in state_args.items()
-            }
-        else:
-            tool_state_args = {
-                tool_arg: getattr(state, state_field) if state_field else state
-                for tool_arg, state_field in state_args.items()
-            }
-
-        tool_call["args"] = {
-            **tool_call["args"],
-            **tool_state_args,
-        }
-        return tool_call
-
-    def _inject_store(self, tool_call: ToolCall, store: BaseStore | None) -> ToolCall:
-        store_arg = self._tool_to_store_arg[tool_call["name"]]
-        if not store_arg:
-            return tool_call
-
-        if store is None:
-            msg = (
-                "Cannot inject store into tools with InjectedStore annotations - "
-                "please compile your graph with a store."
-            )
-            raise ValueError(msg)
-
-        tool_call["args"] = {
-            **tool_call["args"],
-            store_arg: store,
-        }
-        return tool_call
-
-    def _inject_runtime(
-        self, tool_call: ToolCall, tool_runtime: ToolRuntime
-    ) -> ToolCall:
-        """Inject ToolRuntime into tool call arguments.
-
-        Args:
-            tool_call: The tool call to inject runtime into.
-            tool_runtime: The ToolRuntime instance to inject.
-
-        Returns:
-            The tool call with runtime injected if needed.
-        """
-        runtime_arg = self._tool_to_runtime_arg.get(tool_call["name"])
-        if not runtime_arg:
-            return tool_call
-
-        tool_call["args"] = {
-            **tool_call["args"],
-            runtime_arg: tool_runtime,
-        }
-        return tool_call
-
     def _inject_tool_args(
         self,
         tool_call: ToolCall,
@@ -1317,12 +1301,64 @@ class ToolNode(RunnableCallable):
         if tool_call["name"] not in self.tools_by_name:
             return tool_call
 
+        injected = self._injected_args.get(tool_call["name"])
+        if not injected:
+            return tool_call
+
         tool_call_copy: ToolCall = copy(tool_call)
-        tool_call_with_state = self._inject_state(tool_call_copy, tool_runtime.state)
-        tool_call_with_store = self._inject_store(
-            tool_call_with_state, tool_runtime.store
-        )
-        return self._inject_runtime(tool_call_with_store, tool_runtime)
+        injected_args = {}
+
+        # Inject state
+        if injected.state:
+            state = tool_runtime.state
+            # Handle list state by converting to dict
+            if isinstance(state, list):
+                required_fields = list(injected.state.values())
+                if (
+                    len(required_fields) == 1
+                    and required_fields[0] == self._messages_key
+                ) or required_fields[0] is None:
+                    state = {self._messages_key: state}
+                else:
+                    err_msg = (
+                        f"Invalid input to ToolNode. Tool {tool_call['name']} requires "
+                        f"graph state dict as input."
+                    )
+                    if any(state_field for state_field in injected.state.values()):
+                        required_fields_str = ", ".join(f for f in required_fields if f)
+                        err_msg += (
+                            f" State should contain fields {required_fields_str}."
+                        )
+                    raise ValueError(err_msg)
+
+            # Extract state values
+            if isinstance(state, dict):
+                for tool_arg, state_field in injected.state.items():
+                    injected_args[tool_arg] = (
+                        state[state_field] if state_field else state
+                    )
+            else:
+                for tool_arg, state_field in injected.state.items():
+                    injected_args[tool_arg] = (
+                        getattr(state, state_field) if state_field else state
+                    )
+
+        # Inject store
+        if injected.store:
+            if tool_runtime.store is None:
+                msg = (
+                    "Cannot inject store into tools with InjectedStore annotations - "
+                    "please compile your graph with a store."
+                )
+                raise ValueError(msg)
+            injected_args[injected.store] = tool_runtime.store
+
+        # Inject runtime
+        if injected.runtime:
+            injected_args[injected.runtime] = tool_runtime
+
+        tool_call_copy["args"] = {**tool_call_copy["args"], **injected_args}
+        return tool_call_copy
 
     def _validate_tool_command(
         self,
@@ -1715,120 +1751,86 @@ def _is_injection(
     return False
 
 
-def _get_state_args(tool: BaseTool) -> dict[str, str | None]:
-    """Extract state injection mappings from tool annotations.
-
-    This function analyzes a tool's input schema to identify arguments that should
-    be injected with graph state. It processes InjectedState annotations to build
-    a mapping of tool argument names to state field names.
+def _get_injection_from_type(
+    type_: Any, injection_type: type[InjectedState | InjectedStore | ToolRuntime]
+) -> Any | None:
+    """Extract injection instance from a type annotation.
 
     Args:
-        tool: The tool to analyze for state injection requirements.
+        type_: The type annotation to check.
+        injection_type: The injection type to look for.
 
     Returns:
-        A dictionary mapping tool argument names to state field names. If a field
-        name is None, the entire state should be injected for that argument.
+        The injection instance if found, True if injection marker found without instance, None otherwise.
     """
-    full_schema = tool.get_input_schema()
-    tool_args_to_state_fields: dict = {}
+    type_args = get_args(type_)
+    matches = [arg for arg in type_args if _is_injection(arg, injection_type)]
 
-    for name, type_ in get_all_basemodel_annotations(full_schema).items():
-        injections = [
-            type_arg
-            for type_arg in get_args(type_)
-            if _is_injection(type_arg, InjectedState)
-        ]
-        if len(injections) > 1:
-            msg = (
-                "A tool argument should not be annotated with InjectedState more than "
-                f"once. Received arg {name} with annotations {injections}."
-            )
-            raise ValueError(msg)
-        if len(injections) == 1:
-            injection = injections[0]
-            if isinstance(injection, InjectedState) and injection.field:
-                tool_args_to_state_fields[name] = injection.field
-            else:
-                tool_args_to_state_fields[name] = None
-        else:
-            pass
-    return tool_args_to_state_fields
+    if len(matches) > 1:
+        msg = (
+            f"A tool argument should not be annotated with {injection_type.__name__} "
+            f"more than once. Found: {matches}"
+        )
+        raise ValueError(msg)
 
-
-def _get_store_arg(tool: BaseTool) -> str | None:
-    """Extract store injection argument from tool annotations.
-
-    This function analyzes a tool's input schema to identify the argument that
-    should be injected with the graph store. Only one store argument is supported
-    per tool.
-
-    Args:
-        tool: The tool to analyze for store injection requirements.
-
-    Returns:
-        The name of the argument that should receive the store injection, or None
-        if no store injection is required.
-
-    Raises:
-        ValueError: If a tool argument has multiple InjectedStore annotations.
-    """
-    full_schema = tool.get_input_schema()
-    for name, type_ in get_all_basemodel_annotations(full_schema).items():
-        injections = [
-            type_arg
-            for type_arg in get_args(type_)
-            if _is_injection(type_arg, InjectedStore)
-        ]
-        if len(injections) > 1:
-            msg = (
-                "A tool argument should not be annotated with InjectedStore more than "
-                f"once. Received arg {name} with annotations {injections}."
-            )
-            raise ValueError(msg)
-        if len(injections) == 1:
-            return name
+    if len(matches) == 1:
+        return matches[0]
+    elif _is_injection(type_, injection_type):
+        return True
 
     return None
 
 
-def _get_runtime_arg(tool: BaseTool) -> str | None:
-    """Extract runtime injection argument from tool annotations.
+def _get_all_injected_args(tool: BaseTool) -> _InjectedArgs:
+    """Extract all injected arguments from tool in a single pass.
 
-    This function analyzes a tool's input schema to identify the argument that
-    should be injected with the ToolRuntime instance. Only one runtime argument
-    is supported per tool.
+    This function analyzes both the tool's input schema and function signature
+    to identify all arguments that should be injected (state, store, runtime).
 
     Args:
-        tool: The tool to analyze for runtime injection requirements.
+        tool: The tool to analyze for injection requirements.
 
     Returns:
-        The name of the argument that should receive the runtime injection, or None
-        if no runtime injection is required.
-
-    Raises:
-        ValueError: If a tool argument has multiple ToolRuntime annotations.
+        _InjectedArgs structure containing all detected injections.
     """
+    # Get annotations from both schema and function signature
     full_schema = tool.get_input_schema()
-    for name, type_ in get_all_basemodel_annotations(full_schema).items():
-        # Check if the parameter name is "runtime" (regardless of type)
+    schema_annotations = get_all_basemodel_annotations(full_schema)
+
+    func = getattr(tool, "func", None) or getattr(tool, "coroutine", None)
+    func_annotations = get_type_hints(func, include_extras=True) if func else {}
+
+    # Combine both annotation sources, preferring schema annotations
+    # In the future, we might want to add more restrictions here...
+    all_annotations = {**func_annotations, **schema_annotations}
+
+    # Track injected args
+    state_args: dict[str, str | None] = {}
+    store_arg: str | None = None
+    runtime_arg: str | None = None
+
+    for name, type_ in all_annotations.items():
+        # Check for runtime (special case: parameter named "runtime")
         if name == "runtime":
-            return name
-        # Check if the type itself is ToolRuntime (direct usage)
-        if _is_injection(type_, ToolRuntime):
-            return name
-        # Check if ToolRuntime is in Annotated args
-        injections = [
-            type_arg
-            for type_arg in get_args(type_)
-            if _is_injection(type_arg, ToolRuntime)
-        ]
-        if len(injections) > 1:
-            msg = (
-                "A tool argument should not be annotated with ToolRuntime more than "
-                f"once. Received arg {name} with annotations {injections}."
-            )
-            raise ValueError(msg)
-        if len(injections) == 1:
-            return name
+            runtime_arg = name
 
-    return None
+        # Check for InjectedState
+        if state_inj := _get_injection_from_type(type_, InjectedState):
+            if isinstance(state_inj, InjectedState) and state_inj.field:
+                state_args[name] = state_inj.field
+            else:
+                state_args[name] = None
+
+        # Check for InjectedStore
+        if _get_injection_from_type(type_, InjectedStore):
+            store_arg = name
+
+        # Check for ToolRuntime
+        if _get_injection_from_type(type_, ToolRuntime):
+            runtime_arg = name
+
+    return _InjectedArgs(
+        state=state_args,
+        store=store_arg,
+        runtime=runtime_arg,
+    )

libs/prebuilt/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-prebuilt"
-version = "1.0.2"
+version = "1.0.5"
 description = "Library with high-level APIs for creating and executing LangGraph agents and tools."
 authors = []
 requires-python = ">=3.10"
@@ -29,7 +29,10 @@ dependencies = [
 ]
 
 [project.urls]
-Repository = "https://www.github.com/langchain-ai/langgraph"
+Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/prebuilt"
+Twitter = "https://x.com/LangChainAI"
+Slack = "https://www.langchain.com/join-community"
+Reddit = "https://www.reddit.com/r/LangChain/"
 
 [dependency-groups]
 test = [

libs/prebuilt/tests/test_on_tool_call.py

@@ -130,11 +130,17 @@ def test_modify_arguments() -> None:
         execute: Callable[[ToolCallRequest], ToolMessage | Command],
     ) -> ToolMessage | Command:
         """Handler that doubles the input arguments."""
-        # Modify the arguments
-        request.tool_call["args"]["a"] *= 2
-        request.tool_call["args"]["b"] *= 2
-
-        return execute(request)
+        # Modify the arguments using override method
+        modified_call = {
+            **request.tool_call,
+            "args": {
+                **request.tool_call["args"],
+                "a": request.tool_call["args"]["a"] * 2,
+                "b": request.tool_call["args"]["b"] * 2,
+            },
+        }
+        modified_request = request.override(tool_call=modified_call)
+        return execute(modified_request)
 
     tool_node = ToolNode([add], wrap_tool_call=modify_args_handler)
 
@@ -362,10 +368,17 @@ async def test_handler_with_async_execution() -> None:
         execute: Callable[[ToolCallRequest], ToolMessage | Command],
     ) -> ToolMessage | Command:
         """Handler that modifies arguments."""
-        # Add 10 to both arguments
-        request.tool_call["args"]["a"] += 10
-        request.tool_call["args"]["b"] += 10
-        return execute(request)
+        # Add 10 to both arguments using override method
+        modified_call = {
+            **request.tool_call,
+            "args": {
+                **request.tool_call["args"],
+                "a": request.tool_call["args"]["a"] + 10,
+                "b": request.tool_call["args"]["b"] + 10,
+            },
+        }
+        modified_request = request.override(tool_call=modified_call)
+        return execute(modified_request)
 
     tool_node = ToolNode([async_add], wrap_tool_call=modifying_handler)
 
@@ -1305,3 +1318,64 @@ async def test_state_extraction_with_tool_call_with_context_async() -> None:
     assert state_seen[0] == actual_state
     assert "__type" not in state_seen[0]
     assert "tool_call" not in state_seen[0]
+
+
+def test_tool_call_request_is_frozen() -> None:
+    """Test that ToolCallRequest raises deprecation warnings on direct attribute reassignment."""
+    tool_call: ToolCall = {"name": "add", "args": {"a": 1, "b": 2}, "id": "call_1"}
+    state: dict = {"messages": []}
+    runtime = None
+
+    request = ToolCallRequest(
+        tool_call=tool_call, tool=add, state=state, runtime=runtime
+    )  # type: ignore[arg-type]
+
+    # Test that direct attribute reassignment raises DeprecationWarning
+    with pytest.warns(
+        DeprecationWarning,
+        match="Setting attribute 'tool_call' on ToolCallRequest is deprecated",
+    ):
+        request.tool_call = {"name": "other", "args": {}, "id": "call_2"}  # type: ignore[misc]
+
+    with pytest.warns(
+        DeprecationWarning,
+        match="Setting attribute 'tool' on ToolCallRequest is deprecated",
+    ):
+        request.tool = None  # type: ignore[misc]
+
+    with pytest.warns(
+        DeprecationWarning,
+        match="Setting attribute 'state' on ToolCallRequest is deprecated",
+    ):
+        request.state = {}  # type: ignore[misc]
+
+    with pytest.warns(
+        DeprecationWarning,
+        match="Setting attribute 'runtime' on ToolCallRequest is deprecated",
+    ):
+        request.runtime = None  # type: ignore[misc]
+
+    # Test that override method works correctly
+    new_tool_call: ToolCall = {
+        "name": "multiply",
+        "args": {"x": 5, "y": 10},
+        "id": "call_3",
+    }
+
+    # Original request should be unchanged (note: it was modified by the warnings tests above)
+    # So we create a fresh request to test override properly
+    fresh_request = ToolCallRequest(
+        tool_call=tool_call, tool=add, state=state, runtime=runtime
+    )  # type: ignore[arg-type]
+    fresh_new_request = fresh_request.override(tool_call=new_tool_call)
+
+    # Original request should be unchanged
+    assert fresh_request.tool_call == tool_call
+    assert fresh_request.tool_call["name"] == "add"
+
+    # New request should have the updated tool_call
+    assert fresh_new_request.tool_call == new_tool_call
+    assert fresh_new_request.tool_call["name"] == "multiply"
+    assert fresh_new_request.tool == add  # Other fields should remain the same
+    assert fresh_new_request.state == state
+    assert fresh_new_request.runtime is None

libs/prebuilt/tests/test_react_agent.py

@@ -53,7 +53,6 @@ from langgraph.prebuilt.chat_agent_executor import (
 from langgraph.prebuilt.tool_node import (
     InjectedState,
     InjectedStore,
-    _get_state_args,
     _infer_handled_types,
 )
 from tests.any_str import AnyStr
@@ -639,8 +638,9 @@ def test_react_agent_parallel_tool_calls(
     for event in agent.stream(
         {"messages": [("user", query)]}, config, stream_mode="values"
     ):
-        if messages := event.get("messages"):
-            message_types.append([m.type for m in messages])
+        if "__interrupt__" not in event: 
+            if messages := event.get("messages"):
+                message_types.append([m.type for m in messages])
 
     if version == "v1":
         assert message_types == [
@@ -1084,21 +1084,6 @@ async def test_return_direct(version: str) -> None:
     ]
 
 
-def test__get_state_args() -> None:
-    class Schema1(BaseModel):
-        a: Annotated[str, InjectedState]
-
-    class Schema2(Schema1):
-        b: Annotated[int, InjectedState("bar")]
-
-    @dec_tool(args_schema=Schema2)
-    def foo(a: str, b: int) -> float:
-        """return"""
-        return 0.0
-
-    assert _get_state_args(foo) == {"a": None, "b": "bar"}
-
-
 def test_inspect_react() -> None:
     model = FakeToolCallingModel(tool_calls=[])
     agent = create_react_agent(model, [])

libs/prebuilt/tests/test_tool_node.py

@@ -42,6 +42,7 @@ from langgraph.prebuilt import (
 from langgraph.prebuilt.tool_node import (
     TOOL_CALL_ERROR_TEMPLATE,
     ToolInvocationError,
+    ToolRuntime,
     tools_condition,
 )
 
@@ -1610,3 +1611,252 @@ def test_tool_node_stream_writer() -> None:
             },
         ),
     ]
+
+
+def test_tool_call_request_setattr_deprecation_warning():
+    """Test that ToolCallRequest raises a deprecation warning on direct attribute modification."""
+    import warnings
+
+    from langgraph.prebuilt.tool_node import ToolCallRequest
+
+    # Create a mock ToolCall
+    tool_call = {"name": "test", "args": {"a": 1}, "id": "call_1", "type": "tool_call"}
+
+    # Create a ToolCallRequest
+    request = ToolCallRequest(
+        tool_call=tool_call,
+        tool=None,
+        state={"messages": []},
+        runtime=None,
+    )
+
+    # Test 1: Direct attribute assignment should raise deprecation warning but still work
+    with pytest.warns(DeprecationWarning, match="deprecated.*override"):
+        request.tool_call = {"name": "other", "args": {}, "id": "call_2"}
+
+    # Verify the attribute was actually modified
+    assert request.tool_call == {"name": "other", "args": {}, "id": "call_2"}
+
+    # Reset for further tests
+    with warnings.catch_warnings():
+        warnings.simplefilter("ignore")
+        request.tool_call = tool_call
+
+    # Test 2: override method should work without warnings
+    with warnings.catch_warnings(record=True) as w:
+        warnings.simplefilter("always")
+        new_tool_call = {
+            "name": "new_tool",
+            "args": {"b": 2},
+            "id": "call_3",
+            "type": "tool_call",
+        }
+        new_request = request.override(tool_call=new_tool_call)
+
+        # Verify no warning was raised
+        assert len(w) == 0
+
+    # Verify original is unchanged
+    assert request.tool_call == tool_call
+
+    # Verify new request has updated values
+    assert new_request.tool_call == new_tool_call
+
+    # Test 3: Initialization should not trigger warning
+    with warnings.catch_warnings(record=True) as w:
+        warnings.simplefilter("always")
+        ToolCallRequest(
+            tool_call=tool_call,
+            tool=None,
+            state={"messages": []},
+            runtime=None,
+        )
+        # Verify no warning was raised during initialization
+        assert len(w) == 0
+
+
+async def test_tool_node_inject_async_all_types_signature_only() -> None:
+    """Test all injection types without @tool decorator."""
+    store = InMemoryStore()
+    namespace = ("test",)
+    store.put(namespace, "test_key", {"store_data": "from_store"})
+
+    class TestState(TypedDict):
+        messages: list
+        foo: str
+        bar: int
+
+    async def comprehensive_async_tool(
+        x: int,
+        whole_state: Annotated[TestState, InjectedState],
+        foo_field: Annotated[str, InjectedState("foo")],
+        store: Annotated[BaseStore, InjectedStore()],
+        runtime: ToolRuntime,
+    ) -> str:
+        """Async tool that uses all injection types."""
+        bar_from_whole = whole_state["bar"]
+        foo_value = foo_field
+        store_val = store.get(namespace, "test_key").value["store_data"]
+        foo_from_runtime = runtime.state["foo"]
+        tool_call_id = runtime.tool_call_id
+
+        return (
+            f"x={x}, "
+            f"bar_from_whole={bar_from_whole}, "
+            f"foo_field={foo_value}, "
+            f"store={store_val}, "
+            f"foo_from_runtime={foo_from_runtime}, "
+            f"tool_call_id={tool_call_id}"
+        )
+
+    node = ToolNode([comprehensive_async_tool], handle_tool_errors=True)
+    tool_call = {
+        "name": "comprehensive_async_tool",
+        "args": {"x": 42},
+        "id": "test_call_123",
+        "type": "tool_call",
+    }
+    msg = AIMessage("hi?", tool_calls=[tool_call])
+
+    config = _create_config_with_runtime(store=store)
+    result = await node.ainvoke(
+        {"messages": [msg], "foo": "foo_value", "bar": 99}, config=config
+    )
+
+    tool_message = result["messages"][-1]
+    assert tool_message.content == (
+        "x=42, "
+        "bar_from_whole=99, "
+        "foo_field=foo_value, "
+        "store=from_store, "
+        "foo_from_runtime=foo_value, "
+        "tool_call_id=test_call_123"
+    )
+
+
+async def test_tool_node_inject_async_all_types_with_decorator() -> None:
+    """Test all injection types with @tool decorator."""
+    store = InMemoryStore()
+    namespace = ("test",)
+    store.put(namespace, "test_key", {"store_data": "from_store"})
+
+    class TestState(TypedDict):
+        messages: list
+        foo: str
+        bar: int
+
+    @dec_tool
+    async def comprehensive_async_tool(
+        x: int,
+        whole_state: Annotated[TestState, InjectedState],
+        foo_field: Annotated[str, InjectedState("foo")],
+        store: Annotated[BaseStore, InjectedStore()],
+        runtime: ToolRuntime,
+    ) -> str:
+        """Async tool that uses all injection types."""
+        bar_from_whole = whole_state["bar"]
+        foo_value = foo_field
+        store_val = store.get(namespace, "test_key").value["store_data"]
+        foo_from_runtime = runtime.state["foo"]
+        tool_call_id = runtime.tool_call_id
+
+        return (
+            f"x={x}, "
+            f"bar_from_whole={bar_from_whole}, "
+            f"foo_field={foo_value}, "
+            f"store={store_val}, "
+            f"foo_from_runtime={foo_from_runtime}, "
+            f"tool_call_id={tool_call_id}"
+        )
+
+    node = ToolNode([comprehensive_async_tool], handle_tool_errors=True)
+    tool_call = {
+        "name": "comprehensive_async_tool",
+        "args": {"x": 42},
+        "id": "test_call_456",
+        "type": "tool_call",
+    }
+    msg = AIMessage("hi?", tool_calls=[tool_call])
+
+    config = _create_config_with_runtime(store=store)
+    result = await node.ainvoke(
+        {"messages": [msg], "foo": "foo_value", "bar": 99}, config=config
+    )
+
+    tool_message = result["messages"][-1]
+    assert tool_message.content == (
+        "x=42, "
+        "bar_from_whole=99, "
+        "foo_field=foo_value, "
+        "store=from_store, "
+        "foo_from_runtime=foo_value, "
+        "tool_call_id=test_call_456"
+    )
+
+
+async def test_tool_node_inject_async_all_types_with_schema() -> None:
+    """Test all injection types with explicit schema."""
+    store = InMemoryStore()
+    namespace = ("test",)
+    store.put(namespace, "test_key", {"store_data": "from_store"})
+
+    class TestState(TypedDict):
+        messages: list
+        foo: str
+        bar: int
+
+    class ComprehensiveToolSchema(BaseModel):
+        model_config = {"arbitrary_types_allowed": True}
+        x: int
+        whole_state: Annotated[TestState, InjectedState]
+        foo_field: Annotated[str, InjectedState("foo")]
+        store: Annotated[BaseStore, InjectedStore()]
+        runtime: ToolRuntime
+
+    @dec_tool(args_schema=ComprehensiveToolSchema)
+    async def comprehensive_async_tool(
+        x: int,
+        whole_state: Annotated[TestState, InjectedState],
+        foo_field: Annotated[str, InjectedState("foo")],
+        store: Annotated[BaseStore, InjectedStore()],
+        runtime: ToolRuntime,
+    ) -> str:
+        """Async tool that uses all injection types."""
+        bar_from_whole = whole_state["bar"]
+        foo_value = foo_field
+        store_val = store.get(namespace, "test_key").value["store_data"]
+        foo_from_runtime = runtime.state["foo"]
+        tool_call_id = runtime.tool_call_id
+
+        return (
+            f"x={x}, "
+            f"bar_from_whole={bar_from_whole}, "
+            f"foo_field={foo_value}, "
+            f"store={store_val}, "
+            f"foo_from_runtime={foo_from_runtime}, "
+            f"tool_call_id={tool_call_id}"
+        )
+
+    node = ToolNode([comprehensive_async_tool], handle_tool_errors=True)
+    tool_call = {
+        "name": "comprehensive_async_tool",
+        "args": {"x": 42},
+        "id": "test_call_789",
+        "type": "tool_call",
+    }
+    msg = AIMessage("hi?", tool_calls=[tool_call])
+
+    config = _create_config_with_runtime(store=store)
+    result = await node.ainvoke(
+        {"messages": [msg], "foo": "foo_value", "bar": 99}, config=config
+    )
+
+    tool_message = result["messages"][-1]
+    assert tool_message.content == (
+        "x=42, "
+        "bar_from_whole=99, "
+        "foo_field=foo_value, "
+        "store=from_store, "
+        "foo_from_runtime=foo_value, "
+        "tool_call_id=test_call_789"
+    )

libs/prebuilt/uv.lock

@@ -246,7 +246,7 @@ wheels = [
 
 [[package]]
 name = "langgraph"
-version = "1.0.2"
+version = "1.0.3"
 source = { editable = "../langgraph" }
 dependencies = [
     { name = "langchain-core" },
@@ -377,7 +377,7 @@ test = [
 
 [[package]]
 name = "langgraph-checkpoint-postgres"
-version = "3.0.0"
+version = "3.0.1"
 source = { editable = "../checkpoint-postgres" }
 dependencies = [
     { name = "langgraph-checkpoint" },
@@ -467,7 +467,7 @@ test = [
 
 [[package]]
 name = "langgraph-prebuilt"
-version = "1.0.2"
+version = "1.0.5"
 source = { editable = "." }
 dependencies = [
     { name = "langchain-core" },
@@ -570,6 +570,7 @@ requires-dist = [
 dev = [
     { name = "codespell" },
     { name = "mypy" },
+    { name = "pydantic", specifier = ">=2.12.4" },
     { name = "pytest" },
     { name = "pytest-asyncio" },
     { name = "pytest-mock" },

libs/sdk-py/langgraph_sdk/auth/__init__.py

@@ -90,11 +90,11 @@ class Auth:
     """
 
     __slots__ = (
-        "on",
-        "_handlers",
-        "_global_handlers",
         "_authenticate_handler",
+        "_global_handlers",
         "_handler_cache",
+        "_handlers",
+        "on",
     )
     types = types
     """Reference to auth type definitions.
@@ -259,7 +259,7 @@ class Auth:
         """
         if self._authenticate_handler is not None:
             raise ValueError(
-                "Authentication handler already set as {self._authenticate_handler}."
+                f"Authentication handler already set as {self._authenticate_handler}."
             )
         self._authenticate_handler = fn
         return fn
@@ -383,7 +383,7 @@ class _ResourceOn(typing.Generic[VCreate, VRead, VUpdate, VDelete, VSearch]):
         if fn is not None:
             _validate_handler(fn)
             return typing.cast(
-                _ActionHandler[VCreate | VUpdate | VRead | VDelete | VSearch],
+                "_ActionHandler[VCreate | VUpdate | VRead | VDelete | VSearch]",
                 _register_handler(self.auth, self.resource, "*", fn),
             )
 
@@ -392,7 +392,7 @@ class _ResourceOn(typing.Generic[VCreate, VRead, VUpdate, VDelete, VSearch]):
         ) -> _ActionHandler[VCreate | VUpdate | VRead | VDelete | VSearch]:
             _validate_handler(handler)
             return typing.cast(
-                _ActionHandler[VCreate | VUpdate | VRead | VDelete | VSearch],
+                "_ActionHandler[VCreate | VUpdate | VRead | VDelete | VSearch]",
                 _register_handler(self.auth, self.resource, "*", handler),
             )
 
@@ -612,10 +612,10 @@ class _On:
     __slots__ = (
         "_auth",
         "assistants",
-        "threads",
-        "runs",
         "crons",
+        "runs",
         "store",
+        "threads",
         "value",
     )
 
@@ -740,9 +740,8 @@ def is_studio_user(
 ) -> bool:
     return (
         isinstance(user, types.StudioUser)
-        or isinstance(user, dict)
-        and user.get("kind") == "StudioUser"  # ty: ignore[invalid-argument-type]
+        or (isinstance(user, dict) and user.get("kind") == "StudioUser")  # ty: ignore[invalid-argument-type]
     )
 
 
-__all__ = ["Auth", "types", "exceptions"]
+__all__ = ["Auth", "exceptions", "types"]

libs/sdk-py/langgraph_sdk/auth/types.py

@@ -243,7 +243,7 @@ class StudioUser:
         ```
     """
 
-    __slots__ = ("username", "_is_authenticated", "_permissions")
+    __slots__ = ("_is_authenticated", "_permissions", "username")
 
     def __init__(self, username: str, is_authenticated: bool = False) -> None:
         self.username = username
@@ -1093,22 +1093,22 @@ class on:
 
 
 __all__ = [
-    "on",
+    "AssistantsCreate",
+    "AssistantsDelete",
+    "AssistantsRead",
+    "AssistantsSearch",
+    "AssistantsUpdate",
     "MetadataInput",
     "RunsCreate",
-    "ThreadsCreate",
-    "ThreadsRead",
-    "ThreadsUpdate",
-    "ThreadsDelete",
-    "ThreadsSearch",
-    "AssistantsCreate",
-    "AssistantsRead",
-    "AssistantsUpdate",
-    "AssistantsDelete",
-    "AssistantsSearch",
+    "StoreDelete",
     "StoreGet",
-    "StoreSearch",
     "StoreListNamespaces",
     "StorePut",
-    "StoreDelete",
+    "StoreSearch",
+    "ThreadsCreate",
+    "ThreadsDelete",
+    "ThreadsRead",
+    "ThreadsSearch",
+    "ThreadsUpdate",
+    "on",
 ]

libs/sdk-py/langgraph_sdk/client.py

@@ -1,11 +1,11 @@
 """The LangGraph client implementations connect to the LangGraph API.
 
-This module provides both asynchronous ([get_client(url="http://localhost:2024"))](#get_client) or [LangGraphClient](#LangGraphClient))
-and synchronous ([get_sync_client(url="http://localhost:2024"))](#get_sync_client) or [SyncLanggraphClient](#SyncLanggraphClient))
-clients to interacting with the LangGraph API's core resources such as
-Assistants, Threads, Runs, and Cron jobs, as well as its persistent
-document Store.
-"""  # noqa: E501
+This module provides both asynchronous (`get_client(url="http://localhost:2024")` or
+`LangGraphClient`) and synchronous (`get_sync_client(url="http://localhost:2024")` or
+`SyncLanggraphClient`) clients to interacting with the LangGraph API's core resources
+such as Assistants, Threads, Runs, and Cron jobs, as well as its persistent document
+Store.
+"""
 
 from __future__ import annotations
 
@@ -21,6 +21,7 @@ from types import TracebackType
 from typing import (
     Any,
     Literal,
+    cast,
     overload,
 )
 
@@ -117,9 +118,20 @@ def _get_headers(
 
 
 def _orjson_default(obj: Any) -> Any:
+    is_class = isinstance(obj, type)
     if hasattr(obj, "model_dump") and callable(obj.model_dump):
+        if is_class:
+            raise TypeError(
+                f"Cannot JSON-serialize type object: {obj!r}. Did you mean to pass an instance of the object instead?"
+                f"\nReceived type: {obj!r}"
+            )
         return obj.model_dump()
     elif hasattr(obj, "dict") and callable(obj.dict):
+        if is_class:
+            raise TypeError(
+                f"Cannot JSON-serialize type object: {obj!r}. Did you mean to pass an instance of the object instead?"
+                f"\nReceived type: {obj!r}"
+            )
         return obj.dict()
     elif isinstance(obj, (set, frozenset)):
         return list(obj)
@@ -163,7 +175,7 @@ def get_client(
     Args:
         url:
             Base URL of the LangGraph API.
-            – If `None`, the client first attempts an in-process connection via ASGI transport.
+            - If `None`, the client first attempts an in-process connection via ASGI transport.
               If that fails, it falls back to `http://localhost:8123`.
         api_key:
             API key for authentication. If omitted, the client reads from environment
@@ -176,9 +188,9 @@ def get_client(
             Additional HTTP headers to include in requests. Merged with authentication headers.
         timeout:
             HTTP timeout configuration. May be:
-              – `httpx.Timeout` instance
-              – float (total seconds)
-              – tuple `(connect, read, write, pool)` in seconds
+              - `httpx.Timeout` instance
+              - float (total seconds)
+              - tuple `(connect, read, write, pool)` in seconds
             Defaults: connect=5, read=300, write=300, pool=5.
 
     Returns:
@@ -236,7 +248,7 @@ def get_client(
         base_url=url,
         transport=transport,
         timeout=(
-            httpx.Timeout(timeout)
+            httpx.Timeout(timeout)  # ty: ignore[invalid-argument-type]
             if timeout is not None
             else httpx.Timeout(connect=5, read=300, write=300, pool=5)
         ),
@@ -511,7 +523,7 @@ class HttpClient:
                 decoder = SSEDecoder()
                 try:
                     async for line in aiter_lines_raw(res):
-                        sse = decoder.decode(line=line.rstrip(b"\n"))
+                        sse = decoder.decode(line=cast("bytes", line).rstrip(b"\n"))
                         if sse is not None:
                             if decoder.last_event_id is not None:
                                 last_event_id = decoder.last_event_id
@@ -625,7 +637,7 @@ class AssistantsClient:
                 'name': 'my_assistant'
             }
             ```
-        """  # noqa: E501
+        """
         return await self.http.get(
             f"/assistants/{assistant_id}", headers=headers, params=params
         )
@@ -679,7 +691,7 @@ class AssistantsClient:
             ```
 
 
-        """  # noqa: E501
+        """
         query_params = {"xray": xray}
         if params:
             query_params.update(params)
@@ -804,7 +816,7 @@ class AssistantsClient:
             }
             ```
 
-        """  # noqa: E501
+        """
         return await self.http.get(
             f"/assistants/{assistant_id}/schemas", headers=headers, params=params
         )
@@ -830,7 +842,7 @@ class AssistantsClient:
         Returns:
             Subgraphs: The graph schema for the assistant.
 
-        """  # noqa: E501
+        """
         get_params = {"recurse": recurse}
         if params:
             get_params = {**get_params, **params}
@@ -896,7 +908,7 @@ class AssistantsClient:
                 name="my_name"
             )
             ```
-        """  # noqa: E501
+        """
         payload: dict[str, Any] = {
             "graph_id": graph_id,
         }
@@ -964,7 +976,7 @@ class AssistantsClient:
             )
             ```
 
-        """  # noqa: E501
+        """
         payload: dict[str, Any] = {}
         if graph_id:
             payload["graph_id"] = graph_id
@@ -1011,7 +1023,7 @@ class AssistantsClient:
             )
             ```
 
-        """  # noqa: E501
+        """
         await self.http.delete(
             f"/assistants/{assistant_id}", headers=headers, params=params
         )
@@ -1137,7 +1149,7 @@ class AssistantsClient:
                 assistant_id="my_assistant_id"
             )
             ```
-        """  # noqa: E501
+        """
 
         payload: dict[str, Any] = {
             "limit": limit,
@@ -1181,7 +1193,7 @@ class AssistantsClient:
             )
             ```
 
-        """  # noqa: E501
+        """
 
         payload: dict[str, Any] = {"version": version}
 
@@ -1249,7 +1261,7 @@ class ThreadsClient:
             }
             ```
 
-        """  # noqa: E501
+        """
 
         return await self.http.get(
             f"/threads/{thread_id}", headers=headers, params=params
@@ -1297,7 +1309,7 @@ class ThreadsClient:
                 if_exists="raise"
             )
             ```
-        """  # noqa: E501
+        """
         payload: dict[str, Any] = {}
         if thread_id:
             payload["thread_id"] = thread_id
@@ -1365,7 +1377,7 @@ class ThreadsClient:
                 ttl=43_200,
             )
             ```
-        """  # noqa: E501
+        """
         payload: dict[str, Any] = {"metadata": metadata}
         if ttl is not None:
             if isinstance(ttl, (int, float)):
@@ -1405,7 +1417,7 @@ class ThreadsClient:
             )
             ```
 
-        """  # noqa: E501
+        """
         await self.http.delete(f"/threads/{thread_id}", headers=headers, params=params)
 
     async def search(
@@ -1453,7 +1465,7 @@ class ThreadsClient:
             )
             ```
 
-        """  # noqa: E501
+        """
         payload: dict[str, Any] = {
             "limit": limit,
             "offset": offset,
@@ -1537,7 +1549,7 @@ class ThreadsClient:
             )
             ```
 
-        """  # noqa: E501
+        """
         return await self.http.post(
             f"/threads/{thread_id}/copy", json=None, headers=headers, params=params
         )
@@ -1651,7 +1663,7 @@ class ThreadsClient:
                     }
             }
             ```
-        """  # noqa: E501
+        """
         if checkpoint:
             return await self.http.post(
                 f"/threads/{thread_id}/state/checkpoint",
@@ -1727,7 +1739,7 @@ class ThreadsClient:
                 }
             }
             ```
-        """  # noqa: E501
+        """
         payload: dict[str, Any] = {
             "values": values,
         }
@@ -1776,7 +1788,7 @@ class ThreadsClient:
             )
             ```
 
-        """  # noqa: E501
+        """
         payload: dict[str, Any] = {
             "limit": limit,
         }
@@ -1824,7 +1836,7 @@ class ThreadsClient:
                 print(chunk)
             ```
 
-        """  # noqa: E501
+        """
         query_params = {
             "stream_mode": stream_mode,
         }
@@ -2019,7 +2031,7 @@ class RunsClient:
             StreamPart(event='end', data=None)
             ```
 
-        """  # noqa: E501
+        """
         if checkpoint_during is not None:
             warnings.warn(
                 "`checkpoint_during` is deprecated and will be removed in a future version. Use `durability` instead.",
@@ -2265,7 +2277,7 @@ class RunsClient:
                 'multitask_strategy': 'interrupt'
             }
             ```
-        """  # noqa: E501
+        """
         if checkpoint_during is not None:
             warnings.warn(
                 "`checkpoint_during` is deprecated and will be removed in a future version. Use `durability` instead.",
@@ -2493,7 +2505,7 @@ class RunsClient:
             }
             ```
 
-        """  # noqa: E501
+        """
         if checkpoint_during is not None:
             warnings.warn(
                 "`checkpoint_during` is deprecated and will be removed in a future version. Use `durability` instead.",
@@ -2585,7 +2597,7 @@ class RunsClient:
             )
             ```
 
-        """  # noqa: E501
+        """
         query_params: dict[str, Any] = {
             "limit": limit,
             "offset": offset,
@@ -2629,7 +2641,7 @@ class RunsClient:
             )
             ```
 
-        """  # noqa: E501
+        """
 
         return await self.http.get(
             f"/threads/{thread_id}/runs/{run_id}", headers=headers, params=params
@@ -2671,7 +2683,7 @@ class RunsClient:
             )
             ```
 
-        """  # noqa: E501
+        """
         query_params = {
             "wait": 1 if wait else 0,
             "action": action,
@@ -2722,7 +2734,7 @@ class RunsClient:
             )
             ```
 
-        """  # noqa: E501
+        """
         return await self.http.request_reconnect(
             f"/threads/{thread_id}/runs/{run_id}/join",
             "GET",
@@ -2771,7 +2783,7 @@ class RunsClient:
                 print(part)
             ```
 
-        """  # noqa: E501
+        """
         query_params = {
             "cancel_on_disconnect": cancel_on_disconnect,
             "stream_mode": stream_mode,
@@ -2818,7 +2830,7 @@ class RunsClient:
             )
             ```
 
-        """  # noqa: E501
+        """
         await self.http.delete(
             f"/threads/{thread_id}/runs/{run_id}", headers=headers, params=params
         )
@@ -2913,7 +2925,7 @@ class CronClient:
                 multitask_strategy="interrupt"
             )
             ```
-        """  # noqa: E501
+        """
         payload = {
             "schedule": schedule,
             "input": input,
@@ -2993,7 +3005,7 @@ class CronClient:
             )
             ```
 
-        """  # noqa: E501
+        """
         payload = {
             "schedule": schedule,
             "input": input,
@@ -3039,7 +3051,7 @@ class CronClient:
             )
             ```
 
-        """  # noqa: E501
+        """
         await self.http.delete(f"/runs/crons/{cron_id}", headers=headers, params=params)
 
     async def search(
@@ -3105,7 +3117,7 @@ class CronClient:
             ]
             ```
 
-        """  # noqa: E501
+        """
         payload = {
             "assistant_id": assistant_id,
             "thread_id": thread_id,
@@ -3497,7 +3509,7 @@ def get_sync_client(
         base_url=url,
         transport=transport,
         timeout=(
-            httpx.Timeout(timeout)
+            httpx.Timeout(timeout)  # ty: ignore[invalid-argument-type]
             if timeout is not None
             else httpx.Timeout(connect=5, read=300, write=300, pool=5)
         ),
@@ -3777,7 +3789,7 @@ class SyncHttpClient:
                 decoder = SSEDecoder()
                 try:
                     for line in iter_lines_raw(res):
-                        sse = decoder.decode(line.rstrip(b"\n"))
+                        sse = decoder.decode(cast(bytes, line).rstrip(b"\n"))
                         if sse is not None:
                             if decoder.last_event_id is not None:
                                 last_event_id = decoder.last_event_id
@@ -3880,7 +3892,7 @@ class SyncAssistantsClient:
             }
             ```
 
-        """  # noqa: E501
+        """
         return self.http.get(
             f"/assistants/{assistant_id}", headers=headers, params=params
         )
@@ -3930,7 +3942,7 @@ class SyncAssistantsClient:
             }
             ```
 
-        """  # noqa: E501
+        """
         query_params = {"xray": xray}
         if params:
             query_params.update(params)
@@ -4066,7 +4078,7 @@ class SyncAssistantsClient:
             }
             ```
 
-        """  # noqa: E501
+        """
         return self.http.get(
             f"/assistants/{assistant_id}/schemas", headers=headers, params=params
         )
@@ -4090,7 +4102,7 @@ class SyncAssistantsClient:
         Returns:
             Subgraphs: The graph schema for the assistant.
 
-        """  # noqa: E501
+        """
         get_params = {"recurse": recurse}
         if params:
             get_params = {**get_params, **params}
@@ -4156,7 +4168,7 @@ class SyncAssistantsClient:
                 name="my_name"
             )
             ```
-        """  # noqa: E501
+        """
         payload: dict[str, Any] = {
             "graph_id": graph_id,
         }
@@ -4222,7 +4234,7 @@ class SyncAssistantsClient:
                 metadata={"number":2}
             )
             ```
-        """  # noqa: E501
+        """
         payload: dict[str, Any] = {}
         if graph_id:
             payload["graph_id"] = graph_id
@@ -4269,7 +4281,7 @@ class SyncAssistantsClient:
             )
             ```
 
-        """  # noqa: E501
+        """
         self.http.delete(f"/assistants/{assistant_id}", headers=headers, params=params)
 
     def search(
@@ -4390,7 +4402,7 @@ class SyncAssistantsClient:
             )
             ```
 
-        """  # noqa: E501
+        """
 
         payload: dict[str, Any] = {
             "limit": limit,
@@ -4433,7 +4445,7 @@ class SyncAssistantsClient:
             )
             ```
 
-        """  # noqa: E501
+        """
 
         payload: dict[str, Any] = {"version": version}
 
@@ -4498,7 +4510,7 @@ class SyncThreadsClient:
             }
             ```
 
-        """  # noqa: E501
+        """
 
         return self.http.get(f"/threads/{thread_id}", headers=headers, params=params)
 
@@ -4544,7 +4556,7 @@ class SyncThreadsClient:
             )
             ```
             )
-        """  # noqa: E501
+        """
         payload: dict[str, Any] = {}
         if thread_id:
             payload["thread_id"] = thread_id
@@ -4610,7 +4622,7 @@ class SyncThreadsClient:
                 ttl=43_200,
             )
             ```
-        """  # noqa: E501
+        """
         payload: dict[str, Any] = {"metadata": metadata}
         if ttl is not None:
             if isinstance(ttl, (int, float)):
@@ -4649,7 +4661,7 @@ class SyncThreadsClient:
             )
             ```
 
-        """  # noqa: E501
+        """
         self.http.delete(f"/threads/{thread_id}", headers=headers, params=params)
 
     def search(
@@ -4693,7 +4705,7 @@ class SyncThreadsClient:
                 offset=5
             )
             ```
-        """  # noqa: E501
+        """
         payload: dict[str, Any] = {
             "limit": limit,
             "offset": offset,
@@ -4774,7 +4786,7 @@ class SyncThreadsClient:
             )
             ```
 
-        """  # noqa: E501
+        """
         return self.http.post(
             f"/threads/{thread_id}/copy", json=None, headers=headers, params=params
         )
@@ -4887,7 +4899,7 @@ class SyncThreadsClient:
             }
             ```
 
-        """  # noqa: E501
+        """
         if checkpoint:
             return self.http.post(
                 f"/threads/{thread_id}/state/checkpoint",
@@ -4960,7 +4972,7 @@ class SyncThreadsClient:
             }
             ```
 
-        """  # noqa: E501
+        """
         payload: dict[str, Any] = {
             "values": values,
         }
@@ -5010,7 +5022,7 @@ class SyncThreadsClient:
             )
             ```
 
-        """  # noqa: E501
+        """
         payload: dict[str, Any] = {
             "limit": limit,
         }
@@ -5059,7 +5071,7 @@ class SyncThreadsClient:
                 print(chunk)
             ```
 
-        """  # noqa: E501
+        """
         query_params = {
             "stream_mode": stream_mode,
         }
@@ -5251,7 +5263,7 @@ class SyncRunsClient:
             StreamPart(event='values', data={'messages': [{'content': 'how are you?', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'human', 'name': None, 'id': 'fe0a5778-cfe9-42ee-b807-0adaa1873c10', 'example': False}, {'content': "I'm doing well, thanks for asking! I'm an AI assistant created by Anthropic to be helpful, honest, and harmless.", 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-159b782c-b679-4830-83c6-cef87798fe8b', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}]})
             StreamPart(event='end', data=None)
             ```
-        """  # noqa: E501
+        """
         if checkpoint_during is not None:
             warnings.warn(
                 "`checkpoint_during` is deprecated and will be removed in a future version. Use `durability` instead.",
@@ -5496,7 +5508,7 @@ class SyncRunsClient:
                 'multitask_strategy': 'interrupt'
             }
             ```
-        """  # noqa: E501
+        """
         if checkpoint_during is not None:
             warnings.warn(
                 "`checkpoint_during` is deprecated and will be removed in a future version. Use `durability` instead.",
@@ -5726,7 +5738,7 @@ class SyncRunsClient:
             }
             ```
 
-        """  # noqa: E501
+        """
         if checkpoint_during is not None:
             warnings.warn(
                 "`checkpoint_during` is deprecated and will be removed in a future version. Use `durability` instead.",
@@ -5808,7 +5820,7 @@ class SyncRunsClient:
             )
             ```
 
-        """  # noqa: E501
+        """
         query_params: dict[str, Any] = {"limit": limit, "offset": offset}
         if status is not None:
             query_params["status"] = status
@@ -5847,7 +5859,7 @@ class SyncRunsClient:
                 run_id="run_id_to_delete",
             )
             ```
-        """  # noqa: E501
+        """
 
         return self.http.get(
             f"/threads/{thread_id}/runs/{run_id}", headers=headers, params=params
@@ -5889,7 +5901,7 @@ class SyncRunsClient:
             )
             ```
 
-        """  # noqa: E501
+        """
         query_params = {
             "wait": 1 if wait else 0,
             "action": action,
@@ -5940,7 +5952,7 @@ class SyncRunsClient:
             )
             ```
 
-        """  # noqa: E501
+        """
         return self.http.request_reconnect(
             f"/threads/{thread_id}/runs/{run_id}/join",
             "GET",
@@ -5988,7 +6000,7 @@ class SyncRunsClient:
             )
             ```
 
-        """  # noqa: E501
+        """
         query_params = {
             "stream_mode": stream_mode,
             "cancel_on_disconnect": cancel_on_disconnect,
@@ -6035,7 +6047,7 @@ class SyncRunsClient:
             )
             ```
 
-        """  # noqa: E501
+        """
         self.http.delete(
             f"/threads/{thread_id}/runs/{run_id}", headers=headers, params=params
         )
@@ -6121,7 +6133,7 @@ class SyncCronClient:
                 multitask_strategy="interrupt"
             )
             ```
-        """  # noqa: E501
+        """
         payload = {
             "schedule": schedule,
             "input": input,
@@ -6200,7 +6212,7 @@ class SyncCronClient:
             )
             ```
 
-        """  # noqa: E501
+        """
         payload = {
             "schedule": schedule,
             "input": input,
@@ -6245,7 +6257,7 @@ class SyncCronClient:
             )
             ```
 
-        """  # noqa: E501
+        """
         self.http.delete(f"/runs/crons/{cron_id}", headers=headers, params=params)
 
     def search(
@@ -6309,7 +6321,7 @@ class SyncCronClient:
                 }
             ]
             ```
-        """  # noqa: E501
+        """
         payload = {
             "assistant_id": assistant_id,
             "thread_id": thread_id,

libs/sdk-py/langgraph_sdk/errors.py

@@ -24,19 +24,28 @@ class APIError(httpx.HTTPStatusError, LangGraphError):
     type: str | None
 
     def __init__(
-        self, message: str, response: httpx.Response, *, body: object | None
+        self,
+        message: str,
+        response_or_request: httpx.Response | httpx.Request,
+        *,
+        body: object | None,
     ) -> None:
-        httpx.HTTPStatusError.__init__(
-            self, message, request=response.request, response=response
-        )
+        if isinstance(response_or_request, httpx.Response):
+            req = response_or_request.request
+            response = response_or_request
+        else:
+            req = response_or_request
+            response = None
+
+        httpx.HTTPStatusError.__init__(self, message, request=req, response=response)  # type: ignore[arg-type]
         LangGraphError.__init__(self)
 
-        self.request = response.request
+        self.request = req
         self.message = message
         self.body = body
 
         if isinstance(body, dict):
-            b = cast(dict[str, Any], body)
+            b = cast("dict[str, Any]", body)
             # Best-effort extraction of common fields if present
             code_val = b.get("code")
             self.code = code_val if isinstance(code_val, str) else None
@@ -88,7 +97,7 @@ class APIConnectionError(APIError):
     def __init__(
         self, *, message: str = "Connection error.", request: httpx.Request
     ) -> None:
-        super().__init__(message, request, body=None)
+        super().__init__(message, response_or_request=request, body=None)
 
 
 class APITimeoutError(APIConnectionError):
@@ -130,7 +139,7 @@ class InternalServerError(APIStatusError):
 
 def _extract_error_message(body: object | None, fallback: str) -> str:
     if isinstance(body, dict):
-        b = cast(dict[str, Any], body)
+        b = cast("dict[str, Any]", body)
         for key in ("message", "detail", "error"):
             val = b.get(key)
             if isinstance(val, str) and val:
@@ -138,7 +147,7 @@ def _extract_error_message(body: object | None, fallback: str) -> str:
         # Sometimes errors are structured like {"error": {"message": "..."}}
         err = b.get("error")
         if isinstance(err, dict):
-            e = cast(dict[str, Any], err)
+            e = cast("dict[str, Any]", err)
             for key in ("message", "detail"):
                 val = e.get(key)
                 if isinstance(val, str) and val:
@@ -196,7 +205,7 @@ def _map_status_error(response: httpx.Response, body: object | None) -> APIStatu
         return UnprocessableEntityError(message, response=response, body=body)
     if status == 429:
         return RateLimitError(message, response=response, body=body)
-    if 500 <= status:
+    if status >= 500:
         return InternalServerError(message, response=response, body=body)
     return APIStatusError(message, response=response, body=body)
 

libs/sdk-py/langgraph_sdk/sse.py

@@ -2,7 +2,9 @@
 
 from __future__ import annotations
 
+import contextlib
 from collections.abc import AsyncIterator, Iterator
+from typing import cast
 
 import httpx
 import orjson
@@ -42,7 +44,7 @@ class BytesLineDecoder:
             return []  # pragma: no cover
 
         trailing_newline = text[-1] in NEWLINE_CHARS
-        lines = text.splitlines()
+        lines = cast(list[BytesLike], text.splitlines())
 
         if len(lines) == 1 and not trailing_newline:
             # No new lines, buffer the input and continue.
@@ -53,7 +55,7 @@ class BytesLineDecoder:
             # Include any existing buffer in the first portion of the
             # splitlines result.
             self.buffer.extend(lines[0])
-            lines = [self.buffer] + lines[1:]
+            lines = cast(list[BytesLike], [self.buffer, *lines[1:]])
             self.buffer = bytearray()
 
         if not trailing_newline:
@@ -87,7 +89,7 @@ class SSEDecoder:
         return self._last_event_id or None
 
     def decode(self, line: bytes) -> StreamPart | None:
-        # See: https://html.spec.whatwg.org/multipage/server-sent-events.html#event-stream-interpretation  # noqa: E501
+        # See: https://html.spec.whatwg.org/multipage/server-sent-events.html#event-stream-interpretation
 
         if not line:
             if (
@@ -128,10 +130,8 @@ class SSEDecoder:
             else:
                 self._last_event_id = value.decode()
         elif fieldname == b"retry":
-            try:
+            with contextlib.suppress(TypeError, ValueError):
                 self._retry = int(value)
-            except (TypeError, ValueError):
-                pass
         else:
             pass  # Field is ignored.
 

libs/sdk-py/pyproject.toml

@@ -11,32 +11,24 @@ requires-python = ">=3.10"
 readme = "README.md"
 license = "MIT"
 license-files = ['LICENSE']
-dependencies = [
-    "httpx>=0.25.2",
-    "orjson>=3.10.1",
-]
+dependencies = ["httpx>=0.25.2", "orjson>=3.10.1"]
 
 [tool.hatch.version]
 path = "langgraph_sdk/__init__.py"
 
 [project.urls]
-Repository = "https://www.github.com/langchain-ai/langgraph"
+Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/sdk-py"
+Twitter = "https://x.com/LangChainAI"
+Slack = "https://www.langchain.com/join-community"
+Reddit = "https://www.reddit.com/r/LangChain/"
 
 [dependency-groups]
-test = [
-  "pytest",
-  "pytest-asyncio",
-  "pytest-mock",
-  "pytest-watch",
-]
-lint = [
-  "ruff",
-  "codespell",
-  "mypy",
-]
+test = ["pytest", "pytest-asyncio", "pytest-mock", "pytest-watch"]
+lint = ["ruff", "codespell", "mypy"]
 dev = [
-  {include-group = "test"},
-  {include-group = "lint"},
+  { include-group = "test" },
+  { include-group = "lint" },
+  "pydantic>=2.12.4",
 ]
 
 [tool.hatch.build.targets.wheel]
@@ -50,14 +42,29 @@ asyncio_mode = "auto"
 default-groups = ['dev']
 
 [tool.ruff]
-lint.select = [
-  "E",  # pycodestyle
-  "F",  # Pyflakes
-  "UP", # pyupgrade
-  "B",  # flake8-bugbear
-  "I",  # isort
-  "ARG", # flake8-unused-arguments
-  "UP", # pyupgrade
+exclude = ["venv", ".venv", "build", "dist"]
+[tool.ruff.lint]
+select = [
+  "E",      # pycodestyle errors
+  "F",      # pyflakes
+  "I",      # isort (import sorting)
+  "ARG",    # unused arguments
+  "TID251", # banned imports
+  "TID252", # banned relative imports
+  "T20",    # print statements
+  "UP",     # pyupgrade (Python version-specific fixes)
+  "B",      # flake8-bugbear (common bugs)
+  "SIM",    # flake8-simplify (code simplification)
+  "RUF",    # ruff-specific rules
+  "S101",   # flake8-bandit: use of assert
 ]
-lint.ignore = ["E501", "B008"]
-target-version = "py310"
+ignore = [
+  "E501",   # line too long (handled by formatter)
+  "B006",   # mutable default arguments (sometimes intentional)
+  "B904",   # raise without from inside except (sometimes intentional)
+  "SIM102", # nested if statements (sometimes clearer)
+]
+per-file-ignores = { "tests/**" = ["S101", "B017"] }
+
+[tool.ty.rules]
+no-matching-overload = "ignore"

libs/sdk-py/tests/test_api_parity.py

@@ -71,8 +71,8 @@ def test_sync_api_matches_async(async_cls, sync_cls):
         sync_fn = sync_methods[name]
 
         # Use inspect.signature for parameter names (robust across versions)
-        async_sig = _strip_self(inspect.signature(async_fn))
-        sync_sig = _strip_self(inspect.signature(sync_fn))
+        async_sig = _strip_self(inspect.signature(async_fn))  # type: ignore
+        sync_sig = _strip_self(inspect.signature(sync_fn))  # type: ignore
 
         a_names = list(async_sig.parameters.keys())
         s_names = list(sync_sig.parameters.keys())

libs/sdk-py/tests/test_client_stream.py

@@ -59,7 +59,7 @@ def test_stream_see():
 
         decoder = SSEDecoder()
         for line in iter_lines_raw(groups):
-            sse = decoder.decode(line=line.rstrip(b"\n"))
+            sse = decoder.decode(line=line.rstrip(b"\n"))  # type: ignore
             if sse is not None:
                 parts.append(sse)
         if sse := decoder.decode(b""):
@@ -152,7 +152,7 @@ def test_sync_http_client_stream_recovers_after_disconnect():
     assert parts == [
         StreamPart(event="values", data={"step": 1}),
         StreamPart(event="values", data={"step": 2}),
-        StreamPart(event="end", data=None),
+        StreamPart(event="end", data=None),  # ty: ignore
     ]
 
 

libs/sdk-py/tests/test_errors.py

@@ -65,7 +65,7 @@ def test_raise_for_status_typed_maps_exceptions_and_sets_status_code(
     with pytest.raises(exc_type) as ei:
         _raise_for_status_typed(r)
 
-    err = cast(APIStatusError, ei.value)
+    err = cast("APIStatusError", ei.value)
     assert err.status_code == status
     # response attribute should be present and match
     assert err.response.status_code == status
@@ -77,7 +77,7 @@ def test_request_id_is_extracted_when_present() -> None:
     )
     with pytest.raises(NotFoundError) as ei:
         _raise_for_status_typed(r)
-    err = cast(APIStatusError, ei.value)
+    err = cast("APIStatusError", ei.value)
     # request_id only exists on APIStatusError subclasses
     assert err.request_id == "req-123"
 
@@ -86,7 +86,7 @@ def test_non_json_body_does_not_break_mapping() -> None:
     r = make_response(429, text_body="Too many requests")
     with pytest.raises(RateLimitError) as ei:
         _raise_for_status_typed(r)
-    err = cast(APIStatusError, ei.value)
+    err = cast("APIStatusError", ei.value)
     assert err.status_code == 429
 
 
@@ -102,7 +102,7 @@ def test_field_extraction_from_json_body() -> None:
     )
     with pytest.raises(BadRequestError) as ei:
         _raise_for_status_typed(r)
-    err = cast(APIStatusError, ei.value)
+    err = cast("APIStatusError", ei.value)
     assert err.code == "invalid_param"
     assert err.param == "limit"
     assert err.type == "invalid_request_error"

libs/sdk-py/tests/test_serde.py

@@ -0,0 +1,40 @@
+from typing import Any
+
+import orjson
+import pytest
+from pydantic import BaseModel
+
+from langgraph_sdk.client import _aencode_json
+
+
+async def _serde_roundtrip(data: Any):
+    _, body = await _aencode_json(data)
+    return orjson.loads(body)  # ty: ignore[invalid-argument-type]
+
+
+async def test_serde_basic():
+    # Test basic serialization
+    data = {"key": "value", "number": 42}
+    assert await _serde_roundtrip(data) == data
+
+
+async def test_serde_pydantic():
+    # Test serialization with Pydantic model (if available)
+
+    class TestModel(BaseModel):
+        name: str
+        age: int
+
+    model = TestModel(name="test", age=25)
+    result = await _serde_roundtrip(model)
+    assert result["name"] == "test"
+    assert result["age"] == 25
+
+
+async def test_serde_pydantic_cls_fails():
+    # Test that serialization fails gracefully for Pydantic model when not available
+    class TestModel(BaseModel):
+        name: str
+
+    with pytest.raises(TypeError, match="Type is not JSON serializable"):
+        await _serde_roundtrip({"foo": TestModel})

libs/sdk-py/uv.lock

@@ -1,7 +1,16 @@
 version = 1
-revision = 2
+revision = 3
 requires-python = ">=3.10"
 
+[[package]]
+name = "annotated-types"
+version = "0.7.0"
+source = { registry = "https://pypi.org/simple" }
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+wheels = [
+    { url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643, upload-time = "2024-05-20T21:33:24.1Z" },
+]
+
 [[package]]
 name = "anyio"
 version = "4.11.0"
@@ -28,11 +37,11 @@ wheels = [
 
 [[package]]
 name = "certifi"
-version = "2025.8.3"
+version = "2025.11.12"
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+    { url = "https://files.pythonhosted.org/packages/70/7d/9bc192684cea499815ff478dfcdc13835ddf401365057044fb721ec6bddb/certifi-2025.11.12-py3-none-any.whl", hash = "sha256:97de8790030bbd5c2d96b7ec782fc2f7820ef8dba6db909ccf95449f2d062d4b", size = 159438, upload-time = "2025-11-12T02:54:49.735Z" },
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@@ -110,20 +119,20 @@ wheels = [
 
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+version = "3.11"
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+    { url = "https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl", hash = "sha256:f631c04d2c48c52b84d0d0549c99ff3859c98df65b3101406327ecc7d53fbf12", size = 7484, upload-time = "2025-10-18T21:55:41.639Z" },
 ]
 
 [[package]]
@@ -138,6 +147,7 @@ dependencies = [
 dev = [
     { name = "codespell" },
     { name = "mypy" },
+    { name = "pydantic" },
     { name = "pytest" },
     { name = "pytest-asyncio" },
     { name = "pytest-mock" },
@@ -166,6 +176,7 @@ requires-dist = [
 dev = [
     { name = "codespell" },
     { name = "mypy" },
+    { name = "pydantic", specifier = ">=2.12.4" },
     { name = "pytest" },
     { name = "pytest-asyncio" },
     { name = "pytest-mock" },
@@ -240,79 +251,83 @@ wheels = [
 
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-version = "3.11.3"
+version = "3.11.4"
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