bump redis major

README.md

@@ -11,7 +11,7 @@
 [![Version](https://img.shields.io/pypi/v/langgraph.svg)](https://pypi.org/project/langgraph/)
 [![Downloads](https://static.pepy.tech/badge/langgraph/month)](https://pepy.tech/project/langgraph)
 [![Open Issues](https://img.shields.io/github/issues-raw/langchain-ai/langgraph)](https://github.com/langchain-ai/langgraph/issues)
-[![Docs](https://img.shields.io/badge/docs-latest-blue)](https://docs.langchain.com/oss/python/langgraph/overview)
+[![Docs](https://img.shields.io/badge/docs-latest-blue)](https://langchain-ai.github.io/langgraph/)
 
 Trusted by companies shaping the future of agents – including Klarna, Replit, Elastic, and more – LangGraph is a low-level orchestration framework for building, managing, and deploying long-running, stateful agents.
 
@@ -23,55 +23,47 @@ Install LangGraph:
 pip install -U langgraph
 ```
 
-Create a simple workflow:
+Then, create an agent [using prebuilt components](https://langchain-ai.github.io/langgraph/agents/agents/):
 
 ```python
-from langgraph.graph import START, StateGraph
-from typing_extensions import TypedDict
+# pip install -qU "langchain[anthropic]" to call the model
 
+from langgraph.prebuilt import create_react_agent
 
-class State(TypedDict):
-    text: str
+def get_weather(city: str) -> str:
+    """Get weather for a given city."""
+    return f"It's always sunny in {city}!"
 
+agent = create_react_agent(
+    model="anthropic:claude-3-7-sonnet-latest",
+    tools=[get_weather],
+    prompt="You are a helpful assistant"
+)
 
-def node_a(state: State) -> dict:
-    return {"text": state["text"] + "a"}
-
-
-def node_b(state: State) -> dict:
-    return {"text": state["text"] + "b"}
-
-
-graph = StateGraph(State)
-graph.add_node("node_a", node_a)
-graph.add_node("node_b", node_b)
-graph.add_edge(START, "node_a")
-graph.add_edge("node_a", "node_b")
-
-print(graph.compile().invoke({"text": ""}))
-# {'text': 'ab'}
+# Run the agent
+agent.invoke(
+    {"messages": [{"role": "user", "content": "what is the weather in sf"}]}
+)
 ```
 
-Get started with the [LangGraph Quickstart](https://docs.langchain.com/oss/python/langgraph/quickstart).
-
-To quickly build agents with LangChain's `create_agent` (built on LangGraph), see the [LangChain Agents documentation](https://docs.langchain.com/oss/python/langchain/agents).
+For more information, see the [Quickstart](https://langchain-ai.github.io/langgraph/agents/agents/). Or, to learn how to build an [agent workflow](https://langchain-ai.github.io/langgraph/concepts/low_level/) with a customizable architecture, long-term memory, and other complex task handling, see the [LangGraph basics tutorials](https://langchain-ai.github.io/langgraph/tutorials/get-started/1-build-basic-chatbot/).
 
 ## Core benefits
 
 LangGraph provides low-level supporting infrastructure for *any* long-running, stateful workflow or agent. LangGraph does not abstract prompts or architecture, and provides the following central benefits:
 
-- [Durable execution](https://docs.langchain.com/oss/python/langgraph/durable-execution): Build agents that persist through failures and can run for extended periods, automatically resuming from exactly where they left off.
-- [Human-in-the-loop](https://docs.langchain.com/oss/python/langgraph/interrupts): Seamlessly incorporate human oversight by inspecting and modifying agent state at any point during execution.
-- [Comprehensive memory](https://docs.langchain.com/oss/python/langgraph/memory): Create truly stateful agents with both short-term working memory for ongoing reasoning and long-term persistent memory across sessions.
+- [Durable execution](https://langchain-ai.github.io/langgraph/concepts/durable_execution/): Build agents that persist through failures and can run for extended periods, automatically resuming from exactly where they left off.
+- [Human-in-the-loop](https://langchain-ai.github.io/langgraph/concepts/human_in_the_loop/): Seamlessly incorporate human oversight by inspecting and modifying agent state at any point during execution.
+- [Comprehensive memory](https://langchain-ai.github.io/langgraph/concepts/memory/): Create truly stateful agents with both short-term working memory for ongoing reasoning and long-term persistent memory across sessions.
 - [Debugging with LangSmith](http://www.langchain.com/langsmith): Gain deep visibility into complex agent behavior with visualization tools that trace execution paths, capture state transitions, and provide detailed runtime metrics.
-- [Production-ready deployment](https://docs.langchain.com/langsmith/app-development): Deploy sophisticated agent systems confidently with scalable infrastructure designed to handle the unique challenges of stateful, long-running workflows.
+- [Production-ready deployment](https://langchain-ai.github.io/langgraph/concepts/deployment_options/): Deploy sophisticated agent systems confidently with scalable infrastructure designed to handle the unique challenges of stateful, long-running workflows.
 
 ## LangGraph’s ecosystem
 
 While LangGraph can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools for building agents. To improve your LLM application development, pair LangGraph with:
 
 - [LangSmith](http://www.langchain.com/langsmith) — Helpful for agent evals and observability. Debug poor-performing LLM app runs, evaluate agent trajectories, gain visibility in production, and improve performance over time.
-- [LangSmith Deployment](https://docs.langchain.com/langsmith/deployments) — Deploy and scale agents effortlessly with a purpose-built deployment platform for long running, stateful workflows. Discover, reuse, configure, and share agents across teams — and iterate quickly with visual prototyping in [LangGraph Studio](https://docs.langchain.com/oss/python/langgraph/studio).
+- [LangSmith Deployment](https://langchain-ai.github.io/langgraph/concepts/langgraph_platform/) — Deploy and scale agents effortlessly with a purpose-built deployment platform for long running, stateful workflows. Discover, reuse, configure, and share agents across teams — and iterate quickly with visual prototyping in [LangGraph Studio](https://langchain-ai.github.io/langgraph/concepts/langgraph_studio/).
 - [LangChain](https://docs.langchain.com/oss/python/langchain/overview) – Provides integrations and composable components to streamline LLM application development.
 
 > [!NOTE]
@@ -79,11 +71,12 @@ While LangGraph can be used standalone, it also integrates seamlessly with any L
 
 ## Additional resources
 
-- [Guides](https://docs.langchain.com/oss/python/langgraph/guides): Quick, actionable code snippets for topics such as streaming, adding memory & persistence, and design patterns (e.g. branching, subgraphs, etc.).
-- [Reference](https://reference.langchain.com/python/langgraph/): Detailed reference on core classes, methods, how to use the graph and checkpointing APIs, and higher-level prebuilt components.
-- [Examples](https://docs.langchain.com/oss/python/langgraph/agentic-rag): Guided examples on getting started with LangGraph.
+- [Guides](https://langchain-ai.github.io/langgraph/guides/): Quick, actionable code snippets for topics such as streaming, adding memory & persistence, and design patterns (e.g. branching, subgraphs, etc.).
+- [Reference](https://langchain-ai.github.io/langgraph/reference/graphs/): Detailed reference on core classes, methods, how to use the graph and checkpointing APIs, and higher-level prebuilt components.
+- [Examples](https://langchain-ai.github.io/langgraph/examples/): Guided examples on getting started with LangGraph.
 - [LangChain Forum](https://forum.langchain.com/): Connect with the community and share all of your technical questions, ideas, and feedback.
 - [LangChain Academy](https://academy.langchain.com/courses/intro-to-langgraph): Learn the basics of LangGraph in our free, structured course.
+- [Templates](https://langchain-ai.github.io/langgraph/concepts/template_applications/): Pre-built reference apps for common agentic workflows (e.g. ReAct agent, memory, retrieval etc.) that can be cloned and adapted.
 - [Case studies](https://www.langchain.com/built-with-langgraph): Hear how industry leaders use LangGraph to ship AI applications at scale.
 
 ## Acknowledgements

libs/checkpoint-postgres/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-checkpoint-postgres"
-version = "3.0.2"
+version = "3.0.3"
 description = "Library with a Postgres implementation of LangGraph checkpoint saver."
 authors = []
 requires-python = ">=3.10"
@@ -12,7 +12,7 @@ readme = "README.md"
 license = "MIT"
 license-files = ['LICENSE']
 dependencies = [
-  "langgraph-checkpoint>=2.1.2,<4.0.0",
+  "langgraph-checkpoint>=2.1.2,<5.0.0",
   "orjson>=3.10.1",
   "psycopg>=3.2.0",
   "psycopg-pool>=3.2.0",

libs/checkpoint-postgres/uv.lock

@@ -259,7 +259,7 @@ wheels = [
 
 [[package]]
 name = "langgraph-checkpoint"
-version = "3.0.1"
+version = "4.0.0"
 source = { editable = "../checkpoint" }
 dependencies = [
     { name = "langchain-core" },
@@ -306,7 +306,7 @@ test = [
 
 [[package]]
 name = "langgraph-checkpoint-postgres"
-version = "3.0.2"
+version = "3.0.3"
 source = { editable = "." }
 dependencies = [
     { name = "langgraph-checkpoint" },

libs/checkpoint-sqlite/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-checkpoint-sqlite"
-version = "3.0.1"
+version = "3.0.2"
 description = "Library with a SQLite implementation of LangGraph checkpoint saver."
 authors = []
 requires-python = ">=3.10"
@@ -12,7 +12,7 @@ readme = "README.md"
 license = "MIT"
 license-files = ['LICENSE']
 dependencies = [
-    "langgraph-checkpoint>=3,<4.0.0",
+    "langgraph-checkpoint>=3,<5.0.0",
     "aiosqlite>=0.20",
     "sqlite-vec>=0.1.6",
 ]

libs/checkpoint-sqlite/uv.lock

@@ -1,5 +1,5 @@
 version = 1
-revision = 2
+revision = 3
 requires-python = ">=3.10"
 
 [[package]]
@@ -246,7 +246,7 @@ wheels = [
 
 [[package]]
 name = "langgraph-checkpoint"
-version = "3.0.1"
+version = "4.0.0"
 source = { editable = "../checkpoint" }
 dependencies = [
     { name = "langchain-core" },
@@ -293,7 +293,7 @@ test = [
 
 [[package]]
 name = "langgraph-checkpoint-sqlite"
-version = "3.0.1"
+version = "3.0.2"
 source = { editable = "." }
 dependencies = [
     { name = "aiosqlite" },

libs/checkpoint/langgraph/cache/base/__init__.py

@@ -15,7 +15,7 @@ FullKey = tuple[Namespace, str]
 class BaseCache(ABC, Generic[ValueT]):
     """Base class for a cache."""
 
-    serde: SerializerProtocol = JsonPlusSerializer(pickle_fallback=True)
+    serde: SerializerProtocol = JsonPlusSerializer(pickle_fallback=False)
 
     def __init__(self, *, serde: SerializerProtocol | None = None) -> None:
         """Initialize the cache with a serializer."""

libs/checkpoint/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-checkpoint"
-version = "3.0.1"
+version = "4.0.0"
 description = "Library with base interfaces for LangGraph checkpoint savers."
 authors = []
 requires-python = ">=3.10"

libs/cli/langgraph_cli/__init__.py

@@ -1 +1 @@
-__version__ = "0.4.11"
+__version__ = "0.4.9"

libs/cli/langgraph_cli/cli.py

@@ -336,13 +336,13 @@ def _build(
 
     # apply config
     stdin, additional_contexts = langgraph_cli.config.config_to_docker(
-        config_path=config,
-        config=config_json,
-        base_image=base_image,
-        api_version=api_version,
-        install_command=install_command,
-        build_command=build_command,
-        build_context=build_context,
+        config,
+        config_json,
+        base_image,
+        api_version,
+        install_command,
+        build_command,
+        build_context,
     )
     # add additional_contexts
     if additional_contexts:
@@ -522,8 +522,8 @@ def dockerfile(
 
     secho(f"📝 Generating Dockerfile at {save_path}", fg="yellow")
     dockerfile, additional_contexts = langgraph_cli.config.config_to_docker(
-        config_path=config,
-        config=config_json,
+        config,
+        config_json,
         base_image=base_image,
         api_version=api_version,
     )

libs/cli/langgraph_cli/config.py

@@ -824,8 +824,6 @@ def python_config_to_docker(
     config: Config,
     base_image: str,
     api_version: str | None = None,
-    *,
-    escape_variables: bool = False,
 ) -> tuple[str, dict[str, str]]:
     """Generate a Dockerfile from the configuration."""
     pip_installer = config.get("pip_installer", "auto")
@@ -1005,7 +1003,6 @@ ADD {relpath} /deps/{name}
         )
 
     # Add main dockerfile content
-    dep_vname = "$$dep" if escape_variables else "$dep"
     docker_file_contents.extend(
         [
             f"FROM {image_str}",
@@ -1016,10 +1013,10 @@ ADD {relpath} /deps/{name}
             "",
             "# -- Installing all local dependencies --",
             f"""RUN for dep in /deps/*; do \
-            echo "Installing {dep_vname}"; \
-            if [ -d "{dep_vname}" ]; then \
-                echo "Installing {dep_vname}"; \
-                (cd "{dep_vname}" && {global_reqs_pip_install} -e .); \
+            echo "Installing $dep"; \
+            if [ -d "$dep" ]; then \
+                echo "Installing $dep"; \
+                (cd "$dep" && {global_reqs_pip_install} -e .); \
             fi; \
         done""",
             "# -- End of local dependencies install --",
@@ -1205,34 +1202,26 @@ def _calculate_relative_workdir(config_path: pathlib.Path, build_context: str) -
 def config_to_docker(
     config_path: pathlib.Path,
     config: Config,
-    *,
     base_image: str | None = None,
     api_version: str | None = None,
     install_command: str | None = None,
     build_command: str | None = None,
     build_context: str | None = None,
-    escape_variables: bool = False,
 ) -> tuple[str, dict[str, str]]:
     base_image = base_image or default_base_image(config)
 
     if config.get("node_version") and not config.get("python_version"):
         return node_config_to_docker(
-            config_path=config_path,
-            config=config,
-            base_image=base_image,
-            api_version=api_version,
-            install_command=install_command,
-            build_command=build_command,
-            build_context=build_context,
+            config_path,
+            config,
+            base_image,
+            api_version,
+            install_command,
+            build_command,
+            build_context,
         )
 
-    return python_config_to_docker(
-        config_path=config_path,
-        config=config,
-        base_image=base_image,
-        api_version=api_version,
-        escape_variables=escape_variables,
-    )
+    return python_config_to_docker(config_path, config, base_image, api_version)
 
 
 def config_to_compose(
@@ -1276,11 +1265,7 @@ def config_to_compose(
 
     else:
         dockerfile, additional_contexts = config_to_docker(
-            config_path=config_path,
-            config=config,
-            base_image=base_image,
-            api_version=api_version,
-            escape_variables=True,
+            config_path, config, base_image, api_version
         )
 
         additional_contexts_str = "\n".join(

libs/cli/pyproject.toml

@@ -19,7 +19,7 @@ dependencies = [
 path = "langgraph_cli/__init__.py"
 [project.optional-dependencies]
 inmem = [
-    "langgraph-api>=0.5.35,<0.7.0 ; python_version >= '3.11'",
+    "langgraph-api>=0.5.35,<0.6.0 ; python_version >= '3.11'",
     "langgraph-runtime-inmem>=0.7 ; python_version >= '3.11'",
     "python-dotenv>=0.8.0",
 ]

libs/cli/tests/unit_tests/cli/test_cli.py

@@ -150,7 +150,7 @@ services:
                 COPY --from=cli_1 . /deps/cli_1
                 # -- End of local package ../../.. --
                 # -- Installing all local dependencies --
-                RUN for dep in /deps/*; do             echo "Installing $$dep";             if [ -d "$$dep" ]; then                 echo "Installing $$dep";                 (cd "$$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e .);             fi;         done
+                RUN for dep in /deps/*; do             echo "Installing $dep";             if [ -d "$dep" ]; then                 echo "Installing $dep";                 (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e .);             fi;         done
                 # -- End of local dependencies install --
                 ENV LANGSERVE_GRAPHS='{{"agent": "agent.py:graph"}}'
 {textwrap.indent(textwrap.dedent(FORMATTED_CLEANUP_LINES), "                ")}

libs/cli/tests/unit_tests/test_config.py

@@ -420,7 +420,7 @@ def test_config_to_docker_simple():
                 "http": {"app": "../../examples/my_app.py:app"},
             }
         ),
-        base_image="langchain/langgraph-api",
+        "langchain/langgraph-api",
     )
     expected_docker_stdin = f"""\
 # syntax=docker/dockerfile:1.4
@@ -483,7 +483,7 @@ def test_config_to_docker_outside_path():
     actual_docker_stdin, additional_contexts = config_to_docker(
         PATH_TO_CONFIG,
         validate_config({"dependencies": [".", ".."], "graphs": graphs}),
-        base_image="langchain/langgraph-api",
+        "langchain/langgraph-api",
     )
     expected_docker_stdin = (
         """\
@@ -544,7 +544,7 @@ def test_config_to_docker_pipconfig():
                 "pip_config_file": "pipconfig.txt",
             }
         ),
-        base_image="langchain/langgraph-api",
+        "langchain/langgraph-api",
     )
     expected_docker_stdin = (
         """\
@@ -585,7 +585,7 @@ def test_config_to_docker_invalid_inputs():
         config_to_docker(
             PATH_TO_CONFIG,
             validate_config({"dependencies": ["./missing"], "graphs": graphs}),
-            base_image="langchain/langgraph-api",
+            "langchain/langgraph-api",
         )
 
     # test missing local module
@@ -594,7 +594,7 @@ def test_config_to_docker_invalid_inputs():
         config_to_docker(
             PATH_TO_CONFIG,
             validate_config({"dependencies": ["."], "graphs": graphs}),
-            base_image="langchain/langgraph-api",
+            "langchain/langgraph-api",
         )
 
 
@@ -608,7 +608,7 @@ def test_config_to_docker_local_deps():
                 "graphs": graphs,
             }
         ),
-        base_image="langchain/langgraph-api-custom",
+        "langchain/langgraph-api-custom",
     )
     expected_docker_stdin = f"""\
 FROM langchain/langgraph-api-custom:3.11
@@ -654,7 +654,7 @@ dependencies = ["langchain"]"""
                 "graphs": graphs,
             }
         ),
-        base_image="langchain/langgraph-api",
+        "langchain/langgraph-api",
     )
     os.remove(pyproject_path)
     expected_docker_stdin = (
@@ -689,7 +689,7 @@ def test_config_to_docker_end_to_end():
                 "dockerfile_lines": ["ARG meow", "ARG foo"],
             }
         ),
-        base_image="langchain/langgraph-api",
+        "langchain/langgraph-api",
     )
     expected_docker_stdin = f"""FROM langchain/langgraph-api:3.12
 ARG meow
@@ -734,7 +734,7 @@ def test_config_to_docker_nodejs():
                 "ui_config": {"shared": ["nuqs"]},
             }
         ),
-        base_image="langchain/langgraphjs-api",
+        "langchain/langgraphjs-api",
     )
     expected_docker_stdin = """FROM langchain/langgraphjs-api:20
 ARG meow
@@ -786,7 +786,7 @@ def test_config_to_docker_python_encryption_bad_path():
 def test_config_to_docker_python_encryption_formatted():
     # Test that encryption config is properly formatted in Docker output
     graphs = {"agent": "./graphs/agent.py:graph"}
-    actual_docker_stdin, _ = config_to_docker(
+    actual_docker_stdin, additional_contexts = config_to_docker(
         PATH_TO_CONFIG,
         validate_config(
             {
@@ -796,7 +796,7 @@ def test_config_to_docker_python_encryption_formatted():
                 "encryption": {"path": "./agent.py:my_encryption"},
             }
         ),
-        base_image="langchain/langgraph-api",
+        "langchain/langgraph-api",
     )
     # Verify that LANGGRAPH_ENCRYPTION is in the docker output with the correct path
     assert "LANGGRAPH_ENCRYPTION=" in actual_docker_stdin
@@ -821,7 +821,7 @@ def test_config_to_docker_nodejs_internal_docker_tag():
                 "_INTERNAL_docker_tag": "my-tag",
             }
         ),
-        base_image="langchain/langgraphjs-api",
+        "langchain/langgraphjs-api",
     )
     expected_docker_stdin = """FROM langchain/langgraphjs-api:my-tag
 ARG meow
@@ -875,7 +875,7 @@ def test_config_to_docker_webhooks_python():
                 "webhooks": webhooks,
             }
         ),
-        base_image="langchain/langgraph-api",
+        "langchain/langgraph-api",
     )
 
     # Ensure the ENV line is present and the payload round-trips via JSON
@@ -900,7 +900,7 @@ def test_config_to_docker_webhooks_node():
                 "webhooks": webhooks,
             }
         ),
-        base_image="langchain/langgraphjs-api",
+        "langchain/langgraphjs-api",
     )
 
     parsed = _extract_env_json(dockerfile, "LANGGRAPH_WEBHOOKS")
@@ -912,7 +912,7 @@ def test_config_to_docker_no_webhooks():
     dockerfile, _ = config_to_docker(
         PATH_TO_CONFIG,
         validate_config({"dependencies": ["."], "graphs": graphs}),
-        base_image="langchain/langgraph-api",
+        "langchain/langgraph-api",
     )
 
     assert "ENV LANGGRAPH_WEBHOOKS=" not in dockerfile
@@ -930,7 +930,7 @@ def test_config_to_docker_gen_ui_python():
                 "ui_config": {"shared": ["nuqs"]},
             }
         ),
-        base_image="langchain/langgraph-api",
+        "langchain/langgraph-api",
     )
 
     expected_docker_stdin = f"""FROM langchain/langgraph-api:3.11
@@ -976,7 +976,7 @@ def test_config_to_docker_multiplatform():
         validate_config(
             {"node_version": "22", "dependencies": ["."], "graphs": graphs}
         ),
-        base_image="langchain/langgraph-api",
+        "langchain/langgraph-api",
     )
 
     expected_docker_stdin = f"""FROM langchain/langgraph-api:3.11
@@ -1024,7 +1024,7 @@ def test_config_to_docker_pip_installer():
         {**copy.deepcopy(base_config), "pip_installer": "auto"}
     )
     docker_auto, _ = config_to_docker(
-        PATH_TO_CONFIG, config_auto, base_image="langchain/langgraph-api:0.2.47"
+        PATH_TO_CONFIG, config_auto, "langchain/langgraph-api:0.2.47"
     )
     assert "uv pip install --system " in docker_auto
     assert "rm /usr/bin/uv /usr/bin/uvx" in docker_auto
@@ -1032,7 +1032,7 @@ def test_config_to_docker_pip_installer():
     # Test explicit pip setting
     config_pip = validate_config({**copy.deepcopy(base_config), "pip_installer": "pip"})
     docker_pip, _ = config_to_docker(
-        PATH_TO_CONFIG, config_pip, base_image="langchain/langgraph-api:0.2.47"
+        PATH_TO_CONFIG, config_pip, "langchain/langgraph-api:0.2.47"
     )
     assert "uv pip install --system " not in docker_pip
     assert "pip install" in docker_pip
@@ -1041,7 +1041,7 @@ def test_config_to_docker_pip_installer():
     # Test explicit uv setting
     config_uv = validate_config({**copy.deepcopy(base_config), "pip_installer": "uv"})
     docker_uv, _ = config_to_docker(
-        PATH_TO_CONFIG, config_uv, base_image="langchain/langgraph-api:0.2.47"
+        PATH_TO_CONFIG, config_uv, "langchain/langgraph-api:0.2.47"
     )
     assert "uv pip install --system " in docker_uv
     assert "rm /usr/bin/uv /usr/bin/uvx" in docker_uv
@@ -1051,7 +1051,7 @@ def test_config_to_docker_pip_installer():
         {**copy.deepcopy(base_config), "pip_installer": "auto"}
     )
     docker_auto_old, _ = config_to_docker(
-        PATH_TO_CONFIG, config_auto_old, base_image="langchain/langgraph-api:0.2.46"
+        PATH_TO_CONFIG, config_auto_old, "langchain/langgraph-api:0.2.46"
     )
     assert "uv pip install --system " not in docker_auto_old
     assert "pip install" in docker_auto_old
@@ -1060,7 +1060,7 @@ def test_config_to_docker_pip_installer():
     # Test that missing pip_installer defaults to auto behavior
     config_default = validate_config(copy.deepcopy(base_config))
     docker_default, _ = config_to_docker(
-        PATH_TO_CONFIG, config_default, base_image="langchain/langgraph-api:0.2.47"
+        PATH_TO_CONFIG, config_default, "langchain/langgraph-api:0.2.47"
     )
     assert "uv pip install --system " in docker_default
 
@@ -1076,7 +1076,7 @@ def test_config_retain_build_tools():
         {**copy.deepcopy(base_config), "keep_pkg_tools": True}
     )
     docker_true, _ = config_to_docker(
-        PATH_TO_CONFIG, config_true, base_image="langchain/langgraph-api:0.2.47"
+        PATH_TO_CONFIG, config_true, "langchain/langgraph-api:0.2.47"
     )
     assert not any(
         "/usr/local/lib/python*/site-packages/" + pckg + "*" in docker_true
@@ -1087,7 +1087,7 @@ def test_config_retain_build_tools():
         {**copy.deepcopy(base_config), "keep_pkg_tools": False}
     )
     docker_false, _ = config_to_docker(
-        PATH_TO_CONFIG, config_false, base_image="langchain/langgraph-api:0.2.47"
+        PATH_TO_CONFIG, config_false, "langchain/langgraph-api:0.2.47"
     )
     assert all(
         "/usr/local/lib/python*/site-packages/" + pckg + "*" in docker_false
@@ -1098,7 +1098,7 @@ def test_config_retain_build_tools():
         {**copy.deepcopy(base_config), "keep_pkg_tools": ["pip", "setuptools"]}
     )
     docker_list, _ = config_to_docker(
-        PATH_TO_CONFIG, config_list, base_image="langchain/langgraph-api:0.2.47"
+        PATH_TO_CONFIG, config_list, "langchain/langgraph-api:0.2.47"
     )
     assert all(
         "/usr/local/lib/python*/site-packages/" + pckg + "*" in docker_list
@@ -1137,7 +1137,7 @@ def test_config_to_compose_simple_config():
                     done
                 # -- End of non-package dependency unit_tests --
                 # -- Installing all local dependencies --
-                RUN for dep in /deps/*; do             echo "Installing $$dep";             if [ -d "$$dep" ]; then                 echo "Installing $$dep";                 (cd "$$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e .);             fi;         done
+                RUN for dep in /deps/*; do             echo "Installing $dep";             if [ -d "$dep" ]; then                 echo "Installing $dep";                 (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e .);             fi;         done
                 # -- End of local dependencies install --
                 ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}}'
 {textwrap.indent(textwrap.dedent(FORMATTED_CLEANUP_LINES), "                ")}
@@ -1178,7 +1178,7 @@ def test_config_to_compose_env_vars():
                     done
                 # -- End of non-package dependency unit_tests --
                 # -- Installing all local dependencies --
-                RUN for dep in /deps/*; do             echo "Installing $$dep";             if [ -d "$$dep" ]; then                 echo "Installing $$dep";                 (cd "$$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e .);             fi;         done
+                RUN for dep in /deps/*; do             echo "Installing $dep";             if [ -d "$dep" ]; then                 echo "Installing $dep";                 (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e .);             fi;         done
                 # -- End of local dependencies install --
                 ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}}'
 {textwrap.indent(textwrap.dedent(FORMATTED_CLEANUP_LINES), "                ")}
@@ -1223,7 +1223,7 @@ def test_config_to_compose_env_file():
                     done
                 # -- End of non-package dependency unit_tests --
                 # -- Installing all local dependencies --
-                RUN for dep in /deps/*; do             echo "Installing $$dep";             if [ -d "$$dep" ]; then                 echo "Installing $$dep";                 (cd "$$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e .);             fi;         done
+                RUN for dep in /deps/*; do             echo "Installing $dep";             if [ -d "$dep" ]; then                 echo "Installing $dep";                 (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e .);             fi;         done
                 # -- End of local dependencies install --
                 ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}}'
 {textwrap.indent(textwrap.dedent(FORMATTED_CLEANUP_LINES), "                ")}
@@ -1261,7 +1261,7 @@ def test_config_to_compose_watch():
                     done
                 # -- End of non-package dependency unit_tests --
                 # -- Installing all local dependencies --
-                RUN for dep in /deps/*; do             echo "Installing $$dep";             if [ -d "$$dep" ]; then                 echo "Installing $$dep";                 (cd "$$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e .);             fi;         done
+                RUN for dep in /deps/*; do             echo "Installing $dep";             if [ -d "$dep" ]; then                 echo "Installing $dep";                 (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e .);             fi;         done
                 # -- End of local dependencies install --
                 ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}}'
 {textwrap.indent(textwrap.dedent(FORMATTED_CLEANUP_LINES), "                ")}
@@ -1308,7 +1308,7 @@ def test_config_to_compose_end_to_end():
                     done
                 # -- End of non-package dependency unit_tests --
                 # -- Installing all local dependencies --
-                RUN for dep in /deps/*; do             echo "Installing $$dep";             if [ -d "$$dep" ]; then                 echo "Installing $$dep";                 (cd "$$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e .);             fi;         done
+                RUN for dep in /deps/*; do             echo "Installing $dep";             if [ -d "$dep" ]; then                 echo "Installing $dep";                 (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e .);             fi;         done
                 # -- End of local dependencies install --
                 ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}}'
 {textwrap.indent(textwrap.dedent(FORMATTED_CLEANUP_LINES), "                ")}
@@ -1619,7 +1619,7 @@ def test_config_to_docker_with_api_version():
     actual_docker_stdin, additional_contexts = config_to_docker(
         PATH_TO_CONFIG,
         validate_config({"dependencies": ["."], "graphs": graphs}),
-        base_image="langchain/langgraph-api",
+        "langchain/langgraph-api",
         api_version="0.2.74",
     )
 
@@ -1633,7 +1633,7 @@ def test_config_to_docker_with_api_version():
     actual_docker_stdin, additional_contexts = config_to_docker(
         PATH_TO_CONFIG,
         validate_config({"node_version": "20", "graphs": graphs}),
-        base_image="langchain/langgraphjs-api",
+        "langchain/langgraphjs-api",
         api_version="0.2.74",
     )
 

libs/cli/uv.lock

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 [[package]]

libs/langgraph/README.md

@@ -11,7 +11,7 @@
 [![Version](https://img.shields.io/pypi/v/langgraph.svg)](https://pypi.org/project/langgraph/)
 [![Downloads](https://static.pepy.tech/badge/langgraph/month)](https://pepy.tech/project/langgraph)
 [![Open Issues](https://img.shields.io/github/issues-raw/langchain-ai/langgraph)](https://github.com/langchain-ai/langgraph/issues)
-[![Docs](https://img.shields.io/badge/docs-latest-blue)](https://docs.langchain.com/oss/python/langgraph/overview)
+[![Docs](https://img.shields.io/badge/docs-latest-blue)](https://langchain-ai.github.io/langgraph/)
 
 Trusted by companies shaping the future of agents – including Klarna, Replit, Elastic, and more – LangGraph is a low-level orchestration framework for building, managing, and deploying long-running, stateful agents.
 
@@ -23,55 +23,47 @@ Install LangGraph:
 pip install -U langgraph
 ```
 
-Create a simple workflow:
+Then, create an agent [using prebuilt components](https://langchain-ai.github.io/langgraph/agents/agents/):
 
 ```python
-from langgraph.graph import START, StateGraph
-from typing_extensions import TypedDict
+# pip install -qU "langchain[anthropic]" to call the model
 
+from langgraph.prebuilt import create_react_agent
 
-class State(TypedDict):
-    text: str
+def get_weather(city: str) -> str:
+    """Get weather for a given city."""
+    return f"It's always sunny in {city}!"
 
+agent = create_react_agent(
+    model="anthropic:claude-3-7-sonnet-latest",
+    tools=[get_weather],
+    prompt="You are a helpful assistant"
+)
 
-def node_a(state: State) -> dict:
-    return {"text": state["text"] + "a"}
-
-
-def node_b(state: State) -> dict:
-    return {"text": state["text"] + "b"}
-
-
-graph = StateGraph(State)
-graph.add_node("node_a", node_a)
-graph.add_node("node_b", node_b)
-graph.add_edge(START, "node_a")
-graph.add_edge("node_a", "node_b")
-
-print(graph.compile().invoke({"text": ""}))
-# {'text': 'ab'}
+# Run the agent
+agent.invoke(
+    {"messages": [{"role": "user", "content": "what is the weather in sf"}]}
+)
 ```
 
-Get started with the [LangGraph Quickstart](https://docs.langchain.com/oss/python/langgraph/quickstart).
-
-To quickly build agents with LangChain's `create_agent` (built on LangGraph), see the [LangChain Agents documentation](https://docs.langchain.com/oss/python/langchain/agents).
+For more information, see the [Quickstart](https://langchain-ai.github.io/langgraph/agents/agents/). Or, to learn how to build an [agent workflow](https://langchain-ai.github.io/langgraph/concepts/low_level/) with a customizable architecture, long-term memory, and other complex task handling, see the [LangGraph basics tutorials](https://langchain-ai.github.io/langgraph/tutorials/get-started/1-build-basic-chatbot/).
 
 ## Core benefits
 
 LangGraph provides low-level supporting infrastructure for *any* long-running, stateful workflow or agent. LangGraph does not abstract prompts or architecture, and provides the following central benefits:
 
-- [Durable execution](https://docs.langchain.com/oss/python/langgraph/durable-execution): Build agents that persist through failures and can run for extended periods, automatically resuming from exactly where they left off.
-- [Human-in-the-loop](https://docs.langchain.com/oss/python/langgraph/interrupts): Seamlessly incorporate human oversight by inspecting and modifying agent state at any point during execution.
-- [Comprehensive memory](https://docs.langchain.com/oss/python/langgraph/memory): Create truly stateful agents with both short-term working memory for ongoing reasoning and long-term persistent memory across sessions.
+- [Durable execution](https://langchain-ai.github.io/langgraph/concepts/durable_execution/): Build agents that persist through failures and can run for extended periods, automatically resuming from exactly where they left off.
+- [Human-in-the-loop](https://langchain-ai.github.io/langgraph/concepts/human_in_the_loop/): Seamlessly incorporate human oversight by inspecting and modifying agent state at any point during execution.
+- [Comprehensive memory](https://langchain-ai.github.io/langgraph/concepts/memory/): Create truly stateful agents with both short-term working memory for ongoing reasoning and long-term persistent memory across sessions.
 - [Debugging with LangSmith](http://www.langchain.com/langsmith): Gain deep visibility into complex agent behavior with visualization tools that trace execution paths, capture state transitions, and provide detailed runtime metrics.
-- [Production-ready deployment](https://docs.langchain.com/langsmith/app-development): Deploy sophisticated agent systems confidently with scalable infrastructure designed to handle the unique challenges of stateful, long-running workflows.
+- [Production-ready deployment](https://langchain-ai.github.io/langgraph/concepts/deployment_options/): Deploy sophisticated agent systems confidently with scalable infrastructure designed to handle the unique challenges of stateful, long-running workflows.
 
 ## LangGraph’s ecosystem
 
 While LangGraph can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools for building agents. To improve your LLM application development, pair LangGraph with:
 
 - [LangSmith](http://www.langchain.com/langsmith) — Helpful for agent evals and observability. Debug poor-performing LLM app runs, evaluate agent trajectories, gain visibility in production, and improve performance over time.
-- [LangSmith Deployment](https://docs.langchain.com/langsmith/deployments) — Deploy and scale agents effortlessly with a purpose-built deployment platform for long running, stateful workflows. Discover, reuse, configure, and share agents across teams — and iterate quickly with visual prototyping in [LangGraph Studio](https://docs.langchain.com/oss/python/langgraph/studio).
+- [LangSmith Deployment](https://langchain-ai.github.io/langgraph/concepts/langgraph_platform/) — Deploy and scale agents effortlessly with a purpose-built deployment platform for long running, stateful workflows. Discover, reuse, configure, and share agents across teams — and iterate quickly with visual prototyping in [LangGraph Studio](https://langchain-ai.github.io/langgraph/concepts/langgraph_studio/).
 - [LangChain](https://docs.langchain.com/oss/python/langchain/overview) – Provides integrations and composable components to streamline LLM application development.
 
 > [!NOTE]
@@ -79,11 +71,12 @@ While LangGraph can be used standalone, it also integrates seamlessly with any L
 
 ## Additional resources
 
-- [Guides](https://docs.langchain.com/oss/python/langgraph/guides): Quick, actionable code snippets for topics such as streaming, adding memory & persistence, and design patterns (e.g. branching, subgraphs, etc.).
-- [Reference](https://reference.langchain.com/python/langgraph/): Detailed reference on core classes, methods, how to use the graph and checkpointing APIs, and higher-level prebuilt components.
-- [Examples](https://docs.langchain.com/oss/python/langgraph/agentic-rag): Guided examples on getting started with LangGraph.
+- [Guides](https://langchain-ai.github.io/langgraph/guides/): Quick, actionable code snippets for topics such as streaming, adding memory & persistence, and design patterns (e.g. branching, subgraphs, etc.).
+- [Reference](https://langchain-ai.github.io/langgraph/reference/graphs/): Detailed reference on core classes, methods, how to use the graph and checkpointing APIs, and higher-level prebuilt components.
+- [Examples](https://langchain-ai.github.io/langgraph/examples/): Guided examples on getting started with LangGraph.
 - [LangChain Forum](https://forum.langchain.com/): Connect with the community and share all of your technical questions, ideas, and feedback.
 - [LangChain Academy](https://academy.langchain.com/courses/intro-to-langgraph): Learn the basics of LangGraph in our free, structured course.
+- [Templates](https://langchain-ai.github.io/langgraph/concepts/template_applications/): Pre-built reference apps for common agentic workflows (e.g. ReAct agent, memory, retrieval etc.) that can be cloned and adapted.
 - [Case studies](https://www.langchain.com/built-with-langgraph): Hear how industry leaders use LangGraph to ship AI applications at scale.
 
 ## Acknowledgements

libs/langgraph/langgraph/graph/state.py

@@ -78,7 +78,6 @@ from langgraph.types import (
     Command,
     RetryPolicy,
     Send,
-    ensure_valid_checkpointer,
 )
 from langgraph.typing import ContextT, InputT, NodeInputT, OutputT, StateT
 from langgraph.warnings import LangGraphDeprecatedSinceV05, LangGraphDeprecatedSinceV10
@@ -854,8 +853,6 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
         Returns:
             CompiledStateGraph: The compiled `StateGraph`.
         """
-        checkpointer = ensure_valid_checkpointer(checkpointer)
-
         # assign default values
         interrupt_before = interrupt_before or []
         interrupt_after = interrupt_after or []

libs/langgraph/langgraph/pregel/main.py

@@ -142,7 +142,6 @@ from langgraph.types import (
     StateSnapshot,
     StateUpdate,
     StreamMode,
-    ensure_valid_checkpointer,
 )
 from langgraph.typing import ContextT, InputT, OutputT, StateT
 from langgraph.warnings import LangGraphDeprecatedSinceV10
@@ -643,7 +642,7 @@ class Pregel(
         input_channels: str | Sequence[str],
         step_timeout: float | None = None,
         debug: bool | None = None,
-        checkpointer: Checkpointer = None,
+        checkpointer: BaseCheckpointSaver | None = None,
         store: BaseStore | None = None,
         cache: BaseCache | None = None,
         retry_policy: RetryPolicy | Sequence[RetryPolicy] = (),
@@ -666,8 +665,6 @@ class Pregel(
             if context_schema is None:
                 context_schema = cast(type[ContextT], config_type)
 
-        checkpointer = ensure_valid_checkpointer(checkpointer)
-
         self.nodes = {
             k: v.build() if isinstance(v, NodeBuilder) else v for k, v in nodes.items()
         }

libs/langgraph/langgraph/pregel/remote.py

@@ -631,26 +631,6 @@ class RemoteGraph(PregelProtocol):
         )
         return self._get_config(response["checkpoint"])
 
-    def _prepare_run_input(
-        self,
-        input: dict[str, Any] | Any,
-        config: RunnableConfig | None,
-    ) -> tuple[RunnableConfig, dict[str, Any] | Any, CommandSDK | None, str | None]:
-        """Prepare input for run calls.
-
-        Returns:
-            Tuple of (sanitized_config, input, command, thread_id)
-        """
-        merged_config = merge_configs(self.config, config)
-        sanitized_config = self._sanitize_config(merged_config)
-        if isinstance(input, Command):
-            command: CommandSDK | None = cast(CommandSDK, asdict(input))
-            input = None
-        else:
-            command = None
-        thread_id = sanitized_config.get("configurable", {}).pop("thread_id", None)
-        return sanitized_config, input, command, thread_id
-
     def _get_stream_modes(
         self,
         stream_mode: StreamMode | list[StreamMode] | None,
@@ -735,12 +715,17 @@ class RemoteGraph(PregelProtocol):
             The output of the graph.
         """
         sync_client = self._validate_sync_client()
-        sanitized_config, input, command, thread_id = self._prepare_run_input(
-            input, config
-        )
+        merged_config = merge_configs(self.config, config)
+        sanitized_config = self._sanitize_config(merged_config)
         stream_modes, requested, req_single, stream = self._get_stream_modes(
             stream_mode, config
         )
+        if isinstance(input, Command):
+            command: CommandSDK | None = cast(CommandSDK, asdict(input))
+            input = None
+        else:
+            command = None
+        thread_id = sanitized_config.get("configurable", {}).pop("thread_id", None)
 
         for chunk in sync_client.runs.stream(
             thread_id=thread_id,
@@ -840,12 +825,17 @@ class RemoteGraph(PregelProtocol):
             The output of the graph.
         """
         client = self._validate_client()
-        sanitized_config, input, command, thread_id = self._prepare_run_input(
-            input, config
-        )
+        merged_config = merge_configs(self.config, config)
+        sanitized_config = self._sanitize_config(merged_config)
         stream_modes, requested, req_single, stream = self._get_stream_modes(
             stream_mode, config
         )
+        if isinstance(input, Command):
+            command: CommandSDK | None = cast(CommandSDK, asdict(input))
+            input = None
+        else:
+            command = None
+        thread_id = sanitized_config.get("configurable", {}).pop("thread_id", None)
 
         async for chunk in client.runs.stream(
             thread_id=thread_id,
@@ -947,31 +937,27 @@ class RemoteGraph(PregelProtocol):
             interrupt_before: Interrupt the graph before these nodes.
             interrupt_after: Interrupt the graph after these nodes.
             headers: Additional headers to pass to the request.
-            **kwargs: Additional params to pass to client.runs.wait.
+            **kwargs: Additional params to pass to RemoteGraph.stream.
 
         Returns:
             The output of the graph.
         """
-        sync_client = self._validate_sync_client()
-        sanitized_config, input, command, thread_id = self._prepare_run_input(
-            input, config
-        )
-
-        return sync_client.runs.wait(  # type: ignore
-            thread_id=thread_id,
-            assistant_id=self.assistant_id,
-            input=input,
-            command=command,
-            config=sanitized_config,
+        for chunk in self.stream(
+            input,
+            config=config,
             interrupt_before=interrupt_before,
             interrupt_after=interrupt_after,
-            if_not_exists="create",
-            headers=(
-                _merge_tracing_headers(headers) if self.distributed_tracing else headers
-            ),
+            headers=headers,
+            stream_mode="values",
             params=params,
             **kwargs,
-        )
+        ):
+            pass
+        try:
+            return chunk
+        except UnboundLocalError:
+            logger.warning("No events received from remote graph")
+            return None
 
     async def ainvoke(
         self,
@@ -992,31 +978,27 @@ class RemoteGraph(PregelProtocol):
             interrupt_before: Interrupt the graph before these nodes.
             interrupt_after: Interrupt the graph after these nodes.
             headers: Additional headers to pass to the request.
-            **kwargs: Additional params to pass to client.runs.wait.
+            **kwargs: Additional params to pass to RemoteGraph.astream.
 
         Returns:
             The output of the graph.
         """
-        client = self._validate_client()
-        sanitized_config, input, command, thread_id = self._prepare_run_input(
-            input, config
-        )
-
-        return await client.runs.wait(
-            thread_id=thread_id,
-            assistant_id=self.assistant_id,
-            input=input,
-            command=command,
-            config=sanitized_config,
+        async for chunk in self.astream(
+            input,
+            config=config,
             interrupt_before=interrupt_before,
             interrupt_after=interrupt_after,
-            if_not_exists="create",
-            headers=(
-                _merge_tracing_headers(headers) if self.distributed_tracing else headers
-            ),
+            headers=headers,
+            stream_mode="values",
             params=params,
             **kwargs,
-        )
+        ):
+            pass
+        try:
+            return chunk
+        except UnboundLocalError:
+            logger.warning("No events received from remote graph")
+            return None
 
 
 def _merge_tracing_headers(headers: dict[str, str] | None) -> dict[str, str] | None:

libs/langgraph/langgraph/types.py

@@ -56,7 +56,6 @@ __all__ = (
     "Durability",
     "interrupt",
     "Overwrite",
-    "ensure_valid_checkpointer",
 )
 
 Durability = Literal["sync", "async", "exit"]
@@ -74,20 +73,6 @@ Checkpointer = None | bool | BaseCheckpointSaver
 - False disables checkpointing, even if the parent graph has a checkpointer.
 - None inherits checkpointer from the parent graph."""
 
-
-def ensure_valid_checkpointer(checkpointer: Checkpointer) -> Checkpointer:
-    if checkpointer not in (None, True, False) and not isinstance(
-        checkpointer, BaseCheckpointSaver
-    ):
-        raise TypeError(
-            "Invalid checkpointer provided. Expected an instance of "
-            "`BaseCheckpointSaver`, `True`, `False`, or `None`. "
-            f"Received {type(checkpointer).__name__!s}. "
-            "Pass a proper saver (e.g., InMemorySaver, AsyncPostgresSaver)."
-        )
-    return checkpointer
-
-
 StreamMode = Literal[
     "values", "updates", "checkpoints", "tasks", "debug", "messages", "custom"
 ]

libs/langgraph/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph"
-version = "1.0.5"
+version = "2.0.0"
 description = "Building stateful, multi-actor applications with LLMs"
 authors = []
 requires-python = ">=3.10"
@@ -25,8 +25,8 @@ classifiers = [
 ]
 dependencies = [
     "langchain-core>=0.1",
-    "langgraph-checkpoint>=2.1.0,<4.0.0",
-    "langgraph-sdk>=0.3.0,<0.4.0",
+    "langgraph-checkpoint>=2.1.0,<5.0.0",
+    "langgraph-sdk>=0.2.2,<0.3.0",
     "langgraph-prebuilt>=1.0.2,<1.1.0",
     "xxhash>=3.5.0",
     "pydantic>=2.7.4",

libs/langgraph/tests/test_pregel.py

@@ -120,22 +120,6 @@ def test_graph_validation() -> None:
         graph.invoke({"hello": "there"})
 
 
-def test_invalid_checkpointer_type() -> None:
-    class State(TypedDict):
-        foo: str
-
-    builder = StateGraph(State)
-    builder.add_node("start", lambda state: state)
-    builder.set_entry_point("start")
-    builder.set_finish_point("start")
-
-    class NotACheckpointer:
-        pass
-
-    with pytest.raises(TypeError, match="Invalid checkpointer provided"):
-        builder.compile(checkpointer=NotACheckpointer())
-
-
 def test_graph_validation_with_command() -> None:
     class State(TypedDict):
         foo: str

libs/langgraph/tests/test_remote_graph.py

@@ -567,9 +567,9 @@ def test_stream():
         stream_parts.append(stream_part)
 
     assert stream_parts == [
-        ("updates", {"chunk": "data3"}, None),
-        ("updates", {"chunk": "data4"}, None),
-        ("updates", {"__interrupt__": ()}, None),
+        ("updates", {"chunk": "data3"}),
+        ("updates", {"chunk": "data4"}),
+        ("updates", {"__interrupt__": ()}),
     ]
 
     # subgraphs + list modes
@@ -739,9 +739,9 @@ async def test_astream():
         stream_parts.append(stream_part)
 
     assert stream_parts == [
-        ("updates", {"chunk": "data3"}, None),
-        ("updates", {"chunk": "data4"}, None),
-        ("updates", {"__interrupt__": ()}, None),
+        ("updates", {"chunk": "data3"}),
+        ("updates", {"chunk": "data4"}),
+        ("updates", {"__interrupt__": ()}),
     ]
 
     # subgraphs + list modes
@@ -818,9 +818,13 @@ async def test_astream():
 def test_invoke():
     # set up test
     mock_sync_client = MagicMock()
-    mock_sync_client.runs.wait.return_value = {
-        "messages": [{"type": "human", "content": "world"}]
-    }
+    mock_sync_client.runs.stream.return_value = [
+        StreamPart(event="values", data={"chunk": "data1"}),
+        StreamPart(event="values", data={"chunk": "data2"}),
+        StreamPart(
+            event="values", data={"messages": [{"type": "human", "content": "world"}]}
+        ),
+    ]
 
     # call method / assertions
     remote_pregel = RemoteGraph(
@@ -834,19 +838,13 @@ def test_invoke():
     )
 
     assert result == {"messages": [{"type": "human", "content": "world"}]}
-    # verify runs.wait was called with expected args
-    assert mock_sync_client.runs.wait.called
-    _, kwargs = mock_sync_client.runs.wait.call_args
-    assert kwargs.get("thread_id") == "thread_1"
-    assert kwargs.get("assistant_id") == "test_graph_id"
-    assert kwargs.get("if_not_exists") == "create"
 
 
 def test_invoke_sanitizes_thread_id():
     # Ensure that invoking with thread_id passes thread_id as a top-level arg
     # and removes it from the config body.
     mock_sync_client = MagicMock()
-    mock_sync_client.runs.wait.return_value = {}
+    mock_sync_client.runs.stream.return_value = []
     remote_pregel = RemoteGraph("test_graph_id", sync_client=mock_sync_client)
 
     config = {"configurable": {"thread_id": "thread_1"}}
@@ -854,8 +852,8 @@ def test_invoke_sanitizes_thread_id():
         {"input": {"messages": [{"type": "human", "content": "hello"}]}}, config
     )
 
-    assert mock_sync_client.runs.wait.called
-    _, kwargs = mock_sync_client.runs.wait.call_args
+    assert mock_sync_client.runs.stream.called
+    _, kwargs = mock_sync_client.runs.stream.call_args
     assert kwargs.get("thread_id") == "thread_1"
     passed_config = kwargs.get("config") or {}
     assert "configurable" in passed_config
@@ -885,10 +883,16 @@ def test_stream_sanitizes_thread_id():
 @pytest.mark.anyio
 async def test_ainvoke():
     # set up test
-    mock_async_client = AsyncMock()
-    mock_async_client.runs.wait.return_value = {
-        "messages": [{"type": "human", "content": "world"}]
-    }
+    mock_async_client = MagicMock()
+    async_iter = MagicMock()
+    async_iter.__aiter__.return_value = [
+        StreamPart(event="values", data={"chunk": "data1"}),
+        StreamPart(event="values", data={"chunk": "data2"}),
+        StreamPart(
+            event="values", data={"messages": [{"type": "human", "content": "world"}]}
+        ),
+    ]
+    mock_async_client.runs.stream.return_value = async_iter
 
     # call method / assertions
     remote_pregel = RemoteGraph(
@@ -902,12 +906,6 @@ async def test_ainvoke():
     )
 
     assert result == {"messages": [{"type": "human", "content": "world"}]}
-    # verify runs.wait was called with expected args
-    assert mock_async_client.runs.wait.called
-    _, kwargs = mock_async_client.runs.wait.call_args
-    assert kwargs.get("thread_id") == "thread_1"
-    assert kwargs.get("assistant_id") == "test_graph_id"
-    assert kwargs.get("if_not_exists") == "create"
 
 
 @pytest.mark.skip(
@@ -1243,18 +1241,12 @@ async def test_include_headers(
     async_iter.__aiter__.return_value = return_value
     astream_mock = mock_async_client.runs.stream
     astream_mock.return_value = async_iter
-    # Mock for ainvoke which uses runs.wait
-    await_mock = AsyncMock(return_value={"chunk": "data1"})
-    mock_async_client.runs.wait = await_mock
 
     mock_sync_client = MagicMock()
     sync_iter = MagicMock()
     sync_iter.__iter__.return_value = return_value
     stream_mock = mock_sync_client.runs.stream
     stream_mock.return_value = async_iter
-    # Mock for invoke which uses runs.wait
-    wait_mock = MagicMock(return_value={"chunk": "data1"})
-    mock_sync_client.runs.wait = wait_mock
 
     remote_pregel = RemoteGraph(
         "test_graph_id",
@@ -1287,12 +1279,8 @@ async def test_include_headers(
         expected["langsmith-trace"] = AnyStr()
         expected["baggage"] = AnyStr("langsmith-metadata=")
 
-    if stream:
-        assert astream_mock.call_args.kwargs["headers"] == expected
-    else:
-        assert await_mock.call_args.kwargs["headers"] == expected
+    assert astream_mock.call_args.kwargs["headers"] == expected
     stream_mock.assert_not_called()
-    wait_mock.assert_not_called()
 
     with ls.tracing_context(enabled=True, client=MagicMock()):
         with ls.trace("foo"):
@@ -1310,7 +1298,4 @@ async def test_include_headers(
                     config,
                     headers=headers,
                 )
-    if stream:
-        assert stream_mock.call_args.kwargs["headers"] == expected
-    else:
-        assert wait_mock.call_args.kwargs["headers"] == expected
+    assert stream_mock.call_args.kwargs["headers"] == expected

libs/langgraph/uv.lock

@@ -423,101 +423,101 @@ wheels = [
 
 [[package]]
 name = "coverage"
-version = "7.12.0"
+version = "7.13.0"
 source = { registry = "https://pypi.org/simple" }
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+sdist = { url = "https://files.pythonhosted.org/packages/b6/45/2c665ca77ec32ad67e25c77daf1cee28ee4558f3bc571cdbaf88a00b9f23/coverage-7.13.0.tar.gz", hash = "sha256:a394aa27f2d7ff9bc04cf703817773a59ad6dfbd577032e690f961d2460ee936", size = 820905, upload-time = "2025-12-08T13:14:38.055Z" }
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/fa/d0/c20f4e668e89494972e551c31be2a0016e3f50d552d7ae9ac07086407599/psycopg_binary-3.3.2-cp314-cp314-musllinux_1_2_riscv64.whl", hash = "sha256:1586e220be05547c77afc326741dd41cc7fba38a81f9931f616ae98865439678", size = 3928660, upload-time = "2025-12-06T17:34:46.757Z" },
+    { url = "https://files.pythonhosted.org/packages/0f/e1/99746c171de22539fd5eb1c9ca21dc805b54cfae502d7451d237d1dbc349/psycopg_binary-3.3.2-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:458696a5fa5dad5b6fb5d5862c22454434ce4fe1cf66ca6c0de5f904cbc1ae3e", size = 4239169, upload-time = "2025-12-06T17:34:49.751Z" },
+    { url = "https://files.pythonhosted.org/packages/72/f7/212343c1c9cfac35fd943c527af85e9091d633176e2a407a0797856ff7b9/psycopg_binary-3.3.2-cp314-cp314-win_amd64.whl", hash = "sha256:04bb2de4ba69d6f8395b446ede795e8884c040ec71d01dd07ac2b2d18d4153d1", size = 3642122, upload-time = "2025-12-06T17:34:52.506Z" },
 ]
 
 [[package]]
@@ -2865,7 +2865,7 @@ wheels = [
 
 [[package]]
 name = "pytest"
-version = "9.0.1"
+version = "9.0.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "colorama", marker = "sys_platform == 'win32'" },
@@ -2876,9 +2876,9 @@ dependencies = [
     { name = "pygments" },
     { name = "tomli", marker = "python_full_version < '3.11'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/07/56/f013048ac4bc4c1d9be45afd4ab209ea62822fb1598f40687e6bf45dcea4/pytest-9.0.1.tar.gz", hash = "sha256:3e9c069ea73583e255c3b21cf46b8d3c56f6e3a1a8f6da94ccb0fcf57b9d73c8", size = 1564125, upload-time = "2025-11-12T13:05:09.333Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/d1/db/7ef3487e0fb0049ddb5ce41d3a49c235bf9ad299b6a25d5780a89f19230f/pytest-9.0.2.tar.gz", hash = "sha256:75186651a92bd89611d1d9fc20f0b4345fd827c41ccd5c299a868a05d70edf11", size = 1568901, upload-time = "2025-12-06T21:30:51.014Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/0b/8b/6300fb80f858cda1c51ffa17075df5d846757081d11ab4aa35cef9e6258b/pytest-9.0.1-py3-none-any.whl", hash = "sha256:67be0030d194df2dfa7b556f2e56fb3c3315bd5c8822c6951162b92b32ce7dad", size = 373668, upload-time = "2025-11-12T13:05:07.379Z" },
+    { url = "https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl", hash = "sha256:711ffd45bf766d5264d487b917733b453d917afd2b0ad65223959f59089f875b", size = 374801, upload-time = "2025-12-06T21:30:49.154Z" },
 ]
 
 [[package]]
@@ -3663,11 +3663,11 @@ wheels = [
 
 [[package]]
 name = "urllib3"
-version = "2.6.0"
+version = "2.6.1"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/1c/43/554c2569b62f49350597348fc3ac70f786e3c32e7f19d266e19817812dd3/urllib3-2.6.0.tar.gz", hash = "sha256:cb9bcef5a4b345d5da5d145dc3e30834f58e8018828cbc724d30b4cb7d4d49f1", size = 432585, upload-time = "2025-12-05T15:08:47.885Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/5e/1d/0f3a93cca1ac5e8287842ed4eebbd0f7a991315089b1a0b01c7788aa7b63/urllib3-2.6.1.tar.gz", hash = "sha256:5379eb6e1aba4088bae84f8242960017ec8d8e3decf30480b3a1abdaa9671a3f", size = 432678, upload-time = "2025-12-08T15:25:26.773Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/56/1a/9ffe814d317c5224166b23e7c47f606d6e473712a2fad0f704ea9b99f246/urllib3-2.6.0-py3-none-any.whl", hash = "sha256:c90f7a39f716c572c4e3e58509581ebd83f9b59cced005b7db7ad2d22b0db99f", size = 131083, upload-time = "2025-12-05T15:08:45.983Z" },
+    { url = "https://files.pythonhosted.org/packages/bc/56/190ceb8cb10511b730b564fb1e0293fa468363dbad26145c34928a60cb0c/urllib3-2.6.1-py3-none-any.whl", hash = "sha256:e67d06fe947c36a7ca39f4994b08d73922d40e6cca949907be05efa6fd75110b", size = 131138, upload-time = "2025-12-08T15:25:25.51Z" },
 ]
 
 [[package]]

libs/prebuilt/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-prebuilt"
-version = "1.0.5"
+version = "1.0.6"
 description = "Library with high-level APIs for creating and executing LangGraph agents and tools."
 authors = []
 requires-python = ">=3.10"
@@ -24,7 +24,7 @@ classifiers = [
     'Programming Language :: Python :: 3.13',
 ]
 dependencies = [
-    "langgraph-checkpoint>=2.1.0,<4.0.0",
+    "langgraph-checkpoint>=2.1.0,<5.0.0",
     "langchain-core>=1.0.0",
 ]
 

libs/prebuilt/uv.lock

@@ -271,7 +271,7 @@ wheels = [
 
 [[package]]
 name = "langgraph"
-version = "1.0.5"
+version = "2.0.0"
 source = { editable = "../langgraph" }
 dependencies = [
     { name = "langchain-core" },
@@ -355,7 +355,7 @@ test = [
 
 [[package]]
 name = "langgraph-checkpoint"
-version = "3.0.1"
+version = "4.0.0"
 source = { editable = "../checkpoint" }
 dependencies = [
     { name = "langchain-core" },
@@ -402,7 +402,7 @@ test = [
 
 [[package]]
 name = "langgraph-checkpoint-postgres"
-version = "3.0.2"
+version = "3.0.3"
 source = { editable = "../checkpoint-postgres" }
 dependencies = [
     { name = "langgraph-checkpoint" },
@@ -449,7 +449,7 @@ test = [
 
 [[package]]
 name = "langgraph-checkpoint-sqlite"
-version = "3.0.1"
+version = "3.0.2"
 source = { editable = "../checkpoint-sqlite" }
 dependencies = [
     { name = "aiosqlite" },
@@ -492,7 +492,7 @@ test = [
 
 [[package]]
 name = "langgraph-prebuilt"
-version = "1.0.5"
+version = "1.0.6"
 source = { editable = "." }
 dependencies = [
     { name = "langchain-core" },

libs/sdk-py/langgraph_sdk/__init__.py

@@ -3,6 +3,6 @@ from langgraph_sdk.client import get_client, get_sync_client
 from langgraph_sdk.encryption import Encryption
 from langgraph_sdk.encryption.types import EncryptionContext
 
-__version__ = "0.3.1"
+__version__ = "0.2.15"
 
 __all__ = ["Auth", "Encryption", "EncryptionContext", "get_client", "get_sync_client"]

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

@@ -64,6 +64,114 @@ def _validate_handler(fn: typing.Callable, handler_type: str) -> None:
         )
 
 
+class _JsonEncryptDecorators:
+    """Dynamic decorator factory for JSON encryption handlers.
+
+    Supports both default and model-specific handlers:
+    - @encrypt.json - default handler for all models
+    - @encrypt.json.thread - handler for thread model
+    """
+
+    def __init__(self, parent: Encryption):
+        self._parent = parent
+
+    def __call__(self, fn: types.JsonEncryptor) -> types.JsonEncryptor:
+        """Register the default JSON encryption handler.
+
+        Args:
+            fn: The handler function
+
+        Returns:
+            The registered handler function
+
+        Raises:
+            DuplicateHandlerError: If handler already registered
+            TypeError: If handler has invalid signature
+        """
+        if self._parent._json_encryptor is not None:
+            raise DuplicateHandlerError("Default JSON encryptor already registered")
+        _validate_handler(fn, "Default JSON encryptor")
+        self._parent._json_encryptor = fn
+        return fn
+
+    def __getattr__(
+        self, model: str
+    ) -> typing.Callable[[types.JsonEncryptor], types.JsonEncryptor]:
+        """Dynamic attribute access for model-specific handlers.
+
+        Allows @encryption.encrypt.json.thread, @encryption.encrypt.json.assistant, etc.
+
+        Raises:
+            DuplicateHandlerError: If handler already registered for this model
+            TypeError: If handler has invalid signature
+        """
+
+        def decorator(fn: types.JsonEncryptor) -> types.JsonEncryptor:
+            if model in self._parent._json_encryptors:
+                raise DuplicateHandlerError(
+                    f"JSON encryptor for model '{model}' already registered"
+                )
+            _validate_handler(fn, f"JSON encryptor for model '{model}'")
+            self._parent._json_encryptors[model] = fn
+            return fn
+
+        return decorator
+
+
+class _JsonDecryptDecorators:
+    """Dynamic decorator factory for JSON decryption handlers.
+
+    Supports both default and model-specific handlers:
+    - @encryption.decrypt.json - default handler for all models
+    - @encryption.decrypt.json.thread - handler for thread model
+    """
+
+    def __init__(self, parent: Encryption):
+        self._parent = parent
+
+    def __call__(self, fn: types.JsonDecryptor) -> types.JsonDecryptor:
+        """Register the default JSON decryption handler.
+
+        Args:
+            fn: The handler function
+
+        Returns:
+            The registered handler function
+
+        Raises:
+            DuplicateHandlerError: If handler already registered
+            TypeError: If handler has invalid signature
+        """
+        if self._parent._json_decryptor is not None:
+            raise DuplicateHandlerError("Default JSON decryptor already registered")
+        _validate_handler(fn, "Default JSON decryptor")
+        self._parent._json_decryptor = fn
+        return fn
+
+    def __getattr__(
+        self, model: str
+    ) -> typing.Callable[[types.JsonDecryptor], types.JsonDecryptor]:
+        """Dynamic attribute access for model-specific handlers.
+
+        Allows @encryption.decrypt.json.thread, @encryption.decrypt.json.assistant, etc.
+
+        Raises:
+            DuplicateHandlerError: If handler already registered for this model
+            TypeError: If handler has invalid signature
+        """
+
+        def decorator(fn: types.JsonDecryptor) -> types.JsonDecryptor:
+            if model in self._parent._json_decryptors:
+                raise DuplicateHandlerError(
+                    f"JSON decryptor for model '{model}' already registered"
+                )
+            _validate_handler(fn, f"JSON decryptor for model '{model}'")
+            self._parent._json_decryptors[model] = fn
+            return fn
+
+        return decorator
+
+
 class _EncryptDecorators:
     """Decorators for encryption handlers.
 
@@ -73,6 +181,7 @@ class _EncryptDecorators:
 
     def __init__(self, parent: Encryption):
         self._parent = parent
+        self._json = _JsonEncryptDecorators(parent)
 
     def blob(self, fn: types.BlobEncryptor) -> types.BlobEncryptor:
         """Register a blob encryption handler.
@@ -103,32 +212,29 @@ class _EncryptDecorators:
         self._parent._blob_encryptor = fn
         return fn
 
-    def json(self, fn: types.JsonEncryptor) -> types.JsonEncryptor:
-        """Register the JSON encryption handler.
+    @property
+    def json(self) -> _JsonEncryptDecorators:
+        """Access JSON encryption decorators.
+
+        Supports model-specific handlers:
+        - @encryption.encrypt.json - default handler for all models
+        - @encryption.encrypt.json.thread - handler for thread model only
+        - @encryption.encrypt.json.assistant - handler for assistant model only
 
         Example:
             ```python
             @encryption.encrypt.json
-            async def encrypt_json(ctx: EncryptionContext, data: dict) -> dict:
-                # Encrypt the data
+            async def default_encrypt(ctx: EncryptionContext, data: dict) -> dict:
+                # Default encryption for all models
                 return encrypt_data(data)
+
+            @encryption.encrypt.json.thread
+            async def encrypt_thread(ctx: EncryptionContext, data: dict) -> dict:
+                # Special encryption for thread model only
+                return encrypt_thread_data(data)
             ```
-
-        Args:
-            fn: The encryption handler function
-
-        Returns:
-            The registered handler function
-
-        Raises:
-            DuplicateHandlerError: If JSON encryptor already registered
-            TypeError: If handler has invalid signature
         """
-        if self._parent._json_encryptor is not None:
-            raise DuplicateHandlerError("JSON encryptor already registered")
-        _validate_handler(fn, "JSON encryptor")
-        self._parent._json_encryptor = fn
-        return fn
+        return self._json
 
 
 class _DecryptDecorators:
@@ -140,6 +246,7 @@ class _DecryptDecorators:
 
     def __init__(self, parent: Encryption):
         self._parent = parent
+        self._json = _JsonDecryptDecorators(parent)
 
     def blob(self, fn: types.BlobDecryptor) -> types.BlobDecryptor:
         """Register a blob decryption handler.
@@ -170,32 +277,29 @@ class _DecryptDecorators:
         self._parent._blob_decryptor = fn
         return fn
 
-    def json(self, fn: types.JsonDecryptor) -> types.JsonDecryptor:
-        """Register the JSON decryption handler.
+    @property
+    def json(self) -> _JsonDecryptDecorators:
+        """Access JSON decryption decorators.
+
+        Supports model-specific handlers:
+        - @encryption.decrypt.json - default handler for all models
+        - @encryption.decrypt.json.thread - handler for thread model only
+        - @encryption.decrypt.json.assistant - handler for assistant model only
 
         Example:
             ```python
             @encryption.decrypt.json
-            async def decrypt_json(ctx: EncryptionContext, data: dict) -> dict:
-                # Decrypt the data
+            async def default_decrypt(ctx: EncryptionContext, data: dict) -> dict:
+                # Default decryption for all models
                 return decrypt_data(data)
+
+            @encryption.decrypt.json.thread
+            async def decrypt_thread(ctx: EncryptionContext, data: dict) -> dict:
+                # Special decryption for thread model only
+                return decrypt_thread_data(data)
             ```
-
-        Args:
-            fn: The decryption handler function
-
-        Returns:
-            The registered handler function
-
-        Raises:
-            DuplicateHandlerError: If JSON decryptor already registered
-            TypeError: If handler has invalid signature
         """
-        if self._parent._json_decryptor is not None:
-            raise DuplicateHandlerError("JSON decryptor already registered")
-        _validate_handler(fn, "JSON decryptor")
-        self._parent._json_decryptor = fn
-        return fn
+        return self._json
 
 
 class Encryption:
@@ -232,28 +336,6 @@ class Encryption:
     Then the LangGraph server will load your encryption file and use it to
     encrypt/decrypt data at rest.
 
-    !!! warning "JSON Encryptors Must Preserve Keys"
-
-        JSON encryptors **must not add or remove keys** from the input dict.
-        Only values may be transformed. This constraint is **enforced at runtime
-        by the server** and exists because SQL JSONB merge operations (used for
-        partial updates) work at the key level.
-
-        **Correct (per-key encryption):**
-        ```python
-        # Input:  {"secret": "value", "plain": "x"}
-        # Output: {"secret": "<encrypted>", "plain": "x"}  ✓ Keys preserved
-        ```
-
-        **Incorrect (key consolidation):**
-        ```python
-        # Input:  {"secret": "value", "plain": "x"}
-        # Output: {"__encrypted__": "<blob>", "plain": "x"}  ✗ Key changed
-        ```
-
-        If your encryptor needs to store auxiliary data (DEK, IV, etc.), embed it
-        within the encrypted value itself, not as separate keys.
-
     ???+ example "Basic Usage"
 
         ```python
@@ -261,48 +343,89 @@ class Encryption:
 
         my_encryption = Encryption()
 
-        SKIP_FIELDS = {"tenant_id", "owner", "thread_id", "assistant_id"}
-        ENCRYPTED_PREFIX = "encrypted:"
-
         @my_encryption.encrypt.blob
         async def encrypt_blob(ctx: EncryptionContext, blob: bytes) -> bytes:
-            return your_encrypt_bytes(blob)
+            # Call your encryption service
+            return encrypted_blob
 
         @my_encryption.decrypt.blob
         async def decrypt_blob(ctx: EncryptionContext, blob: bytes) -> bytes:
-            return your_decrypt_bytes(blob)
+            # Call your decryption service
+            return decrypted_blob
 
         @my_encryption.encrypt.json
         async def encrypt_json(ctx: EncryptionContext, data: dict) -> dict:
-            result = {}
-            for k, v in data.items():
-                if k in SKIP_FIELDS or v is None:
-                    result[k] = v
+            # Practical encryption strategy:
+            # - "owner" field: unencrypted (for search/filtering)
+            # - "my.customer.org/" prefixed fields: encrypt VALUES only
+            # - All other fields: pass through unencrypted
+            encrypted = {}
+            for key, value in data.items():
+                if key.startswith("my.customer.org/"):
+                    # Encrypt VALUE for sensitive customer data
+                    encrypted[key] = encrypt_value(value)
                 else:
-                    result[k] = ENCRYPTED_PREFIX + your_encrypt_string(v)
-            return result
+                    # Pass through (including "owner" for search)
+                    encrypted[key] = value
+            return encrypted
 
         @my_encryption.decrypt.json
         async def decrypt_json(ctx: EncryptionContext, data: dict) -> dict:
-            result = {}
-            for k, v in data.items():
-                if isinstance(v, str) and v.startswith(ENCRYPTED_PREFIX):
-                    result[k] = your_decrypt_string(v[len(ENCRYPTED_PREFIX):])
+            # Decrypt VALUES for "my.customer.org/" prefixed fields
+            decrypted = {}
+            for key, value in data.items():
+                if key.startswith("my.customer.org/"):
+                    decrypted[key] = decrypt_value(value)
                 else:
-                    result[k] = v
-            return result
+                    decrypted[key] = value
+            return decrypted
+        ```
+
+    ???+ example "Model-Specific Handlers"
+
+        You can register different encryption handlers for different model types
+        (thread, assistant, run, cron, checkpoint, etc.):
+
+        ```python
+        from langgraph_sdk import Encryption, EncryptionContext
+
+        my_encryption = Encryption()
+
+        # Default handler for models without specific handlers
+        @my_encryption.encrypt.json
+        async def default_encrypt(ctx: EncryptionContext, data: dict) -> dict:
+            return standard_encrypt(data)
+
+        # Thread-specific handler (uses different KMS key)
+        @my_encryption.encrypt.json.thread
+        async def encrypt_thread(ctx: EncryptionContext, data: dict) -> dict:
+            return encrypt_with_thread_key(data)
+
+        # Assistant-specific handler
+        @my_encryption.encrypt.json.assistant
+        async def encrypt_assistant(ctx: EncryptionContext, data: dict) -> dict:
+            return encrypt_with_assistant_key(data)
+
+        # Same pattern for decryption
+        @my_encryption.decrypt.json
+        async def default_decrypt(ctx: EncryptionContext, data: dict) -> dict:
+            return standard_decrypt(data)
+
+        @my_encryption.decrypt.json.thread
+        async def decrypt_thread(ctx: EncryptionContext, data: dict) -> dict:
+            return decrypt_with_thread_key(data)
         ```
 
     ???+ example "Field-Specific Logic"
 
-        The `ctx.model` and `ctx.field` attributes tell you which model type and
-        specific field is being encrypted, allowing different logic:
+        The `ctx.field` attribute tells you which specific field is being encrypted,
+        allowing different logic within the same model:
 
         ```python
-        @my_encryption.encrypt.json
-        async def encrypt_json(ctx: EncryptionContext, data: dict) -> dict:
+        @my_encryption.encrypt.json.thread
+        async def encrypt_thread(ctx: EncryptionContext, data: dict) -> dict:
             if ctx.field == "metadata":
-                # Metadata - standard encryption
+                # Thread metadata - standard encryption
                 return encrypt_standard(data)
             elif ctx.field == "values":
                 # Thread values - more sensitive, use stronger encryption
@@ -310,49 +433,6 @@ class Encryption:
             else:
                 return encrypt_standard(data)
         ```
-
-        !!! warning "Model/Field May Differ Between Encrypt and Decrypt"
-
-            Data encrypted with one `(model, field)` pair is **not guaranteed**
-            to be decrypted with the same pair. The server performs SQL JSONB
-            merges that can move encrypted values between models (e.g., cron
-            metadata → run metadata). Your decryption logic must handle data
-            regardless of the `ctx.model` or `ctx.field` values at decrypt time.
-
-            **Safe:** Use `ctx.model`/`ctx.field` for logging or metrics only.
-
-            **Safe:** Encrypt different keys based on `ctx.field`, but use a
-            single decrypt handler that decrypts any value with the encrypted
-            prefix (and passes through plaintext unchanged):
-
-            ```python
-            ENCRYPTED_PREFIX = "enc:"
-
-            @my_encryption.encrypt.json
-            async def encrypt_json(ctx: EncryptionContext, data: dict) -> dict:
-                # Encrypt different keys depending on the field
-                if ctx.field == "context":
-                    keys_to_encrypt = {"api_key", "secret_token"}
-                else:
-                    keys_to_encrypt = {"email", "ssn"}
-                return {
-                    k: ENCRYPTED_PREFIX + encrypt(v) if k in keys_to_encrypt else v
-                    for k, v in data.items()
-                }
-
-            @my_encryption.decrypt.json
-            async def decrypt_json(ctx: EncryptionContext, data: dict) -> dict:
-                # Decrypt ANY value with the prefix, regardless of model/field
-                return {
-                    k: decrypt(v[len(ENCRYPTED_PREFIX):])
-                       if isinstance(v, str) and v.startswith(ENCRYPTED_PREFIX)
-                       else v
-                    for k, v in data.items()
-                }
-            ```
-
-            **Unsafe:** Using different encryption keys or algorithms based on
-            `ctx.model`/`ctx.field` will cause decryption failures.
     """
 
     __slots__ = (
@@ -360,7 +440,9 @@ class Encryption:
         "_blob_encryptor",
         "_context_handler",
         "_json_decryptor",
+        "_json_decryptors",
         "_json_encryptor",
+        "_json_encryptors",
         "decrypt",
         "encrypt",
     )
@@ -382,6 +464,8 @@ class Encryption:
         self._blob_decryptor: types.BlobDecryptor | None = None
         self._json_encryptor: types.JsonEncryptor | None = None
         self._json_decryptor: types.JsonDecryptor | None = None
+        self._json_encryptors: dict[str, types.JsonEncryptor] = {}
+        self._json_decryptors: dict[str, types.JsonDecryptor] = {}
         self._context_handler: types.ContextHandler | None = None
 
     def context(self, fn: types.ContextHandler) -> types.ContextHandler:
@@ -422,33 +506,33 @@ class Encryption:
         return fn
 
     def get_json_encryptor(
-        self,
-        _model: str | None = None,  # kept for langgraph-api compat
+        self, model: str | None = None
     ) -> types.JsonEncryptor | None:
-        """Get the JSON encryptor.
+        """Get the JSON encryptor for a specific model.
 
         Args:
-            _model: Ignored. Kept for backwards compatibility with langgraph-api
-                which passes model_type to this method.
+            model: The model type (e.g., "thread", "assistant"). If None, returns default.
 
         Returns:
-            The JSON encryptor, or None if not registered.
+            Model-specific encryptor if registered, otherwise default encryptor, or None.
         """
+        if model and model in self._json_encryptors:
+            return self._json_encryptors[model]
         return self._json_encryptor
 
     def get_json_decryptor(
-        self,
-        _model: str | None = None,  # kept for langgraph-api compat
+        self, model: str | None = None
     ) -> types.JsonDecryptor | None:
-        """Get the JSON decryptor.
+        """Get the JSON decryptor for a specific model.
 
         Args:
-            _model: Ignored. Kept for backwards compatibility with langgraph-api
-                which passes model_type to this method.
+            model: The model type (e.g., "thread", "assistant"). If None, returns default.
 
         Returns:
-            The JSON decryptor, or None if not registered.
+            Model-specific decryptor if registered, otherwise default decryptor, or None.
         """
+        if model and model in self._json_decryptors:
+            return self._json_decryptors[model]
         return self._json_decryptor
 
     def __repr__(self) -> str:
@@ -461,6 +545,10 @@ class Encryption:
             handlers.append("json_encryptor")
         if self._json_decryptor:
             handlers.append("json_decryptor")
+        if self._json_encryptors:
+            handlers.append(f"json_encryptors({list(self._json_encryptors.keys())})")
+        if self._json_decryptors:
+            handlers.append(f"json_decryptors({list(self._json_decryptors.keys())})")
         if self._context_handler:
             handlers.append("context_handler")
         return f"Encryption(handlers=[{', '.join(handlers)}])"

libs/sdk-py/langgraph_sdk/schema.py

@@ -167,7 +167,7 @@ class Config(TypedDict, total=False):
     """
     Runtime values for attributes previously made configurable on this Runnable,
     or sub-Runnables, through .configurable_fields() or .configurable_alternatives().
-    Check .output_schema() for a description of the attributes that have been made
+    Check .output_schema() for a description of the attributes that have been made 
     configurable.
     """
 
@@ -301,7 +301,7 @@ class ThreadState(TypedDict):
     values: list[dict] | dict[str, Any]
     """The state values."""
     next: Sequence[str]
-    """The next nodes to execute. If empty, the thread is done until new input is
+    """The next nodes to execute. If empty, the thread is done until new input is 
     received."""
     checkpoint: Checkpoint
     """The ID of the checkpoint."""
@@ -476,7 +476,7 @@ class Item(TypedDict):
     """The namespace of the item. A namespace is analogous to a document's directory."""
     key: str
     """The unique identifier of the item within its namespace.
-
+    
     In general, keys needn't be globally unique.
     """
     value: dict[str, Any]
@@ -519,8 +519,6 @@ class StreamPart(NamedTuple):
     """The type of event for this stream part."""
     data: dict
     """The data payload associated with the event."""
-    id: str | None = None
-    """The ID of the event."""
 
 
 class Send(TypedDict):

libs/sdk-py/langgraph_sdk/sse.py

@@ -103,7 +103,6 @@ class SSEDecoder:
             sse = StreamPart(
                 event=self._event,
                 data=orjson.loads(self._data) if self._data else None,  # type: ignore[invalid-argument-type]
-                id=self.last_event_id,
             )
 
             # NOTE: as per the SSE spec, do not reset last_event_id.

libs/sdk-py/tests/test_client_stream.py

@@ -50,7 +50,7 @@ def iter_lines_raw(payload: list[bytes]) -> Iterator[BytesLike]:
     yield from decoder.flush()
 
 
-def test_stream_sse():
+def test_stream_see():
     for groups in (
         [RESPONSE_PAYLOAD],
         RESPONSE_PAYLOAD.splitlines(keepends=True),
@@ -150,9 +150,9 @@ def test_sync_http_client_stream_recovers_after_disconnect():
 
     assert call_count == 2
     assert parts == [
-        StreamPart(event="values", data={"step": 1}, id="1"),
-        StreamPart(event="values", data={"step": 2}, id="2"),
-        StreamPart(event="end", data=None, id="2"),
+        StreamPart(event="values", data={"step": 1}),
+        StreamPart(event="values", data={"step": 2}),
+        StreamPart(event="end", data=None),  # ty: ignore
     ]
 
 
@@ -222,9 +222,9 @@ async def test_http_client_stream_recovers_after_disconnect():
 
     assert call_count == 2
     assert parts == [
-        StreamPart(event="values", data={"step": 1}, id="1"),
-        StreamPart(event="values", data={"step": 2}, id="2"),
-        StreamPart(event="end", data=None, id="2"),
+        StreamPart(event="values", data={"step": 1}),
+        StreamPart(event="values", data={"step": 2}),
+        StreamPart(event="end", data=None),
     ]
 
 

libs/sdk-py/tests/test_encryption.py

@@ -26,6 +26,14 @@ class TestHandlerValidation:
         async def json_dec(_ctx, data):
             return data
 
+        @encryption.encrypt.json.thread
+        async def thread_enc(_ctx, data):
+            return data
+
+        @encryption.decrypt.json.custom
+        async def custom_dec(_ctx, data):
+            return data
+
         # All duplicates should raise
         with pytest.raises(DuplicateHandlerError):
 
@@ -51,6 +59,18 @@ class TestHandlerValidation:
             async def dup(_ctx, data):
                 return data
 
+        with pytest.raises(DuplicateHandlerError):
+
+            @encryption.encrypt.json.thread
+            async def dup(_ctx, data):
+                return data
+
+        with pytest.raises(DuplicateHandlerError):
+
+            @encryption.decrypt.json.custom
+            async def dup(_ctx, data):
+                return data
+
     def test_handlers_must_be_async(self):
         """Sync functions raise TypeError."""
         encryption = Encryption()