chore: server runtime type (#6774)

Main jtbd here:
a) clarify who/how a graph is being accessed and make the factory aware
of the `context` where relevant (and make it obvious when it is
available)
b) make it more clear when you can bypass / defer resources with
expensive lifespans (like MCp connections)
c) make auth access more type-safe.

Gives us room to add other information, like:
- langsmith distributed tracing information



---- old
Can start doing things like this:

```
def my_graph(runtime: ServerRuntime):
     if runtime.ensure_user().permissions not in ("foo"):
         raise ValueError("bar")
```
etc.

Points of expected confusion:
- You won't have a stream_writer in this context.
- This won't be an accessible object within the graph, only the graph
factory.


For maintainers, related draft PR int he server
https://github.com/langchain-ai/langgraph/pull/6774

.github/CONTRIBUTING.md

@@ -1,6 +0,0 @@
-# Contributing to LangGraph
-
-Hi there! Thank you for even being interested in contributing to LangGraph.
-As an open-source project in a rapidly developing field, we are extremely open to contributions, whether they involve new features, improved infrastructure, better documentation, or bug fixes.
-
-To learn how to contribute to LangGraph, please follow the [contribution guide here](https://docs.langchain.com/oss/python/contributing).

.github/ISSUE_TEMPLATE/bug-report.yml

@@ -1,43 +1,60 @@
 name: "\U0001F41B Bug Report"
-description: Report a bug in LangGraph. To report a security issue, please instead use the security option below. For questions, please use the LangChain Forum at forum.langchain.com.
-labels: [pending, bug]
+description: Report a bug in LangGraph. To report a security issue, please instead use the security option (below). For questions, please use the LangChain forum (below).
+labels: ["bug"]
+type: bug
 body:
   - type: markdown
     attributes:
       value: |
-        Thank you for taking the time to file a bug report. 
+        Thank you for taking the time to file a bug report.
 
-        Use this to report BUGS in LangGraph. For usage questions, feature requests and general design questions, please use the [LangChain Forum](https://forum.langchain.com/).
+        For usage questions, feature requests and general design questions, please use the [LangChain Forum](https://forum.langchain.com/).
 
-        Relevant links to check before filing a bug report to see if your issue has already been reported, fixed or
-        if there's another way to solve your problem:
+        Check these before submitting to see if your issue has already been reported, fixed or if there's another way to solve your problem:
 
-        * [LangChain Forum](https://forum.langchain.com/),
-        * [LangGraph Github Issues](https://github.com/langchain-ai/langgraph/issues),
-        * [LangChain documentation with the integrated search](https://docs.langchain.com/),
+        * [Documentation](https://docs.langchain.com/oss/python/langgraph/overview),
+        * [API Reference Documentation](https://reference.langchain.com/python/),
+        * [LangChain ChatBot](https://chat.langchain.com/)
         * [GitHub search](https://github.com/langchain-ai/langgraph),
+        * [LangChain Forum](https://forum.langchain.com/),
   - type: checkboxes
     id: checks
     attributes:
       label: Checked other resources
-      description: Before submitting this issue, please confirm that you have completed all the steps below by checking each option. These steps help ensure your issue is well-defined, relevant, and actionable.
+      description: Please confirm and check all the following options.
       options:
-        - label: This is a bug, not a usage question. For questions, please use the LangChain Forum (https://forum.langchain.com/).
+        - label: This is a bug, not a usage question.
           required: true
-        - label: I added a clear and detailed title that summarizes the issue.
+        - label: I added a clear and descriptive title that summarizes this issue.
           required: true
-        - label: I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
+        - label: I used the GitHub search to find a similar question and didn't find it.
           required: true
-        - label: I included a self-contained, minimal example that demonstrates the issue INCLUDING all the relevant imports. The code run AS IS to reproduce the issue.
+        - label: I am sure that this is a bug in LangGraph rather than my code.
+          required: true
+        - label: The bug is not resolved by updating to the latest stable version of LangGraph (or the specific integration package).
+          required: true
+        - label: This is not related to the langchain-community package.
+          required: true
+        - label: I posted a self-contained, minimal, reproducible example. A maintainer can copy it and run it AS IS.
           required: true
   - type: textarea
     id: reproduction
     validations:
       required: true
     attributes:
-      label: Example Code
+      label: Reproduction Steps / Example Code (Python)
       description: |
-        Please add a self-contained, [minimal, reproducible, example](https://stackoverflow.com/help/minimal-reproducible-example) with your use case. Replace this code with your own!
+        Please add a self-contained, [minimal, reproducible, example](https://stackoverflow.com/help/minimal-reproducible-example) with your use case.
+
+        If a maintainer can copy it, run it, and see it right away, there's a much higher chance that you'll be able to get help.
+
+        **Important!**
+
+        * Avoid screenshots, as they are hard to read and (more importantly) don't allow others to copy-and-paste your code.
+        * Reduce your code to the minimum required to reproduce the issue if possible.
+
+        (This will be automatically formatted into code, so no need for backticks.)
+      render: python
       placeholder: |
         from langgraph.graph import StateGraph
 
@@ -46,17 +63,13 @@ body:
           
         chain = StateGraph(list)
         chain.invoke('Hello!')
-      render: python
   - type: textarea
-    id: error
-    validations:
-      required: false
     attributes:
       label: Error Message and Stack Trace (if applicable)
       description: |
-        If you are reporting an error, please include the full error message and stack trace.
-      placeholder: |
-        Exception + full stack trace
+        If you are reporting an error, please copy and paste the full error message and
+        stack trace.
+        (This will be automatically formatted into code, so no need for backticks.)
       render: shell
   - type: textarea
     id: description
@@ -77,7 +90,18 @@ body:
     attributes:
       label: System Info
       description: |
-        Run on your machine: `python -m langchain_core.sys_info`
+        Please share your system info with us.
+
+        Run the following command in your terminal and paste the output here:
+
+        `python -m langchain_core.sys_info`
+
+        or if you have an existing python interpreter running:
+
+        ```python
+        from langchain_core import sys_info
+        sys_info.print_sys_info()
+        ```
       placeholder: |
         python -m langchain_core.sys_info
     validations:

.github/ISSUE_TEMPLATE/config.yml

@@ -1,9 +1,15 @@
 blank_issues_enabled: false
 version: 2.1
 contact_links:
-  - name: Documentation
-    url: https://github.com/langchain-ai/docs/issues/new?template=langgraph.yml
-    about: Report an issue related to the LangGraph documentation
-  - name: LangChain Forum
+  - name: 💬 LangChain Forum
     url:  https://forum.langchain.com/
     about: General community discussions and support
+  - name: 📚 LangGraph Documentation
+    url: https://docs.langchain.com/oss/python/langgraph/overview
+    about: View the official LangGraph documentation
+  - name: 📚 API Reference Documentation
+    url: https://reference.langchain.com/python/
+    about: View the official LangGraph API reference documentation
+  - name: 📚 Documentation issue
+    url: https://github.com/langchain-ai/docs/issues/new?template=02-langgraph.yml
+    about: Report an issue related to the LangGraph documentation

.github/PULL_REQUEST_TEMPLATE.md

@@ -21,7 +21,7 @@ Thank you for contributing to LangGraph! Follow these steps to mark your pull re
   1. A test for the integration, preferably unit tests that do not rely on network access,
   2. An example notebook showing its use. It lives in `docs/docs/integrations` directory.
 
-- [ ] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. We will not consider a PR unless these three are passing in CI. See [contribution guidelines](https://github.com/langchain-ai/langgraph/blob/main/CONTRIBUTING.md) for more.
+- [ ] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. We will not consider a PR unless these three are passing in CI. See [contribution guidelines](https://docs.langchain.com/oss/python/contributing/overview) for more.
 
 Additional guidelines:
 

AGENTS.md

@@ -53,3 +53,5 @@ sdk-js (standalone)
 ```
 
 Changes to a library may impact all of its dependents shown above.
+
+- Do NOT use Sphinx-style double backtick formatting (` ``code`` `). Use single backticks (`` `code` ``) for inline code references in docstrings and comments.

CLAUDE.md

@@ -53,3 +53,5 @@ sdk-js (standalone)
 ```
 
 Changes to a library may impact all of its dependents shown above.
+
+- Do NOT use Sphinx-style double backtick formatting (` ``code`` `). Use single backticks (`` `code` ``) for inline code references in docstrings and comments.

README.md

@@ -79,7 +79,7 @@ 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.).
+- [Guides](https://docs.langchain.com/oss/python/langgraph/overview): 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.
 - [LangChain Forum](https://forum.langchain.com/): Connect with the community and share all of your technical questions, ideas, and feedback.

examples/README.md

@@ -0,0 +1,3 @@
+# LangGraph examples
+
+This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview). Please refer to the LangChain docs for the most up-to-date examples and usage guidelines for LangGraph.

examples/chatbot-simulation-evaluation/agent-simulation-evaluation.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "10251c1c",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/chatbot-simulation-evaluation/agent-simulation-evaluation.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c5fc63df",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/chatbot-simulation-evaluation/langsmith-agent-simulation-evaluation.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "a4351a24",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/chatbot-simulation-evaluation/langsmith-agent-simulation-evaluation.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4cc9af1e",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/chatbot-simulation-evaluation/simulation_utils.py

@@ -0,0 +1,203 @@
+import functools
+from typing import Annotated, Any, Callable, Dict, List, Optional, Union
+
+from langchain_community.adapters.openai import convert_message_to_dict
+from langchain_core.messages import AIMessage, AnyMessage, BaseMessage, HumanMessage
+from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
+from langchain_core.runnables import Runnable, RunnableLambda
+from langchain_core.runnables import chain as as_runnable
+from langchain_openai import ChatOpenAI
+from typing_extensions import TypedDict
+
+from langgraph.graph import END, StateGraph, START
+
+
+def langchain_to_openai_messages(messages: List[BaseMessage]):
+    """
+    Convert a list of langchain base messages to a list of openai messages.
+
+    Parameters:
+        messages (List[BaseMessage]): A list of langchain base messages.
+
+    Returns:
+        List[dict]: A list of openai messages.
+    """
+
+    return [
+        convert_message_to_dict(m) if isinstance(m, BaseMessage) else m
+        for m in messages
+    ]
+
+
+def create_simulated_user(
+    system_prompt: str, llm: Runnable | None = None
+) -> Runnable[Dict, AIMessage]:
+    """
+    Creates a simulated user for chatbot simulation.
+
+    Args:
+        system_prompt (str): The system prompt to be used by the simulated user.
+        llm (Runnable | None, optional): The language model to be used for the simulation.
+            Defaults to gpt-3.5-turbo.
+
+    Returns:
+        Runnable[Dict, AIMessage]: The simulated user for chatbot simulation.
+    """
+    return ChatPromptTemplate.from_messages(
+        [
+            ("system", system_prompt),
+            MessagesPlaceholder(variable_name="messages"),
+        ]
+    ) | (llm or ChatOpenAI(model="gpt-3.5-turbo")).with_config(
+        run_name="simulated_user"
+    )
+
+
+Messages = Union[list[AnyMessage], AnyMessage]
+
+
+def add_messages(left: Messages, right: Messages) -> Messages:
+    if not isinstance(left, list):
+        left = [left]
+    if not isinstance(right, list):
+        right = [right]
+    return left + right
+
+
+class SimulationState(TypedDict):
+    """
+    Represents the state of a simulation.
+
+    Attributes:
+        messages (List[AnyMessage]): A list of messages in the simulation.
+        inputs (Optional[dict[str, Any]]): Optional inputs for the simulation.
+    """
+
+    messages: Annotated[List[AnyMessage], add_messages]
+    inputs: Optional[dict[str, Any]]
+
+
+def create_chat_simulator(
+    assistant: (
+        Callable[[List[AnyMessage]], str | AIMessage]
+        | Runnable[List[AnyMessage], str | AIMessage]
+    ),
+    simulated_user: Runnable[Dict, AIMessage],
+    *,
+    input_key: str,
+    max_turns: int = 6,
+    should_continue: Optional[Callable[[SimulationState], str]] = None,
+):
+    """Creates a chat simulator for evaluating a chatbot.
+
+    Args:
+        assistant: The chatbot assistant function or runnable object.
+        simulated_user: The simulated user object.
+        input_key: The key for the input to the chat simulation.
+        max_turns: The maximum number of turns in the chat simulation. Default is 6.
+        should_continue: Optional function to determine if the simulation should continue.
+            If not provided, a default function will be used.
+
+    Returns:
+        The compiled chat simulation graph.
+
+    """
+    graph_builder = StateGraph(SimulationState)
+    graph_builder.add_node(
+        "user",
+        _create_simulated_user_node(simulated_user),
+    )
+    graph_builder.add_node(
+        "assistant", _fetch_messages | assistant | _coerce_to_message
+    )
+    graph_builder.add_edge("assistant", "user")
+    graph_builder.add_conditional_edges(
+        "user",
+        should_continue or functools.partial(_should_continue, max_turns=max_turns),
+    )
+    # If your dataset has a 'leading question/input', then we route first to the assistant, otherwise, we let the user take the lead.
+    graph_builder.add_edge(START, "assistant" if input_key is not None else "user")
+
+    return (
+        RunnableLambda(_prepare_example).bind(input_key=input_key)
+        | graph_builder.compile()
+    )
+
+
+## Private methods
+
+
+def _prepare_example(inputs: dict[str, Any], input_key: Optional[str] = None):
+    if input_key is not None:
+        if input_key not in inputs:
+            raise ValueError(
+                f"Dataset's example input must contain the provided input key: '{input_key}'.\nFound: {list(inputs.keys())}"
+            )
+        messages = [HumanMessage(content=inputs[input_key])]
+        return {
+            "inputs": {k: v for k, v in inputs.items() if k != input_key},
+            "messages": messages,
+        }
+    return {"inputs": inputs, "messages": []}
+
+
+def _invoke_simulated_user(state: SimulationState, simulated_user: Runnable):
+    """Invoke the simulated user node."""
+    runnable = (
+        simulated_user
+        if isinstance(simulated_user, Runnable)
+        else RunnableLambda(simulated_user)
+    )
+    inputs = state.get("inputs", {})
+    inputs["messages"] = state["messages"]
+    return runnable.invoke(inputs)
+
+
+def _swap_roles(state: SimulationState):
+    new_messages = []
+    for m in state["messages"]:
+        if isinstance(m, AIMessage):
+            new_messages.append(HumanMessage(content=m.content))
+        else:
+            new_messages.append(AIMessage(content=m.content))
+    return {
+        "inputs": state.get("inputs", {}),
+        "messages": new_messages,
+    }
+
+
+@as_runnable
+def _fetch_messages(state: SimulationState):
+    """Invoke the simulated user node."""
+    return state["messages"]
+
+
+def _convert_to_human_message(message: BaseMessage):
+    return {"messages": [HumanMessage(content=message.content)]}
+
+
+def _create_simulated_user_node(simulated_user: Runnable):
+    """Simulated user accepts a {"messages": [...]} argument and returns a single message."""
+    return (
+        _swap_roles
+        | RunnableLambda(_invoke_simulated_user).bind(simulated_user=simulated_user)
+        | _convert_to_human_message
+    )
+
+
+def _coerce_to_message(assistant_output: str | BaseMessage):
+    if isinstance(assistant_output, str):
+        return {"messages": [AIMessage(content=assistant_output)]}
+    else:
+        return {"messages": [assistant_output]}
+
+
+def _should_continue(state: SimulationState, max_turns: int = 6):
+    messages = state["messages"]
+    # TODO support other stop criteria
+    if len(messages) > max_turns:
+        return END
+    elif messages[-1].content.strip() == "FINISHED":
+        return END
+    else:
+        return "assistant"

examples/chatbots/information-gather-prompting.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "a9014f94",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/chatbots/information-gather-prompting.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f47ce992",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/code_assistant/langgraph_code_assistant.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "1f2f13ca",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/code_assistant/langgraph_code_assistant.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5e4c9bfe",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/customer-support/customer-support.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "a8232bc9",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/customer-support/customer-support.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "63da8671",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/extraction/retries.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "8dbdba5b",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/extraction/retries.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1d444b7f",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/human_in_the_loop/wait-user-input.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "3ecab357",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/how-tos/human_in_the_loop/wait-user-input.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3f2866bd",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/lats/lats.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "09038b53",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/lats/lats.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b1669748",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/llm-compiler/LLMCompiler.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "85205e97",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/llm-compiler/LLMCompiler.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2fdab366",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/multi_agent/hierarchical_agent_teams.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "5cc8a2ad",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/multi_agent/hierarchical_agent_teams.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b9f3508a",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/multi_agent/multi-agent-collaboration.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "d2b507b9",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/multi_agent/multi-agent-collaboration.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "41a8f10a",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/plan-and-execute/plan-and-execute.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "9138f92e",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/plan-and-execute/plan-and-execute.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "093678ba",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/react-agent-from-scratch.ipynb

@@ -0,0 +1,40 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "294995c4",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/how-tos/react-agent-from-scratch.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

examples/react-agent-structured-output.ipynb

@@ -0,0 +1,40 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "40f0d107",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/how-tos/react-agent-structured-output.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

examples/reflection/reflection.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "658773a2",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/reflection/reflection.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1cb60657",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/reflexion/reflexion.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "caf07859",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/reflexion/reflexion.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cd1df0e0",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/rewoo/rewoo.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "961f43ec",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/rewoo/rewoo.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7f00c427",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/run-id-langsmith.ipynb

@@ -0,0 +1,40 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "bbd6e9b8",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/how-tos/run-id-langsmith.md)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

examples/self-discover/self-discover.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "f6db1873",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/self-discover/self-discover.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "219a78f9",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/subgraph.ipynb

@@ -0,0 +1,40 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "f49876e1",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/how-tos/subgraph.md)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

examples/tool-calling.ipynb

@@ -0,0 +1,40 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "7fd8bd65",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/how-tos/tool-calling.md)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

examples/tutorials/sql-agent.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "83c2223f",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/sql/sql-agent.md)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "57f924b1",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/tutorials/tnt-llm/tnt-llm.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "11140167",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/tnt-llm/tnt-llm.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1a2ba3e6",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/usaco/usaco.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "9dffdb54",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/usaco/usaco.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "579c9959",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/web-navigation/web_voyager.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "007ea2e9",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/web-navigation/web_voyager.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f0d7b895",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

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

@@ -550,6 +550,11 @@ class AsyncPostgresStore(AsyncBatchedBaseStore, BasePostgresStore[_ainternal.Con
                 Will be applied regardless of whether the PostgresStore instance was initialized with a pipeline.
                 If pipeline mode is not supported, will fall back to using transaction context manager.
         """
+        is_pooled_conn = isinstance(self.conn, AsyncConnectionPool)
+        # With AsyncConnectionPool, each _cursor() call checks out its own connection.
+        # The pool does not hand out the same connection concurrently, so a shared lock
+        # across calls is unnecessary here.
+        lock = asyncio.Lock() if is_pooled_conn else self.lock
         async with _ainternal.get_connection(self.conn) as conn:
             if self.pipe:
                 # a connection in pipeline mode can be used concurrently
@@ -566,21 +571,21 @@ class AsyncPostgresStore(AsyncBatchedBaseStore, BasePostgresStore[_ainternal.Con
                 # thread/coroutine at a time, so we acquire a lock
                 if self.supports_pipeline:
                     async with (
-                        self.lock,
+                        lock,
                         conn.pipeline(),
                         conn.cursor(binary=True, row_factory=dict_row) as cur,
                     ):
                         yield cur
                 else:
                     async with (
-                        self.lock,
+                        lock,
                         conn.transaction(),
                         conn.cursor(binary=True, row_factory=dict_row) as cur,
                     ):
                         yield cur
             else:
                 async with (
-                    self.lock,
+                    lock,
                     conn.cursor(binary=True, row_factory=dict_row) as cur,
                 ):
                     yield cur

libs/checkpoint-postgres/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-checkpoint-postgres"
-version = "3.0.3"
+version = "3.0.4"
 description = "Library with a Postgres implementation of LangGraph checkpoint saver."
 authors = []
 requires-python = ">=3.10"
@@ -20,7 +20,7 @@ dependencies = [
 
 [project.urls]
 Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/checkpoint-postgres"
-Twitter = "https://x.com/LangChainAI"
+Twitter = "https://x.com/LangChain"
 Slack = "https://www.langchain.com/join-community"
 Reddit = "https://www.reddit.com/r/LangChain/"
 

libs/checkpoint-postgres/uv.lock

@@ -13,16 +13,16 @@ wheels = [
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
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+    { url = "https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c", size = 113592, upload-time = "2026-01-06T11:45:19.497Z" },
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 [[package]]
@@ -36,11 +36,11 @@ wheels = [
 
 [[package]]
 name = "certifi"
-version = "2025.11.12"
+version = "2026.1.4"
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-sdist = { url = "https://files.pythonhosted.org/packages/a2/8c/58f469717fa48465e4a50c014a0400602d3c437d7c0c468e17ada824da3a/certifi-2025.11.12.tar.gz", hash = "sha256:d8ab5478f2ecd78af242878415affce761ca6bc54a22a27e026d7c25357c3316", size = 160538, upload-time = "2025-11-12T02:54:51.517Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/e0/2d/a891ca51311197f6ad14a7ef42e2399f36cf2f9bd44752b3dc4eab60fdc5/certifi-2026.1.4.tar.gz", hash = "sha256:ac726dd470482006e014ad384921ed6438c457018f4b3d204aea4281258b2120", size = 154268, upload-time = "2026-01-04T02:42:41.825Z" }
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+    { url = "https://files.pythonhosted.org/packages/e6/ad/3cc14f097111b4de0040c83a525973216457bbeeb63739ef1ed275c1c021/certifi-2026.1.4-py3-none-any.whl", hash = "sha256:9943707519e4add1115f44c2bc244f782c0249876bf51b6599fee1ffbedd685c", size = 152900, upload-time = "2026-01-04T02:42:40.15Z" },
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 [[package]]
@@ -240,7 +240,7 @@ wheels = [
 
 [[package]]
 name = "langchain-core"
-version = "1.1.3"
+version = "1.2.7"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "jsonpatch" },
@@ -252,9 +252,9 @@ dependencies = [
     { name = "typing-extensions" },
     { name = "uuid-utils" },
 ]
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+sdist = { url = "https://files.pythonhosted.org/packages/a2/0e/664d8d81b3493e09cbab72448d2f9d693d1fa5aa2bcc488602203a9b6da0/langchain_core-1.2.7.tar.gz", hash = "sha256:e1460639f96c352b4a41c375f25aeb8d16ffc1769499fb1c20503aad59305ced", size = 837039, upload-time = "2026-01-09T17:44:25.505Z" }
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+    { url = "https://files.pythonhosted.org/packages/6e/6f/34a9fba14d191a67f7e2ee3dbce3e9b86d2fa7310e2c7f2c713583481bd2/langchain_core-1.2.7-py3-none-any.whl", hash = "sha256:452f4fef7a3d883357b22600788d37e3d8854ef29da345b7ac7099f33c31828b", size = 490232, upload-time = "2026-01-09T17:44:24.236Z" },
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 [[package]]
@@ -306,7 +306,7 @@ test = [
 
 [[package]]
 name = "langgraph-checkpoint-postgres"
-version = "3.0.3"
+version = "3.0.4"
 source = { editable = "." }
 dependencies = [
     { name = "langgraph-checkpoint" },
@@ -381,7 +381,7 @@ test = [
 
 [[package]]
 name = "langsmith"
-version = "0.4.57"
+version = "0.6.4"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "httpx" },
@@ -393,128 +393,128 @@ dependencies = [
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+    { url = "https://files.pythonhosted.org/packages/dc/14/7061b868a8a6799c8df83768a23f313d4e22075069f01ee3c28fa82aa2c6/uuid_utils-0.13.0-pp311-pypy311_pp73-manylinux_2_24_aarch64.whl", hash = "sha256:5dc4c9f749bd2511b8dcbf0891e658d7d86880022963db050722ad7b502b5e22", size = 333618, upload-time = "2026-01-08T15:48:03.503Z" },
+    { url = "https://files.pythonhosted.org/packages/bc/f1/f48c3c9c343c9071ade5f355403e344d817412d9cf379a2d04b181282e74/uuid_utils-0.13.0-pp311-pypy311_pp73-manylinux_2_24_armv7l.whl", hash = "sha256:516adf07f5b2cdb88d50f489c702b5f1a75ae8b2639bfd254f4192d5f7ee261f", size = 339104, upload-time = "2026-01-08T15:48:05.02Z" },
+    { url = "https://files.pythonhosted.org/packages/47/22/8e3142b4baffee77ce533fe956446d3699ec42f1d5252911208cbef4501e/uuid_utils-0.13.0-pp311-pypy311_pp73-manylinux_2_24_i686.whl", hash = "sha256:aeee3bd89e8de6184a3ab778ce19f5ce9ad32849d1be549516e0ddb257562d8d", size = 359503, upload-time = "2026-01-08T15:48:06.347Z" },
+    { url = "https://files.pythonhosted.org/packages/bd/1a/756f1f9e31b15019c87cd2becb1c596351c50967cd143443da38df8818d1/uuid_utils-0.13.0-pp311-pypy311_pp73-manylinux_2_24_ppc64le.whl", hash = "sha256:97985256c2e59b7caa51f5c8515f64d777328562a9c900ec65e9d627baf72737", size = 467480, upload-time = "2026-01-08T15:48:07.681Z" },
+    { url = "https://files.pythonhosted.org/packages/0a/20/a6929e98d9a461ca49e96194a82a1cc3fd5420f3a2f53cbb34fca438549e/uuid_utils-0.13.0-pp311-pypy311_pp73-manylinux_2_24_x86_64.whl", hash = "sha256:b7ccaa20e24c5f60f41a69ef571ed820737f9b0ade4cbeef56aaa8f80f5aa475", size = 333610, upload-time = "2026-01-08T15:48:09.375Z" },
 ]
 
 [[package]]

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

@@ -3,6 +3,7 @@ from __future__ import annotations
 import asyncio
 import json
 import random
+import threading
 from collections.abc import AsyncIterator, Callable, Iterator, Sequence
 from contextlib import asynccontextmanager
 from typing import Any, TypeVar, cast
@@ -281,8 +282,7 @@ class AsyncSqliteSaver(BaseCheckpointSaver[str]):
         async with self.lock:
             if self.is_setup:
                 return
-            if not self.conn.is_alive():
-                await self.conn
+            await _ensure_connected(self.conn)
             async with self.conn.executescript(
                 """
                 PRAGMA journal_mode=WAL;
@@ -609,3 +609,23 @@ class AsyncSqliteSaver(BaseCheckpointSaver[str]):
         next_v = current_v + 1
         next_h = random.random()
         return f"{next_v:032}.{next_h:016}"
+
+
+async def _ensure_connected(conn: aiosqlite.Connection) -> None:
+    if not _CONN_STARTED_CHECK(conn):
+        await conn
+
+
+def _build_conn_started_check() -> Callable[[aiosqlite.Connection], bool]:
+    is_alive = getattr(aiosqlite.Connection, "is_alive", None)
+    if callable(is_alive):
+        return lambda conn: conn.is_alive()  # type: ignore[attr-defined]
+
+    def _started(conn: aiosqlite.Connection) -> bool:
+        thread: threading.Thread | None = getattr(conn, "_thread", None)
+        return False if thread is None else thread.is_alive()
+
+    return _started
+
+
+_CONN_STARTED_CHECK = _build_conn_started_check()

libs/checkpoint-sqlite/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-checkpoint-sqlite"
-version = "3.0.2"
+version = "3.0.3"
 description = "Library with a SQLite implementation of LangGraph checkpoint saver."
 authors = []
 requires-python = ">=3.10"
@@ -19,7 +19,7 @@ dependencies = [
 
 [project.urls]
 Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/checkpoint-sqlite"
-Twitter = "https://x.com/LangChainAI"
+Twitter = "https://x.com/LangChain"
 Slack = "https://www.langchain.com/join-community"
 Reddit = "https://www.reddit.com/r/LangChain/"
 

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

@@ -119,6 +119,25 @@ class BaseCheckpointSaver(Generic[V]):
     Checkpointers allow LangGraph agents to persist their state
     within and across multiple interactions.
 
+    When a checkpointer is configured, you should pass a `thread_id` in the config when
+    invoking the graph:
+
+    ```python
+    config = {"configurable": {"thread_id": "my-thread"}}
+    graph.invoke(inputs, config)
+    ```
+
+    The `thread_id` is the primary key used to store and retrieve checkpoints. Without
+    it, the checkpointer cannot save state, resume from interrupts, or enable
+    time-travel debugging.
+
+    How you choose ``thread_id`` depends on your use case:
+
+    - **Single-shot workflows**: Use a unique ID (e.g., uuid4) for each run when
+        executions are independent.
+    - **Conversational memory**: Reuse the same `thread_id` across invocations
+        to accumulate state (e.g., chat history) within a conversation.
+
     Attributes:
         serde (SerializerProtocol): Serializer for encoding/decoding checkpoints.
 

libs/checkpoint/pyproject.toml

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

libs/cli/langgraph_cli/__init__.py

@@ -1 +1 @@
-__version__ = "0.4.11"
+__version__ = "0.4.12"

libs/cli/langgraph_cli/schemas.py

@@ -179,6 +179,8 @@ class CheckpointerConfig(TypedDict, total=False):
 
     This configuration requires server version 0.5 or later to take effect.
     """
+    sweep_limit: int | None
+    """Maximum number of threads to process per sweep iteration. Defaults to 1000."""
 
 
 class SecurityConfig(TypedDict, total=False):

libs/cli/pyproject.toml

@@ -19,14 +19,14 @@ 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,<0.8.0 ; python_version >= '3.11'",
     "langgraph-runtime-inmem>=0.7 ; python_version >= '3.11'",
     "python-dotenv>=0.8.0",
 ]
 
 [project.urls]
 Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/cli"
-Twitter = "https://x.com/LangChainAI"
+Twitter = "https://x.com/LangChain"
 Slack = "https://www.langchain.com/join-community"
 Reddit = "https://www.reddit.com/r/LangChain/"
 

libs/cli/schemas/schema.json

@@ -554,6 +554,17 @@
           ],
           "description": "Optional. Defines the serde configuration.\n\nIf provided, the checkpointer will apply serde settings according to the configuration.\nIf omitted, no serde behavior is configured.\n\nThis configuration requires server version 0.5 or later to take effect.\n"
         },
+        "sweep_limit": {
+          "anyOf": [
+            {
+              "type": "integer"
+            },
+            {
+              "type": "null"
+            }
+          ],
+          "description": "Maximum number of threads to process per sweep iteration. Defaults to 1000."
+        },
         "ttl": {
           "anyOf": [
             {

libs/cli/schemas/schema.v0.json

@@ -554,6 +554,17 @@
           ],
           "description": "Optional. Defines the serde configuration.\n\nIf provided, the checkpointer will apply serde settings according to the configuration.\nIf omitted, no serde behavior is configured.\n\nThis configuration requires server version 0.5 or later to take effect.\n"
         },
+        "sweep_limit": {
+          "anyOf": [
+            {
+              "type": "integer"
+            },
+            {
+              "type": "null"
+            }
+          ],
+          "description": "Maximum number of threads to process per sweep iteration. Defaults to 1000."
+        },
         "ttl": {
           "anyOf": [
             {

libs/langgraph/langgraph/_internal/_queue.py

@@ -25,7 +25,7 @@ class AsyncQueue(asyncio.Queue):
             self._getters.append(getter)
             try:
                 await getter
-            except:
+            except BaseException:
                 getter.cancel()  # Just in case getter is not done yet.
                 try:
                     # Clean self._getters from canceled getters.

libs/langgraph/langgraph/graph/state.py

@@ -300,7 +300,56 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
         **kwargs: Unpack[DeprecatedKwargs],
     ) -> Self:
         """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.
+
+        Args:
+            node: The function or runnable this node will run.
+            defer: Whether to defer the execution of the node until the run is about to end.
+            metadata: The metadata associated with the node.
+            input_schema: The input schema for the node. (Default: the graph's state schema)
+            retry_policy: The retry policy for the node.
+
+                If a sequence is provided, the first matching policy will be applied.
+            cache_policy: The cache policy for the node.
+            destinations: Destinations that indicate where a node can route to.
+
+                Useful for edgeless graphs with nodes that return `Command` objects.
+
+                If a `dict` is provided, the keys will be used as the target node names and the values will be used as the labels for the edges.
+
+                If a `tuple` is provided, the values will be used as the target node names.
+
+                !!! warning
+
+                    This is only used for graph rendering and doesn't have any effect on the graph execution.
+
+        Example:
+            ```python
+            from typing_extensions import TypedDict
+
+            from langchain_core.runnables import RunnableConfig
+            from langgraph.graph import START, StateGraph
+
+
+            class State(TypedDict):
+                x: int
+
+
+            def my_node(state: State, config: RunnableConfig) -> State:
+                return {"x": state["x"] + 1}
+
+
+            builder = StateGraph(State)
+            builder.add_node(my_node)  # node name will be 'my_node'
+            builder.add_edge(START, "my_node")
+            graph = builder.compile()
+            graph.invoke({"x": 1})
+            # {'x': 2}
+            ```
+
+        Returns:
+            Self: The instance of the `StateGraph`, allowing for method chaining.
         """
         ...
 
@@ -317,8 +366,61 @@ 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 `StateGraph`, input schema is specified.
+        """Add a new node to the `StateGraph` where input schema is specified.
+
         Will take the name of the function/runnable as the node name.
+
+        Args:
+            node: The function or runnable this node will run.
+            defer: Whether to defer the execution of the node until the run is about to end.
+            metadata: The metadata associated with the node.
+            input_schema: The input schema for the node.
+            retry_policy: The retry policy for the node.
+
+                If a sequence is provided, the first matching policy will be applied.
+            cache_policy: The cache policy for the node.
+            destinations: Destinations that indicate where a node can route to.
+
+                Useful for edgeless graphs with nodes that return `Command` objects.
+
+                If a `dict` is provided, the keys will be used as the target node names and the values will be used as the labels for the edges.
+
+                If a `tuple` is provided, the values will be used as the target node names.
+
+                !!! warning
+
+                    This is only used for graph rendering and doesn't have any effect on the graph execution.
+
+        Example:
+            ```python
+            from typing_extensions import TypedDict
+
+            from langchain_core.runnables import RunnableConfig
+            from langgraph.graph import START, StateGraph
+
+
+            class State(TypedDict):
+                x: int
+
+
+            class NodeInput(TypedDict):
+                x: int
+
+
+            def my_node(state: NodeInput, config: RunnableConfig) -> State:
+                return {"x": state["x"] + 1}
+
+
+            builder = StateGraph(State)
+            builder.add_node(my_node, input_schema=NodeInput)  # node name will be 'my_node'
+            builder.add_edge(START, "my_node")
+            graph = builder.compile()
+            graph.invoke({"x": 1})
+            # {'x': 2}
+            ```
+
+        Returns:
+            Self: The instance of the `StateGraph`, allowing for method chaining.
         """
         ...
 
@@ -336,7 +438,57 @@ 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 `StateGraph`, input schema is inferred as the state schema."""
+        """Add a new node to the `StateGraph`, input schema is inferred as the state schema.
+
+        Args:
+            node: The name of the node.
+            action: The function or runnable this node will run.
+            defer: Whether to defer the execution of the node until the run is about to end.
+            metadata: The metadata associated with the node.
+            input_schema: The input schema for the node. (Default: the graph's state schema)
+            retry_policy: The retry policy for the node.
+
+                If a sequence is provided, the first matching policy will be applied.
+            cache_policy: The cache policy for the node.
+            destinations: Destinations that indicate where a node can route to.
+
+                Useful for edgeless graphs with nodes that return `Command` objects.
+
+                If a `dict` is provided, the keys will be used as the target node names and the values will be used as the labels for the edges.
+
+                If a `tuple` is provided, the values will be used as the target node names.
+
+                !!! warning
+
+                    This is only used for graph rendering and doesn't have any effect on the graph execution.
+
+        Example:
+            ```python
+            from typing_extensions import TypedDict
+
+            from langchain_core.runnables import RunnableConfig
+            from langgraph.graph import START, StateGraph
+
+
+            class State(TypedDict):
+                x: int
+
+
+            def my_node(state: State, config: RunnableConfig) -> State:
+                return {"x": state["x"] + 1}
+
+
+            builder = StateGraph(State)
+            builder.add_node("my_fair_node", my_node)
+            builder.add_edge(START, "my_fair_node")
+            graph = builder.compile()
+            graph.invoke({"x": 1})
+            # {'x': 2}
+            ```
+
+        Returns:
+            Self: The instance of the `StateGraph`, allowing for method chaining.
+        """
         ...
 
     @overload
@@ -353,7 +505,65 @@ 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 `StateGraph`, input schema is specified."""
+        """Add a new node to the `StateGraph`, input schema is specified.
+
+        Args:
+            node: The function or runnable this node will run.
+
+                If a string is provided, it will be used as the node name, and action will be used as the function or runnable.
+            action: The action associated with the node.
+
+                Will be used as the node function or runnable if `node` is a string (node name).
+            defer: Whether to defer the execution of the node until the run is about to end.
+            metadata: The metadata associated with the node.
+            input_schema: The input schema for the node.
+            retry_policy: The retry policy for the node.
+
+                If a sequence is provided, the first matching policy will be applied.
+            cache_policy: The cache policy for the node.
+            destinations: Destinations that indicate where a node can route to.
+
+                Useful for edgeless graphs with nodes that return `Command` objects.
+
+                If a `dict` is provided, the keys will be used as the target node names and the values will be used as the labels for the edges.
+
+                If a `tuple` is provided, the values will be used as the target node names.
+
+                !!! warning
+
+                    This is only used for graph rendering and doesn't have any effect on the graph execution.
+
+        Example:
+            ```python
+            from typing_extensions import TypedDict
+
+            from langchain_core.runnables import RunnableConfig
+            from langgraph.graph import START, StateGraph
+
+
+            class State(TypedDict):
+                x: int
+
+
+            class NodeInput(TypedDict):
+                x: int
+
+
+            def my_node(state: NodeInput, config: RunnableConfig) -> State:
+                return {"x": state["x"] + 1}
+
+
+            builder = StateGraph(State)
+            builder.add_node("my_fair_node", my_node, input_schema=NodeInput)
+            builder.add_edge(START, "my_fair_node")
+            graph = builder.compile()
+            graph.invoke({"x": 1})
+            # {'x': 2}
+            ```
+
+        Returns:
+            Self: The instance of the `StateGraph`, allowing for method chaining.
+        """
         ...
 
     def add_node(
@@ -376,6 +586,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
 
                 If a string is provided, it will be used as the node name, and action will be used as the function or runnable.
             action: The action associated with the node.
+
                 Will be used as the node function or runnable if `node` is a string (node name).
             defer: Whether to defer the execution of the node until the run is about to end.
             metadata: The metadata associated with the node.
@@ -392,7 +603,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
 
                 If a `tuple` is provided, the values will be used as the target node names.
 
-                !!! note
+                !!! warning
 
                     This is only used for graph rendering and doesn't have any effect on the graph execution.
 
@@ -846,6 +1057,19 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
                 If `None`, it may inherit the parent graph's checkpointer when used as a subgraph.
 
                 If `False`, it will not use or inherit any checkpointer.
+
+                **Important**: When a checkpointer is enabled, you should pass a `thread_id`
+                in the config when invoking the graph:
+
+                ```python
+                config = {"configurable": {"thread_id": "my-thread"}}
+                graph.invoke(inputs, config)
+                ```
+
+                The `thread_id` is the key used to store and retrieve checkpoints. Use a
+                unique ID for independent runs, or reuse the same ID to accumulate state
+                across invocations (e.g., for conversation memory).
+
             interrupt_before: An optional list of node names to interrupt before.
             interrupt_after: An optional list of node names to interrupt after.
             debug: A flag indicating whether to enable debug mode.

libs/langgraph/langgraph/pregel/_messages.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 from collections.abc import AsyncIterator, Callable, Iterator, Sequence
+from dataclasses import fields, is_dataclass
 from typing import (
     Any,
     TypeVar,
@@ -11,6 +12,7 @@ from uuid import UUID, uuid4
 from langchain_core.callbacks import BaseCallbackHandler
 from langchain_core.messages import BaseMessage
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, LLMResult
+from pydantic import BaseModel
 
 from langgraph._internal._constants import NS_SEP
 from langgraph.constants import TAG_HIDDEN, TAG_NOSTREAM
@@ -26,6 +28,17 @@ T = TypeVar("T")
 Meta = tuple[tuple[str, ...], dict[str, Any]]
 
 
+def _state_values(obj: Any) -> Sequence[Any]:
+    """Extract top-level field values from a state object (dict, BaseModel, or dataclass)."""
+    if isinstance(obj, dict):
+        return list(obj.values())
+    elif isinstance(obj, BaseModel):
+        return [getattr(obj, k) for k in type(obj).model_fields]
+    elif is_dataclass(obj) and not isinstance(obj, type):
+        return [getattr(obj, f.name) for f in fields(obj)]
+    return ()
+
+
 class StreamMessagesHandler(BaseCallbackHandler, _StreamingCallbackHandler):
     """A callback handler that implements stream_mode=messages.
 
@@ -90,26 +103,14 @@ class StreamMessagesHandler(BaseCallbackHandler, _StreamingCallbackHandler):
             for value in response:
                 if isinstance(value, BaseMessage):
                     self._emit(meta, value, dedupe=True)
-        elif isinstance(response, dict):
-            for value in response.values():
+        else:
+            for value in _state_values(response):
                 if isinstance(value, BaseMessage):
                     self._emit(meta, value, dedupe=True)
                 elif isinstance(value, Sequence):
                     for item in value:
                         if isinstance(item, BaseMessage):
                             self._emit(meta, item, dedupe=True)
-        elif hasattr(response, "__dir__") and callable(response.__dir__):
-            for key in dir(response):
-                try:
-                    value = getattr(response, key)
-                    if isinstance(value, BaseMessage):
-                        self._emit(meta, value, dedupe=True)
-                    elif isinstance(value, Sequence):
-                        for item in value:
-                            if isinstance(item, BaseMessage):
-                                self._emit(meta, item, dedupe=True)
-                except AttributeError:
-                    pass
 
     def tap_output_aiter(
         self, run_id: UUID, output: AsyncIterator[T]
@@ -203,16 +204,15 @@ class StreamMessagesHandler(BaseCallbackHandler, _StreamingCallbackHandler):
             if not self.subgraphs and len(ns) > 0:
                 return
             self.metadata[run_id] = (ns, metadata)
-            if isinstance(inputs, dict):
-                for key, value in inputs.items():
-                    if isinstance(value, BaseMessage):
-                        if value.id is not None:
-                            self.seen.add(value.id)
-                    elif isinstance(value, Sequence) and not isinstance(value, str):
-                        for item in value:
-                            if isinstance(item, BaseMessage):
-                                if item.id is not None:
-                                    self.seen.add(item.id)
+            for value in _state_values(inputs):
+                if isinstance(value, BaseMessage):
+                    if value.id is not None:
+                        self.seen.add(value.id)
+                elif isinstance(value, Sequence) and not isinstance(value, str):
+                    for item in value:
+                        if isinstance(item, BaseMessage):
+                            if item.id is not None:
+                                self.seen.add(item.id)
 
     def on_chain_end(
         self,

libs/langgraph/langgraph/pregel/_runner.py

@@ -565,7 +565,7 @@ def _call(
         if fut := next(
             (
                 f
-                for f, t in futures().items()  # type: ignore[union-attr]
+                for f, t in list(futures().items())  # type: ignore[union-attr]
                 if t is not None and t == next_task.id
             ),
             None,
@@ -708,7 +708,7 @@ async def _acall_impl(
             if fut := next(
                 (
                     f
-                    for f, t in futures().items()  # type: ignore[union-attr]
+                    for f, t in list(futures().items())  # type: ignore[union-attr]
                     if t is not None and t == next_task.id
                 ),
                 None,

libs/langgraph/langgraph/runtime.py

@@ -28,6 +28,21 @@ class _RuntimeOverrides(TypedDict, Generic[ContextT], total=False):
 class Runtime(Generic[ContextT]):
     """Convenience class that bundles run-scoped context and other runtime utilities.
 
+    This class is injected into graph nodes and middleware. It provides access to
+    `context`, `store`, `stream_writer`, and `previous`.
+
+    !!! note "Accessing `config`"
+
+        `Runtime` does not include `config`. To access `RunnableConfig`, you can inject
+        it directly by adding a `config: RunnableConfig` parameter to your node function
+        (recommended), or use `get_config()` from `langgraph.config`.
+
+    !!! note
+        `ToolRuntime` (from `langgraph.prebuilt`) is a subclass that provides similar
+        functionality but is designed specifically for tools. It shares `context`, `store`,
+        and `stream_writer` with `Runtime`, and adds tool-specific attributes like `config`,
+        `state`, and `tool_call_id`.
+
     !!! version-added "Added in version v0.6.0"
 
     Example:

libs/langgraph/langgraph/types.py

@@ -61,18 +61,22 @@ __all__ = (
 
 Durability = Literal["sync", "async", "exit"]
 """Durability mode for the graph execution.
-- `"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."""
+
+- `'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.
+"""
 
 All = Literal["*"]
 """Special value to indicate that graph should interrupt on all nodes."""
 
 Checkpointer = None | bool | BaseCheckpointSaver
 """Type of the checkpointer to use for a subgraph.
-- True enables persistent checkpointing for this subgraph.
-- False disables checkpointing, even if the parent graph has a checkpointer.
-- None inherits checkpointer from the parent graph."""
+
+- `True` enables persistent checkpointing for this subgraph.
+- `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:

libs/langgraph/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph"
-version = "1.0.6"
+version = "1.0.8"
 description = "Building stateful, multi-actor applications with LLMs"
 authors = []
 requires-python = ">=3.10"
@@ -27,7 +27,7 @@ dependencies = [
     "langchain-core>=0.1",
     "langgraph-checkpoint>=2.1.0,<5.0.0",
     "langgraph-sdk>=0.3.0,<0.4.0",
-    "langgraph-prebuilt>=1.0.2,<1.1.0",
+    "langgraph-prebuilt>=1.0.7,<1.1.0",
     "xxhash>=3.5.0",
     "pydantic>=2.7.4",
 ]
@@ -38,7 +38,7 @@ 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"
+Twitter = "https://x.com/LangChain"
 Slack = "https://www.langchain.com/join-community"
 Reddit = "https://www.reddit.com/r/LangChain/"
 

libs/langgraph/tests/test_pregel.py

@@ -16,7 +16,7 @@ from typing import Annotated, Any, Literal, get_type_hints
 
 import pytest
 from langchain_core.language_models import GenericFakeChatModel
-from langchain_core.messages import AnyMessage
+from langchain_core.messages import AIMessage, AnyMessage, HumanMessage
 from langchain_core.runnables import (
     RunnableConfig,
     RunnableLambda,
@@ -1264,18 +1264,20 @@ def test_imp_task(
     }
 
     thread1 = {"configurable": {"thread_id": "1"}}
-    assert [*graph.stream([0, 1], thread1, durability=durability)] == [
+    result = [*graph.stream([0, 1], thread1, durability=durability)]
+    # mapper tasks run concurrently so output order is non-deterministic
+    assert sorted(result[:-1], key=lambda d: str(d)) == [
         {"mapper": "00"},
         {"mapper": "11"},
-        {
-            "__interrupt__": (
-                Interrupt(
-                    value="question",
-                    id=AnyStr(),
-                ),
-            )
-        },
     ]
+    assert result[-1] == {
+        "__interrupt__": (
+            Interrupt(
+                value="question",
+                id=AnyStr(),
+            ),
+        )
+    }
     assert mapper_calls == 2
 
     assert graph.invoke(Command(resume="answer"), thread1, durability=durability) == [
@@ -6978,6 +6980,93 @@ def test_stream_messages_dedupe_state(sync_checkpointer: BaseCheckpointSaver) ->
     assert chunks[0][1]["langgraph_node"] == "call_model"
 
 
+def test_stream_messages_dedupe_pydantic_subgraph_interrupt(
+    sync_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Pydantic BaseModel state should not cause duplicate messages when
+    streaming from subgraphs that use interrupts. Regression test for a bug
+    where ``on_chain_start`` only populated the ``seen`` set for dict inputs,
+    skipping Pydantic model inputs entirely."""
+
+    class PydanticState(BaseModel):
+        messages: Annotated[list[AnyMessage], add_messages] = Field(
+            default_factory=list
+        )
+
+    def subgraph_proposal(state) -> Command[Literal["subgraph_approval"]]:
+        return Command(
+            goto="subgraph_approval",
+            update={"messages": [AIMessage(content="Proposal", id="proposal_msg")]},
+        )
+
+    def subgraph_approval(state) -> Command[Literal["__end__"]]:
+        resume_value = interrupt({"message": "Waiting for approval"})
+        user_msg = resume_value.get("user_message", "")
+        msgs = [HumanMessage(content=user_msg)] if user_msg else []
+        return Command(goto="__end__", update={"messages": msgs})
+
+    subgraph = (
+        StateGraph(PydanticState)
+        .add_node("proposal", subgraph_proposal)
+        .add_node("subgraph_approval", subgraph_approval)
+        .add_edge(START, "proposal")
+        .compile(checkpointer=sync_checkpointer)
+    )
+
+    def finalize(state) -> Command[Literal["__end__"]]:
+        return Command(
+            goto="__end__",
+            update={"messages": [AIMessage(content="Finalized", id="finalize_msg")]},
+        )
+
+    graph = (
+        StateGraph(PydanticState)
+        .add_node("subgraph", subgraph)
+        .add_node("finalize", finalize)
+        .add_edge(START, "subgraph")
+        .add_edge("subgraph", "finalize")
+        .compile(checkpointer=sync_checkpointer)
+    )
+
+    thread1 = {"configurable": {"thread_id": "1"}}
+
+    # First stream: should hit interrupt after proposal
+    chunks_req0 = [
+        (ns, chunk)
+        for ns, chunk in graph.stream(
+            {"messages": [HumanMessage(content="Create a proposal")]},
+            thread1,
+            stream_mode="messages",
+            subgraphs=True,
+        )
+    ]
+
+    msg_ids_req0 = {chunk[0].id for _, chunk in chunks_req0}
+    assert "proposal_msg" in msg_ids_req0
+
+    # Verify interrupted
+    state = graph.get_state(thread1)
+    assert state.next
+
+    # Second stream: resume — should NOT duplicate messages from first stream
+    chunks_req1 = [
+        (ns, chunk)
+        for ns, chunk in graph.stream(
+            Command(resume={"user_message": "Yes"}),
+            thread1,
+            stream_mode="messages",
+            subgraphs=True,
+        )
+    ]
+
+    msg_ids_req1 = {chunk[0].id for _, chunk in chunks_req1}
+    assert "finalize_msg" in msg_ids_req1
+
+    # The key assertion: no message IDs from request 0 should appear in request 1
+    duplicates = msg_ids_req0 & msg_ids_req1
+    assert not duplicates, f"Duplicate message IDs across requests: {duplicates}"
+
+
 def test_interrupt_subgraph_reenter_checkpointer_true(
     sync_checkpointer: BaseCheckpointSaver,
 ) -> None:

libs/langgraph/tests/test_pregel_async.py

@@ -2262,18 +2262,20 @@ async def test_imp_task(
 
     tracer = FakeTracer()
     thread1 = {"configurable": {"thread_id": "1"}, "callbacks": [tracer]}
-    assert [c async for c in graph.astream([0, 1], thread1, durability=durability)] == [
+    result = [c async for c in graph.astream([0, 1], thread1, durability=durability)]
+    # mapper tasks run concurrently so output order is non-deterministic
+    assert sorted(result[:-1], key=lambda d: str(d)) == [
         {"mapper": "00"},
         {"mapper": "11"},
-        {
-            "__interrupt__": (
-                Interrupt(
-                    value="question",
-                    id=AnyStr(),
-                ),
-            )
-        },
     ]
+    assert result[-1] == {
+        "__interrupt__": (
+            Interrupt(
+                value="question",
+                id=AnyStr(),
+            ),
+        )
+    }
     assert mapper_calls == 2
     assert len(tracer.runs) == 1
     assert len(tracer.runs[0].child_runs) == 1

libs/prebuilt/langgraph/prebuilt/chat_agent_executor.py

@@ -308,7 +308,13 @@ def create_react_agent(
 ) -> CompiledStateGraph:
     """Creates an agent graph that calls tools in a loop until a stopping condition is met.
 
-    For more details on using `create_react_agent`, visit [Agents](https://langchain-ai.github.io/langgraph/agents/overview/) documentation.
+    !!! warning
+
+        This function is deprecated in favor of
+        [`create_agent`][langchain.agents.create_agent] from the `langchain`
+        package, which provides an equivalent agent factory with a flexible
+        middleware system. For migration guidance, see
+        [Migrating from LangGraph v0](https://docs.langchain.com/oss/python/migrate/langgraph-v1).
 
     Args:
         model: The language model for the agent. Supports static and dynamic

libs/prebuilt/langgraph/prebuilt/tool_node.py

@@ -121,6 +121,7 @@ class _ToolCallRequestOverrides(TypedDict, total=False):
     """Possible overrides for ToolCallRequest.override() method."""
 
     tool_call: ToolCall
+    tool: BaseTool
     state: Any
 
 
@@ -1530,16 +1531,23 @@ def tools_condition(
 class ToolRuntime(_DirectlyInjectedToolArg, Generic[ContextT, StateT]):
     """Runtime context automatically injected into tools.
 
-    When a tool function has a parameter named `tool_runtime` with type hint
+    !!! note
+
+        This is distinct from `Runtime` (from `langgraph.runtime`), which is injected
+        into graph nodes and middleware. `ToolRuntime` includes additional tool-specific
+        attributes like `config`, `state`, and `tool_call_id` that `Runtime` does not
+        have.
+
+    When a tool function has a parameter named `runtime` with type hint
     `ToolRuntime`, the tool execution system will automatically inject an instance
     containing:
 
     - `state`: The current graph state
     - `tool_call_id`: The ID of the current tool call
     - `config`: `RunnableConfig` for the current execution
-    - `context`: Runtime context (from langgraph `Runtime`)
-    - `store`: `BaseStore` instance for persistent storage (from langgraph `Runtime`)
-    - `stream_writer`: `StreamWriter` for streaming output (from langgraph `Runtime`)
+    - `context`: Runtime context (shared with `Runtime`)
+    - `store`: `BaseStore` instance for persistent storage (shared with `Runtime`)
+    - `stream_writer`: `StreamWriter` for streaming output (shared with `Runtime`)
 
     No `Annotated` wrapper is needed - just use `runtime: ToolRuntime`
     as a parameter.

libs/prebuilt/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-prebuilt"
-version = "1.0.6"
+version = "1.0.7"
 description = "Library with high-level APIs for creating and executing LangGraph agents and tools."
 authors = []
 requires-python = ">=3.10"
@@ -30,7 +30,7 @@ dependencies = [
 
 [project.urls]
 Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/prebuilt"
-Twitter = "https://x.com/LangChainAI"
+Twitter = "https://x.com/LangChain"
 Slack = "https://www.langchain.com/join-community"
 Reddit = "https://www.reddit.com/r/LangChain/"
 

libs/prebuilt/tests/test_tool_node_interceptor_unregistered.py

@@ -220,7 +220,10 @@ def test_unregistered_tool_error_when_interceptor_calls_execute() -> None:
     )
     # Should get validation error message
     assert result[0].status == "error"
-    assert "is not a valid tool" in result[0].content
+    assert (
+        result[0].content
+        == "Error: unregistered_tool is not a valid tool, try one of [registered_tool]."
+    )
     assert result[0].tool_call_id == "2"
 
 
@@ -576,3 +579,226 @@ def test_interceptor_verifies_tool_is_none_for_unregistered() -> None:
     assert len(captured_requests) == 1
     assert captured_requests[0].tool is not None
     assert captured_requests[0].tool.name == "registered_tool"
+
+
+def test_wrap_tool_call_override_unregistered_tool_with_custom_impl() -> None:
+    """Test that wrap_tool_call can provide custom implementation for unregistered tool."""
+    called = False
+
+    @dec_tool
+    def custom_tool_impl() -> str:
+        """Custom tool implementation."""
+        nonlocal called
+        called = True
+        return "custom result"
+
+    def hook(
+        request: ToolCallRequest,
+        execute: Callable[[ToolCallRequest], ToolMessage | Command],
+    ) -> ToolMessage | Command:
+        if request.tool_call["name"] == "custom_tool":
+            assert request.tool is None  # Unregistered tools have tool=None
+            return execute(request.override(tool=custom_tool_impl))
+        return execute(request)
+
+    node = ToolNode([registered_tool], wrap_tool_call=hook)
+
+    result = node.invoke(
+        [
+            AIMessage(
+                "",
+                tool_calls=[
+                    {"name": "custom_tool", "args": {}, "id": "1", "type": "tool_call"}
+                ],
+            )
+        ],
+        config=_create_config_with_runtime(),
+    )
+
+    assert called
+    assert result[0].content == "custom result"
+    assert result[0].tool_call_id == "1"
+
+
+async def test_awrap_tool_call_override_unregistered_tool_with_custom_impl() -> None:
+    """Test that awrap_tool_call can provide custom implementation for unregistered tool."""
+    called = False
+
+    @dec_tool
+    def custom_async_tool_impl() -> str:
+        """Custom async tool implementation."""
+        nonlocal called
+        called = True
+        return "async custom result"
+
+    async def hook(
+        request: ToolCallRequest,
+        execute: Callable[[ToolCallRequest], Awaitable[ToolMessage | Command]],
+    ) -> ToolMessage | Command:
+        if request.tool_call["name"] == "custom_async_tool":
+            assert request.tool is None  # Unregistered tools have tool=None
+            return await execute(request.override(tool=custom_async_tool_impl))
+        return await execute(request)
+
+    node = ToolNode([registered_tool], awrap_tool_call=hook)
+
+    result = await node.ainvoke(
+        [
+            AIMessage(
+                "",
+                tool_calls=[
+                    {
+                        "name": "custom_async_tool",
+                        "args": {},
+                        "id": "1",
+                        "type": "tool_call",
+                    }
+                ],
+            )
+        ],
+        config=_create_config_with_runtime(),
+    )
+
+    assert called
+    assert result[0].content == "async custom result"
+    assert result[0].tool_call_id == "1"
+
+
+def test_graceful_failure_when_hook_does_not_override_unregistered_tool_sync() -> None:
+    """Test graceful failure when hook doesn't override unregistered tool."""
+
+    def passthrough_hook(
+        request: ToolCallRequest,
+        execute: Callable[[ToolCallRequest], ToolMessage | Command],
+    ) -> ToolMessage | Command:
+        return execute(request)
+
+    node = ToolNode(
+        [registered_tool],
+        wrap_tool_call=passthrough_hook,
+        handle_tool_errors=True,
+    )
+
+    result = node.invoke(
+        [
+            AIMessage(
+                "",
+                tool_calls=[
+                    {"name": "nonexistent", "args": {}, "id": "1", "type": "tool_call"}
+                ],
+            )
+        ],
+        config=_create_config_with_runtime(),
+    )
+
+    assert result[0].status == "error"
+    assert result[0].tool_call_id == "1"
+    assert (
+        result[0].content
+        == "Error: nonexistent is not a valid tool, try one of [registered_tool]."
+    )
+
+
+def test_graceful_failure_even_when_handle_errors_disabled_sync() -> None:
+    """Test that unregistered tool validation returns error even with handle_tool_errors=False."""
+
+    def passthrough_hook(
+        request: ToolCallRequest,
+        execute: Callable[[ToolCallRequest], ToolMessage | Command],
+    ) -> ToolMessage | Command:
+        return execute(request)
+
+    node = ToolNode(
+        [registered_tool],
+        wrap_tool_call=passthrough_hook,
+        handle_tool_errors=False,
+    )
+
+    result = node.invoke(
+        [
+            AIMessage(
+                "",
+                tool_calls=[
+                    {"name": "missing", "args": {}, "id": "1", "type": "tool_call"}
+                ],
+            )
+        ],
+        config=_create_config_with_runtime(),
+    )
+
+    assert result[0].status == "error"
+    assert (
+        result[0].content
+        == "Error: missing is not a valid tool, try one of [registered_tool]."
+    )
+
+
+async def test_graceful_failure_when_hook_does_not_override_unregistered_tool_async() -> (
+    None
+):
+    """Test graceful failure when async hook doesn't override unregistered tool."""
+
+    async def passthrough_hook(
+        request: ToolCallRequest,
+        execute: Callable[[ToolCallRequest], Awaitable[ToolMessage | Command]],
+    ) -> ToolMessage | Command:
+        return await execute(request)
+
+    node = ToolNode(
+        [registered_tool],
+        awrap_tool_call=passthrough_hook,
+        handle_tool_errors=True,
+    )
+
+    result = await node.ainvoke(
+        [
+            AIMessage(
+                "",
+                tool_calls=[
+                    {"name": "unknown", "args": {}, "id": "1", "type": "tool_call"}
+                ],
+            )
+        ],
+        config=_create_config_with_runtime(),
+    )
+
+    assert result[0].status == "error"
+    assert result[0].tool_call_id == "1"
+    assert (
+        result[0].content
+        == "Error: unknown is not a valid tool, try one of [registered_tool]."
+    )
+
+
+async def test_graceful_failure_even_when_handle_errors_disabled_async() -> None:
+    """Test that async unregistered tool validation returns error even with handle_tool_errors=False."""
+
+    async def passthrough_hook(
+        request: ToolCallRequest,
+        execute: Callable[[ToolCallRequest], Awaitable[ToolMessage | Command]],
+    ) -> ToolMessage | Command:
+        return await execute(request)
+
+    node = ToolNode(
+        [registered_tool],
+        awrap_tool_call=passthrough_hook,
+        handle_tool_errors=False,
+    )
+
+    result = await node.ainvoke(
+        [
+            AIMessage(
+                "",
+                tool_calls=[
+                    {"name": "missing", "args": {}, "id": "1", "type": "tool_call"}
+                ],
+            )
+        ],
+        config=_create_config_with_runtime(),
+    )
+
+    assert result[0].status == "error"
+    assert (
+        result[0].content
+        == "Error: missing is not a valid tool, try one of [registered_tool]."
+    )

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__ = "0.3.2"
+__version__ = "0.3.5"
 
 __all__ = ["Auth", "Encryption", "EncryptionContext", "get_client", "get_sync_client"]

libs/sdk-py/langgraph_sdk/client.py

@@ -2984,6 +2984,7 @@ class CronClient:
         webhook: str | None = None,
         multitask_strategy: str | None = None,
         end_time: datetime | None = None,
+        enabled: bool | None = None,
         headers: Mapping[str, str] | None = None,
         params: QueryParamTypes | None = None,
     ) -> Run:
@@ -2994,6 +2995,7 @@ class CronClient:
             assistant_id: The assistant ID or graph name to use for the cron job.
                 If using graph name, will default to first assistant created from that graph.
             schedule: The cron schedule to execute this job on.
+                Schedules are interpreted in UTC.
             input: The input to the graph.
             metadata: Metadata to assign to the cron job runs.
             config: The configuration for the assistant.
@@ -3008,6 +3010,7 @@ class CronClient:
             multitask_strategy: Multitask strategy to use.
                 Must be one of 'reject', 'interrupt', 'rollback', or 'enqueue'.
             end_time: The time to stop running the cron job. If not provided, the cron job will run indefinitely.
+            enabled: Whether the cron job is enabled or not.
             headers: Optional custom headers to include with the request.
             params: Optional query parameters to include with the request.
 
@@ -3028,7 +3031,8 @@ class CronClient:
                 interrupt_before=["node_to_stop_before_1","node_to_stop_before_2"],
                 interrupt_after=["node_to_stop_after_1","node_to_stop_after_2"],
                 webhook="https://my.fake.webhook.com",
-                multitask_strategy="interrupt"
+                multitask_strategy="interrupt",
+                enabled=True,
             )
             ```
         """
@@ -3044,6 +3048,7 @@ class CronClient:
             "interrupt_after": interrupt_after,
             "webhook": webhook,
             "end_time": end_time.isoformat() if end_time else None,
+            "enabled": enabled,
         }
         if multitask_strategy:
             payload["multitask_strategy"] = multitask_strategy
@@ -3071,6 +3076,7 @@ class CronClient:
         on_run_completed: OnCompletionBehavior | None = None,
         multitask_strategy: str | None = None,
         end_time: datetime | None = None,
+        enabled: bool | None = None,
         headers: Mapping[str, str] | None = None,
         params: QueryParamTypes | None = None,
     ) -> Run:
@@ -3080,6 +3086,7 @@ class CronClient:
             assistant_id: The assistant ID or graph name to use for the cron job.
                 If using graph name, will default to first assistant created from that graph.
             schedule: The cron schedule to execute this job on.
+                Schedules are interpreted in UTC.
             input: The input to the graph.
             metadata: Metadata to assign to the cron job runs.
             config: The configuration for the assistant.
@@ -3096,6 +3103,7 @@ class CronClient:
             multitask_strategy: Multitask strategy to use.
                 Must be one of 'reject', 'interrupt', 'rollback', or 'enqueue'.
             end_time: The time to stop running the cron job. If not provided, the cron job will run indefinitely.
+            enabled: Whether the cron job is enabled or not.
             headers: Optional custom headers to include with the request.
             params: Optional query parameters to include with the request.
 
@@ -3115,7 +3123,8 @@ class CronClient:
                 interrupt_before=["node_to_stop_before_1","node_to_stop_before_2"],
                 interrupt_after=["node_to_stop_after_1","node_to_stop_after_2"],
                 webhook="https://my.fake.webhook.com",
-                multitask_strategy="interrupt"
+                multitask_strategy="interrupt",
+                enabled=True,
             )
             ```
 
@@ -3133,6 +3142,7 @@ class CronClient:
             "webhook": webhook,
             "on_run_completed": on_run_completed,
             "end_time": end_time.isoformat() if end_time else None,
+            "enabled": enabled,
         }
         if multitask_strategy:
             payload["multitask_strategy"] = multitask_strategy
@@ -3170,11 +3180,88 @@ class CronClient:
         """
         await self.http.delete(f"/runs/crons/{cron_id}", headers=headers, params=params)
 
+    async def update(
+        self,
+        cron_id: str,
+        *,
+        schedule: str | None = None,
+        end_time: datetime | None = None,
+        input: Input | None = None,
+        metadata: Mapping[str, Any] | None = None,
+        config: Config | None = None,
+        context: Context | None = None,
+        webhook: str | None = None,
+        interrupt_before: All | list[str] | None = None,
+        interrupt_after: All | list[str] | None = None,
+        on_run_completed: OnCompletionBehavior | None = None,
+        enabled: bool | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Cron:
+        """Update a cron job by ID.
+
+        Args:
+            cron_id: The cron ID to update.
+            schedule: The cron schedule to execute this job on.
+                Schedules are interpreted in UTC.
+            end_time: The end date to stop running the cron.
+            input: The input to the graph.
+            metadata: Metadata to assign to the cron job runs.
+            config: The configuration for the assistant.
+            context: Static context added to the assistant.
+            webhook: Webhook to call after LangGraph API call is done.
+            interrupt_before: Nodes to interrupt immediately before they get executed.
+            interrupt_after: Nodes to interrupt immediately after they get executed.
+            on_run_completed: What to do with the thread after the run completes.
+                Must be one of 'delete' or 'keep'. 'delete' removes the thread
+                after execution. 'keep' creates a new thread for each execution but does not
+                clean them up.
+            enabled: Enable or disable the cron job.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            The updated cron job.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            updated_cron = await client.crons.update(
+                cron_id="1ef3cefa-4c09-6926-96d0-3dc97fd5e39b",
+                schedule="0 10 * * *",
+                enabled=False,
+            )
+            ```
+
+        """
+        payload = {
+            "schedule": schedule,
+            "end_time": end_time.isoformat() if end_time else None,
+            "input": input,
+            "metadata": metadata,
+            "config": config,
+            "context": context,
+            "webhook": webhook,
+            "interrupt_before": interrupt_before,
+            "interrupt_after": interrupt_after,
+            "on_run_completed": on_run_completed,
+            "enabled": enabled,
+        }
+        payload = {k: v for k, v in payload.items() if v is not None}
+        return await self.http.patch(
+            f"/runs/crons/{cron_id}",
+            json=payload,
+            headers=headers,
+            params=params,
+        )
+
     async def search(
         self,
         *,
         assistant_id: str | None = None,
         thread_id: str | None = None,
+        enabled: bool | None = None,
         limit: int = 10,
         offset: int = 0,
         sort_by: CronSortBy | None = None,
@@ -3188,6 +3275,7 @@ class CronClient:
         Args:
             assistant_id: The assistant ID or graph name to search for.
             thread_id: the thread ID to search for.
+            enabled: The enabled status to search for.
             limit: The maximum number of results to return.
             offset: The number of results to skip.
             headers: Optional custom headers to include with the request.
@@ -3203,6 +3291,7 @@ class CronClient:
             cron_jobs = await client.crons.search(
                 assistant_id="my_assistant_id",
                 thread_id="my_thread_id",
+                enabled=True,
                 limit=5,
                 offset=5,
             )
@@ -3237,6 +3326,7 @@ class CronClient:
         payload = {
             "assistant_id": assistant_id,
             "thread_id": thread_id,
+            "enabled": enabled,
             "limit": limit,
             "offset": offset,
         }
@@ -6292,6 +6382,7 @@ class SyncCronClient:
         webhook: str | None = None,
         multitask_strategy: str | None = None,
         end_time: datetime | None = None,
+        enabled: bool | None = None,
         headers: Mapping[str, str] | None = None,
         params: QueryParamTypes | None = None,
     ) -> Run:
@@ -6302,6 +6393,7 @@ class SyncCronClient:
             assistant_id: The assistant ID or graph name to use for the cron job.
                 If using graph name, will default to first assistant created from that graph.
             schedule: The cron schedule to execute this job on.
+                Schedules are interpreted in UTC.
             input: The input to the graph.
             metadata: Metadata to assign to the cron job runs.
             config: The configuration for the assistant.
@@ -6314,6 +6406,7 @@ class SyncCronClient:
             multitask_strategy: Multitask strategy to use.
                 Must be one of 'reject', 'interrupt', 'rollback', or 'enqueue'.
             end_time: The time to stop running the cron job. If not provided, the cron job will run indefinitely.
+            enabled: Whether the cron job is enabled. By default, it is considered enabled.
             headers: Optional custom headers to include with the request.
 
         Returns:
@@ -6333,7 +6426,8 @@ class SyncCronClient:
                 interrupt_before=["node_to_stop_before_1","node_to_stop_before_2"],
                 interrupt_after=["node_to_stop_after_1","node_to_stop_after_2"],
                 webhook="https://my.fake.webhook.com",
-                multitask_strategy="interrupt"
+                multitask_strategy="interrupt",
+                enabled=True
             )
             ```
         """
@@ -6350,6 +6444,7 @@ class SyncCronClient:
             "webhook": webhook,
             "multitask_strategy": multitask_strategy,
             "end_time": end_time.isoformat() if end_time else None,
+            "enabled": enabled,
         }
         payload = {k: v for k, v in payload.items() if v is not None}
         return self.http.post(
@@ -6375,6 +6470,7 @@ class SyncCronClient:
         on_run_completed: OnCompletionBehavior | None = None,
         multitask_strategy: str | None = None,
         end_time: datetime | None = None,
+        enabled: bool | None = None,
         headers: Mapping[str, str] | None = None,
         params: QueryParamTypes | None = None,
     ) -> Run:
@@ -6384,6 +6480,7 @@ class SyncCronClient:
             assistant_id: The assistant ID or graph name to use for the cron job.
                 If using graph name, will default to first assistant created from that graph.
             schedule: The cron schedule to execute this job on.
+                Schedules are interpreted in UTC.
             input: The input to the graph.
             metadata: Metadata to assign to the cron job runs.
             config: The configuration for the assistant.
@@ -6400,6 +6497,7 @@ class SyncCronClient:
             multitask_strategy: Multitask strategy to use.
                 Must be one of 'reject', 'interrupt', 'rollback', or 'enqueue'.
             end_time: The time to stop running the cron job. If not provided, the cron job will run indefinitely.
+            enabled: Whether the cron job is enabled. By default, it is considered enabled.
             headers: Optional custom headers to include with the request.
 
         Returns:
@@ -6419,7 +6517,8 @@ class SyncCronClient:
                 interrupt_before=["node_to_stop_before_1","node_to_stop_before_2"],
                 interrupt_after=["node_to_stop_after_1","node_to_stop_after_2"],
                 webhook="https://my.fake.webhook.com",
-                multitask_strategy="interrupt"
+                multitask_strategy="interrupt",
+                enabled=True
             )
             ```
 
@@ -6438,6 +6537,7 @@ class SyncCronClient:
             "on_run_completed": on_run_completed,
             "multitask_strategy": multitask_strategy,
             "end_time": end_time.isoformat() if end_time else None,
+            "enabled": enabled,
         }
         payload = {k: v for k, v in payload.items() if v is not None}
         return self.http.post(
@@ -6473,11 +6573,88 @@ class SyncCronClient:
         """
         self.http.delete(f"/runs/crons/{cron_id}", headers=headers, params=params)
 
+    def update(
+        self,
+        cron_id: str,
+        *,
+        schedule: str | None = None,
+        end_time: datetime | None = None,
+        input: Input | None = None,
+        metadata: Mapping[str, Any] | None = None,
+        config: Config | None = None,
+        context: Context | None = None,
+        webhook: str | None = None,
+        interrupt_before: All | list[str] | None = None,
+        interrupt_after: All | list[str] | None = None,
+        on_run_completed: OnCompletionBehavior | None = None,
+        enabled: bool | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Cron:
+        """Update a cron job by ID.
+
+        Args:
+            cron_id: The cron ID to update.
+            schedule: The cron schedule to execute this job on.
+                Schedules are interpreted in UTC.
+            end_time: The end date to stop running the cron.
+            input: The input to the graph.
+            metadata: Metadata to assign to the cron job runs.
+            config: The configuration for the assistant.
+            context: Static context added to the assistant.
+            webhook: Webhook to call after LangGraph API call is done.
+            interrupt_before: Nodes to interrupt immediately before they get executed.
+            interrupt_after: Nodes to interrupt immediately after they get executed.
+            on_run_completed: What to do with the thread after the run completes.
+                Must be one of 'delete' or 'keep'. 'delete' removes the thread
+                after execution. 'keep' creates a new thread for each execution but does not
+                clean them up.
+            enabled: Enable or disable the cron job.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            The updated cron job.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:8123")
+            updated_cron = client.crons.update(
+                cron_id="1ef3cefa-4c09-6926-96d0-3dc97fd5e39b",
+                schedule="0 10 * * *",
+                enabled=False,
+            )
+            ```
+
+        """
+        payload = {
+            "schedule": schedule,
+            "end_time": end_time.isoformat() if end_time else None,
+            "input": input,
+            "metadata": metadata,
+            "config": config,
+            "context": context,
+            "webhook": webhook,
+            "interrupt_before": interrupt_before,
+            "interrupt_after": interrupt_after,
+            "on_run_completed": on_run_completed,
+            "enabled": enabled,
+        }
+        payload = {k: v for k, v in payload.items() if v is not None}
+        return self.http.patch(
+            f"/runs/crons/{cron_id}",
+            json=payload,
+            headers=headers,
+            params=params,
+        )
+
     def search(
         self,
         *,
         assistant_id: str | None = None,
         thread_id: str | None = None,
+        enabled: bool | None = None,
         limit: int = 10,
         offset: int = 0,
         sort_by: CronSortBy | None = None,
@@ -6491,6 +6668,7 @@ class SyncCronClient:
         Args:
             assistant_id: The assistant ID or graph name to search for.
             thread_id: the thread ID to search for.
+            enabled: Whether the cron job is enabled.
             limit: The maximum number of results to return.
             offset: The number of results to skip.
             headers: Optional custom headers to include with the request.
@@ -6505,6 +6683,7 @@ class SyncCronClient:
             cron_jobs = client.crons.search(
                 assistant_id="my_assistant_id",
                 thread_id="my_thread_id",
+                enabled=True,
                 limit=5,
                 offset=5,
             )
@@ -6538,6 +6717,7 @@ class SyncCronClient:
         payload = {
             "assistant_id": assistant_id,
             "thread_id": thread_id,
+            "enabled": enabled,
             "limit": limit,
             "offset": offset,
         }

libs/sdk-py/langgraph_sdk/errors.py

@@ -38,7 +38,7 @@ class APIError(httpx.HTTPStatusError, LangGraphError):
             response = None
 
         httpx.HTTPStatusError.__init__(self, message, request=req, response=response)  # type: ignore[arg-type]
-        LangGraphError.__init__(self)
+        LangGraphError.__init__(self, message)
 
         self.request = req
         self.message = message

libs/sdk-py/langgraph_sdk/runtime.py

@@ -0,0 +1,238 @@
+from __future__ import annotations
+
+import sys
+from dataclasses import dataclass, field
+from typing import TYPE_CHECKING, Generic, Literal, TypeVar
+
+if sys.version_info >= (3, 13):
+    ContextT = TypeVar("ContextT", default=None)
+else:
+    ContextT = TypeVar("ContextT")
+
+if sys.version_info >= (3, 12):
+    from typing import TypeAliasType
+else:
+    from typing_extensions import TypeAliasType
+
+from langgraph_sdk.auth.types import BaseUser
+
+if TYPE_CHECKING:
+    from langgraph.store.base import BaseStore
+
+__all__ = [
+    "AccessContext",
+    "ServerRuntime",
+]
+
+
+AccessContext = Literal[
+    "threads.create_run",
+    "threads.update",
+    "threads.read",
+    "assistants.read",
+]
+
+
+@dataclass(kw_only=True, slots=True, frozen=True)
+class _ServerRuntimeBase(Generic[ContextT]):
+    """Base for server runtime variants.
+
+    !!! warning "Beta"
+        This API is in beta and may change in future releases.
+    """
+
+    access_context: AccessContext
+    """Why the graph factory is being called.
+
+    The server accesses graphs in several contexts beyond just executing runs.
+    For example, it calls the graph factory to retrieve schemas, render the
+    graph structure, or read state history. This field tells you which
+    operation triggered the current call.
+
+    In all contexts, the returned graph must have the same topology (nodes,
+    edges, state schema) as the graph used for execution. Use
+    `.execution_runtime` to conditionally set up expensive *resources*
+    (MCP servers, DB connections) without changing the graph structure.
+
+    Write contexts (graph is used to write state):
+
+    - `threads.create_run` (`graph.astream`) — full graph execution
+      (nodes + edges). `context` is available (use `.execution_runtime`
+      to narrow).
+    - `threads.update` (`graph.aupdate_state`) — does NOT execute node
+      functions or evaluate edges. Only runs the node's channel writers
+      to apply the provided values to state channels as if the specified
+      node had returned them. Reducers are applied and channel triggers
+      are set, so the next `invoke`/`stream` call will evaluate edges
+      from that node to determine the next step. Does not need access to
+      external resources, but a different graph topology will apply
+      writes to the wrong channels.
+
+    Read state contexts (graph used to format the returned
+    `StateSnapshot`). A different topology may cause `get_state` to
+    report incorrect pending tasks. Note that `useStream` uses the state
+    history endpoint to render interrupts and support branching:
+
+    - `threads.read` (`graph.aget_state`, `graph.aget_state_history`) —
+      the graph structure informs which tasks to include in the prepared
+      view of the latest checkpoint and how to process subgraphs.
+
+    Introspection contexts (graph structure only, no execution).
+    A different topology may cause schemas and visualizations to not
+    match actual execution:
+
+    - `assistants.read` (`graph.aget_graph`, `graph.aget_subgraphs`,
+      `graph.aget_schemas`) — return the graph definition, subgraph
+      definitions, and input/output/config schemas. Used for
+      visualization in the studio UI and to populate schemas for MCP,
+      A2A, and other protocol integrations.
+    """
+
+    user: BaseUser | None = field(default=None)
+    """The authenticated user, or `None` if no custom auth is configured."""
+
+    store: BaseStore
+    """Store for the graph run, enabling persistence and memory."""
+
+    @property
+    def execution_runtime(self) -> _ExecutionRuntime[ContextT] | None:
+        """Narrow to the execution runtime, or `None` if not in an execution context.
+
+        When the server calls the graph factory for `threads.create_run`, the returned
+        object provides access to `context` (typed by the graph's
+        `context_schema`). For all other access contexts (introspection, state
+        reads, state updates), this returns `None`.
+
+        Use this to conditionally set up expensive resources (MCP tool servers,
+        database connections, etc.) that are only needed during execution:
+
+        ```python
+        import contextlib
+        from langgraph_sdk.runtime import ServerRuntime
+
+        @contextlib.asynccontextmanager
+        async def my_factory(runtime: ServerRuntime[MyCtx]):
+            if ert := runtime.execution_runtime:
+                # Only connect to MCP servers when actually executing a run.
+                # Introspection calls (get_schema, get_graph, ...) skip this.
+                mcp_tools = await connect_mcp(ert.context.mcp_endpoint)
+                yield create_agent(model, tools=mcp_tools)
+                await disconnect_mcp()
+            else:
+                yield create_agent(model, tools=[])
+        ```
+        """
+        if isinstance(self, _ExecutionRuntime):
+            return self
+        return None
+
+    def ensure_user(self) -> BaseUser:
+        """Return the authenticated user, or raise if not available.
+
+        When custom auth is configured, `user` is set for all access contexts
+        (the factory is only called from HTTP handlers where the auth
+        middleware has already run). This method raises only when no custom
+        auth is configured.
+
+        Raises:
+            PermissionError: If no user is authenticated.
+        """
+        if self.user is None:
+            raise PermissionError(
+                f"No authenticated user available in access_context='{self.access_context}'. "
+                "Ensure custom auth is configured for the server."
+            )
+        return self.user
+
+
+@dataclass(kw_only=True, slots=True, frozen=True)
+class _ExecutionRuntime(_ServerRuntimeBase[ContextT], Generic[ContextT]):
+    """Runtime for `threads.create_run` — the graph will be fully executed.
+
+    Access this via `.execution_runtime` on `ServerRuntime`. Do not
+    construct directly.
+
+    !!! warning "Beta"
+        This API is in beta and may change in future releases.
+    """
+
+    context: ContextT = field(default=None)  # type: ignore[assignment]
+    """The graph run context, typed by the graph's `context_schema`.
+
+    Only available during `threads.create_run`.
+    """
+
+
+@dataclass(kw_only=True, slots=True, frozen=True)
+class _ReadRuntime(_ServerRuntimeBase[ContextT], Generic[ContextT]):
+    """Runtime for non-execution access contexts.
+
+    Used for introspection (`assistants.read`), state operations
+    (`threads.read`), and state updates (`threads.update`).
+    No `context` is available.
+
+    !!! warning "Beta"
+        This API is in beta and may change in future releases.
+    """
+
+
+ServerRuntime = TypeAliasType(
+    "ServerRuntime",
+    _ExecutionRuntime[ContextT] | _ReadRuntime[ContextT],
+    type_params=(ContextT,),
+)
+"""Runtime context passed to graph builder factories within the Agent Server.
+
+Requires version 0.7.30 or later of the agent server.
+
+The server calls your graph factory in multiple contexts: executing runs,
+reading state, fetching schemas, and more. `ServerRuntime` provides
+the authenticated user, store, and access context for every call. Use
+`.execution_runtime` to narrow to the execution variant and access
+`context`.
+
+Example — conditionally initialize MCP tools only during execution:
+
+```python
+import contextlib
+from dataclasses import dataclass
+
+from langchain.agents import create_agent
+from langgraph_sdk.runtime import ServerRuntime
+from my_agent import connect_mcp, disconnect_mcp
+
+@dataclass
+class MyCtx:
+    mcp_endpoint: str
+
+_readonly_agent = create_agent("anthropic:claude-3-5-haiku", tools=[])
+
+@contextlib.asynccontextmanager
+async def my_factory(runtime: ServerRuntime[MyCtx]):
+    if ert := runtime.execution_runtime:
+        # Only connect to MCP servers for actual runs.
+        # Schema / graph introspection calls skip this.
+        user_id = runtime.ensure_user().identity
+        mcp_tools = await connect_mcp(ert.context.mcp_endpoint, user_id)
+        yield create_agent("anthropic:claude-3-5-haiku", tools=mcp_tools)
+        await disconnect_mcp()
+    else:
+        yield _readonly_agent
+```
+
+Example — simple factory that ignores context:
+
+```python
+from langgraph_sdk.runtime import ServerRuntime
+
+def build_graph(user: BaseUser) -> CompiledGraph:
+    ...
+
+async def my_factory(runtime: ServerRuntime) -> CompiledGraph:
+    # No generic needed if you don't use context.
+    return build_graph(runtime.ensure_user())
+```
+
+!!! warning "Beta"
+    This API is in beta and may change in future releases.
+"""

libs/sdk-py/langgraph_sdk/schema.py

@@ -372,6 +372,35 @@ class Cron(TypedDict):
     """The next run date of the cron."""
     metadata: dict
     """The metadata of the cron."""
+    enabled: bool
+    """Whether the cron is enabled."""
+
+
+class CronUpdate(TypedDict, total=False):
+    """Payload for updating a cron job. All fields are optional."""
+
+    schedule: str
+    """The cron schedule to execute this job on."""
+    end_time: datetime
+    """The end date to stop running the cron."""
+    input: Input
+    """The input to the graph."""
+    metadata: dict[str, Any]
+    """Metadata to assign to the cron job runs."""
+    config: Config
+    """The configuration for the assistant."""
+    context: Context
+    """Static context added to the assistant."""
+    webhook: str
+    """Webhook to call after LangGraph API call is done."""
+    interrupt_before: All | list[str]
+    """Nodes to interrupt immediately before they get executed."""
+    interrupt_after: All | list[str]
+    """Nodes to interrupt immediately after they get executed."""
+    on_run_completed: OnCompletionBehavior
+    """What to do with the thread after the run completes."""
+    enabled: bool
+    """Enable or disable the cron job."""
 
 
 # Select field aliases for client-side typing of `select` parameters.
@@ -428,6 +457,7 @@ CronSelectField = Literal[
     "metadata",
     "now",
     "on_run_completed",
+    "enabled",
 ]
 
 PrimitiveData = str | int | float | bool | None

libs/sdk-py/pyproject.toml

@@ -18,7 +18,7 @@ path = "langgraph_sdk/__init__.py"
 
 [project.urls]
 Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/sdk-py"
-Twitter = "https://x.com/LangChainAI"
+Twitter = "https://x.com/LangChain"
 Slack = "https://www.langchain.com/join-community"
 Reddit = "https://www.reddit.com/r/LangChain/"
 
@@ -30,7 +30,7 @@ test = [
     "pytest-watch",
 ]
 lint = [
-    "ruff==0.14.7",
+    "ruff==0.14.11",
     "codespell",
     "mypy==1.19.0",
     "ty==0.0.1a27",
@@ -39,6 +39,7 @@ lint = [
 dev = [
   { include-group = "test" },
   { include-group = "lint" },
+  "langgraph",
   "pydantic>=2.12.4",
 ]
 
@@ -52,6 +53,9 @@ asyncio_mode = "auto"
 [tool.uv]
 default-groups = ['dev']
 
+[tool.uv.sources]
+langgraph = { path = "../langgraph", editable = true }
+
 [tool.ruff]
 exclude = ["venv", ".venv", "build", "dist"]
 [tool.ruff.lint]

libs/sdk-py/tests/test_crons_client.py

@@ -276,3 +276,212 @@ def test_sync_create_with_end_time():
         )
 
     assert result == cron
+
+
+@pytest.mark.parametrize(
+    "enabled_value",
+    [True, False],
+    ids=["enabled", "disabled"],
+)
+def test_sync_create_with_enabled_parameter(enabled_value):
+    """Test that SyncCronClient.create includes enabled parameter in the payload."""
+    cron = _cron_payload()
+
+    def handler(request: httpx.Request) -> httpx.Response:
+        assert request.method == "POST"
+        assert request.url.path == "/runs/crons"
+
+        body = json.loads(request.content)
+        assert body["schedule"] == "0 12 * * *"
+        assert body["assistant_id"] == "asst_456"
+        assert body["enabled"] == enabled_value
+
+        return httpx.Response(200, json=cron)
+
+    transport = httpx.MockTransport(handler)
+    with httpx.Client(transport=transport, base_url="https://example.com") as client:
+        http_client = SyncHttpClient(client)
+        cron_client = SyncCronClient(http_client)
+        result = cron_client.create(
+            assistant_id="asst_456",
+            schedule="0 12 * * *",
+            enabled=enabled_value,
+        )
+
+    assert result == cron
+
+
+def _cron_response() -> dict[str, object]:
+    """Return a mock Cron object response."""
+    return {
+        "cron_id": "cron_123",
+        "assistant_id": "asst_123",
+        "thread_id": "thread_123",
+        "on_run_completed": None,
+        "end_time": "2025-12-31T23:59:59+00:00",
+        "schedule": "0 10 * * *",
+        "created_at": "2024-01-01T00:00:00Z",
+        "updated_at": "2024-01-02T00:00:00Z",
+        "payload": {},
+        "user_id": None,
+        "next_run_date": "2024-01-03T10:00:00Z",
+        "metadata": {},
+        "enabled": True,
+    }
+
+
+@pytest.mark.asyncio
+async def test_async_update():
+    """Test that CronClient.update works with schedule and enabled parameters."""
+    cron = _cron_response()
+
+    async def handler(request: httpx.Request) -> httpx.Response:
+        assert request.method == "PATCH"
+        assert request.url.path == "/runs/crons/cron_123"
+
+        # Parse the request body
+        body = json.loads(request.content)
+        assert body["schedule"] == "0 10 * * *"
+        assert body["enabled"] is False
+        assert "end_time" not in body  # Should be filtered out by the None check
+
+        return httpx.Response(200, json=cron)
+
+    transport = httpx.MockTransport(handler)
+    async with httpx.AsyncClient(
+        transport=transport, base_url="https://example.com"
+    ) as client:
+        http_client = HttpClient(client)
+        cron_client = CronClient(http_client)
+        result = await cron_client.update(
+            cron_id="cron_123",
+            schedule="0 10 * * *",
+            enabled=False,
+        )
+
+    assert result == cron
+
+
+@pytest.mark.asyncio
+async def test_async_update_with_end_time():
+    """Test that CronClient.update includes end_time in the payload."""
+    cron = _cron_response()
+    end_time = datetime(2025, 12, 31, 23, 59, 59, tzinfo=timezone.utc)
+
+    async def handler(request: httpx.Request) -> httpx.Response:
+        assert request.method == "PATCH"
+        assert request.url.path == "/runs/crons/cron_123"
+
+        # Parse the request body
+        body = json.loads(request.content)
+        assert body["schedule"] == "0 10 * * *"
+        assert body["end_time"] == "2025-12-31T23:59:59+00:00"
+        assert body["enabled"] is True
+
+        return httpx.Response(200, json=cron)
+
+    transport = httpx.MockTransport(handler)
+    async with httpx.AsyncClient(
+        transport=transport, base_url="https://example.com"
+    ) as client:
+        http_client = HttpClient(client)
+        cron_client = CronClient(http_client)
+        result = await cron_client.update(
+            cron_id="cron_123",
+            schedule="0 10 * * *",
+            end_time=end_time,
+            enabled=True,
+        )
+
+    assert result == cron
+
+
+def test_sync_update():
+    """Test that SyncCronClient.update works with schedule and enabled parameters."""
+    cron = _cron_response()
+
+    def handler(request: httpx.Request) -> httpx.Response:
+        assert request.method == "PATCH"
+        assert request.url.path == "/runs/crons/cron_123"
+
+        # Parse the request body
+        body = json.loads(request.content)
+        assert body["schedule"] == "0 10 * * *"
+        assert body["enabled"] is False
+        assert "end_time" not in body  # Should be filtered out by the None check
+
+        return httpx.Response(200, json=cron)
+
+    transport = httpx.MockTransport(handler)
+    with httpx.Client(transport=transport, base_url="https://example.com") as client:
+        http_client = SyncHttpClient(client)
+        cron_client = SyncCronClient(http_client)
+        result = cron_client.update(
+            cron_id="cron_123",
+            schedule="0 10 * * *",
+            enabled=False,
+        )
+
+    assert result == cron
+
+
+def test_sync_update_with_end_time():
+    """Test that SyncCronClient.update includes end_time in the payload."""
+    cron = _cron_response()
+    end_time = datetime(2025, 12, 31, 23, 59, 59, tzinfo=timezone.utc)
+
+    def handler(request: httpx.Request) -> httpx.Response:
+        assert request.method == "PATCH"
+        assert request.url.path == "/runs/crons/cron_123"
+
+        # Parse the request body
+        body = json.loads(request.content)
+        assert body["schedule"] == "0 10 * * *"
+        assert body["end_time"] == "2025-12-31T23:59:59+00:00"
+        assert body["enabled"] is True
+
+        return httpx.Response(200, json=cron)
+
+    transport = httpx.MockTransport(handler)
+    with httpx.Client(transport=transport, base_url="https://example.com") as client:
+        http_client = SyncHttpClient(client)
+        cron_client = SyncCronClient(http_client)
+        result = cron_client.update(
+            cron_id="cron_123",
+            schedule="0 10 * * *",
+            end_time=end_time,
+            enabled=True,
+        )
+
+    assert result == cron
+
+
+@pytest.mark.parametrize(
+    "enabled_value",
+    [True, False],
+    ids=["enabled", "disabled"],
+)
+def test_sync_update_with_enabled_parameter(enabled_value):
+    """Test that SyncCronClient.update includes enabled parameter in the payload."""
+    cron = _cron_response()
+
+    def handler(request: httpx.Request) -> httpx.Response:
+        assert request.method == "PATCH"
+        assert request.url.path == "/runs/crons/cron_456"
+
+        body = json.loads(request.content)
+        assert body["enabled"] == enabled_value
+        assert "schedule" not in body  # Only enabled is set
+
+        return httpx.Response(200, json=cron)
+
+    transport = httpx.MockTransport(handler)
+    with httpx.Client(transport=transport, base_url="https://example.com") as client:
+        http_client = SyncHttpClient(client)
+        cron_client = SyncCronClient(http_client)
+        result = cron_client.update(
+            cron_id="cron_456",
+            enabled=enabled_value,
+        )
+
+    assert result == cron

libs/sdk-py/tests/test_errors.py

@@ -106,3 +106,39 @@ def test_field_extraction_from_json_body() -> None:
     assert err.code == "invalid_param"
     assert err.param == "limit"
     assert err.type == "invalid_request_error"
+
+
+def test_error_message_in_str_and_args() -> None:
+    """Test that error message is accessible via str() and args."""
+    r = make_response(422, json_body={"message": "Validation failed"})
+    with pytest.raises(UnprocessableEntityError) as ei:
+        _raise_for_status_typed(r)
+    err = cast("UnprocessableEntityError", ei.value)
+    assert str(err) == "Validation failed"
+    assert err.args == ("Validation failed",)
+    assert err.message == "Validation failed"
+
+
+@pytest.mark.parametrize(
+    "status,exc_type",
+    [
+        (400, BadRequestError),
+        (401, AuthenticationError),
+        (403, PermissionDeniedError),
+        (404, NotFoundError),
+        (409, ConflictError),
+        (422, UnprocessableEntityError),
+        (429, RateLimitError),
+        (500, InternalServerError),
+    ],
+)
+def test_all_error_types_display_message(
+    status: int, exc_type: type[APIStatusError]
+) -> None:
+    """Test that all error subclasses properly display their message."""
+    r = make_response(status, json_body={"message": "test error message"})
+    with pytest.raises(exc_type) as ei:
+        _raise_for_status_typed(r)
+    err = ei.value
+    assert str(err) == "test error message"
+    assert "test error message" in err.args