chore: Omit lock when using connection pool (#6734)

Co-authored-by: Conrad Ludgate <conradludgate@gmail.com>

.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:
 

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

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+version = "4.12.1"
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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/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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+    { 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 = [
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@@ -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/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/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/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 = "1.0.7"
 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/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__ = "0.3.3"
 
 __all__ = ["Auth", "Encryption", "EncryptionContext", "get_client", "get_sync_client"]

libs/sdk-py/langgraph_sdk/client.py

@@ -2994,6 +2994,7 @@ 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.
@@ -3080,6 +3081,7 @@ 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.
@@ -6302,6 +6304,7 @@ 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.
@@ -6384,6 +6387,7 @@ 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.

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/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/"
 

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

libs/sdk-py/uv.lock

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