fix: dependabot (#6806)

- Add schedule.day: monday to all entries
- Add groups configuration to prevent noisy per-dependency PRs
- Split pip directories into individual entries per Dependabot v2 spec
- Add npm ecosystem entries for js-examples and js-monorepo-example
subdirectories
- Specify package-manager: uv for all Python entries (repo uses uv.lock)

Thank you for contributing to LangGraph! Follow these steps to mark your
pull request as ready for review. **If any of these steps are not
completed, your PR will not be considered for review.**

- [x] **PR title**: Follows the format: {TYPE}({SCOPE}): {DESCRIPTION}
  - Examples:
    - feat(core): add multi-tenant support
    - fix(cli): resolve flag parsing error
    - docs(openai): update API usage examples
  - Allowed `{TYPE}` values:
- feat, fix, docs, style, refactor, perf, test, build, ci, chore,
revert, release
  - Allowed `{SCOPE}` values (optional):
- langgraph, docs, cli, checkpoint, checkpoint-postgres,
checkpoint-sqlite, prebuilt, scheduler-kafka, sdk-py
- Once you've written the title, please delete this checklist item; do
not include it in the PR.

- [x] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** a description of the change. Include a [closing
keyword](https://docs.github.com/en/issues/tracking-your-work-with-issues/using-issues/linking-a-pull-request-to-an-issue#linking-a-pull-request-to-an-issue-using-a-keyword)
if applicable.
  - **Issue:** the issue # it fixes, if applicable
  - **Dependencies:** any dependencies required for this change
- **Twitter handle:** if your PR gets announced, and you'd like a
mention, we'll gladly shout you out!

- [x] **Add tests and docs**: If you're adding a new integration, you
must include:
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.

- [x] **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:

- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to `pyproject.toml` files (even
optional ones) unless they are **required** for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.

.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:
 

.github/dependabot.yml

@@ -4,15 +4,98 @@ updates:
     directory: "/"
     schedule:
       interval: "weekly"
+      day: "monday"
+    groups:
+      all-dependencies:
+        patterns:
+          - "*"
 
-  - package-ecosystem: "pip"
-    directories:
-      - "libs/checkpoint"
-      - "libs/checkpoint-postgres"
-      - "libs/checkpoint-sqlite"
-      - "libs/cli"
-      - "libs/langgraph"
-      - "libs/prebuilt"
-      - "libs/sdk-py"
+  - package-ecosystem: "uv"
+    directory: "/libs/checkpoint"
     schedule:
       interval: "weekly"
+      day: "monday"
+    groups:
+      all-dependencies:
+        patterns:
+          - "*"
+
+  - package-ecosystem: "uv"
+    directory: "/libs/checkpoint-postgres"
+    schedule:
+      interval: "weekly"
+      day: "monday"
+    groups:
+      all-dependencies:
+        patterns:
+          - "*"
+
+  - package-ecosystem: "uv"
+    directory: "/libs/checkpoint-sqlite"
+    schedule:
+      interval: "weekly"
+      day: "monday"
+    groups:
+      all-dependencies:
+        patterns:
+          - "*"
+
+  - package-ecosystem: "uv"
+    directory: "/libs/cli"
+    schedule:
+      interval: "weekly"
+      day: "monday"
+    groups:
+      all-dependencies:
+        patterns:
+          - "*"
+
+  - package-ecosystem: "uv"
+    directory: "/libs/langgraph"
+    schedule:
+      interval: "weekly"
+      day: "monday"
+    groups:
+      all-dependencies:
+        patterns:
+          - "*"
+
+  - package-ecosystem: "uv"
+    directory: "/libs/prebuilt"
+    schedule:
+      interval: "weekly"
+      day: "monday"
+    groups:
+      all-dependencies:
+        patterns:
+          - "*"
+
+  - package-ecosystem: "uv"
+    directory: "/libs/sdk-py"
+    schedule:
+      interval: "weekly"
+      day: "monday"
+    groups:
+      all-dependencies:
+        patterns:
+          - "*"
+
+  - package-ecosystem: "npm"
+    directory: "/libs/cli/js-examples"
+    schedule:
+      interval: "weekly"
+      day: "monday"
+    groups:
+      all-dependencies:
+        patterns:
+          - "*"
+
+  - package-ecosystem: "npm"
+    directory: "/libs/cli/js-monorepo-example"
+    schedule:
+      interval: "weekly"
+      day: "monday"
+    groups:
+      all-dependencies:
+        patterns:
+          - "*"

.github/scripts/run_langgraph_cli_test.py

@@ -63,7 +63,7 @@ def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
             try:
                 sys.stderr.write("\n== docker compose ps ==\n")
                 runner.run(
-                    subp_exec(*compose_cmd, *args, "ps", input=stdin, verbose=False)
+                    subp_exec(*compose_cmd, *args, "ps", input=stdin, verbose=True)
                 )
             except Exception:
                 pass
@@ -76,7 +76,7 @@ def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
                         "logs",
                         "langgraph-api",
                         input=stdin,
-                        verbose=False,
+                        verbose=True,
                     )
                 )
             except Exception:

.github/workflows/_integration_test.yml

@@ -96,8 +96,8 @@ jobs:
           timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-h
           echo "Finished starting up langgraph-test-h"
           LANGGRAPH_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langgraph'); print(v);")
-          if [ "$LANGGRAPH_VERSION" != "1.0.2" ]; then
-            echo "LANGGRAPH_VERSION != 1.0.2; $LANGGRAPH_VERSION"
+          if [ "$LANGGRAPH_VERSION" != "1.0.8" ]; then
+            echo "LANGGRAPH_VERSION != 1.0.8; $LANGGRAPH_VERSION"
             exit 1
           fi
           LANGCHAIN_OPENAI_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langchain-openai'); print(v);")

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"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "exceptiongroup", marker = "python_full_version < '3.11'" },
     { name = "idna" },
     { name = "typing-extensions", marker = "python_full_version < '3.13'" },
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+sdist = { url = "https://files.pythonhosted.org/packages/96/f0/5eb65b2bb0d09ac6776f2eb54adee6abe8228ea05b20a5ad0e4945de8aac/anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703", size = 228685, upload-time = "2026-01-06T11:45:21.246Z" }
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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" },
 ]
 
 [[package]]
@@ -36,11 +36,11 @@ wheels = [
 
 [[package]]
 name = "certifi"
-version = "2025.11.12"
+version = "2026.1.4"
 source = { registry = "https://pypi.org/simple" }
-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" }
 wheels = [
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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" },
 ]
 
 [[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" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/0b/6f/9e959821df556cf32d57d26aa7b86905a63a91e6e9e744994f8045fe2d70/langchain_core-1.1.3.tar.gz", hash = "sha256:ff0bc5e6e701c4d6fe00c73c4feae5c993a7a8e0b91f0a1d07015277d4634275", size = 801750, upload-time = "2025-12-09T14:55:55.741Z" }
+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" },
 ]
 
 [[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 = [
     { name = "uuid-utils" },
     { name = "zstandard" },
 ]
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+sdist = { url = "https://files.pythonhosted.org/packages/e7/85/9c7933052a997da1b85bc5c774f3865e9b1da1c8d71541ea133178b13229/langsmith-0.6.4.tar.gz", hash = "sha256:36f7223a01c218079fbb17da5e536ebbaf5c1468c028abe070aa3ae59bc99ec8", size = 919964, upload-time = "2026-01-15T20:02:28.873Z" }
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+    { url = "https://files.pythonhosted.org/packages/66/0f/09a6637a7ba777eb307b7c80852d9ee26438e2bdafbad6fcc849ff9d9192/langsmith-0.6.4-py3-none-any.whl", hash = "sha256:ac4835860160be371042c7adbba3cb267bcf8d96a5ea976c33a8a4acad6c5486", size = 283503, upload-time = "2026-01-15T20:02:26.662Z" },
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 [[package]]
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 ]
 
 [[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/examples/graph_prerelease_reqs/deps/additional_deps/pyproject.toml

@@ -5,5 +5,5 @@ description = "Test for prerelease stuff"
 readme = "README.md"
 requires-python = ">=3.10"
 dependencies = [
-  "langgraph==1.0.2"
+  "langgraph==1.0.8"
 ]

libs/cli/examples/graph_prerelease_reqs/pyproject.toml

@@ -7,7 +7,7 @@ requires-python = ">=3.10"
 dependencies = [
   "langchain-openai==1.0.0a2",
   "langchain-anthropic==1.0.0a5",
-  "langgraph==1.0.2"
+  "langgraph==1.0.8"
 ]
 
 [tool.uv]

libs/cli/langgraph_cli/__init__.py

@@ -1 +1 @@
-__version__ = "0.4.11"
+__version__ = "0.4.13"

libs/cli/langgraph_cli/config.py

@@ -196,6 +196,11 @@ def validate_config(config: Config) -> Config:
                 f"Python version {pyversion} is not supported. "
                 f"Minimum required version is {MIN_PYTHON_VERSION}."
             )
+        if "bullseye" in pyversion:
+            raise click.UsageError(
+                "Bullseye images were deprecated in version 0.4.13. "
+                "Please use 'bookworm' or 'debian' instead."
+            )
 
         if not config["dependencies"]:
             raise click.UsageError(
@@ -210,10 +215,15 @@ def validate_config(config: Config) -> Config:
 
     # Validate image_distro config
     if image_distro := config.get("image_distro"):
+        if image_distro == "bullseye":
+            raise click.UsageError(
+                "Bullseye images were deprecated in version 0.4.13. "
+                "Please use 'bookworm' or 'debian' instead."
+            )
         if image_distro not in Distros.__args__:
             raise click.UsageError(
                 f"Invalid image_distro: '{image_distro}'. "
-                "Must be one of 'debian', 'bullseye', or 'bookworm'."
+                "Must be one of 'debian', 'wolfi', or 'bookworm'."
             )
 
     if pip_installer := config.get("pip_installer"):

libs/cli/langgraph_cli/schemas.py

@@ -1,6 +1,6 @@
 from typing import Any, Literal, TypedDict
 
-Distros = Literal["debian", "wolfi", "bullseye", "bookworm"]
+Distros = Literal["debian", "wolfi", "bookworm"]
 MiddlewareOrders = Literal["auth_first", "middleware_first"]
 
 
@@ -107,17 +107,19 @@ class StoreConfig(TypedDict, total=False):
 class ThreadTTLConfig(TypedDict, total=False):
     """Configure a default TTL for checkpointed data within threads."""
 
-    strategy: Literal["delete"]
-    """Strategy to use for deleting checkpointed data.
-    
-    Choices:
-      - "delete": Delete all checkpoints for a thread after TTL expires.
+    strategy: Literal["delete", "keep_latest"]
+    """Action taken when a thread exceeds its TTL.
+
+    - "delete": Remove the thread and all its data entirely.
+    - "keep_latest": Prune old checkpoints but keep the thread and its latest state.
     """
     default_ttl: float | None
     """Default TTL (time-to-live) in minutes for checkpointed data."""
     sweep_interval_minutes: int | None
     """Interval in minutes between sweep iterations.
     If omitted, a default interval will be used (typically ~ 5 minutes)."""
+    sweep_limit: int | None
+    """Maximum number of threads to process per sweep iteration. Defaults to 1000."""
 
 
 class SerdeConfig(TypedDict, total=False):
@@ -173,7 +175,7 @@ class CheckpointerConfig(TypedDict, total=False):
     """
     serde: SerdeConfig | None
     """Optional. Defines the serde configuration.
-    
+
     If provided, the checkpointer will apply serde settings according to the configuration.
     If omitted, no serde behavior is configured.
 
@@ -557,7 +559,7 @@ class Config(TypedDict, total=False):
     image_distro: Distros | None
     """Optional. Linux distribution for the base image.
     
-    Must be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.
+    Must be one of 'wolfi', 'debian', or 'bookworm'.
     If omitted, defaults to 'debian' ('latest').
     """
 

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

@@ -147,7 +147,6 @@
                 {
                   "enum": [
                     "bookworm",
-                    "bullseye",
                     "debian",
                     "wolfi"
                   ]
@@ -156,7 +155,7 @@
                   "type": "null"
                 }
               ],
-              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
+              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
             },
             "keep_pkg_tools": {
               "anyOf": [
@@ -370,7 +369,7 @@
                   "type": "null"
                 }
               ],
-              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
+              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
             },
             "keep_pkg_tools": {
               "anyOf": [
@@ -618,9 +617,10 @@
         },
         "strategy": {
           "enum": [
-            "delete"
+            "delete",
+            "keep_latest"
           ],
-          "description": "Strategy to use for deleting checkpointed data.\n"
+          "description": "Action taken when a thread exceeds its TTL.\n\n"
         },
         "sweep_interval_minutes": {
           "anyOf": [
@@ -632,6 +632,17 @@
             }
           ],
           "description": "Interval in minutes between sweep iterations.\nIf omitted, a default interval will be used (typically ~ 5 minutes)."
+        },
+        "sweep_limit": {
+          "anyOf": [
+            {
+              "type": "integer"
+            },
+            {
+              "type": "null"
+            }
+          ],
+          "description": "Maximum number of threads to process per sweep iteration. Defaults to 1000."
         }
       },
       "required": []

libs/cli/schemas/schema.v0.json

@@ -147,7 +147,6 @@
                 {
                   "enum": [
                     "bookworm",
-                    "bullseye",
                     "debian",
                     "wolfi"
                   ]
@@ -156,7 +155,7 @@
                   "type": "null"
                 }
               ],
-              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
+              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
             },
             "keep_pkg_tools": {
               "anyOf": [
@@ -370,7 +369,7 @@
                   "type": "null"
                 }
               ],
-              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
+              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
             },
             "keep_pkg_tools": {
               "anyOf": [
@@ -618,9 +617,10 @@
         },
         "strategy": {
           "enum": [
-            "delete"
+            "delete",
+            "keep_latest"
           ],
-          "description": "Strategy to use for deleting checkpointed data.\n"
+          "description": "Action taken when a thread exceeds its TTL.\n\n"
         },
         "sweep_interval_minutes": {
           "anyOf": [
@@ -632,6 +632,17 @@
             }
           ],
           "description": "Interval in minutes between sweep iterations.\nIf omitted, a default interval will be used (typically ~ 5 minutes)."
+        },
+        "sweep_limit": {
+          "anyOf": [
+            {
+              "type": "integer"
+            },
+            {
+              "type": "null"
+            }
+          ],
+          "description": "Maximum number of threads to process per sweep iteration. Defaults to 1000."
         }
       },
       "required": []

libs/cli/tests/unit_tests/test_config.py

@@ -120,14 +120,14 @@ def test_validate_config():
         validate_config({"python_version": "3.10"})
     assert "Minimum required version" in str(exc_info.value)
 
-    config = validate_config(
-        {
-            "python_version": "3.11-bullseye",
-            "dependencies": ["."],
-            "graphs": {"agent": "./agent.py:graph"},
-        }
-    )
-    assert config["python_version"] == "3.11-bullseye"
+    with pytest.raises(click.UsageError, match="Bullseye images were deprecated"):
+        validate_config(
+            {
+                "python_version": "3.11-bullseye",
+                "dependencies": ["."],
+                "graphs": {"agent": "./agent.py:graph"},
+            }
+        )
 
     config = validate_config(
         {
@@ -181,6 +181,17 @@ def test_validate_config_image_distro():
     )
     assert config["image_distro"] == "debian"
 
+    # Bullseye should raise deprecation error
+    with pytest.raises(click.UsageError, match="Bullseye images were deprecated"):
+        validate_config(
+            {
+                "python_version": "3.11",
+                "dependencies": ["."],
+                "graphs": {"agent": "./agent.py:graph"},
+                "image_distro": "bullseye",
+            }
+        )
+
     # Invalid image_distro values should raise error
     with pytest.raises(click.UsageError) as exc_info:
         validate_config(

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__ = "0.3.3"
+__version__ = "0.3.6"
 
 __all__ = ["Auth", "Encryption", "EncryptionContext", "get_client", "get_sync_client"]

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

@@ -0,0 +1,20 @@
+"""Async client exports."""
+
+from langgraph_sdk._async.assistants import AssistantsClient
+from langgraph_sdk._async.client import LangGraphClient, get_client
+from langgraph_sdk._async.cron import CronClient
+from langgraph_sdk._async.http import HttpClient
+from langgraph_sdk._async.runs import RunsClient
+from langgraph_sdk._async.store import StoreClient
+from langgraph_sdk._async.threads import ThreadsClient
+
+__all__ = [
+    "AssistantsClient",
+    "CronClient",
+    "HttpClient",
+    "LangGraphClient",
+    "RunsClient",
+    "StoreClient",
+    "ThreadsClient",
+    "get_client",
+]

libs/sdk-py/langgraph_sdk/_async/assistants.py

@@ -0,0 +1,733 @@
+"""Async client for managing assistants in LangGraph."""
+
+from __future__ import annotations
+
+from collections.abc import Mapping
+from typing import Any, Literal, cast, overload
+
+import httpx
+
+from langgraph_sdk._async.http import HttpClient
+from langgraph_sdk.schema import (
+    Assistant,
+    AssistantSelectField,
+    AssistantSortBy,
+    AssistantsSearchResponse,
+    AssistantVersion,
+    Config,
+    Context,
+    GraphSchema,
+    Json,
+    OnConflictBehavior,
+    QueryParamTypes,
+    SortOrder,
+    Subgraphs,
+)
+
+
+class AssistantsClient:
+    """Client for managing assistants in LangGraph.
+
+    This class provides methods to interact with assistants,
+    which are versioned configurations of your graph.
+
+    ???+ example "Example"
+
+        ```python
+        client = get_client(url="http://localhost:2024")
+        assistant = await client.assistants.get("assistant_id_123")
+        ```
+    """
+
+    def __init__(self, http: HttpClient) -> None:
+        self.http = http
+
+    async def get(
+        self,
+        assistant_id: str,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Assistant:
+        """Get an assistant by ID.
+
+        Args:
+            assistant_id: The ID of the assistant to get.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            Assistant: Assistant Object.
+
+        ???+ example "Example Usage"
+
+            ```python
+            assistant = await client.assistants.get(
+                assistant_id="my_assistant_id"
+            )
+            print(assistant)
+            ```
+
+            ```shell
+            ----------------------------------------------------
+
+            {
+                'assistant_id': 'my_assistant_id',
+                'graph_id': 'agent',
+                'created_at': '2024-06-25T17:10:33.109781+00:00',
+                'updated_at': '2024-06-25T17:10:33.109781+00:00',
+                'config': {},
+                'metadata': {'created_by': 'system'},
+                'version': 1,
+                'name': 'my_assistant'
+            }
+            ```
+        """
+        return await self.http.get(
+            f"/assistants/{assistant_id}", headers=headers, params=params
+        )
+
+    async def get_graph(
+        self,
+        assistant_id: str,
+        *,
+        xray: int | bool = False,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> dict[str, list[dict[str, Any]]]:
+        """Get the graph of an assistant by ID.
+
+        Args:
+            assistant_id: The ID of the assistant to get the graph of.
+            xray: Include graph representation of subgraphs. If an integer value is provided, only subgraphs with a depth less than or equal to the value will be included.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            Graph: The graph information for the assistant in JSON format.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            graph_info = await client.assistants.get_graph(
+                assistant_id="my_assistant_id"
+            )
+            print(graph_info)
+            ```
+
+            ```shell
+
+            --------------------------------------------------------------------------------------------------------------------------
+
+            {
+                'nodes':
+                    [
+                        {'id': '__start__', 'type': 'schema', 'data': '__start__'},
+                        {'id': '__end__', 'type': 'schema', 'data': '__end__'},
+                        {'id': 'agent','type': 'runnable','data': {'id': ['langgraph', 'utils', 'RunnableCallable'],'name': 'agent'}},
+                    ],
+                'edges':
+                    [
+                        {'source': '__start__', 'target': 'agent'},
+                        {'source': 'agent','target': '__end__'}
+                    ]
+            }
+            ```
+
+
+        """
+        query_params = {"xray": xray}
+        if params:
+            query_params.update(params)
+
+        return await self.http.get(
+            f"/assistants/{assistant_id}/graph", params=query_params, headers=headers
+        )
+
+    async def get_schemas(
+        self,
+        assistant_id: str,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> GraphSchema:
+        """Get the schemas of an assistant by ID.
+
+        Args:
+            assistant_id: The ID of the assistant to get the schema of.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            GraphSchema: The graph schema for the assistant.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            schema = await client.assistants.get_schemas(
+                assistant_id="my_assistant_id"
+            )
+            print(schema)
+            ```
+
+            ```shell
+
+            ----------------------------------------------------------------------------------------------------------------------------
+
+            {
+                'graph_id': 'agent',
+                'state_schema':
+                    {
+                        'title': 'LangGraphInput',
+                        '$ref': '#/definitions/AgentState',
+                        'definitions':
+                            {
+                                'BaseMessage':
+                                    {
+                                        'title': 'BaseMessage',
+                                        'description': 'Base abstract Message class. Messages are the inputs and outputs of ChatModels.',
+                                        'type': 'object',
+                                        'properties':
+                                            {
+                                             'content':
+                                                {
+                                                    'title': 'Content',
+                                                    'anyOf': [
+                                                        {'type': 'string'},
+                                                        {'type': 'array','items': {'anyOf': [{'type': 'string'}, {'type': 'object'}]}}
+                                                    ]
+                                                },
+                                            'additional_kwargs':
+                                                {
+                                                    'title': 'Additional Kwargs',
+                                                    'type': 'object'
+                                                },
+                                            'response_metadata':
+                                                {
+                                                    'title': 'Response Metadata',
+                                                    'type': 'object'
+                                                },
+                                            'type':
+                                                {
+                                                    'title': 'Type',
+                                                    'type': 'string'
+                                                },
+                                            'name':
+                                                {
+                                                    'title': 'Name',
+                                                    'type': 'string'
+                                                },
+                                            'id':
+                                                {
+                                                    'title': 'Id',
+                                                    'type': 'string'
+                                                }
+                                            },
+                                        'required': ['content', 'type']
+                                    },
+                                'AgentState':
+                                    {
+                                        'title': 'AgentState',
+                                        'type': 'object',
+                                        'properties':
+                                            {
+                                                'messages':
+                                                    {
+                                                        'title': 'Messages',
+                                                        'type': 'array',
+                                                        'items': {'$ref': '#/definitions/BaseMessage'}
+                                                    }
+                                            },
+                                        'required': ['messages']
+                                    }
+                            }
+                    },
+                'context_schema':
+                    {
+                        'title': 'Context',
+                        'type': 'object',
+                        'properties':
+                            {
+                                'model_name':
+                                    {
+                                        'title': 'Model Name',
+                                        'enum': ['anthropic', 'openai'],
+                                        'type': 'string'
+                                    }
+                            }
+                    }
+            }
+            ```
+
+        """
+        return await self.http.get(
+            f"/assistants/{assistant_id}/schemas", headers=headers, params=params
+        )
+
+    async def get_subgraphs(
+        self,
+        assistant_id: str,
+        namespace: str | None = None,
+        recurse: bool = False,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Subgraphs:
+        """Get the schemas of an assistant by ID.
+
+        Args:
+            assistant_id: The ID of the assistant to get the schema of.
+            namespace: Optional namespace to filter by.
+            recurse: Whether to recursively get subgraphs.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            Subgraphs: The graph schema for the assistant.
+
+        """
+        get_params = {"recurse": recurse}
+        if params:
+            get_params = {**get_params, **params}
+        if namespace is not None:
+            return await self.http.get(
+                f"/assistants/{assistant_id}/subgraphs/{namespace}",
+                params=get_params,
+                headers=headers,
+            )
+        else:
+            return await self.http.get(
+                f"/assistants/{assistant_id}/subgraphs",
+                params=get_params,
+                headers=headers,
+            )
+
+    async def create(
+        self,
+        graph_id: str | None,
+        config: Config | None = None,
+        *,
+        context: Context | None = None,
+        metadata: Json = None,
+        assistant_id: str | None = None,
+        if_exists: OnConflictBehavior | None = None,
+        name: str | None = None,
+        headers: Mapping[str, str] | None = None,
+        description: str | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Assistant:
+        """Create a new assistant.
+
+        Useful when graph is configurable and you want to create different assistants based on different configurations.
+
+        Args:
+            graph_id: The ID of the graph the assistant should use. The graph ID is normally set in your langgraph.json configuration.
+            config: Configuration to use for the graph.
+            metadata: Metadata to add to assistant.
+            context: Static context to add to the assistant.
+                !!! version-added "Added in version 0.6.0"
+            assistant_id: Assistant ID to use, will default to a random UUID if not provided.
+            if_exists: How to handle duplicate creation. Defaults to 'raise' under the hood.
+                Must be either 'raise' (raise error if duplicate), or 'do_nothing' (return existing assistant).
+            name: The name of the assistant. Defaults to 'Untitled' under the hood.
+            headers: Optional custom headers to include with the request.
+            description: Optional description of the assistant.
+                The description field is available for langgraph-api server version>=0.0.45
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            Assistant: The created assistant.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            assistant = await client.assistants.create(
+                graph_id="agent",
+                context={"model_name": "openai"},
+                metadata={"number":1},
+                assistant_id="my-assistant-id",
+                if_exists="do_nothing",
+                name="my_name"
+            )
+            ```
+        """
+        payload: dict[str, Any] = {
+            "graph_id": graph_id,
+        }
+        if config:
+            payload["config"] = config
+        if context:
+            payload["context"] = context
+        if metadata:
+            payload["metadata"] = metadata
+        if assistant_id:
+            payload["assistant_id"] = assistant_id
+        if if_exists:
+            payload["if_exists"] = if_exists
+        if name:
+            payload["name"] = name
+        if description:
+            payload["description"] = description
+        return await self.http.post(
+            "/assistants", json=payload, headers=headers, params=params
+        )
+
+    async def update(
+        self,
+        assistant_id: str,
+        *,
+        graph_id: str | None = None,
+        config: Config | None = None,
+        context: Context | None = None,
+        metadata: Json = None,
+        name: str | None = None,
+        headers: Mapping[str, str] | None = None,
+        description: str | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Assistant:
+        """Update an assistant.
+
+        Use this to point to a different graph, update the configuration, or change the metadata of an assistant.
+
+        Args:
+            assistant_id: Assistant to update.
+            graph_id: The ID of the graph the assistant should use.
+                The graph ID is normally set in your langgraph.json configuration. If `None`, assistant will keep pointing to same graph.
+            config: Configuration to use for the graph.
+            context: Static context to add to the assistant.
+                !!! version-added "Added in version 0.6.0"
+            metadata: Metadata to merge with existing assistant metadata.
+            name: The new name for the assistant.
+            headers: Optional custom headers to include with the request.
+            description: Optional description of the assistant.
+                The description field is available for langgraph-api server version>=0.0.45
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            The updated assistant.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            assistant = await client.assistants.update(
+                assistant_id='e280dad7-8618-443f-87f1-8e41841c180f',
+                graph_id="other-graph",
+                context={"model_name": "anthropic"},
+                metadata={"number":2}
+            )
+            ```
+
+        """
+        payload: dict[str, Any] = {}
+        if graph_id:
+            payload["graph_id"] = graph_id
+        if config:
+            payload["config"] = config
+        if context:
+            payload["context"] = context
+        if metadata:
+            payload["metadata"] = metadata
+        if name:
+            payload["name"] = name
+        if description:
+            payload["description"] = description
+        return await self.http.patch(
+            f"/assistants/{assistant_id}",
+            json=payload,
+            headers=headers,
+            params=params,
+        )
+
+    async def delete(
+        self,
+        assistant_id: str,
+        *,
+        delete_threads: bool = False,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> None:
+        """Delete an assistant.
+
+        Args:
+            assistant_id: The assistant ID to delete.
+            delete_threads: If true, delete all threads with `metadata.assistant_id`
+                matching this assistant, along with runs and checkpoints belonging to
+                those threads.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            `None`
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            await client.assistants.delete(
+                assistant_id="my_assistant_id"
+            )
+            ```
+
+        """
+        query_params: dict[str, Any] = {}
+        if delete_threads:
+            query_params["delete_threads"] = True
+        if params:
+            query_params.update(params)
+        await self.http.delete(
+            f"/assistants/{assistant_id}",
+            headers=headers,
+            params=query_params or None,
+        )
+
+    @overload
+    async def search(
+        self,
+        *,
+        metadata: Json = None,
+        graph_id: str | None = None,
+        name: str | None = None,
+        limit: int = 10,
+        offset: int = 0,
+        sort_by: AssistantSortBy | None = None,
+        sort_order: SortOrder | None = None,
+        select: list[AssistantSelectField] | None = None,
+        response_format: Literal["object"],
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> AssistantsSearchResponse: ...
+
+    @overload
+    async def search(
+        self,
+        *,
+        metadata: Json = None,
+        graph_id: str | None = None,
+        name: str | None = None,
+        limit: int = 10,
+        offset: int = 0,
+        sort_by: AssistantSortBy | None = None,
+        sort_order: SortOrder | None = None,
+        select: list[AssistantSelectField] | None = None,
+        response_format: Literal["array"] = "array",
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> list[Assistant]: ...
+
+    async def search(
+        self,
+        *,
+        metadata: Json = None,
+        graph_id: str | None = None,
+        name: str | None = None,
+        limit: int = 10,
+        offset: int = 0,
+        sort_by: AssistantSortBy | None = None,
+        sort_order: SortOrder | None = None,
+        select: list[AssistantSelectField] | None = None,
+        response_format: Literal["array", "object"] = "array",
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> AssistantsSearchResponse | list[Assistant]:
+        """Search for assistants.
+
+        Args:
+            metadata: Metadata to filter by. Exact match filter for each KV pair.
+            graph_id: The ID of the graph to filter by.
+                The graph ID is normally set in your langgraph.json configuration.
+            name: The name of the assistant to filter by.
+                The filtering logic will match assistants where 'name' is a substring (case insensitive) of the assistant name.
+            limit: The maximum number of results to return.
+            offset: The number of results to skip.
+            sort_by: The field to sort by.
+            sort_order: The order to sort by.
+            select: Specific assistant fields to include in the response.
+            response_format: Controls the response shape. Use `"array"` (default)
+                to return a bare list of assistants, or `"object"` to return
+                a mapping containing assistants plus pagination metadata.
+                Defaults to "array", though this default will be changed to "object" in a future release.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            A list of assistants (when `response_format="array"`) or a mapping
+            with the assistants and the next pagination cursor (when
+            `response_format="object"`).
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            response = await client.assistants.search(
+                metadata = {"name":"my_name"},
+                graph_id="my_graph_id",
+                limit=5,
+                offset=5,
+                response_format="object"
+            )
+            next_cursor = response["next"]
+            assistants = response["assistants"]
+            ```
+        """
+        if response_format not in ("array", "object"):
+            raise ValueError(
+                f"response_format must be 'array' or 'object', got {response_format!r}"
+            )
+        payload: dict[str, Any] = {
+            "limit": limit,
+            "offset": offset,
+        }
+        if metadata:
+            payload["metadata"] = metadata
+        if graph_id:
+            payload["graph_id"] = graph_id
+        if name:
+            payload["name"] = name
+        if sort_by:
+            payload["sort_by"] = sort_by
+        if sort_order:
+            payload["sort_order"] = sort_order
+        if select:
+            payload["select"] = select
+        next_cursor: str | None = None
+
+        def capture_pagination(response: httpx.Response) -> None:
+            nonlocal next_cursor
+            next_cursor = response.headers.get("X-Pagination-Next")
+
+        assistants = cast(
+            list[Assistant],
+            await self.http.post(
+                "/assistants/search",
+                json=payload,
+                headers=headers,
+                params=params,
+                on_response=capture_pagination if response_format == "object" else None,
+            ),
+        )
+        if response_format == "object":
+            return {"assistants": assistants, "next": next_cursor}
+        return assistants
+
+    async def count(
+        self,
+        *,
+        metadata: Json = None,
+        graph_id: str | None = None,
+        name: str | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> int:
+        """Count assistants matching filters.
+
+        Args:
+            metadata: Metadata to filter by. Exact match for each key/value.
+            graph_id: Optional graph id to filter by.
+            name: Optional name to filter by.
+                The filtering logic will match assistants where 'name' is a substring (case insensitive) of the assistant name.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            int: Number of assistants matching the criteria.
+        """
+        payload: dict[str, Any] = {}
+        if metadata:
+            payload["metadata"] = metadata
+        if graph_id:
+            payload["graph_id"] = graph_id
+        if name:
+            payload["name"] = name
+        return await self.http.post(
+            "/assistants/count", json=payload, headers=headers, params=params
+        )
+
+    async def get_versions(
+        self,
+        assistant_id: str,
+        metadata: Json = None,
+        limit: int = 10,
+        offset: int = 0,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> list[AssistantVersion]:
+        """List all versions of an assistant.
+
+        Args:
+            assistant_id: The assistant ID to get versions for.
+            metadata: Metadata to filter versions by. Exact match filter for each KV pair.
+            limit: The maximum number of versions to return.
+            offset: The number of versions to skip.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            A list of assistant versions.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            assistant_versions = await client.assistants.get_versions(
+                assistant_id="my_assistant_id"
+            )
+            ```
+        """
+
+        payload: dict[str, Any] = {
+            "limit": limit,
+            "offset": offset,
+        }
+        if metadata:
+            payload["metadata"] = metadata
+        return await self.http.post(
+            f"/assistants/{assistant_id}/versions",
+            json=payload,
+            headers=headers,
+            params=params,
+        )
+
+    async def set_latest(
+        self,
+        assistant_id: str,
+        version: int,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Assistant:
+        """Change the version of an assistant.
+
+        Args:
+            assistant_id: The assistant ID to delete.
+            version: The version to change to.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            Assistant Object.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            new_version_assistant = await client.assistants.set_latest(
+                assistant_id="my_assistant_id",
+                version=3
+            )
+            ```
+
+        """
+
+        payload: dict[str, Any] = {"version": version}
+
+        return await self.http.post(
+            f"/assistants/{assistant_id}/latest",
+            json=payload,
+            headers=headers,
+            params=params,
+        )

libs/sdk-py/langgraph_sdk/_async/client.py

@@ -0,0 +1,178 @@
+"""Async LangGraph client."""
+
+from __future__ import annotations
+
+import logging
+import os
+from collections.abc import Mapping
+from types import TracebackType
+
+import httpx
+
+from langgraph_sdk._async.assistants import AssistantsClient
+from langgraph_sdk._async.cron import CronClient
+from langgraph_sdk._async.http import HttpClient
+from langgraph_sdk._async.runs import RunsClient
+from langgraph_sdk._async.store import StoreClient
+from langgraph_sdk._async.threads import ThreadsClient
+from langgraph_sdk._shared.types import TimeoutTypes
+from langgraph_sdk._shared.utilities import (
+    NOT_PROVIDED,
+    _get_headers,
+    _registered_transports,
+    get_asgi_transport,
+)
+
+logger = logging.getLogger(__name__)
+
+
+def get_client(
+    *,
+    url: str | None = None,
+    api_key: str | None = NOT_PROVIDED,
+    headers: Mapping[str, str] | None = None,
+    timeout: TimeoutTypes | None = None,
+) -> LangGraphClient:
+    """Create and configure a LangGraphClient.
+
+    The client provides programmatic access to LangSmith Deployment. It supports
+    both remote servers and local in-process connections (when running inside a LangGraph server).
+
+    Args:
+        url:
+            Base URL of the LangGraph API.
+            - If `None`, the client first attempts an in-process connection via ASGI transport.
+              If that fails, it defers registration until after app initialization. This
+              only works if the client is used from within the Agent server.
+        api_key:
+            API key for authentication. Can be:
+              - A string: use this exact API key
+              - `None`: explicitly skip loading from environment variables
+              - Not provided (default): auto-load from environment in this order:
+                1. `LANGGRAPH_API_KEY`
+                2. `LANGSMITH_API_KEY`
+                3. `LANGCHAIN_API_KEY`
+        headers:
+            Additional HTTP headers to include in requests. Merged with authentication headers.
+        timeout:
+            HTTP timeout configuration. May be:
+              - `httpx.Timeout` instance
+              - float (total seconds)
+              - tuple `(connect, read, write, pool)` in seconds
+            Defaults: connect=5, read=300, write=300, pool=5.
+
+    Returns:
+        LangGraphClient:
+            A top-level client exposing sub-clients for assistants, threads,
+            runs, and cron operations.
+
+    ???+ example "Connect to a remote server:"
+
+        ```python
+        from langgraph_sdk import get_client
+
+        # get top-level LangGraphClient
+        client = get_client(url="http://localhost:8123")
+
+        # example usage: client.<model>.<method_name>()
+        assistants = await client.assistants.get(assistant_id="some_uuid")
+        ```
+
+    ???+ example "Connect in-process to a running LangGraph server:"
+
+        ```python
+        from langgraph_sdk import get_client
+
+        client = get_client(url=None)
+
+        async def my_node(...):
+            subagent_result = await client.runs.wait(
+                thread_id=None,
+                assistant_id="agent",
+                input={"messages": [{"role": "user", "content": "Foo"}]},
+            )
+        ```
+
+    ???+ example "Skip auto-loading API key from environment:"
+
+        ```python
+        from langgraph_sdk import get_client
+
+        # Don't load API key from environment variables
+        client = get_client(
+            url="http://localhost:8123",
+            api_key=None
+        )
+        ```
+    """
+
+    transport: httpx.AsyncBaseTransport | None = None
+    if url is None:
+        url = "http://api"
+        if os.environ.get("__LANGGRAPH_DEFER_LOOPBACK_TRANSPORT") == "true":
+            transport = get_asgi_transport()(app=None, root_path="/noauth")
+            _registered_transports.append(transport)
+        else:
+            try:
+                from langgraph_api.server import app  # type: ignore
+
+                transport = get_asgi_transport()(app, root_path="/noauth")
+            except Exception:
+                logger.debug(
+                    "Failed to connect to in-process LangGraph server. Deferring configuration.",
+                    exc_info=True,
+                )
+                transport = get_asgi_transport()(app=None, root_path="/noauth")
+                _registered_transports.append(transport)
+
+    if transport is None:
+        transport = httpx.AsyncHTTPTransport(retries=5)
+    client = httpx.AsyncClient(
+        base_url=url,
+        transport=transport,
+        timeout=(
+            httpx.Timeout(timeout)  # type: ignore[arg-type]
+            if timeout is not None
+            else httpx.Timeout(connect=5, read=300, write=300, pool=5)
+        ),
+        headers=_get_headers(api_key, headers),
+    )
+    return LangGraphClient(client)
+
+
+class LangGraphClient:
+    """Top-level client for LangGraph API.
+
+    Attributes:
+        assistants: Manages versioned configuration for your graphs.
+        threads: Handles (potentially) multi-turn interactions, such as conversational threads.
+        runs: Controls individual invocations of the graph.
+        crons: Manages scheduled operations.
+        store: Interfaces with persistent, shared data storage.
+    """
+
+    def __init__(self, client: httpx.AsyncClient) -> None:
+        self.http = HttpClient(client)
+        self.assistants = AssistantsClient(self.http)
+        self.threads = ThreadsClient(self.http)
+        self.runs = RunsClient(self.http)
+        self.crons = CronClient(self.http)
+        self.store = StoreClient(self.http)
+
+    async def __aenter__(self) -> LangGraphClient:
+        """Enter the async context manager."""
+        return self
+
+    async def __aexit__(
+        self,
+        exc_type: type[BaseException] | None,
+        exc_val: BaseException | None,
+        exc_tb: TracebackType | None,
+    ) -> None:
+        """Exit the async context manager."""
+        await self.aclose()
+
+    async def aclose(self) -> None:
+        """Close the underlying HTTP client."""
+        if hasattr(self, "http"):
+            await self.http.client.aclose()

libs/sdk-py/langgraph_sdk/_async/cron.py

@@ -0,0 +1,452 @@
+"""Async client for managing recurrent runs (cron jobs) in LangGraph."""
+
+from __future__ import annotations
+
+from collections.abc import Mapping
+from datetime import datetime
+from typing import Any
+
+from langgraph_sdk._async.http import HttpClient
+from langgraph_sdk.schema import (
+    All,
+    Config,
+    Context,
+    Cron,
+    CronSelectField,
+    CronSortBy,
+    Input,
+    OnCompletionBehavior,
+    QueryParamTypes,
+    Run,
+    SortOrder,
+)
+
+
+class CronClient:
+    """Client for managing recurrent runs (cron jobs) in LangGraph.
+
+    A run is a single invocation of an assistant with optional input, config, and context.
+    This client allows scheduling recurring runs to occur automatically.
+
+    ???+ example "Example Usage"
+
+        ```python
+        client = get_client(url="http://localhost:2024"))
+        cron_job = await client.crons.create_for_thread(
+            thread_id="thread_123",
+            assistant_id="asst_456",
+            schedule="0 9 * * *",
+            input={"message": "Daily update"}
+        )
+        ```
+
+    !!! note "Feature Availability"
+
+        The crons client functionality is not supported on all licenses.
+        Please check the relevant license documentation for the most up-to-date
+        details on feature availability.
+    """
+
+    def __init__(self, http_client: HttpClient) -> None:
+        self.http = http_client
+
+    async def create_for_thread(
+        self,
+        thread_id: str,
+        assistant_id: str,
+        *,
+        schedule: str,
+        input: Input | None = None,
+        metadata: Mapping[str, Any] | None = None,
+        config: Config | None = None,
+        context: Context | None = None,
+        checkpoint_during: bool | None = None,
+        interrupt_before: All | list[str] | None = None,
+        interrupt_after: All | list[str] | None = None,
+        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:
+        """Create a cron job for a thread.
+
+        Args:
+            thread_id: the thread ID to run the cron job on.
+            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.
+            context: Static context to add to the assistant.
+                !!! version-added "Added in version 0.6.0"
+            checkpoint_during: Whether to checkpoint during the run (or only at the end/interruption).
+            interrupt_before: Nodes to interrupt immediately before they get executed.
+
+            interrupt_after: Nodes to Nodes to interrupt immediately after they get executed.
+
+            webhook: Webhook to call after LangGraph API call is done.
+            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.
+
+        Returns:
+            The cron run.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            cron_run = await client.crons.create_for_thread(
+                thread_id="my-thread-id",
+                assistant_id="agent",
+                schedule="27 15 * * *",
+                input={"messages": [{"role": "user", "content": "hello!"}]},
+                metadata={"name":"my_run"},
+                context={"model_name": "openai"},
+                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",
+                enabled=True,
+            )
+            ```
+        """
+        payload = {
+            "schedule": schedule,
+            "input": input,
+            "config": config,
+            "metadata": metadata,
+            "context": context,
+            "assistant_id": assistant_id,
+            "checkpoint_during": checkpoint_during,
+            "interrupt_before": interrupt_before,
+            "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
+        payload = {k: v for k, v in payload.items() if v is not None}
+        return await self.http.post(
+            f"/threads/{thread_id}/runs/crons",
+            json=payload,
+            headers=headers,
+            params=params,
+        )
+
+    async def create(
+        self,
+        assistant_id: str,
+        *,
+        schedule: str,
+        input: Input | None = None,
+        metadata: Mapping[str, Any] | None = None,
+        config: Config | None = None,
+        context: Context | None = None,
+        checkpoint_during: bool | None = None,
+        interrupt_before: All | list[str] | None = None,
+        interrupt_after: All | list[str] | None = None,
+        webhook: str | None = None,
+        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:
+        """Create a cron run.
+
+        Args:
+            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.
+            context: Static context to add to the assistant.
+                !!! version-added "Added in version 0.6.0"
+            checkpoint_during: Whether to checkpoint during the run (or only at the end/interruption).
+            interrupt_before: Nodes to interrupt immediately before they get executed.
+            interrupt_after: Nodes to Nodes to interrupt immediately after they get executed.
+            webhook: Webhook to call after LangGraph API call is done.
+            on_run_completed: What to do with the thread after the run completes.
+                Must be one of 'delete' (default) or 'keep'. 'delete' removes the thread
+                after execution. 'keep' creates a new thread for each execution but does not
+                clean them up. Clients are responsible for cleaning up kept threads.
+            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.
+
+        Returns:
+            The cron run.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            cron_run = client.crons.create(
+                assistant_id="agent",
+                schedule="27 15 * * *",
+                input={"messages": [{"role": "user", "content": "hello!"}]},
+                metadata={"name":"my_run"},
+                context={"model_name": "openai"},
+                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",
+                enabled=True,
+            )
+            ```
+
+        """
+        payload = {
+            "schedule": schedule,
+            "input": input,
+            "config": config,
+            "metadata": metadata,
+            "context": context,
+            "assistant_id": assistant_id,
+            "checkpoint_during": checkpoint_during,
+            "interrupt_before": interrupt_before,
+            "interrupt_after": interrupt_after,
+            "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
+        payload = {k: v for k, v in payload.items() if v is not None}
+        return await self.http.post(
+            "/runs/crons", json=payload, headers=headers, params=params
+        )
+
+    async def delete(
+        self,
+        cron_id: str,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> None:
+        """Delete a cron.
+
+        Args:
+            cron_id: The cron ID to delete.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            `None`
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            await client.crons.delete(
+                cron_id="cron_to_delete"
+            )
+            ```
+
+        """
+        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,
+        sort_order: SortOrder | None = None,
+        select: list[CronSelectField] | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> list[Cron]:
+        """Get a list of cron jobs.
+
+        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.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            The list of cron jobs returned by the search,
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            cron_jobs = await client.crons.search(
+                assistant_id="my_assistant_id",
+                thread_id="my_thread_id",
+                enabled=True,
+                limit=5,
+                offset=5,
+            )
+            print(cron_jobs)
+            ```
+            ```shell
+
+            ----------------------------------------------------------
+
+            [
+                {
+                    'cron_id': '1ef3cefa-4c09-6926-96d0-3dc97fd5e39b',
+                    'assistant_id': 'my_assistant_id',
+                    'thread_id': 'my_thread_id',
+                    'user_id': None,
+                    'payload':
+                        {
+                            'input': {'start_time': ''},
+                            'schedule': '4 * * * *',
+                            'assistant_id': 'my_assistant_id'
+                        },
+                    'schedule': '4 * * * *',
+                    'next_run_date': '2024-07-25T17:04:00+00:00',
+                    'end_time': None,
+                    'created_at': '2024-07-08T06:02:23.073257+00:00',
+                    'updated_at': '2024-07-08T06:02:23.073257+00:00'
+                }
+            ]
+            ```
+
+        """
+        payload = {
+            "assistant_id": assistant_id,
+            "thread_id": thread_id,
+            "enabled": enabled,
+            "limit": limit,
+            "offset": offset,
+        }
+        if sort_by:
+            payload["sort_by"] = sort_by
+        if sort_order:
+            payload["sort_order"] = sort_order
+        if select:
+            payload["select"] = select
+        payload = {k: v for k, v in payload.items() if v is not None}
+        return await self.http.post(
+            "/runs/crons/search", json=payload, headers=headers, params=params
+        )
+
+    async def count(
+        self,
+        *,
+        assistant_id: str | None = None,
+        thread_id: str | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> int:
+        """Count cron jobs matching filters.
+
+        Args:
+            assistant_id: Assistant ID to filter by.
+            thread_id: Thread ID to filter by.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            int: Number of crons matching the criteria.
+        """
+        payload: dict[str, Any] = {}
+        if assistant_id:
+            payload["assistant_id"] = assistant_id
+        if thread_id:
+            payload["thread_id"] = thread_id
+        return await self.http.post(
+            "/runs/crons/count", json=payload, headers=headers, params=params
+        )

libs/sdk-py/langgraph_sdk/_async/http.py

@@ -0,0 +1,305 @@
+"""HTTP client for async operations."""
+
+from __future__ import annotations
+
+import asyncio
+import logging
+import sys
+import warnings
+from collections.abc import AsyncIterator, Callable, Mapping
+from typing import Any, cast
+
+import httpx
+import orjson
+
+from langgraph_sdk._shared.utilities import _orjson_default
+from langgraph_sdk.errors import _araise_for_status_typed
+from langgraph_sdk.schema import QueryParamTypes, StreamPart
+from langgraph_sdk.sse import SSEDecoder, aiter_lines_raw
+
+logger = logging.getLogger(__name__)
+
+
+class HttpClient:
+    """Handle async requests to the LangGraph API.
+
+    Adds additional error messaging & content handling above the
+    provided httpx client.
+
+    Attributes:
+        client (httpx.AsyncClient): Underlying HTTPX async client.
+    """
+
+    def __init__(self, client: httpx.AsyncClient) -> None:
+        self.client = client
+
+    async def get(
+        self,
+        path: str,
+        *,
+        params: QueryParamTypes | None = None,
+        headers: Mapping[str, str] | None = None,
+        on_response: Callable[[httpx.Response], None] | None = None,
+    ) -> Any:
+        """Send a `GET` request."""
+        r = await self.client.get(path, params=params, headers=headers)
+        if on_response:
+            on_response(r)
+        await _araise_for_status_typed(r)
+        return await _adecode_json(r)
+
+    async def post(
+        self,
+        path: str,
+        *,
+        json: dict[str, Any] | list | None,
+        params: QueryParamTypes | None = None,
+        headers: Mapping[str, str] | None = None,
+        on_response: Callable[[httpx.Response], None] | None = None,
+    ) -> Any:
+        """Send a `POST` request."""
+        if json is not None:
+            request_headers, content = await _aencode_json(json)
+        else:
+            request_headers, content = {}, b""
+        # Merge headers, with runtime headers taking precedence
+        if headers:
+            request_headers.update(headers)
+        r = await self.client.post(
+            path, headers=request_headers, content=content, params=params
+        )
+        if on_response:
+            on_response(r)
+        await _araise_for_status_typed(r)
+        return await _adecode_json(r)
+
+    async def put(
+        self,
+        path: str,
+        *,
+        json: dict,
+        params: QueryParamTypes | None = None,
+        headers: Mapping[str, str] | None = None,
+        on_response: Callable[[httpx.Response], None] | None = None,
+    ) -> Any:
+        """Send a `PUT` request."""
+        request_headers, content = await _aencode_json(json)
+        if headers:
+            request_headers.update(headers)
+        r = await self.client.put(
+            path, headers=request_headers, content=content, params=params
+        )
+        if on_response:
+            on_response(r)
+        await _araise_for_status_typed(r)
+        return await _adecode_json(r)
+
+    async def patch(
+        self,
+        path: str,
+        *,
+        json: dict,
+        params: QueryParamTypes | None = None,
+        headers: Mapping[str, str] | None = None,
+        on_response: Callable[[httpx.Response], None] | None = None,
+    ) -> Any:
+        """Send a `PATCH` request."""
+        request_headers, content = await _aencode_json(json)
+        if headers:
+            request_headers.update(headers)
+        r = await self.client.patch(
+            path, headers=request_headers, content=content, params=params
+        )
+        if on_response:
+            on_response(r)
+        await _araise_for_status_typed(r)
+        return await _adecode_json(r)
+
+    async def delete(
+        self,
+        path: str,
+        *,
+        json: Any | None = None,
+        params: QueryParamTypes | None = None,
+        headers: Mapping[str, str] | None = None,
+        on_response: Callable[[httpx.Response], None] | None = None,
+    ) -> None:
+        """Send a `DELETE` request."""
+        r = await self.client.request(
+            "DELETE", path, json=json, params=params, headers=headers
+        )
+        if on_response:
+            on_response(r)
+        await _araise_for_status_typed(r)
+
+    async def request_reconnect(
+        self,
+        path: str,
+        method: str,
+        *,
+        json: dict[str, Any] | None = None,
+        params: QueryParamTypes | None = None,
+        headers: Mapping[str, str] | None = None,
+        on_response: Callable[[httpx.Response], None] | None = None,
+        reconnect_limit: int = 5,
+    ) -> Any:
+        """Send a request that automatically reconnects to Location header."""
+        request_headers, content = await _aencode_json(json)
+        if headers:
+            request_headers.update(headers)
+        async with self.client.stream(
+            method, path, headers=request_headers, content=content, params=params
+        ) as r:
+            if on_response:
+                on_response(r)
+            try:
+                r.raise_for_status()
+            except httpx.HTTPStatusError as e:
+                body = (await r.aread()).decode()
+                if sys.version_info >= (3, 11):
+                    e.add_note(body)
+                else:
+                    logger.error(f"Error from langgraph-api: {body}", exc_info=e)
+                raise e
+            loc = r.headers.get("location")
+            if reconnect_limit <= 0 or not loc:
+                return await _adecode_json(r)
+            try:
+                return await _adecode_json(r)
+            except httpx.HTTPError:
+                warnings.warn(
+                    f"Request failed, attempting reconnect to Location: {loc}",
+                    stacklevel=2,
+                )
+                await r.aclose()
+                return await self.request_reconnect(
+                    loc,
+                    "GET",
+                    headers=request_headers,
+                    # don't pass on_response so it's only called once
+                    reconnect_limit=reconnect_limit - 1,
+                )
+
+    async def stream(
+        self,
+        path: str,
+        method: str,
+        *,
+        json: dict[str, Any] | None = None,
+        params: QueryParamTypes | None = None,
+        headers: Mapping[str, str] | None = None,
+        on_response: Callable[[httpx.Response], None] | None = None,
+    ) -> AsyncIterator[StreamPart]:
+        """Stream results using SSE."""
+        request_headers, content = await _aencode_json(json)
+        request_headers["Accept"] = "text/event-stream"
+        request_headers["Cache-Control"] = "no-store"
+        # Add runtime headers with precedence
+        if headers:
+            request_headers.update(headers)
+
+        reconnect_headers = {
+            key: value
+            for key, value in request_headers.items()
+            if key.lower() not in {"content-length", "content-type"}
+        }
+
+        last_event_id: str | None = None
+        reconnect_path: str | None = None
+        reconnect_attempts = 0
+        max_reconnect_attempts = 5
+
+        while True:
+            current_headers = dict(
+                request_headers if reconnect_path is None else reconnect_headers
+            )
+            if last_event_id is not None:
+                current_headers["Last-Event-ID"] = last_event_id
+
+            current_method = method if reconnect_path is None else "GET"
+            current_content = content if reconnect_path is None else None
+            current_params = params if reconnect_path is None else None
+
+            retry = False
+            async with self.client.stream(
+                current_method,
+                reconnect_path or path,
+                headers=current_headers,
+                content=current_content,
+                params=current_params,
+            ) as res:
+                if reconnect_path is None and on_response:
+                    on_response(res)
+                # check status
+                await _araise_for_status_typed(res)
+                # check content type
+                content_type = res.headers.get("content-type", "").partition(";")[0]
+                if "text/event-stream" not in content_type:
+                    raise httpx.TransportError(
+                        "Expected response header Content-Type to contain 'text/event-stream', "
+                        f"got {content_type!r}"
+                    )
+
+                reconnect_location = res.headers.get("location")
+                if reconnect_location:
+                    reconnect_path = reconnect_location
+
+                # parse SSE
+                decoder = SSEDecoder()
+                try:
+                    async for line in aiter_lines_raw(res):
+                        sse = decoder.decode(line=cast("bytes", line).rstrip(b"\n"))
+                        if sse is not None:
+                            if decoder.last_event_id is not None:
+                                last_event_id = decoder.last_event_id
+                            if sse.event or sse.data is not None:
+                                yield sse
+                except httpx.HTTPError:
+                    # httpx.TransportError inherits from HTTPError, so transient
+                    # disconnects during streaming land here.
+                    if reconnect_path is None:
+                        raise
+                    retry = True
+                else:
+                    if sse := decoder.decode(b""):
+                        if decoder.last_event_id is not None:
+                            last_event_id = decoder.last_event_id
+                        if sse.event or sse.data is not None:
+                            # decoder.decode(b"") flushes the in-flight event and may
+                            # return an empty placeholder when there is no pending
+                            # message. Skip these no-op events so the stream doesn't
+                            # emit a trailing blank item after reconnects.
+                            yield sse
+            if retry:
+                reconnect_attempts += 1
+                if reconnect_attempts > max_reconnect_attempts:
+                    raise httpx.TransportError(
+                        "Exceeded maximum SSE reconnection attempts"
+                    )
+                continue
+            break
+
+
+async def _aencode_json(json: Any) -> tuple[dict[str, str], bytes | None]:
+    if json is None:
+        return {}, None
+    body = await asyncio.get_running_loop().run_in_executor(
+        None,
+        orjson.dumps,
+        json,
+        _orjson_default,
+        orjson.OPT_SERIALIZE_NUMPY | orjson.OPT_NON_STR_KEYS,
+    )
+    content_length = str(len(body))
+    content_type = "application/json"
+    headers = {"Content-Length": content_length, "Content-Type": content_type}
+    return headers, body
+
+
+async def _adecode_json(r: httpx.Response) -> Any:
+    body = await r.aread()
+    return (
+        await asyncio.get_running_loop().run_in_executor(None, orjson.loads, body)
+        if body
+        else None
+    )

libs/sdk-py/langgraph_sdk/_async/store.py

@@ -0,0 +1,313 @@
+"""Async Store client for LangGraph SDK."""
+
+from __future__ import annotations
+
+from collections.abc import Mapping, Sequence
+from typing import Any, Literal
+
+from langgraph_sdk._async.http import HttpClient
+from langgraph_sdk._shared.utilities import _provided_vals
+from langgraph_sdk.schema import (
+    Item,
+    ListNamespaceResponse,
+    QueryParamTypes,
+    SearchItemsResponse,
+)
+
+
+class StoreClient:
+    """Client for interacting with the graph's shared storage.
+
+    The Store provides a key-value storage system for persisting data across graph executions,
+    allowing for stateful operations and data sharing across threads.
+
+    ???+ example "Example"
+
+        ```python
+        client = get_client(url="http://localhost:2024")
+        await client.store.put_item(["users", "user123"], "mem-123451342", {"name": "Alice", "score": 100})
+        ```
+    """
+
+    def __init__(self, http: HttpClient) -> None:
+        self.http = http
+
+    async def put_item(
+        self,
+        namespace: Sequence[str],
+        /,
+        key: str,
+        value: Mapping[str, Any],
+        index: Literal[False] | list[str] | None = None,
+        ttl: int | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> None:
+        """Store or update an item.
+
+        Args:
+            namespace: A list of strings representing the namespace path.
+            key: The unique identifier for the item within the namespace.
+            value: A dictionary containing the item's data.
+            index: Controls search indexing - None (use defaults), False (disable), or list of field paths to index.
+            ttl: Optional time-to-live in minutes for the item, or None for no expiration.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            `None`
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            await client.store.put_item(
+                ["documents", "user123"],
+                key="item456",
+                value={"title": "My Document", "content": "Hello World"}
+            )
+            ```
+        """
+        for label in namespace:
+            if "." in label:
+                raise ValueError(
+                    f"Invalid namespace label '{label}'. Namespace labels cannot contain periods ('.')."
+                )
+        payload = {
+            "namespace": namespace,
+            "key": key,
+            "value": value,
+            "index": index,
+            "ttl": ttl,
+        }
+        await self.http.put(
+            "/store/items", json=_provided_vals(payload), headers=headers, params=params
+        )
+
+    async def get_item(
+        self,
+        namespace: Sequence[str],
+        /,
+        key: str,
+        *,
+        refresh_ttl: bool | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Item:
+        """Retrieve a single item.
+
+        Args:
+            key: The unique identifier for the item.
+            namespace: Optional list of strings representing the namespace path.
+            refresh_ttl: Whether to refresh the TTL on this read operation. If `None`, uses the store's default behavior.
+
+        Returns:
+            Item: The retrieved item.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            item = await client.store.get_item(
+                ["documents", "user123"],
+                key="item456",
+            )
+            print(item)
+            ```
+            ```shell
+
+            ----------------------------------------------------------------
+
+            {
+                'namespace': ['documents', 'user123'],
+                'key': 'item456',
+                'value': {'title': 'My Document', 'content': 'Hello World'},
+                'created_at': '2024-07-30T12:00:00Z',
+                'updated_at': '2024-07-30T12:00:00Z'
+            }
+            ```
+        """
+        for label in namespace:
+            if "." in label:
+                raise ValueError(
+                    f"Invalid namespace label '{label}'. Namespace labels cannot contain periods ('.')."
+                )
+        get_params = {"namespace": ".".join(namespace), "key": key}
+        if refresh_ttl is not None:
+            get_params["refresh_ttl"] = refresh_ttl
+        if params:
+            get_params = {**get_params, **params}
+        return await self.http.get("/store/items", params=get_params, headers=headers)
+
+    async def delete_item(
+        self,
+        namespace: Sequence[str],
+        /,
+        key: str,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> None:
+        """Delete an item.
+
+        Args:
+            key: The unique identifier for the item.
+            namespace: Optional list of strings representing the namespace path.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            `None`
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            await client.store.delete_item(
+                ["documents", "user123"],
+                key="item456",
+            )
+            ```
+        """
+        await self.http.delete(
+            "/store/items",
+            json={"namespace": namespace, "key": key},
+            headers=headers,
+            params=params,
+        )
+
+    async def search_items(
+        self,
+        namespace_prefix: Sequence[str],
+        /,
+        filter: Mapping[str, Any] | None = None,
+        limit: int = 10,
+        offset: int = 0,
+        query: str | None = None,
+        refresh_ttl: bool | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> SearchItemsResponse:
+        """Search for items within a namespace prefix.
+
+        Args:
+            namespace_prefix: List of strings representing the namespace prefix.
+            filter: Optional dictionary of key-value pairs to filter results.
+            limit: Maximum number of items to return (default is 10).
+            offset: Number of items to skip before returning results (default is 0).
+            query: Optional query for natural language search.
+            refresh_ttl: Whether to refresh the TTL on items returned by this search. If `None`, uses the store's default behavior.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            A list of items matching the search criteria.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            items = await client.store.search_items(
+                ["documents"],
+                filter={"author": "John Doe"},
+                limit=5,
+                offset=0
+            )
+            print(items)
+            ```
+            ```shell
+
+            ----------------------------------------------------------------
+
+            {
+                "items": [
+                    {
+                        "namespace": ["documents", "user123"],
+                        "key": "item789",
+                        "value": {
+                            "title": "Another Document",
+                            "author": "John Doe"
+                        },
+                        "created_at": "2024-07-30T12:00:00Z",
+                        "updated_at": "2024-07-30T12:00:00Z"
+                    },
+                    # ... additional items ...
+                ]
+            }
+            ```
+        """
+        payload = {
+            "namespace_prefix": namespace_prefix,
+            "filter": filter,
+            "limit": limit,
+            "offset": offset,
+            "query": query,
+            "refresh_ttl": refresh_ttl,
+        }
+
+        return await self.http.post(
+            "/store/items/search",
+            json=_provided_vals(payload),
+            headers=headers,
+            params=params,
+        )
+
+    async def list_namespaces(
+        self,
+        prefix: list[str] | None = None,
+        suffix: list[str] | None = None,
+        max_depth: int | None = None,
+        limit: int = 100,
+        offset: int = 0,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> ListNamespaceResponse:
+        """List namespaces with optional match conditions.
+
+        Args:
+            prefix: Optional list of strings representing the prefix to filter namespaces.
+            suffix: Optional list of strings representing the suffix to filter namespaces.
+            max_depth: Optional integer specifying the maximum depth of namespaces to return.
+            limit: Maximum number of namespaces to return (default is 100).
+            offset: Number of namespaces to skip before returning results (default is 0).
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            A list of namespaces matching the criteria.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            namespaces = await client.store.list_namespaces(
+                prefix=["documents"],
+                max_depth=3,
+                limit=10,
+                offset=0
+            )
+            print(namespaces)
+
+            ----------------------------------------------------------------
+
+            [
+                ["documents", "user123", "reports"],
+                ["documents", "user456", "invoices"],
+                ...
+            ]
+            ```
+        """
+        payload = {
+            "prefix": prefix,
+            "suffix": suffix,
+            "max_depth": max_depth,
+            "limit": limit,
+            "offset": offset,
+        }
+        return await self.http.post(
+            "/store/namespaces",
+            json=_provided_vals(payload),
+            headers=headers,
+            params=params,
+        )

libs/sdk-py/langgraph_sdk/_async/threads.py

@@ -0,0 +1,722 @@
+"""Async client for managing threads in LangGraph."""
+
+from __future__ import annotations
+
+from collections.abc import AsyncIterator, Mapping, Sequence
+from typing import Any
+
+from langgraph_sdk._async.http import HttpClient
+from langgraph_sdk.schema import (
+    Checkpoint,
+    Json,
+    OnConflictBehavior,
+    PruneStrategy,
+    QueryParamTypes,
+    SortOrder,
+    StreamPart,
+    Thread,
+    ThreadSelectField,
+    ThreadSortBy,
+    ThreadState,
+    ThreadStatus,
+    ThreadStreamMode,
+    ThreadUpdateStateResponse,
+)
+
+
+class ThreadsClient:
+    """Client for managing threads in LangGraph.
+
+    A thread maintains the state of a graph across multiple interactions/invocations (aka runs).
+    It accumulates and persists the graph's state, allowing for continuity between separate
+    invocations of the graph.
+
+    ???+ example "Example"
+
+        ```python
+        client = get_client(url="http://localhost:2024"))
+        new_thread = await client.threads.create(metadata={"user_id": "123"})
+        ```
+    """
+
+    def __init__(self, http: HttpClient) -> None:
+        self.http = http
+
+    async def get(
+        self,
+        thread_id: str,
+        *,
+        include: Sequence[str] | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Thread:
+        """Get a thread by ID.
+
+        Args:
+            thread_id: The ID of the thread to get.
+            include: Additional fields to include in the response.
+                Supported values: `"ttl"`.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            Thread object.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            thread = await client.threads.get(
+                thread_id="my_thread_id"
+            )
+            print(thread)
+            ```
+
+            ```shell
+            -----------------------------------------------------
+
+            {
+                'thread_id': 'my_thread_id',
+                'created_at': '2024-07-18T18:35:15.540834+00:00',
+                'updated_at': '2024-07-18T18:35:15.540834+00:00',
+                'metadata': {'graph_id': 'agent'}
+            }
+            ```
+
+        """
+        query_params: dict[str, Any] = {}
+        if include:
+            query_params["include"] = ",".join(include)
+        if params:
+            query_params.update(params)
+        return await self.http.get(
+            f"/threads/{thread_id}",
+            headers=headers,
+            params=query_params or None,
+        )
+
+    async def create(
+        self,
+        *,
+        metadata: Json = None,
+        thread_id: str | None = None,
+        if_exists: OnConflictBehavior | None = None,
+        supersteps: Sequence[dict[str, Sequence[dict[str, Any]]]] | None = None,
+        graph_id: str | None = None,
+        ttl: int | Mapping[str, Any] | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Thread:
+        """Create a new thread.
+
+        Args:
+            metadata: Metadata to add to thread.
+            thread_id: ID of thread.
+                If `None`, ID will be a randomly generated UUID.
+            if_exists: How to handle duplicate creation. Defaults to 'raise' under the hood.
+                Must be either 'raise' (raise error if duplicate), or 'do_nothing' (return existing thread).
+            supersteps: Apply a list of supersteps when creating a thread, each containing a sequence of updates.
+                Each update has `values` or `command` and `as_node`. Used for copying a thread between deployments.
+            graph_id: Optional graph ID to associate with the thread.
+            ttl: Optional time-to-live in minutes for the thread. You can pass an
+                integer (minutes) or a mapping with keys `ttl` and optional
+                `strategy` (defaults to "delete").
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            The created thread.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            thread = await client.threads.create(
+                metadata={"number":1},
+                thread_id="my-thread-id",
+                if_exists="raise"
+            )
+            ```
+        """
+        payload: dict[str, Any] = {}
+        if thread_id:
+            payload["thread_id"] = thread_id
+        if metadata or graph_id:
+            payload["metadata"] = {
+                **(metadata or {}),
+                **({"graph_id": graph_id} if graph_id else {}),
+            }
+        if if_exists:
+            payload["if_exists"] = if_exists
+        if supersteps:
+            payload["supersteps"] = [
+                {
+                    "updates": [
+                        {
+                            "values": u["values"],
+                            "command": u.get("command"),
+                            "as_node": u["as_node"],
+                        }
+                        for u in s["updates"]
+                    ]
+                }
+                for s in supersteps
+            ]
+        if ttl is not None:
+            if isinstance(ttl, (int, float)):
+                payload["ttl"] = {"ttl": ttl, "strategy": "delete"}
+            else:
+                payload["ttl"] = ttl
+
+        return await self.http.post(
+            "/threads", json=payload, headers=headers, params=params
+        )
+
+    async def update(
+        self,
+        thread_id: str,
+        *,
+        metadata: Mapping[str, Any],
+        ttl: int | Mapping[str, Any] | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Thread:
+        """Update a thread.
+
+        Args:
+            thread_id: ID of thread to update.
+            metadata: Metadata to merge with existing thread metadata.
+            ttl: Optional time-to-live in minutes for the thread. You can pass an
+                integer (minutes) or a mapping with keys `ttl` and optional
+                `strategy` (defaults to "delete").
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            The created thread.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            thread = await client.threads.update(
+                thread_id="my-thread-id",
+                metadata={"number":1},
+                ttl=43_200,
+            )
+            ```
+        """
+        payload: dict[str, Any] = {"metadata": metadata}
+        if ttl is not None:
+            if isinstance(ttl, (int, float)):
+                payload["ttl"] = {"ttl": ttl, "strategy": "delete"}
+            else:
+                payload["ttl"] = ttl
+        return await self.http.patch(
+            f"/threads/{thread_id}",
+            json=payload,
+            headers=headers,
+            params=params,
+        )
+
+    async def delete(
+        self,
+        thread_id: str,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> None:
+        """Delete a thread.
+
+        Args:
+            thread_id: The ID of the thread to delete.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            `None`
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost2024)
+            await client.threads.delete(
+                thread_id="my_thread_id"
+            )
+            ```
+
+        """
+        await self.http.delete(f"/threads/{thread_id}", headers=headers, params=params)
+
+    async def search(
+        self,
+        *,
+        metadata: Json = None,
+        values: Json = None,
+        ids: Sequence[str] | None = None,
+        status: ThreadStatus | None = None,
+        limit: int = 10,
+        offset: int = 0,
+        sort_by: ThreadSortBy | None = None,
+        sort_order: SortOrder | None = None,
+        select: list[ThreadSelectField] | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> list[Thread]:
+        """Search for threads.
+
+        Args:
+            metadata: Thread metadata to filter on.
+            values: State values to filter on.
+            ids: List of thread IDs to filter by.
+            status: Thread status to filter on.
+                Must be one of 'idle', 'busy', 'interrupted' or 'error'.
+            limit: Limit on number of threads to return.
+            offset: Offset in threads table to start search from.
+            sort_by: Sort by field.
+            sort_order: Sort order.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            List of the threads matching the search parameters.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            threads = await client.threads.search(
+                metadata={"number":1},
+                status="interrupted",
+                limit=15,
+                offset=5
+            )
+            ```
+
+        """
+        payload: dict[str, Any] = {
+            "limit": limit,
+            "offset": offset,
+        }
+        if metadata:
+            payload["metadata"] = metadata
+        if values:
+            payload["values"] = values
+        if ids:
+            payload["ids"] = ids
+        if status:
+            payload["status"] = status
+        if sort_by:
+            payload["sort_by"] = sort_by
+        if sort_order:
+            payload["sort_order"] = sort_order
+        if select:
+            payload["select"] = select
+        return await self.http.post(
+            "/threads/search",
+            json=payload,
+            headers=headers,
+            params=params,
+        )
+
+    async def count(
+        self,
+        *,
+        metadata: Json = None,
+        values: Json = None,
+        status: ThreadStatus | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> int:
+        """Count threads matching filters.
+
+        Args:
+            metadata: Thread metadata to filter on.
+            values: State values to filter on.
+            status: Thread status to filter on.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            int: Number of threads matching the criteria.
+        """
+        payload: dict[str, Any] = {}
+        if metadata:
+            payload["metadata"] = metadata
+        if values:
+            payload["values"] = values
+        if status:
+            payload["status"] = status
+        return await self.http.post(
+            "/threads/count", json=payload, headers=headers, params=params
+        )
+
+    async def copy(
+        self,
+        thread_id: str,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> None:
+        """Copy a thread.
+
+        Args:
+            thread_id: The ID of the thread to copy.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            `None`
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024)
+            await client.threads.copy(
+                thread_id="my_thread_id"
+            )
+            ```
+
+        """
+        return await self.http.post(
+            f"/threads/{thread_id}/copy", json=None, headers=headers, params=params
+        )
+
+    async def prune(
+        self,
+        thread_ids: Sequence[str],
+        *,
+        strategy: PruneStrategy = "delete",
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> dict[str, Any]:
+        """Prune threads by ID.
+
+        Args:
+            thread_ids: List of thread IDs to prune.
+            strategy: The prune strategy. `"delete"` removes threads entirely.
+                `"keep_latest"` prunes old checkpoints but keeps threads and their
+                latest state. Defaults to `"delete"`.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            A dict containing `pruned_count` (number of threads pruned).
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            result = await client.threads.prune(
+                thread_ids=["thread_1", "thread_2"],
+            )
+            print(result)  # {'pruned_count': 2}
+            ```
+
+        """
+        payload: dict[str, Any] = {
+            "thread_ids": thread_ids,
+        }
+        if strategy != "delete":
+            payload["strategy"] = strategy
+        return await self.http.post(
+            "/threads/prune", json=payload, headers=headers, params=params
+        )
+
+    async def get_state(
+        self,
+        thread_id: str,
+        checkpoint: Checkpoint | None = None,
+        checkpoint_id: str | None = None,  # deprecated
+        *,
+        subgraphs: bool = False,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> ThreadState:
+        """Get the state of a thread.
+
+        Args:
+            thread_id: The ID of the thread to get the state of.
+            checkpoint: The checkpoint to get the state of.
+            checkpoint_id: (deprecated) The checkpoint ID to get the state of.
+            subgraphs: Include subgraphs states.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            The thread of the state.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024)
+            thread_state = await client.threads.get_state(
+                thread_id="my_thread_id",
+                checkpoint_id="my_checkpoint_id"
+            )
+            print(thread_state)
+            ```
+
+            ```shell
+            ----------------------------------------------------------------------------------------------------------------------------------------------------------------------
+
+            {
+                'values': {
+                    'messages': [
+                        {
+                            'content': 'how are you?',
+                            'additional_kwargs': {},
+                            'response_metadata': {},
+                            'type': 'human',
+                            'name': None,
+                            'id': 'fe0a5778-cfe9-42ee-b807-0adaa1873c10',
+                            'example': False
+                        },
+                        {
+                            'content': "I'm doing well, thanks for asking! I'm an AI assistant created by Anthropic to be helpful, honest, and harmless.",
+                            'additional_kwargs': {},
+                            'response_metadata': {},
+                            'type': 'ai',
+                            'name': None,
+                            'id': 'run-159b782c-b679-4830-83c6-cef87798fe8b',
+                            'example': False,
+                            'tool_calls': [],
+                            'invalid_tool_calls': [],
+                            'usage_metadata': None
+                        }
+                    ]
+                },
+                'next': [],
+                'checkpoint':
+                    {
+                        'thread_id': 'e2496803-ecd5-4e0c-a779-3226296181c2',
+                        'checkpoint_ns': '',
+                        'checkpoint_id': '1ef4a9b8-e6fb-67b1-8001-abd5184439d1'
+                    }
+                'metadata':
+                    {
+                        'step': 1,
+                        'run_id': '1ef4a9b8-d7da-679a-a45a-872054341df2',
+                        'source': 'loop',
+                        'writes':
+                            {
+                                'agent':
+                                    {
+                                        'messages': [
+                                            {
+                                                'id': 'run-159b782c-b679-4830-83c6-cef87798fe8b',
+                                                'name': None,
+                                                'type': 'ai',
+                                                'content': "I'm doing well, thanks for asking! I'm an AI assistant created by Anthropic to be helpful, honest, and harmless.",
+                                                'example': False,
+                                                'tool_calls': [],
+                                                'usage_metadata': None,
+                                                'additional_kwargs': {},
+                                                'response_metadata': {},
+                                                'invalid_tool_calls': []
+                                            }
+                                        ]
+                                    }
+                            },
+                'user_id': None,
+                'graph_id': 'agent',
+                'thread_id': 'e2496803-ecd5-4e0c-a779-3226296181c2',
+                'created_by': 'system',
+                'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca'},
+                'created_at': '2024-07-25T15:35:44.184703+00:00',
+                'parent_config':
+                    {
+                        'thread_id': 'e2496803-ecd5-4e0c-a779-3226296181c2',
+                        'checkpoint_ns': '',
+                        'checkpoint_id': '1ef4a9b8-d80d-6fa7-8000-9300467fad0f'
+                    }
+            }
+            ```
+        """
+        if checkpoint:
+            return await self.http.post(
+                f"/threads/{thread_id}/state/checkpoint",
+                json={"checkpoint": checkpoint, "subgraphs": subgraphs},
+                headers=headers,
+                params=params,
+            )
+        elif checkpoint_id:
+            get_params = {"subgraphs": subgraphs}
+            if params:
+                get_params = {**get_params, **params}
+            return await self.http.get(
+                f"/threads/{thread_id}/state/{checkpoint_id}",
+                params=get_params,
+                headers=headers,
+            )
+        else:
+            get_params = {"subgraphs": subgraphs}
+            if params:
+                get_params = {**get_params, **params}
+            return await self.http.get(
+                f"/threads/{thread_id}/state",
+                params=get_params,
+                headers=headers,
+            )
+
+    async def update_state(
+        self,
+        thread_id: str,
+        values: dict[str, Any] | Sequence[dict] | None,
+        *,
+        as_node: str | None = None,
+        checkpoint: Checkpoint | None = None,
+        checkpoint_id: str | None = None,  # deprecated
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> ThreadUpdateStateResponse:
+        """Update the state of a thread.
+
+        Args:
+            thread_id: The ID of the thread to update.
+            values: The values to update the state with.
+            as_node: Update the state as if this node had just executed.
+            checkpoint: The checkpoint to update the state of.
+            checkpoint_id: (deprecated) The checkpoint ID to update the state of.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            Response after updating a thread's state.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024)
+            response = await client.threads.update_state(
+                thread_id="my_thread_id",
+                values={"messages":[{"role": "user", "content": "hello!"}]},
+                as_node="my_node",
+            )
+            print(response)
+            ```
+            ```shell
+
+            ----------------------------------------------------------------------------------------------------------------------------------------------------------------------
+
+            {
+                'checkpoint': {
+                    'thread_id': 'e2496803-ecd5-4e0c-a779-3226296181c2',
+                    'checkpoint_ns': '',
+                    'checkpoint_id': '1ef4a9b8-e6fb-67b1-8001-abd5184439d1',
+                    'checkpoint_map': {}
+                }
+            }
+            ```
+        """
+        payload: dict[str, Any] = {
+            "values": values,
+        }
+        if checkpoint_id:
+            payload["checkpoint_id"] = checkpoint_id
+        if checkpoint:
+            payload["checkpoint"] = checkpoint
+        if as_node:
+            payload["as_node"] = as_node
+        return await self.http.post(
+            f"/threads/{thread_id}/state", json=payload, headers=headers, params=params
+        )
+
+    async def get_history(
+        self,
+        thread_id: str,
+        *,
+        limit: int = 10,
+        before: str | Checkpoint | None = None,
+        metadata: Mapping[str, Any] | None = None,
+        checkpoint: Checkpoint | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> list[ThreadState]:
+        """Get the state history of a thread.
+
+        Args:
+            thread_id: The ID of the thread to get the state history for.
+            checkpoint: Return states for this subgraph. If empty defaults to root.
+            limit: The maximum number of states to return.
+            before: Return states before this checkpoint.
+            metadata: Filter states by metadata key-value pairs.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            The state history of the thread.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024)
+            thread_state = await client.threads.get_history(
+                thread_id="my_thread_id",
+                limit=5,
+            )
+            ```
+
+        """
+        payload: dict[str, Any] = {
+            "limit": limit,
+        }
+        if before:
+            payload["before"] = before
+        if metadata:
+            payload["metadata"] = metadata
+        if checkpoint:
+            payload["checkpoint"] = checkpoint
+        return await self.http.post(
+            f"/threads/{thread_id}/history",
+            json=payload,
+            headers=headers,
+            params=params,
+        )
+
+    async def join_stream(
+        self,
+        thread_id: str,
+        *,
+        last_event_id: str | None = None,
+        stream_mode: ThreadStreamMode | Sequence[ThreadStreamMode] = "run_modes",
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> AsyncIterator[StreamPart]:
+        """Get a stream of events for a thread.
+
+        Args:
+            thread_id: The ID of the thread to get the stream for.
+            last_event_id: The ID of the last event to get.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            An iterator of stream parts.
+
+        ???+ example "Example Usage"
+
+            ```python
+
+            for chunk in client.threads.join_stream(
+                thread_id="my_thread_id",
+                last_event_id="my_event_id",
+            ):
+                print(chunk)
+            ```
+
+        """
+        query_params = {
+            "stream_mode": stream_mode,
+        }
+        if params:
+            query_params.update(params)
+        return self.http.stream(
+            f"/threads/{thread_id}/stream",
+            "GET",
+            headers={
+                **({"Last-Event-ID": last_event_id} if last_event_id else {}),
+                **(headers or {}),
+            },
+            params=query_params,
+        )

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

@@ -0,0 +1 @@
+"""Shared utilities for async and sync clients."""

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

@@ -0,0 +1,10 @@
+"""Type aliases and constants."""
+
+from __future__ import annotations
+
+TimeoutTypes = (
+    None
+    | float
+    | tuple[float | None, float | None]
+    | tuple[float | None, float | None, float | None, float | None]
+)

libs/sdk-py/langgraph_sdk/_shared/utilities.py

@@ -0,0 +1,131 @@
+"""Shared utility functions for async and sync clients."""
+
+from __future__ import annotations
+
+import functools
+import os
+import re
+from collections.abc import Mapping
+from typing import Any, cast
+
+import httpx
+
+import langgraph_sdk
+from langgraph_sdk.schema import RunCreateMetadata
+
+RESERVED_HEADERS = ("x-api-key",)
+
+NOT_PROVIDED = cast(None, object())
+
+
+def _get_api_key(api_key: str | None = NOT_PROVIDED) -> str | None:
+    """Get the API key from the environment.
+    Precedence:
+        1. explicit string argument
+        2. LANGGRAPH_API_KEY (if api_key not provided)
+        3. LANGSMITH_API_KEY (if api_key not provided)
+        4. LANGCHAIN_API_KEY (if api_key not provided)
+
+    Args:
+        api_key: The API key to use. Can be:
+            - A string: use this exact API key
+            - None: explicitly skip loading from environment
+            - NOT_PROVIDED (default): auto-load from environment variables
+    """
+    if isinstance(api_key, str):
+        return api_key
+    if api_key is NOT_PROVIDED:
+        # api_key is not explicitly provided, try to load from environment
+        for prefix in ["LANGGRAPH", "LANGSMITH", "LANGCHAIN"]:
+            if env := os.getenv(f"{prefix}_API_KEY"):
+                return env.strip().strip('"').strip("'")
+    # api_key is explicitly None, don't load from environment
+    return None
+
+
+def _get_headers(
+    api_key: str | None,
+    custom_headers: Mapping[str, str] | None,
+) -> dict[str, str]:
+    """Combine api_key and custom user-provided headers."""
+    custom_headers = custom_headers or {}
+    for header in RESERVED_HEADERS:
+        if header in custom_headers:
+            raise ValueError(f"Cannot set reserved header '{header}'")
+
+    headers = {
+        "User-Agent": f"langgraph-sdk-py/{langgraph_sdk.__version__}",
+        **custom_headers,
+    }
+    resolved_api_key = _get_api_key(api_key)
+    if resolved_api_key:
+        headers["x-api-key"] = resolved_api_key
+
+    return headers
+
+
+def _orjson_default(obj: Any) -> Any:
+    is_class = isinstance(obj, type)
+    if hasattr(obj, "model_dump") and callable(obj.model_dump):
+        if is_class:
+            raise TypeError(
+                f"Cannot JSON-serialize type object: {obj!r}. Did you mean to pass an instance of the object instead?"
+                f"\nReceived type: {obj!r}"
+            )
+        return obj.model_dump()
+    elif hasattr(obj, "dict") and callable(obj.dict):
+        if is_class:
+            raise TypeError(
+                f"Cannot JSON-serialize type object: {obj!r}. Did you mean to pass an instance of the object instead?"
+                f"\nReceived type: {obj!r}"
+            )
+        return obj.dict()
+    elif isinstance(obj, (set, frozenset)):
+        return list(obj)
+    else:
+        raise TypeError(f"Object of type {type(obj)} is not JSON serializable")
+
+
+# Compiled regex pattern for extracting run metadata from Content-Location header
+_RUN_METADATA_PATTERN = re.compile(
+    r"(\/threads\/(?P<thread_id>.+))?\/runs\/(?P<run_id>.+)"
+)
+
+
+def _get_run_metadata_from_response(
+    response: httpx.Response,
+) -> RunCreateMetadata | None:
+    """Extract run metadata from the response headers."""
+    if (content_location := response.headers.get("Content-Location")) and (
+        match := _RUN_METADATA_PATTERN.search(content_location)
+    ):
+        return RunCreateMetadata(
+            run_id=match.group("run_id"),
+            thread_id=match.group("thread_id") or None,
+        )
+
+    return None
+
+
+def _provided_vals(d: Mapping[str, Any]) -> dict[str, Any]:
+    return {k: v for k, v in d.items() if v is not None}
+
+
+_registered_transports: list[httpx.ASGITransport] = []
+
+
+# Do not move; this is used in the server.
+def configure_loopback_transports(app: Any) -> None:
+    for transport in _registered_transports:
+        transport.app = app
+
+
+@functools.lru_cache(maxsize=1)
+def get_asgi_transport() -> type[httpx.ASGITransport]:
+    try:
+        from langgraph_api import asgi_transport  # type: ignore[unresolved-import]
+
+        return asgi_transport.ASGITransport
+    except ImportError:
+        # Older versions of the server
+        return httpx.ASGITransport

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

@@ -0,0 +1,20 @@
+"""Sync client exports."""
+
+from langgraph_sdk._sync.assistants import SyncAssistantsClient
+from langgraph_sdk._sync.client import SyncLangGraphClient, get_sync_client
+from langgraph_sdk._sync.cron import SyncCronClient
+from langgraph_sdk._sync.http import SyncHttpClient
+from langgraph_sdk._sync.runs import SyncRunsClient
+from langgraph_sdk._sync.store import SyncStoreClient
+from langgraph_sdk._sync.threads import SyncThreadsClient
+
+__all__ = [
+    "SyncAssistantsClient",
+    "SyncCronClient",
+    "SyncHttpClient",
+    "SyncLangGraphClient",
+    "SyncRunsClient",
+    "SyncStoreClient",
+    "SyncThreadsClient",
+    "get_sync_client",
+]

libs/sdk-py/langgraph_sdk/_sync/assistants.py

@@ -0,0 +1,731 @@
+"""Synchronous client for managing assistants in LangGraph."""
+
+from __future__ import annotations
+
+from collections.abc import Mapping
+from typing import Any, Literal, cast, overload
+
+import httpx
+
+from langgraph_sdk._sync.http import SyncHttpClient
+from langgraph_sdk.schema import (
+    Assistant,
+    AssistantSelectField,
+    AssistantSortBy,
+    AssistantsSearchResponse,
+    AssistantVersion,
+    Config,
+    Context,
+    GraphSchema,
+    Json,
+    OnConflictBehavior,
+    QueryParamTypes,
+    SortOrder,
+    Subgraphs,
+)
+
+
+class SyncAssistantsClient:
+    """Client for managing assistants in LangGraph synchronously.
+
+    This class provides methods to interact with assistants, which are versioned configurations of your graph.
+
+    ???+ example "Example"
+
+        ```python
+        client = get_sync_client(url="http://localhost:2024")
+        assistant = client.assistants.get("assistant_id_123")
+        ```
+    """
+
+    def __init__(self, http: SyncHttpClient) -> None:
+        self.http = http
+
+    def get(
+        self,
+        assistant_id: str,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Assistant:
+        """Get an assistant by ID.
+
+        Args:
+            assistant_id: The ID of the assistant to get OR the name of the graph (to use the default assistant).
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            `Assistant` Object.
+
+        ???+ example "Example Usage"
+
+            ```python
+            assistant = client.assistants.get(
+                assistant_id="my_assistant_id"
+            )
+            print(assistant)
+            ```
+
+            ```shell
+            ----------------------------------------------------
+
+            {
+                'assistant_id': 'my_assistant_id',
+                'graph_id': 'agent',
+                'created_at': '2024-06-25T17:10:33.109781+00:00',
+                'updated_at': '2024-06-25T17:10:33.109781+00:00',
+                'config': {},
+                'context': {},
+                'metadata': {'created_by': 'system'}
+            }
+            ```
+
+        """
+        return self.http.get(
+            f"/assistants/{assistant_id}", headers=headers, params=params
+        )
+
+    def get_graph(
+        self,
+        assistant_id: str,
+        *,
+        xray: int | bool = False,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> dict[str, list[dict[str, Any]]]:
+        """Get the graph of an assistant by ID.
+
+        Args:
+            assistant_id: The ID of the assistant to get the graph of.
+            xray: Include graph representation of subgraphs. If an integer value is provided, only subgraphs with a depth less than or equal to the value will be included.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            The graph information for the assistant in JSON format.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:2024")
+            graph_info = client.assistants.get_graph(
+                assistant_id="my_assistant_id"
+            )
+            print(graph_info)
+
+            --------------------------------------------------------------------------------------------------------------------------
+
+            {
+                'nodes':
+                    [
+                        {'id': '__start__', 'type': 'schema', 'data': '__start__'},
+                        {'id': '__end__', 'type': 'schema', 'data': '__end__'},
+                        {'id': 'agent','type': 'runnable','data': {'id': ['langgraph', 'utils', 'RunnableCallable'],'name': 'agent'}},
+                    ],
+                'edges':
+                    [
+                        {'source': '__start__', 'target': 'agent'},
+                        {'source': 'agent','target': '__end__'}
+                    ]
+            }
+            ```
+
+        """
+        query_params = {"xray": xray}
+        if params:
+            query_params.update(params)
+        return self.http.get(
+            f"/assistants/{assistant_id}/graph", params=query_params, headers=headers
+        )
+
+    def get_schemas(
+        self,
+        assistant_id: str,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> GraphSchema:
+        """Get the schemas of an assistant by ID.
+
+        Args:
+            assistant_id: The ID of the assistant to get the schema of.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            GraphSchema: The graph schema for the assistant.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:2024")
+            schema = client.assistants.get_schemas(
+                assistant_id="my_assistant_id"
+            )
+            print(schema)
+            ```
+            ```shell
+            ----------------------------------------------------------------------------------------------------------------------------
+
+            {
+                'graph_id': 'agent',
+                'state_schema':
+                    {
+                        'title': 'LangGraphInput',
+                        '$ref': '#/definitions/AgentState',
+                        'definitions':
+                            {
+                                'BaseMessage':
+                                    {
+                                        'title': 'BaseMessage',
+                                        'description': 'Base abstract Message class. Messages are the inputs and outputs of ChatModels.',
+                                        'type': 'object',
+                                        'properties':
+                                            {
+                                             'content':
+                                                {
+                                                    'title': 'Content',
+                                                    'anyOf': [
+                                                        {'type': 'string'},
+                                                        {'type': 'array','items': {'anyOf': [{'type': 'string'}, {'type': 'object'}]}}
+                                                    ]
+                                                },
+                                            'additional_kwargs':
+                                                {
+                                                    'title': 'Additional Kwargs',
+                                                    'type': 'object'
+                                                },
+                                            'response_metadata':
+                                                {
+                                                    'title': 'Response Metadata',
+                                                    'type': 'object'
+                                                },
+                                            'type':
+                                                {
+                                                    'title': 'Type',
+                                                    'type': 'string'
+                                                },
+                                            'name':
+                                                {
+                                                    'title': 'Name',
+                                                    'type': 'string'
+                                                },
+                                            'id':
+                                                {
+                                                    'title': 'Id',
+                                                    'type': 'string'
+                                                }
+                                            },
+                                        'required': ['content', 'type']
+                                    },
+                                'AgentState':
+                                    {
+                                        'title': 'AgentState',
+                                        'type': 'object',
+                                        'properties':
+                                            {
+                                                'messages':
+                                                    {
+                                                        'title': 'Messages',
+                                                        'type': 'array',
+                                                        'items': {'$ref': '#/definitions/BaseMessage'}
+                                                    }
+                                            },
+                                        'required': ['messages']
+                                    }
+                            }
+                    },
+                'config_schema':
+                    {
+                        'title': 'Configurable',
+                        'type': 'object',
+                        'properties':
+                            {
+                                'model_name':
+                                    {
+                                        'title': 'Model Name',
+                                        'enum': ['anthropic', 'openai'],
+                                        'type': 'string'
+                                    }
+                            }
+                    },
+                'context_schema':
+                    {
+                        'title': 'Context',
+                        'type': 'object',
+                        'properties':
+                            {
+                                'model_name':
+                                    {
+                                        'title': 'Model Name',
+                                        'enum': ['anthropic', 'openai'],
+                                        'type': 'string'
+                                    }
+                            }
+                    }
+            }
+            ```
+
+        """
+        return self.http.get(
+            f"/assistants/{assistant_id}/schemas", headers=headers, params=params
+        )
+
+    def get_subgraphs(
+        self,
+        assistant_id: str,
+        namespace: str | None = None,
+        recurse: bool = False,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Subgraphs:
+        """Get the schemas of an assistant by ID.
+
+        Args:
+            assistant_id: The ID of the assistant to get the schema of.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            Subgraphs: The graph schema for the assistant.
+
+        """
+        get_params = {"recurse": recurse}
+        if params:
+            get_params = {**get_params, **params}
+        if namespace is not None:
+            return self.http.get(
+                f"/assistants/{assistant_id}/subgraphs/{namespace}",
+                params=get_params,
+                headers=headers,
+            )
+        else:
+            return self.http.get(
+                f"/assistants/{assistant_id}/subgraphs",
+                params=get_params,
+                headers=headers,
+            )
+
+    def create(
+        self,
+        graph_id: str | None,
+        config: Config | None = None,
+        *,
+        context: Context | None = None,
+        metadata: Json = None,
+        assistant_id: str | None = None,
+        if_exists: OnConflictBehavior | None = None,
+        name: str | None = None,
+        headers: Mapping[str, str] | None = None,
+        description: str | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Assistant:
+        """Create a new assistant.
+
+        Useful when graph is configurable and you want to create different assistants based on different configurations.
+
+        Args:
+            graph_id: The ID of the graph the assistant should use. The graph ID is normally set in your langgraph.json configuration.
+            config: Configuration to use for the graph.
+            context: Static context to add to the assistant.
+                !!! version-added "Added in version 0.6.0"
+            metadata: Metadata to add to assistant.
+            assistant_id: Assistant ID to use, will default to a random UUID if not provided.
+            if_exists: How to handle duplicate creation. Defaults to 'raise' under the hood.
+                Must be either 'raise' (raise error if duplicate), or 'do_nothing' (return existing assistant).
+            name: The name of the assistant. Defaults to 'Untitled' under the hood.
+            headers: Optional custom headers to include with the request.
+            description: Optional description of the assistant.
+                The description field is available for langgraph-api server version>=0.0.45
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            The created assistant.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:2024")
+            assistant = client.assistants.create(
+                graph_id="agent",
+                context={"model_name": "openai"},
+                metadata={"number":1},
+                assistant_id="my-assistant-id",
+                if_exists="do_nothing",
+                name="my_name"
+            )
+            ```
+        """
+        payload: dict[str, Any] = {
+            "graph_id": graph_id,
+        }
+        if config:
+            payload["config"] = config
+        if context:
+            payload["context"] = context
+        if metadata:
+            payload["metadata"] = metadata
+        if assistant_id:
+            payload["assistant_id"] = assistant_id
+        if if_exists:
+            payload["if_exists"] = if_exists
+        if name:
+            payload["name"] = name
+        if description:
+            payload["description"] = description
+        return self.http.post(
+            "/assistants", json=payload, headers=headers, params=params
+        )
+
+    def update(
+        self,
+        assistant_id: str,
+        *,
+        graph_id: str | None = None,
+        config: Config | None = None,
+        context: Context | None = None,
+        metadata: Json = None,
+        name: str | None = None,
+        headers: Mapping[str, str] | None = None,
+        description: str | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Assistant:
+        """Update an assistant.
+
+        Use this to point to a different graph, update the configuration, or change the metadata of an assistant.
+
+        Args:
+            assistant_id: Assistant to update.
+            graph_id: The ID of the graph the assistant should use.
+                The graph ID is normally set in your langgraph.json configuration. If `None`, assistant will keep pointing to same graph.
+            config: Configuration to use for the graph.
+            context: Static context to add to the assistant.
+                !!! version-added "Added in version 0.6.0"
+            metadata: Metadata to merge with existing assistant metadata.
+            name: The new name for the assistant.
+            headers: Optional custom headers to include with the request.
+            description: Optional description of the assistant.
+                The description field is available for langgraph-api server version>=0.0.45
+
+        Returns:
+            The updated assistant.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:2024")
+            assistant = client.assistants.update(
+                assistant_id='e280dad7-8618-443f-87f1-8e41841c180f',
+                graph_id="other-graph",
+                context={"model_name": "anthropic"},
+                metadata={"number":2}
+            )
+            ```
+        """
+        payload: dict[str, Any] = {}
+        if graph_id:
+            payload["graph_id"] = graph_id
+        if config:
+            payload["config"] = config
+        if context:
+            payload["context"] = context
+        if metadata:
+            payload["metadata"] = metadata
+        if name:
+            payload["name"] = name
+        if description:
+            payload["description"] = description
+        return self.http.patch(
+            f"/assistants/{assistant_id}",
+            json=payload,
+            headers=headers,
+            params=params,
+        )
+
+    def delete(
+        self,
+        assistant_id: str,
+        *,
+        delete_threads: bool = False,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> None:
+        """Delete an assistant.
+
+        Args:
+            assistant_id: The assistant ID to delete.
+            delete_threads: If true, delete all threads with `metadata.assistant_id`
+                matching this assistant, along with runs and checkpoints belonging to
+                those threads.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            `None`
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:2024")
+            client.assistants.delete(
+                assistant_id="my_assistant_id"
+            )
+            ```
+
+        """
+        query_params: dict[str, Any] = {}
+        if delete_threads:
+            query_params["delete_threads"] = True
+        if params:
+            query_params.update(params)
+        self.http.delete(
+            f"/assistants/{assistant_id}",
+            headers=headers,
+            params=query_params or None,
+        )
+
+    @overload
+    def search(
+        self,
+        *,
+        metadata: Json = None,
+        graph_id: str | None = None,
+        name: str | None = None,
+        limit: int = 10,
+        offset: int = 0,
+        sort_by: AssistantSortBy | None = None,
+        sort_order: SortOrder | None = None,
+        select: list[AssistantSelectField] | None = None,
+        response_format: Literal["object"],
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> AssistantsSearchResponse: ...
+
+    @overload
+    def search(
+        self,
+        *,
+        metadata: Json = None,
+        graph_id: str | None = None,
+        name: str | None = None,
+        limit: int = 10,
+        offset: int = 0,
+        sort_by: AssistantSortBy | None = None,
+        sort_order: SortOrder | None = None,
+        select: list[AssistantSelectField] | None = None,
+        response_format: Literal["array"] = "array",
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> list[Assistant]: ...
+
+    def search(
+        self,
+        *,
+        metadata: Json = None,
+        graph_id: str | None = None,
+        name: str | None = None,
+        limit: int = 10,
+        offset: int = 0,
+        sort_by: AssistantSortBy | None = None,
+        sort_order: SortOrder | None = None,
+        select: list[AssistantSelectField] | None = None,
+        response_format: Literal["array", "object"] = "array",
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> AssistantsSearchResponse | list[Assistant]:
+        """Search for assistants.
+
+        Args:
+            metadata: Metadata to filter by. Exact match filter for each KV pair.
+            graph_id: The ID of the graph to filter by.
+                The graph ID is normally set in your langgraph.json configuration.
+            name: The name of the assistant to filter by.
+                The filtering logic will match assistants where 'name' is a substring (case insensitive) of the assistant name.
+            limit: The maximum number of results to return.
+            offset: The number of results to skip.
+            sort_by: The field to sort by.
+            sort_order: The order to sort by.
+            select: Specific assistant fields to include in the response.
+            response_format: Controls the response shape. Use `"array"` (default)
+                to return a bare list of assistants, or `"object"` to return
+                a mapping containing assistants plus pagination metadata.
+                Defaults to "array", though this default will be changed to "object" in a future release.
+            headers: Optional custom headers to include with the request.
+
+        Returns:
+            A list of assistants (when `response_format="array"`) or a mapping
+            with the assistants and the next pagination cursor (when
+            `response_format="object"`).
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:2024")
+            response = client.assistants.search(
+                metadata = {"name":"my_name"},
+                graph_id="my_graph_id",
+                limit=5,
+                offset=5,
+                response_format="object",
+            )
+            assistants = response["assistants"]
+            next_cursor = response["next"]
+            ```
+        """
+        if response_format not in ("array", "object"):
+            raise ValueError("response_format must be 'array' or 'object'")
+        payload: dict[str, Any] = {
+            "limit": limit,
+            "offset": offset,
+        }
+        if metadata:
+            payload["metadata"] = metadata
+        if graph_id:
+            payload["graph_id"] = graph_id
+        if name:
+            payload["name"] = name
+        if sort_by:
+            payload["sort_by"] = sort_by
+        if sort_order:
+            payload["sort_order"] = sort_order
+        if select:
+            payload["select"] = select
+        next_cursor: str | None = None
+
+        def capture_pagination(response: httpx.Response) -> None:
+            nonlocal next_cursor
+            next_cursor = response.headers.get("X-Pagination-Next")
+
+        assistants = cast(
+            list[Assistant],
+            self.http.post(
+                "/assistants/search",
+                json=payload,
+                headers=headers,
+                params=params,
+                on_response=capture_pagination if response_format == "object" else None,
+            ),
+        )
+        if response_format == "object":
+            return {"assistants": assistants, "next": next_cursor}
+        return assistants
+
+    def count(
+        self,
+        *,
+        metadata: Json = None,
+        graph_id: str | None = None,
+        name: str | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> int:
+        """Count assistants matching filters.
+
+        Args:
+            metadata: Metadata to filter by. Exact match for each key/value.
+            graph_id: Optional graph id to filter by.
+            name: Optional name to filter by.
+                The filtering logic will match assistants where 'name' is a substring (case insensitive) of the assistant name.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            int: Number of assistants matching the criteria.
+        """
+        payload: dict[str, Any] = {}
+        if metadata:
+            payload["metadata"] = metadata
+        if graph_id:
+            payload["graph_id"] = graph_id
+        if name:
+            payload["name"] = name
+        return self.http.post(
+            "/assistants/count", json=payload, headers=headers, params=params
+        )
+
+    def get_versions(
+        self,
+        assistant_id: str,
+        metadata: Json = None,
+        limit: int = 10,
+        offset: int = 0,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> list[AssistantVersion]:
+        """List all versions of an assistant.
+
+        Args:
+            assistant_id: The assistant ID to get versions for.
+            metadata: Metadata to filter versions by. Exact match filter for each KV pair.
+            limit: The maximum number of versions to return.
+            offset: The number of versions to skip.
+            headers: Optional custom headers to include with the request.
+
+        Returns:
+            A list of assistants.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:2024")
+            assistant_versions = client.assistants.get_versions(
+                assistant_id="my_assistant_id"
+            )
+            ```
+
+        """
+
+        payload: dict[str, Any] = {
+            "limit": limit,
+            "offset": offset,
+        }
+        if metadata:
+            payload["metadata"] = metadata
+        return self.http.post(
+            f"/assistants/{assistant_id}/versions",
+            json=payload,
+            headers=headers,
+            params=params,
+        )
+
+    def set_latest(
+        self,
+        assistant_id: str,
+        version: int,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Assistant:
+        """Change the version of an assistant.
+
+        Args:
+            assistant_id: The assistant ID to delete.
+            version: The version to change to.
+            headers: Optional custom headers to include with the request.
+
+        Returns:
+            `Assistant` Object.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:2024")
+            new_version_assistant = client.assistants.set_latest(
+                assistant_id="my_assistant_id",
+                version=3
+            )
+            ```
+
+        """
+
+        payload: dict[str, Any] = {"version": version}
+
+        return self.http.post(
+            f"/assistants/{assistant_id}/latest",
+            json=payload,
+            headers=headers,
+            params=params,
+        )

libs/sdk-py/langgraph_sdk/_sync/client.py

@@ -0,0 +1,127 @@
+"""Sync LangGraph client."""
+
+from __future__ import annotations
+
+from collections.abc import Mapping
+from types import TracebackType
+
+import httpx
+
+from langgraph_sdk._shared.types import TimeoutTypes
+from langgraph_sdk._shared.utilities import NOT_PROVIDED, _get_headers
+from langgraph_sdk._sync.assistants import SyncAssistantsClient
+from langgraph_sdk._sync.cron import SyncCronClient
+from langgraph_sdk._sync.http import SyncHttpClient
+from langgraph_sdk._sync.runs import SyncRunsClient
+from langgraph_sdk._sync.store import SyncStoreClient
+from langgraph_sdk._sync.threads import SyncThreadsClient
+
+
+def get_sync_client(
+    *,
+    url: str | None = None,
+    api_key: str | None = NOT_PROVIDED,
+    headers: Mapping[str, str] | None = None,
+    timeout: TimeoutTypes | None = None,
+) -> SyncLangGraphClient:
+    """Get a synchronous LangGraphClient instance.
+
+    Args:
+        url: The URL of the LangGraph API.
+        api_key: API key for authentication. Can be:
+            - A string: use this exact API key
+            - `None`: explicitly skip loading from environment variables
+            - Not provided (default): auto-load from environment in this order:
+                1. `LANGGRAPH_API_KEY`
+                2. `LANGSMITH_API_KEY`
+                3. `LANGCHAIN_API_KEY`
+        headers: Optional custom headers
+        timeout: Optional timeout configuration for the HTTP client.
+            Accepts an httpx.Timeout instance, a float (seconds), or a tuple of timeouts.
+            Tuple format is (connect, read, write, pool)
+            If not provided, defaults to connect=5s, read=300s, write=300s, and pool=5s.
+    Returns:
+        SyncLangGraphClient: The top-level synchronous client for accessing AssistantsClient,
+        ThreadsClient, RunsClient, and CronClient.
+
+    ???+ example "Example"
+
+        ```python
+        from langgraph_sdk import get_sync_client
+
+        # get top-level synchronous LangGraphClient
+        client = get_sync_client(url="http://localhost:8123")
+
+        # example usage: client.<model>.<method_name>()
+        assistant = client.assistants.get(assistant_id="some_uuid")
+        ```
+
+    ???+ example "Skip auto-loading API key from environment:"
+
+        ```python
+        from langgraph_sdk import get_sync_client
+
+        # Don't load API key from environment variables
+        client = get_sync_client(
+            url="http://localhost:8123",
+            api_key=None
+        )
+        ```
+    """
+
+    if url is None:
+        url = "http://localhost:8123"
+
+    transport = httpx.HTTPTransport(retries=5)
+    client = httpx.Client(
+        base_url=url,
+        transport=transport,
+        timeout=(
+            httpx.Timeout(timeout)  # type: ignore[arg-type]
+            if timeout is not None
+            else httpx.Timeout(connect=5, read=300, write=300, pool=5)
+        ),
+        headers=_get_headers(api_key, headers),
+    )
+    return SyncLangGraphClient(client)
+
+
+class SyncLangGraphClient:
+    """Synchronous client for interacting with the LangGraph API.
+
+    This class provides synchronous access to LangGraph API endpoints for managing
+    assistants, threads, runs, cron jobs, and data storage.
+
+    ???+ example "Example"
+
+        ```python
+        client = get_sync_client(url="http://localhost:2024")
+        assistant = client.assistants.get("asst_123")
+        ```
+    """
+
+    def __init__(self, client: httpx.Client) -> None:
+        self.http = SyncHttpClient(client)
+        self.assistants = SyncAssistantsClient(self.http)
+        self.threads = SyncThreadsClient(self.http)
+        self.runs = SyncRunsClient(self.http)
+        self.crons = SyncCronClient(self.http)
+        self.store = SyncStoreClient(self.http)
+
+    def __enter__(self) -> SyncLangGraphClient:
+        """Enter the sync context manager."""
+        return self
+
+    def __exit__(
+        self,
+        exc_type: type[BaseException] | None,
+        exc_val: BaseException | None,
+        exc_tb: TracebackType | None,
+    ) -> None:
+        """Exit the sync context manager."""
+        self.close()
+
+    def close(self) -> None:
+        """Close the underlying HTTP client."""
+        if hasattr(self, "http"):
+            self.http.client.close()

libs/sdk-py/langgraph_sdk/_sync/cron.py

@@ -0,0 +1,439 @@
+"""Synchronous cron client for LangGraph SDK."""
+
+from __future__ import annotations
+
+from collections.abc import Mapping
+from datetime import datetime
+from typing import Any
+
+from langgraph_sdk._sync.http import SyncHttpClient
+from langgraph_sdk.schema import (
+    All,
+    Config,
+    Context,
+    Cron,
+    CronSelectField,
+    CronSortBy,
+    Input,
+    OnCompletionBehavior,
+    QueryParamTypes,
+    Run,
+    SortOrder,
+)
+
+
+class SyncCronClient:
+    """Synchronous client for managing cron jobs in LangGraph.
+
+    This class provides methods to create and manage scheduled tasks (cron jobs) for automated graph executions.
+
+    ???+ example "Example"
+
+        ```python
+        client = get_sync_client(url="http://localhost:8123")
+        cron_job = client.crons.create_for_thread(thread_id="thread_123", assistant_id="asst_456", schedule="0 * * * *")
+        ```
+
+    !!! note "Feature Availability"
+
+        The crons client functionality is not supported on all licenses.
+        Please check the relevant license documentation for the most up-to-date
+        details on feature availability.
+    """
+
+    def __init__(self, http_client: SyncHttpClient) -> None:
+        self.http = http_client
+
+    def create_for_thread(
+        self,
+        thread_id: str,
+        assistant_id: str,
+        *,
+        schedule: str,
+        input: Input | None = None,
+        metadata: Mapping[str, Any] | None = None,
+        config: Config | None = None,
+        context: Context | None = None,
+        checkpoint_during: bool | None = None,
+        interrupt_before: All | list[str] | None = None,
+        interrupt_after: All | list[str] | None = None,
+        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:
+        """Create a cron job for a thread.
+
+        Args:
+            thread_id: the thread ID to run the cron job on.
+            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.
+            context: Static context to add to the assistant.
+                !!! version-added "Added in version 0.6.0"
+            checkpoint_during: Whether to checkpoint during the run (or only at the end/interruption).
+            interrupt_before: Nodes to interrupt immediately before they get executed.
+            interrupt_after: Nodes to Nodes to interrupt immediately after they get executed.
+            webhook: Webhook to call after LangGraph API call is done.
+            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:
+            The cron `Run`.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:8123")
+            cron_run = client.crons.create_for_thread(
+                thread_id="my-thread-id",
+                assistant_id="agent",
+                schedule="27 15 * * *",
+                input={"messages": [{"role": "user", "content": "hello!"}]},
+                metadata={"name":"my_run"},
+                context={"model_name": "openai"},
+                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",
+                enabled=True
+            )
+            ```
+        """
+        payload = {
+            "schedule": schedule,
+            "input": input,
+            "config": config,
+            "metadata": metadata,
+            "context": context,
+            "assistant_id": assistant_id,
+            "interrupt_before": interrupt_before,
+            "interrupt_after": interrupt_after,
+            "checkpoint_during": checkpoint_during,
+            "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(
+            f"/threads/{thread_id}/runs/crons",
+            json=payload,
+            headers=headers,
+            params=params,
+        )
+
+    def create(
+        self,
+        assistant_id: str,
+        *,
+        schedule: str,
+        input: Input | None = None,
+        metadata: Mapping[str, Any] | None = None,
+        config: Config | None = None,
+        context: Context | None = None,
+        checkpoint_during: bool | None = None,
+        interrupt_before: All | list[str] | None = None,
+        interrupt_after: All | list[str] | None = None,
+        webhook: str | None = None,
+        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:
+        """Create a cron run.
+
+        Args:
+            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.
+            context: Static context to add to the assistant.
+                !!! version-added "Added in version 0.6.0"
+            checkpoint_during: Whether to checkpoint during the run (or only at the end/interruption).
+            interrupt_before: Nodes to interrupt immediately before they get executed.
+            interrupt_after: Nodes to Nodes to interrupt immediately after they get executed.
+            webhook: Webhook to call after LangGraph API call is done.
+            on_run_completed: What to do with the thread after the run completes.
+                Must be one of 'delete' (default) or 'keep'. 'delete' removes the thread
+                after execution. 'keep' creates a new thread for each execution but does not
+                clean them up. Clients are responsible for cleaning up kept threads.
+            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:
+            The cron `Run`.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:8123")
+            cron_run = client.crons.create(
+                assistant_id="agent",
+                schedule="27 15 * * *",
+                input={"messages": [{"role": "user", "content": "hello!"}]},
+                metadata={"name":"my_run"},
+                context={"model_name": "openai"},
+                checkpoint_during=True,
+                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",
+                enabled=True
+            )
+            ```
+
+        """
+        payload = {
+            "schedule": schedule,
+            "input": input,
+            "config": config,
+            "metadata": metadata,
+            "context": context,
+            "assistant_id": assistant_id,
+            "interrupt_before": interrupt_before,
+            "interrupt_after": interrupt_after,
+            "webhook": webhook,
+            "checkpoint_during": checkpoint_during,
+            "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(
+            "/runs/crons", json=payload, headers=headers, params=params
+        )
+
+    def delete(
+        self,
+        cron_id: str,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> None:
+        """Delete a cron.
+
+        Args:
+            cron_id: The cron ID to delete.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            `None`
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:8123")
+            client.crons.delete(
+                cron_id="cron_to_delete"
+            )
+            ```
+
+        """
+        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,
+        sort_order: SortOrder | None = None,
+        select: list[CronSelectField] | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> list[Cron]:
+        """Get a list of cron jobs.
+
+        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.
+
+        Returns:
+            The list of cron jobs returned by the search,
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:8123")
+            cron_jobs = client.crons.search(
+                assistant_id="my_assistant_id",
+                thread_id="my_thread_id",
+                enabled=True,
+                limit=5,
+                offset=5,
+            )
+            print(cron_jobs)
+            ```
+
+            ```shell
+            ----------------------------------------------------------
+
+            [
+                {
+                    'cron_id': '1ef3cefa-4c09-6926-96d0-3dc97fd5e39b',
+                    'assistant_id': 'my_assistant_id',
+                    'thread_id': 'my_thread_id',
+                    'user_id': None,
+                    'payload':
+                        {
+                            'input': {'start_time': ''},
+                            'schedule': '4 * * * *',
+                            'assistant_id': 'my_assistant_id'
+                        },
+                    'schedule': '4 * * * *',
+                    'next_run_date': '2024-07-25T17:04:00+00:00',
+                    'end_time': None,
+                    'created_at': '2024-07-08T06:02:23.073257+00:00',
+                    'updated_at': '2024-07-08T06:02:23.073257+00:00'
+                }
+            ]
+            ```
+        """
+        payload = {
+            "assistant_id": assistant_id,
+            "thread_id": thread_id,
+            "enabled": enabled,
+            "limit": limit,
+            "offset": offset,
+        }
+        if sort_by:
+            payload["sort_by"] = sort_by
+        if sort_order:
+            payload["sort_order"] = sort_order
+        if select:
+            payload["select"] = select
+        payload = {k: v for k, v in payload.items() if v is not None}
+        return self.http.post(
+            "/runs/crons/search", json=payload, headers=headers, params=params
+        )
+
+    def count(
+        self,
+        *,
+        assistant_id: str | None = None,
+        thread_id: str | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> int:
+        """Count cron jobs matching filters.
+
+        Args:
+            assistant_id: Assistant ID to filter by.
+            thread_id: Thread ID to filter by.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            int: Number of crons matching the criteria.
+        """
+        payload: dict[str, Any] = {}
+        if assistant_id:
+            payload["assistant_id"] = assistant_id
+        if thread_id:
+            payload["thread_id"] = thread_id
+        return self.http.post(
+            "/runs/crons/count", json=payload, headers=headers, params=params
+        )

libs/sdk-py/langgraph_sdk/_sync/http.py

@@ -0,0 +1,296 @@
+"""Synchronous HTTP client for LangGraph API."""
+
+from __future__ import annotations
+
+import logging
+import sys
+import warnings
+from collections.abc import Callable, Iterator, Mapping
+from typing import Any, cast
+
+import httpx
+import orjson
+
+from langgraph_sdk._shared.utilities import _orjson_default
+from langgraph_sdk.errors import _raise_for_status_typed
+from langgraph_sdk.schema import QueryParamTypes, StreamPart
+from langgraph_sdk.sse import SSEDecoder, iter_lines_raw
+
+logger = logging.getLogger(__name__)
+
+
+class SyncHttpClient:
+    """Handle synchronous requests to the LangGraph API.
+
+    Provides error messaging and content handling enhancements above the
+    underlying httpx client, mirroring the interface of [HttpClient](#HttpClient)
+    but for sync usage.
+
+    Attributes:
+        client (httpx.Client): Underlying HTTPX sync client.
+    """
+
+    def __init__(self, client: httpx.Client) -> None:
+        self.client = client
+
+    def get(
+        self,
+        path: str,
+        *,
+        params: QueryParamTypes | None = None,
+        headers: Mapping[str, str] | None = None,
+        on_response: Callable[[httpx.Response], None] | None = None,
+    ) -> Any:
+        """Send a `GET` request."""
+        r = self.client.get(path, params=params, headers=headers)
+        if on_response:
+            on_response(r)
+        _raise_for_status_typed(r)
+        return _decode_json(r)
+
+    def post(
+        self,
+        path: str,
+        *,
+        json: dict[str, Any] | list | None,
+        params: QueryParamTypes | None = None,
+        headers: Mapping[str, str] | None = None,
+        on_response: Callable[[httpx.Response], None] | None = None,
+    ) -> Any:
+        """Send a `POST` request."""
+        if json is not None:
+            request_headers, content = _encode_json(json)
+        else:
+            request_headers, content = {}, b""
+        if headers:
+            request_headers.update(headers)
+        r = self.client.post(
+            path, headers=request_headers, content=content, params=params
+        )
+        if on_response:
+            on_response(r)
+        _raise_for_status_typed(r)
+        return _decode_json(r)
+
+    def put(
+        self,
+        path: str,
+        *,
+        json: dict,
+        params: QueryParamTypes | None = None,
+        headers: Mapping[str, str] | None = None,
+        on_response: Callable[[httpx.Response], None] | None = None,
+    ) -> Any:
+        """Send a `PUT` request."""
+        request_headers, content = _encode_json(json)
+        if headers:
+            request_headers.update(headers)
+
+        r = self.client.put(
+            path, headers=request_headers, content=content, params=params
+        )
+        if on_response:
+            on_response(r)
+        _raise_for_status_typed(r)
+        return _decode_json(r)
+
+    def patch(
+        self,
+        path: str,
+        *,
+        json: dict,
+        params: QueryParamTypes | None = None,
+        headers: Mapping[str, str] | None = None,
+        on_response: Callable[[httpx.Response], None] | None = None,
+    ) -> Any:
+        """Send a `PATCH` request."""
+        request_headers, content = _encode_json(json)
+        if headers:
+            request_headers.update(headers)
+        r = self.client.patch(
+            path, headers=request_headers, content=content, params=params
+        )
+        if on_response:
+            on_response(r)
+        _raise_for_status_typed(r)
+        return _decode_json(r)
+
+    def delete(
+        self,
+        path: str,
+        *,
+        json: Any | None = None,
+        params: QueryParamTypes | None = None,
+        headers: Mapping[str, str] | None = None,
+        on_response: Callable[[httpx.Response], None] | None = None,
+    ) -> None:
+        """Send a `DELETE` request."""
+        r = self.client.request(
+            "DELETE", path, json=json, params=params, headers=headers
+        )
+        if on_response:
+            on_response(r)
+        _raise_for_status_typed(r)
+
+    def request_reconnect(
+        self,
+        path: str,
+        method: str,
+        *,
+        json: dict[str, Any] | None = None,
+        params: QueryParamTypes | None = None,
+        headers: Mapping[str, str] | None = None,
+        on_response: Callable[[httpx.Response], None] | None = None,
+        reconnect_limit: int = 5,
+    ) -> Any:
+        """Send a request that automatically reconnects to Location header."""
+        request_headers, content = _encode_json(json)
+        if headers:
+            request_headers.update(headers)
+        with self.client.stream(
+            method, path, headers=request_headers, content=content, params=params
+        ) as r:
+            if on_response:
+                on_response(r)
+            try:
+                r.raise_for_status()
+            except httpx.HTTPStatusError as e:
+                body = r.read().decode()
+                if sys.version_info >= (3, 11):
+                    e.add_note(body)
+                else:
+                    logger.error(f"Error from langgraph-api: {body}", exc_info=e)
+                raise e
+            loc = r.headers.get("location")
+            if reconnect_limit <= 0 or not loc:
+                return _decode_json(r)
+            try:
+                return _decode_json(r)
+            except httpx.HTTPError:
+                warnings.warn(
+                    f"Request failed, attempting reconnect to Location: {loc}",
+                    stacklevel=2,
+                )
+                r.close()
+                return self.request_reconnect(
+                    loc,
+                    "GET",
+                    headers=request_headers,
+                    # don't pass on_response so it's only called once
+                    reconnect_limit=reconnect_limit - 1,
+                )
+
+    def stream(
+        self,
+        path: str,
+        method: str,
+        *,
+        json: dict[str, Any] | None = None,
+        params: QueryParamTypes | None = None,
+        headers: Mapping[str, str] | None = None,
+        on_response: Callable[[httpx.Response], None] | None = None,
+    ) -> Iterator[StreamPart]:
+        """Stream the results of a request using SSE."""
+        if json is not None:
+            request_headers, content = _encode_json(json)
+        else:
+            request_headers, content = {}, None
+        request_headers["Accept"] = "text/event-stream"
+        request_headers["Cache-Control"] = "no-store"
+        if headers:
+            request_headers.update(headers)
+
+        reconnect_headers = {
+            key: value
+            for key, value in request_headers.items()
+            if key.lower() not in {"content-length", "content-type"}
+        }
+
+        last_event_id: str | None = None
+        reconnect_path: str | None = None
+        reconnect_attempts = 0
+        max_reconnect_attempts = 5
+
+        while True:
+            current_headers = dict(
+                request_headers if reconnect_path is None else reconnect_headers
+            )
+            if last_event_id is not None:
+                current_headers["Last-Event-ID"] = last_event_id
+
+            current_method = method if reconnect_path is None else "GET"
+            current_content = content if reconnect_path is None else None
+            current_params = params if reconnect_path is None else None
+
+            retry = False
+            with self.client.stream(
+                current_method,
+                reconnect_path or path,
+                headers=current_headers,
+                content=current_content,
+                params=current_params,
+            ) as res:
+                if reconnect_path is None and on_response:
+                    on_response(res)
+                # check status
+                _raise_for_status_typed(res)
+                # check content type
+                content_type = res.headers.get("content-type", "").partition(";")[0]
+                if "text/event-stream" not in content_type:
+                    raise httpx.TransportError(
+                        "Expected response header Content-Type to contain 'text/event-stream', "
+                        f"got {content_type!r}"
+                    )
+
+                reconnect_location = res.headers.get("location")
+                if reconnect_location:
+                    reconnect_path = reconnect_location
+
+                decoder = SSEDecoder()
+                try:
+                    for line in iter_lines_raw(res):
+                        sse = decoder.decode(cast(bytes, line).rstrip(b"\n"))
+                        if sse is not None:
+                            if decoder.last_event_id is not None:
+                                last_event_id = decoder.last_event_id
+                            if sse.event or sse.data is not None:
+                                yield sse
+                except httpx.HTTPError:
+                    # httpx.TransportError inherits from HTTPError, so transient
+                    # disconnects during streaming land here.
+                    if reconnect_path is None:
+                        raise
+                    retry = True
+                else:
+                    if sse := decoder.decode(b""):
+                        if decoder.last_event_id is not None:
+                            last_event_id = decoder.last_event_id
+                        if sse.event or sse.data is not None:
+                            # See async stream implementation for rationale on
+                            # skipping empty flush events.
+                            yield sse
+            if retry:
+                reconnect_attempts += 1
+                if reconnect_attempts > max_reconnect_attempts:
+                    raise httpx.TransportError(
+                        "Exceeded maximum SSE reconnection attempts"
+                    )
+                continue
+            break
+
+
+def _encode_json(json: Any) -> tuple[dict[str, str], bytes]:
+    body = orjson.dumps(
+        json,
+        _orjson_default,
+        orjson.OPT_SERIALIZE_NUMPY | orjson.OPT_NON_STR_KEYS,
+    )
+    content_length = str(len(body))
+    content_type = "application/json"
+    headers = {"Content-Length": content_length, "Content-Type": content_type}
+    return headers, body
+
+
+def _decode_json(r: httpx.Response) -> Any:
+    body = r.read()
+    return orjson.loads(body) if body else None