comments

`aiosqlite` changed it's Connection type to no longer subclass
`threading.Thread`. This removed the is_alive method, which is called
proactively in setup().

This PR handles this in a backwards compat way.

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 should NOT be used for documentation. All new documentation must be added to `docs/docs/` directory.

examples/async.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "23544406",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/async.ipynb"
+   ]
+  }
+ ],
+ "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/branching.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "14f7ca50",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/branching.ipynb"
+   ]
+  }
+ ],
+ "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": "3.11.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

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

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "10251c1c",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/chatbot-simulation-evaluation/agent-simulation-evaluation.ipynb"
+   ]
+  }
+ ],
+ "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 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "a4351a24",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/chatbot-simulation-evaluation/langsmith-agent-simulation-evaluation.ipynb"
+   ]
+  }
+ ],
+ "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 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "a9014f94",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/chatbots/information-gather-prompting.ipynb"
+   ]
+  }
+ ],
+ "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/cloud_examples/langgraph_to_langgraph_cloud.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "2b789e16",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/cloud/how-tos/langgraph_to_langgraph_cloud.ipynb"
+   ]
+  }
+ ],
+ "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/code_assistant/langgraph_code_assistant.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "1f2f13ca",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/code_assistant/langgraph_code_assistant.ipynb"
+   ]
+  }
+ ],
+ "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/configuration.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "e9a58c69",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/configuration.ipynb"
+   ]
+  }
+ ],
+ "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/create-react-agent-hitl.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "a1e6efeb",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/create-react-agent-hitl.ipynb"
+   ]
+  }
+ ],
+ "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/create-react-agent-memory.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "1ef41a89",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/create-react-agent-memory.ipynb"
+   ]
+  }
+ ],
+ "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/create-react-agent-system-prompt.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "9e2f7902",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/create-react-agent-system-prompt.ipynb"
+   ]
+  }
+ ],
+ "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/create-react-agent.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "eb07372e",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/create-react-agent.ipynb"
+   ]
+  }
+ ],
+ "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/customer-support/customer-support.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "a8232bc9",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/customer-support/customer-support.ipynb"
+   ]
+  }
+ ],
+ "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 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "8dbdba5b",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/extraction/retries.ipynb"
+   ]
+  }
+ ],
+ "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 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "3ecab357",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/human_in_the_loop/wait-user-input.ipynb"
+   ]
+  }
+ ],
+ "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/input_output_schema.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "fc0793cb",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/input_output_schema.ipynb"
+   ]
+  }
+ ],
+ "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/lats/lats.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "09038b53",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/lats/lats.ipynb"
+   ]
+  }
+ ],
+ "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 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "85205e97",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/llm-compiler/LLMCompiler.ipynb"
+   ]
+  }
+ ],
+ "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/map-reduce.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "42abb708",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/map-reduce.ipynb"
+   ]
+  }
+ ],
+ "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/memory/add-summary-conversation-history.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "298784f6",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/memory/add-summary-conversation-history.ipynb"
+   ]
+  }
+ ],
+ "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/memory/delete-messages.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "3f4370fd",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/memory/delete-messages.ipynb"
+   ]
+  }
+ ],
+ "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/memory/manage-conversation-history.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "6ec7cb13",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/memory/manage-conversation-history.ipynb"
+   ]
+  }
+ ],
+ "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": 5
+}

examples/multi_agent/hierarchical_agent_teams.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "5cc8a2ad",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/multi_agent/hierarchical_agent_teams.ipynb"
+   ]
+  }
+ ],
+ "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 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "d2b507b9",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/multi_agent/multi-agent-collaboration.ipynb"
+   ]
+  }
+ ],
+ "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/node-retries.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "017a01f4",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/node-retries.ipynb"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "env",
+   "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/pass-config-to-tools.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "05f6ad0a",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/pass-config-to-tools.ipynb"
+   ]
+  }
+ ],
+ "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/pass-run-time-values-to-tools.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "8f38bec5",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/pass-run-time-values-to-tools.ipynb"
+   ]
+  }
+ ],
+ "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/pass_private_state.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "4da17088",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/pass_private_state.ipynb"
+   ]
+  }
+ ],
+ "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/persistence.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "d16e8b9c",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/memory/add-memory.md."
+   ]
+  }
+ ],
+ "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/persistence_mongodb.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "78217098",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/persistence_mongodb.ipynb"
+   ]
+  }
+ ],
+ "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/persistence_postgres.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "18526f23",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/memory/add-memory.md"
+   ]
+  }
+ ],
+ "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/persistence_redis.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "eee6ecdd",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/persistence_redis.ipynb"
+   ]
+  }
+ ],
+ "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/plan-and-execute/plan-and-execute.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "9138f92e",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/plan-and-execute/plan-and-execute.ipynb"
+   ]
+  }
+ ],
+ "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 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "294995c4",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/react-agent-from-scratch.ipynb"
+   ]
+  }
+ ],
+ "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 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "40f0d107",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/react-agent-structured-output.ipynb"
+   ]
+  }
+ ],
+ "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/recursion-limit.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "fa3f7c50",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/recursion-limit.ipynb"
+   ]
+  }
+ ],
+ "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/reflection/reflection.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "658773a2",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/reflection/reflection.ipynb"
+   ]
+  }
+ ],
+ "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 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "caf07859",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/reflexion/reflexion.ipynb"
+   ]
+  }
+ ],
+ "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 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "961f43ec",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/rewoo/rewoo.ipynb"
+   ]
+  }
+ ],
+ "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 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "bbd6e9b8",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/run-id-langsmith.ipynb"
+   ]
+  }
+ ],
+ "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 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "f6db1873",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/self-discover/self-discover.ipynb"
+   ]
+  }
+ ],
+ "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/state-model.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "4149ffcc",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/state-model.ipynb"
+   ]
+  }
+ ],
+ "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/storm/storm.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "3e05d7f9",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/storm/storm.ipynb"
+   ]
+  }
+ ],
+ "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": 4
+}

examples/stream-multiple.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "e663f597",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/stream-multiple.ipynb"
+   ]
+  }
+ ],
+ "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/stream-updates.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "e6829c80",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/stream-updates.ipynb"
+   ]
+  }
+ ],
+ "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/stream-values.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "5ec11895",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/stream-values.ipynb"
+   ]
+  }
+ ],
+ "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/streaming-content.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "6619387c",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/streaming-content.ipynb"
+   ]
+  }
+ ],
+ "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/streaming-events-from-within-tools-without-langchain.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "57b7e303",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/streaming-events-from-within-tools-without-langchain.ipynb"
+   ]
+  }
+ ],
+ "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/streaming-events-from-within-tools.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "8e71a0c8",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/streaming-events-from-within-tools.ipynb"
+   ]
+  }
+ ],
+ "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/streaming-from-final-node.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "756e4554",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/streaming-from-final-node.ipynb"
+   ]
+  }
+ ],
+ "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/streaming-subgraphs.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "47164a72",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/streaming-subgraphs.ipynb"
+   ]
+  }
+ ],
+ "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/streaming-tokens-without-langchain.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "218dfbcb",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/streaming-tokens-without-langchain.ipynb"
+   ]
+  }
+ ],
+ "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/streaming-tokens.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "99eb887e",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/streaming-tokens.ipynb"
+   ]
+  }
+ ],
+ "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/subgraph-transform-state.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "0de7689f",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/subgraph-transform-state.ipynb"
+   ]
+  }
+ ],
+ "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/subgraph.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "f49876e1",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/subgraph.ipynb"
+   ]
+  }
+ ],
+ "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/subgraphs-manage-state.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "5106959e",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/subgraphs-manage-state.ipynb"
+   ]
+  }
+ ],
+ "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-errors.ipynb

@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "dc21501d",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/tool-calling-errors.ipynb"
+   ]
+  }
+ ],
+ "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 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "7fd8bd65",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/tool-calling.ipynb"
+   ]
+  }
+ ],
+ "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 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "83c2223f",
+   "metadata": {},
+   "source": [
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/sql-agent.ipynb"
+   ]
+  }
+ ],
+ "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

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+   ]
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+ ],
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+   "metadata": {},
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+   ]
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+ ],
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examples/web-navigation/web_voyager.ipynb

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+Twitter = "https://x.com/LangChain"
 Slack = "https://www.langchain.com/join-community"
 Reddit = "https://www.reddit.com/r/LangChain/"
 

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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/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/pyproject.toml

@@ -26,7 +26,7 @@ inmem = [
 
 [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/uv.lock

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 [[package]]
 name = "uvicorn"
-version = "0.38.0"
+version = "0.40.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "click", marker = "python_full_version >= '3.11'" },
     { name = "h11", marker = "python_full_version >= '3.11'" },
 ]
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+sdist = { url = "https://files.pythonhosted.org/packages/c3/d1/8f3c683c9561a4e6689dd3b1d345c815f10f86acd044ee1fb9a4dcd0b8c5/uvicorn-0.40.0.tar.gz", hash = "sha256:839676675e87e73694518b5574fd0f24c9d97b46bea16df7b8c05ea1a51071ea", size = 81761, upload-time = "2025-12-21T14:16:22.45Z" }
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+    { url = "https://files.pythonhosted.org/packages/3d/d8/2083a1daa7439a66f3a48589a57d576aa117726762618f6bb09fe3798796/uvicorn-0.40.0-py3-none-any.whl", hash = "sha256:c6c8f55bc8bf13eb6fa9ff87ad62308bbbc33d0b67f84293151efe87e0d5f2ee", size = 68502, upload-time = "2025-12-21T14:16:21.041Z" },
 ]
 
 [[package]]
 name = "virtualenv"
-version = "20.35.4"
+version = "20.36.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "distlib" },
@@ -2250,9 +2276,9 @@ dependencies = [
     { name = "platformdirs" },
     { name = "typing-extensions", marker = "python_full_version < '3.11'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/20/28/e6f1a6f655d620846bd9df527390ecc26b3805a0c5989048c210e22c5ca9/virtualenv-20.35.4.tar.gz", hash = "sha256:643d3914d73d3eeb0c552cbb12d7e82adf0e504dbf86a3182f8771a153a1971c", size = 6028799, upload-time = "2025-10-29T06:57:40.511Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/aa/a3/4d310fa5f00863544e1d0f4de93bddec248499ccf97d4791bc3122c9d4f3/virtualenv-20.36.1.tar.gz", hash = "sha256:8befb5c81842c641f8ee658481e42641c68b5eab3521d8e092d18320902466ba", size = 6032239, upload-time = "2026-01-09T18:21:01.296Z" }
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/6a/2a/dc2228b2888f51192c7dc766106cd475f1b768c10caaf9727659726f7391/virtualenv-20.36.1-py3-none-any.whl", hash = "sha256:575a8d6b124ef88f6f51d56d656132389f961062a9177016a50e4f507bbcc19f", size = 6008258, upload-time = "2026-01-09T18:20:59.425Z" },
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 [[package]]

libs/langgraph/pyproject.toml

@@ -38,7 +38,7 @@ Homepage = "https://docs.langchain.com/oss/python/langgraph/overview"
 Documentation = "https://reference.langchain.com/python/langgraph/"
 Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/langgraph"
 Changelog = "https://github.com/langchain-ai/langgraph/releases"
-Twitter = "https://x.com/LangChainAI"
+Twitter = "https://x.com/LangChain"
 Slack = "https://www.langchain.com/join-community"
 Reddit = "https://www.reddit.com/r/LangChain/"
 

libs/prebuilt/langgraph/prebuilt/chat_agent_executor.py

@@ -287,7 +287,10 @@ def create_react_agent(
         [StateSchema, Runtime[ContextT]],
         Awaitable[Runnable[LanguageModelInput, BaseMessage]],
     ],
-    tools: Sequence[BaseTool | Callable | dict[str, Any]] | ToolNode,
+    tools: Sequence[BaseTool | Callable | dict[str, Any]]
+    | Callable[[], Sequence[BaseTool]]
+    | Callable[[], Awaitable[Sequence[BaseTool]]]
+    | ToolNode,
     *,
     prompt: Prompt | None = None,
     response_format: StructuredResponseSchema
@@ -355,8 +358,9 @@ def create_react_agent(
                 `.bind_tools()` and support required functionality. Bound tools
                 must be a subset of those specified in the `tools` parameter.
 
-        tools: A list of tools or a `ToolNode` instance.
+        tools: A list of tools, a `ToolNode` instance, or a callable that returns tools.
             If an empty list is provided, the agent will consist of a single LLM node without tool calling.
+            Callable tools providers (both sync and async) enable dynamic tool selection at runtime.
         prompt: An optional prompt for the LLM. Can take a few different forms:
 
             - `str`: This is converted to a `SystemMessage` and added to the beginning of the list of messages in `state["messages"]`.
@@ -546,18 +550,30 @@ def create_react_agent(
         )
 
     llm_builtin_tools: list[dict] = []
+    is_dynamic_tools = callable(tools) and not isinstance(tools, ToolNode)
     if isinstance(tools, ToolNode):
         tool_classes = list(tools.tools_by_name.values())
         tool_node = tools
+    elif is_dynamic_tools:
+        # Dynamic tools provider - pass directly to ToolNode
+        tool_node = ToolNode(
+            cast(
+                "Callable[[], Sequence[BaseTool]] | Callable[[], Awaitable[Sequence[BaseTool]]]",
+                tools,
+            )
+        )
+        # For dynamic tools, we can't know the tools at compile time
+        tool_classes = []
     else:
-        llm_builtin_tools = [t for t in tools if isinstance(t, dict)]
-        tool_node = ToolNode([t for t in tools if not isinstance(t, dict)])
+        tools_seq = cast("Sequence[BaseTool | Callable | dict[str, Any]]", tools)
+        llm_builtin_tools = [t for t in tools_seq if isinstance(t, dict)]
+        tool_node = ToolNode([t for t in tools_seq if not isinstance(t, dict)])
         tool_classes = list(tool_node.tools_by_name.values())
 
     is_dynamic_model = not isinstance(model, (str, Runnable)) and callable(model)
     is_async_dynamic_model = is_dynamic_model and inspect.iscoroutinefunction(model)
 
-    tool_calling_enabled = len(tool_classes) > 0
+    tool_calling_enabled = len(tool_classes) > 0 or is_dynamic_tools
 
     if not is_dynamic_model:
         if isinstance(model, str):

libs/prebuilt/langgraph/prebuilt/tool_node.py

@@ -42,7 +42,7 @@ from __future__ import annotations
 import asyncio
 import inspect
 import json
-from collections.abc import Awaitable, Callable
+from collections.abc import Awaitable, Callable, Sequence
 from copy import copy, deepcopy
 from dataclasses import dataclass, replace
 from types import UnionType
@@ -90,8 +90,6 @@ from pydantic import BaseModel, ValidationError
 from typing_extensions import TypeVar, Unpack
 
 if TYPE_CHECKING:
-    from collections.abc import Sequence
-
     from langgraph.runtime import Runtime
     from pydantic_core import ErrorDetails
 
@@ -653,9 +651,25 @@ class ToolNode(RunnableCallable):
         - `Command` can update state, trigger navigation, or send messages
 
     Args:
-        tools: A sequence of tools that can be invoked by this node.
+        tools: Tools that can be invoked by this node. Can be either:
 
-            Supports:
+            - **A sequence of tools**: A list/tuple of tools (static)
+            - **A callable**: A function that returns a sequence of tools (dynamic).
+              The callable is invoked on every `invoke()` or `ainvoke()` call,
+              allowing the available tools to change between invocations.
+
+              **Invocation semantics for dynamic tools callables:**
+
+              - Called once at the start of each ToolNode invocation
+              - Should return a consistent set of tools for a given invocation
+                (i.e., idempotent within a single invocation)
+              - Stochastic behavior (returning different tools across invocations)
+                is supported but be aware the model may reference tools that are
+                no longer available
+              - Must return `BaseTool` instances (not plain callables) to avoid
+                expensive introspection on every invocation
+
+            Each tool in the sequence supports:
 
             - **BaseTool instances**: Tools with schemas and metadata
             - **Plain functions**: Automatically converted to tools with inferred schemas
@@ -735,7 +749,9 @@ class ToolNode(RunnableCallable):
 
     def __init__(
         self,
-        tools: Sequence[BaseTool | Callable],
+        tools: Sequence[BaseTool | Callable]
+        | Callable[[], Sequence[BaseTool]]
+        | Callable[[], Awaitable[Sequence[BaseTool]]],
         *,
         name: str = "tools",
         tags: list[str] | None = None,
@@ -751,7 +767,8 @@ class ToolNode(RunnableCallable):
         """Initialize `ToolNode` with tools and configuration.
 
         Args:
-            tools: Sequence of tools to make available for execution.
+            tools: Tools to make available for execution. Can be a sequence of tools
+                or a callable that returns a sequence of tools (for dynamic tools).
             name: Node name for graph identification.
             tags: Optional metadata tags.
             handle_tool_errors: Error handling configuration.
@@ -763,25 +780,117 @@ class ToolNode(RunnableCallable):
                 If not provided, falls back to wrap_tool_call for async execution.
         """
         super().__init__(self._func, self._afunc, name=name, tags=tags, trace=False)
-        self._tools_by_name: dict[str, BaseTool] = {}
-        self._injected_args: dict[str, _InjectedArgs] = {}
         self._handle_tool_errors = handle_tool_errors
         self._messages_key = messages_key
         self._wrap_tool_call = wrap_tool_call
         self._awrap_tool_call = awrap_tool_call
+
+        self._tools_provider: Callable[[], Sequence[BaseTool]] | None = None
+        self._async_tools_provider: (
+            Callable[[], Awaitable[Sequence[BaseTool]]] | None
+        ) = None
+        self._tools_by_name: dict[str, BaseTool] = {}
+
+        if callable(tools) and not isinstance(tools, (list, tuple)):
+            # It's a dynamic tools provider
+            if inspect.iscoroutinefunction(tools):
+                self._async_tools_provider = cast(
+                    "Callable[[], Awaitable[Sequence[BaseTool]]]", tools
+                )
+            else:
+                self._tools_provider = cast("Callable[[], Sequence[BaseTool]]", tools)
+        else:
+            # It's a sequence of tools - process them statically
+            self._tools_by_name = self._build_tools_mapping(tools)
+
+    def _build_tools_mapping(
+        self,
+        tools: Sequence[BaseTool | Callable],
+        *,
+        convert_callables: bool = True,
+    ) -> dict[str, BaseTool]:
+        """Build tools_by_name mapping from a sequence of tools.
+
+        Args:
+            tools: Sequence of tools to process.
+            convert_callables: Whether to convert plain callables to BaseTools.
+                Set to False when processing tools from a dynamic provider
+                (which should already be BaseTools).
+
+        Returns:
+            Dictionary mapping tool names to BaseTool instances.
+        """
+        tools_by_name: dict[str, BaseTool] = {}
         for tool in tools:
             if not isinstance(tool, BaseTool):
-                tool_ = create_tool(cast("type[BaseTool]", tool))
+                if convert_callables:
+                    tool_ = create_tool(cast("type[BaseTool]", tool))
+                else:
+                    # Dynamic tools providers must return BaseTool instances, not plain
+                    # callables. Converting callables to tools requires calling
+                    # create_tool() which performs introspection. Doing this on every
+                    # invocation would be expensive and could have unexpected side effects.
+                    # Users should convert their callables to tools once upfront.
+                    msg = (
+                        f"Dynamic tools provider must return BaseTool instances, "
+                        f"got {type(tool).__name__}"
+                    )
+                    raise TypeError(msg)
             else:
                 tool_ = tool
-            self._tools_by_name[tool_.name] = tool_
-            # Build injected args mapping once during initialization in a single pass
-            self._injected_args[tool_.name] = _get_all_injected_args(tool_)
+            tools_by_name[tool_.name] = tool_
+        return tools_by_name
+
+    def _get_tools(self) -> dict[str, BaseTool]:
+        """Get the current tools mapping.
+
+        If a tools provider was configured, calls it to get the current tools.
+        Otherwise, returns the statically configured tools.
+
+        Returns:
+            Dictionary mapping tool names to BaseTool instances.
+
+        Raises:
+            TypeError: If an async tools provider is used in synchronous context.
+        """
+        if self._async_tools_provider is not None:
+            msg = (
+                "Cannot use async tools provider in synchronous context. "
+                "Use ainvoke() instead of invoke()."
+            )
+            raise TypeError(msg)
+        if self._tools_provider is not None:
+            tools = self._tools_provider()
+            return self._build_tools_mapping(tools, convert_callables=False)
+        return self._tools_by_name
+
+    async def _aget_tools(self) -> dict[str, BaseTool]:
+        """Get the current tools mapping asynchronously.
+
+        If an async or sync tools provider was configured, calls it to get
+        the current tools. Otherwise, returns the statically configured tools.
+
+        Returns:
+            Dictionary mapping tool names to BaseTool instances.
+        """
+        if self._async_tools_provider is not None:
+            tools = await self._async_tools_provider()
+            return self._build_tools_mapping(tools, convert_callables=False)
+        if self._tools_provider is not None:
+            tools = self._tools_provider()
+            return self._build_tools_mapping(tools, convert_callables=False)
+        return self._tools_by_name
 
     @property
     def tools_by_name(self) -> dict[str, BaseTool]:
-        """Mapping from tool name to BaseTool instance."""
-        return self._tools_by_name
+        """Mapping from tool name to BaseTool instance.
+
+        Note: If a sync dynamic tools provider was configured, this property
+        calls the provider to get the current tools on each access.
+        If an async tools provider was configured, this property will raise
+        a TypeError - use ainvoke() instead.
+        """
+        return self._get_tools()
 
     def _func(
         self,
@@ -792,6 +901,9 @@ class ToolNode(RunnableCallable):
         tool_calls, input_type = self._parse_input(input)
         config_list = get_config_list(config, len(tool_calls))
 
+        # Get tools once at the start of invocation (supports dynamic tools)
+        tools_by_name = self._get_tools()
+
         # Construct ToolRuntime instances at the top level for each tool call
         tool_runtimes = []
         for call, cfg in zip(tool_calls, config_list, strict=False):
@@ -806,11 +918,17 @@ class ToolNode(RunnableCallable):
             )
             tool_runtimes.append(tool_runtime)
 
-        # Pass original tool calls without injection
+        def run_one_with_tools(
+            call: ToolCall,
+            input_type: Literal["list", "dict", "tool_calls"],
+            tool_runtime: ToolRuntime,
+        ) -> ToolMessage | Command:
+            return self._run_one(call, input_type, tool_runtime, tools_by_name)
+
         input_types = [input_type] * len(tool_calls)
         with get_executor_for_config(config) as executor:
             outputs = list(
-                executor.map(self._run_one, tool_calls, input_types, tool_runtimes)
+                executor.map(run_one_with_tools, tool_calls, input_types, tool_runtimes)
             )
 
         return self._combine_tool_outputs(outputs, input_type)
@@ -824,6 +942,9 @@ class ToolNode(RunnableCallable):
         tool_calls, input_type = self._parse_input(input)
         config_list = get_config_list(config, len(tool_calls))
 
+        # Get tools once at the start of invocation (supports dynamic tools)
+        tools_by_name = await self._aget_tools()
+
         # Construct ToolRuntime instances at the top level for each tool call
         tool_runtimes = []
         for call, cfg in zip(tool_calls, config_list, strict=False):
@@ -838,10 +959,10 @@ class ToolNode(RunnableCallable):
             )
             tool_runtimes.append(tool_runtime)
 
-        # Pass original tool calls without injection
-        coros = []
-        for call, tool_runtime in zip(tool_calls, tool_runtimes, strict=False):
-            coros.append(self._arun_one(call, input_type, tool_runtime))  # type: ignore[arg-type]
+        coros = [
+            self._arun_one(call, input_type, tool_runtime, tools_by_name)  # type: ignore[arg-type]
+            for call, tool_runtime in zip(tool_calls, tool_runtimes, strict=False)
+        ]
         outputs = await asyncio.gather(*coros)
 
         return self._combine_tool_outputs(outputs, input_type)
@@ -895,13 +1016,17 @@ class ToolNode(RunnableCallable):
         request: ToolCallRequest,
         input_type: Literal["list", "dict", "tool_calls"],
         config: RunnableConfig,
+        tools_by_name: dict[str, BaseTool],
     ) -> ToolMessage | Command:
         """Execute tool call with configured error handling.
 
         Args:
-            request: Tool execution request.
+            request: Tool execution request (includes the specific tool to execute).
             input_type: Input format.
             config: Runnable configuration.
+            tools_by_name: Mapping from tool name to BaseTool. Used only for
+                validation error messages when the requested tool doesn't exist,
+                to list available tools in the error response.
 
         Returns:
             ToolMessage or Command.
@@ -914,14 +1039,14 @@ class ToolNode(RunnableCallable):
 
         # Validate tool exists when we actually need to execute it
         if tool is None:
-            if invalid_tool_message := self._validate_tool_call(call):
+            if invalid_tool_message := self._validate_tool_call(call, tools_by_name):
                 return invalid_tool_message
             # This should never happen if validation works correctly
             msg = f"Tool {call['name']} is not registered with ToolNode"
             raise TypeError(msg)
 
         # Inject state, store, and runtime right before invocation
-        injected_call = self._inject_tool_args(call, request.runtime)
+        injected_call = self._inject_tool_args(call, request.runtime, tool)
         call_args = {**injected_call, "type": "tool_call"}
 
         try:
@@ -929,7 +1054,7 @@ class ToolNode(RunnableCallable):
                 response = tool.invoke(call_args, config)
             except ValidationError as exc:
                 # Filter out errors for injected arguments
-                injected = self._injected_args.get(call["name"])
+                injected = _get_all_injected_args(tool)
                 filtered_errors = _filter_validation_errors(exc, injected)
                 # Use original call["args"] without injected values for error reporting
                 raise ToolInvocationError(
@@ -993,6 +1118,7 @@ class ToolNode(RunnableCallable):
         call: ToolCall,
         input_type: Literal["list", "dict", "tool_calls"],
         tool_runtime: ToolRuntime,
+        tools_by_name: dict[str, BaseTool],
     ) -> ToolMessage | Command:
         """Execute single tool call with wrap_tool_call wrapper if configured.
 
@@ -1000,13 +1126,14 @@ class ToolNode(RunnableCallable):
             call: Tool call dict.
             input_type: Input format.
             tool_runtime: Tool runtime.
+            tools_by_name: Mapping from tool name to BaseTool.
 
         Returns:
             ToolMessage or Command.
         """
         # Validation is deferred to _execute_tool_sync to allow interceptors
         # to short-circuit requests for unregistered tools
-        tool = self.tools_by_name.get(call["name"])
+        tool = tools_by_name.get(call["name"])
 
         # Create the tool request with state and runtime
         tool_request = ToolCallRequest(
@@ -1020,12 +1147,14 @@ class ToolNode(RunnableCallable):
 
         if self._wrap_tool_call is None:
             # No wrapper - execute directly
-            return self._execute_tool_sync(tool_request, input_type, config)
+            return self._execute_tool_sync(
+                tool_request, input_type, config, tools_by_name
+            )
 
         # Define execute callable that can be called multiple times
         def execute(req: ToolCallRequest) -> ToolMessage | Command:
             """Execute tool with given request. Can be called multiple times."""
-            return self._execute_tool_sync(req, input_type, config)
+            return self._execute_tool_sync(req, input_type, config, tools_by_name)
 
         # Call wrapper with request and execute callable
         try:
@@ -1048,13 +1177,17 @@ class ToolNode(RunnableCallable):
         request: ToolCallRequest,
         input_type: Literal["list", "dict", "tool_calls"],
         config: RunnableConfig,
+        tools_by_name: dict[str, BaseTool],
     ) -> ToolMessage | Command:
         """Execute tool call asynchronously with configured error handling.
 
         Args:
-            request: Tool execution request.
+            request: Tool execution request (includes the specific tool to execute).
             input_type: Input format.
             config: Runnable configuration.
+            tools_by_name: Mapping from tool name to BaseTool. Used only for
+                validation error messages when the requested tool doesn't exist,
+                to list available tools in the error response.
 
         Returns:
             ToolMessage or Command.
@@ -1067,14 +1200,14 @@ class ToolNode(RunnableCallable):
 
         # Validate tool exists when we actually need to execute it
         if tool is None:
-            if invalid_tool_message := self._validate_tool_call(call):
+            if invalid_tool_message := self._validate_tool_call(call, tools_by_name):
                 return invalid_tool_message
             # This should never happen if validation works correctly
             msg = f"Tool {call['name']} is not registered with ToolNode"
             raise TypeError(msg)
 
         # Inject state, store, and runtime right before invocation
-        injected_call = self._inject_tool_args(call, request.runtime)
+        injected_call = self._inject_tool_args(call, request.runtime, tool)
         call_args = {**injected_call, "type": "tool_call"}
 
         try:
@@ -1082,7 +1215,7 @@ class ToolNode(RunnableCallable):
                 response = await tool.ainvoke(call_args, config)
             except ValidationError as exc:
                 # Filter out errors for injected arguments
-                injected = self._injected_args.get(call["name"])
+                injected = _get_all_injected_args(tool)
                 filtered_errors = _filter_validation_errors(exc, injected)
                 # Use original call["args"] without injected values for error reporting
                 raise ToolInvocationError(
@@ -1146,6 +1279,7 @@ class ToolNode(RunnableCallable):
         call: ToolCall,
         input_type: Literal["list", "dict", "tool_calls"],
         tool_runtime: ToolRuntime,
+        tools_by_name: dict[str, BaseTool],
     ) -> ToolMessage | Command:
         """Execute single tool call asynchronously with awrap_tool_call wrapper if configured.
 
@@ -1153,13 +1287,14 @@ class ToolNode(RunnableCallable):
             call: Tool call dict.
             input_type: Input format.
             tool_runtime: Tool runtime.
+            tools_by_name: Mapping from tool name to BaseTool.
 
         Returns:
             ToolMessage or Command.
         """
         # Validation is deferred to _execute_tool_async to allow interceptors
         # to short-circuit requests for unregistered tools
-        tool = self.tools_by_name.get(call["name"])
+        tool = tools_by_name.get(call["name"])
 
         # Create the tool request with state and runtime
         tool_request = ToolCallRequest(
@@ -1173,16 +1308,20 @@ class ToolNode(RunnableCallable):
 
         if self._awrap_tool_call is None and self._wrap_tool_call is None:
             # No wrapper - execute directly
-            return await self._execute_tool_async(tool_request, input_type, config)
+            return await self._execute_tool_async(
+                tool_request, input_type, config, tools_by_name
+            )
 
         # Define async execute callable that can be called multiple times
         async def execute(req: ToolCallRequest) -> ToolMessage | Command:
             """Execute tool with given request. Can be called multiple times."""
-            return await self._execute_tool_async(req, input_type, config)
+            return await self._execute_tool_async(
+                req, input_type, config, tools_by_name
+            )
 
         def _sync_execute(req: ToolCallRequest) -> ToolMessage | Command:
             """Sync execute fallback for sync wrapper."""
-            return self._execute_tool_sync(req, input_type, config)
+            return self._execute_tool_sync(req, input_type, config, tools_by_name)
 
         # Call wrapper with request and execute callable
         try:
@@ -1248,10 +1387,12 @@ class ToolNode(RunnableCallable):
         tool_calls = list(latest_ai_message.tool_calls)
         return tool_calls, input_type
 
-    def _validate_tool_call(self, call: ToolCall) -> ToolMessage | None:
+    def _validate_tool_call(
+        self, call: ToolCall, tools_by_name: dict[str, BaseTool]
+    ) -> ToolMessage | None:
         requested_tool = call["name"]
-        if requested_tool not in self.tools_by_name:
-            all_tool_names = list(self.tools_by_name.keys())
+        if requested_tool not in tools_by_name:
+            all_tool_names = list(tools_by_name.keys())
             content = INVALID_TOOL_NAME_ERROR_TEMPLATE.format(
                 requested_tool=requested_tool,
                 available_tools=", ".join(all_tool_names),
@@ -1280,6 +1421,7 @@ class ToolNode(RunnableCallable):
         self,
         tool_call: ToolCall,
         tool_runtime: ToolRuntime,
+        tool: BaseTool,
     ) -> ToolCall:
         """Inject graph state, store, and runtime into tool call arguments.
 
@@ -1298,6 +1440,7 @@ class ToolNode(RunnableCallable):
                 Must contain 'name', 'args', 'id', and 'type' fields.
             tool_runtime: The ToolRuntime instance containing all runtime context
                 (state, config, store, context, stream_writer) to inject into tools.
+            tool: The BaseTool instance to inject arguments for.
 
         Returns:
             A new ToolCall dictionary with the same structure as the input but with
@@ -1311,11 +1454,8 @@ class ToolNode(RunnableCallable):
             This method is called automatically during tool execution. It should not
             be called from outside the `ToolNode`.
         """
-        if tool_call["name"] not in self.tools_by_name:
-            return tool_call
-
-        injected = self._injected_args.get(tool_call["name"])
-        if not injected:
+        injected = _get_all_injected_args(tool)
+        if not injected.state and not injected.store and not injected.runtime:
             return tool_call
 
         tool_call_copy: ToolCall = copy(tool_call)

libs/prebuilt/pyproject.toml

@@ -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.py

@@ -1902,3 +1902,356 @@ async def test_tool_node_tool_runtime_generic() -> None:
     assert tool_message.type == "tool"
     assert tool_message.content == "test_info"
     assert tool_message.tool_call_id == "call_1"
+
+
+async def test_tool_node_dynamic_tools() -> None:
+    """Test ToolNode with a dynamic tools provider callable."""
+
+    @dec_tool
+    def add(a: int, b: int) -> int:
+        """Add two numbers."""
+        return a + b
+
+    @dec_tool
+    def multiply(a: int, b: int) -> int:
+        """Multiply two numbers."""
+        return a * b
+
+    @dec_tool
+    def subtract(a: int, b: int) -> int:
+        """Subtract two numbers."""
+        return a - b
+
+    # Track which tools are available
+    available_tools: list[BaseTool] = [add, multiply]
+
+    def get_tools() -> list[BaseTool]:
+        return available_tools
+
+    # Create ToolNode with dynamic tools provider
+    tool_node = ToolNode(get_tools)
+
+    # Test that tools_by_name returns the current tools
+    assert set(tool_node.tools_by_name.keys()) == {"add", "multiply"}
+
+    # Test invoking a tool
+    result = tool_node.invoke(
+        {
+            "messages": [
+                AIMessage(
+                    "test",
+                    tool_calls=[
+                        {"name": "add", "args": {"a": 2, "b": 3}, "id": "call_1"}
+                    ],
+                )
+            ]
+        },
+        config=_create_config_with_runtime(),
+    )
+    tool_message = result["messages"][-1]
+    assert tool_message.content == "5"
+
+    # Test invoking another tool
+    result = await tool_node.ainvoke(
+        {
+            "messages": [
+                AIMessage(
+                    "test",
+                    tool_calls=[
+                        {"name": "multiply", "args": {"a": 4, "b": 5}, "id": "call_2"}
+                    ],
+                )
+            ]
+        },
+        config=_create_config_with_runtime(),
+    )
+    tool_message = result["messages"][-1]
+    assert tool_message.content == "20"
+
+    # Change the available tools dynamically
+    available_tools.clear()
+    available_tools.extend([subtract])
+
+    # Verify tools_by_name reflects the change
+    assert set(tool_node.tools_by_name.keys()) == {"subtract"}
+
+    # Test that the old tool is no longer available
+    result = tool_node.invoke(
+        {
+            "messages": [
+                AIMessage(
+                    "test",
+                    tool_calls=[
+                        {"name": "add", "args": {"a": 2, "b": 3}, "id": "call_3"}
+                    ],
+                )
+            ]
+        },
+        config=_create_config_with_runtime(),
+    )
+    tool_message = result["messages"][-1]
+    assert tool_message.status == "error"
+    assert "add is not a valid tool" in tool_message.content
+
+    # Test that the new tool works
+    result = tool_node.invoke(
+        {
+            "messages": [
+                AIMessage(
+                    "test",
+                    tool_calls=[
+                        {"name": "subtract", "args": {"a": 10, "b": 3}, "id": "call_4"}
+                    ],
+                )
+            ]
+        },
+        config=_create_config_with_runtime(),
+    )
+    tool_message = result["messages"][-1]
+    assert tool_message.content == "7"
+
+
+async def test_tool_node_dynamic_tools_with_injection() -> None:
+    """Test dynamic tools with state injection."""
+
+    class TestState(TypedDict):
+        messages: list
+        multiplier: int
+
+    @dec_tool
+    def scale(
+        value: int,
+        multiplier: Annotated[int, InjectedState("multiplier")],
+    ) -> int:
+        """Scale a value by the multiplier from state."""
+        return value * multiplier
+
+    available_tools: list[BaseTool] = [scale]
+
+    def get_tools() -> list[BaseTool]:
+        return available_tools
+
+    tool_node = ToolNode(get_tools)
+
+    result = tool_node.invoke(
+        {
+            "messages": [
+                AIMessage(
+                    "test",
+                    tool_calls=[
+                        {"name": "scale", "args": {"value": 5}, "id": "call_1"}
+                    ],
+                )
+            ],
+            "multiplier": 3,
+        },
+        config=_create_config_with_runtime(),
+    )
+    tool_message = result["messages"][-1]
+    assert tool_message.content == "15"
+
+
+def test_tool_node_dynamic_tools_type_error() -> None:
+    """Test that dynamic tools provider must return BaseTool instances."""
+
+    def bad_tool_provider():
+        # Returns a plain function instead of BaseTool
+        def not_a_base_tool(x: int) -> int:
+            return x
+
+        return [not_a_base_tool]
+
+    tool_node = ToolNode(bad_tool_provider)
+
+    # Should raise TypeError when trying to invoke since the provider returns
+    # a function instead of BaseTool
+    with pytest.raises(TypeError, match="must return BaseTool instances"):
+        tool_node.invoke(
+            {
+                "messages": [
+                    AIMessage(
+                        "test",
+                        tool_calls=[
+                            {
+                                "name": "not_a_base_tool",
+                                "args": {"x": 1},
+                                "id": "call_1",
+                            }
+                        ],
+                    )
+                ]
+            },
+            config=_create_config_with_runtime(),
+        )
+
+
+async def test_tool_node_async_tools_provider() -> None:
+    """Test ToolNode with an async tools provider callable."""
+
+    @dec_tool
+    def add(a: int, b: int) -> int:
+        """Add two numbers."""
+        return a + b
+
+    @dec_tool
+    def multiply(a: int, b: int) -> int:
+        """Multiply two numbers."""
+        return a * b
+
+    @dec_tool
+    def subtract(a: int, b: int) -> int:
+        """Subtract two numbers."""
+        return a - b
+
+    # Track which tools are available
+    available_tools: list[BaseTool] = [add, multiply]
+
+    async def get_tools_async() -> list[BaseTool]:
+        # Simulate async operation (e.g., fetching tools from a database)
+        return available_tools
+
+    # Create ToolNode with async dynamic tools provider
+    tool_node = ToolNode(get_tools_async)
+
+    # Test invoking a tool asynchronously
+    result = await tool_node.ainvoke(
+        {
+            "messages": [
+                AIMessage(
+                    "test",
+                    tool_calls=[
+                        {"name": "add", "args": {"a": 2, "b": 3}, "id": "call_1"}
+                    ],
+                )
+            ]
+        },
+        config=_create_config_with_runtime(),
+    )
+    tool_message = result["messages"][-1]
+    assert tool_message.content == "5"
+
+    # Test invoking another tool
+    result = await tool_node.ainvoke(
+        {
+            "messages": [
+                AIMessage(
+                    "test",
+                    tool_calls=[
+                        {"name": "multiply", "args": {"a": 4, "b": 5}, "id": "call_2"}
+                    ],
+                )
+            ]
+        },
+        config=_create_config_with_runtime(),
+    )
+    tool_message = result["messages"][-1]
+    assert tool_message.content == "20"
+
+    # Change the available tools dynamically
+    available_tools.clear()
+    available_tools.extend([subtract])
+
+    # Test that the new tool works
+    result = await tool_node.ainvoke(
+        {
+            "messages": [
+                AIMessage(
+                    "test",
+                    tool_calls=[
+                        {"name": "subtract", "args": {"a": 10, "b": 3}, "id": "call_4"}
+                    ],
+                )
+            ]
+        },
+        config=_create_config_with_runtime(),
+    )
+    tool_message = result["messages"][-1]
+    assert tool_message.content == "7"
+
+
+def test_tool_node_async_tools_provider_sync_context_error() -> None:
+    """Test that async tools provider raises TypeError in sync context."""
+
+    @dec_tool
+    def add(a: int, b: int) -> int:
+        """Add two numbers."""
+        return a + b
+
+    async def get_tools_async() -> list[BaseTool]:
+        return [add]
+
+    tool_node = ToolNode(get_tools_async)
+
+    # Should raise TypeError when trying to invoke synchronously
+    with pytest.raises(
+        TypeError,
+        match="Cannot use async tools provider in synchronous context",
+    ):
+        tool_node.invoke(
+            {
+                "messages": [
+                    AIMessage(
+                        "test",
+                        tool_calls=[
+                            {"name": "add", "args": {"a": 2, "b": 3}, "id": "call_1"}
+                        ],
+                    )
+                ]
+            },
+            config=_create_config_with_runtime(),
+        )
+
+
+def test_tool_node_async_tools_provider_tools_by_name_error() -> None:
+    """Test that tools_by_name raises TypeError with async tools provider."""
+
+    @dec_tool
+    def add(a: int, b: int) -> int:
+        """Add two numbers."""
+        return a + b
+
+    async def get_tools_async() -> list[BaseTool]:
+        return [add]
+
+    tool_node = ToolNode(get_tools_async)
+
+    # Should raise TypeError when accessing tools_by_name
+    with pytest.raises(
+        TypeError,
+        match="Cannot use async tools provider in synchronous context",
+    ):
+        _ = tool_node.tools_by_name
+
+
+async def test_tool_node_async_tools_provider_type_error() -> None:
+    """Test that async tools provider must return BaseTool instances."""
+
+    async def bad_tool_provider():
+        # Returns a plain function instead of BaseTool
+        def not_a_base_tool(x: int) -> int:
+            return x
+
+        return [not_a_base_tool]
+
+    tool_node = ToolNode(bad_tool_provider)
+
+    # Should raise TypeError when trying to invoke since the provider returns
+    # a function instead of BaseTool
+    with pytest.raises(TypeError, match="must return BaseTool instances"):
+        await tool_node.ainvoke(
+            {
+                "messages": [
+                    AIMessage(
+                        "test",
+                        tool_calls=[
+                            {
+                                "name": "not_a_base_tool",
+                                "args": {"x": 1},
+                                "id": "call_1",
+                            }
+                        ],
+                    )
+                ]
+            },
+            config=_create_config_with_runtime(),
+        )

libs/prebuilt/uv.lock

@@ -4,14 +4,11 @@ requires-python = ">=3.10"
 
 [[package]]
 name = "aiosqlite"
-version = "0.21.0"
+version = "0.22.1"
 source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "typing-extensions" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/13/7d/8bca2bf9a247c2c5dfeec1d7a5f40db6518f88d314b8bca9da29670d2671/aiosqlite-0.21.0.tar.gz", hash = "sha256:131bb8056daa3bc875608c631c678cda73922a2d4ba8aec373b19f18c17e7aa3", size = 13454, upload-time = "2025-02-03T07:30:16.235Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/4e/8a/64761f4005f17809769d23e518d915db74e6310474e733e3593cfc854ef1/aiosqlite-0.22.1.tar.gz", hash = "sha256:043e0bd78d32888c0a9ca90fc788b38796843360c855a7262a532813133a0650", size = 14821, upload-time = "2025-12-23T19:25:43.997Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/f5/10/6c25ed6de94c49f88a91fa5018cb4c0f3625f31d5be9f771ebe5cc7cd506/aiosqlite-0.21.0-py3-none-any.whl", hash = "sha256:2549cf4057f95f53dcba16f2b64e8e2791d7e1adedb13197dd8ed77bb226d7d0", size = 15792, upload-time = "2025-02-03T07:30:13.6Z" },
+    { url = "https://files.pythonhosted.org/packages/00/b7/e3bf5133d697a08128598c8d0abc5e16377b51465a33756de24fa7dee953/aiosqlite-0.22.1-py3-none-any.whl", hash = "sha256:21c002eb13823fad740196c5a2e9d8e62f6243bd9e7e4a1f87fb5e44ecb4fceb", size = 17405, upload-time = "2025-12-23T19:25:42.139Z" },
 ]
 
 [[package]]
@@ -25,16 +22,16 @@ 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'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/16/ce/8a777047513153587e5434fd752e89334ac33e379aa3497db860eeb60377/anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0", size = 228266, upload-time = "2025-11-28T23:37:38.911Z" }
+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" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/7f/9c/36c5c37947ebfb8c7f22e0eb6e4d188ee2d53aa3880f3f2744fb894f0cb1/anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb", size = 113362, upload-time = "2025-11-28T23:36:57.897Z" },
+    { 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]]
@@ -48,11 +45,11 @@ 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 = [
-    { url = "https://files.pythonhosted.org/packages/70/7d/9bc192684cea499815ff478dfcdc13835ddf401365057044fb721ec6bddb/certifi-2025.11.12-py3-none-any.whl", hash = "sha256:97de8790030bbd5c2d96b7ec782fc2f7820ef8dba6db909ccf95449f2d062d4b", size = 159438, upload-time = "2025-11-12T02:54:49.735Z" },
+    { 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]]
@@ -252,7 +249,7 @@ wheels = [
 
 [[package]]
 name = "langchain-core"
-version = "1.1.1"
+version = "1.2.7"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "jsonpatch" },
@@ -264,9 +261,9 @@ dependencies = [
     { name = "typing-extensions" },
     { name = "uuid-utils" },
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 [[package]]

libs/sdk-py/langgraph_sdk/__init__.py

@@ -3,6 +3,6 @@ from langgraph_sdk.client import get_client, get_sync_client
 from langgraph_sdk.encryption import Encryption
 from langgraph_sdk.encryption.types import EncryptionContext
 
-__version__ = "0.3.2"
+__version__ = "0.3.3"
 
 __all__ = ["Auth", "Encryption", "EncryptionContext", "get_client", "get_sync_client"]

libs/sdk-py/langgraph_sdk/client.py

@@ -2994,6 +2994,7 @@ class CronClient:
             assistant_id: The assistant ID or graph name to use for the cron job.
                 If using graph name, will default to first assistant created from that graph.
             schedule: The cron schedule to execute this job on.
+                Schedules are interpreted in UTC.
             input: The input to the graph.
             metadata: Metadata to assign to the cron job runs.
             config: The configuration for the assistant.
@@ -3080,6 +3081,7 @@ class CronClient:
             assistant_id: The assistant ID or graph name to use for the cron job.
                 If using graph name, will default to first assistant created from that graph.
             schedule: The cron schedule to execute this job on.
+                Schedules are interpreted in UTC.
             input: The input to the graph.
             metadata: Metadata to assign to the cron job runs.
             config: The configuration for the assistant.
@@ -6302,6 +6304,7 @@ class SyncCronClient:
             assistant_id: The assistant ID or graph name to use for the cron job.
                 If using graph name, will default to first assistant created from that graph.
             schedule: The cron schedule to execute this job on.
+                Schedules are interpreted in UTC.
             input: The input to the graph.
             metadata: Metadata to assign to the cron job runs.
             config: The configuration for the assistant.
@@ -6384,6 +6387,7 @@ class SyncCronClient:
             assistant_id: The assistant ID or graph name to use for the cron job.
                 If using graph name, will default to first assistant created from that graph.
             schedule: The cron schedule to execute this job on.
+                Schedules are interpreted in UTC.
             input: The input to the graph.
             metadata: Metadata to assign to the cron job runs.
             config: The configuration for the assistant.

libs/sdk-py/langgraph_sdk/errors.py

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

libs/sdk-py/pyproject.toml

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

libs/sdk-py/tests/test_errors.py

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

libs/sdk-py/uv.lock

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