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This reverts commit cff349e22e.

docs/cassettes/create-react-agent-manage-message-history_26c53429-90ba-4d0b-abb9-423d9120ad26.msgpack.zlib

@@ -0,0 +1 @@
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

docs/docs/cloud/how-tos/generative_ui_react.md

@@ -12,10 +12,6 @@ Generative user interfaces (Generative UI) allows agents to go beyond text and g
 
 LangGraph Platform supports colocating your React components with your graph code. This allows you to focus on building specific UI components for your graph while easily plugging into existing chat interfaces such as [Agent Chat](https://agentchat.vercel.app) and loading the code only when actually needed.
 
-!!! warning "LangGraph.js only"
-
-    Currently only LangGraph.js supports Generative UI. Support for Python is coming soon.
-
 ## Tutorial
 
 ### 1. Define and configure UI components
@@ -74,58 +70,105 @@ CSS and Tailwind 4.x is also supported out of the box, so you can freely use Tai
 
 ### 2. Send the UI components in your graph
 
-Use the `typedUi` utility to emit UI elements from your agent nodes:
+=== "Python"
 
-```typescript title="src/agent/index.ts"
-import {
-  typedUi,
-  uiMessageReducer,
-} from "@langchain/langgraph-sdk/react-ui/server";
+    ```python title="src/agent.py"
+    import uuid
+    from typing import Annotated, Sequence, TypedDict
 
-import { ChatOpenAI } from "@langchain/openai";
-import { v4 as uuidv4 } from "uuid";
-import { z } from "zod";
+    from langchain_core.messages import AIMessage, BaseMessage
+    from langchain_openai import ChatOpenAI
+    from langgraph.graph import StateGraph
+    from langgraph.graph.message import add_messages
+    from langgraph.graph.ui import AnyUIMessage, ui_message_reducer, push_ui_message
 
-import type ComponentMap from "./ui.js";
 
-import {
-  Annotation,
-  MessagesAnnotation,
-  StateGraph,
-  type LangGraphRunnableConfig,
-} from "@langchain/langgraph";
+    class AgentState(TypedDict):  # noqa: D101
+        messages: Annotated[Sequence[BaseMessage], add_messages]
+        ui: Annotated[Sequence[AnyUIMessage], ui_message_reducer]
 
-const AgentState = Annotation.Root({
-  ...MessagesAnnotation.spec,
-  ui: Annotation({ reducer: uiMessageReducer, default: () => [] }),
-});
 
-export const graph = new StateGraph(AgentState)
-  .addNode("weather", async (state, config) => {
-    // Provide the type of the component map to ensure
-    // type safety of `ui.push()` calls as well as
-    // pushing the messages to the `ui` and sending a custom event as well.
-    const ui = typedUi<typeof ComponentMap>(config);
+    async def weather(state: AgentState):
+        class WeatherOutput(TypedDict):
+            city: str
 
-    const weather = await new ChatOpenAI({ model: "gpt-4o-mini" })
-      .withStructuredOutput(z.object({ city: z.string() }))
-      .withConfig({ tags: ["langsmith:nostream"] })
-      .invoke(state.messages);
+        weather: WeatherOutput = (
+            await ChatOpenAI(model="gpt-4o-mini")
+            .with_structured_output(WeatherOutput)
+            .with_config({"tags": ["nostream"]})
+            .ainvoke(state["messages"])
+        )
 
-    const response = {
-      id: uuidv4(),
-      type: "ai",
-      content: `Here's the weather for ${weather.city}`,
-    };
+        message = AIMessage(
+            id=str(uuid.uuid4()),
+            content=f"Here's the weather for {weather['city']}",
+        )
 
-    // Emit UI elements with associated AI message
-    ui.push({ name: "weather", props: weather }, { message: response });
+        # Emit UI elements associated with the message
+        push_ui_message("weather", weather, message=message)
+        return {"messages": [message]}
 
-    return { messages: [response] };
-  })
-  .addEdge("__start__", "weather")
-  .compile();
-```
+
+    workflow = StateGraph(AgentState)
+    workflow.add_node(weather)
+    workflow.add_edge("__start__", "weather")
+    graph = workflow.compile()
+    ```
+
+=== "JS"
+
+    Use the `typedUi` utility to emit UI elements from your agent nodes:
+
+    ```typescript title="src/agent/index.ts"
+    import {
+      typedUi,
+      uiMessageReducer,
+    } from "@langchain/langgraph-sdk/react-ui/server";
+
+    import { ChatOpenAI } from "@langchain/openai";
+    import { v4 as uuidv4 } from "uuid";
+    import { z } from "zod";
+
+    import type ComponentMap from "./ui.js";
+
+    import {
+      Annotation,
+      MessagesAnnotation,
+      StateGraph,
+      type LangGraphRunnableConfig,
+    } from "@langchain/langgraph";
+
+    const AgentState = Annotation.Root({
+      ...MessagesAnnotation.spec,
+      ui: Annotation({ reducer: uiMessageReducer, default: () => [] }),
+    });
+
+    export const graph = new StateGraph(AgentState)
+      .addNode("weather", async (state, config) => {
+        // Provide the type of the component map to ensure
+        // type safety of `ui.push()` calls as well as
+        // pushing the messages to the `ui` and sending a custom event as well.
+        const ui = typedUi<typeof ComponentMap>(config);
+
+        const weather = await new ChatOpenAI({ model: "gpt-4o-mini" })
+          .withStructuredOutput(z.object({ city: z.string() }))
+          .withConfig({ tags: ["nostream"] })
+          .invoke(state.messages);
+
+        const response = {
+          id: uuidv4(),
+          type: "ai",
+          content: `Here's the weather for ${weather.city}`,
+        };
+
+        // Emit UI elements associated with the AI message
+        ui.push({ name: "weather", props: weather }, { message: response });
+
+        return { messages: [response] };
+      })
+      .addEdge("__start__", "weather")
+      .compile();
+    ```
 
 ### 3. Handle UI elements in your React application
 
@@ -294,18 +337,29 @@ const { thread, submit } = useStream({
 
 ### Remove UI messages from state
 
-Similar to how messages can be removed from the state by appending a RemoveMessage you can remove an UI message from the state by calling `ui.delete` with the ID of the UI message.
+Similar to how messages can be removed from the state by appending a RemoveMessage you can remove an UI message from the state by calling `remove_ui_message` / `ui.delete` with the ID of the UI message.
 
-```tsx
-// pushed message
-const message = ui.push({ name: "weather", props: { city: "London" } });
+=== "Python"
 
-// remove said message
-ui.delete(message.id);
+    ```python
+    from langgraph.graph.ui import push_ui_message, delete_ui_message
 
-// return new state to persist changes
-return { ui: ui.items };
-```
+    # push message
+    message = push_ui_message("weather", {"city": "London"})
+
+    # remove said message
+    delete_ui_message(message["id"])
+    ```
+
+=== "JS"
+
+    ```tsx
+    // push message
+    const message = ui.push({ name: "weather", props: { city: "London" } });
+
+    // remove said message
+    ui.delete(message.id);
+    ```
 
 ## Learn more
 

docs/docs/concepts/persistence.md

@@ -4,6 +4,10 @@ LangGraph has a built-in persistence layer, implemented through checkpointers. W
 
 ![Checkpoints](img/persistence/checkpoints.jpg)
 
+!!! info "LangGraph API handles checkpointing automatically"
+
+    When using the LangGraph API, you don't need to implement or configure checkpointers manually. The API handles all persistence infrastructure for you behind the scenes.
+
 ## Threads
 
 A thread is a unique ID or [thread identifier](#threads) assigned to each checkpoint saved by a checkpointer. When invoking graph with a checkpointer, you **must** specify a `thread_id` as part of the `configurable` portion of the config:
@@ -26,7 +30,7 @@ Let's see what checkpoints are saved when a simple graph is invoked as follows:
 
 ```python
 from langgraph.graph import StateGraph, START, END
-from langgraph.checkpoint.memory import MemorySaver
+from langgraph.checkpoint.memory import InMemorySaver
 from typing import Annotated
 from typing_extensions import TypedDict
 from operator import add
@@ -49,7 +53,7 @@ workflow.add_edge(START, "node_a")
 workflow.add_edge("node_a", "node_b")
 workflow.add_edge("node_b", END)
 
-checkpointer = MemorySaver()
+checkpointer = InMemorySaver()
 graph = workflow.compile(checkpointer=checkpointer)
 
 config = {"configurable": {"thread_id": "1"}}
@@ -223,6 +227,10 @@ But, what if we want to retain some information *across threads*? Consider the c
 
 With checkpointers alone, we cannot share information across threads. This motivates the need for the [`Store`](../reference/store.md#langgraph.store.base.BaseStore) interface. As an illustration, we can define an `InMemoryStore` to store information about a user across threads. We simply compile our graph with a checkpointer, as before, and with our new `in_memory_store` variable.
 
+!!!  info "LangGraph API handles stores automatically"
+
+    When using the LangGraph API, you don't need to implement or configure stores manually. The API handles all storage infrastructure for you behind the scenes.
+
 ### Basic Usage
 
 First, let's showcase this in isolation without using LangGraph.
@@ -324,10 +332,10 @@ store.put(
 With this all in place, we use the `in_memory_store` in LangGraph. The `in_memory_store` works hand-in-hand with the checkpointer: the checkpointer saves state to threads, as discussed above, and the `in_memory_store` allows us to store arbitrary information for access *across* threads. We compile the graph with both the checkpointer and the `in_memory_store` as follows. 
 
 ```python
-from langgraph.checkpoint.memory import MemorySaver
+from langgraph.checkpoint.memory import InMemorySaver
 
 # We need this because we want to enable threads (conversations)
-checkpointer = MemorySaver()
+checkpointer = InMemorySaver()
 
 # ... Define the graph ...
 
@@ -440,6 +448,7 @@ Under the hood, checkpointing is powered by checkpointer objects that conform to
 * `langgraph-checkpoint-sqlite`: An implementation of LangGraph checkpointer that uses SQLite database ([SqliteSaver][langgraph.checkpoint.sqlite.SqliteSaver] / [AsyncSqliteSaver][langgraph.checkpoint.sqlite.aio.AsyncSqliteSaver]). Ideal for experimentation and local workflows. Needs to be installed separately.
 * `langgraph-checkpoint-postgres`: An advanced checkpointer that uses Postgres database ([PostgresSaver][langgraph.checkpoint.postgres.PostgresSaver] / [AsyncPostgresSaver][langgraph.checkpoint.postgres.aio.AsyncPostgresSaver]), used in LangGraph Cloud. Ideal for using in production. Needs to be installed separately.
 
+
 ### Checkpointer interface
 
 Each checkpointer conforms to [BaseCheckpointSaver][langgraph.checkpoint.base.BaseCheckpointSaver] interface and implements the following methods:
@@ -452,7 +461,7 @@ Each checkpointer conforms to [BaseCheckpointSaver][langgraph.checkpoint.base.Ba
 If the checkpointer is used with asynchronous graph execution (i.e. executing the graph via `.ainvoke`, `.astream`, `.abatch`), asynchronous versions of the above methods will be used (`.aput`, `.aput_writes`, `.aget_tuple`, `.alist`).
 
 !!! note Note
-    For running your graph asynchronously, you can use `MemorySaver`, or async versions of Sqlite/Postgres checkpointers -- `AsyncSqliteSaver` / `AsyncPostgresSaver` checkpointers.
+    For running your graph asynchronously, you can use `InMemorySaver`, or async versions of Sqlite/Postgres checkpointers -- `AsyncSqliteSaver` / `AsyncPostgresSaver` checkpointers.
 
 ### Serializer
 

docs/docs/how-tos/index.md

@@ -163,6 +163,7 @@ These guides show how to use the prebuilt ReAct agent:
 - [How to add human-in-the-loop processes to a ReAct agent](create-react-agent-hitl.ipynb)
 - [How to return structured output from a ReAct agent](create-react-agent-structured-output.ipynb)
 - [How to add semantic search for long-term memory to a ReAct agent](memory/semantic-search.ipynb#using-in-create-react-agent)
+- [How to manage message history in a ReAct agent](create-react-agent-manage-message-history.ipynb)
 
 Interested in further customizing the ReAct agent? This guide provides an
 overview of its underlying implementation to help you customize for your own needs:

docs/docs/how-tos/persistence-functional.ipynb

@@ -16,6 +16,10 @@
     "    - [Memory](../../concepts/memory/)\n",
     "    - [Chat Models](https://python.langchain.com/docs/concepts/chat_models/)\n",
     "\n",
+    "!!! info \"Not needed for LangGraph API users\"\n",
+    "\n",
+    "    If you're using the LangGraph API, you needn't manually implement a checkpointer. The API automatically handles checkpointing for you. This guide is relevant when implementing LangGraph in your own custom server.\n",
+    "\n",
     "Many AI applications need memory to share context across multiple interactions on the same [thread](../../concepts/persistence#threads) (e.g., multiple turns of a conversation). In LangGraph functional API, this kind of memory can be added to any [entrypoint()][langgraph.func.entrypoint] workflow using [thread-level persistence](https://langchain-ai.github.io/langgraph/concepts/persistence).\n",
     "\n",
     "When creating a LangGraph workflow, you can set it up to persist its results by using a [checkpointer](https://langchain-ai.github.io/langgraph/reference/checkpoints/#basecheckpointsaver):\n",

docs/docs/how-tos/persistence.ipynb

@@ -31,6 +31,10 @@
     "    </p>\n",
     "</div> \n",
     "\n",
+    "!!! info \"Not needed for LangGraph API users\"\n",
+    "\n",
+    "    If you're using the LangGraph API, you needn't manually implement a checkpointer. The API automatically handles checkpointing for you. This guide is relevant when implementing LangGraph in your own custom server.\n",
+    "\n",
     "Many AI applications need memory to share context across multiple interactions. In LangGraph, this kind of memory can be added to any [StateGraph](https://langchain-ai.github.io/langgraph/reference/graphs/#langgraph.graph.StateGraph) using [thread-level persistence](https://langchain-ai.github.io/langgraph/concepts/persistence) .\n",
     "\n",
     "When creating any LangGraph graph, you can set it up to persist its state by adding a [checkpointer](https://langchain-ai.github.io/langgraph/reference/checkpoints/#basecheckpointsaver) when compiling the graph:\n",

docs/docs/how-tos/persistence_postgres.ipynb

@@ -26,6 +26,10 @@
     "    </p>\n",
     "</div> \n",
     "\n",
+    "!!! info \"Not needed for LangGraph API users\"\n",
+    "\n",
+    "    If you're using the LangGraph API, you needn't manually implement a checkpointer. The API automatically handles checkpointing for you. This guide is relevant when implementing LangGraph in your own custom server.\n",
+    "\n",
     "When creating LangGraph agents, you can also set them up so that they persist their state. This allows you to do things like interact with an agent multiple times and have it remember previous interactions.\n",
     "\n",
     "This how-to guide shows how to use `Postgres` as the backend for persisting checkpoint state using the [`langgraph-checkpoint-postgres`](https://github.com/langchain-ai/langgraph/tree/main/libs/checkpoint-postgres) library.\n",
@@ -44,7 +48,7 @@
     "...\n",
     "```\n",
     "\n",
-    "!!! info \"Setup\"",
+    "!!! info \"Setup\"\n",
     "\n",
     "    You need to run `.setup()` once on your checkpointer to initialize the database before you can use it."
    ]

docs/mkdocs.yml

@@ -185,6 +185,7 @@ nav:
               - how-tos/create-react-agent-system-prompt.ipynb
               - how-tos/create-react-agent-hitl.ipynb
               - how-tos/create-react-agent-structured-output.ipynb
+              - how-tos/create-react-agent-manage-message-history.ipynb
               - how-tos/react-agent-from-scratch.ipynb
               - how-tos/react-agent-from-scratch-functional.ipynb
         - LangGraph Platform:

docs/overrides/main.html

@@ -1,6 +1,7 @@
 {% extends "base.html" %}
 
 {% block extrahead %}
+  <meta name="algolia-site-verification" content="165B7E7C89E49946" />
   <style>
     @import url("https://fonts.googleapis.com/css2?family=Public+Sans&display=swap");
     :root {

docs/pyproject.toml

@@ -50,7 +50,8 @@ langchain-community = "^0.3.0"
 langchain-experimental = "^0.3.2"
 langchain-mistralai = "^0.2.6"
 langgraph-checkpoint-mongodb = "^0.1.0"
-langsmith = "^0.2.0"
+langmem = "^0.0.19"
+langsmith = "^0.3.0"
 chromadb = "^0.5.5"
 gpt4all = "^2.8.2"
 scikit-learn = "^1.5.2"

libs/checkpoint-sqlite/poetry.lock

@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 2.0.0 and should not be changed by hand.
+# This file is automatically @generated by Poetry 2.1.1 and should not be changed by hand.
 
 [[package]]
 name = "aiosqlite"
@@ -51,7 +51,7 @@ typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}
 
 [package.extras]
 doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
-test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17) ; platform_python_implementation == \"CPython\" and platform_system != \"Windows\""]
 trio = ["trio (>=0.23)"]
 
 [[package]]
@@ -181,7 +181,7 @@ files = [
 [package.extras]
 dev = ["Pygments", "build", "chardet", "pre-commit", "pytest", "pytest-cov", "pytest-dependency", "ruff", "tomli", "twine"]
 hard-encoding-detection = ["chardet"]
-toml = ["tomli"]
+toml = ["tomli ; python_version < \"3.11\""]
 types = ["chardet (>=5.1.0)", "mypy", "pytest", "pytest-cov", "pytest-dependency"]
 
 [[package]]
@@ -267,7 +267,7 @@ idna = "*"
 sniffio = "*"
 
 [package.extras]
-brotli = ["brotli", "brotlicffi"]
+brotli = ["brotli ; platform_python_implementation == \"CPython\"", "brotlicffi ; platform_python_implementation != \"CPython\""]
 cli = ["click (==8.*)", "pygments (==2.*)", "rich (>=10,<14)"]
 http2 = ["h2 (>=3,<5)"]
 socks = ["socksio (==1.*)"]
@@ -326,26 +326,26 @@ files = [
 
 [[package]]
 name = "langchain-core"
-version = "0.3.0"
+version = "0.3.15"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.9"
 groups = ["main", "dev"]
 files = [
-    {file = "langchain_core-0.3.0-py3-none-any.whl", hash = "sha256:bee6dae2366d037ef0c5b87401fed14b5497cad26f97724e8c9ca7bc9239e847"},
-    {file = "langchain_core-0.3.0.tar.gz", hash = "sha256:1249149ea3ba24c9c761011483c14091573a5eb1a773aa0db9c8ad155dd4a69d"},
+    {file = "langchain_core-0.3.15-py3-none-any.whl", hash = "sha256:3d4ca6dbb8ed396a6ee061063832a2451b0ce8c345570f7b086ffa7288e4fa29"},
+    {file = "langchain_core-0.3.15.tar.gz", hash = "sha256:b1a29787a4ffb7ec2103b4e97d435287201da7809b369740dd1e32f176325aba"},
 ]
 
 [package.dependencies]
 jsonpatch = ">=1.33,<2.0"
-langsmith = ">=0.1.117,<0.2.0"
+langsmith = ">=0.1.125,<0.2.0"
 packaging = ">=23.2,<25"
 pydantic = [
     {version = ">=2.5.2,<3.0.0", markers = "python_full_version < \"3.12.4\""},
     {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
 ]
 PyYAML = ">=5.3"
-tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
+tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10.0.0"
 typing-extensions = ">=4.7"
 
 [[package]]
@@ -368,24 +368,28 @@ url = "../checkpoint"
 
 [[package]]
 name = "langsmith"
-version = "0.1.120"
+version = "0.1.147"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 groups = ["main", "dev"]
 files = [
-    {file = "langsmith-0.1.120-py3-none-any.whl", hash = "sha256:54d2785e301646c0988e0a69ebe4d976488c87b41928b358cb153b6ddd8db62b"},
-    {file = "langsmith-0.1.120.tar.gz", hash = "sha256:25499ca187b41bd89d784b272b97a8d76f60e0e21bdf20336e8a2aa6a9b23ac9"},
+    {file = "langsmith-0.1.147-py3-none-any.whl", hash = "sha256:7166fc23b965ccf839d64945a78e9f1157757add228b086141eb03a60d699a15"},
+    {file = "langsmith-0.1.147.tar.gz", hash = "sha256:2e933220318a4e73034657103b3b1a3a6109cc5db3566a7e8e03be8d6d7def7a"},
 ]
 
 [package.dependencies]
 httpx = ">=0.23.0,<1"
-orjson = ">=3.9.14,<4.0.0"
+orjson = {version = ">=3.9.14,<4.0.0", markers = "platform_python_implementation != \"PyPy\""}
 pydantic = [
     {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""},
     {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
 ]
 requests = ">=2,<3"
+requests-toolbelt = ">=1.0.0,<2.0.0"
+
+[package.extras]
+langsmith-pyo3 = ["langsmith-pyo3 (>=0.1.0rc2,<0.2.0)"]
 
 [[package]]
 name = "mypy"
@@ -454,6 +458,7 @@ description = "Fast, correct Python JSON library supporting dataclasses, datetim
 optional = false
 python-versions = ">=3.8"
 groups = ["main", "dev"]
+markers = "platform_python_implementation != \"PyPy\""
 files = [
     {file = "orjson-3.10.6-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:fb0ee33124db6eaa517d00890fc1a55c3bfe1cf78ba4a8899d71a06f2d6ff5c7"},
     {file = "orjson-3.10.6-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9c1c4b53b24a4c06547ce43e5fee6ec4e0d8fe2d597f4647fc033fd205707365"},
@@ -858,6 +863,21 @@ urllib3 = ">=1.21.1,<3"
 socks = ["PySocks (>=1.5.6,!=1.5.7)"]
 use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
+[[package]]
+name = "requests-toolbelt"
+version = "1.0.0"
+description = "A utility belt for advanced users of python-requests"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+groups = ["main", "dev"]
+files = [
+    {file = "requests-toolbelt-1.0.0.tar.gz", hash = "sha256:7681a0a3d047012b5bdc0ee37d7f8f07ebe76ab08caeccfc3921ce23c88d5bc6"},
+    {file = "requests_toolbelt-1.0.0-py2.py3-none-any.whl", hash = "sha256:cccfdd665f0a24fcf4726e690f65639d272bb0637b9b92dfd91a5568ccf6bd06"},
+]
+
+[package.dependencies]
+requests = ">=2.0.1,<3.0.0"
+
 [[package]]
 name = "ruff"
 version = "0.6.2"
@@ -952,7 +972,7 @@ files = [
 ]
 
 [package.extras]
-brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)"]
+brotli = ["brotli (>=1.0.9) ; platform_python_implementation == \"CPython\"", "brotlicffi (>=0.8.0) ; platform_python_implementation != \"CPython\""]
 h2 = ["h2 (>=4,<5)"]
 socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
 zstd = ["zstandard (>=0.18.0)"]

libs/checkpoint/langgraph/checkpoint/memory/__init__.py

@@ -38,6 +38,8 @@ class InMemorySaver(
         Only use `InMemorySaver` for debugging or testing purposes.
         For production use cases we recommend installing [langgraph-checkpoint-postgres](https://pypi.org/project/langgraph-checkpoint-postgres/) and using `PostgresSaver` / `AsyncPostgresSaver`.
 
+        If you are using the LangGraph Platform, no checkpointer needs to be specified. The correct managed checkpointer will be used automatically.
+
     Args:
         serde (Optional[SerializerProtocol]): The serializer to use for serializing and deserializing checkpoints. Defaults to None.
 

libs/checkpoint/poetry.lock

@@ -12,6 +12,29 @@ files = [
     {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
 ]
 
+[[package]]
+name = "anyio"
+version = "4.9.0"
+description = "High level compatibility layer for multiple asynchronous event loop implementations"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
+    {file = "anyio-4.9.0-py3-none-any.whl", hash = "sha256:9f76d541cad6e36af7beb62e978876f3b41e3e04f2c1fbf0884604c0a9c4d93c"},
+    {file = "anyio-4.9.0.tar.gz", hash = "sha256:673c0c244e15788651a4ff38710fea9675823028a6f08a5eda409e0c9840a028"},
+]
+
+[package.dependencies]
+exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
+idna = ">=2.8"
+sniffio = ">=1.1"
+typing_extensions = {version = ">=4.5", markers = "python_version < \"3.13\""}
+
+[package.extras]
+doc = ["Sphinx (>=8.2,<9.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx_rtd_theme"]
+test = ["anyio[trio]", "blockbuster (>=1.5.23)", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21)"]
+trio = ["trio (>=0.26.1)"]
+
 [[package]]
 name = "certifi"
 version = "2024.7.4"
@@ -177,7 +200,7 @@ version = "1.2.2"
 description = "Backport of PEP 654 (exception groups)"
 optional = false
 python-versions = ">=3.7"
-groups = ["dev"]
+groups = ["main", "dev"]
 markers = "python_version < \"3.11\""
 files = [
     {file = "exceptiongroup-1.2.2-py3-none-any.whl", hash = "sha256:3111b9d131c238bec2f8f516e123e14ba243563fb135d3fe885990585aa7795b"},
@@ -187,6 +210,65 @@ files = [
 [package.extras]
 test = ["pytest (>=6)"]
 
+[[package]]
+name = "h11"
+version = "0.14.0"
+description = "A pure-Python, bring-your-own-I/O implementation of HTTP/1.1"
+optional = false
+python-versions = ">=3.7"
+groups = ["main"]
+files = [
+    {file = "h11-0.14.0-py3-none-any.whl", hash = "sha256:e3fe4ac4b851c468cc8363d500db52c2ead036020723024a109d37346efaa761"},
+    {file = "h11-0.14.0.tar.gz", hash = "sha256:8f19fbbe99e72420ff35c00b27a34cb9937e902a8b810e2c88300c6f0a3b699d"},
+]
+
+[[package]]
+name = "httpcore"
+version = "1.0.7"
+description = "A minimal low-level HTTP client."
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "httpcore-1.0.7-py3-none-any.whl", hash = "sha256:a3fff8f43dc260d5bd363d9f9cf1830fa3a458b332856f34282de498ed420edd"},
+    {file = "httpcore-1.0.7.tar.gz", hash = "sha256:8551cb62a169ec7162ac7be8d4817d561f60e08eaa485234898414bb5a8a0b4c"},
+]
+
+[package.dependencies]
+certifi = "*"
+h11 = ">=0.13,<0.15"
+
+[package.extras]
+asyncio = ["anyio (>=4.0,<5.0)"]
+http2 = ["h2 (>=3,<5)"]
+socks = ["socksio (==1.*)"]
+trio = ["trio (>=0.22.0,<1.0)"]
+
+[[package]]
+name = "httpx"
+version = "0.28.1"
+description = "The next generation HTTP client."
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "httpx-0.28.1-py3-none-any.whl", hash = "sha256:d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad"},
+    {file = "httpx-0.28.1.tar.gz", hash = "sha256:75e98c5f16b0f35b567856f597f06ff2270a374470a5c2392242528e3e3e42fc"},
+]
+
+[package.dependencies]
+anyio = "*"
+certifi = "*"
+httpcore = "==1.*"
+idna = "*"
+
+[package.extras]
+brotli = ["brotli", "brotlicffi"]
+cli = ["click (==8.*)", "pygments (==2.*)", "rich (>=10,<14)"]
+http2 = ["h2 (>=3,<5)"]
+socks = ["socksio (==1.*)"]
+zstd = ["zstandard (>=0.18.0)"]
+
 [[package]]
 name = "idna"
 version = "3.7"
@@ -240,19 +322,19 @@ files = [
 
 [[package]]
 name = "langchain-core"
-version = "0.2.38"
+version = "0.2.43"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 groups = ["main"]
 files = [
-    {file = "langchain_core-0.2.38-py3-none-any.whl", hash = "sha256:8a5729bc7e68b4af089af20eff44fe4e7ca21d0e0c87ec21cef7621981fd1a4a"},
-    {file = "langchain_core-0.2.38.tar.gz", hash = "sha256:eb69dbedd344f2ee1f15bcea6c71a05884b867588fadc42d04632e727c1238f3"},
+    {file = "langchain_core-0.2.43-py3-none-any.whl", hash = "sha256:619601235113298ebf8252a349754b7c28d3cf7166c7c922da24944b78a9363a"},
+    {file = "langchain_core-0.2.43.tar.gz", hash = "sha256:42c2ef6adedb911f4254068b6adc9eb4c4075f6c8cb3d83590d3539a815695f5"},
 ]
 
 [package.dependencies]
 jsonpatch = ">=1.33,<2.0"
-langsmith = ">=0.1.75,<0.2.0"
+langsmith = ">=0.1.112,<0.2.0"
 packaging = ">=23.2,<25"
 pydantic = [
     {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""},
@@ -264,23 +346,28 @@ typing-extensions = ">=4.7"
 
 [[package]]
 name = "langsmith"
-version = "0.1.93"
+version = "0.1.147"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 groups = ["main"]
 files = [
-    {file = "langsmith-0.1.93-py3-none-any.whl", hash = "sha256:811210b9d5f108f36431bd7b997eb9476a9ecf5a2abd7ddbb606c1cdcf0f43ce"},
-    {file = "langsmith-0.1.93.tar.gz", hash = "sha256:285b6ad3a54f50fa8eb97b5f600acc57d0e37e139dd8cf2111a117d0435ba9b4"},
+    {file = "langsmith-0.1.147-py3-none-any.whl", hash = "sha256:7166fc23b965ccf839d64945a78e9f1157757add228b086141eb03a60d699a15"},
+    {file = "langsmith-0.1.147.tar.gz", hash = "sha256:2e933220318a4e73034657103b3b1a3a6109cc5db3566a7e8e03be8d6d7def7a"},
 ]
 
 [package.dependencies]
-orjson = ">=3.9.14,<4.0.0"
+httpx = ">=0.23.0,<1"
+orjson = {version = ">=3.9.14,<4.0.0", markers = "platform_python_implementation != \"PyPy\""}
 pydantic = [
     {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""},
     {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
 ]
 requests = ">=2,<3"
+requests-toolbelt = ">=1.0.0,<2.0.0"
+
+[package.extras]
+langsmith-pyo3 = ["langsmith-pyo3 (>=0.1.0rc2,<0.2.0)"]
 
 [[package]]
 name = "marshmallow"
@@ -369,6 +456,7 @@ description = "Fast, correct Python JSON library supporting dataclasses, datetim
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
+markers = "platform_python_implementation != \"PyPy\""
 files = [
     {file = "orjson-3.10.6-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:fb0ee33124db6eaa517d00890fc1a55c3bfe1cf78ba4a8899d71a06f2d6ff5c7"},
     {file = "orjson-3.10.6-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9c1c4b53b24a4c06547ce43e5fee6ec4e0d8fe2d597f4647fc033fd205707365"},
@@ -773,6 +861,21 @@ urllib3 = ">=1.21.1,<3"
 socks = ["PySocks (>=1.5.6,!=1.5.7)"]
 use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
+[[package]]
+name = "requests-toolbelt"
+version = "1.0.0"
+description = "A utility belt for advanced users of python-requests"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+groups = ["main"]
+files = [
+    {file = "requests-toolbelt-1.0.0.tar.gz", hash = "sha256:7681a0a3d047012b5bdc0ee37d7f8f07ebe76ab08caeccfc3921ce23c88d5bc6"},
+    {file = "requests_toolbelt-1.0.0-py2.py3-none-any.whl", hash = "sha256:cccfdd665f0a24fcf4726e690f65639d272bb0637b9b92dfd91a5568ccf6bd06"},
+]
+
+[package.dependencies]
+requests = ">=2.0.1,<3.0.0"
+
 [[package]]
 name = "ruff"
 version = "0.6.2"
@@ -801,6 +904,18 @@ files = [
     {file = "ruff-0.6.2.tar.gz", hash = "sha256:239ee6beb9e91feb8e0ec384204a763f36cb53fb895a1a364618c6abb076b3be"},
 ]
 
+[[package]]
+name = "sniffio"
+version = "1.3.1"
+description = "Sniff out which async library your code is running under"
+optional = false
+python-versions = ">=3.7"
+groups = ["main"]
+files = [
+    {file = "sniffio-1.3.1-py3-none-any.whl", hash = "sha256:2f6da418d1f1e0fddd844478f41680e794e6051915791a034ff65e5f100525a2"},
+    {file = "sniffio-1.3.1.tar.gz", hash = "sha256:f4324edc670a0f49750a81b895f35c3adb843cca46f0530f79fc1babb23789dc"},
+]
+
 [[package]]
 name = "tenacity"
 version = "8.5.0"

libs/cli/langgraph_cli/cli.py

@@ -665,6 +665,8 @@ def dev(
         wait_for_client=wait_for_client,
         auth=config_json.get("auth"),
         http=config_json.get("http"),
+        ui=config_json.get("ui"),
+        ui_config=config_json.get("ui_config"),
         studio_url=studio_url,
         allow_blocking=allow_blocking,
     )

libs/cli/langgraph_cli/config.py

@@ -778,7 +778,22 @@ def _update_graph_paths(
         FileNotFoundError: If the local file (module) does not actually exist on disk.
         IsADirectoryError: If `module_str` points to a directory instead of a file.
     """
-    for graph_id, import_str in config["graphs"].items():
+    for graph_id, data in config["graphs"].items():
+        if isinstance(data, dict):
+            # Then we're looking for a 'path' key
+            if "path" not in data:
+                raise ValueError(
+                    f"Graph '{graph_id}' must contain a 'path' key if "
+                    f" it is a dictionary."
+                )
+            import_str = data["path"]
+        elif isinstance(data, str):
+            import_str = data
+        else:
+            raise ValueError(
+                f"Graph '{graph_id}' must be a string or a dictionary with a 'path' key."
+            )
+
         module_str, _, attr_str = import_str.partition(":")
         if not module_str or not attr_str:
             message = (
@@ -818,7 +833,10 @@ def _update_graph_paths(
                             "Add its containing package to 'dependencies' list."
                         )
             # update the config
-            config["graphs"][graph_id] = f"{module_str}:{attr_str}"
+            if isinstance(data, dict):
+                config["graphs"][graph_id]["path"] = f"{module_str}:{attr_str}"
+            else:
+                config["graphs"][graph_id] = f"{module_str}:{attr_str}"
 
 
 def _update_auth_path(
@@ -915,6 +933,66 @@ def _update_http_app_path(
         http_config["app"] = f"{module_str}:{attr_str}"
 
 
+def _get_node_pm_install_cmd(config_path: pathlib.Path, config: Config) -> str:
+    def test_file(file_name):
+        full_path = config_path.parent / file_name
+        try:
+            return full_path.is_file()
+        except OSError:
+            return False
+
+    # inspired by `package-manager-detector`
+    def get_pkg_manager_name():
+        try:
+            with open(config_path.parent / "package.json") as f:
+                pkg = json.load(f)
+
+                if (pkg_manager_name := pkg.get("packageManager")) and isinstance(
+                    pkg_manager_name, str
+                ):
+                    return pkg_manager_name.lstrip("^").split("@")[0]
+
+                if (
+                    dev_engine_name := (
+                        (pkg.get("devEngines") or {}).get("packageManager") or {}
+                    ).get("name")
+                ) and isinstance(dev_engine_name, str):
+                    return dev_engine_name
+
+                return None
+        except Exception:
+            return None
+
+    npm, yarn, pnpm, bun = [
+        test_file("package-lock.json"),
+        test_file("yarn.lock"),
+        test_file("pnpm-lock.yaml"),
+        test_file("bun.lockb"),
+    ]
+
+    if yarn:
+        install_cmd = "yarn install --frozen-lockfile"
+    elif pnpm:
+        install_cmd = "pnpm i --frozen-lockfile"
+    elif npm:
+        install_cmd = "npm ci"
+    elif bun:
+        install_cmd = "bun i"
+    else:
+        pkg_manager_name = get_pkg_manager_name()
+
+        if pkg_manager_name == "yarn":
+            install_cmd = "yarn install"
+        elif pkg_manager_name == "pnpm":
+            install_cmd = "pnpm i"
+        elif pkg_manager_name == "bun":
+            install_cmd = "bun i"
+        else:
+            install_cmd = "npm i"
+
+    return install_cmd
+
+
 def python_config_to_docker(
     config_path: pathlib.Path, config: Config, base_image: str
 ) -> tuple[str, dict[str, str]]:
@@ -995,10 +1073,32 @@ ADD {relpath} /deps/{name}
         for fullpath, (relpath, name) in local_deps.real_pkgs.items()
     )
 
+    ui_inst_str: str = ""
+    install_node_str: str = ""
+
+    if config.get("ui") and local_deps.working_dir:
+        install_node_str = "RUN /storage/install-node.sh"
+
+        ui_inst: list[str] = []
+        ui_inst.append(f"ENV LANGGRAPH_UI='{json.dumps(config['ui'])}'")
+        if config.get("ui_config"):
+            ui_inst.append(
+                f"ENV LANGGRAPH_UI_CONFIG='{json.dumps(config['ui_config'])}'"
+            )
+
+        ui_inst.append(
+            f"RUN cd {local_deps.working_dir} && {_get_node_pm_install_cmd(config_path, config)} && tsx /api/langgraph_api/js/build.mts",
+        )
+
+        ui_inst_str = f"""# -- Installing UI dependencies --
+{os.linesep.join(ui_inst)}
+# -- End of UI dependencies install --"""
+
     installs = f"{os.linesep}{os.linesep}".join(
         filter(
             None,
             [
+                install_node_str,
                 pip_config_file_str,
                 pip_pkgs_str,
                 pip_reqs_str,
@@ -1039,6 +1139,8 @@ ADD {relpath} /deps/{name}
         "# -- End of local dependencies install --",
         os.linesep.join(env_vars),
         "",
+        ui_inst_str,
+        "",
         f"WORKDIR {local_deps.working_dir}" if local_deps.working_dir else "",
     ]
 
@@ -1059,62 +1161,7 @@ def node_config_to_docker(
     config_path: pathlib.Path, config: Config, base_image: str
 ) -> tuple[str, dict[str, str]]:
     faux_path = f"/deps/{config_path.parent.name}"
-
-    def test_file(file_name):
-        full_path = config_path.parent / file_name
-        try:
-            return full_path.is_file()
-        except OSError:
-            return False
-
-    # inspired by `package-manager-detector`
-    def get_pkg_manager_name():
-        try:
-            with open(config_path.parent / "package.json") as f:
-                pkg = json.load(f)
-
-                if (pkg_manager_name := pkg.get("packageManager")) and isinstance(
-                    pkg_manager_name, str
-                ):
-                    return pkg_manager_name.lstrip("^").split("@")[0]
-
-                if (
-                    dev_engine_name := (
-                        (pkg.get("devEngines") or {}).get("packageManager") or {}
-                    ).get("name")
-                ) and isinstance(dev_engine_name, str):
-                    return dev_engine_name
-
-                return None
-        except Exception:
-            return None
-
-    npm, yarn, pnpm, bun = [
-        test_file("package-lock.json"),
-        test_file("yarn.lock"),
-        test_file("pnpm-lock.yaml"),
-        test_file("bun.lockb"),
-    ]
-
-    if yarn:
-        install_cmd = "yarn install --frozen-lockfile"
-    elif pnpm:
-        install_cmd = "pnpm i --frozen-lockfile"
-    elif npm:
-        install_cmd = "npm ci"
-    elif bun:
-        install_cmd = "bun i"
-    else:
-        pkg_manager_name = get_pkg_manager_name()
-
-        if pkg_manager_name == "yarn":
-            install_cmd = "yarn install"
-        elif pkg_manager_name == "pnpm":
-            install_cmd = "pnpm i"
-        elif pkg_manager_name == "bun":
-            install_cmd = "bun i"
-        else:
-            install_cmd = "npm i"
+    install_cmd = _get_node_pm_install_cmd(config_path, config)
     store_config = config.get("store")
     env_additional_config = (
         ""

libs/cli/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langgraph-cli"
-version = "0.1.83"
+version = "0.1.89"
 description = "CLI for interacting with LangGraph API"
 authors = []
 license = "MIT"

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

@@ -196,6 +196,50 @@ def test_dockerfile_command_basic() -> None:
         assert save_path.exists()
 
 
+def test_dockerfile_command_new_style_config() -> None:
+    """Test `dockerfile` command with a new style config.
+
+    This config format allows specifying agent data as a dictionary.
+    {
+        "graphs": {
+            "agent1": {
+                "path": ... # path to graph definition,
+                ... # other fields
+            }
+        }
+    }
+    """
+    runner = CliRunner()
+    config_content = {
+        "dependencies": ["./my_agent"],
+        "graphs": {
+            "agent": {
+                "path": "./my_agent/agent.py:graph",
+                "description": "This is a test agent",
+            }
+        },
+        "env": ".env",
+    }
+    with temporary_config_folder(config_content) as temp_dir:
+        save_path = temp_dir / "Dockerfile"
+        # Add agent.py file
+        agent_path = temp_dir / "my_agent" / "agent.py"
+        agent_path.parent.mkdir(parents=True, exist_ok=True)
+        agent_path.touch()
+
+        result = runner.invoke(
+            cli,
+            ["dockerfile", str(save_path), "--config", str(temp_dir / "config.json")],
+        )
+
+        # Assert command was successful
+        assert result.exit_code == 0, result.output
+        assert "✅ Created: Dockerfile" in result.output
+
+        # Check if Dockerfile was created
+        assert save_path.exists()
+
+
 def test_dockerfile_command_with_docker_compose() -> None:
     """Test the 'dockerfile' command with Docker Compose configuration."""
     runner = CliRunner()

libs/cli/tests/unit_tests/test_config.py

@@ -494,6 +494,49 @@ RUN (test ! -f /api/langgraph_api/js/build.mts && echo "Prebuild script not foun
     assert additional_contexts == {}
 
 
+def test_config_to_docker_gen_ui_python():
+    graphs = {"agent": "./agent.py:graph"}
+    actual_docker_stdin, additional_contexts = config_to_docker(
+        PATH_TO_CONFIG,
+        validate_config(
+            {
+                "dependencies": ["."],
+                "graphs": graphs,
+                "ui": {"agent": "./graphs/agent.ui.jsx"},
+                "ui_config": {"shared": ["nuqs"]},
+            }
+        ),
+        "langchain/langgraph-api",
+    )
+
+    expected_docker_stdin = """FROM langchain/langgraph-api:3.11
+RUN /storage/install-node.sh
+# -- Adding non-package dependency unit_tests --
+ADD . /deps/__outer_unit_tests/unit_tests
+RUN set -ex && \\
+    for line in '[project]' \\
+                'name = "unit_tests"' \\
+                'version = "0.1"' \\
+                '[tool.setuptools.package-data]' \\
+                '"*" = ["**/*"]'; do \\
+        echo "$line" >> /deps/__outer_unit_tests/pyproject.toml; \\
+    done
+# -- End of non-package dependency unit_tests --
+# -- Installing all local dependencies --
+RUN PYTHONDONTWRITEBYTECODE=1 pip install --no-cache-dir -c /api/constraints.txt -e /deps/*
+# -- End of local dependencies install --
+ENV LANGSERVE_GRAPHS='{"agent": "/deps/__outer_unit_tests/unit_tests/agent.py:graph"}'
+# -- Installing UI dependencies --
+ENV LANGGRAPH_UI='{"agent": "./graphs/agent.ui.jsx"}'
+ENV LANGGRAPH_UI_CONFIG='{"shared": ["nuqs"]}'
+RUN cd /deps/__outer_unit_tests/unit_tests && npm i && tsx /api/langgraph_api/js/build.mts
+# -- End of UI dependencies install --
+WORKDIR /deps/__outer_unit_tests/unit_tests"""
+
+    assert clean_empty_lines(actual_docker_stdin) == expected_docker_stdin
+    assert additional_contexts == {}
+
+
 # config_to_compose
 def test_config_to_compose_simple_config():
     graphs = {"agent": "./agent.py:graph"}

libs/langgraph/bench/__main__.py

@@ -9,6 +9,7 @@ from bench.fanout_to_subgraph import fanout_to_subgraph, fanout_to_subgraph_sync
 from bench.pydantic_state import pydantic_state
 from bench.react_agent import react_agent
 from bench.sequential import create_sequential
+from bench.wide_dict import wide_dict
 from bench.wide_state import wide_state
 from langgraph.checkpoint.memory import MemorySaver
 from langgraph.graph import StateGraph
@@ -251,6 +252,102 @@ benchmarks = (
             ]
         },
     ),
+    (
+        "wide_dict_25x300",
+        wide_dict(300).compile(checkpointer=None),
+        wide_dict(300).compile(checkpointer=None),
+        {
+            "messages": [
+                {
+                    str(i) * 10: {
+                        str(j) * 10: ["hi?" * 10, True, 1, 6327816386138, None] * 5
+                        for j in range(5)
+                    }
+                    for i in range(5)
+                }
+            ]
+        },
+    ),
+    (
+        "wide_dict_25x300_checkpoint",
+        wide_dict(300).compile(checkpointer=MemorySaver()),
+        wide_dict(300).compile(checkpointer=MemorySaver()),
+        {
+            "messages": [
+                {
+                    str(i) * 10: {
+                        str(j) * 10: ["hi?" * 10, True, 1, 6327816386138, None] * 5
+                        for j in range(5)
+                    }
+                    for i in range(5)
+                }
+            ]
+        },
+    ),
+    (
+        "wide_dict_15x600",
+        wide_dict(600).compile(checkpointer=None),
+        wide_dict(600).compile(checkpointer=None),
+        {
+            "messages": [
+                {
+                    str(i) * 10: {
+                        str(j) * 10: ["hi?" * 10, True, 1, 6327816386138, None] * 5
+                        for j in range(5)
+                    }
+                    for i in range(3)
+                }
+            ]
+        },
+    ),
+    (
+        "wide_dict_15x600_checkpoint",
+        wide_dict(600).compile(checkpointer=MemorySaver()),
+        wide_dict(600).compile(checkpointer=MemorySaver()),
+        {
+            "messages": [
+                {
+                    str(i) * 10: {
+                        str(j) * 10: ["hi?" * 10, True, 1, 6327816386138, None] * 5
+                        for j in range(5)
+                    }
+                    for i in range(3)
+                }
+            ]
+        },
+    ),
+    (
+        "wide_dict_9x1200",
+        wide_dict(1200).compile(checkpointer=None),
+        wide_dict(1200).compile(checkpointer=None),
+        {
+            "messages": [
+                {
+                    str(i) * 10: {
+                        str(j) * 10: ["hi?" * 10, True, 1, 6327816386138, None] * 5
+                        for j in range(3)
+                    }
+                    for i in range(3)
+                }
+            ]
+        },
+    ),
+    (
+        "wide_dict_9x1200_checkpoint",
+        wide_dict(1200).compile(checkpointer=MemorySaver()),
+        wide_dict(1200).compile(checkpointer=MemorySaver()),
+        {
+            "messages": [
+                {
+                    str(i) * 10: {
+                        str(j) * 10: ["hi?" * 10, True, 1, 6327816386138, None] * 5
+                        for j in range(3)
+                    }
+                    for i in range(3)
+                }
+            ]
+        },
+    ),
     (
         "sequential_10",
         create_sequential(10).compile(),

libs/langgraph/bench/wide_dict.py

@@ -0,0 +1,153 @@
+import operator
+from functools import partial
+from random import choice
+from typing import Annotated, Optional, Sequence
+
+from typing_extensions import TypedDict
+
+from langgraph.constants import END, START
+from langgraph.graph.state import StateGraph
+
+
+def wide_dict(n: int) -> StateGraph:
+    class State(TypedDict):
+        messages: Annotated[list, operator.add]
+        trigger_events: Annotated[list, operator.add]
+        """The external events that are converted by the graph."""
+        primary_issue_medium: Annotated[str, lambda x, y: y or x]
+        autoresponse: Annotated[Optional[dict], lambda _, y: y]  # Always overwrite
+        issue: Annotated[dict | None, lambda x, y: y if y else x]
+        relevant_rules: Optional[list[dict]]
+        """SOPs fetched from the rulebook that are relevant to the current conversation."""
+        memory_docs: Optional[list[dict]]
+        """Memory docs fetched from the memory service that are relevant to the current conversation."""
+        categorizations: Annotated[list[dict], operator.add]
+        """The issue categorizations auto-generated by the AI."""
+        responses: Annotated[list[dict], operator.add]
+        """The draft responses recommended by the AI."""
+
+        user_info: Annotated[Optional[dict], lambda x, y: y if y is not None else x]
+        """The current user state (by email)."""
+        crm_info: Annotated[Optional[dict], lambda x, y: y if y is not None else x]
+        """The CRM information for organization the current user is from."""
+        email_thread_id: Annotated[
+            Optional[str], lambda x, y: y if y is not None else x
+        ]
+        """The current email thread ID."""
+        slack_participants: Annotated[dict, operator.or_]
+        """The growing list of current slack participants."""
+        bot_id: Optional[str]
+        """The ID of the bot user in the slack channel."""
+        notified_assignees: Annotated[dict, operator.or_]
+
+    list_fields = {
+        "messages",
+        "trigger_events",
+        "categorizations",
+        "responses",
+        "memory_docs",
+        "relevant_rules",
+    }
+    dict_fields = {
+        "user_info",
+        "crm_info",
+        "slack_participants",
+        "notified_assignees",
+        "autoresponse",
+        "issue",
+    }
+
+    def read_write(read: str, write: Sequence[str], input: State) -> dict:
+        val = input.get(read)
+        val = {val: val} if isinstance(val, str) else val
+        val_single = val[-1] if isinstance(val, list) else val
+        val_list = val if isinstance(val, list) else [val]
+        return {
+            k: val_list
+            if k in list_fields
+            else val_single
+            if k in dict_fields
+            else "".join(choice("abcdefghijklmnopqrstuvwxyz") for _ in range(n))
+            for k in write
+        }
+
+    builder = StateGraph(State)
+    builder.add_edge(START, "one")
+    builder.add_node(
+        "one",
+        partial(read_write, "messages", ["trigger_events", "primary_issue_medium"]),
+    )
+    builder.add_edge("one", "two")
+    builder.add_node(
+        "two",
+        partial(read_write, "trigger_events", ["autoresponse", "issue"]),
+    )
+    builder.add_edge("two", "three")
+    builder.add_edge("two", "four")
+    builder.add_node(
+        "three",
+        partial(read_write, "autoresponse", ["relevant_rules"]),
+    )
+    builder.add_node(
+        "four",
+        partial(
+            read_write,
+            "trigger_events",
+            ["categorizations", "responses", "memory_docs"],
+        ),
+    )
+    builder.add_node(
+        "five",
+        partial(
+            read_write,
+            "categorizations",
+            [
+                "user_info",
+                "crm_info",
+                "email_thread_id",
+                "slack_participants",
+                "bot_id",
+                "notified_assignees",
+            ],
+        ),
+    )
+    builder.add_edge(["three", "four"], "five")
+    builder.add_edge("five", "six")
+    builder.add_node(
+        "six",
+        partial(read_write, "responses", ["messages"]),
+    )
+    builder.add_conditional_edges(
+        "six", lambda state: END if len(state["messages"]) > n else "one"
+    )
+
+    return builder
+
+
+if __name__ == "__main__":
+    import asyncio
+
+    import uvloop
+
+    from langgraph.checkpoint.memory import MemorySaver
+
+    graph = wide_dict(1000).compile(checkpointer=MemorySaver())
+    input = {
+        "messages": [
+            {
+                str(i) * 10: {
+                    str(j) * 10: ["hi?" * 10, True, 1, 6327816386138, None] * 5
+                    for j in range(50)
+                }
+                for i in range(50)
+            }
+        ]
+    }
+    config = {"configurable": {"thread_id": "1"}, "recursion_limit": 20000000000}
+
+    async def run():
+        async for c in graph.astream(input, config=config):
+            print(c.keys())
+
+    uvloop.install()
+    asyncio.run(run())

libs/langgraph/bench/wide_state.py

@@ -1,6 +1,7 @@
 import operator
 from dataclasses import dataclass, field
 from functools import partial
+from random import choice
 from typing import Annotated, Optional, Sequence
 
 from langgraph.constants import END, START
@@ -49,12 +50,34 @@ def wide_state(n: int) -> StateGraph:
         """The ID of the bot user in the slack channel."""
         notified_assignees: Annotated[dict, operator.or_] = field(default_factory=dict)
 
+    list_fields = {
+        "messages",
+        "trigger_events",
+        "categorizations",
+        "responses",
+        "memory_docs",
+        "relevant_rules",
+    }
+    dict_fields = {
+        "user_info",
+        "crm_info",
+        "slack_participants",
+        "notified_assignees",
+        "autoresponse",
+        "issue",
+    }
+
     def read_write(read: str, write: Sequence[str], input: State) -> dict:
         val = getattr(input, read)
+        val = {val: val} if isinstance(val, str) else val
         val_single = val[-1] if isinstance(val, list) else val
         val_list = val if isinstance(val, list) else [val]
         return {
-            k: val_list if isinstance(getattr(input, k), list) else val_single
+            k: val_list
+            if k in list_fields
+            else val_single
+            if k in dict_fields
+            else "".join(choice("abcdefghijklmnopqrstuvwxyz") for _ in range(n))
             for k in write
         }
 

libs/langgraph/langgraph/graph/schema_utils.py

@@ -1,210 +1,55 @@
 import logging
 import weakref
-from inspect import isclass
 from typing import (
     Any,
     Callable,
     Optional,
     Type,
-    Union,
-    get_args,
-    get_origin,
-    get_type_hints,
 )
 
 from pydantic import BaseModel
 from pydantic.v1 import BaseModel as BaseModelV1
-from typing_extensions import Annotated
 
 logger = logging.getLogger(__name__)
 
 
-_cache: weakref.WeakKeyDictionary[Type[Any], dict[int, "SchemaCoercionMapper"]] = (
+_cache: weakref.WeakKeyDictionary[Type[Any], "SchemaCoercionMapper"] = (
     weakref.WeakKeyDictionary()
 )
 
 
 class SchemaCoercionMapper:
+    __slots__ = ("_inited", "schema", "_fields", "_construct", "_field_coercers")
+
     def __new__(
         cls,
         schema: Type[Any],
-        type_hints: Optional[dict[str, Any]] = None,
-        max_depth: int = 12,
+        **kwargs: Any,
     ) -> "SchemaCoercionMapper":
-        if schema not in _cache:
-            _cache[schema] = {}
-        if max_depth in _cache[schema]:
-            return _cache[schema][max_depth]
-
+        if schema in _cache:
+            return _cache[schema]
         inst = super().__new__(cls)
-        _cache[schema][max_depth] = inst
+        _cache[schema] = inst
         return inst
 
     def __init__(
         self,
         schema: Type[Any],
-        type_hints: Optional[dict[str, Any]] = None,
-        max_depth: int = 12,
+        **kwargs: Any,
     ):
         if hasattr(self, "_inited"):
             return
         self._inited = True
-        self.schema = schema
-        self.type_hints = (
-            type_hints
-            if type_hints is not None
-            else get_type_hints(schema, localns={schema.__name__: schema})
-        )
-        self.max_depth = max_depth
+        if issubclass(schema, BaseModelV1):
+            self._construct: Callable[..., Any] = schema.parse_obj
 
-        if issubclass(schema, BaseModel):
-            self._fields = {
-                n: self.type_hints.get(n, f.annotation)
-                for n, f in schema.model_fields.items()
-            }
-            self._construct: Callable[..., Any] = schema.model_construct
+        elif issubclass(schema, BaseModel):
+            self._construct = schema.model_validate
 
-        elif issubclass(schema, BaseModelV1):
-            self._fields = {
-                n: self.type_hints.get(n, f.annotation)
-                for n, f in schema.__fields__.items()
-            }
-            self._construct = schema.construct
         else:
             raise TypeError("Schema is neither valid Pydantic v1 nor v2 model.")
-        self._field_coercers: Optional[dict[str, Callable[[Any, Any], Any]]] = None
 
     def __call__(self, input_data: Any, depth: Optional[int] = None) -> Any:
-        return self.coerce(input_data, depth)
-
-    def coerce(self, input_data: Any, depth: Optional[int] = None) -> Any:
-        if depth is None:
-            depth = self.max_depth
-        if not isinstance(input_data, dict) or depth <= 0:
+        if not isinstance(input_data, dict):
             return input_data
-        processed = {}
-        if self._field_coercers is None:
-            self._field_coercers = {
-                n: self._build_coercer(t, depth - 1) for n, t in self._fields.items()
-            }
-        for k, v in input_data.items():
-            fn = self._field_coercers.get(k)
-            processed[k] = fn(v, depth - 1) if fn else v
-        return self._construct(**processed)
-
-    def _build_coercer(
-        self, field_type: Any, depth: int, throw: bool = False
-    ) -> Callable[[Any, Any], Any]:
-        if depth == 0:
-            return self._passthrough
-        origin = get_origin(field_type)
-
-        if origin is Annotated:
-            real_type, *_ = get_args(field_type)
-            sub = self._build_coercer(real_type, depth - 1)
-            return lambda v, d: sub(v, d)
-        if isclass(field_type):
-            is_class_ = True
-            try:
-                is_base_model = issubclass(field_type, BaseModel)
-            except TypeError:
-                is_class_ = False
-                is_base_model = False
-
-            if is_base_model:
-                mapper = SchemaCoercionMapper(field_type, max_depth=depth - 1)
-                return lambda v, d: mapper.coerce(v, d) if isinstance(v, dict) else v
-            if is_class_ and issubclass(field_type, BaseModelV1):
-                mapper = SchemaCoercionMapper(field_type, max_depth=depth - 1)
-                return lambda v, d: mapper.coerce(v, d) if isinstance(v, dict) else v
-        if origin is list or field_type is list:
-            args = get_args(field_type)
-            if len(args) != 1:
-                return lambda v, d: v
-            sub = self._build_coercer(args[0], depth - 1)
-
-            def list_coercer(v: Any, d: Any) -> Any:
-                if not isinstance(v, (list, tuple)):
-                    return v
-                return [sub(x, d - 1) for x in v]
-
-            return list_coercer
-        if origin is set or field_type is set:
-            args = get_args(field_type)
-            if len(args) != 1:
-                return lambda v, d: v
-            sub = self._build_coercer(args[0], depth - 1)
-
-            def set_coercer(v: Any, d: Any) -> Any:
-                if not isinstance(v, (list, tuple, set)):
-                    return v
-                return {sub(x, d - 1) for x in v}
-
-            return set_coercer
-        if origin is dict or field_type is dict:
-            args = get_args(field_type)
-            if len(args) != 2:
-
-                def dict_coercer(v: Any, d: Any) -> Any:
-                    if not isinstance(v, dict):
-                        if throw:
-                            raise TypeError("Expected dict, got %s" % type(v))
-                    return v
-
-                return dict_coercer
-            k_sub = self._build_coercer(args[0], depth - 1)
-            v_sub = self._build_coercer(args[1], depth - 1)
-
-            def dict_coercer(v: Any, d: Any) -> Any:
-                if not isinstance(v, dict):
-                    if throw:
-                        raise TypeError("Expected dict, got %s" % type(v))
-                    return v
-                return {k_sub(k, d - 1): v_sub(val, d - 1) for k, val in v.items()}
-
-            return dict_coercer
-
-        if origin is tuple:
-            targs = get_args(field_type)
-            if not targs:
-                return lambda v, d: v
-            subs = [self._build_coercer(a, depth - 1) for a in targs]
-
-            def tuple_coercer(v: Any, d: Any) -> Any:
-                if not isinstance(v, (list, tuple)):
-                    return v
-                out = []
-                for i, sp in enumerate(subs):
-                    out.append(sp(v[i] if i < len(v) else None, d - 1))
-                return tuple(out)
-
-            return tuple_coercer
-        if origin is Union:
-            uargs = get_args(field_type)
-            subs, none_in_union = [], False
-            for ix, arg in enumerate(uargs):
-                if arg is type(None):
-                    none_in_union = True
-                else:
-                    subs.append(
-                        self._build_coercer(arg, depth - 1, throw=ix < len(uargs) - 1)
-                    )
-
-            def union_coercer(v: Any, d: Any) -> Any:
-                if v is None and none_in_union:
-                    return None
-                err = None
-                for sp in subs:
-                    try:
-                        return sp(v, d - 1)
-                    except TypeError as e:
-                        err = e
-                if err:
-                    raise err
-                return v
-
-            return union_coercer
-        return self._passthrough
-
-    def _passthrough(self, v: Any, d: Any) -> Any:
-        return v
+        return self._construct(input_data)

libs/langgraph/langgraph/graph/state.py

@@ -1060,7 +1060,7 @@ def _pick_mapper(
         if issubclass(schema, dict):
             return None
         if issubclass(schema, (BaseModel, BaseModelV1)):
-            return SchemaCoercionMapper(schema, type_hints)
+            return SchemaCoercionMapper(schema)
     return partial(_coerce_state, schema)
 
 

libs/langgraph/langgraph/graph/ui.py

@@ -0,0 +1,206 @@
+from typing import Any, Literal, Optional, Union
+from uuid import uuid4
+
+from langchain_core.messages import AnyMessage
+from typing_extensions import TypedDict
+
+from langgraph.constants import CONF, CONFIG_KEY_SEND
+from langgraph.utils.config import get_config, get_stream_writer
+
+
+class UIMessage(TypedDict):
+    """A message type for UI updates in LangGraph.
+
+    This TypedDict represents a UI message that can be sent to update the UI state.
+    It contains information about the UI component to render and its properties.
+
+    Attributes:
+        type: Literal type indicating this is a UI message.
+        id: Unique identifier for the UI message.
+        name: Name of the UI component to render.
+        props: Properties to pass to the UI component.
+        metadata: Additional metadata about the UI message.
+    """
+
+    type: Literal["ui"]
+    id: str
+    name: str
+    props: dict[str, Any]
+    metadata: dict[str, Any]
+
+
+class RemoveUIMessage(TypedDict):
+    """A message type for removing UI components in LangGraph.
+
+    This TypedDict represents a message that can be sent to remove a UI component
+    from the current state.
+
+    Attributes:
+        type: Literal type indicating this is a remove-ui message.
+        id: Unique identifier of the UI message to remove.
+    """
+
+    type: Literal["remove-ui"]
+    id: str
+
+
+AnyUIMessage = Union[UIMessage, RemoveUIMessage]
+
+
+def push_ui_message(
+    name: str,
+    props: dict[str, Any],
+    *,
+    id: Optional[str] = None,
+    metadata: Optional[dict[str, Any]] = None,
+    message: Optional[AnyMessage] = None,
+    state_key: str = "ui",
+) -> UIMessage:
+    """Push a new UI message to update the UI state.
+
+    This function creates and sends a UI message that will be rendered in the UI.
+    It also updates the graph state with the new UI message.
+
+    Args:
+        name: Name of the UI component to render.
+        props: Properties to pass to the UI component.
+        id: Optional unique identifier for the UI message.
+            If not provided, a random UUID will be generated.
+        metadata: Optional additional metadata about the UI message.
+        message: Optional message object to associate with the UI message.
+        state_key: Key in the graph state where the UI messages are stored.
+            Defaults to "ui".
+
+    Returns:
+        The created UI message.
+
+    Example:
+
+    .. code-block:: python
+
+        push_ui_message(
+            name="component-name",
+            props={"content": "Hello world"},
+        )
+
+    """
+    writer = get_stream_writer()
+    config = get_config()
+
+    message_id = None
+    if message:
+        if isinstance(message, dict) and "id" in message:
+            message_id = message.get("id")
+        elif hasattr(message, "id"):
+            message_id = message.id
+
+    evt: UIMessage = {
+        "type": "ui",
+        "id": id or str(uuid4()),
+        "name": name,
+        "props": props,
+        "metadata": {
+            **(config.get("metadata") or {}),
+            "tags": config.get("tags", None),
+            "name": config.get("run_name", None),
+            "run_id": config.get("run_id", None),
+            **(metadata or {}),
+            **({"message_id": message_id} if message_id else {}),
+        },
+    }
+
+    writer(evt)
+    config[CONF][CONFIG_KEY_SEND]([(state_key, evt)])
+
+    return evt
+
+
+def delete_ui_message(id: str, *, state_key: str = "ui") -> RemoveUIMessage:
+    """Delete a UI message by ID from the UI state.
+
+    This function creates and sends a message to remove a UI component from the current state.
+    It also updates the graph state to remove the UI message.
+
+    Args:
+        id: Unique identifier of the UI component to remove.
+        state_key: Key in the graph state where the UI messages are stored. Defaults to "ui".
+
+    Returns:
+        The remove UI message.
+
+    Example:
+
+    .. code-block:: python
+
+        delete_ui_message("message-123")
+
+    """
+    writer = get_stream_writer()
+    config = get_config()
+
+    evt: RemoveUIMessage = {"type": "remove-ui", "id": id}
+
+    writer(evt)
+    config[CONF][CONFIG_KEY_SEND]([(state_key, evt)])
+
+    return evt
+
+
+def ui_message_reducer(
+    left: Union[list[AnyUIMessage], AnyUIMessage],
+    right: Union[list[AnyUIMessage], AnyUIMessage],
+) -> list[AnyUIMessage]:
+    """Merge two lists of UI messages, supporting removing UI messages.
+
+    This function combines two lists of UI messages, handling both regular UI messages
+    and `remove-ui` messages. When a `remove-ui` message is encountered, it removes any
+    UI message with the matching ID from the current state.
+
+    Args:
+        left: First list of UI messages or single UI message.
+        right: Second list of UI messages or single UI message.
+
+    Returns:
+        Combined list of UI messages with removals applied.
+
+    Example:
+
+    .. code-block:: python
+
+        messages = ui_message_reducer(
+            [{"type": "ui", "id": "1", "name": "Chat", "props": {}}],
+            {"type": "remove-ui", "id": "1"}
+        )
+
+    """
+    if not isinstance(left, list):
+        left = [left]
+
+    if not isinstance(right, list):
+        right = [right]
+
+    # merge messages
+    merged = left.copy()
+    merged_by_id = {m.get("id"): i for i, m in enumerate(merged)}
+    ids_to_remove = set()
+
+    for msg in right:
+        msg_id = msg.get("id")
+
+        if (existing_idx := merged_by_id.get(msg_id)) is not None:
+            if msg.get("type") == "remove-ui":
+                ids_to_remove.add(msg_id)
+            else:
+                ids_to_remove.discard(msg_id)
+                merged[existing_idx] = msg
+        else:
+            if msg.get("type") == "remove-ui":
+                raise ValueError(
+                    f"Attempting to delete an UI message with an ID that doesn't exist ('{msg_id}')"
+                )
+
+            merged_by_id[msg_id] = len(merged)
+            merged.append(msg)
+
+    merged = [m for m in merged if m.get("id") not in ids_to_remove]
+    return merged

libs/langgraph/langgraph/pregel/__init__.py

@@ -39,7 +39,6 @@ from langchain_core.runnables.utils import (
     ConfigurableFieldSpec,
     get_unique_config_specs,
 )
-from langchain_core.tracers._streaming import _StreamingCallbackHandler
 from pydantic import BaseModel
 from typing_extensions import Self
 
@@ -125,6 +124,11 @@ from langgraph.utils.fields import get_enhanced_type_hints
 from langgraph.utils.pydantic import create_model, is_supported_by_pydantic
 from langgraph.utils.queue import AsyncQueue, SyncQueue  # type: ignore[attr-defined]
 
+try:
+    from langchain_core.tracers._streaming import _StreamingCallbackHandler
+except ImportError:
+    _StreamingCallbackHandler = None  # type: ignore
+
 WriteValue = Union[Callable[[Input], Output], Any]
 
 
@@ -2529,13 +2533,17 @@ class Pregel(PregelProtocol):
             run_id=config.get("run_id"),
         )
         # if running from astream_log() run each proc with streaming
-        do_stream = next(
-            (
-                cast(_StreamingCallbackHandler, h)
-                for h in run_manager.handlers
-                if isinstance(h, _StreamingCallbackHandler)
-            ),
-            None,
+        do_stream = (
+            next(
+                (
+                    cast(_StreamingCallbackHandler, h)
+                    for h in run_manager.handlers
+                    if isinstance(h, _StreamingCallbackHandler)
+                ),
+                None,
+            )
+            if _StreamingCallbackHandler is not None
+            else False
         )
         try:
             # assign defaults

libs/langgraph/langgraph/pregel/messages.py

@@ -7,6 +7,7 @@ from typing import (
     List,
     Optional,
     Sequence,
+    TypeVar,
     Union,
     cast,
 )
@@ -15,11 +16,16 @@ from uuid import UUID, uuid4
 from langchain_core.callbacks import BaseCallbackHandler
 from langchain_core.messages import BaseMessage
 from langchain_core.outputs import ChatGenerationChunk, LLMResult
-from langchain_core.tracers._streaming import T, _StreamingCallbackHandler
 
 from langgraph.constants import NS_SEP, TAG_HIDDEN, TAG_NOSTREAM
 from langgraph.types import StreamChunk
 
+try:
+    from langchain_core.tracers._streaming import _StreamingCallbackHandler
+except ImportError:
+    _StreamingCallbackHandler = object  # type: ignore
+
+T = TypeVar("T")
 Meta = tuple[tuple[str, ...], dict[str, Any]]
 
 

libs/langgraph/langgraph/pregel/remote.py

@@ -10,7 +10,6 @@ from typing import (
     cast,
 )
 
-import orjson
 from langchain_core.runnables import RunnableConfig
 from langchain_core.runnables.graph import (
     Edge as DrawableEdge,
@@ -35,6 +34,8 @@ from typing_extensions import Self
 from langgraph.checkpoint.base import CheckpointMetadata
 from langgraph.constants import (
     CONF,
+    CONFIG_KEY_CHECKPOINT_ID,
+    CONFIG_KEY_CHECKPOINT_MAP,
     CONFIG_KEY_CHECKPOINT_NS,
     CONFIG_KEY_STREAM,
     INTERRUPT,
@@ -46,6 +47,14 @@ from langgraph.pregel.types import All, PregelTask, StateSnapshot, StreamMode
 from langgraph.types import Command, Interrupt, StreamProtocol
 from langgraph.utils.config import merge_configs
 
+CONF_DROPLIST = frozenset(
+    (
+        CONFIG_KEY_CHECKPOINT_MAP,
+        CONFIG_KEY_CHECKPOINT_ID,
+        CONFIG_KEY_CHECKPOINT_NS,
+    ),
+)
+
 
 class RemoteException(Exception):
     """Exception raised when an error occurs in the remote graph."""
@@ -290,47 +299,26 @@ class RemoteGraph(PregelProtocol):
         }
 
     def _sanitize_config(self, config: RunnableConfig) -> RunnableConfig:
-        reserved_configurable_keys = frozenset(
-            [
-                "callbacks",
-                "checkpoint_map",
-                "checkpoint_id",
-                "checkpoint_ns",
-            ]
-        )
-
-        def _sanitize_obj(obj: Any) -> Any:
-            """Remove non-JSON serializable fields from the given object."""
-            if isinstance(obj, dict):
-                return {k: _sanitize_obj(v) for k, v in obj.items()}
-            elif isinstance(obj, list):
-                return [_sanitize_obj(v) for v in obj]
-            else:
-                try:
-                    orjson.dumps(obj)
-                    return obj
-                except orjson.JSONEncodeError:
-                    return None
-
-        # Remove non-JSON serializable fields from the config.
-        config = _sanitize_obj(config)
-
-        # Only include configurable keys that are not reserved and
-        # not starting with "__pregel_" prefix.
-        new_configurable = {
-            k: v
-            for k, v in config["configurable"].items()
-            if k not in reserved_configurable_keys and not k.startswith("__pregel_")
-        }
-
-        sanitized: RunnableConfig = {
-            "tags": config.get("tags") or [],
-            "metadata": config.get("metadata") or {},
-            "configurable": new_configurable,
-        }
+        """Sanitize the config to remove non-serializable fields."""
+        sanitized: RunnableConfig = {}
         if "recursion_limit" in config:
             sanitized["recursion_limit"] = config["recursion_limit"]
-
+        if "tags" in config:
+            sanitized["tags"] = [tag for tag in config["tags"] if isinstance(tag, str)]
+        if "metadata" in config:
+            sanitized["metadata"] = {}
+            for k, v in config["metadata"].items():
+                if isinstance(k, str) and isinstance(v, (str, int, float, bool)):
+                    sanitized["metadata"][k] = v
+        if "configurable" in config:
+            sanitized["configurable"] = {}
+            for k, v in config["configurable"].items():
+                if (
+                    isinstance(k, str)
+                    and k not in CONF_DROPLIST
+                    and isinstance(v, (str, int, float, bool))
+                ):
+                    sanitized["configurable"][k] = v
         return sanitized
 
     def get_state(
@@ -654,9 +642,10 @@ class RemoteGraph(PregelProtocol):
             # raise interrupt or errors
             if chunk.event.startswith("updates"):
                 if isinstance(chunk.data, dict) and INTERRUPT in chunk.data:
-                    raise GraphInterrupt(
-                        [Interrupt(**i) for i in chunk.data[INTERRUPT]]
-                    )
+                    if caller_ns:
+                        raise GraphInterrupt(
+                            [Interrupt(**i) for i in chunk.data[INTERRUPT]]
+                        )
             elif chunk.event.startswith("error"):
                 raise RemoteException(chunk.data)
             # filter for what was actually requested
@@ -748,9 +737,10 @@ class RemoteGraph(PregelProtocol):
             # raise interrupt or errors
             if chunk.event.startswith("updates"):
                 if isinstance(chunk.data, dict) and INTERRUPT in chunk.data:
-                    raise GraphInterrupt(
-                        [Interrupt(**i) for i in chunk.data[INTERRUPT]]
-                    )
+                    if caller_ns:
+                        raise GraphInterrupt(
+                            [Interrupt(**i) for i in chunk.data[INTERRUPT]]
+                        )
             elif chunk.event.startswith("error"):
                 raise RemoteException(chunk.data)
             # filter for what was actually requested

libs/langgraph/langgraph/utils/runnable.py

@@ -36,7 +36,6 @@ from langchain_core.runnables.config import (
     var_child_runnable_config,
 )
 from langchain_core.runnables.utils import Input, Output
-from langchain_core.tracers._streaming import _StreamingCallbackHandler
 from typing_extensions import TypeGuard
 
 from langgraph.constants import (
@@ -54,6 +53,11 @@ from langgraph.utils.config import (
     patch_config,
 )
 
+try:
+    from langchain_core.tracers._streaming import _StreamingCallbackHandler
+except ImportError:
+    _StreamingCallbackHandler = None  # type: ignore
+
 
 def _set_config_context(
     config: RunnableConfig,
@@ -683,13 +687,15 @@ class RunnableSeq(Runnable):
                     iterator = step.stream(input, config, **kwargs)
                 else:
                     iterator = step.transform(iterator, config)
-            if stream_handler := next(
-                (
-                    cast(_StreamingCallbackHandler, h)
-                    for h in run_manager.handlers
-                    if isinstance(h, _StreamingCallbackHandler)
-                ),
-                None,
+            if _StreamingCallbackHandler is not None and (
+                stream_handler := next(
+                    (
+                        cast(_StreamingCallbackHandler, h)
+                        for h in run_manager.handlers
+                        if isinstance(h, _StreamingCallbackHandler)
+                    ),
+                    None,
+                )
             ):
                 # populates streamed_output in astream_log() output if needed
                 iterator = stream_handler.tap_output_iter(run_manager.run_id, iterator)
@@ -749,13 +755,15 @@ class RunnableSeq(Runnable):
                         aiterator = step.atransform(aiterator, config)
                     if hasattr(aiterator, "aclose"):
                         stack.push_async_callback(aiterator.aclose)
-                if stream_handler := next(
-                    (
-                        cast(_StreamingCallbackHandler, h)
-                        for h in run_manager.handlers
-                        if isinstance(h, _StreamingCallbackHandler)
-                    ),
-                    None,
+                if _StreamingCallbackHandler is not None and (
+                    stream_handler := next(
+                        (
+                            cast(_StreamingCallbackHandler, h)
+                            for h in run_manager.handlers
+                            if isinstance(h, _StreamingCallbackHandler)
+                        ),
+                        None,
+                    )
                 ):
                     # populates streamed_output in astream_log() output if needed
                     aiterator = stream_handler.tap_output_aiter(

libs/langgraph/poetry.lock

@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 2.0.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 2.0.0 and should not be changed by hand.
 
 [[package]]
 name = "aiosqlite"
@@ -946,14 +946,14 @@ testing = ["Django", "attrs", "colorama", "docopt", "pytest (<7.0.0)"]
 
 [[package]]
 name = "jinja2"
-version = "3.1.5"
+version = "3.1.6"
 description = "A very fast and expressive template engine."
 optional = false
 python-versions = ">=3.7"
 groups = ["dev"]
 files = [
-    {file = "jinja2-3.1.5-py3-none-any.whl", hash = "sha256:aba0f4dc9ed8013c424088f68a5c226f7d6097ed89b246d7749c2ec4175c6adb"},
-    {file = "jinja2-3.1.5.tar.gz", hash = "sha256:8fefff8dc3034e27bb80d67c671eb8a9bc424c0ef4c0826edbff304cceff43bb"},
+    {file = "jinja2-3.1.6-py3-none-any.whl", hash = "sha256:85ece4451f492d0c13c5dd7c13a64681a86afae63a5f347908daf103ce6d2f67"},
+    {file = "jinja2-3.1.6.tar.gz", hash = "sha256:0137fb05990d35f1275a587e9aee6d56da821fc83491a0fb838183be43f66d6d"},
 ]
 
 [package.dependencies]

libs/langgraph/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langgraph"
-version = "0.3.24"
+version = "0.3.26"
 description = "Building stateful, multi-actor applications with LLMs"
 authors = []
 license = "MIT"

libs/langgraph/tests/test_remote_graph.py

@@ -437,15 +437,17 @@ def test_stream():
         sync_client=mock_sync_client,
     )
 
-    # stream modes doesn't include 'updates'
-    stream_parts = []
+    # test raising graph interrupt if invoked as a subgraph
     with pytest.raises(GraphInterrupt) as exc:
         for stream_part in remote_pregel.stream(
             {"input": "data"},
-            config={"configurable": {"thread_id": "thread_1"}},
+            # pretend we invoked this as a subgraph
+            config={
+                "configurable": {"thread_id": "thread_1", "checkpoint_ns": "some_ns"}
+            },
             stream_mode="values",
         ):
-            stream_parts.append(stream_part)
+            pass
 
     assert exc.value.args[0] == [
         Interrupt(
@@ -456,6 +458,15 @@ def test_stream():
         )
     ]
 
+    # stream modes doesn't include 'updates'
+    stream_parts = []
+    for stream_part in remote_pregel.stream(
+        {"input": "data"},
+        config={"configurable": {"thread_id": "thread_1"}},
+        stream_mode="values",
+    ):
+        stream_parts.append(stream_part)
+
     assert stream_parts == [
         {"chunk": "data1"},
         {"chunk": "data2"},
@@ -470,62 +481,62 @@ def test_stream():
 
     # default stream_mode is updates
     stream_parts = []
-    with pytest.raises(GraphInterrupt):
-        for stream_part in remote_pregel.stream(
-            {"input": "data"},
-            config={"configurable": {"thread_id": "thread_1"}},
-        ):
-            stream_parts.append(stream_part)
+    for stream_part in remote_pregel.stream(
+        {"input": "data"},
+        config={"configurable": {"thread_id": "thread_1"}},
+    ):
+        stream_parts.append(stream_part)
 
     assert stream_parts == [
         {"chunk": "data3"},
         {"chunk": "data4"},
+        {"__interrupt__": ()},
     ]
 
     # list stream_mode includes mode names
     stream_parts = []
-    with pytest.raises(GraphInterrupt):
-        for stream_part in remote_pregel.stream(
-            {"input": "data"},
-            config={"configurable": {"thread_id": "thread_1"}},
-            stream_mode=["updates"],
-        ):
-            stream_parts.append(stream_part)
+    for stream_part in remote_pregel.stream(
+        {"input": "data"},
+        config={"configurable": {"thread_id": "thread_1"}},
+        stream_mode=["updates"],
+    ):
+        stream_parts.append(stream_part)
 
     assert stream_parts == [
         ("updates", {"chunk": "data3"}),
         ("updates", {"chunk": "data4"}),
+        ("updates", {"__interrupt__": ()}),
     ]
 
     # subgraphs + list modes
     stream_parts = []
-    with pytest.raises(GraphInterrupt):
-        for stream_part in remote_pregel.stream(
-            {"input": "data"},
-            config={"configurable": {"thread_id": "thread_1"}},
-            stream_mode=["updates"],
-            subgraphs=True,
-        ):
-            stream_parts.append(stream_part)
+    for stream_part in remote_pregel.stream(
+        {"input": "data"},
+        config={"configurable": {"thread_id": "thread_1"}},
+        stream_mode=["updates"],
+        subgraphs=True,
+    ):
+        stream_parts.append(stream_part)
 
     assert stream_parts == [
         ((), "updates", {"chunk": "data3"}),
         ((), "updates", {"chunk": "data4"}),
+        ((), "updates", {"__interrupt__": ()}),
     ]
 
     # subgraphs + single mode
     stream_parts = []
-    with pytest.raises(GraphInterrupt):
-        for stream_part in remote_pregel.stream(
-            {"input": "data"},
-            config={"configurable": {"thread_id": "thread_1"}},
-            subgraphs=True,
-        ):
-            stream_parts.append(stream_part)
+    for stream_part in remote_pregel.stream(
+        {"input": "data"},
+        config={"configurable": {"thread_id": "thread_1"}},
+        subgraphs=True,
+    ):
+        stream_parts.append(stream_part)
 
     assert stream_parts == [
         ((), {"chunk": "data3"}),
         ((), {"chunk": "data4"}),
+        ((), {"__interrupt__": ()}),
     ]
 
 
@@ -561,15 +572,17 @@ async def test_astream():
         client=mock_async_client,
     )
 
-    # stream modes doesn't include 'updates'
-    stream_parts = []
+    # test raising graph interrupt if invoked as a subgraph
     with pytest.raises(GraphInterrupt) as exc:
         async for stream_part in remote_pregel.astream(
             {"input": "data"},
-            config={"configurable": {"thread_id": "thread_1"}},
+            # pretend we invoked this as a subgraph
+            config={
+                "configurable": {"thread_id": "thread_1", "checkpoint_ns": "some_ns"}
+            },
             stream_mode="values",
         ):
-            stream_parts.append(stream_part)
+            pass
 
     assert exc.value.args[0] == [
         Interrupt(
@@ -580,6 +593,15 @@ async def test_astream():
         )
     ]
 
+    # stream modes doesn't include 'updates'
+    stream_parts = []
+    async for stream_part in remote_pregel.astream(
+        {"input": "data"},
+        config={"configurable": {"thread_id": "thread_1"}},
+        stream_mode="values",
+    ):
+        stream_parts.append(stream_part)
+
     assert stream_parts == [
         {"chunk": "data1"},
         {"chunk": "data2"},
@@ -596,62 +618,62 @@ async def test_astream():
 
     # default stream_mode is updates
     stream_parts = []
-    with pytest.raises(GraphInterrupt):
-        async for stream_part in remote_pregel.astream(
-            {"input": "data"},
-            config={"configurable": {"thread_id": "thread_1"}},
-        ):
-            stream_parts.append(stream_part)
+    async for stream_part in remote_pregel.astream(
+        {"input": "data"},
+        config={"configurable": {"thread_id": "thread_1"}},
+    ):
+        stream_parts.append(stream_part)
 
     assert stream_parts == [
         {"chunk": "data3"},
         {"chunk": "data4"},
+        {"__interrupt__": ()},
     ]
 
     # list stream_mode includes mode names
     stream_parts = []
-    with pytest.raises(GraphInterrupt):
-        async for stream_part in remote_pregel.astream(
-            {"input": "data"},
-            config={"configurable": {"thread_id": "thread_1"}},
-            stream_mode=["updates"],
-        ):
-            stream_parts.append(stream_part)
+    async for stream_part in remote_pregel.astream(
+        {"input": "data"},
+        config={"configurable": {"thread_id": "thread_1"}},
+        stream_mode=["updates"],
+    ):
+        stream_parts.append(stream_part)
 
     assert stream_parts == [
         ("updates", {"chunk": "data3"}),
         ("updates", {"chunk": "data4"}),
+        ("updates", {"__interrupt__": ()}),
     ]
 
     # subgraphs + list modes
     stream_parts = []
-    with pytest.raises(GraphInterrupt):
-        async for stream_part in remote_pregel.astream(
-            {"input": "data"},
-            config={"configurable": {"thread_id": "thread_1"}},
-            stream_mode=["updates"],
-            subgraphs=True,
-        ):
-            stream_parts.append(stream_part)
+    async for stream_part in remote_pregel.astream(
+        {"input": "data"},
+        config={"configurable": {"thread_id": "thread_1"}},
+        stream_mode=["updates"],
+        subgraphs=True,
+    ):
+        stream_parts.append(stream_part)
 
     assert stream_parts == [
         ((), "updates", {"chunk": "data3"}),
         ((), "updates", {"chunk": "data4"}),
+        ((), "updates", {"__interrupt__": ()}),
     ]
 
     # subgraphs + single mode
     stream_parts = []
-    with pytest.raises(GraphInterrupt):
-        async for stream_part in remote_pregel.astream(
-            {"input": "data"},
-            config={"configurable": {"thread_id": "thread_1"}},
-            subgraphs=True,
-        ):
-            stream_parts.append(stream_part)
+    async for stream_part in remote_pregel.astream(
+        {"input": "data"},
+        config={"configurable": {"thread_id": "thread_1"}},
+        subgraphs=True,
+    ):
+        stream_parts.append(stream_part)
 
     assert stream_parts == [
         ((), {"chunk": "data3"}),
         ((), {"chunk": "data4"}),
+        ((), {"__interrupt__": ()}),
     ]
 
     async_iter = MagicMock()
@@ -664,33 +686,33 @@ async def test_astream():
 
     # subgraphs + list modes
     stream_parts = []
-    with pytest.raises(GraphInterrupt):
-        async for stream_part in remote_pregel.astream(
-            {"input": "data"},
-            config={"configurable": {"thread_id": "thread_1"}},
-            stream_mode=["updates"],
-            subgraphs=True,
-        ):
-            stream_parts.append(stream_part)
+    async for stream_part in remote_pregel.astream(
+        {"input": "data"},
+        config={"configurable": {"thread_id": "thread_1"}},
+        stream_mode=["updates"],
+        subgraphs=True,
+    ):
+        stream_parts.append(stream_part)
 
     assert stream_parts == [
         (("my", "subgraph"), "updates", {"chunk": "data3"}),
         (("hello", "subgraph"), "updates", {"chunk": "data4"}),
+        (("bye", "subgraph"), "updates", {"__interrupt__": ()}),
     ]
 
     # subgraphs + single mode
     stream_parts = []
-    with pytest.raises(GraphInterrupt):
-        async for stream_part in remote_pregel.astream(
-            {"input": "data"},
-            config={"configurable": {"thread_id": "thread_1"}},
-            subgraphs=True,
-        ):
-            stream_parts.append(stream_part)
+    async for stream_part in remote_pregel.astream(
+        {"input": "data"},
+        config={"configurable": {"thread_id": "thread_1"}},
+        subgraphs=True,
+    ):
+        stream_parts.append(stream_part)
 
     assert stream_parts == [
         (("my", "subgraph"), {"chunk": "data3"}),
         (("hello", "subgraph"), {"chunk": "data4"}),
+        (("bye", "subgraph"), {"__interrupt__": ()}),
     ]
 
 

libs/prebuilt/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langgraph-prebuilt"
-version = "0.1.7"
+version = "0.1.8"
 description = "Library with high-level APIs for creating and executing LangGraph agents and tools."
 authors = []
 license = "MIT"

libs/sdk-js/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@langchain/langgraph-sdk",
-  "version": "0.0.62",
+  "version": "0.0.63",
   "description": "Client library for interacting with the LangGraph API",
   "type": "module",
   "packageManager": "yarn@1.22.19",

libs/sdk-js/src/client.ts

@@ -340,6 +340,7 @@ export class AssistantsClient extends BaseClient {
     assistantId?: string;
     ifExists?: OnConflictBehavior;
     name?: string;
+    description?: string;
   }): Promise<Assistant> {
     return this.fetch<Assistant>("/assistants", {
       method: "POST",
@@ -350,6 +351,7 @@ export class AssistantsClient extends BaseClient {
         assistant_id: payload.assistantId,
         if_exists: payload.ifExists,
         name: payload.name,
+        description: payload.description,
       },
     });
   }
@@ -367,6 +369,7 @@ export class AssistantsClient extends BaseClient {
       config?: Config;
       metadata?: Metadata;
       name?: string;
+      description?: string;
     },
   ): Promise<Assistant> {
     return this.fetch<Assistant>(`/assistants/${assistantId}`, {
@@ -376,6 +379,7 @@ export class AssistantsClient extends BaseClient {
         config: payload.config,
         metadata: payload.metadata,
         name: payload.name,
+        description: payload.description,
       },
     });
   }

libs/sdk-js/src/schema.ts

@@ -113,6 +113,9 @@ export interface AssistantBase {
 
   /** The name of the assistant */
   name: string;
+
+  /** The description of the assistant */
+  description?: string;
 }
 
 export interface AssistantVersion extends AssistantBase {}

libs/sdk-js/src/types.ts

@@ -19,7 +19,7 @@ export type StreamEvent =
 
 export interface Send {
   node: string;
-  input: Record<string, unknown> | null;
+  input: unknown | null;
 }
 
 export interface Command {