fix(cli): only render progress when in TTY (#4299 )

Prevents logging terminal clear commands in non-TTY environments (LangSmith / CI)
Bump to 0.2.4
2026-08-18 13:45:44 +02:00 · 2025-04-16 23:41:35 +02:00 · 2025-04-16 23:34:54 +02:00 · 2025-04-16 23:28:07 +02:00 · 2025-04-16 22:33:58 +02:00 · 2025-04-16 22:29:00 +02:00
49 changed files with 1421 additions and 496 deletions
@@ -40,6 +40,9 @@ agent.invoke(
 )
 ```

+> [!TIP]
+> Check out [this guide](https://langchain-ai.github.io/langgraph/tutorials/workflows/) that walks through implementing common patterns (workflows and agents) in LangGraph. 
+
 ## Why use LangGraph?

 LangGraph is built for developers who want to build powerful, adaptable AI agents. Developers choose LangGraph for:
@@ -1,4 +1,4 @@
-# How to Deploy to Cloud SaaS
+# How to Deploy to Cloud SaaS (Beta)

 Before deploying, review the [conceptual guide for the Cloud SaaS](../../concepts/langgraph_cloud.md) deployment option.

@@ -1,4 +1,4 @@
-# How to Deploy Self-Hosted Control Plane
+# How to Deploy Self-Hosted Control Plane (Beta)

 Before deploying, review the [conceptual guide for the Self-Hosted Control Plane](../../concepts/langgraph_self_hosted_control_plane.md) deployment option.

@@ -1,4 +1,4 @@
-# How to Deploy Self-Hosted Data Plane
+# How to Deploy Self-Hosted Data Plane (Beta)

 Before deploying, review the [conceptual guide for the Self-Hosted Data Plane](../../concepts/langgraph_self_hosted_data_plane.md) deployment option.

@@ -158,7 +158,7 @@ export default function HomePage() {
 }
 ```

-Under the hood, the `useStream()` hook will use the `streamMode: "messages-key"` to receive a stream of messages (i.e. individual LLM tokens) from any LangChain chat model invocations inside your graph nodes. Learn more about messages streaming in the [How to stream messages from your graph](./stream_messages.md) guide.
+Under the hood, the `useStream()` hook will use the `streamMode: "messages-tuple"` to receive a stream of messages (i.e. individual LLM tokens) from any LangChain chat model invocations inside your graph nodes. Learn more about messages streaming in the [How to stream messages from your graph](./stream_messages.md) guide.

 ### Interrupts

@@ -1,6 +1,6 @@
 # Environment Variables

-The LangGraph Cloud Server supports specific environment variables for configuring a deployment.
+The LangGraph Server supports specific environment variables for configuring a deployment.

 ## `BG_JOB_ISOLATED_LOOPS`

@@ -32,7 +32,7 @@ See <a href="https://docs.smith.langchain.com/how_to_guides/tracing/sample_trace

 ## `LANGGRAPH_AUTH_TYPE`

-Type of authentication for the LangGraph Cloud Server deployment. Valid values: `langsmith`, `noop`.
+Type of authentication for the LangGraph Server deployment. Valid values: `langsmith`, `noop`.

 For deployments to LangGraph Cloud, this environment variable is set automatically. For local development or deployments where authentication is handled externally (e.g. self-hosted), set this environment variable to `noop`.

@@ -44,19 +44,27 @@ Set this environment variable to have a BYOC deployment send traces to a self-ho

 `SELF_HOSTED_LANGSMITH_HOSTNAME` is the hostname of the self-hosted LangSmith instance. It must be accessible to the BYOC deployment. `LANGSMITH_API_KEY` is a LangSmith API generated from the self-hosted LangSmith instance.

+## `LANGSMITH_TRACING`
+
+!!! info "Only for Self-Hosted Data Plane, Self-Hosted Control Plane, and Standalone Container"
+    Disabling LangSmith tracing is only available for [Self-Hosted Data Plane](../../concepts/langgraph_self_hosted_data_plane.md), [Self-Hosted Control Plane](../../concepts/langgraph_self_hosted_control_plane.md), and [Standalone Container](../../concepts/langgraph_standalone_container.md) deployments.
+
+Set `LANGSMITH_TRACING` to `false` to disable tracing to LangSmith.
+
 ## `LOG_LEVEL`

 Configure [log level](https://docs.python.org/3/library/logging.html#logging-levels). Defaults to `INFO`.

 ## `N_JOBS_PER_WORKER`

-Number of jobs per worker for the LangGraph Cloud task queue. Defaults to `10`.
+Number of jobs per worker for the LangGraph Server task queue. Defaults to `10`.

 ## `POSTGRES_URI_CUSTOM`

-For [Bring Your Own Cloud (BYOC)](../../concepts/bring_your_own_cloud.md) deployments only.
+!!! info "Only for Self-Hosted Data Plane and Self-Hosted Control Plane"
+    Custom Postgres instances are only available for [Self-Hosted Data Plane](../../concepts/langgraph_self_hosted_data_plane.md) and [Self-Hosted Control Plane](../../concepts/langgraph_self_hosted_control_plane.md) deployments.

-Specify `POSTGRES_URI_CUSTOM` to use an externally managed Postgres instance. The value of `POSTGRES_URI_CUSTOM` must be a valid [Postgres connection URI](https://www.postgresql.org/docs/current/libpq-connect.html#LIBPQ-CONNSTRING-URIS).
+Specify `POSTGRES_URI_CUSTOM` to use a custom Postgres instance. The value of `POSTGRES_URI_CUSTOM` must be a valid [Postgres connection URI](https://www.postgresql.org/docs/current/libpq-connect.html#LIBPQ-CONNSTRING-URIS).

 Postgres:

@@ -73,11 +81,11 @@ Control Plane Functionality:

 Database Connectivity:

- The externally managed Postgres instance must be accessible by the LangGraph Server service in the ECS cluster. The BYOC user is responsible for ensuring connectivity.
- For example, if an AWS RDS Postgres instance is provisioned, it can be provisioned in the same VPC (`langgraph-cloud-vpc`) as the ECS cluster with the `langgraph-cloud-service-sg` security group to ensure connectivity.
+- The custom Postgres instance must be accessible by the LangGraph Server. The user is responsible for ensuring connectivity.

 ## `REDIS_URI_CUSTOM`

-For [Bring Your Own Cloud (BYOC)](../../concepts/bring_your_own_cloud.md) deployments only.
+!!! info "Only for Self-Hosted Data Plane and Self-Hosted Control Plane"
+    Custom Redis instances are only available for [Self-Hosted Data Plane](../../concepts/langgraph_self_hosted_data_plane.md) and [Self-Hosted Control Plane](../../concepts/langgraph_self_hosted_control_plane.md) deployments.

-Specify `REDIS_URI_CUSTOM` to use an externally managed Redis instance. The value of `REDIS_URI_CUSTOM` must be a valid [Redis connection URI](https://redis-py.readthedocs.io/en/stable/connections.html#redis.Redis.from_url).
+Specify `REDIS_URI_CUSTOM` to use a custom Redis instance. The value of `REDIS_URI_CUSTOM` must be a valid [Redis connection URI](https://redis-py.readthedocs.io/en/stable/connections.html#redis.Redis.from_url).
@@ -10,11 +10,11 @@

 There are 4 main options for deploying with the LangGraph Platform:

-1. **[Cloud SaaS](#cloud-saas)**: Available for **Plus** and **Enterprise** plans.
+1. **<a href="#cloud-saas">Cloud SaaS<sup>(Beta)</sup></a>**: Available for **Plus** and **Enterprise** plans.

-1. **[Self-Hosted Data Plane](#self-hosted-data-plane)**: Available for the **Enterprise** plan.
+1. **<a href="#self-hosted-data-plane">Self-Hosted Data Plane<sup>(Beta)</sup></a>**: Available for the **Enterprise** plan.

-1. **[Self-Hosted Control Plane](#self-hosted-control-plane)**: Available for the **Enterprise** plan.
+1. **<a href="#self-hosted-control-plane">Self-Hosted Control Plane<sup>(Beta)</sup></a>**: Available for the **Enterprise** plan.

 1. **[Standalone Container](#standalone-container)**: Available for all plans.

@@ -76,7 +76,7 @@ The LangGraph Platform comprises several components that work together to suppor

 ### Deployment Options

- [Cloud SaaS](../concepts/langgraph_cloud.md): Connect to your GitHub repositories and deploy LangGraph Servers to LangChain's cloud. We manage everything.
- [Self-Hosted Data Plane](../concepts/langgraph_self_hosted_data_plane.md): Create deployments from the [Control Plane UI](../concepts/langgraph_control_plane.md#control-plane-ui) and deploy LangGraph Servers to your cloud. We manage the [control plane](../concepts/langgraph_control_plane.md), you manage the deployments.
- [Self-Hosted Control Plane](../concepts/langgraph_self_hosted_control_plane.md#control-plane-ui): Create deployments from a self-hosted [Control Plane UI](../concepts/langgraph_control_plane.md) and deploy LangGraph Servers to your cloud. You manage everything.
+- <a href="./langgraph_cloud/">Cloud SaaS<sup>(Beta)</sup></a>: Connect to your GitHub repositories and deploy LangGraph Servers to LangChain's cloud. We manage everything.
+- <a href="./langgraph_self_hosted_data_plane/">Self-Hosted Data Plane<sup>(Beta)</sup></a>: Create deployments from the [Control Plane UI](../concepts/langgraph_control_plane.md#control-plane-ui) and deploy LangGraph Servers to your cloud. We manage the [control plane](../concepts/langgraph_control_plane.md), you manage the deployments.
+- <a href="./langgraph_self_hosted_control_plane/">Self-Hosted Control Plane<sup>(Beta)</sup></a>: Create deployments from a self-hosted [Control Plane UI](../concepts/langgraph_control_plane.md#control-plane-ui) and deploy LangGraph Servers to your cloud. You manage everything.
 - [Standalone Container](../concepts/langgraph_standalone_container.md): Deploy LangGraph Server Docker images however you like.
@@ -1,4 +1,4 @@
-# Cloud SaaS
+# Cloud SaaS (Beta)

 To deploy a [LangGraph Server](../concepts/langgraph_server.md), follow the how-to guide for [how to deploy to Cloud SaaS](../cloud/deployment/cloud.md).

@@ -44,21 +44,24 @@ Feature Differences:

 ### Autoscaling

-[`Production` type](../concepts/langgraph_control_plane.md#deployment-types) deployments automatically scale up to 10 containers. Scaling is based on the current request load for a single container. Specifically, the autoscaling implementation scales the deployment so that each container is processing about 10 concurrent requests. For example... 
+[`Production` type](../concepts/langgraph_control_plane.md#deployment-types) deployments automatically scale up to 10 containers. Scaling is based on 3 metrics:

- If the deployment is processing 20 concurrent requests, the deployment will scale up from 1 container to 2 containers (20 requests / 2 containers = 10 requests per container).
- If a deployment of 2 containers is processing 10 requests, the deployment will scale down from 2 containers to 1 container (10 requests / 1 container = 10 requests per container).
+1. CPU utilization
+1. Memory utilization
+1. Number of pending (in progress) [runs](../concepts/langgraph_server.md#runs)

-10 concurrent requests per container is the target threshold. However, 10 concurrent requests per container is not a hard limit. The number of concurrent requests can exceed 10 if there is a sudden burst of requests.
+For CPU utilization, the autoscaler targets 75% utilization. This means the autoscaler will scale the number of containers up or down to ensure that CPU utilization is at or near 75%. For memory utilization, the autoscaler targets 75% utilization as well.

-Scale down actions are delayed for 30 minutes before any action is taken. In other words, if the autoscaling implementation decides to scale down a deployment, it will first wait for 30 minutes before scaling down. After 30 minutes, the concurrency metric is recomputed and the deployment will scale down if the concurrency metric has met the target threshold. Otherwise, the deployment remains scaled up. This "cool down" period ensures that deployments do not scale up and down too frequently.
+For number of pending runs, the autoscaler targets 10 pending runs. For example, if the current number of containers is 1, but the number of pending runs in 20, the autoscaler will scale up the deployment to 2 containers (20 pending runs / 2 containers = 10 pending runs per container).

-In the future, the autoscaling implementation may evolve to accommodate other metrics such as background run queue size.
+Each metric is computed independently and the autoscaler will determine the scaling action based on the metric that results in the most number of containers.
+
+Scale down actions are delayed for 30 minutes before any action is taken. In other words, if the autoscaler decides to scale down a deployment, it will first wait for 30 minutes before scaling down. After 30 minutes, the metrics are recomputed and the deployment will scale down if the recomputed metrics result in a lower number of containers than the current number. Otherwise, the deployment remains scaled up. This "cool down" period ensures that deployments do not scale up and down too frequently.

 ### Static IP Addresses

 !!! info "Only for Cloud SaaS"
-    Static IP addresses are only available for [Cloud SaaS](../concepts/langgraph_cloud.md).
+    Static IP addresses are only available for [Cloud SaaS](../concepts/langgraph_cloud.md) deployments.

 All traffic from deployments created after January 6th 2025 will come through a NAT gateway. This NAT gateway will have several static IP addresses depending on the data region. Refer to the table below for the list of static IP addresses:

@@ -72,3 +75,46 @@ All traffic from deployments created after January 6th 2025 will come through a
 | 34.169.88.30   | 34.91.238.184  |
 | 34.19.93.202   | 35.204.101.241 |
 | 34.19.34.50    | 35.204.48.32   |
+
+### Custom Postgres
+
+!!! info "Only for Self-Hosted Data Plane and Self-Hosted Control Plane"
+    Custom Postgres instances are only available for [Self-Hosted Data Plane](../concepts/langgraph_self_hosted_data_plane.md) and [Self-Hosted Control Plane](../concepts/langgraph_self_hosted_control_plane.md) deployments.
+
+A custom Postgres instance can be used instead of the [one automatically created by the control plane](./langgraph_control_plane.md#database-provisioning). Specify the [`POSTGRES_URI_CUSTOM`](../cloud/reference/env_var.md#postgres_uri_custom) environment variable to use a custom Postgres instance.
+
+Multiple deployments can share the same Postgres instance. For example, for `Deployment A`, `POSTGRES_URI_CUSTOM` can be set to `postgres://<user>:<password>@/<database_name_1>?host=<hostname_1>` and for `Deployment B`, `POSTGRES_URI_CUSTOM` can be set to `postgres://<user>:<password>@/<database_name_2>?host=<hostname_1>`. `<database_name_1>` and `database_name_2` are different databases within the same instance, but `<hostname_1>` is shared. **The same database cannot be used for separate deployments**.
+
+### Custom Redis
+
+!!! info "Only for Self-Hosted Data Plane and Self-Hosted Control Plane"
+    Custom Redis instances are only available for [Self-Hosted Data Plane](../concepts/langgraph_self_hosted_data_plane.md) and [Self-Hosted Control Plane](../concepts/langgraph_self_hosted_control_plane.md) deployments.
+
+A custom Redis instance can be used instead of the one automatically created by the control plane. Specify the [REDIS_URI_CUSTOM](../cloud/reference/env_var.md#redis_uri_custom) environment variable to use a custom Redis instance.
+
+
+Multiple deployments can share the same Redis instance. For example, for `Deployment A`, `REDIS_URI_CUSTOM` can be set to `redis://<hostname_1>:<port>/1` and for `Deployment B`, `REDIS_URI_CUSTOM` can be set to `redis://<hostname_1>:<port>/2`. `1` and `2` are different database numbers within the same instance, but `<hostname_1>` is shared. **The same database number cannot be used for separate deployments**.
+
+### LangSmith Tracing
+
+LangGraph Server is automatically configured to send traces to LangSmith. See the table below for details with respect to each deployment option.
+
+| Cloud SaaS | Self-Hosted Data Plane | Self-Hosted Control Plane | Standalone Container |
+|------------|------------------------|---------------------------|----------------------|
+| Required<br><br>Trace to LangSmith SaaS. | Optional<br><br>Disable tracing or trace to LangSmith SaaS. | Optional<br><br>Disable tracing or trace to Self-Hosted LangSmith. | Optional<br><br>Disable tracing, trace to LangSmith SaaS, or trace to Self-Hosted LangSmith. |
+
+### Telemetry
+
+LangGraph Server is automatically configured to report telemetry metadata for billing purposes. See the table below for details with respect to each deployment option.
+
+| Cloud SaaS | Self-Hosted Data Plane | Self-Hosted Control Plane | Standalone Container |
+|------------|------------------------|---------------------------|----------------------|
+| Telemetry sent to LangSmith SaaS. | Telemetry sent to LangSmith SaaS. | Self-reported usage (audit) for air-gapped license key.<br><br>Telemetry sent to LangSmith SaaS for LangGraph Platform License Key. | Self-reported usage (audit) for air-gapped license key.<br><br>Telemetry sent to LangSmith SaaS for LangGraph Platform License Key. |
+
+### Licensing
+
+LangGraph Server is automatically configured to perform license key validation. See the table below for details with respect to each deployment option.
+
+| Cloud SaaS | Self-Hosted Data Plane | Self-Hosted Control Plane | Standalone Container |
+|------------|------------------------|---------------------------|----------------------|
+| LangSmith API Key validated against LangSmith SaaS. | LangSmith API Key validated against LangSmith SaaS. | Air-gapped license key or LangGraph Platform License Key validated against LangSmith SaaS. | Air-gapped license key or LangGraph Platform License Key validated against LangSmith SaaS. |
@@ -5,6 +5,10 @@ search:

 # LangGraph Platform

+Watch this 4-minute overview of LangGraph Platform to see how it helps you build, deploy, and evaluate agentic applications.
+
+<iframe width="560" height="315" src="https://www.youtube.com/embed/pfAQxBS5z88?si=XGS6Chydn6lhSO1S" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
+
 ## Overview

 LangGraph Platform is a commercial solution for deploying agentic applications to production, built on the open-source [LangGraph framework](./high_level.md).
@@ -1,4 +1,4 @@
-# Self-Hosted Control Plane
+# Self-Hosted Control Plane (Beta)

 To deploy a [LangGraph Server](../concepts/langgraph_server.md), follow the how-to guide for [how to deploy the Self-Hosted Control Plane](../cloud/deployment/self_hosted_control_plane.md).

@@ -1,4 +1,4 @@
-# Self-Hosted Data Plane
+# Self-Hosted Data Plane (Beta)

 To deploy a [LangGraph Server](../concepts/langgraph_server.md), follow the how-to guide for [how to deploy the Self-Hosted Data Plane](../cloud/deployment/self_hosted_data_plane.md).

@@ -4,7 +4,7 @@

 ## How we use Postgres

-Postgres is the persistence layer for all user and run data in LGP. This stores both checkpoints (see more info [here](./persistence.md)) as well as the server resources (threads, runs, assistants and crons).
+Postgres is the persistence layer for all user, run, and long-term memory data in LGP. This stores both checkpoints (see more info [here](./persistence.md)), server resources (threads, runs, assistants and crons), as well as items saved in the long-term memory store (see more info [here](./persistence.md#memory-store)).

 ## How we use Redis

@@ -8,10 +8,6 @@ Defining a custom app object lets you add any routes you'd like, so you can do a

 Below is an example using FastAPI.

-???+ note "Python only"
-
-    We currently only support custom authentication and authorization in Python deployments with `langgraph-api>=0.0.26`.
-
 ## Create app

 Starting from an **existing** LangGraph Platform application, add the following custom route code to your `webapp.py` file. If you are starting from scratch, you can create a new app from a template using the CLI.
@@ -17,9 +17,9 @@ Get started deploying your LangGraph applications locally or on the cloud with

 ## Deployment Options

- [Cloud SaaS](../concepts/langgraph_cloud.md): Connect to your GitHub repositories and deploy LangGraph Servers to LangChain's cloud. We manage everything.
- [Self-Hosted Data Plane](../concepts/langgraph_self_hosted_data_plane.md): Create deployments from the [Control Plane UI](../concepts/langgraph_control_plane.md#control-plane-ui) and deploy LangGraph Servers to your cloud. We manage the [control plane](../concepts/langgraph_control_plane.md), you manage the deployments.
- [Self-Hosted Control Plane](../concepts/langgraph_self_hosted_control_plane.md#control-plane-ui): Create deployments from a self-hosted [Control Plane UI](../concepts/langgraph_control_plane.md) and deploy LangGraph Servers to your cloud. You manage everything.
+- <a href="../../concepts/langgraph_cloud/">Cloud SaaS<sup>(Beta)</sup></a>: Connect to your GitHub repositories and deploy LangGraph Servers to LangChain's cloud. We manage everything.
+- <a href="../../concepts/langgraph_self_hosted_data_plane/">Self-Hosted Data Plane<sup>(Beta)</sup></a>: Create deployments from the [Control Plane UI](../concepts/langgraph_control_plane.md#control-plane-ui) and deploy LangGraph Servers to your cloud. We manage the [control plane](../concepts/langgraph_control_plane.md), you manage the deployments.
+- <a href="../../concepts/langgraph_self_hosted_control_plane/">Self-Hosted Control Plane<sup>(Beta)</sup></a>: Create deployments from a self-hosted [Control Plane UI](../concepts/langgraph_control_plane.md#control-plane-ui) and deploy LangGraph Servers to your cloud. You manage everything.
 - [Standalone Container](../concepts/langgraph_standalone_container.md): Deploy LangGraph Server Docker images however you like.

 A quick comparison...
@@ -222,7 +222,7 @@ As noted in the Anthropic blog on `Building Effective Agents`:


    @entrypoint()
-    def parallel_workflow(topic: str):
+    def prompt_chaining_workflow(topic: str):
        original_joke = generate_joke(topic).result()
        if check_punchline(original_joke) == "Pass":
            return original_joke
@@ -231,7 +231,7 @@ As noted in the Anthropic blog on `Building Effective Agents`:
        return polish_joke(improved_joke).result()

    # Invoke
-    for step in parallel_workflow.stream("cats", stream_mode="updates"):
+    for step in prompt_chaining_workflow.stream("cats", stream_mode="updates"):
        print(step)
        print("\n")
    ```
@@ -57,12 +57,16 @@ plugins:
      separator: '[\s\u200b\-,:!=\[\]()"`/]+|\.(?!\d)|&[lg]t;'
  - autorefs
  - mkdocstrings:
+      custom_templates: templates
      handlers:
        python:
          import:
            - https://docs.python.org/3/objects.inv
            - https://python.langchain.com/api_reference/objects.inv
          options:
+            preload_modules:
+              - langchain
+              - langchain_core
            enable_inventory: true
            members_order: source
            allow_inspection: true
@@ -75,7 +79,10 @@ plugins:
              docstring_style: google
            docstring_section_style: list
            show_root_toc_entry: false
+            show_signature: true
            show_signature_annotations: true
+            separate_signature: true
+            line_length: 60
            show_symbol_type_heading: true
            show_symbol_type_toc: true
            signature_crossrefs: true
@@ -213,8 +220,8 @@ nav:
                - how-tos/ttl/configure_ttl.md
            - Authentication & Access Control:
                - Authentication & Access Control: how-tos#authentication-access-control
-                - cloud/how-tos/auth/custom_auth_new.md
-                - cloud/how-tos/auth/openapi_security_new.md
+                - how-tos/auth/custom_auth.md
+                - how-tos/auth/openapi_security.md
            - Assistants:
                - Assistants: how-tos#assistants
                - cloud/how-tos/configuration_cloud.md
@@ -256,6 +263,11 @@ nav:
                - cloud/how-tos/webhooks.md
            - Cron Jobs:
                - cloud/how-tos/cron_jobs.md
+            - Modifying the API:
+                - Modifying the API: how-tos#modifying-the-api
+                - how-tos/http/custom_lifespan.md
+                - how-tos/http/custom_middleware.md
+                - how-tos/http/custom_routes.md
            - LangGraph Studio:
                - LangGraph Studio: how-tos#langgraph-studio
                - cloud/how-tos/test_deployment.md
@@ -265,6 +277,7 @@ nav:
                - cloud/how-tos/datasets_studio.md
                - cloud/how-tos/iterate_graph_studio.md
                - cloud/how-tos/clone_traces_studio.md
+                - how-tos/local-studio.md
      - Concepts:
        - concepts/index.md
        - LangGraph:
@@ -273,8 +286,9 @@ nav:
          - concepts/low_level.md
          - concepts/agentic_concepts.md
          - concepts/multi_agent.md
-          - concepts/breakpoints
+          - concepts/breakpoints.md
          - concepts/human_in_the_loop.md
+          - concepts/v0-human-in-the-loop.md
          - concepts/time-travel.md
          - concepts/persistence.md
          - concepts/memory.md
@@ -287,7 +301,10 @@ nav:
          - High Level:
            - High Level: concepts#high-level
            - concepts/langgraph_platform.md
+            - concepts/platform_architecture.md
+            - concepts/scalability_and_resilience.md
            - concepts/deployment_options.md
+            - concepts/bring_your_own_cloud.md
            - concepts/plans.md
            - concepts/template_applications.md
          - Components:
@@ -311,6 +328,7 @@ nav:
            - concepts/langgraph_self_hosted_data_plane.md
            - concepts/langgraph_self_hosted_control_plane.md
            - concepts/langgraph_standalone_container.md
+            - concepts/self_hosted.md
      - Tutorials:
        - tutorials/index.md
        - Quick Start:
@@ -387,6 +405,7 @@ nav:
      - LangGraph Academy Course: https://academy.langchain.com/courses/intro-to-langgraph

  - API reference:
+    - reference/index.md
    - Library:
      - Graphs: reference/graphs.md
      - Checkpointing: reference/checkpoints.md
@@ -497,13 +516,8 @@ extra:
            Thanks for your feedback! Please help us improve this page by adding to the discussion below.
 validation:
  # https://www.mkdocs.org/user-guide/configuration/
-  # We're `ignoring` nav.omitted_files because we are going to rely
-  # on files being properly links to from the index pages of:
-  # - tutorials
-  # - concepts
-  # - how-tos
-  # - reference
-  omitted_files: ignore
+  # We are still raising for omitted files because they determine the breadcrumbs for pages.
+  omitted_files: warn 
  absolute_links: warn
  unrecognized_links: warn
  # TODO: figure out how to enable 'warn' for this
@@ -11,6 +11,7 @@ python = "^3.10"
 aiohappyeyeballs = "2.4.3"
 hub = "^3.0.1"
 xxhash = "^3.5.0"
+black = "^25.1.0"

 [tool.poetry.group.docs.dependencies]
 langgraph = { path = "../libs/langgraph/", develop = true }
@@ -0,0 +1,121 @@
+{#- Template for Python functions.
+   
+This template renders a Python function or method.
+
+Context:
+  function (griffe.Function): The function to render.
+  root (bool): Whether this is the root object, injected with `:::` in a Markdown page.
+  heading_level (int): The HTML heading level to use.
+  config (dict): The configuration options.
+-#}
+
+{% block logs scoped %}
+  {{ log.debug("Rendering " + function.path) }}
+{% endblock logs %}
+
+{% import "language"|get_template as lang with context %}
+{#- Language module providing the `t` translation method. -#}
+
+<div class="doc doc-object doc-function">
+  {% with obj = function, html_id = function.path %}
+    {% if root %}
+      {% set show_full_path = config.show_root_full_path %}
+      {% set root_members = True %}
+    {% elif root_members %}
+      {% set show_full_path = config.show_root_members_full_path or config.show_object_full_path %}
+      {% set root_members = False %}
+    {% else %}
+      {% set show_full_path = config.show_object_full_path %}
+    {% endif %}
+
+    {% set function_name = function.path if show_full_path else function.name %}
+    {#- Brief or full function name depending on configuration. -#}
+    {% set symbol_type = "method" if function.parent.is_class else "function" %}
+    {#- Symbol type: method when parent is a class, function otherwise. -#}
+
+    {% if not root or config.show_root_heading %}
+      {% filter heading(
+          heading_level,
+          role="function",
+          id=html_id,
+          class="doc doc-heading",
+          toc_label=(('<code class="doc-symbol doc-symbol-toc doc-symbol-' + symbol_type + '"></code>&nbsp;')|safe if config.show_symbol_type_toc else '') + function.name,
+        ) %}
+      
+        {% block heading scoped %}
+          {% if config.show_symbol_type_heading %}<code class="doc-symbol doc-symbol-heading doc-symbol-{{ symbol_type }}"></code>{% endif %}
+          {% if config.separate_signature %}
+            <span class="doc doc-object-name doc-function-name">{{ config.heading if config.heading and root else function_name }}</span>
+          {% else %}
+            {%+ filter highlight(language="python", inline=True) %}
+              {{ function_name }}{% include "signature"|get_template with context %}
+            {% endfilter %}
+          {% endif %}
+        {% endblock heading %}
+
+        {% block labels scoped %}
+          {% with labels = function.labels %}
+            {% include "labels"|get_template with context %}
+          {% endwith %}
+        {% endblock labels %}
+
+      {% endfilter %}
+
+      {% block signature scoped %}
+        {#- Signature block.
+        
+        This block renders only the main signature and deliberately omits the overloads.
+        -#}
+        {% if config.separate_signature %}
+          {% filter format_signature(function, config.line_length, crossrefs=config.signature_crossrefs) %}
+            {{ function.name }}
+          {% endfilter %}
+        {% endif %}
+      {% endblock signature %}
+
+    {% else %}
+
+      {% if config.show_root_toc_entry %}
+        {% filter heading(
+            heading_level,
+            role="function",
+            id=html_id,
+            toc_label=(('<code class="doc-symbol doc-symbol-toc doc-symbol-' + symbol_type + '"></code>&nbsp;')|safe if config.show_symbol_type_toc else '') + (config.toc_label if config.toc_label and root else function.name),
+            hidden=True,
+          ) %}
+        {% endfilter %}
+      {% endif %}
+      {% set heading_level = heading_level - 1 %}
+    {% endif %}
+
+    <div class="doc doc-contents {% if root %}first{% endif %}">
+      {% block contents scoped %}
+        {#- Contents block.
+        
+        This block renders the function’s docstring and source.
+        -#}
+        {% block docstring scoped %}
+          {% with docstring_sections = function.docstring.parsed %}
+            {% include "docstring"|get_template with context %}
+          {% endwith %}
+        {% endblock docstring %}
+
+        {% block source scoped %}
+          {% if config.show_source and function.source %}
+            <details class="quote">
+              <summary>{{ lang.t("Source code in") }} <code>
+                {%- if function.relative_filepath.is_absolute() -%}
+                  {{ function.relative_package_filepath }}
+                {%- else -%}
+                  {{ function.relative_filepath }}
+                {%- endif -%}
+              </code></summary>
+              {{ function.source|highlight(language="python", linestart=function.lineno or 0, linenums=True) }}
+            </details>
+          {% endif %}
+        {% endblock source %}
+      {% endblock contents %}
+    </div>
+
+  {% endwith %}
+</div>
@@ -44,21 +44,30 @@ class Progress:
            sys.stdout.flush()

    def __enter__(self) -> Callable[[str], None]:
-        self.thread = threading.Thread(target=self.spinner_task)
-        self.thread.start()
+        if sys.stdout.isatty():
+            self.thread = threading.Thread(target=self.spinner_task)
+            self.thread.start()

-        def set_message(message):
-            self.message = message
-            if not message:
-                self.thread.join()
+            def set_message(message):
+                self.message = message
+                if not message:
+                    self.thread.join()

-        return set_message
+            return set_message
+        else:
+
+            def set_message(message):
+                sys.stderr.write(message + "\n")
+                sys.stderr.flush()
+
+            return set_message

    def __exit__(self, exception, value, tb):
-        self.message = ""
-        try:
-            self.thread.join()
-        finally:
-            del self.thread
-        if exception is not None:
-            return False
+        if sys.stdout.isatty():
+            self.message = ""
+            try:
+                self.thread.join()
+            finally:
+                del self.thread
+            if exception is not None:
+                return False
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langgraph-cli"
-version = "0.2.3"
+version = "0.2.4"
 description = "CLI for interacting with LangGraph API"
 authors = []
 license = "MIT"
@@ -40,6 +40,9 @@ agent.invoke(
 )
 ```

+> [!TIP]
+> Check out [this guide](https://langchain-ai.github.io/langgraph/tutorials/workflows/) that walks through implementing common patterns (workflows and agents) in LangGraph. 
+
 ## Why use LangGraph?

 LangGraph is built for developers who want to build powerful, adaptable AI agents. Developers choose LangGraph for:
@@ -106,6 +106,7 @@ def fanout_to_subgraph_sync() -> StateGraph:
 if __name__ == "__main__":
    import asyncio
    import random
+    import time

    import uvloop

@@ -123,4 +124,7 @@ if __name__ == "__main__":
        len([c async for c in graph.astream(input, config=config)])

    uvloop.install()
+    start = time.time()
    asyncio.run(run())
+    end = time.time()
+    print(f"Time taken: {end - start:.4f} seconds")
@@ -69,6 +69,8 @@ CONFIG_KEY_ENSURE_LATEST = sys.intern("__pregel_ensure_latest")
 # (for distributed mode)
 CONFIG_KEY_DELEGATE = sys.intern("__pregel_delegate")
 # holds a boolean indicating whether to delegate subgraphs (for distributed mode)
+CONFIG_KEY_THREAD_ID = sys.intern("thread_id")
+# holds the thread ID for the current invocation
 CONFIG_KEY_CHECKPOINT_MAP = sys.intern("checkpoint_map")
 # holds a mapping of checkpoint_ns -> checkpoint_id for parent graphs
 CONFIG_KEY_CHECKPOINT_ID = sys.intern("checkpoint_id")
@@ -20,7 +20,7 @@ from typing import (
 from langgraph.channels.ephemeral_value import EphemeralValue
 from langgraph.channels.last_value import LastValue
 from langgraph.checkpoint.base import BaseCheckpointSaver
-from langgraph.constants import END, PREVIOUS, START, TAG_HIDDEN
+from langgraph.constants import END, PREVIOUS, START
 from langgraph.pregel import Pregel
 from langgraph.pregel.call import (
    P,
@@ -434,8 +434,7 @@ class entrypoint:
                            [
                                ChannelWriteEntry(END, mapper=_pluck_return_value),
                                ChannelWriteEntry(PREVIOUS, mapper=_pluck_save_value),
-                            ],
-                            tags=[TAG_HIDDEN],
+                            ]
                        )
                    ],
                )
@@ -1,4 +1,3 @@
-import asyncio
 from inspect import (
    isfunction,
    ismethod,
@@ -178,7 +177,7 @@ class Branch(NamedTuple):
        ],
    ) -> Runnable:
        if reader:
-            value = await asyncio.to_thread(reader, config)
+            value = reader(config)
            # passthrough additional keys from node to branch
            # only doable when using dict states
            if (
@@ -366,16 +366,14 @@ class CompiledGraph(Pregel):
        self.nodes[key] = (
            PregelNode(channels=[], triggers=[], metadata=node.metadata)
            | node.runnable
-            | ChannelWrite([ChannelWriteEntry(key)], tags=[TAG_HIDDEN])
+            | ChannelWrite([ChannelWriteEntry(key)])
        )
        cast(list[str], self.stream_channels).append(key)

    def attach_edge(self, start: str, end: str) -> None:
        if end == END:
            # publish to end channel
-            self.nodes[start].writers.append(
-                ChannelWrite([ChannelWriteEntry(END)], tags=[TAG_HIDDEN])
-            )
+            self.nodes[start].writers.append(ChannelWrite([ChannelWriteEntry(END)]))
        else:
            # subscribe to start channel
            self.nodes[end].triggers.append(start)
@@ -393,10 +391,7 @@ class CompiledGraph(Pregel):
                )
                for p in packets
            ]
-            return ChannelWrite(
-                cast(Sequence[Union[ChannelWriteEntry, Send]], writes),
-                tags=[TAG_HIDDEN],
-            )
+            return ChannelWrite(cast(Sequence[Union[ChannelWriteEntry, Send]], writes))

        # add hidden start node
        if start == START and start not in self.nodes:
@@ -43,8 +43,8 @@ from langgraph.constants import (
    MISSING,
    NS_END,
    NS_SEP,
-    SELF,
    TAG_HIDDEN,
+    TASKS,
 )
 from langgraph.errors import (
    ErrorCode,
@@ -77,9 +77,9 @@ from langgraph.pregel.write import (
 )
 from langgraph.store.base import BaseStore
 from langgraph.types import All, Checkpointer, Command, RetryPolicy
-from langgraph.utils.fields import get_field_default
+from langgraph.utils.fields import get_field_default, get_update_as_tuples
 from langgraph.utils.pydantic import create_model
-from langgraph.utils.runnable import RunnableCallable, RunnableLike, coerce_to_runnable
+from langgraph.utils.runnable import RunnableLike, coerce_to_runnable

 logger = logging.getLogger(__name__)

@@ -639,6 +639,7 @@ class StateGraph(Graph):

        compiled = CompiledStateGraph(
            builder=self,
+            schema_to_mapper={},
            config_type=self.config_schema,
            input_model=(
                self.input
@@ -670,10 +671,6 @@ class StateGraph(Graph):
        for key, node in self.nodes.items():
            compiled.attach_node(key, node)

-        compiled.attach_branch(START, SELF, CONTROL_BRANCH, with_reader=False)
-        for key, node in self.nodes.items():
-            compiled.attach_branch(key, SELF, CONTROL_BRANCH, with_reader=False)
-
        for start, end in self.edges:
            compiled.attach_edge(start, end)

@@ -689,6 +686,16 @@ class StateGraph(Graph):

 class CompiledStateGraph(CompiledGraph):
    builder: StateGraph
+    schema_to_mapper: dict[Type[Any], Optional[Callable[[Any], Any]]]
+
+    def __init__(
+        self,
+        *,
+        schema_to_mapper: dict[Type[Any], Optional[Callable[[Any], Any]]],
+        **kwargs: Any,
+    ) -> None:
+        super().__init__(**kwargs)
+        self.schema_to_mapper = schema_to_mapper

    def get_input_schema(
        self, config: Optional[RunnableConfig] = None
@@ -724,28 +731,6 @@ class CompiledStateGraph(CompiledGraph):
                if is_writable_managed_value(v)
            ]

-        def _get_root(input: Any) -> Optional[Sequence[tuple[str, Any]]]:
-            if isinstance(input, Command):
-                if input.graph == Command.PARENT:
-                    return ()
-                return input._update_as_tuples()
-            elif (
-                isinstance(input, (list, tuple))
-                and input
-                and any(isinstance(i, Command) for i in input)
-            ):
-                updates: list[tuple[str, Any]] = []
-                for i in input:
-                    if isinstance(i, Command):
-                        if i.graph == Command.PARENT:
-                            continue
-                        updates.extend(i._update_as_tuples())
-                    else:
-                        updates.append(("__root__", i))
-                return updates
-            elif input is not None:
-                return [("__root__", input)]
-
        def _get_updates(
            input: Union[None, dict, Any],
        ) -> Optional[Sequence[tuple[str, Any]]]:
@@ -776,32 +761,7 @@ class CompiledStateGraph(CompiledGraph):
                        updates.extend(_get_updates(i) or ())
                return updates
            elif (t := type(input)) and get_type_hints(t):
-                # Pydantic v2
-                if isinstance(input, BaseModelV1):
-                    keep: Optional[set[str]] = input.__fields_set__
-                    defaults = {k: v.default for k, v in t.__fields__.items()}
-                elif isinstance(input, BaseModel):
-                    keep = input.model_fields_set
-                    defaults = {k: v.default for k, v in input.model_fields.items()}
-                # Pydantic v1
-                else:
-                    keep = None
-                    defaults = {}
-
-                # NOTE: This behavior for Pydantic is somewhat inelegant,
-                # but we keep around for backwards compatibility
-                # if input is a Pydantic model, only update values
-                # that are different from the default values or in the keep set
-                return [
-                    (k, value)
-                    for k in output_keys
-                    if (value := getattr(input, k, MISSING)) is not MISSING
-                    and (
-                        value is not None
-                        or defaults.get(k, MISSING) is not None
-                        or (keep is not None and k in keep)
-                    )
-                ]
+                return get_update_as_tuples(input, output_keys)
            else:
                msg = create_error_message(
                    message=f"Expected dict, got {input}",
@@ -814,6 +774,7 @@ class CompiledStateGraph(CompiledGraph):
            ChannelWriteTupleEntry(
                mapper=_get_root if output_keys == ["__root__"] else _get_updates
            ),
+            ChannelWriteTupleEntry(mapper=_control_branch),
        )

        # add node and output channel
@@ -822,12 +783,21 @@ class CompiledStateGraph(CompiledGraph):
                tags=[TAG_HIDDEN],
                triggers=[START],
                channels=[START],
-                writers=[ChannelWrite(write_entries, tags=[TAG_HIDDEN])],
+                writers=[ChannelWrite(write_entries)],
            )
        elif node is not None:
            input_schema = node.input if node else self.builder.schema
            input_values = {k: k for k in self.builder.schemas[input_schema]}
            is_single_input = len(input_values) == 1 and "__root__" in input_values
+            if input_schema in self.schema_to_mapper:
+                mapper = self.schema_to_mapper[input_schema]
+            else:
+                mapper = _pick_mapper(
+                    list(input_values),
+                    input_schema,
+                    self.builder.type_hints[input_schema],
+                )
+                self.schema_to_mapper[input_schema] = mapper

            branch_channel = CHANNEL_BRANCH_TO.format(key)
            self.channels[branch_channel] = EphemeralValue(Any, guard=False)
@@ -836,13 +806,9 @@ class CompiledStateGraph(CompiledGraph):
                # read state keys and managed values
                channels=(list(input_values) if is_single_input else input_values),
                # coerce state dict to schema class (eg. pydantic model)
-                mapper=_pick_mapper(
-                    list(input_values),
-                    input_schema,
-                    self.builder.type_hints[input_schema],
-                ),
+                mapper=mapper,
                # publish to state keys
-                writers=[ChannelWrite(write_entries, tags=[TAG_HIDDEN])],
+                writers=[ChannelWrite(write_entries)],
                metadata=node.metadata,
                retry_policy=node.retry_policy,
                bound=node.runnable,
@@ -868,9 +834,7 @@ class CompiledStateGraph(CompiledGraph):
            # publish to channel
            for start in starts:
                self.nodes[start].writers.append(
-                    ChannelWrite(
-                        (ChannelWriteEntry(channel_name, start),), tags=[TAG_HIDDEN]
-                    )
+                    ChannelWrite((ChannelWriteEntry(channel_name, start),))
                )

    def attach_branch(
@@ -901,19 +865,33 @@ class CompiledStateGraph(CompiledGraph):
                    config, cast(Sequence[Union[Send, ChannelWriteEntry]], writes)
                )

-        schema = branch.input_schema or (
-            self.builder.nodes[start].input
-            if start in self.builder.nodes
-            else self.builder.schema
-        )
+        if with_reader:
+            # get schema
+            schema = branch.input_schema or (
+                self.builder.nodes[start].input
+                if start in self.builder.nodes
+                else self.builder.schema
+            )
+            channels = list(self.builder.schemas[schema])
+            # get mapper
+            if schema in self.schema_to_mapper:
+                mapper = self.schema_to_mapper[schema]
+            else:
+                mapper = _pick_mapper(channels, schema, self.builder.type_hints[schema])
+                self.schema_to_mapper[schema] = mapper
+            # create reader
+            reader: Optional[Callable[[RunnableConfig], Any]] = partial(
+                ChannelRead.do_read,
+                select=channels[0] if channels == ["__root__"] else channels,
+                fresh=True,
+                # coerce state dict to schema class (eg. pydantic model)
+                mapper=mapper,
+            )
+        else:
+            reader = None

        # attach branch publisher
-        self.nodes[start].writers.append(
-            branch.run(
-                branch_writer,
-                _get_state_reader(self.builder, schema) if with_reader else None,
-            )
-        )
+        self.nodes[start].writers.append(branch.run(branch_writer, reader))

        # attach then subscriber
        if branch.then and branch.then != END:
@@ -928,9 +906,7 @@ class CompiledStateGraph(CompiledGraph):
            for end in ends:
                if end != END:
                    self.nodes[end].writers.append(
-                        ChannelWrite(
-                            [ChannelWriteEntry(channel_name, end)], tags=[TAG_HIDDEN]
-                        )
+                        ChannelWrite((ChannelWriteEntry(channel_name, end),))
                    )

    def _migrate_checkpoint(self, checkpoint: Checkpoint) -> None:
@@ -1038,20 +1014,6 @@ class CompiledStateGraph(CompiledGraph):
                        seen[INTERRUPT].pop(k, MISSING)


-def _get_state_reader(
-    builder: StateGraph, schema: Type[Any]
-) -> Callable[[RunnableConfig], Any]:
-    state_keys = list(builder.channels)
-    select = list(builder.schemas[schema])
-    return partial(
-        ChannelRead.do_read,
-        select=select[0] if select == ["__root__"] else select,
-        fresh=True,
-        # coerce state dict to schema class (eg. pydantic model)
-        mapper=_pick_mapper(state_keys, schema, builder.type_hints[schema]),
-    )
-
-
 def _pick_mapper(
    state_keys: Sequence[str], schema: Type[Any], type_hints: Optional[dict[str, Any]]
 ) -> Optional[Callable[[Any], Any]]:
@@ -1069,9 +1031,9 @@ def _coerce_state(schema: Type[Any], input: dict[str, Any]) -> dict[str, Any]:
    return schema(**input)


-def _control_branch(value: Any) -> Sequence[Union[str, Send]]:
+def _control_branch(value: Any) -> Sequence[tuple[str, Any]]:
    if isinstance(value, Send):
-        return [value]
+        return ((TASKS, value),)
    commands: list[Command] = []
    if isinstance(value, Command):
        commands.append(value)
@@ -1079,51 +1041,45 @@ def _control_branch(value: Any) -> Sequence[Union[str, Send]]:
        for cmd in value:
            if isinstance(cmd, Command):
                commands.append(cmd)
-    rtn: list[Union[str, Send]] = []
+    rtn: list[tuple[str, Any]] = []
    for command in commands:
        if command.graph == Command.PARENT:
            raise ParentCommand(command)
        if isinstance(command.goto, Send):
-            rtn.append(command.goto)
+            rtn.append((TASKS, command.goto))
        elif isinstance(command.goto, str):
-            rtn.append(command.goto)
+            rtn.append((CHANNEL_BRANCH_TO.format(command.goto), None))
        else:
-            rtn.extend(command.goto)
+            rtn.extend(
+                (TASKS, go)
+                if isinstance(go, Send)
+                else (CHANNEL_BRANCH_TO.format(go), None)
+                for go in command.goto
+            )
    return rtn


-async def _acontrol_branch(value: Any) -> Sequence[Union[str, Send]]:
-    if isinstance(value, Send):
-        return [value]
-    commands: list[Command] = []
-    if isinstance(value, Command):
-        commands.append(value)
-    elif isinstance(value, (list, tuple)):
-        for cmd in value:
-            if isinstance(cmd, Command):
-                commands.append(cmd)
-    rtn: list[Union[str, Send]] = []
-    for command in commands:
-        if command.graph == Command.PARENT:
-            raise ParentCommand(command)
-        if isinstance(command.goto, Send):
-            rtn.append(command.goto)
-        elif isinstance(command.goto, str):
-            rtn.append(command.goto)
-        else:
-            rtn.extend(command.goto)
-    return rtn
-
-
-CONTROL_BRANCH_PATH = RunnableCallable(
-    _control_branch,
-    _acontrol_branch,
-    tags=[TAG_HIDDEN],
-    trace=False,
-    recurse=False,
-    func_accepts_config=False,
-)
-CONTROL_BRANCH = Branch(CONTROL_BRANCH_PATH, None)
+def _get_root(input: Any) -> Optional[Sequence[tuple[str, Any]]]:
+    if isinstance(input, Command):
+        if input.graph == Command.PARENT:
+            return ()
+        return input._update_as_tuples()
+    elif (
+        isinstance(input, (list, tuple))
+        and input
+        and any(isinstance(i, Command) for i in input)
+    ):
+        updates: list[tuple[str, Any]] = []
+        for i in input:
+            if isinstance(i, Command):
+                if i.graph == Command.PARENT:
+                    continue
+                updates.extend(i._update_as_tuples())
+            else:
+                updates.append(("__root__", i))
+        return updates
+    elif input is not None:
+        return [("__root__", input)]


 def _get_channels(
@@ -66,6 +66,7 @@ from langgraph.constants import (
    CONFIG_KEY_STREAM,
    CONFIG_KEY_STREAM_WRITER,
    CONFIG_KEY_TASK_ID,
+    CONFIG_KEY_THREAD_ID,
    END,
    ERROR,
    INPUT,
@@ -1044,6 +1045,9 @@ class Pregel(PregelProtocol):
            config = merge_configs(
                config, {CONF: {CONFIG_KEY_CHECKPOINT_NS: recast_checkpoint_ns(ns)}}
            )
+        thread_id = config[CONF][CONFIG_KEY_THREAD_ID]
+        if not isinstance(thread_id, str):
+            config[CONF][CONFIG_KEY_THREAD_ID] = str(thread_id)

        saved = checkpointer.get_tuple(config)
        return self._prepare_state_snapshot(
@@ -1083,6 +1087,9 @@ class Pregel(PregelProtocol):
            config = merge_configs(
                config, {CONF: {CONFIG_KEY_CHECKPOINT_NS: recast_checkpoint_ns(ns)}}
            )
+        thread_id = config[CONF][CONFIG_KEY_THREAD_ID]
+        if not isinstance(thread_id, str):
+            config[CONF][CONFIG_KEY_THREAD_ID] = str(thread_id)

        saved = await checkpointer.aget_tuple(config)
        return await self._aprepare_state_snapshot(
@@ -1128,7 +1135,12 @@ class Pregel(PregelProtocol):
        config = merge_configs(
            self.config,
            config,
-            {CONF: {CONFIG_KEY_CHECKPOINT_NS: checkpoint_ns}},
+            {
+                CONF: {
+                    CONFIG_KEY_CHECKPOINT_NS: checkpoint_ns,
+                    CONFIG_KEY_THREAD_ID: str(config[CONF][CONFIG_KEY_THREAD_ID]),
+                }
+            },
        )
        # eagerly consume list() to avoid holding up the db cursor
        for checkpoint_tuple in list(
@@ -1175,7 +1187,12 @@ class Pregel(PregelProtocol):
        config = merge_configs(
            self.config,
            config,
-            {CONF: {CONFIG_KEY_CHECKPOINT_NS: checkpoint_ns}},
+            {
+                CONF: {
+                    CONFIG_KEY_CHECKPOINT_NS: checkpoint_ns,
+                    CONFIG_KEY_THREAD_ID: str(config[CONF][CONFIG_KEY_THREAD_ID]),
+                }
+            },
        )
        # eagerly consume list() to avoid holding up the db cursor
        for checkpoint_tuple in [
@@ -1595,7 +1612,9 @@ class Pregel(PregelProtocol):

            return patch_checkpoint_map(next_config, saved.metadata if saved else None)

-        current_config = config
+        current_config = patch_configurable(
+            config, {CONFIG_KEY_THREAD_ID: str(config[CONF][CONFIG_KEY_THREAD_ID])}
+        )
        for superstep in supersteps:
            current_config = perform_superstep(current_config, superstep)
        return current_config
@@ -2005,7 +2024,9 @@ class Pregel(PregelProtocol):
                    await checkpointer.aput_writes(next_config, push_writes, task_id)
            return patch_checkpoint_map(next_config, saved.metadata if saved else None)

-        current_config = config
+        current_config = patch_configurable(
+            config, {CONFIG_KEY_THREAD_ID: str(config[CONF][CONFIG_KEY_THREAD_ID])}
+        )
        for superstep in supersteps:
            current_config = await aperform_superstep(current_config, superstep)
        return current_config
@@ -2550,11 +2571,12 @@ class Pregel(PregelProtocol):
        do_stream = (
            next(
                (
-                    cast(_StreamingCallbackHandler, h)
+                    True
                    for h in run_manager.handlers
                    if isinstance(h, _StreamingCallbackHandler)
+                    and not isinstance(h, StreamMessagesHandler)
                ),
-                None,
+                False,
            )
            if _StreamingCallbackHandler is not None
            else False
@@ -2624,7 +2646,7 @@ class Pregel(PregelProtocol):
                    ),
                    put_writes=weakref.WeakMethod(loop.put_writes),
                    schedule_task=weakref.WeakMethod(loop.accept_push),
-                    use_astream=do_stream is not None,
+                    use_astream=do_stream,
                    node_finished=config[CONF].get(CONFIG_KEY_NODE_FINISHED),
                )
                # enable subgraph streaming
@@ -3,13 +3,13 @@ import itertools
 import sys
 import threading
 from collections import defaultdict, deque
+from copy import copy
 from functools import partial
 from hashlib import sha1
 from typing import (
    Any,
    Callable,
    Iterable,
-    Iterator,
    Literal,
    Mapping,
    NamedTuple,
@@ -49,6 +49,7 @@ from langgraph.constants import (
    EMPTY_SEQ,
    ERROR,
    INTERRUPT,
+    MISSING,
    NO_WRITES,
    NS_END,
    NS_SEP,
@@ -63,12 +64,12 @@ from langgraph.constants import (
    TASKS,
    Send,
 )
-from langgraph.errors import EmptyChannelError, InvalidUpdateError
+from langgraph.errors import InvalidUpdateError
 from langgraph.managed.base import ManagedValueMapping
 from langgraph.pregel.call import get_runnable_for_task
-from langgraph.pregel.io import read_channel, read_channels
+from langgraph.pregel.io import read_channels
 from langgraph.pregel.log import logger
-from langgraph.pregel.read import PregelNode
+from langgraph.pregel.read import INPUT_CACHE_KEY_TYPE, PregelNode
 from langgraph.store.base import BaseStore
 from langgraph.types import (
    All,
@@ -423,6 +424,7 @@ def prepare_next_tasks(
        are the tasks themselves. This is the union of all PUSH tasks (Sends)
        and PULL tasks (nodes triggered by edges).
    """
+    input_cache: dict[INPUT_CACHE_KEY_TYPE, Any] = {}
    checkpoint_id_bytes = binascii.unhexlify(checkpoint["id"].replace("-", ""))
    null_version = checkpoint_null_version(checkpoint)
    tasks: list[Union[PregelTask, PregelExecutableTask]] = []
@@ -444,6 +446,7 @@ def prepare_next_tasks(
            store=store,
            checkpointer=checkpointer,
            manager=manager,
+            input_cache=input_cache,
        ):
            tasks.append(task)

@@ -486,6 +489,7 @@ def prepare_next_tasks(
            store=store,
            checkpointer=checkpointer,
            manager=manager,
+            input_cache=input_cache,
        ):
            tasks.append(task)
    return {t.id: t for t in tasks}
@@ -511,6 +515,7 @@ def prepare_single_task(
    store: Optional[BaseStore] = None,
    checkpointer: Optional[BaseCheckpointSaver] = None,
    manager: Union[None, ParentRunManager, AsyncParentRunManager] = None,
+    input_cache: Optional[dict[INPUT_CACHE_KEY_TYPE, Any]] = None,
 ) -> Union[None, PregelTask, PregelExecutableTask]:
    """Prepares a single task for the next Pregel step, given a task path, which
    uniquely identifies a PUSH or PULL task within the graph."""
@@ -729,11 +734,15 @@ def prepare_single_task(
        ):
            triggers = tuple(sorted(proc.triggers))
            try:
-                val = next(
-                    _proc_input(proc, managed, channels, for_execution=for_execution)
+                val = _proc_input(
+                    proc,
+                    managed,
+                    channels,
+                    for_execution=for_execution,
+                    input_cache=input_cache,
                )
-            except StopIteration:
-                return
+                if val is MISSING:
+                    return
            except Exception as exc:
                if SUPPORTS_EXC_NOTES:
                    exc.add_note(
@@ -926,34 +935,32 @@ def _proc_input(
    channels: Mapping[str, BaseChannel],
    *,
    for_execution: bool,
-) -> Iterator[Any]:
+    input_cache: Optional[dict[INPUT_CACHE_KEY_TYPE, Any]],
+) -> Any:
    """Prepare input for a PULL task, based on the process's channels and triggers."""
+    # if in cache return shallow copy
+    if input_cache is not None and proc.input_cache_key in input_cache:
+        return copy(input_cache[proc.input_cache_key])
    # If all trigger channels subscribed by this process are not empty
    # then invoke the process with the values of all non-empty channels
    if isinstance(proc.channels, dict):
-        try:
-            val: dict[str, Any] = {}
-            for k, chan in proc.channels.items():
-                if chan in proc.triggers:
-                    val[k] = read_channel(channels, chan, catch=False)
-                elif chan in channels:
-                    try:
-                        val[k] = read_channel(channels, chan, catch=False)
-                    except EmptyChannelError:
-                        continue
-                else:
-                    val[k] = managed[k]()
-        except EmptyChannelError:
-            return
+        val: dict[str, Any] = {}
+        for k, chan in proc.channels.items():
+            if chan in channels:
+                if channels[chan].is_available():
+                    val[k] = channels[chan].get()
+            else:
+                val[k] = managed[k]()
    elif isinstance(proc.channels, list):
        for chan in proc.channels:
-            try:
-                val = read_channel(channels, chan, catch=False)
-                break
-            except EmptyChannelError:
-                pass
+            if chan in channels:
+                if channels[chan].is_available():
+                    val = channels[chan].get()
+                    break
+            else:
+                val[k] = managed[k]()
        else:
-            return
+            return MISSING
    else:
        raise RuntimeError(
            "Invalid channels type, expected list or dict, got {proc.channels}"
@@ -963,7 +970,11 @@ def _proc_input(
    if for_execution and proc.mapper is not None:
        val = proc.mapper(val)

-    yield val
+    # Cache the input value
+    if input_cache is not None:
+        input_cache[proc.input_cache_key] = val
+
+    return val


 def _uuid5_str(namespace: bytes, *parts: str) -> str:
@@ -10,7 +10,7 @@ from typing import Any, Callable, Generator, Generic, Optional, Sequence, TypeVa
 from langchain_core.runnables import Runnable
 from typing_extensions import ParamSpec

-from langgraph.constants import CONF, CONFIG_KEY_CALL, RETURN, TAG_HIDDEN
+from langgraph.constants import CONF, CONFIG_KEY_CALL, RETURN
 from langgraph.pregel.write import ChannelWrite, ChannelWriteEntry
 from langgraph.types import RetryPolicy
 from langgraph.utils.config import get_config
@@ -197,7 +197,7 @@ def get_runnable_for_task(func: Callable[..., Any]) -> RunnableSeq:
            )
        seq = RunnableSeq(
            run,
-            ChannelWrite([ChannelWriteEntry(RETURN)], tags=[TAG_HIDDEN]),
+            ChannelWrite([ChannelWriteEntry(RETURN)]),
            name=name,
            trace_inputs=functools.partial(
                _explode_args_trace_inputs, inspect.signature(func)
@@ -52,6 +52,7 @@ from langgraph.constants import (
    CONFIG_KEY_SCRATCHPAD,
    CONFIG_KEY_STREAM,
    CONFIG_KEY_TASK_ID,
+    CONFIG_KEY_THREAD_ID,
    EMPTY_SEQ,
    ERROR,
    INPUT,
@@ -285,6 +286,12 @@ class PregelLoop(LoopProtocol):
            )
        else:
            self.checkpoint_config = self.config
+        if thread_id := self.checkpoint_config[CONF].get(CONFIG_KEY_THREAD_ID):
+            if not isinstance(thread_id, str):
+                self.checkpoint_config = patch_configurable(
+                    self.checkpoint_config,
+                    {CONFIG_KEY_THREAD_ID: str(thread_id)},
+                )
        self.checkpoint_ns = (
            tuple(cast(str, self.config[CONF][CONFIG_KEY_CHECKPOINT_NS]).split(NS_SEP))
            if self.config[CONF].get(CONFIG_KEY_CHECKPOINT_NS)
@@ -1043,16 +1050,16 @@ class SyncPregelLoop(PregelLoop, ContextManager):
            saved = None
        if saved is None:
            saved = CheckpointTuple(
-                self.config, empty_checkpoint(), {"step": -2}, None, []
+                self.checkpoint_config, empty_checkpoint(), {"step": -2}, None, []
            )
        elif self._migrate_checkpoint is not None:
            self._migrate_checkpoint(saved.checkpoint)
        self.checkpoint_config = {
-            **self.config,
+            **self.checkpoint_config,
            **saved.config,
            CONF: {
                CONFIG_KEY_CHECKPOINT_NS: "",
-                **self.config.get(CONF, {}),
+                **self.checkpoint_config.get(CONF, {}),
                **saved.config.get(CONF, {}),
            },
        }
@@ -1193,16 +1200,16 @@ class AsyncPregelLoop(PregelLoop, AsyncContextManager):
            saved = None
        if saved is None:
            saved = CheckpointTuple(
-                self.config, empty_checkpoint(), {"step": -2}, None, []
+                self.checkpoint_config, empty_checkpoint(), {"step": -2}, None, []
            )
        elif self._migrate_checkpoint is not None:
            self._migrate_checkpoint(saved.checkpoint)
        self.checkpoint_config = {
-            **self.config,
+            **self.checkpoint_config,
            **saved.config,
            CONF: {
                CONFIG_KEY_CHECKPOINT_NS: "",
-                **self.config.get(CONF, {}),
+                **self.checkpoint_config.get(CONF, {}),
                **saved.config.get(CONF, {}),
            },
        }
@@ -18,7 +18,7 @@ from langchain_core.messages import BaseMessage
 from langchain_core.outputs import ChatGenerationChunk, LLMResult

 from langgraph.constants import NS_SEP, TAG_HIDDEN, TAG_NOSTREAM
-from langgraph.types import StreamChunk
+from langgraph.types import Command, StreamChunk

 try:
    from langchain_core.tracers._streaming import _StreamingCallbackHandler
@@ -153,6 +153,17 @@ class StreamMessagesHandler(BaseCallbackHandler, _StreamingCallbackHandler):
        **kwargs: Any,
    ) -> Any:
        if meta := self.metadata.pop(run_id, None):
+            if isinstance(response, Command):
+                response = response.update
+
+            if isinstance(response, Sequence) and any(
+                isinstance(value, Command) for value in response
+            ):
+                response = [
+                    value.update if isinstance(value, Command) else value
+                    for value in response
+                ]
+
            if isinstance(response, BaseMessage):
                self._emit(meta, response, dedupe=True)
            elif isinstance(response, Sequence):
@@ -30,6 +30,7 @@ from langgraph.utils.config import merge_configs
 from langgraph.utils.runnable import RunnableCallable, RunnableSeq

 READ_TYPE = Callable[[Union[str, Sequence[str]], bool], Union[Any, dict[str, Any]]]
+INPUT_CACHE_KEY_TYPE = tuple[Callable[..., Any], tuple[str, ...]]


 class ChannelRead(RunnableCallable):
@@ -67,6 +68,7 @@ class ChannelRead(RunnableCallable):
            afunc=self._aread,
            tags=tags,
            name=None,
+            trace=False,
            func_accepts_config=True,
        )
        self.fresh = fresh
@@ -231,6 +233,17 @@ class PregelNode(Runnable):
        else:
            return self.bound

+    @cached_property
+    def input_cache_key(self) -> INPUT_CACHE_KEY_TYPE:
+        """Get a cache key for the input to the node.
+        This is used to avoid calculating the same input multiple times."""
+        return (
+            self.mapper,
+            tuple(f"{key}:{value}" for key, value in self.channels.items())
+            if isinstance(self.channels, dict)
+            else tuple(self.channels),
+        )
+
    def join(self, channels: Sequence[str]) -> PregelNode:
        assert isinstance(channels, list) or isinstance(
            channels, tuple
@@ -54,14 +54,14 @@ class ChannelWrite(RunnableCallable):
        self,
        writes: Sequence[Union[ChannelWriteEntry, ChannelWriteTupleEntry, Send]],
        *,
-        tags: Optional[Sequence[str]] = None,
+        tags: Optional[Sequence[str]] = None,  # ignored
        require_at_least_one_of: Optional[Sequence[str]] = None,  # ignored
    ):
        super().__init__(
            func=self._write,
            afunc=self._awrite,
            name=None,
-            tags=tags,
+            trace=False,
            func_accepts_config=True,
        )
        self.writes = cast(
@@ -152,6 +152,8 @@ class ChannelWrite(RunnableCallable):
                tuples.append((w.channel, value))
            else:
                raise ValueError(f"Invalid write entry: {w}")
+        # if we want to persist writes found before hitting a ParentCommand
+        # can move this to a finally block
        write: TYPE_SEND = config[CONF][CONFIG_KEY_SEND]
        write(tuples)

@@ -23,6 +23,7 @@ from langchain_core.runnables import Runnable, RunnableConfig
 from typing_extensions import Self

 from langgraph.checkpoint.base import BaseCheckpointSaver, CheckpointMetadata
+from langgraph.utils.fields import get_update_as_tuples

 if TYPE_CHECKING:
    from langgraph.pregel.protocol import PregelProtocol
@@ -318,7 +319,7 @@ class Command(Generic[N], ToolOutputMixin):
        ):
            return self.update
        elif hints := get_type_hints(type(self.update)):
-            return [(k, getattr(self.update, k)) for k in hints]
+            return get_update_as_tuples(self.update, tuple(hints.keys()))
        elif self.update is not None:
            return [("__root__", self.update)]
        else:
@@ -1,8 +1,14 @@
 import dataclasses
-from typing import Any, Generator, Optional, Type, Union, get_type_hints
+from typing import Any, Generator, Optional, Sequence, Type, Union, get_type_hints

+from pydantic import BaseModel
+from pydantic.v1 import BaseModel as BaseModelV1
 from typing_extensions import Annotated, NotRequired, ReadOnly, Required, get_origin

+# NOTE: this is redefined here separately from langgraph.constants
+# to avoid a circular import
+MISSING = object()
+

 def _is_optional_type(type_: Any) -> bool:
    """Check if a type is Optional."""
@@ -147,3 +153,33 @@ def get_enhanced_type_hints(
            pass

        yield name, typ, default, description
+
+
+def get_update_as_tuples(input: Any, keys: Sequence[str]) -> list[tuple[str, Any]]:
+    """Get Pydantic state update as a list of (key, value) tuples."""
+    # Pydantic v1
+    if isinstance(input, BaseModelV1):
+        keep: Optional[set[str]] = input.__fields_set__
+        defaults = {k: v.default for k, v in input.__fields__.items()}
+    # Pydantic v2
+    elif isinstance(input, BaseModel):
+        keep = input.model_fields_set
+        defaults = {k: v.default for k, v in input.model_fields.items()}
+    else:
+        keep = None
+        defaults = {}
+
+    # NOTE: This behavior for Pydantic is somewhat inelegant,
+    # but we keep around for backwards compatibility
+    # if input is a Pydantic model, only update values
+    # that are different from the default values or in the keep set
+    return [
+        (k, value)
+        for k in keys
+        if (value := getattr(input, k, MISSING)) is not MISSING
+        and (
+            value is not None
+            or defaults.get(k, MISSING) is not None
+            or (keep is not None and k in keep)
+        )
+    ]
@@ -36,6 +36,7 @@ from langchain_core.runnables.config import (
    var_child_runnable_config,
 )
 from langchain_core.runnables.utils import Input, Output
+from langchain_core.tracers.langchain import LangChainTracer
 from typing_extensions import TypeGuard

 from langgraph.constants import (
@@ -60,58 +61,34 @@ except ImportError:


 def _set_config_context(
-    config: RunnableConfig,
-) -> tuple[Token[Optional[RunnableConfig]], Optional[dict[str, Any]]]:
+    config: RunnableConfig, run: Any = None
+) -> Token[Optional[RunnableConfig]]:
    """Set the child Runnable config + tracing context.

    Args:
        config (RunnableConfig): The config to set.
    """
-    from langchain_core.tracers.langchain import LangChainTracer
-
    config_token = var_child_runnable_config.set(config)
-    current_context = None
-    if (
-        (callbacks := config.get("callbacks"))
-        and (
-            parent_run_id := getattr(callbacks, "parent_run_id", None)
-        )  # Is callback manager
-        and (
-            tracer := next(
-                (
-                    handler
-                    for handler in getattr(callbacks, "handlers", [])
-                    if isinstance(handler, LangChainTracer)
-                ),
-                None,
-            )
-        )
-        and (run := tracer.run_map.get(str(parent_run_id)))
-    ):
-        from langsmith.run_helpers import _set_tracing_context, get_tracing_context
+    if run is not None:
+        from langsmith.run_helpers import _set_tracing_context

-        current_context = get_tracing_context()
        _set_tracing_context({"parent": run})
-    return config_token, current_context
+    return config_token


-@contextmanager
-def set_config_context(config: RunnableConfig) -> Generator[Context, None, None]:
+def _unset_config_context(
+    token: Token[Optional[RunnableConfig]], run: Any = None
+) -> None:
    """Set the child Runnable config + tracing context.

    Args:
        config (RunnableConfig): The config to set.
    """
-    from langsmith.run_helpers import _set_tracing_context
+    var_child_runnable_config.reset(token)
+    if run is not None:
+        from langsmith.run_helpers import _set_tracing_context

-    ctx = copy_context()
-    config_token, _ = ctx.run(_set_config_context, config)
-    try:
-        yield ctx
-    finally:
-        ctx.run(var_child_runnable_config.reset, config_token)
-        ctx.run(
-            _set_tracing_context,
+        _set_tracing_context(
            {
                "parent": None,
                "project_name": None,
@@ -119,10 +96,27 @@ def set_config_context(config: RunnableConfig) -> Generator[Context, None, None]
                "metadata": None,
                "enabled": None,
                "client": None,
-            },
+            }
        )


+@contextmanager
+def set_config_context(
+    config: RunnableConfig, run: Any = None
+) -> Generator[Context, None, None]:
+    """Set the child Runnable config + tracing context.
+
+    Args:
+        config (RunnableConfig): The config to set.
+    """
+    ctx = copy_context()
+    config_token = ctx.run(_set_config_context, config, run)
+    try:
+        yield ctx
+    finally:
+        ctx.run(_unset_config_context, config_token, run)
+
+
 # Before Python 3.11 native StrEnum is not available
 class StrEnum(str, enum.Enum):
    """A string enum."""
@@ -363,7 +357,15 @@ class RunnableCallable(Runnable):
            )
            try:
                child_config = patch_config(config, callbacks=run_manager.get_child())
-                with set_config_context(child_config) as context:
+                # get the run
+                for h in run_manager.handlers:
+                    if isinstance(h, LangChainTracer):
+                        run = h.run_map.get(str(run_manager.run_id))
+                        break
+                else:
+                    run = None
+                # run in context
+                with set_config_context(child_config, run) as context:
                    ret = context.run(self.func, *args, **kwargs)
            except BaseException as e:
                run_manager.on_chain_error(e)
@@ -371,9 +373,8 @@ class RunnableCallable(Runnable):
            else:
                run_manager.on_chain_end(ret)
        else:
-            with set_config_context(config) as context:
-                ret = context.run(self.func, *args, **kwargs)
-        if isinstance(ret, Runnable) and self.recurse:
+            ret = self.func(*args, **kwargs)
+        if self.recurse and isinstance(ret, Runnable):
            return ret.invoke(input, config)
        return ret

@@ -417,25 +418,26 @@ class RunnableCallable(Runnable):
            )
            try:
                child_config = patch_config(config, callbacks=run_manager.get_child())
-                with set_config_context(child_config) as context:
-                    coro = cast(Coroutine[None, None, Any], self.afunc(*args, **kwargs))
-                    if ASYNCIO_ACCEPTS_CONTEXT:
-                        ret = await asyncio.create_task(coro, context=context)
+                coro = cast(Coroutine[None, None, Any], self.afunc(*args, **kwargs))
+                if ASYNCIO_ACCEPTS_CONTEXT:
+                    for h in run_manager.handlers:
+                        if isinstance(h, LangChainTracer):
+                            run = h.run_map.get(str(run_manager.run_id))
+                            break
                    else:
-                        ret = await coro
+                        run = None
+                    with set_config_context(child_config, run) as context:
+                        ret = await asyncio.create_task(coro, context=context)
+                else:
+                    ret = await coro
            except BaseException as e:
                await run_manager.on_chain_error(e)
                raise
            else:
                await run_manager.on_chain_end(ret)
        else:
-            with set_config_context(config) as context:
-                if ASYNCIO_ACCEPTS_CONTEXT:
-                    coro = cast(Coroutine[None, None, Any], self.afunc(*args, **kwargs))
-                    ret = await asyncio.create_task(coro, context=context)
-                else:
-                    ret = await self.afunc(*args, **kwargs)
-        if isinstance(ret, Runnable) and self.recurse:
+            ret = await self.afunc(*args, **kwargs)
+        if self.recurse and isinstance(ret, Runnable):
            return await ret.ainvoke(input, config)
        return ret

@@ -598,7 +600,6 @@ class RunnableSeq(Runnable):
            name=config.get("run_name") or self.get_name(),
            run_id=config.pop("run_id", None),
        )
-
        # invoke all steps in sequence
        try:
            for i, step in enumerate(self.steps):
@@ -606,8 +607,19 @@ class RunnableSeq(Runnable):
                config = patch_config(
                    config, callbacks=run_manager.get_child(f"seq:step:{i + 1}")
                )
+                # 1st step is the actual node,
+                # others are writers which don't need to be run in context
                if i == 0:
-                    input = step.invoke(input, config, **kwargs)
+                    # get the run object
+                    for h in run_manager.handlers:
+                        if isinstance(h, LangChainTracer):
+                            run = h.run_map.get(str(run_manager.run_id))
+                            break
+                    else:
+                        run = None
+                    # run in context
+                    with set_config_context(config, run) as context:
+                        input = context.run(step.invoke, input, config, **kwargs)
                else:
                    input = step.invoke(input, config)
        # finish the root run
@@ -643,8 +655,24 @@ class RunnableSeq(Runnable):
                config = patch_config(
                    config, callbacks=run_manager.get_child(f"seq:step:{i + 1}")
                )
+                # 1st step is the actual node,
+                # others are writers which don't need to be run in context
                if i == 0:
-                    input = await step.ainvoke(input, config, **kwargs)
+                    if ASYNCIO_ACCEPTS_CONTEXT:
+                        # get the run object
+                        for h in run_manager.handlers:
+                            if isinstance(h, LangChainTracer):
+                                run = h.run_map.get(str(run_manager.run_id))
+                                break
+                        else:
+                            run = None
+                        # run in context
+                        with set_config_context(config, run) as context:
+                            input = await asyncio.create_task(
+                                step.ainvoke(input, config, **kwargs), context=context
+                            )
+                    else:
+                        input = await step.ainvoke(input, config, **kwargs)
                else:
                    input = await step.ainvoke(input, config)
        # finish the root run
@@ -672,53 +700,48 @@ class RunnableSeq(Runnable):
            name=config.get("run_name") or self.get_name(),
            run_id=config.pop("run_id", None),
        )
-
-        try:
-            # stream the last steps
-            # transform the input stream of each step with the next
-            # steps that don't natively support transforming an input stream will
-            # buffer input in memory until all available, and then start emitting output
-            for idx, step in enumerate(self.steps):
-                config = patch_config(
-                    config,
-                    callbacks=run_manager.get_child(f"seq:step:{idx + 1}"),
-                )
-                if idx == 0:
-                    iterator = step.stream(input, config, **kwargs)
-                else:
-                    iterator = step.transform(iterator, config)
-            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)
-            output: Any = None
-            add_supported = False
-            for chunk in iterator:
-                yield chunk
-                # collect final output
-                if output is None:
-                    output = chunk
-                elif add_supported:
-                    try:
-                        output = output + chunk
-                    except TypeError:
-                        output = chunk
-                        add_supported = False
-                else:
-                    output = chunk
-        except BaseException as e:
-            run_manager.on_chain_error(e)
-            raise
+        # get the run object
+        for h in run_manager.handlers:
+            if isinstance(h, LangChainTracer):
+                run = h.run_map.get(str(run_manager.run_id))
+                break
        else:
-            run_manager.on_chain_end(output)
+            run = None
+        # create first step config
+        config = patch_config(
+            config,
+            callbacks=run_manager.get_child(f"seq:step:{1}"),
+        )
+        # run all in context
+        with set_config_context(config, run) as context:
+            try:
+                # stream the last steps
+                # transform the input stream of each step with the next
+                # steps that don't natively support transforming an input stream will
+                # buffer input in memory until all available, and then start emitting output
+                for idx, step in enumerate(self.steps):
+                    if idx == 0:
+                        iterator = step.stream(input, config, **kwargs)
+                    else:
+                        config = patch_config(
+                            config,
+                            callbacks=run_manager.get_child(f"seq:step:{idx + 1}"),
+                        )
+                        iterator = step.transform(iterator, config)
+                # populates streamed_output in astream_log() output if needed
+                if _StreamingCallbackHandler is not None:
+                    for h in run_manager.handlers:
+                        if isinstance(h, _StreamingCallbackHandler):
+                            iterator = h.tap_output_iter(run_manager.run_id, iterator)
+                # consume into final output
+                output = context.run(_consume_iter, iterator)
+                # sequence doesn't emit output, yield to mark as generator
+                yield
+            except BaseException as e:
+                run_manager.on_chain_error(e)
+                raise
+            else:
+                run_manager.on_chain_end(output)

    async def astream(
        self,
@@ -737,53 +760,121 @@ class RunnableSeq(Runnable):
            name=config.get("run_name") or self.get_name(),
            run_id=config.pop("run_id", None),
        )
-
-        try:
-            async with AsyncExitStack() as stack:
-                # stream the last steps
-                # transform the input stream of each step with the next
-                # steps that don't natively support transforming an input stream will
-                # buffer input in memory until all available, and then start emitting output
-                for idx, step in enumerate(self.steps):
-                    config = patch_config(
-                        config,
-                        callbacks=run_manager.get_child(f"seq:step:{idx + 1}"),
-                    )
-                    if idx == 0:
-                        aiterator = step.astream(input, config, **kwargs)
-                    else:
-                        aiterator = step.atransform(aiterator, config)
-                    if hasattr(aiterator, "aclose"):
-                        stack.push_async_callback(aiterator.aclose)
-                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(
-                        run_manager.run_id, aiterator
-                    )
-                output: Any = None
-                add_supported = False
-                async for chunk in aiterator:
-                    yield chunk
-                    # collect final output
-                    if add_supported:
-                        try:
-                            output = output + chunk
-                        except TypeError:
-                            output = chunk
-                            add_supported = False
-                    else:
-                        output = chunk
-        except BaseException as e:
-            await run_manager.on_chain_error(e)
-            raise
+        # stream the last steps
+        # transform the input stream of each step with the next
+        # steps that don't natively support transforming an input stream will
+        # buffer input in memory until all available, and then start emitting output
+        if ASYNCIO_ACCEPTS_CONTEXT:
+            # get the run object
+            for h in run_manager.handlers:
+                if isinstance(h, LangChainTracer):
+                    run = h.run_map.get(str(run_manager.run_id))
+                    break
+            else:
+                run = None
+            # create first step config
+            config = patch_config(
+                config,
+                callbacks=run_manager.get_child(f"seq:step:{1}"),
+            )
+            # run all in context
+            with set_config_context(config, run) as context:
+                try:
+                    async with AsyncExitStack() as stack:
+                        for idx, step in enumerate(self.steps):
+                            if idx == 0:
+                                aiterator = step.astream(input, config, **kwargs)
+                            else:
+                                config = patch_config(
+                                    config,
+                                    callbacks=run_manager.get_child(
+                                        f"seq:step:{idx + 1}"
+                                    ),
+                                )
+                                aiterator = step.atransform(aiterator, config)
+                            if hasattr(aiterator, "aclose"):
+                                stack.push_async_callback(aiterator.aclose)
+                        # populates streamed_output in astream_log() output if needed
+                        if _StreamingCallbackHandler is not None:
+                            for h in run_manager.handlers:
+                                if isinstance(h, _StreamingCallbackHandler):
+                                    aiterator = h.tap_output_aiter(
+                                        run_manager.run_id, aiterator
+                                    )
+                        # consume into final output
+                        output = await asyncio.create_task(
+                            _consume_aiter(aiterator), context=context
+                        )
+                        # sequence doesn't emit output, yield to mark as generator
+                        yield
+                except BaseException as e:
+                    await run_manager.on_chain_error(e)
+                    raise
+                else:
+                    await run_manager.on_chain_end(output)
        else:
-            await run_manager.on_chain_end(output)
+            try:
+                async with AsyncExitStack() as stack:
+                    for idx, step in enumerate(self.steps):
+                        config = patch_config(
+                            config,
+                            callbacks=run_manager.get_child(f"seq:step:{idx + 1}"),
+                        )
+                        if idx == 0:
+                            aiterator = step.astream(input, config, **kwargs)
+                        else:
+                            aiterator = step.atransform(aiterator, config)
+                        if hasattr(aiterator, "aclose"):
+                            stack.push_async_callback(aiterator.aclose)
+                    # populates streamed_output in astream_log() output if needed
+                    if _StreamingCallbackHandler is not None:
+                        for h in run_manager.handlers:
+                            if isinstance(h, _StreamingCallbackHandler):
+                                aiterator = h.tap_output_aiter(
+                                    run_manager.run_id, aiterator
+                                )
+                    # consume into final output
+                    output = await _consume_aiter(aiterator)
+                    # sequence doesn't emit output, yield to mark as generator
+                    yield
+            except BaseException as e:
+                await run_manager.on_chain_error(e)
+                raise
+            else:
+                await run_manager.on_chain_end(output)
+
+
+def _consume_iter(it: Iterator[Any]) -> Any:
+    """Consume an iterator."""
+    output: Any = None
+    add_supported = False
+    for chunk in it:
+        # collect final output
+        if output is None:
+            output = chunk
+        elif add_supported:
+            try:
+                output = output + chunk
+            except TypeError:
+                output = chunk
+                add_supported = False
+        else:
+            output = chunk
+    return output
+
+
+async def _consume_aiter(it: AsyncIterator[Any]) -> Any:
+    """Consume an async iterator."""
+    output: Any = None
+    add_supported = False
+    async for chunk in it:
+        # collect final output
+        if add_supported:
+            try:
+                output = output + chunk
+            except TypeError:
+                output = chunk
+                add_supported = False
+        else:
+            output = chunk
+    return output
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langgraph"
-version = "0.3.28"
+version = "0.3.30"
 description = "Building stateful, multi-actor applications with LLMs"
 authors = []
 license = "MIT"
@@ -4660,7 +4660,7 @@ def test_root_graph(
                    content="result for query",
                    name="search_api",
                    tool_call_id="tool_call123",
-                    id="00000000-0000-4000-8000-000000000040",
+                    id="00000000-0000-4000-8000-000000000024",
                )
            ]
        },
@@ -4683,7 +4683,7 @@ def test_root_graph(
                    content="result for another",
                    name="search_api",
                    tool_call_id="tool_call456",
-                    id="00000000-0000-4000-8000-000000000049",
+                    id="00000000-0000-4000-8000-000000000030",
                )
            ]
        },
@@ -5387,7 +5387,7 @@ def test_root_graph(
        "__root__": [
            HumanMessage(
                content="what is weather in sf",
-                id="00000000-0000-4000-8000-000000000083",
+                id="00000000-0000-4000-8000-000000000051",
            ),
            AIMessage(
                content="",
@@ -5407,7 +5407,7 @@ def test_root_graph(
            ),
            AIMessage(content="answer", id="ai2"),
            AIMessage(
-                content="an extra message", id="00000000-0000-4000-8000-000000000107"
+                content="an extra message", id="00000000-0000-4000-8000-000000000066"
            ),
            HumanMessage(content="what is weather in la"),
        ],
@@ -6156,7 +6156,7 @@ def test_falsy_return_from_task(
        falsy_task().result()
        interrupt("test")

-    configurable = {"configurable": {"thread_id": str(uuid.uuid4())}}
+    configurable = {"configurable": {"thread_id": uuid.uuid4()}}
    assert [
        chunk for chunk in graph.stream({"a": 5}, configurable, stream_mode="debug")
    ] == [
@@ -6169,7 +6169,7 @@ def test_falsy_return_from_task(
                        "checkpoint_ns": "",
                        "thread_id": AnyStr(),
                    },
-                    "metadata": configurable["configurable"],
+                    "metadata": {},
                    "recursion_limit": 25,
                    "tags": [],
                },
@@ -6177,7 +6177,6 @@ def test_falsy_return_from_task(
                    "parents": {},
                    "source": "input",
                    "step": -1,
-                    "thread_id": AnyStr(),
                    "writes": {
                        "__start__": {
                            "a": 5,
@@ -6268,6 +6267,7 @@ def test_falsy_return_from_task(
            "type": "task_result",
        },
    ]
+    print(type(configurable["configurable"]["thread_id"]))
    assert [
        c
        for c in graph.stream(Command(resume="123"), configurable, stream_mode="debug")
@@ -6281,7 +6281,7 @@ def test_falsy_return_from_task(
                        "checkpoint_ns": "",
                        "thread_id": AnyStr(),
                    },
-                    "metadata": configurable["configurable"],
+                    "metadata": {},
                    "recursion_limit": 25,
                    "tags": [],
                },
@@ -6376,7 +6376,7 @@ def test_falsy_return_from_task(
                        "checkpoint_ns": "",
                        "thread_id": AnyStr(),
                    },
-                    "metadata": configurable["configurable"],
+                    "metadata": {},
                    "recursion_limit": 25,
                    "tags": [],
                },
@@ -6384,7 +6384,6 @@ def test_falsy_return_from_task(
                    "parents": {},
                    "source": "loop",
                    "step": 0,
-                    "thread_id": AnyStr(),
                    "writes": {
                        "falsy_task": False,
                        "graph": None,
@@ -6398,7 +6397,7 @@ def test_falsy_return_from_task(
                        "checkpoint_ns": "",
                        "thread_id": AnyStr(),
                    },
-                    "metadata": configurable["configurable"],
+                    "metadata": {},
                    "recursion_limit": 25,
                    "tags": [],
                },
@@ -7168,6 +7167,52 @@ def test_tags_stream_mode_messages() -> None:
    ]


+def test_stream_mode_messages_command() -> None:
+    from langchain_core.messages import HumanMessage
+
+    def my_node(state):
+        return {"messages": HumanMessage(content="foo")}
+
+    def my_other_node(state):
+        return Command(update={"messages": HumanMessage(content="bar")})
+
+    graph = (
+        StateGraph(MessagesState)
+        .add_sequence([my_node, my_other_node])
+        .add_edge(START, "my_node")
+        .compile()
+    )
+    assert list(
+        graph.stream(
+            {
+                "messages": [],
+            },
+            stream_mode="messages",
+        )
+    ) == [
+        (
+            _AnyIdHumanMessage(content="foo"),
+            {
+                "langgraph_step": 1,
+                "langgraph_node": "my_node",
+                "langgraph_triggers": ("branch:to:my_node",),
+                "langgraph_path": ("__pregel_pull", "my_node"),
+                "langgraph_checkpoint_ns": AnyStr("my_node:"),
+            },
+        ),
+        (
+            _AnyIdHumanMessage(content="bar"),
+            {
+                "langgraph_step": 2,
+                "langgraph_node": "my_other_node",
+                "langgraph_triggers": ("branch:to:my_other_node",),
+                "langgraph_path": ("__pregel_pull", "my_other_node"),
+                "langgraph_checkpoint_ns": AnyStr("my_other_node:"),
+            },
+        ),
+    ]
+
+
 def test_node_destinations() -> None:
    class State(TypedDict):
        foo: Annotated[str, operator.add]
@@ -7246,6 +7291,39 @@ def test_pydantic_none_state_update() -> None:
    assert graph.invoke({"foo": ""}) == {"foo": None}


+def test_pydantic_state_update_command() -> None:
+    from pydantic import BaseModel
+
+    class State(BaseModel):
+        foo: Optional[str]
+
+    def node_a(state: State) -> State:
+        return Command(update=State(foo=None))
+
+    graph = StateGraph(State).add_node(node_a).add_edge(START, "node_a").compile()
+    assert graph.invoke({"foo": ""}) == {"foo": None}
+
+    class State(BaseModel):
+        foo: Optional[str] = None
+        bar: Optional[str] = None
+
+    def node_a(state: State):
+        return State(foo="foo")
+
+    def node_b(state: State):
+        return Command(update=State(bar="bar"))
+
+    builder = StateGraph(State)
+    builder.add_node(node_a)
+    builder.add_node(node_b)
+    builder.add_edge(START, "node_a")
+    builder.add_edge("node_a", "node_b")
+    builder.add_edge("node_b", END)
+    graph = builder.compile()
+
+    assert graph.invoke(State()) == {"foo": "foo", "bar": "bar"}
+
+
 def test_pydantic_state_mutation() -> None:
    from pydantic import BaseModel, Field

@@ -7280,6 +7358,40 @@ def test_pydantic_state_mutation() -> None:
    assert graph.invoke({"outer": 1}) == {"outer": 10, "inner": Inner(a=5)}


+def test_pydantic_state_mutation_command() -> None:
+    from pydantic import BaseModel, Field
+
+    class Inner(BaseModel):
+        a: int = 0
+
+    class State(BaseModel):
+        inner: Inner = Inner()
+        outer: int = 0
+
+    def my_node(state: State) -> State:
+        state.inner.a = 5
+        state.outer = 10
+        return Command(update=state)
+
+    graph = StateGraph(State).add_node(my_node).add_edge(START, "my_node").compile()
+
+    assert graph.invoke({"outer": 1}) == {"outer": 10, "inner": Inner(a=5)}
+
+    # test w/ default_factory
+    class State(BaseModel):
+        inner: Inner = Field(default_factory=Inner)
+        outer: int = 0
+
+    def my_node(state: State) -> State:
+        state.inner.a = 5
+        state.outer = 10
+        return Command(update=state)
+
+    graph = StateGraph(State).add_node(my_node).add_edge(START, "my_node").compile()
+
+    assert graph.invoke({"outer": 1}) == {"outer": 10, "inner": Inner(a=5)}
+
+
 def test_get_stream_writer() -> None:
    class State(TypedDict):
        foo: str
@@ -7894,6 +7894,53 @@ async def test_tags_stream_mode_messages() -> None:
    ]


+async def test_stream_mode_messages_command() -> None:
+    from langchain_core.messages import HumanMessage
+
+    async def my_node(state):
+        return {"messages": HumanMessage(content="foo")}
+
+    async def my_other_node(state):
+        return Command(update={"messages": HumanMessage(content="bar")})
+
+    graph = (
+        StateGraph(MessagesState)
+        .add_sequence([my_node, my_other_node])
+        .add_edge(START, "my_node")
+        .compile()
+    )
+    assert [
+        c
+        async for c in graph.astream(
+            {
+                "messages": [],
+            },
+            stream_mode="messages",
+        )
+    ] == [
+        (
+            _AnyIdHumanMessage(content="foo"),
+            {
+                "langgraph_step": 1,
+                "langgraph_node": "my_node",
+                "langgraph_triggers": ("branch:to:my_node",),
+                "langgraph_path": ("__pregel_pull", "my_node"),
+                "langgraph_checkpoint_ns": AnyStr("my_node:"),
+            },
+        ),
+        (
+            _AnyIdHumanMessage(content="bar"),
+            {
+                "langgraph_step": 2,
+                "langgraph_node": "my_other_node",
+                "langgraph_triggers": ("branch:to:my_other_node",),
+                "langgraph_path": ("__pregel_pull", "my_other_node"),
+                "langgraph_checkpoint_ns": AnyStr("my_other_node:"),
+            },
+        ),
+    ]
+
+
 async def test_stream_messages_dedupe_inputs() -> None:
    from langchain_core.messages import AIMessage

@@ -1,6 +1,6 @@
 {
  "name": "@langchain/langgraph-sdk",
-  "version": "0.0.66",
+  "version": "0.0.67",
  "description": "Client library for interacting with the LangGraph API",
  "type": "module",
  "packageManager": "yarn@1.22.19",
@@ -84,18 +84,37 @@ class BaseClient {
  protected defaultHeaders: Record<string, string | null | undefined>;

  constructor(config?: ClientConfig) {
-    this.asyncCaller = new AsyncCaller({
+    const callerOptions = {
      maxRetries: 4,
      maxConcurrency: 4,
      ...config?.callerOptions,
-    });
+    };

+    let defaultApiUrl = "http://localhost:8123";
+    if (
+      !config?.apiUrl &&
+      typeof globalThis === "object" &&
+      globalThis != null
+    ) {
+      const fetchSmb = Symbol.for("langgraph_api:fetch");
+      const urlSmb = Symbol.for("langgraph_api:url");
+
+      const global = globalThis as unknown as {
+        [fetchSmb]?: typeof fetch;
+        [urlSmb]?: string;
+      };
+
+      if (global[fetchSmb]) callerOptions.fetch ??= global[fetchSmb];
+      if (global[urlSmb]) defaultApiUrl = global[urlSmb];
+    }
+
+    this.asyncCaller = new AsyncCaller(callerOptions);
    this.timeoutMs = config?.timeoutMs;

    // default limit being capped by Chrome
    // https://github.com/nodejs/undici/issues/1373
    // Regex to remove trailing slash, if present
-    this.apiUrl = config?.apiUrl?.replace(/\/$/, "") || "http://localhost:8123";
+    this.apiUrl = config?.apiUrl?.replace(/\/$/, "") || defaultApiUrl;
    this.defaultHeaders = config?.defaultHeaders || {};
    const apiKey = getApiKey(config?.apiKey);
    if (apiKey) {
@@ -1 +1,6 @@
-export { useStream, type MessageMetadata } from "./stream.js";
+export {
+  useStream,
+  type MessageMetadata,
+  type UseStream,
+  type UseStreamOptions,
+} from "./stream.js";
@@ -405,7 +405,7 @@ type GetCustomEventType<Bag extends BagTemplate> = Bag extends {
  ? Bag["CustomEventType"]
  : unknown;

-interface UseStreamOptions<
+export interface UseStreamOptions<
  StateType extends Record<string, unknown> = Record<string, unknown>,
  Bag extends BagTemplate = BagTemplate,
 > {
Author	SHA1	Message	Date
David DuongandGitHub	6ee112851c	fix(cli): only render progress when in TTY (#4299 ) Prevents logging terminal clear commands in non-TTY environments (LangSmith / CI)	2025-04-16 23:41:35 +02:00
Tat Dat Duong	960f612dd7	Bump to 0.2.4	2025-04-16 23:34:54 +02:00
Tat Dat Duong	43af618bb5	Remove negation	2025-04-16 23:28:07 +02:00
Tat Dat Duong	9b87b45322	retrigger checks	2025-04-16 22:33:58 +02:00
David DuongandGitHub	39adc05357	fix(docs): fix typo (#4301 )	2025-04-16 22:29:00 +02:00
Tat Dat Duong	c5ac80d2f0	fix(docs): fix typo	2025-04-16 22:28:27 +02:00
Tat Dat Duong	2fc941c1df	fix(cli): only render progress when in TTY Prevents logging terminal clear commands in non-TTY environments (LangSmith / CI)	2025-04-16 21:25:21 +02:00
Vadym BardaandGitHub	7bafc5dd36	docs: add more prominent workflows link (#4297 )	2025-04-16 18:29:54 +00:00
David DuongandGitHub	c78588b995	feat(sdk-js): export more useStream types, allow loopback clients using globals (#4295 )	2025-04-16 17:14:25 +02:00
Tat Dat Duong	ecb15acb80	feat(sdk-js): export more useStream types, allow loopback clients using globals	2025-04-16 17:10:44 +02:00
Nuno CamposandGitHub	07ba931105	Stringify thread_id when of a different type (#4281 )	2025-04-15 17:07:26 -07:00
Nuno Campos	88ccde6274	Same in get/update state/history	2025-04-15 17:01:01 -07:00
Nuno Campos	5cca153b72	Fix	2025-04-15 16:52:52 -07:00
HeardACatandGitHub	63ebb3a846	docs: rename parallel_workflow --> prompt_chaining_workflow (#4283 ) Make the docs clearer within the prompt chaining section	2025-04-15 17:38:39 -04:00
Nuno Campos	48c08421fa	Stringify thread_id when of a different type	2025-04-15 12:51:33 -07:00
William FHandGitHub	cd967c40ac	Add function templates (#4270 )	2025-04-15 11:51:20 -07:00
Andrew NguonlyandGitHub	854b76addd	docs: Update LangGraph Platform autoscaling docs (#4268 )	2025-04-14 15:55:07 -07:00
Vadym BardaandGitHub	73b3535c4d	langgraph: release 0.3.30 (#4267 )	2025-04-14 17:05:10 -04:00
Nuno CamposandGitHub	3e0629c56c	langgraph: support streaming messages from Command.update (#4250 )	2025-04-14 12:25:20 -07:00
vbarda	04dd69b1cd	simplify	2025-04-14 14:53:08 -04:00
Nuno CamposandGitHub	ff22eb6495	langgraph: handle pydantic updates consistently in Command (#4255 ) Fixes https://github.com/langchain-ai/langgraph/issues/3950	2025-04-14 11:47:22 -07:00
vbarda	07ca03ff15	lower depth	2025-04-14 14:12:40 -04:00
William FHandGitHub	6eea15ec3b	Add store in platform (#4266 )	2025-04-14 17:52:14 +00:00
vbarda	0e111b2f44	3.9	2025-04-14 13:23:26 -04:00
vbarda	b526fe0a4b	set max recursion depth	2025-04-14 13:21:00 -04:00
vbarda	062bf4d717	Merge branch 'vb/fix-command-messages' of github.com:langchain-ai/langgraph into vb/fix-command-messages	2025-04-14 13:20:48 -04:00
vbarda	173f4f6ccf	Merge branch 'main' into vb/fix-command-messages	2025-04-14 13:13:49 -04:00
Vadym BardaandGitHub	9a45a5b0f2	Merge branch 'main' into vb/pydantic-command	2025-04-14 13:06:22 -04:00
vbarda	2c557e9e46	move to fields	2025-04-14 13:00:03 -04:00
William FHandGitHub	6c34e599ab	Re-warn for omitted nav (#4265 )	2025-04-14 09:56:41 -07:00
vbarda	d4224a7abb	Merge branch 'main' into vb/pydantic-command	2025-04-14 12:56:22 -04:00
Andrew NguonlyandGitHub	c700dab97c	docs: Add docs for `LANGSMITH_TRACING` env var (#4257 )	2025-04-13 15:33:44 -07:00
vbarda	704b78b8fe	tests	2025-04-12 10:45:10 -04:00
vbarda	2ed453debe	factor out util	2025-04-12 10:34:02 -04:00
Nuno Campos	62b2580ad5	0.3.29	2025-04-11 16:21:09 -07:00
Nuno Campos	dfbf0ddbcb	Don't run branch reader in bg thread	2025-04-11 16:20:45 -07:00
Nuno CamposandGitHub	41bb20ee5e	Reduce perf impact of set_context (#4256 ) - call it less often - find the run from the run manager at callsite	2025-04-11 15:32:42 -07:00
Nuno Campos	560d6a1f65	Reduce perf impact of set_context - call it less often - find the run from the run manager at callsite	2025-04-11 15:01:17 -07:00
vbarda	dc6fa9ed30	langgraph: handle pydantic updates consistently in Command	2025-04-11 17:51:56 -04:00
Andrew NguonlyandGitHub	a9be75f745	docs: Add Data Plane features sections for custom Postgres/Redis, tracing, telemetry, and licensing (#4254 )	2025-04-11 14:48:20 -07:00
Nuno CamposandGitHub	20e3469296	Merge branch 'main' into vb/fix-command-messages	2025-04-11 14:27:26 -07:00
Eugene Yurtsev GitHub Catherine	233cca1357	Update langgraph_platform.md (#4251 ) Co-authored-by: Catherine <catherine@langchain.dev>	2025-04-11 15:29:11 -04:00
Andrew NguonlyandGitHub	d1ac0a0e13	docs: Add alpha and beta labels for respective LangGraph Platform deployment options (#4249 ) ### Summary Examples: ![image](https://github.com/user-attachments/assets/2a36a262-5373-498d-9907-19d5447fbb6a) ![image](https://github.com/user-attachments/assets/70671e08-34b6-40ed-964d-9d195ea8308d) ![image](https://github.com/user-attachments/assets/fcb877a6-475c-47a4-b8af-91cbdc00f89b)	2025-04-11 12:01:43 -07:00
vbarda	5071a6cd97	langgraph: support streaming messages from Command.update	2025-04-11 14:05:13 -04:00
Nuno CamposandGitHub	72d7b23638	Use tuple entry for control branch (#4248 )	2025-04-11 10:29:44 -07:00
Nuno Campos	64aa1e6cd8	Use tuple entry for control branch	2025-04-11 09:53:54 -07:00
Nuno CamposandGitHub	d6f2f0c90d	Simplify path for control branch attached to every node (#4247 ) - attached to every node to handle command/send return values - used to be a full blown conditional edge, can be simpler by doing all of it in a single function	2025-04-11 09:44:18 -07:00
Nuno Campos	5a7edead8c	Lint	2025-04-11 09:20:10 -07:00
Nuno Campos	8ff5c43cf0	Avoid creating contexts for control branches	2025-04-11 09:10:58 -07:00
Nuno CamposandGitHub	0eb32a4251	Avoid validating node input more than once per superstep (#4242 )	2025-04-11 09:06:07 -07:00
Nuno Campos	3d12a2df59	Simplify path for control branch attached to every node - attached to every node to handle command/send return values - used to be a full blown conditional edge, can be simpler by doing all of it in a single function	2025-04-11 09:00:16 -07:00
Nuno Campos	04d3c9d30f	Use cache in attach_branch too	2025-04-11 08:38:14 -07:00
Nuno Campos	4d1b3370df	Lint	2025-04-10 17:38:25 -07:00
Nuno Campos	bf5017f6e0	Lint	2025-04-10 17:29:36 -07:00
Nuno Campos	64086aa814	Avoid validating node input more than once per superstep	2025-04-10 17:28:00 -07:00