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Sydney Runkle
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docs/docs/cloud/deployment/egress.md
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# Egress for Subscription Metrics and Operational Metadata
> **Important: Self Hosted Only**
> This section only applies to customers who are not running in offline mode and assumes you are using a self-hosted LangGraph Platform instance.
> This does not apply to SaaS or Hybrid deployments.
Self-Hosted LangGraph Platform instances store all information locally and will never send sensitive information outside of your network. We currently only track platform usage for billing purposes according to the entitlements in your order. In order to better remotely support our customers, we do require egress to `https://beacon.langchain.com`.
In the future, we will be introducing support diagnostics to help us ensure that the LangGraph Platform is running at an optimal level within your environment.
> **Warning**
> **This will require egress to `https://beacon.langchain.com` from your network.**
> **If using an API key, you will also need to allow egress to `https://api.smith.langchain.com` or `https://eu.api.smith.langchain.com` for API key verification.**
Generally, data that we send to Beacon can be categorized as follows:
- **Subscription Metrics**
- Subscription metrics are used to determine level of access and utilization of LangSmith. This includes, but are not limited to:
- Nodes Executed
- Runs Executed
- License Key Verification
- **Operational Metadata**
- This metadata will contain and collect the above subscription metrics to assist with remote support, allowing the LangChain team to diagnose and troubleshoot performance issues more effectively and proactively.
## Example Payloads
In an effort to maximize transparency, we provide sample payloads here:
### License Verification (If using an Enterprise License)
**Endpoint:**
`POST beacon.langchain.com/v1/beacon/verify`
**Request:**
```json
{
"license": "<YOUR_LICENSE_KEY>"
}
```
**Response:**
```json
{
"token": "Valid JWT" // Short-lived JWT token to avoid repeated license checks
}
```
### Api Key Verification (If using a LangSmith API Key)
**Endpoint:**
`POST api.smith.langchain.com/auth`
**Request:**
```json
"Headers": {
X-Api-Key: <YOUR_API_KEY>
}
```
**Response:**
```json
{
"org_config": {
"org_id": "3a1c2b6f-4430-4b92-8a5b-79b8b567bbc1",
... // Additional organization details
}
}
```
### Usage Reporting
**Endpoint:**
`POST beacon.langchain.com/v1/metadata/submit`
**Request:**
```json
{
"license": "<YOUR_LICENSE_KEY>",
"from_timestamp": "2025-01-06T09:00:00Z",
"to_timestamp": "2025-01-06T10:00:00Z",
"tags": {
"langgraph.python.version": "0.1.0",
"langgraph_api.version": "0.2.0",
"langgraph.platform.revision": "abc123",
"langgraph.platform.variant": "standard",
"langgraph.platform.host": "host-1",
"langgraph.platform.tenant_id": "3a1c2b6f-4430-4b92-8a5b-79b8b567bbc1",
"langgraph.platform.project_id": "c5b5f53a-4716-4326-8967-d4f7f7799735",
"langgraph.platform.plan": "enterprise",
"user_app.uses_indexing": "true",
"user_app.uses_custom_app": "false",
"user_app.uses_custom_auth": "true",
"user_app.uses_thread_ttl": "true",
"user_app.uses_store_ttl": "false"
},
"measures": {
"langgraph.platform.runs": 150,
"langgraph.platform.nodes": 450
},
"logs": []
}
```
**Response:**
```json
"204 No Content"
```
## Our Commitment
LangChain will not store any sensitive information in the Subscription Metrics or Operational Metadata. Any data collected will not be shared with a third party. If you have any concerns about the data being sent, please reach out to your account team.
docs/docs/cloud/deployment/self_hosted_control_plane.md
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kubectl get storageclass
1. Egress to `https://beacon.langchain.com` from your network. This is required for license verification and usage reporting if not running in air-gapped mode. See the [Egress documentation](../../cloud/deployment/egress.md) for more details.
## Setup
1. As part of configuring your Self-Hosted LangSmith instance, you enable the `langgraphPlatform` option. This will provision a few key resources.
docs/docs/cloud/deployment/standalone_container.md
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1. `LANGSMITH_API_KEY`: (if using [Lite](../../concepts/langgraph_server.md#server-versions)) LangSmith API key. This will be used to authenticate ONCE at server start up.
1. `LANGGRAPH_CLOUD_LICENSE_KEY`: (if using [Enterprise](../../concepts/langgraph_data_plane.md#licensing)) LangGraph Platform license key. This will be used to authenticate ONCE at server start up.
1. `LANGSMITH_ENDPOINT`: To send traces to a [self-hosted LangSmith](https://docs.smith.langchain.com/self_hosting) instance, set `LANGSMITH_ENDPOINT` to the hostname of the self-hosted LangSmith instance.
1. Egress to `https://beacon.langchain.com` from your network. This is required for license verification and usage reporting if not running in air-gapped mode. See the [Egress documentation](../../cloud/deployment/egress.md) for more details.
## Kubernetes (Helm)
docs/docs/cloud/how-tos/generative_ui_react.md
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Next, define your UI components in your `langgraph.json` configuration:
```json
{
"node_version": "20",
"graphs": {
"agent": "./src/agent/index.ts:graph"
},
"ui": {
"agent": "./src/agent/ui.tsx"
}
}
```
=== "Python agent"
```json title="langgraph.json"
{
"node_version": "20",
"graphs": {
"agent": "./src/agent.py:graph"
},
"ui": {
"agent": "./src/agent/ui.tsx"
}
}
```
=== "JS agent"
```json title="langgraph.json"
{
"node_version": "20",
"graphs": {
"agent": "./src/agent/index.ts:graph"
},
"ui": {
"agent": "./src/agent/ui.tsx"
}
}
```
The `ui` section points to the UI components that will be used by graphs. By default, we recommend using the same key as the graph name, but you can split out the components however you like, see [Customise the namespace of UI components](#customise-the-namespace-of-ui-components) for more details.
docs/docs/cloud/how-tos/webhooks.md
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Your server should extract and validate this token before processing requests.
## Disable webhooks
As of `langgraph-api>=0.2.78`, developers can disable webhooks in the `langgraph.json` file:
```json
{
"http": {
"disable_webhooks": true
}
}
```
This feature is primarily intended for self-hosted deployments, where platform administrators or developers may prefer to disable webhooks to simplify their security posture—especially if they are not configuring firewall rules or other network controls. Disabling webhooks helps prevent untrusted payloads from being sent to internal endpoints.
For full configuration details, refer to the [configuration file reference](https://langchain-ai.github.io/langgraph/cloud/reference/cli/?h=disable_webhooks#configuration-file).
## Test webhooks
You can test your webhook using online services like:
docs/docs/cloud/reference/cli.md
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| Option | Default | Description |
| ---------------------------- | ------------------------- | ----------------------------------------------------------------------------------------------------------------------- |
| `--wait` | | Wait for services to start before returning. Implies --detach |
| `--base-image TEXT` | `langchain/langgraph-api` | Base image to use for the LangGraph API server. Pin to specific versions using version tags. |
| `--image TEXT` | | Docker image to use for the langgraph-api service. If specified, skips building and uses this image directly. |
| `--base-image TEXT` | `langchain/langgraph-api` | Base image to use for the LangGraph API server. Pin to specific versions using version tags. |
| `--image TEXT` | | Docker image to use for the langgraph-api service. If specified, skips building and uses this image directly. |
| `--postgres-uri TEXT` | Local database | Postgres URI to use for the database. |
| `--watch` | | Restart on file changes |
| `--debugger-base-url TEXT` | `http://127.0.0.1:[PORT]` | URL used by the debugger to access LangGraph API. |
@@ -438,8 +438,8 @@ The LangGraph CLI requires a JSON configuration file that follows this [schema](
| Option | Default | Description |
| ---------------------------------------------------------------------- | ------------------------- | ----------------------------------------------------------------------------------------------------------------------- |
| <span style="white-space: nowrap;">`--wait`</span> | | Wait for services to start before returning. Implies --detach |
| <span style="white-space: nowrap;">`--base-image TEXT`</span> | <span style="white-space: nowrap;">`langchain/langgraph-api`</span> | Base image to use for the LangGraph API server. Pin to specific versions using version tags. |
| <span style="white-space: nowrap;">`--image TEXT`</span> | | Docker image to use for the langgraph-api service. If specified, skips building and uses this image directly. |
| <span style="white-space: nowrap;">`--base-image TEXT`</span> | <span style="white-space: nowrap;">`langchain/langgraph-api`</span> | Base image to use for the LangGraph API server. Pin to specific versions using version tags. |
| <span style="white-space: nowrap;">`--image TEXT`</span> | | Docker image to use for the langgraph-api service. If specified, skips building and uses this image directly. |
| <span style="white-space: nowrap;">`--postgres-uri TEXT`</span> | Local database | Postgres URI to use for the database. |
| <span style="white-space: nowrap;">`--watch`</span> | | Restart on file changes |
| <span style="white-space: nowrap;">`-c, --config FILE`</span> | `langgraph.json` | Path to configuration file declaring dependencies, graphs and environment variables. |
docs/docs/cloud/reference/env_var.md
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If `DD_API_KEY` is specified, the application process is wrapped in the [`ddtrace-run` command](https://ddtrace.readthedocs.io/en/stable/installation_quickstart.html). Other `DD_*` environment variables (e.g. `DD_SITE`, `DD_ENV`, `DD_SERVICE`, `DD_TRACE_ENABLED`) are typically needed to properly configure the tracing instrumentation. See [`DD_*` environment variables](https://ddtrace.readthedocs.io/en/stable/configuration.html) for more details.
!!! note
Enabling `DD_API_KEY` (and thus `ddtrace-run`) can override or interfere with other auto-instrumentation solutions (such as OpenTelemetry) that you may have instrumented into your application code.
## `LANGCHAIN_TRACING_SAMPLING_RATE`
Sampling rate for traces sent to LangSmith. Valid values: Any float between `0` and `1`.
docs/docs/cloud/reference/langgraph_server_changelog.md
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---
## v0.2.96 (2025-07-17)
- Added a fallback mechanism for configurable header patterns to handle exclude/include settings more effectively.
## v0.2.95 (2025-07-17)
- Avoided setting the future if it is already done to prevent redundant operations.
- Resolved compatibility errors in CI by switching from `typing.TypedDict` to `typing_extensions.TypedDict` for Python versions below 3.12.
## v0.2.94 (2025-07-16)
- Improved performance by omitting pending sends for langgraph versions 0.5 and above.
- Improved server startup logs to provide clearer warnings when the DD_API_KEY environment variable is set.
## v0.2.93 (2025-07-16)
- Removed the GIN index for run metadata to improve performance.
docs/docs/concepts/deployment_options.md
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There are two free options for deploying LangGraph applications via the LangGraph Server:
1. [Local](../tutorials/langgraph-platform/local-server.md): Deploy for local testing and development.
1. [Standalone Container (Lite)](../concepts/langgraph_standalone_container.md): A limited version of Standalone Container for deployments unlikely to see more that 1 million node executions per year and that do not need crons and other enterprise features. Standalone Container (Lite) deployment option is free with a LangSmith API key.
1. [Standalone Container (Lite)](../concepts/langgraph_standalone_container.md): A limited version of Standalone Container for deployments unlikely to see more than 1 million node executions per year and that do not need crons and other enterprise features. Standalone Container (Lite) deployment option is free with a LangSmith API key.
## Production deployment
docs/docs/concepts/low_level.md
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### Schema
The main documented way to specify the schema of a graph is by using `TypedDict`. However, we also support [using a Pydantic BaseModel](../how-tos/graph-api.md#use-pydantic-models-for-graph-state) as your graph state to add **default values** and additional data validation.
The main documented way to specify the schema of a graph is by using a [`TypedDict`](https://docs.python.org/3/library/typing.html#typing.TypedDict). If you want to provide default values in your state, use a [`dataclass`](https://docs.python.org/3/library/dataclasses.html). We also support using a Pydantic [BaseModel](../how-tos/graph-api.md#use-pydantic-models-for-graph-state) as your graph state if you want recursive data validation (though note that pydantic is less performant than a `TypedDict` or `dataclass`).
By default, the graph will have the same input and output schemas. If you want to change this, you can also specify explicit input and output schemas directly. This is useful when you have a lot of keys, and some are explicitly for input and others for output. See the [guide here](../how-tos/graph-api.md#define-input-and-output-schemas) for how to use.
docs/docs/concepts/tracing.md
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# Tracing
Traces are a series of steps that your application takes to go from input to output. Each of these individual steps is represented by a run. You can use [LangSmith](https://smith.langchain.com/) to visualize these execution steps. To use it, [enable tracing for your application](../how-tos/enable-tracing.md). This enables you to do the following:
- [Debug a locally running application](../cloud/how-tos/clone_traces_studio.md).
- [Evaluate the application performance](../agents/evals.md).
- [Monitor the application](https://docs.smith.langchain.com/observability/how_to_guides/dashboards).
To get started, sign up for a free account at [LangSmith](https://smith.langchain.com/).
## Learn more
- [Graph runs in LangSmith](../how-tos/run-id-langsmith.md)
- [LangSmith Observability quickstart](https://docs.smith.langchain.com/observability)
- [Trace with LangGraph](https://docs.smith.langchain.com/observability/how_to_guides/trace_with_langgraph)
- [Tracing conceptual guide](https://docs.smith.langchain.com/observability/concepts#traces)
docs/docs/guides/index.md
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The pages in this section provide a conceptual overview and how-tos for the following topics:
## Agent development
- [Overview](../agents/overview.md): Use prebuilt components to build an agent.
- [Run an agent](../agents/run_agents.md): Run an agent by providing input, interpreting output, enabling streaming, and controlling execution limits.
## LangGraph APIs
- [Graph API](../concepts/low_level.md): Use the Graph API to define workflows using a graph paradigm.
docs/docs/how-tos/autogen-integration.md
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```
langgraph>=0.1.0
pyautogen>=0.2.0
ag2>=0.2.0
langchain-core>=0.1.0
langchain-openai>=0.0.5
```
docs/docs/how-tos/enable-tracing.md
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# Enable tracing for your application
To enable [tracing](../concepts/tracing.md) for your application, set the following environment variables:
```python
export LANGSMITH_TRACING=true
export LANGSMITH_API_KEY=<your-api-key>
```
For more information, see [Trace with LangGraph](https://docs.smith.langchain.com/observability/how_to_guides/trace_with_langgraph).
## Learn more
- [Graph runs in LangSmith](../how-tos/run-id-langsmith.md)
- [LangSmith Observability quickstart](https://docs.smith.langchain.com/observability)
- [Tracing conceptual guide](https://docs.smith.langchain.com/observability/concepts#traces)
docs/docs/how-tos/graph-api.md
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A [StateGraph](https://langchain-ai.github.io/langgraph/reference/graphs.md#langgraph.graph.StateGraph) accepts a `state_schema` argument on initialization that specifies the "shape" of the state that the nodes in the graph can access and update.
In our examples, we typically use a python-native `TypedDict` for `state_schema`, but `state_schema` can be any [type](https://docs.python.org/3/library/stdtypes.html#type-objects).
In our examples, we typically use a python-native `TypedDict` or [`dataclass`](https://docs.python.org/3/library/dataclasses.html) for `state_schema`, but `state_schema` can be any [type](https://docs.python.org/3/library/stdtypes.html#type-objects).
Here, we'll see how a [Pydantic BaseModel](https://docs.pydantic.dev/latest/api/base_model/). can be used for `state_schema` to add run time validation on **inputs**.
Here, we'll see how a [Pydantic BaseModel](https://docs.pydantic.dev/latest/api/base_model/) can be used for `state_schema` to add run-time validation on **inputs**.
!!! note "Known Limitations"
- Currently, the output of the graph will **NOT** be an instance of a pydantic model.
- Run-time validation only occurs on inputs into nodes, not on the outputs.
- The validation error trace from pydantic does not show which node the error arises in.
- Pydantic's recursive validation can be slow. For performance-sensitive applications, you may want to consider using a `dataclass` instead.
```python
from langgraph.graph import StateGraph, START, END
@@ -1151,12 +1152,13 @@ LangGraph supports map-reduce and other advanced branching patterns using the Se
```python
from langgraph.graph import StateGraph, START, END
from langgraph.types import Send
from typing_extensions import TypedDict
from typing_extensions import TypedDict, Annotated
import operator
class OverallState(TypedDict):
topic: str
subjects: list[str]
jokes: list[str]
jokes: Annotated[list[str], operator.add]
best_selected_joke: str
def generate_topics(state: OverallState):
@@ -1565,9 +1567,9 @@ class State(TypedDict):
def node_a(state: State) -> Command[Literal["node_b", "node_c"]]:
print("Called A")
value = random.choice(["a", "b"])
value = random.choice(["b", "c"])
# this is a replacement for a conditional edge function
if value == "a":
if value == "b":
goto = "node_b"
else:
goto = "node_c"
docs/docs/how-tos/observability.md
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# Observability
Use [LangSmith](https://smith.langchain.com/) to visualize the execution of a LangGraph application and do the following:
- [Enable tracing for your application](#enable-tracing-for-your-application).
- [Debug a locally running application](../cloud/how-tos/clone_traces_studio.md).
- [Evaluate the application performance](../agents/evals.md).
- [Monitor the application](https://docs.smith.langchain.com/observability/how_to_guides/dashboards).
To get started, sign up for a free account at [LangSmith](https://smith.langchain.com/).
## Enable tracing for your application
To use LangSmith with your LangGraph application, enable tracing:
```python
export LANGSMITH_TRACING=true
export LANGSMITH_API_KEY=<your-api-key>
```
For more information, see [Trace with LangGraph](https://docs.smith.langchain.com/observability/how_to_guides/trace_with_langgraph).