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Change LG Cloud > Platform
This commit is contained in:
Lauren Hirata Singh
@@ -89,4 +89,4 @@ LangGraph Studio Web is a specialized UI that you can connect to LangGraph API s
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## Deployment
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Once your LangGraph app is running locally, you can deploy it using LangGraph Cloud or self-hosted options. Refer to the [deployment options guide](../tutorials/deployment.md) for detailed instructions on all supported deployment models.
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Once your LangGraph app is running locally, you can deploy it using LangGraph Platform. Refer to the [deployment options guide](../tutorials/deployment.md) for detailed instructions on all supported deployment models.
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@@ -13,7 +13,7 @@ You can use a prebuilt chat UI for interacting with any LangGraph agent through
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## Run agent in UI
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First, set up LangGraph API server [locally](./deployment.md#launch-langgraph-server-locally) or deploy your agent on [LangGraph Cloud](https://langchain-ai.github.io/langgraph/cloud/quick_start/).
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First, set up LangGraph API server [locally](./deployment.md#launch-langgraph-server-locally) or deploy your agent on [LangGraph Platform](https://langchain-ai.github.io/langgraph/cloud/quick_start/).
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Then, navigate to [Agent Chat UI](https://agentchat.vercel.app), or clone the repository and [run the dev server locally](https://github.com/langchain-ai/agent-chat-ui?tab=readme-ov-file#setup):
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@@ -5,11 +5,11 @@ There are many situations in which it is useful to run an assistant on a schedul
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For example, say that you're building an assistant that runs daily and sends an email summary
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of the day's news. You could use a cron job to run the assistant every day at 8:00 PM.
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LangGraph Cloud supports cron jobs, which run on a user-defined schedule. The user specifies a schedule, an assistant, and some input. After that, on the specified schedule, the server will:
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LangGraph Platform supports cron jobs, which run on a user-defined schedule. The user specifies a schedule, an assistant, and some input. After that, on the specified schedule, the server will:
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- Create a new thread with the specified assistant
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- Send the specified input to that thread
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Note that this sends the same input to the thread every time. See the [how-to guide](../../cloud/how-tos/cron_jobs.md) for creating cron jobs.
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The LangGraph Cloud API provides several endpoints for creating and managing cron jobs. See the [API reference](../../cloud/reference/api/api_ref.html#tag/runscreate/POST/threads/{thread_id}/runs/crons) for more details.
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The LangGraph Platform API provides several endpoints for creating and managing cron jobs. See the [API reference](../../cloud/reference/api/api_ref.html#tag/runscreate/POST/threads/{thread_id}/runs/crons) for more details.
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@@ -2,4 +2,4 @@
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A run is an invocation of an [assistant](../../concepts/assistants.md). Each run may have its own input, configuration, and metadata, which may affect execution and output of the underlying graph. A run can optionally be executed on a [thread](./threads.md).
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The LangGraph Cloud API provides several endpoints for creating and managing runs. See the [API reference](../../cloud/reference/api/api_ref.html#tag/thread-runs/) for more details.
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The LangGraph Platform API provides several endpoints for creating and managing runs. See the [API reference](../../cloud/reference/api/api_ref.html#tag/thread-runs/) for more details.
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@@ -8,4 +8,4 @@ The state of a thread at a particular point in time is called a [checkpoint](../
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For more on threads and checkpoints, see this section of the [LangGraph conceptual guide](../../concepts/persistence.md).
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The LangGraph Cloud API provides several endpoints for creating and managing threads and thread state. See the [API reference](../../cloud/reference/api/api_ref.html#tag/threads) for more details.
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The LangGraph Platform API provides several endpoints for creating and managing threads and thread state. See the [API reference](../../cloud/reference/api/api_ref.html#tag/threads) for more details.
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@@ -1,7 +1,7 @@
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# Webhooks
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Webhooks enable event-driven communication from your LangGraph Cloud application to external services. For example, you may want to issue an update to a separate service once an API call to LangGraph Cloud has finished running.
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Webhooks enable event-driven communication from your LangGraph Platform application to external services. For example, you may want to issue an update to a separate service once an API call to LangGraph Platform has finished running.
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Many LangGraph Cloud endpoints accept a `webhook` parameter. If this parameter is specified by a an endpoint that can accept POST requests, LangGraph Cloud will send a request at the completion of a run.
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Many LangGraph Platform endpoints accept a `webhook` parameter. If this parameter is specified by a an endpoint that can accept POST requests, LangGraph Platform will send a request at the completion of a run.
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See the corresponding [how-to guide](../../cloud/how-tos/webhooks.md) for more detail.
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@@ -4,14 +4,14 @@ Before deploying, review the [conceptual guide for the Cloud SaaS](../../concept
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## Prerequisites
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1. LangGraph Cloud applications are deployed from GitHub repositories. Configure and upload a LangGraph Cloud application to a GitHub repository in order to deploy it to LangGraph Cloud.
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1. [Verify that the LangGraph API runs locally](../../tutorials/langgraph-platform/local-server.md). If the API does not run successfully (i.e. `langgraph dev`), deploying to LangGraph Cloud will fail as well.
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1. LangGraph Platform applications are deployed from GitHub repositories. Configure and upload a LangGraph Platform application to a GitHub repository in order to deploy it to LangGraph Platform.
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1. [Verify that the LangGraph API runs locally](../../tutorials/langgraph-platform/local-server.md). If the API does not run successfully (i.e. `langgraph dev`), deploying to LangGraph Platform will fail as well.
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## Create New Deployment
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Starting from the <a href="https://smith.langchain.com/" target="_blank">LangSmith UI</a>...
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1. In the left-hand navigation panel, select `LangGraph Platform`. The `LangGraph Platform` view contains a list of existing LangGraph Cloud deployments.
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1. In the left-hand navigation panel, select `LangGraph Platform`. The `LangGraph Platform` view contains a list of existing LangGraph Platform deployments.
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1. In the top-right corner, select `+ New Deployment` to create a new deployment.
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1. In the `Create New Deployment` panel, fill out the required fields.
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1. `Deployment details`
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@@ -38,7 +38,7 @@ When [creating a new deployment](#create-new-deployment), a new revision is crea
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Starting from the <a href="https://smith.langchain.com/" target="_blank">LangSmith UI</a>...
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1. In the left-hand navigation panel, select `LangGraph Platform`. The `LangGraph Platform` view contains a list of existing LangGraph Cloud deployments.
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1. In the left-hand navigation panel, select `LangGraph Platform`. The `LangGraph Platform` view contains a list of existing LangGraph Platform deployments.
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1. Select an existing deployment to create a new revision for.
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1. In the `Deployment` view, in the top-right corner, select `+ New Revision`.
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1. In the `New Revision` modal, fill out the required fields.
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@@ -79,7 +79,7 @@ Starting from the `LangGraph Platform` view...
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Starting from the <a href="https://smith.langchain.com/" target="_blank">LangSmith UI</a>...
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1. In the left-hand navigation panel, select `LangGraph Platform`. The `LangGraph Platform` view contains a list of existing LangGraph Cloud deployments.
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1. In the left-hand navigation panel, select `LangGraph Platform`. The `LangGraph Platform` view contains a list of existing LangGraph Platform deployments.
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1. Select the menu icon (three dots) on the right-hand side of the row for the desired deployment and select `Delete`.
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1. A `Confirmation` modal will appear. Select `Delete`.
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@@ -1,11 +1,11 @@
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# How to Set Up a LangGraph Application with requirements.txt
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A LangGraph application must be configured with a [LangGraph configuration file](../reference/cli.md#configuration-file) in order to be deployed to LangGraph Cloud (or to be self-hosted). This how-to guide discusses the basic steps to setup a LangGraph application for deployment using `requirements.txt` to specify project dependencies.
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A LangGraph application must be configured with a [LangGraph configuration file](../reference/cli.md#configuration-file) in order to be deployed to LangGraph Platform (or to be self-hosted). This how-to guide discusses the basic steps to setup a LangGraph application for deployment using `requirements.txt` to specify project dependencies.
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This walkthrough is based on [this repository](https://github.com/langchain-ai/langgraph-example), which you can play around with to learn more about how to setup your LangGraph application for deployment.
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!!! tip "Setup with pyproject.toml"
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If you prefer using poetry for dependency management, check out [this how-to guide](./setup_pyproject.md) on using `pyproject.toml` for LangGraph Cloud.
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If you prefer using poetry for dependency management, check out [this how-to guide](./setup_pyproject.md) on using `pyproject.toml` for LangGraph Platform.
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!!! tip "Setup with a Monorepo"
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If you are interested in deploying a graph located inside a monorepo, take a look at [this repository](https://github.com/langchain-ai/langgraph-example-monorepo) for an example of how to do so.
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@@ -130,7 +130,7 @@ graph = workflow.compile()
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```
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!!! warning "Assign `CompiledGraph` to Variable"
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The build process for LangGraph Cloud requires that the `CompiledGraph` object be assigned to a variable at the top-level of a Python module (alternatively, you can provide [a function that creates a graph](./graph_rebuild.md)).
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The build process for LangGraph Platform requires that the `CompiledGraph` object be assigned to a variable at the top-level of a Python module (alternatively, you can provide [a function that creates a graph](./graph_rebuild.md)).
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Example file directory:
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@@ -1,6 +1,6 @@
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# How to Set Up a LangGraph.js Application
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A [LangGraph.js](https://langchain-ai.github.io/langgraphjs/) application must be configured with a [LangGraph configuration file](../reference/cli.md#configuration-file) in order to be deployed to LangGraph Cloud (or to be self-hosted). This how-to guide discusses the basic steps to setup a LangGraph.js application for deployment using `package.json` to specify project dependencies.
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A [LangGraph.js](https://langchain-ai.github.io/langgraphjs/) application must be configured with a [LangGraph configuration file](../reference/cli.md#configuration-file) in order to be deployed to LangGraph Platform (or to be self-hosted). This how-to guide discusses the basic steps to setup a LangGraph.js application for deployment using `package.json` to specify project dependencies.
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This walkthrough is based on [this repository](https://github.com/langchain-ai/langgraphjs-studio-starter), which you can play around with to learn more about how to setup your LangGraph application for deployment.
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@@ -157,7 +157,7 @@ export const graph = workflow.compile();
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!!! info "Assign `CompiledGraph` to Variable"
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The build process for LangGraph Cloud requires that the `CompiledGraph` object be assigned to a variable at the top-level of a JavaScript module (alternatively, you can provide [a function that creates a graph](./graph_rebuild.md)).
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The build process for LangGraph Platform requires that the `CompiledGraph` object be assigned to a variable at the top-level of a JavaScript module (alternatively, you can provide [a function that creates a graph](./graph_rebuild.md)).
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Example file directory:
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@@ -1,6 +1,6 @@
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# How to Set Up a LangGraph Application with pyproject.toml
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A LangGraph application must be configured with a [LangGraph configuration file](../reference/cli.md#configuration-file) in order to be deployed to LangGraph Cloud (or to be self-hosted). This how-to guide discusses the basic steps to setup a LangGraph application for deployment using `pyproject.toml` to define your package's dependencies.
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A LangGraph application must be configured with a [LangGraph configuration file](../reference/cli.md#configuration-file) in order to be deployed to LangGraph Platform (or to be self-hosted). This how-to guide discusses the basic steps to setup a LangGraph application for deployment using `pyproject.toml` to define your package's dependencies.
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This walkthrough is based on [this repository](https://github.com/langchain-ai/langgraph-example-pyproject), which you can play around with to learn more about how to setup your LangGraph application for deployment.
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@@ -59,7 +59,7 @@ Example `pyproject.toml` file:
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[tool.poetry]
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name = "my-agent"
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version = "0.0.1"
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description = "An excellent agent build for LangGraph cloud."
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description = "An excellent agent build for LangGraph Platform."
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authors = ["Polly the parrot <1223+polly@users.noreply.github.com>"]
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license = "MIT"
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readme = "README.md"
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@@ -138,7 +138,7 @@ graph = workflow.compile()
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```
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!!! warning "Assign `CompiledGraph` to Variable"
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The build process for LangGraph Cloud requires that the `CompiledGraph` object be assigned to a variable at the top-level of a Python module.
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The build process for LangGraph Platform requires that the `CompiledGraph` object be assigned to a variable at the top-level of a Python module.
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Example file directory:
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@@ -1,6 +1,6 @@
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# Cron Jobs
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Sometimes you don't want to run your graph based on user interaction, but rather you would like to schedule your graph to run on a schedule - for example if you wish for your graph to compose and send out a weekly email of to-dos for your team. LangGraph Cloud allows you to do this without having to write your own script by using the `Crons` client. To schedule a graph job, you need to pass a [cron expression](https://crontab.cronhub.io/) to inform the client when you want to run the graph. `Cron` jobs are run in the background and do not interfere with normal invocations of the graph.
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Sometimes you don't want to run your graph based on user interaction, but rather you would like to schedule your graph to run on a schedule - for example if you wish for your graph to compose and send out a weekly email of to-dos for your team. LangGraph Platform allows you to do this without having to write your own script by using the `Crons` client. To schedule a graph job, you need to pass a [cron expression](https://crontab.cronhub.io/) to inform the client when you want to run the graph. `Cron` jobs are run in the background and do not interfere with normal invocations of the graph.
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## Setup
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@@ -1,10 +1,10 @@
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# How to Replay and Branch from Prior States
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With LangGraph Cloud you have the ability to return to any of your prior states and either re-run the graph to reproduce issues noticed during testing, or branch out in a different way from what was originally done in the prior states. In this guide we will show a quick example of how to rerun past states and how to branch off from previous states as well.
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With LangGraph Platform you have the ability to return to any of your prior states and either re-run the graph to reproduce issues noticed during testing, or branch out in a different way from what was originally done in the prior states. In this guide we will show a quick example of how to rerun past states and how to branch off from previous states as well.
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## Setup
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The examples below are executed against a specific deployment on LangGraph Cloud. You will use
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The examples below are executed against a specific deployment on LangGraph Platform. You will use
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the SDK in a similar way, but you will expect to see different results based on the graph you have deployed.
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### SDK initialization
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@@ -1,6 +1,6 @@
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# How to run multiple agents on the same thread
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In LangGraph Cloud, a thread is not explicitly associated with a particular agent.
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In LangGraph Platform, a thread is not explicitly associated with a particular agent.
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This means that you can run multiple agents on the same thread, which allows a different agent to continue from an initial agent's progress.
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In this example, we will create two agents and then call them both on the same thread.
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@@ -1,6 +1,6 @@
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# Stateless Runs
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Most of the time, you provide a `thread_id` to your client when you run your graph in order to keep track of prior runs through the persistent state implemented in LangGraph Cloud. However, if you don't need to persist the runs you don't need to use the built in persistent state and can create stateless runs.
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Most of the time, you provide a `thread_id` to your client when you run your graph in order to keep track of prior runs through the persistent state implemented in LangGraph Platform. However, if you don't need to persist the runs you don't need to use the built in persistent state and can create stateless runs.
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## Setup
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@@ -1,6 +1,6 @@
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# Using Webhooks
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When working with LangGraph Cloud, you may want to use webhooks to receive updates after an API call completes. Webhooks are useful for triggering actions in your service once a run has finished processing. To implement this, you need to expose an endpoint that can accept `POST` requests and pass this endpoint as a `webhook` parameter in your API request.
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When working with LangGraph Platform, you may want to use webhooks to receive updates after an API call completes. Webhooks are useful for triggering actions in your service once a run has finished processing. To implement this, you need to expose an endpoint that can accept `POST` requests and pass this endpoint as a `webhook` parameter in your API request.
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Currently, the SDK does not provide built-in support for defining webhook endpoints, but you can specify them manually using API requests.
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@@ -71,7 +71,7 @@ curl --request POST \
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## Using a Webhook with a Graph Run
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To use a webhook, specify the `webhook` parameter in your API request. When the run completes, LangGraph Cloud sends a `POST` request to the specified webhook URL.
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To use a webhook, specify the `webhook` parameter in your API request. When the run completes, LangGraph Platform sends a `POST` request to the specified webhook URL.
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For example, if your server listens for webhook events at `https://my-server.app/my-webhook-endpoint`, include this in your request:
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@@ -121,7 +121,7 @@ curl --request POST \
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## Webhook Payload
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LangGraph Cloud sends webhook notifications in the format of a [Run](../../cloud/concepts/runs.md). See the [API Reference](https://langchain-ai.github.io/langgraph/cloud/reference/api/api_ref.html#model/run) for details. The request payload includes run input, configuration, and other metadata in the `kwargs` field.
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LangGraph Platform sends webhook notifications in the format of a [Run](../../cloud/concepts/runs.md). See the [API Reference](https://langchain-ai.github.io/langgraph/cloud/reference/api/api_ref.html#model/run) for details. The request payload includes run input, configuration, and other metadata in the `kwargs` field.
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## Securing Webhooks
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@@ -140,8 +140,8 @@ You can test your webhook using online services like:
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- **[Beeceptor](https://beeceptor.com/)** – Quickly create a test endpoint and inspect incoming webhook payloads.
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- **[Webhook.site](https://webhook.site/)** – View, debug, and log incoming webhook requests in real time.
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These tools help you verify that LangGraph Cloud is correctly triggering and sending webhooks to your service.
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These tools help you verify that LangGraph Platform is correctly triggering and sending webhooks to your service.
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---
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By following these steps, you can integrate webhooks into your LangGraph Cloud workflow, automating actions based on completed runs.
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By following these steps, you can integrate webhooks into your LangGraph Platform workflow, automating actions based on completed runs.
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@@ -16,7 +16,7 @@ This quickstart uses the [pre-built Python ReAct agent template](https://github.
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## 1. Create a repository on GitHub
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||||
To deploy a LangGraph application to **LangGraph Cloud**, your application code must reside in a GitHub repository. Both public and private repositories are supported. For this quickstart, use the [pre-built Python ReAct agent template](https://github.com/langchain-ai/react-agent) for your application:
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To deploy a LangGraph application to **LangGraph Platform**, your application code must reside in a GitHub repository. Both public and private repositories are supported. For this quickstart, use the [pre-built Python ReAct agent template](https://github.com/langchain-ai/react-agent) for your application:
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||||
|
||||
1. Go to the [ReAct Agent](https://github.com/langchain-ai/react-agent) repository.
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1. Click the `Fork` button in the top right corner to fork the repository to your GitHub account.
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@@ -1,7 +1,7 @@
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<!doctype html>
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<html>
|
||||
<head>
|
||||
<title>LangGraph Cloud API Reference</title>
|
||||
<title>LangGraph Platform API Reference</title>
|
||||
<meta charset="utf-8" />
|
||||
<meta
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||||
name="viewport"
|
||||
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||||
@@ -1,12 +1,12 @@
|
||||
# API Reference
|
||||
|
||||
The LangGraph Cloud API reference is available with each deployment at the `/docs` URL path (e.g. `http://localhost:8124/docs`).
|
||||
The LangGraph Platform API reference is available with each deployment at the `/docs` URL path (e.g. `http://localhost:8124/docs`).
|
||||
|
||||
Click <a href="/langgraph/cloud/reference/api/api_ref.html" target="_blank">here</a> to view the API reference.
|
||||
|
||||
## Authentication
|
||||
|
||||
For deployments to LangGraph Cloud, authentication is required. Pass the `X-Api-Key` header with each request to the LangGraph Cloud API. The value of the header should be set to a valid LangSmith API key for the organization where the API is deployed.
|
||||
For deployments to LangGraph Platform, authentication is required. Pass the `X-Api-Key` header with each request to the LangGraph Platform API. The value of the header should be set to a valid LangSmith API key for the organization where the API is deployed.
|
||||
|
||||
Example `curl` command:
|
||||
```shell
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||||
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||||
@@ -1,7 +1,7 @@
|
||||
<!doctype html>
|
||||
<html>
|
||||
<head>
|
||||
<title>LangGraph Cloud API Reference</title>
|
||||
<title>LangGraph Platform API Reference</title>
|
||||
<meta charset="utf-8" />
|
||||
<meta
|
||||
name="viewport"
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
# LangGraph CLI
|
||||
|
||||
The LangGraph command line interface includes commands to build and run a LangGraph Cloud API server locally in [Docker](https://www.docker.com/). For development and testing, you can use the CLI to deploy a local API server.
|
||||
The LangGraph command line interface includes commands to build and run a LangGraph Platform API server locally in [Docker](https://www.docker.com/). For development and testing, you can use the CLI to deploy a local API server.
|
||||
|
||||
## Installation
|
||||
|
||||
@@ -39,7 +39,7 @@ The LangGraph CLI requires a JSON configuration file that follows this [schema](
|
||||
|
||||
| Key | Description |
|
||||
| ------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
|
||||
| <span style="white-space: nowrap;">`dependencies`</span> | **Required**. Array of dependencies for LangGraph Cloud API server. Dependencies can be one of the following: <ul><li>A single period (`"."`), which will look for local Python packages.</li><li>The directory path where `pyproject.toml`, `setup.py` or `requirements.txt` is located.</br></br>For example, if `requirements.txt` is located in the root of the project directory, specify `"./"`. If it's located in a subdirectory called `local_package`, specify `"./local_package"`. Do not specify the string `"requirements.txt"` itself.</li><li>A Python package name.</li></ul> |
|
||||
| <span style="white-space: nowrap;">`dependencies`</span> | **Required**. Array of dependencies for LangGraph Platform API server. Dependencies can be one of the following: <ul><li>A single period (`"."`), which will look for local Python packages.</li><li>The directory path where `pyproject.toml`, `setup.py` or `requirements.txt` is located.</br></br>For example, if `requirements.txt` is located in the root of the project directory, specify `"./"`. If it's located in a subdirectory called `local_package`, specify `"./local_package"`. Do not specify the string `"requirements.txt"` itself.</li><li>A Python package name.</li></ul> |
|
||||
| <span style="white-space: nowrap;">`graphs`</span> | **Required**. Mapping from graph ID to path where the compiled graph or a function that makes a graph is defined. Example: <ul><li>`./your_package/your_file.py:variable`, where `variable` is an instance of `langgraph.graph.state.CompiledStateGraph`</li><li>`./your_package/your_file.py:make_graph`, where `make_graph` is a function that takes a config dictionary (`langchain_core.runnables.RunnableConfig`) and creates an instance of `langgraph.graph.state.StateGraph` / `langgraph.graph.state.CompiledStateGraph`.</li></ul> |
|
||||
| <span style="white-space: nowrap;">`auth`</span> | _(Added in v0.0.11)_ Auth configuration containing the path to your authentication handler. Example: `./your_package/auth.py:auth`, where `auth` is an instance of `langgraph_sdk.Auth`. See [authentication guide](../../concepts/auth.md) for details. |
|
||||
| <span style="white-space: nowrap;">`base_image`</span> | Optional. Base image to use for the LangGraph API server. Defaults to `langchain/langgraph-api` or `langchain/langgraphjs-api`. Use this to pin your builds to a particular version of the langgraph API, such as `"langchain/langgraph-server:0.2"`. See https://hub.docker.com/r/langchain/langgraph-server/tags for more details. (added in `langgraph-cli==0.2.8`) |
|
||||
@@ -336,7 +336,7 @@ The LangGraph CLI requires a JSON configuration file that follows this [schema](
|
||||
|
||||
=== "Python"
|
||||
|
||||
Build LangGraph Cloud API server Docker image.
|
||||
Build LangGraph Platform API server Docker image.
|
||||
|
||||
**Usage**
|
||||
|
||||
@@ -350,13 +350,13 @@ The LangGraph CLI requires a JSON configuration file that follows this [schema](
|
||||
| -------------------- | ---------------- | ---------------------------------------------------------------------------------------------------------------------------- |
|
||||
| `--platform TEXT` | | Target platform(s) to build the Docker image for. Example: `langgraph build --platform linux/amd64,linux/arm64` |
|
||||
| `-t, --tag TEXT` | | **Required**. Tag for the Docker image. Example: `langgraph build -t my-image` |
|
||||
| `--pull / --no-pull` | `--pull` | Build with latest remote Docker image. Use `--no-pull` for running the LangGraph Cloud API server with locally built images. |
|
||||
| `--pull / --no-pull` | `--pull` | Build with latest remote Docker image. Use `--no-pull` for running the LangGraph Platform API server with locally built images. |
|
||||
| `-c, --config FILE` | `langgraph.json` | Path to configuration file declaring dependencies, graphs and environment variables. |
|
||||
| `--help` | | Display command documentation. |
|
||||
|
||||
=== "JS"
|
||||
|
||||
Build LangGraph Cloud API server Docker image.
|
||||
Build LangGraph Platform API server Docker image.
|
||||
|
||||
**Usage**
|
||||
|
||||
@@ -379,7 +379,7 @@ The LangGraph CLI requires a JSON configuration file that follows this [schema](
|
||||
|
||||
=== "Python"
|
||||
|
||||
Start LangGraph API server. For local testing, requires a LangSmith API key with access to LangGraph Cloud closed beta. Requires a license key for production use.
|
||||
Start LangGraph API server. For local testing, requires a LangSmith API key with access to LangGraph Platform closed beta. Requires a license key for production use.
|
||||
|
||||
**Usage**
|
||||
|
||||
@@ -406,7 +406,7 @@ The LangGraph CLI requires a JSON configuration file that follows this [schema](
|
||||
|
||||
=== "JS"
|
||||
|
||||
Start LangGraph API server. For local testing, requires a LangSmith API key with access to LangGraph Cloud closed beta. Requires a license key for production use.
|
||||
Start LangGraph API server. For local testing, requires a LangSmith API key with access to LangGraph Platform closed beta. Requires a license key for production use.
|
||||
|
||||
**Usage**
|
||||
|
||||
@@ -432,7 +432,7 @@ The LangGraph CLI requires a JSON configuration file that follows this [schema](
|
||||
|
||||
=== "Python"
|
||||
|
||||
Generate a Dockerfile for building a LangGraph Cloud API server Docker image.
|
||||
Generate a Dockerfile for building a LangGraph Platform API server Docker image.
|
||||
|
||||
**Usage**
|
||||
|
||||
@@ -482,7 +482,7 @@ The LangGraph CLI requires a JSON configuration file that follows this [schema](
|
||||
|
||||
=== "JS"
|
||||
|
||||
Generate a Dockerfile for building a LangGraph Cloud API server Docker image.
|
||||
Generate a Dockerfile for building a LangGraph Platform API server Docker image.
|
||||
|
||||
**Usage**
|
||||
|
||||
|
||||
@@ -38,7 +38,7 @@ See <a href="https://docs.smith.langchain.com/how_to_guides/tracing/sample_trace
|
||||
|
||||
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`.
|
||||
For deployments to LangGraph Platform, 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`.
|
||||
|
||||
## `LANGSMITH_RUNS_ENDPOINTS`
|
||||
|
||||
@@ -118,7 +118,7 @@ Defaults to `''`.
|
||||
## `REDIS_CLUSTER`
|
||||
|
||||
!!! info "Only Allowed in Self-Hosted Deployments"
|
||||
Redis Cluster mode is only available in Self-Hosted Deployment models, LangGraph Cloud SaaS will provision a redis instance for you by default.
|
||||
Redis Cluster mode is only available in Self-Hosted Deployment models, LangGraph Platform SaaS will provision a redis instance for you by default.
|
||||
|
||||
Set `REDIS_CLUSTER` to `True` to enable Redis Cluster mode. When enabled, the system will connect to Redis using cluster mode. This is useful when connecting to a Redis Cluster deployment.
|
||||
|
||||
|
||||
@@ -22,14 +22,14 @@ In LangGraph Platform, authentication is handled by your [`@auth.authenticate`](
|
||||
|
||||
LangGraph Platform provides different security defaults:
|
||||
|
||||
### LangGraph Cloud
|
||||
### LangGraph Platform
|
||||
|
||||
- Uses LangSmith API keys by default
|
||||
- Requires valid API key in `x-api-key` header
|
||||
- Can be customized with your auth handler
|
||||
|
||||
!!! note "Custom auth"
|
||||
Custom auth **is supported** for all plans in LangGraph Cloud.
|
||||
Custom auth **is supported** for all plans in LangGraph Platform.
|
||||
|
||||
### Self-Hosted
|
||||
|
||||
|
||||
@@ -534,11 +534,11 @@
|
||||
"locked": false,
|
||||
"fontSize": 28,
|
||||
"fontFamily": 1,
|
||||
"text": "LangGraph Cloud Deployment",
|
||||
"text": "LangGraph Platform Deployment",
|
||||
"textAlign": "center",
|
||||
"verticalAlign": "top",
|
||||
"containerId": null,
|
||||
"originalText": "LangGraph Cloud Deployment",
|
||||
"originalText": "LangGraph Platform Deployment",
|
||||
"autoResize": true,
|
||||
"lineHeight": 1.25
|
||||
},
|
||||
|
||||
@@ -58,11 +58,11 @@ LangGraph Server leverages a database for [persistence](persistence.md) and a ta
|
||||
|
||||
Currently, only [Postgres](https://www.postgresql.org/) is supported as a database for LangGraph Server and [Redis](https://redis.io/) as the task queue.
|
||||
|
||||
If you're deploying using [LangGraph Cloud](./langgraph_cloud.md), these components are managed for you. If you're deploying LangGraph Server on your own infrastructure, you'll need to set up and manage these components yourself.
|
||||
If you're deploying using [LangGraph Platform](./langgraph_cloud.md), these components are managed for you. If you're deploying LangGraph Server on your own infrastructure, you'll need to set up and manage these components yourself.
|
||||
|
||||
Please review the [deployment options](./deployment_options.md) guide for more information on how these components are set up and managed.
|
||||
|
||||
## Learn more
|
||||
|
||||
* LangGraph [Application Structure](./application_structure.md) guide explains how to structure your LangGraph application for deployment.
|
||||
* The [LangGraph Cloud API Reference](../cloud/reference/api/api_ref.html) provides detailed information on the API endpoints and data models.
|
||||
* The [LangGraph Platform API Reference](../cloud/reference/api/api_ref.html) provides detailed information on the API endpoints and data models.
|
||||
|
||||
@@ -428,7 +428,7 @@ for update in graph.stream(
|
||||
print(update)
|
||||
```
|
||||
|
||||
When we use the LangGraph Platform, either locally (e.g., in LangGraph Studio) or with LangGraph Cloud, the base store is available to use by default and does not need to be specified during graph compilation. To enable semantic search, however, you **do** need to configure the indexing settings in your `langgraph.json` file. For example:
|
||||
When we use the LangGraph Platform, either locally (e.g., in LangGraph Studio) or with LangGraph Platform, the base store is available to use by default and does not need to be specified during graph compilation. To enable semantic search, however, you **do** need to configure the indexing settings in your `langgraph.json` file. For example:
|
||||
|
||||
```json
|
||||
{
|
||||
@@ -451,7 +451,7 @@ Under the hood, checkpointing is powered by checkpointer objects that conform to
|
||||
|
||||
* `langgraph-checkpoint`: The base interface for checkpointer savers ([BaseCheckpointSaver][langgraph.checkpoint.base.BaseCheckpointSaver]) and serialization/deserialization interface ([SerializerProtocol][langgraph.checkpoint.serde.base.SerializerProtocol]). Includes in-memory checkpointer implementation ([InMemorySaver][langgraph.checkpoint.memory.InMemorySaver]) for experimentation. LangGraph comes with `langgraph-checkpoint` included.
|
||||
* `langgraph-checkpoint-sqlite`: An implementation of LangGraph checkpointer that uses SQLite database ([SqliteSaver][langgraph.checkpoint.sqlite.SqliteSaver] / [AsyncSqliteSaver][langgraph.checkpoint.sqlite.aio.AsyncSqliteSaver]). Ideal for experimentation and local workflows. Needs to be installed separately.
|
||||
* `langgraph-checkpoint-postgres`: An advanced checkpointer that uses Postgres database ([PostgresSaver][langgraph.checkpoint.postgres.PostgresSaver] / [AsyncPostgresSaver][langgraph.checkpoint.postgres.aio.AsyncPostgresSaver]), used in LangGraph Cloud. Ideal for using in production. Needs to be installed separately.
|
||||
* `langgraph-checkpoint-postgres`: An advanced checkpointer that uses Postgres database ([PostgresSaver][langgraph.checkpoint.postgres.PostgresSaver] / [AsyncPostgresSaver][langgraph.checkpoint.postgres.aio.AsyncPostgresSaver]), used in LangGraph Platform. Ideal for using in production. Needs to be installed separately.
|
||||
|
||||
|
||||
### Checkpointer interface
|
||||
|
||||
@@ -33,7 +33,7 @@ There are three different plans for using it.
|
||||
| Publish/subscribe API for state | -- | Coming Soon! | Coming Soon! |
|
||||
| Scheduling prioritization | -- | Coming Soon! | Coming Soon! |
|
||||
|
||||
Please see the [LangGraph Platform Pricing](https://www.langchain.com/langgraph-platform-pricing) for information on pricing.
|
||||
For pricing information, see [LangGraph Platform Pricing](https://www.langchain.com/langgraph-platform-pricing).
|
||||
|
||||
## Related
|
||||
|
||||
|
||||
@@ -97,4 +97,4 @@ After configuring the app properly and adding your API keys, you can start the a
|
||||
See the following guides for more information on how to deploy your app:
|
||||
|
||||
- **[Launch Local LangGraph Server](../tutorials/langgraph-platform/local-server.md)**: This quick start guide shows how to start a LangGraph Server locally for the **ReAct Agent** template. The steps are similar for other templates.
|
||||
- **[Deploy to LangGraph Cloud](../cloud/quick_start.md)**: Deploy your LangGraph app using LangGraph Cloud.
|
||||
- **[Deploy to LangGraph Platform](../cloud/quick_start.md)**: Deploy your LangGraph app using LangGraph Platform.
|
||||
|
||||
@@ -11,9 +11,9 @@
|
||||
|
||||
???+ note "Support by deployment type"
|
||||
|
||||
Custom auth is supported for all deployments in the **managed LangGraph Cloud**, as well as **Enterprise** self-hosted plans. It is not supported for **Lite** self-hosted plans.
|
||||
Custom auth is supported for all deployments in the **managed LangGraph Platform**, as well as **Enterprise** self-hosted plans. It is not supported for **Lite** self-hosted plans.
|
||||
|
||||
This guide shows how to add custom authentication to your LangGraph Platform application. This guide applies to both LangGraph Cloud and self-hosted deployments. It does not apply to isolated usage of the LangGraph open source library in your own custom server.
|
||||
This guide shows how to add custom authentication to your LangGraph Platform application. This guide applies to both LangGraph Platform and self-hosted deployments. It does not apply to isolated usage of the LangGraph open source library in your own custom server.
|
||||
|
||||
## 1. Implement authentication
|
||||
|
||||
|
||||
@@ -11,9 +11,9 @@ This guide applies to all LangGraph Platform deployments (Cloud and self-hosted)
|
||||
|
||||
The default security scheme varies by deployment type:
|
||||
|
||||
=== "LangGraph Cloud"
|
||||
=== "LangGraph Platform"
|
||||
|
||||
By default, LangGraph Cloud requires a LangSmith API key in the `x-api-key` header:
|
||||
By default, LangGraph Platform requires a LangSmith API key in the `x-api-key` header:
|
||||
|
||||
```yaml
|
||||
components:
|
||||
|
||||
@@ -75,7 +75,7 @@ You should see your startup message printed when the server starts, and your cle
|
||||
|
||||
## Deploying
|
||||
|
||||
You can deploy your app as-is to LangGraph Cloud or to your self-hosted platform.
|
||||
You can deploy your app as-is to LangGraph Platform or to your self-hosted platform.
|
||||
|
||||
## Next steps
|
||||
|
||||
|
||||
@@ -68,7 +68,7 @@ Now any request to your server will include the custom header `X-Custom-Header`
|
||||
|
||||
## Deploying
|
||||
|
||||
You can deploy this app as-is to LangGraph Cloud or to your self-hosted platform.
|
||||
You can deploy this app as-is to LangGraph Platform or to your self-hosted platform.
|
||||
|
||||
## Next steps
|
||||
|
||||
|
||||
@@ -67,7 +67,7 @@ If you navigate to `localhost:2024/hello` in your browser (`2024` is the default
|
||||
|
||||
## Deploying
|
||||
|
||||
You can deploy this app as-is to LangGraph Cloud or to your self-hosted platform.
|
||||
You can deploy this app as-is to LangGraph Platform or to your self-hosted platform.
|
||||
|
||||
## Next steps
|
||||
|
||||
|
||||
@@ -220,7 +220,7 @@
|
||||
"source": [
|
||||
"!!! note Note\n",
|
||||
"\n",
|
||||
" If you're using LangGraph Cloud or LangGraph Studio, you __don't need__ to pass checkpointer to the entrypoint decorator, since it's done automatically."
|
||||
" If you're using LangGraph Platform or LangGraph Studio, you __don't need__ to pass checkpointer to the entrypoint decorator, since it's done automatically."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
@@ -15,7 +15,7 @@ This guide assumes basic familiarity with the following concepts:
|
||||
|
||||
!!! note
|
||||
|
||||
Custom auth is only available for LangGraph Cloud SaaS deployments or Enterprise Self-Hosted deployments.
|
||||
Custom auth is only available for LangGraph Platform SaaS deployments or Enterprise Self-Hosted deployments.
|
||||
|
||||
## 1. Create your app
|
||||
|
||||
@@ -42,7 +42,7 @@ The server will start and open the studio in your browser:
|
||||
> - 📚 API Docs: http://127.0.0.1:2024/docs
|
||||
>
|
||||
> This in-memory server is designed for development and testing.
|
||||
> For production use, please use LangGraph Cloud.
|
||||
> For production use, please use LangGraph Platform.
|
||||
```
|
||||
|
||||
If you were to self-host this on the public internet, anyone could access it!
|
||||
|
||||
@@ -114,10 +114,10 @@ Tool Calls:
|
||||
================================= Tool Message =================================
|
||||
Name: tavily_search_results_json
|
||||
|
||||
[{"url": "https://blog.langchain.dev/langgraph-cloud/", "content": "We also have a new stable release of LangGraph. By LangChain 6 min read Jun 27, 2024 (Oct '24) Edit: Since the launch of LangGraph Cloud, we now have multiple deployment options alongside LangGraph Studio - which now fall under LangGraph Platform. LangGraph Cloud is synonymous with our Cloud SaaS deployment option."}, {"url": "https://changelog.langchain.com/announcements/langgraph-cloud-deploy-at-scale-monitor-carefully-iterate-boldly", "content": "LangChain - Changelog | ☁ 🚀 LangGraph Cloud: Deploy at scale, monitor LangChain LangSmith LangGraph LangChain LangSmith LangGraph LangChain LangSmith LangGraph LangChain Changelog Sign up for our newsletter to stay up to date DATE: The LangChain Team LangGraph LangGraph Cloud ☁ 🚀 LangGraph Cloud: Deploy at scale, monitor carefully, iterate boldly DATE: June 27, 2024 AUTHOR: The LangChain Team LangGraph Cloud is now in closed beta, offering scalable, fault-tolerant deployment for LangGraph agents. LangGraph Cloud also includes a new playground-like studio for debugging agent failure modes and quick iteration: Join the waitlist today for LangGraph Cloud. And to learn more, read our blog post announcement or check out our docs. Subscribe By clicking subscribe, you accept our privacy policy and terms and conditions."}]
|
||||
[{"url": "https://blog.langchain.dev/langgraph-cloud/", "content": "We also have a new stable release of LangGraph. By LangChain 6 min read Jun 27, 2024 (Oct '24) Edit: Since the launch of LangGraph Platform, we now have multiple deployment options alongside LangGraph Studio - which now fall under LangGraph Platform. LangGraph Platform is synonymous with our Cloud SaaS deployment option."}, {"url": "https://changelog.langchain.com/announcements/langgraph-cloud-deploy-at-scale-monitor-carefully-iterate-boldly", "content": "LangChain - Changelog | ☁ 🚀 LangGraph Platform: Deploy at scale, monitor LangChain LangSmith LangGraph LangChain LangSmith LangGraph LangChain LangSmith LangGraph LangChain Changelog Sign up for our newsletter to stay up to date DATE: The LangChain Team LangGraph LangGraph Platform ☁ 🚀 LangGraph Platform: Deploy at scale, monitor carefully, iterate boldly DATE: June 27, 2024 AUTHOR: The LangChain Team LangGraph Platform is now in closed beta, offering scalable, fault-tolerant deployment for LangGraph agents. LangGraph Platform also includes a new playground-like studio for debugging agent failure modes and quick iteration: Join the waitlist today for LangGraph Platform. And to learn more, read our blog post announcement or check out our docs. Subscribe By clicking subscribe, you accept our privacy policy and terms and conditions."}]
|
||||
================================== Ai Message ==================================
|
||||
|
||||
[{'text': "Based on the search results, it appears that LangGraph was already in existence before June 27, 2024, when LangGraph Cloud was announced. However, the search results don't provide a specific release date for the original LangGraph. \n\nGiven this information, I'll use the human_assistance tool to review and potentially provide more accurate information about LangGraph's initial release date.", 'type': 'text'}, {'id': 'toolu_01JDQAV7nPqMkHHhNs3j3XoN', 'input': {'name': 'Assistant', 'birthday': '2023-01-01'}, 'name': 'human_assistance', 'type': 'tool_use'}]
|
||||
[{'text': "Based on the search results, it appears that LangGraph was already in existence before June 27, 2024, when LangGraph Platform was announced. However, the search results don't provide a specific release date for the original LangGraph. \n\nGiven this information, I'll use the human_assistance tool to review and potentially provide more accurate information about LangGraph's initial release date.", 'type': 'text'}, {'id': 'toolu_01JDQAV7nPqMkHHhNs3j3XoN', 'input': {'name': 'Assistant', 'birthday': '2023-01-01'}, 'name': 'human_assistance', 'type': 'tool_use'}]
|
||||
Tool Calls:
|
||||
human_assistance (toolu_01JDQAV7nPqMkHHhNs3j3XoN)
|
||||
Call ID: toolu_01JDQAV7nPqMkHHhNs3j3XoN
|
||||
@@ -149,7 +149,7 @@ for event in events:
|
||||
```
|
||||
================================== Ai Message ==================================
|
||||
|
||||
[{'text': "Based on the search results, it appears that LangGraph was already in existence before June 27, 2024, when LangGraph Cloud was announced. However, the search results don't provide a specific release date for the original LangGraph. \n\nGiven this information, I'll use the human_assistance tool to review and potentially provide more accurate information about LangGraph's initial release date.", 'type': 'text'}, {'id': 'toolu_01JDQAV7nPqMkHHhNs3j3XoN', 'input': {'name': 'Assistant', 'birthday': '2023-01-01'}, 'name': 'human_assistance', 'type': 'tool_use'}]
|
||||
[{'text': "Based on the search results, it appears that LangGraph was already in existence before June 27, 2024, when LangGraph Platform was announced. However, the search results don't provide a specific release date for the original LangGraph. \n\nGiven this information, I'll use the human_assistance tool to review and potentially provide more accurate information about LangGraph's initial release date.", 'type': 'text'}, {'id': 'toolu_01JDQAV7nPqMkHHhNs3j3XoN', 'input': {'name': 'Assistant', 'birthday': '2023-01-01'}, 'name': 'human_assistance', 'type': 'tool_use'}]
|
||||
Tool Calls:
|
||||
human_assistance (toolu_01JDQAV7nPqMkHHhNs3j3XoN)
|
||||
Call ID: toolu_01JDQAV7nPqMkHHhNs3j3XoN
|
||||
@@ -168,9 +168,9 @@ LangGraph was initially released on January 17, 2024. This information comes fro
|
||||
|
||||
To summarize:
|
||||
1. LangGraph's original release date: January 17, 2024
|
||||
2. LangGraph Cloud announcement: June 27, 2024
|
||||
2. LangGraph Platform announcement: June 27, 2024
|
||||
|
||||
It's worth noting that LangGraph had been in development and use for some time before the LangGraph Cloud announcement, but the official initial release of LangGraph itself was on January 17, 2024.
|
||||
It's worth noting that LangGraph had been in development and use for some time before the LangGraph Platform announcement, but the official initial release of LangGraph itself was on January 17, 2024.
|
||||
```
|
||||
|
||||
Note that these fields are now reflected in the state:
|
||||
|
||||
@@ -105,7 +105,7 @@ Tool Calls:
|
||||
================================= Tool Message =================================
|
||||
Name: tavily_search_results_json
|
||||
|
||||
[{"url": "https://blockchain.news/news/langchain-new-features-upcoming-events-update", "content": "LangChain, a leading platform in the AI development space, has released its latest updates, showcasing new use cases and enhancements across its ecosystem. According to the LangChain Blog, the updates cover advancements in LangGraph Cloud, LangSmith's self-improving evaluators, and revamped documentation for LangGraph."}, {"url": "https://blog.langchain.dev/langgraph-platform-announce/", "content": "With these learnings under our belt, we decided to couple some of our latest offerings under LangGraph Platform. LangGraph Platform today includes LangGraph Server, LangGraph Studio, plus the CLI and SDK. ... we added features in LangGraph Server to deliver on a few key value areas. Below, we'll focus on these aspects of LangGraph Platform."}]
|
||||
[{"url": "https://blockchain.news/news/langchain-new-features-upcoming-events-update", "content": "LangChain, a leading platform in the AI development space, has released its latest updates, showcasing new use cases and enhancements across its ecosystem. According to the LangChain Blog, the updates cover advancements in LangGraph Platform, LangSmith's self-improving evaluators, and revamped documentation for LangGraph."}, {"url": "https://blog.langchain.dev/langgraph-platform-announce/", "content": "With these learnings under our belt, we decided to couple some of our latest offerings under LangGraph Platform. LangGraph Platform today includes LangGraph Server, LangGraph Studio, plus the CLI and SDK. ... we added features in LangGraph Server to deliver on a few key value areas. Below, we'll focus on these aspects of LangGraph Platform."}]
|
||||
================================== Ai Message ==================================
|
||||
|
||||
Thank you for your patience. I've found some recent information about LangGraph for you. Let me summarize the key points:
|
||||
@@ -114,9 +114,9 @@ Thank you for your patience. I've found some recent information about LangGraph
|
||||
|
||||
2. Recent updates and features of LangGraph include:
|
||||
|
||||
a. LangGraph Cloud: This seems to be a cloud-based version of LangGraph, though specific details weren't provided in the search results.
|
||||
a. LangGraph Platform: This seems to be a cloud-based version of LangGraph, though specific details weren't provided in the search results.
|
||||
...
|
||||
3. Keep an eye on LangGraph Cloud developments, as cloud-based solutions often provide an easier starting point for learners.
|
||||
3. Keep an eye on LangGraph Platform developments, as cloud-based solutions often provide an easier starting point for learners.
|
||||
4. Consider how LangGraph fits into the broader LangChain ecosystem, especially its interaction with tools like LangSmith.
|
||||
|
||||
Is there any specific aspect of LangGraph you'd like to know more about? I'd be happy to do a more focused search on particular features or use cases.
|
||||
@@ -284,5 +284,5 @@ The graph resumed execution from the `action` node. You can tell this is the cas
|
||||
Take your LangGraph journey further by exploring deployment and advanced features:
|
||||
|
||||
- **[LangGraph Server quickstart](../../tutorials/langgraph-platform/local-server.md)**: Launch a LangGraph server locally and interact with it using the REST API and LangGraph Studio Web UI.
|
||||
- **[LangGraph Cloud quickstart](../../cloud/quick_start.md)**: Deploy your LangGraph app using LangGraph Cloud.
|
||||
- **[LangGraph Platform quickstart](../../cloud/quick_start.md)**: Deploy your LangGraph app using LangGraph Platform.
|
||||
- **[LangGraph Platform concepts](../../concepts/langgraph_platform.md)**: Understand the foundational concepts of the LangGraph Platform.
|
||||
@@ -14,7 +14,7 @@ New to LangGraph or LLM app development? Read this material to get up and runnin
|
||||
- [Common Workflows](workflows/index.md): Overview of the most common workflows using LLMs implemented with LangGraph.
|
||||
- [LangGraph Server Quickstart](langgraph-platform/local-server.md): Launch a LangGraph server locally and interact with it using REST API and LangGraph Studio Web UI.
|
||||
- [LangGraph Template Quickstart](../concepts/template_applications.md): Start building with LangGraph Platform using a template application.
|
||||
- [Deploy with LangGraph Cloud Quickstart](../cloud/quick_start.md): Deploy a LangGraph app using LangGraph Cloud.
|
||||
- [Deploy with LangGraph Platform Quickstart](../cloud/quick_start.md): Deploy a LangGraph app using LangGraph Platform.
|
||||
|
||||
## Use cases 🛠️ {#use-cases}
|
||||
|
||||
|
||||
@@ -206,7 +206,7 @@ def up(
|
||||
):
|
||||
click.secho("Starting LangGraph API server...", fg="green")
|
||||
click.secho(
|
||||
"""For local dev, requires env var LANGSMITH_API_KEY with access to LangGraph Cloud closed beta.
|
||||
"""For local dev, requires env var LANGSMITH_API_KEY with access to LangGraph Platform closed beta.
|
||||
For production use, requires a license key in env var LANGGRAPH_CLOUD_LICENSE_KEY.""",
|
||||
)
|
||||
with Runner() as runner, Progress(message="Pulling...") as set:
|
||||
@@ -529,7 +529,7 @@ def dockerfile(
|
||||
"\n",
|
||||
"# LANGSMITH_API_KEY=your-api-key",
|
||||
"\n",
|
||||
"# Or if you have a LangGraph Cloud license key, "
|
||||
"# Or if you have a LangGraph Platform license key, "
|
||||
"then uncomment the following line: ",
|
||||
"\n",
|
||||
"# LANGGRAPH_CLOUD_LICENSE_KEY=your-license-key",
|
||||
|
||||
@@ -538,7 +538,7 @@ ENV LANGSERVE_GRAPHS='{{"agent": "/deps/__outer_graphs/src/agent.py:graph"}}'
|
||||
assert additional_contexts == {}
|
||||
|
||||
|
||||
# node.js build used for LangGraph Cloud
|
||||
# node.js build used for LangGraph Platform
|
||||
def test_config_to_docker_nodejs():
|
||||
graphs = {"agent": "./graphs/agent.js:graph"}
|
||||
actual_docker_stdin, additional_contexts = config_to_docker(
|
||||
|
||||
@@ -89,7 +89,7 @@ class RemoteGraph(PregelProtocol):
|
||||
APIs that implement the LangGraph Server API specification.
|
||||
|
||||
For example, the `RemoteGraph` class can be used to call APIs from deployments
|
||||
on LangGraph Cloud.
|
||||
on LangGraph Platform.
|
||||
|
||||
`RemoteGraph` behaves the same way as a `Graph` and can be used directly as
|
||||
a node in another `Graph`.
|
||||
|
||||
@@ -863,7 +863,7 @@ async def test_ainvoke():
|
||||
assert result == {"messages": [{"type": "human", "content": "world"}]}
|
||||
|
||||
|
||||
@pytest.mark.skip("Unskip this test to manually test the LangGraph Cloud integration")
|
||||
@pytest.mark.skip("Unskip this test to manually test the LangGraph Platform integration")
|
||||
@pytest.mark.anyio
|
||||
async def test_langgraph_cloud_integration():
|
||||
from langgraph_sdk.client import get_client, get_sync_client
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
# LangGraph Python SDK
|
||||
|
||||
This repository contains the Python SDK for interacting with the LangGraph Cloud REST API.
|
||||
This repository contains the Python SDK for interacting with the LangGraph Platform REST API.
|
||||
|
||||
## Quick Start
|
||||
|
||||
|
||||
Reference in New Issue
Block a user