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[docs]: restructuring (#834)
* restructuring * spelling * links * restructuring * edits * Update docs/docs/cloud/concepts/index.md * Update docs/docs/cloud/concepts/index.md --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
This commit is contained in:
Isaac Francisco
co-authored by
Harrison Chase
Harrison Chase
parent
a6e25ba7c1
commit
0bccc19a50
@@ -59,11 +59,11 @@ See the <a href="../reference/api/api_ref.html#tag/runscreate/POST/threads/{thre
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### Human-in-the-Loop
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There are many occasions where the graph cannot run completely autonomously. For instance, the user might need to input some additional arguments to a function call, or select the next edge for the graph to continue on. In these instances, we need to insert some human in the loop interaction, which you can learn about in the [human in the loop how-tos](../how-tos/cloud_examples/human_in_the_loop_breakpoint.ipynb).
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There are many occasions where the graph cannot run completely autonomously. For instance, the user might need to input some additional arguments to a function call, or select the next edge for the graph to continue on. In these instances, we need to insert some human in the loop interaction, which you can learn about in the [human in the loop how-tos](../how-tos/index.md#human-in-the-loop).
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### Double Texting
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Many times users might interact with your graph in unintended ways. For instance, a user may send one message and before the graph has finished running send a second message. To solve this issue of "double-texting" (i.e. prompting the graph a second time before the first run has finished), Langgraph has provided four different solutions, all of which are covered in the [Double Texting how-tos](../how-tos/cloud_examples/interrupt_concurrent.ipynb). These options are:
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Many times users might interact with your graph in unintended ways. For instance, a user may send one message and before the graph has finished running send a second message. To solve this issue of "double-texting" (i.e. prompting the graph a second time before the first run has finished), Langgraph has provided four different solutions, all of which are covered in the [Double Texting how-tos](../how-tos/index.md#double-texting). These options are:
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- `reject`: This is the simplest option, this just rejects any follow up runs and does not allow double texting. See the [how-to guide](../how-tos/cloud_examples/reject_concurrent.ipynb) for configuring the reject double text option.
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- `enqueue`: This is a relatively simple option which continues the first run until it completes the whole run, then sends the new input as a separate run. See the [how-to guide](../how-tos/cloud_examples/enqueue_concurrent.ipynb) for configuring the enqueue double text option.
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@@ -88,6 +88,12 @@ The only difference is in stateless background runs, if the task worker dies hal
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See the [how-to guide](../how-tos/cloud_examples/stateless_runs.ipynb) for creating stateless runs.
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### Webhooks
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For all types of runs, langgraph cloud supports completion webhooks. When you create the run you can pass a webhook URL to be called when the completes (successfully or not). This is especially useful for background runs and cron jobs, as the webhook can give you an indication the run has completed and you can perform further actions for your appilcation.
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See this [how-to guide](https://langchain-ai.github.io/langgraph/cloud/how-tos/cloud_examples/webhooks/) to learn about how to use webhooks with LangGraph Cloud.
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## Deployment
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The LangGraph Cloud offers several features to support secure and robost deployments.
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@@ -1,44 +0,0 @@
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# How to Test with LangGraph Studio
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LangGraph applications can be tested with LangGraph Studio. LangGraph Studio is a robust UI for testing and exercising functionality of the graphs in a LangGraph application. The LangGraph Studio UI connects directly to a LangGraph Cloud deployments or to a local LangGraph API instance.
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The LangGraph Studio UI is available within <a href="https://www.langchain.com/langsmith" target="_blank">LangSmith</a>. To test a LangGraph application, navigate to the <a href="https://smith.langchain.com/" target="_blank">LangSmith UI</a>.
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## Test Cloud Deployment
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The LangGraph Studio UI connects directly to LangGraph Cloud deployments.
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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 `Deployments`. The `Deployments` view contains a list of existing LangGraph Cloud deployments.
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1. Select an existing deployment to test with LangGraph Studio.
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1. In the top-right corner, select `Open LangGraph Studio`.
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1. [Invoke an assistant](#invoke-assistant) or [view an existing thread](#view-thread).
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## Test Local Instance
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The LangGraph Studio UI connects directly to local LangGraph API instances. This is helpful for quickly iterating and testing during the development process.
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Starting from the <a href="https://smith.langchain.com/" target="_blank">LangSmith UI</a>...
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1. Find the hostname of the local LangGraph API instance. For example, `http://localhost:9123`.
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1. Navigate to the URL `/studio/thread/` and set the `baseUrl` query parameter to the hostname. For example, `https://smith.langchain.com/studio/thread?baseUrl=http://localhost:9123`.
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1. [Invoke an assistant](#invoke-assistant) or [view an existing thread](#view-thread).
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## Invoke Assistant
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1. The LangGraph Studio UI displays a visualization of the selected assistant.
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1. In the top-right dropdown menu of the left-hand pane, select an assistant.
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1. In the bottom of the left-hand pane, edit the `Input` and `Configure` the assistant.
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1. Select `Submit` to invoke the selected assistant.
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1. View output of the invocation in the right-hand pane.
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## View Thread
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1. In the top of the right-hand pane, select the `New Thread` dropdown menu to view existing threads.
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1. View the state of the thread (i.e. the output) in the right-hand pane.
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1. To create a new thread, select `+ New Thread`.
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## Edit Thread State
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The LangGraph Studio UI contains features for editing thread state. Explore these features in the right-hand pane. Select the `Edit` icon, modify the desired state, and then select `Fork` to invoke the assistant with the updated state.
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---
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hide:
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- toc
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---
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# How-to Guides
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Welcome to the LangGraph Cloud how-to guides! These guides provide practical, step-by-step instructions for accomplishing key tasks in LangGraph Cloud.
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## Deployment
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LangGraph Cloud gives you best in class observability, testing, and hosting services. Read more about them in these how to guides:
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- [How to set up app for deployment](https://langchain-ai.github.io/langgraph/cloud/deployment/setup/)
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- [How to deploy to LangGraph cloud](https://langchain-ai.github.io/langgraph/cloud/deployment/cloud/)
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- [How to self-host](https://langchain-ai.github.io/langgraph/cloud/deployment/self_hosted/)
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## Streaming
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Streaming the results of your LLM application is vital for ensuring a good user experience, especially when your graph may call multiple models and take a long time to fully complete a run. Read about how to stream values from your graph in these how to guides:
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- [How to stream values](https://langchain-ai.github.io/langgraph/cloud/how-tos/cloud_examples/stream_values/)
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- [How to stream updates](https://langchain-ai.github.io/langgraph/cloud/how-tos/cloud_examples/stream_updates/)
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- [How to stream messages](https://langchain-ai.github.io/langgraph/cloud/how-tos/cloud_examples/stream_messages/)
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- [How to stream events](https://langchain-ai.github.io/langgraph/cloud/how-tos/cloud_examples/stream_events/)
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- [How to stream in debug mode](https://langchain-ai.github.io/langgraph/cloud/how-tos/cloud_examples/stream_debug/)
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- [How to stream multiple modes](https://langchain-ai.github.io/langgraph/cloud/how-tos/cloud_examples/stream_multiple/)
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## Double-texting
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Graph execution can take a while, and sometimes users may change their mind about the input they wanted to send before their original input has finished running. For example, a user might notice a typo in their original request and will edit the prompt and resend it. Deciding what to do in these cases is important for ensuring a smooth user experience and preventing your graphs from behaving in unexpected ways. The following how-to guides provide information on the various options LangGraph Cloud gives you for dealing with double-texting:
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- [How to use the interrupt option](https://langchain-ai.github.io/langgraph/cloud/how-tos/cloud_examples/interrupt_concurrent/)
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- [How to use the rollback option](https://langchain-ai.github.io/langgraph/cloud/how-tos/cloud_examples/rollback_concurrent/)
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- [How to use the reject option](https://langchain-ai.github.io/langgraph/cloud/how-tos/cloud_examples/reject_concurrent/)
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- [How to use the rnqueue option](https://langchain-ai.github.io/langgraph/cloud/how-tos/cloud_examples/enqueue_concurrent/)
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## Human-in-the-loop
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When creating complex graphs, leaving every decision up to the LLM can be dangerous, especially when the decisions involve invoking certain tools or accessing specific documents. To remedy this, LangGraph allows you to insert human-in-the-loop behavior to ensure your graph does not have undesired outcomes. Read more about the different ways you can add human-in-the-loop capabilities to your LangGraph Cloud projects in these how-to guides:
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- [How to add a breakpoint](https://langchain-ai.github.io/langgraph/cloud/how-tos/cloud_examples/human_in_the_loop_breakpoint/)
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- [How to wait for user input](https://langchain-ai.github.io/langgraph/cloud/how-tos/cloud_examples/human_in_the_loop_user_input/)
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- [How to edit graph state](https://langchain-ai.github.io/langgraph/cloud/how-tos/cloud_examples/human_in_the_loop_edit_state/)
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- [How to replay and branch from prior states](https://langchain-ai.github.io/langgraph/cloud/how-tos/cloud_examples/human_in_the_loop_time_travel/)
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## LangGraph Studio
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- [Test Cloud Deployment](https://langchain-ai.github.io/langgraph/cloud/how-tos/test_deployment/)
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- [Invoke graph in LangGraph Studio](https://langchain-ai.github.io/langgraph/cloud/how-tos/invoke_studio/)
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- [Interact with threads in LangGraph Studio](https://langchain-ai.github.io/langgraph/cloud/how-tos/threads_studio/)
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## And more!
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The four sections above don't cover everything that is possible with LangGraph cloud - make sure to check out our other how-to guides to learn even more!
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@@ -0,0 +1,13 @@
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# Invoke Assistant
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The LangGraph Studio lets you test different configurations and inputs to your graph. The UI allows you to see exactly how your
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1. The LangGraph Studio UI displays a visualization of the selected assistant.
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1. In the top-right dropdown menu of the left-hand pane, select an assistant.
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1. In the bottom of the left-hand pane, edit the `Input` and `Configure` the assistant.
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1. Select `Submit` to invoke the selected assistant.
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1. View output of the invocation in the right-hand pane.
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The following GIF shows these exact steps being carried out:
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@@ -0,0 +1,14 @@
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# Test Cloud Deployment
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The LangGraph Studio UI connects directly to LangGraph Cloud deployments.
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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 `Deployments`. The `Deployments` view contains a list of existing LangGraph Cloud deployments.
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1. Select an existing deployment to test with LangGraph Studio.
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1. In the top-right corner, select `Open LangGraph Studio`.
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1. [Invoke an assistant](./invoke_studio.md) or [view an existing thread](./threads_studio.md).
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The following GIF shows these exact steps being carried out:
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@@ -0,0 +1,19 @@
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# Interacting with Threads in Studio
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## View Thread
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1. In the top of the right-hand pane, select the `New Thread` dropdown menu to view existing threads.
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1. View the state of the thread (i.e. the output) in the right-hand pane.
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1. To create a new thread, select `+ New Thread`.
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The following GIF shows these exact steps being carried out:
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## Edit Thread State
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The LangGraph Studio UI contains features for editing thread state. Explore these features in the right-hand pane. Select the `Edit` icon, modify the desired state, and then select `Fork` to invoke the assistant with the updated state.
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The following GIF shows how to edit a thread in the studio:
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@@ -6,6 +6,8 @@
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!!! warning "Under Construction"
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LangGraph Cloud documentation is under construction. Contents may change until general availability.
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## Overview
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LangGraph Cloud is a managed service for deploying and hosting LangGraph applications. Deploying applications with LangGraph Cloud shortens the time-to-market for developers. With one click, deploy a production-ready API with built-in persistence for your LangGraph application. LangGraph Cloud APIs are horizontally scalable and deployed with durable storage.
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@@ -28,6 +30,6 @@ The LangGraph Cloud API supports key LangGraph features in addition to new funct
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## Documentation
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- [Tutorials](./quick_start.md): Learn to build and deploy applications for LangGraph Cloud.
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- [How-to Guides](./deployment/setup.md): Learn how to set up a LangGraph application for deployment and implement features of the LangGraph Cloud API such as streaming tokens, configuring double texting, and creating cron jobs. Go here if you want to copy and run a specific code snippet.
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- [How-to Guides](./how-tos/index.md): Learn how to set up a LangGraph application for deployment and implement features of the LangGraph Cloud API such as streaming tokens, configuring double texting, and creating cron jobs. Go here if you want to copy and run a specific code snippet.
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- [Conceptual Guides](./concepts/index.md): In-depth explanations of the core data models (e.g. assistants) and key features (e.g. double texting) of the LangGraph Cloud API.
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- [Reference](./reference/api/api_ref.md): References for the LangGraph Cloud API, the corresponding Python and JS/TS SDKs, the LangGraph CLI, and deployment environment variables.
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@@ -239,11 +239,11 @@ Congratulations! If you've worked your way through this tutorial you are well on
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### LangGraph Cloud How-tos
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If you want to learn more about streaming from hosted graphs, check out the Streaming [how-to guides](https://langchain-ai.github.io/langgraph/cloud/how-tos/cloud_examples/stream_values/).
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If you want to learn more about streaming from hosted graphs, check out the Streaming [how-to guides](https://langchain-ai.github.io/langgraph/cloud/how-tos/#streaming).
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To learn more about double-texting and all the ways you can handle it in your application, read up on these [how-to guides](https://langchain-ai.github.io/langgraph/cloud/how-tos/cloud_examples/interrupt_concurrent/).
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To learn more about double-texting and all the ways you can handle it in your application, read up on these [how-to guides](https://langchain-ai.github.io/langgraph/cloud/how-tos/#double-texting).
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To learn about how to include different human-in-the-loop behavior in your graph, take a look at [these how-tos](https://langchain-ai.github.io/langgraph/cloud/how-tos/cloud_examples/human_in_the_loop_breakpoint/).
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To learn about how to include different human-in-the-loop behavior in your graph, take a look at [these how-tos](https://langchain-ai.github.io/langgraph/cloud/how-tos/#human-in-the-loop).
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### LangGraph Tutorials
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@@ -82,61 +82,20 @@ langgraph build [OPTIONS]
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| `-c, --config FILE` | `langgraph.json` | Path to configuration file declaring dependencies, graphs and environment variables. |
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| `--help` | | Display command documentation. |
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### `down`
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Stop LangGraph Cloud API server.
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### `test`
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Test your LangGraph in the cloud. The only function you can call from the SDK after testing your graph is `client.runs.stream(thread_id=None, ...)`
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**Usage**
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```
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langgraph down [OPTIONS]
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langgraph test [OPTIONS]
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```
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**Options**
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| Option | Default | Description |
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| ------ | ------- | ----------- |
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| `--debugger-port INTEGER` | | Pull the debugger image locally and serve the UI on specified port. |
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| `--verbose` | | Show more output from the server logs. |
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| `-c, --config FILE` | `langgraph.json` | Path to configuration file declaring dependencies, graphs and environment variables. |
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| `-d, --docker-compose FILE` | | Advanced. Path to `docker-compose.yml` file with additional services to launch. |
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| `-p, --port INTEGER` | `8123` | Port to expose. Example: `langgraph up --port 8000` |
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| `--help` | | Display command documentation. |
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### `logs`
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Show LangGraph Cloud API server logs.
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**Usage**
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```
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langgraph logs [OPTIONS]
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```
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**Options**
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| Option | Default | Description |
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| ------ | ------- | ----------- |
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| `-f, --follow` | | Follow logs. |
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| `-c, --config FILE` | `langgraph.json` | Path to configuration file declaring dependencies, graphs and environment variables. |
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| `-d, --docker-compose FILE` | | Advanced. Path to `docker-compose.yml` file with additional services to launch. |
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| `--help` | | Display command documentation. |
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### `up`
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Start LangGraph Cloud API server.
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**Usage**
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```
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langgraph up [OPTIONS]
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```
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**Options**
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| Option | Default | Description |
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| ------ | ------- | ----------- |
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| `--wait` | | Wait for services to start before returning. Implies `--detach`. |
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| `--watch` | | Restart on file changes. |
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| `--debugger-port INTEGER` | | Pull the debugger image locally and serve the UI on specified port. |
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| `--verbose` | | Show more output from the server logs. |
|
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| `-c, --config FILE` | `langgraph.json` | Path to configuration file declaring dependencies, graphs and environment variables. |
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| `-d, --docker-compose FILE` | | Advanced. Path to `docker-compose.yml` file with additional services to launch. |
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| `-p, --port INTEGER` | `8123` | Port to expose. Example: `langgraph up --port 8000` |
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| `--pull / --no-pull` | `--pull` | Build with latest remote Docker image. Use `--no-pull` for running the LangGraph Cloud API server with locally built images. |
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| `--recreate / --no-recreate` | `--no-recreate` | Recreate containers even if their configuration and image haven't changed. |
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| `--help` | | Display command documentation. |
|
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| `-p, --port INTEGER` | `8123` | Port to expose. Example: `langgraph test --port 8000` |
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| `--pull / --no-pull` | `pull` | Pull latest images. Use --no-pull for running the server with locally-built images. Example: `langgraph up --no-pull` |
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| `--help` | | Display command documentation. |
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+15
-11
@@ -170,11 +170,11 @@ nav:
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- "cloud/index.md"
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- Tutorials:
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- Quick Start: "cloud/quick_start.md"
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- How-to Guides:
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- How-to Guides:
|
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- "cloud/how-tos/index.md"
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- Deployment:
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- Setup App: "cloud/deployment/setup.md"
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- Deploy to Cloud: "cloud/deployment/cloud.md"
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- Test with Studio: "cloud/deployment/studio.md"
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- Self-Host: "cloud/deployment/self_hosted.md"
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- Streaming:
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- Stream Values: "cloud/how-tos/cloud_examples/stream_values.ipynb"
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@@ -188,17 +188,21 @@ nav:
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- Rollback: "cloud/how-tos/cloud_examples/rollback_concurrent.ipynb"
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- Reject: "cloud/how-tos/cloud_examples/reject_concurrent.ipynb"
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- Enqueue: "cloud/how-tos/cloud_examples/enqueue_concurrent.ipynb"
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- Human-in-the-Loop:
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- Add Breakpoint: "cloud/how-tos/cloud_examples/human_in_the_loop_breakpoint.ipynb"
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- Wait for User Input: "cloud/how-tos/cloud_examples/human_in_the_loop_user_input.ipynb"
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- Edit Graph State: "cloud/how-tos/cloud_examples/human_in_the_loop_edit_state.ipynb"
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- Replay and Branch from Prior States: "cloud/how-tos/cloud_examples/human_in_the_loop_time_travel.ipynb"
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- Test with LangGraph Studio:
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- Test Cloud Deployment: "cloud/how-tos/test_deployment.md"
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- Invoke graph in LangGraph Studio: "cloud/how-tos/invoke_studio.md"
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- Interact with threads in LangGraph Studio: "cloud/how-tos/threads_studio.md"
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- Run Agent in Background: "cloud/how-tos/cloud_examples/background_run.ipynb"
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- Run Multiple Agents in Thread: "cloud/how-tos/cloud_examples/same-thread.ipynb"
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- Human-in-the-Loop:
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- Add Breakpoint: 'cloud/how-tos/cloud_examples/human_in_the_loop_breakpoint.ipynb'
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- Wait for User Input: 'cloud/how-tos/cloud_examples/human_in_the_loop_user_input.ipynb'
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- Edit Graph State: 'cloud/how-tos/cloud_examples/human_in_the_loop_edit_state.ipynb'
|
||||
- Replay and Branch from Prior States: 'cloud/how-tos/cloud_examples/human_in_the_loop_time_travel.ipynb'
|
||||
- Create Agents with Configuration: 'cloud/how-tos/cloud_examples/configuration_cloud.ipynb'
|
||||
- Convert LangGraph calls to LangGraph Cloud calls: 'cloud/how-tos/cloud_examples/langgraph_to_langgraph_cloud.ipynb'
|
||||
- Create Cron Jobs: 'cloud/how-tos/cloud_examples/cron_jobs.ipynb'
|
||||
- Create Stateless Runs: 'cloud/how-tos/cloud_examples/stateless_runs.ipynb'
|
||||
- Create Agents with Configuration: "cloud/how-tos/cloud_examples/configuration_cloud.ipynb"
|
||||
- Convert LangGraph calls to LangGraph Cloud calls: "cloud/how-tos/cloud_examples/langgraph_to_langgraph_cloud.ipynb"
|
||||
- Create Cron Jobs: "cloud/how-tos/cloud_examples/cron_jobs.ipynb"
|
||||
- Create Stateless Runs: "cloud/how-tos/cloud_examples/stateless_runs.ipynb"
|
||||
- Integrate Webhooks: 'cloud/how-tos/cloud_examples/webhooks.ipynb'
|
||||
- SDK:
|
||||
- Python: "cloud/sdk/python_sdk.ipynb"
|
||||
|
||||
Reference in New Issue
Block a user