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docs: concepts for cloud and doc-reorg (#2196)
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Update langgraph documentation

---------

Co-authored-by: Vadym Barda <vadym@langchain.dev>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Co-authored-by: Nuno Campos <nuno@langchain.dev>
Co-authored-by: Chester Curme <chester.curme@gmail.com>
Co-authored-by: William FH <13333726+hinthornw@users.noreply.github.com>
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16 changes: 11 additions & 5 deletions docs/docs/cloud/deployment/test_locally.md
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Expand Up @@ -8,19 +8,25 @@ Testing locally ensures that there are no errors or conflicts with Python depend

Install the proper packages:

```shell
pip install langgraph-cli
```

Ensure you have an API key, which you can create from the LangSmith UI (Settings > API Keys). This is required to authenticate that you have LangGraph Cloud access. After you have saved the key to a safe place, place the following line in your `.env` file:
=== "pip"
```bash
pip install -U langgraph-cli
```
=== "Homebrew" (macOS only)
```bash
brew install langgraph-cli
```

Ensure you have an API key, which you can create from the [LangSmith UI](https://smith.langchain.com) (Settings > API Keys). This is required to authenticate that you have LangGraph Cloud access. After you have saved the key to a safe place, place the following line in your `.env` file:

```python
LANGCHAIN_API_KEY = *********
```

## Start the API server

Once you have downloaded the CLI, you can run the following command to start the API server for local testing:
Once you have installed the CLI, you can run the following command to start the API server for local testing:

```shell
langgraph up
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1 change: 1 addition & 0 deletions docs/docs/cloud/how-tos/index.md
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Expand Up @@ -22,6 +22,7 @@ LangGraph Cloud gives you best in class observability, testing, and hosting serv
Learn how to deploy your app to LangGraph Cloud in these how to guides:

- [How to deploy to LangGraph cloud](../deployment/cloud.md)
- [How to interact with the deployment using RemoteGraph](../../how-tos/use-remote-graph.md)


## Streaming
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3 changes: 3 additions & 0 deletions docs/docs/cloud/how-tos/stream_debug.md
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# How to stream debug events

!!! info "Prerequisites"
* [Streaming](../../concepts/streaming.md)

This guide covers how to stream debug events from your graph (`stream_mode="debug"`). Streaming debug events produces responses containing `type` and `timestamp` keys. Debug events correspond to different steps in the graph's execution, and there are three different types of steps that will get streamed back to you:

- `checkpoint`: These events will get streamed anytime the graph saves its state, which occurs after every super-step. Read more about checkpoints [here](https://langchain-ai.github.io/langgraph/concepts/low_level/#checkpointer)
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5 changes: 4 additions & 1 deletion docs/docs/cloud/how-tos/stream_events.md
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# How to stream events

This guide covers how to stream events from your graph (`stream_mode="events"`). Depending on the use case and user experience of your LangGraph application, your application may process event types differently. Read more about events in this [conceptual guide](https://langchain-ai.github.io/langgraph/concepts/low_level/#astream_events-for-streaming-tokens-of-llm-calls).
!!! info "Prerequisites"
* [Streaming](../../concepts/streaming.md#streaming-llm-tokens-and-events-astream_events)

This guide covers how to stream events from your graph (`stream_mode="events"`). Depending on the use case and user experience of your LangGraph application, your application may process event types differently.

## Setup

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