docs: concepts for cloud and doc-reorg

docs/docs/cloud/deployment/test_locally.md

@@ -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

docs/docs/cloud/how-tos/index.md

@@ -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

docs/docs/cloud/how-tos/stream_debug.md

@@ -1,5 +1,8 @@
 # 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)

docs/docs/cloud/how-tos/stream_events.md

@@ -1,6 +1,9 @@
 # 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