docs: remove langgraph up references (#2847)

docs/docs/cloud/deployment/cloud.md

@@ -5,7 +5,7 @@ LangGraph Cloud is available within <a href="https://www.langchain.com/langsmith
 ## Prerequisites
 
 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.
-1. [Verify that the LangGraph API runs locally](test_locally.md). If the API does not build and run successfully (i.e. `langgraph up`), deploying to LangGraph Cloud will fail as well.
+1. [Verify that the LangGraph API runs locally](test_locally.md). If the API does not run successfully (i.e. `langgraph dev`), deploying to LangGraph Cloud will fail as well.
 
 ## Create New Deployment
 

docs/docs/cloud/deployment/test_locally.md

@@ -6,17 +6,11 @@ Testing locally ensures that there are no errors or conflicts with Python depend
 
 ## Setup
 
-Install the proper packages:
+Install the LangGraph CLI package:
 
-
-=== "pip" 
-    ```bash
-    pip install -U langgraph-cli
-    ```
-=== "Homebrew (macOS only)"
-    ```bash
-    brew install langgraph-cli
-    ```
+```bash
+pip install -U "langgraph-cli[inmem]"
+```
 
 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:
 
@@ -29,16 +23,26 @@ LANGSMITH_API_KEY = *********
 Once you have installed the CLI, you can run the following command to start the API server for local testing:
 
 ```shell
-langgraph up
+langgraph dev
 ```
 
 This will start up the LangGraph API server locally. If this runs successfully, you should see something like:
 
-```shell
-Ready!
-- API: http://localhost:8123
-2024-06-26 19:20:41,056:INFO:uvicorn.access 127.0.0.1:44138 - "GET /ok HTTP/1.1" 200
-```
+>    Ready!
+> 
+>    - API: [http://localhost:2024](http://localhost:2024/)
+>     
+>    - Docs: http://localhost:2024/docs
+>     
+>    - LangGraph Studio Web UI: https://smith.langchain.com/studio/?baseUrl=http://127.0.0.1:2024
+
+!!! note "In-Memory Mode"
+
+    The `langgraph dev` command starts LangGraph Server in an in-memory mode. This mode is suitable for development and testing purposes. For production use, you should deploy LangGraph Server with access to a persistent storage backend.
+
+    If you want to test your application with a persistent storage backend, you can use the `langgraph up` command instead of `langgraph dev`. You will
+    need to have `docker` installed on your machine to use this command.
+
 
 ### Interact with the server
 
@@ -53,7 +57,7 @@ You can either initialize by passing authentication or by setting an environment
     ```python
     from langgraph_sdk import get_client
 
-    # only pass the url argument to get_client() if you changed the default port when calling langgraph up
+    # only pass the url argument to get_client() if you changed the default port when calling langgraph dev
     client = get_client(url=<DEPLOYMENT_URL>,api_key=<LANGSMITH_API_KEY>)
     # Using the graph deployed with the name "agent"
     assistant_id = "agent"
@@ -65,7 +69,7 @@ You can either initialize by passing authentication or by setting an environment
     ```js
     import { Client } from "@langchain/langgraph-sdk";
 
-    // only set the apiUrl if you changed the default port when calling langgraph up
+    // only set the apiUrl if you changed the default port when calling langgraph dev
     const client = new Client({ apiUrl: <DEPLOYMENT_URL>, apiKey: <LANGSMITH_API_KEY> });
     // Using the graph deployed with the name "agent"
     const assistantId = "agent";
@@ -91,7 +95,7 @@ If you have a `LANGSMITH_API_KEY` set in your environment, you do not need to ex
     ```python
     from langgraph_sdk import get_client
 
-    # only pass the url argument to get_client() if you changed the default port when calling langgraph up
+    # only pass the url argument to get_client() if you changed the default port when calling langgraph dev
     client = get_client()
     # Using the graph deployed with the name "agent"
     assistant_id = "agent"
@@ -103,7 +107,7 @@ If you have a `LANGSMITH_API_KEY` set in your environment, you do not need to ex
     ```js
     import { Client } from "@langchain/langgraph-sdk";
 
-    // only set the apiUrl if you changed the default port when calling langgraph up
+    // only set the apiUrl if you changed the default port when calling langgraph dev
     const client = new Client();
     // Using the graph deployed with the name "agent"
     const assistantId = "agent";

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

@@ -7,17 +7,21 @@
 
 Make sure you have setup your app correctly, by creating a compiled graph, a `.env` file with any environment variables, and a `langgraph.json` config file that points to your environment file and compiled graph. See [here](https://langchain-ai.github.io/langgraph/cloud/deployment/setup/) for more detailed instructions.
 
-After you have your app setup, head into the directory with your `langgraph.json` file and call `langgraph up -c langgraph.json --watch` to start the API server in watch mode which means it will restart on code changes, which is ideal for local testing. If the API server start correctly you should see logs that look something like this:
+After you have your app setup, head into the directory with your `langgraph.json` file and call `langgraph dev` to start the API server in watch mode which means it will restart on code changes, which is ideal for local testing. If the API server start correctly you should see logs that look something like this:
 
-    Ready!
-    - API: http://localhost:8123
-    2024-06-26 19:20:41,056:INFO:uvicorn.access 127.0.0.1:44138 - "GET /ok HTTP/1.1" 200
+>    Ready!
+> 
+>    - API: [http://localhost:2024](http://localhost:2024/)
+>     
+>    - Docs: http://localhost:2024/docs
+>     
+>    - LangGraph Studio Web UI: https://smith.langchain.com/studio/?baseUrl=http://127.0.0.1:2024
 
 Read this [reference](https://langchain-ai.github.io/langgraph/cloud/reference/cli/#up) to learn about all the options for starting the API server.
 
 ## Access Studio
 
-Once you have successfully started the API server, you can access the studio by going to the following URL: `https://smith.langchain.com/studio/?baseUrl=http://127.0.0.1:8123` (see warning above if using Safari).
+Once you have successfully started the API server, you can access the studio by going to the following URL: `https://smith.langchain.com/studio/?baseUrl=http://127.0.0.1:2024` (see warning above if using Safari).
 
 If everything is working correctly you should see the studio show up looking something like this (with your graph diagram on the left hand side):
 

docs/docs/cloud/quick_start.md

@@ -208,7 +208,6 @@ export LANGSMITH_API_KEY=...
     ```js
     const { Client } = await import("@langchain/langgraph-sdk");
 
-    // only set the apiUrl if you changed the default port when calling langgraph up
     const client = new Client({ apiUrl: "your-deployment-url", apiKey: "your-langsmith-api-key" });
 
     const streamResponse = client.runs.stream(

docs/docs/tutorials/langgraph-platform/local-server.md

@@ -180,7 +180,7 @@ LangGraph Studio Web is a specialized UI that you can connect to LangGraph API s
     ```js
     const { Client } = await import("@langchain/langgraph-sdk");
 
-    // only set the apiUrl if you changed the default port when calling langgraph up
+    // only set the apiUrl if you changed the default port when calling langgraph dev
     const client = new Client({ apiUrl: "http://localhost:2024"});
 
     const streamResponse = client.runs.stream(