docs: Create how-to for setting up LangGraph app and how-to for deploying to LangGraph Cloud (#801)

* Create how-to for setting up LangGraph app and how-to for deploying to LangGraph Cloud.

* Fix spelling errors.

docs/docs/cloud/deployment/setup.md

@@ -0,0 +1,99 @@
+# How to Set Up a LangGraph Application for Deployment
+
+A LangGraph application must be configured with a [LangGraph API 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.
+
+After each step, an example file directory is provided to demonstrate how code can be organized.
+
+## Specify Dependencies
+
+Dependencies can optionally be specified in one of the following files: `pyproject.toml`, `setup.py`, or `requirements.txt`. If neither of these files is created, then dependencies can be specified later in the [LangGraph API configuration file](#create-langgraph-api-config).
+
+Example `requirements.txt` file:
+```
+langgraph
+langchain_openai
+```
+
+Example file directory:
+```
+my-app/
+|-- requirements.txt    # Python packages required for your graph
+```
+
+## Specify Environment Variables
+
+Environment variables can optionally be specified in a file (e.g. `.env`).
+
+Example `.env` file:
+```
+MY_ENV_VAR_1=foo
+MY_ENV_VAR_2=bar
+```
+
+Example file directory:
+```
+my-app/
+|-- requirements.txt
+|-- .env                # file with environment variables
+```
+
+## Define Graphs
+
+Implement your graphs! Graphs can be defined in a single file or multiple files. Make note of the variable names of each [CompiledGraph](../../../reference/graphs/#compiledgraph) to be included in the LangGraph application. The variable names will be used later when creating the [LangGraph API configuration file](../reference/cli.md#configuration-file).
+
+Example `openai_agent.py` file:
+```python
+from langchain_openai import ChatOpenAI
+from langgraph.graph import END, MessageGraph
+
+model = ChatOpenAI(temperature=0)
+
+graph_workflow = MessageGraph()
+
+graph_workflow.add_node("agent", model)
+graph_workflow.add_edge("agent", END)
+graph_workflow.set_entry_point("agent")
+
+agent = graph_workflow.compile()
+```
+
+Example file directory:
+```
+my-app/
+|-- requirements.txt
+|-- .env
+|-- openai_agent.py     # code for your graph
+|-- anthropic_agent.py  # code for your graph
+```
+
+## Create LangGraph API Config
+
+Create a [LangGraph API configuration file](../reference/cli.md#configuration-file) called `langgraph.json`. See the [LangGraph CLI reference](../reference/cli.md#configuration-file) for detailed explanations of each key in the JSON object of the configuration file.
+
+Example `langgraph.json` file:
+```json
+{
+    "dependencies": [
+        "./my-app"
+    ],
+    "graphs": {
+        "openai_agent": "./openai_agent.py:agent",
+        "anthropic_agent": "./anthropic_agent.py:agent"
+    },
+    "env": ".env"
+}
+```
+
+Example file directory:
+```
+my-app/
+|-- requirements.txt
+|-- .env
+|-- openai_agent.py
+|-- anthropic_agent.py
+|-- langgraph.json      # configuration file for LangGraph
+```
+
+## Upload to GitHub
+
+To deploy the LangGraph application to LangGraph Cloud, the code must be uploaded to a GitHub repository.