Create quick start page.

docs/docs/deploy/quick_start.md

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+# Quick Start
+This quick start guide will cover how to develop a LangGraph Deploy API, run it locally in Docker, and call the APIs to invoke a graph.
+
+Alternatively, clone or fork the [`langgraph/example`](https://github.com/langchain-ai/langgraph-example) GitHub repository and follow the instructions in the `README`.
+
+## Develop
+1. Create a new application with the following directory and files:
+
+        <my-app>/
+        |-- agent.py            # code for your LangGraph agent
+        |-- requirements.txt    # Python packages required for your graph
+        |-- langgraph.json      # configuration file for LangGraph
+        |-- .env                # environment files with API keys
+
+2. The `agent.py` file should contain the following Python code for defining a simple graph: 
+
+    ```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")
+
+    graph = graph_workflow.compile()
+    ```
+
+3. The `requirements.txt` file should contain the following dependencies:
+
+        langgraph
+        langchain_openai
+
+4. The `langgraph.json` file should contain the following JSON object:
+
+    ```json
+    {
+        "dependencies": ["."],
+        "graphs": {
+            "agent": "./agent.py:graph"
+        },
+        "env": ".env"
+    }
+    ```
+
+    Learn more about the LangGraph CLI configuration file [here](cli.md#configuration-file).
+
+5. The `.env` file should contain the environment variables:
+
+        OPENAI_API_KEY=<add your key here>
+        LANGGRAPH_AUTH_TYPE=noop
+
+    !!! warning "Disable Authentication"
+        When testing locally, set `LANGGRAPH_AUTH_TYPE` to `noop` to disable authentication.
+
+## Run Locally
+1. Install the [LangGraph CLI](cli.md#installation).
+
+2. Run the following command to start the API server in Docker:
+
+        langgraph up -c langgraph.json
+
+3. The API server is now running at `http://localhost:8123`. Navigate to [`http://localhost:8123/docs`](http://localhost:8123/docs) to view the API docs.
+
+## Call APIs
+
+1. Create an assistant.
+
+    ```python
+    pass
+    ```
+
+2. Create a thread.
+
+    ```python
+    pass
+    ```
+
+3. Execute a run.
+
+    ```python
+    pass
+    ```