AI Agent Foundation

LangChain LangGraph

Module 1 Module 2 Module 3 Module 4 Module 5 Module 6

Module 6 · Production

1 6-1 Creating

2 6-2 Connecting

3 6-3 Double Texting

4 6-4 Assistant

Home›LangGraph›Module 6 · Production›6-1 Creating · Notebook

📓 Notebook 📖 Explained

LangGraph

Module 1 Module 2 Module 3 Module 4 Module 5 Module 6

Creating a deployment

Let's create a deployment of the task_maistro app that we created in module 5.

Code structure

The following information should be provided to create a LangGraph Platform deployment:

• A LangGraph API Configuration file - langgraph.json
• The graphs that implement the logic of the application - e.g., task_maistro.py
• A file that specifies dependencies required to run the application - requirements.txt
• Supply environment variables needed for the application to run - .env or docker-compose.yml

We have this already in the module-6/deployment directory!

CLI

The LangGraph CLI is a command-line interface for creating a LangGraph Platform deployment.

from dotenv import load_dotenv
load_dotenv()

%%capture --no-stderr
%pip install -U langgraph-cli

To create a self-hosted deployment, we'll follow a few steps.

Build Docker Image for LangGraph Server

We first use the langgraph CLI to create a Docker image for the LangGraph Server.

This will package our graph and dependencies into a Docker image.

A Docker image is a template for a Docker container that contains the code and dependencies required to run the application.

Ensure that Docker is installed and then run the following command to create the Docker image, my-image:

$ cd module-6/deployment
$ langgraph build -t my-image

Set Up Redis and PostgreSQL

If you already have Redis and PostgreSQL running (e.g., locally or on other servers), then create and run the LangGraph Server container by itself with the URIs for Redis and PostgreSQL:

docker run \
    --env-file .env \
    -p 8123:8000 \
    -e REDIS_URI="foo" \
    -e DATABASE_URI="bar" \
    -e LANGSMITH_API_KEY="baz" \
    my-image

Alternatively, you can use the provided docker-compose.yml file to create three separate containers based on the services defined:

• langgraph-redis: Creates a new container using the official Redis image.
• langgraph-postgres: Creates a new container using the official Postgres image.
• langgraph-api: Creates a new container using your pre-built image.

Simply copy the docker-compose-example.yml and add the following environment variables to run the deployed task_maistro app:

• IMAGE_NAME (e.g., my-image)
• LANGSMITH_API_KEY
• DEEPSEEK_API_KEY

Then, launch the deployment!

$ cd module-6/deployment
$ docker compose up