Application Structure
Application Structure
:::info[Prerequisites]
Overview
A LangGraph application consists of one or more graphs, a LangGraph API Configuration file (langgraph.json), a file that specifies dependencies, and an optional .env file that specifies environment variables.
This guide shows a typical structure for a LangGraph application and shows how the required information to deploy a LangGraph application using the LangGraph Platform is specified.
Key Concepts
To deploy using the LangGraph Platform, the following information should be provided:
- A LangGraph API Configuration file (
langgraph.json) that specifies the dependencies, graphs, environment variables to use for the application. - The graphs that implement the logic of the application.
- A file that specifies dependencies required to run the application.
- Environment variable that are required for the application to run.
File Structure
Below are examples of directory structures for Python and JavaScript applications:
=== JS (package.json)
my-app/
βββ src # all project code lies within here
β βββ utils # optional utilities for your graph
β β βββ tools.ts # tools for your graph
β β βββ nodes.ts # node functions for your graph
β β βββ state.ts # state definition of your graph
β βββ agent.ts # code for constructing your graph
βββ package.json # package dependencies
βββ .env # environment variables
βββ langgraph.json # configuration file for LangGraph
=== Python (requirements.txt)
my-app/
βββ my_agent # all project code lies within here
β βββ utils # utilities for your graph
β β βββ __init__.py
β β βββ tools.py # tools for your graph
β β βββ nodes.py # node functions for your graph
β β βββ state.py # state definition of your graph
β βββ requirements.txt # package dependencies
β βββ __init__.py
β βββ agent.py # code for constructing your graph
βββ .env # environment variables
βββ langgraph.json # configuration file for LangGraph
=== Python (pyproject.toml)
my-app/
βββ my_agent # all project code lies within here
β βββ utils # utilities for your graph
β β βββ __init__.py
β β βββ tools.py # tools for your graph
β β βββ nodes.py # node functions for your graph
β β βββ state.py # state definition of your graph
β βββ __init__.py
β βββ agent.py # code for constructing your graph
βββ .env # environment variables
βββ langgraph.json # configuration file for LangGraph
βββ pyproject.toml # dependencies for your project
:::note
The directory structure of a LangGraph application can vary depending on the programming language and the package manager used.
Configuration File
The langgraph.json file is a JSON file that specifies the dependencies, graphs, environment variables, and other settings required to deploy a LangGraph application.
The file supports specification of the following information:
| Key | Description |
|---|---|
dependencies | Required. Array of dependencies for LangGraph API server. Dependencies can be one of the following: (1) ".", which will look for local Python packages, (2) pyproject.toml, setup.py or requirements.txt in the app directory "./local_package", or (3) a package name. |
graphs | Required. Mapping from graph ID to path where the compiled graph or a function that makes a graph is defined. Example:
|
env | Path to .env file or a mapping from environment variable to its value. |
node_version | Defaults to 20. |
dockerfile_lines | Array of additional lines to add to Dockerfile following the import from parent image. |
:::tip
The LangGraph CLI defaults to using the configuration file langgraph.json in the current directory.
Examples
=== JavaScript
- The dependencies will be loaded from a dependency file in the local directory (e.g.,
package.json). - A single graph will be loaded from the file
./your_package/your_file.jswith the functionagent. - The environment variable
OPENAI_API_KEYis set inline.
{
"dependencies": [
"."
],
"graphs": {
"my_agent": "./your_package/your_file.js:agent"
},
"env": {
"OPENAI_API_KEY": "secret-key"
}
}
=== Python
- The dependencies involve a custom local package and the
langchain_openaipackage. - A single graph will be loaded from the file
./your_package/your_file.pywith the variablevariable. - The environment variables are loaded from the
.envfile.
{
"dependencies": [
"langchain_openai",
"./your_package"
],
"graphs": {
"my_agent": "./your_package/your_file.py:agent"
},
"env": "./.env"
}
Dependencies
A LangGraph application may depend on other Python packages or JavaScript libraries (depending on the programming language in which the application is written).
You will generally need to specify the following information for dependencies to be set up correctly:
- A file in the directory that specifies the dependencies (e.g.,
requirements.txt,pyproject.toml, orpackage.json). - A
dependencieskey in the LangGraph configuration file that specifies the dependencies required to run the LangGraph application. - Any additional binaries or system libraries can be specified using
dockerfile_lineskey in the LangGraph configuration file.
Graphs
Use the graphs key in the LangGraph configuration file to specify which graphs will be available in the deployed LangGraph application.
You can specify one or more graphs in the configuration file. Each graph is identified by a name (which should be unique) and a path for either: (1) the compiled graph or (2) a function that makes a graph is defined.
Environment Variables
If you're working with a deployed LangGraph application locally, you can configure environment variables in the env key of the LangGraph configuration file.
For a production deployment, you will typically want to configure the environment variables in the deployment environment.
Related
Please see the following resources for more information:
- How-to guides for Application Structure.