How to Set Up a LangGraph Application for Deployment¶
A LangGraph application must be configured with a LangGraph API 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 using pyproject.toml to define your package's dependencies. If you prefer using requirements.txt for dependency management, check out this how-to guide.
The final repo structure will look something like this:
my-app/
├── my_agent # all project code lies within here
│ ├── __init__.py
│ └── agent.py # code for your graph
│-- .env # environment variables
│-- langgraph.json # configuration file for LangGraph
└── pyproject.toml # dependencies for your project
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 none of these files is created, then dependencies can be specified later in the LangGraph API configuration file.
Example pyproject.toml file:
[tool.poetry]
name = "my-agent"
version = "0.0.1"
description = "An excellent agent build for LangGraph cloud."
authors = ["Polly the parrot <1223+polly@users.noreply.github.com>"]
license = "MIT"
readme = "README.md"
[tool.poetry.dependencies]
python = ">=3.9.0,<3.13"
langgraph = "^0.1.0"
langchain-fireworks = "^0.1.3"
[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"
Example file directory:
my-app/
├── my_agent
│ ├── __init__.py
│ └── agent.py
└── pyproject.toml # Python packages required for your graph
Specify Environment Variables¶
Environment variables can optionally be specified in a file (e.g. .env). See the Environment Variables reference to configure additional variables for a deployment.
Example .env file:
Example file directory:
my-app/
├── my_agent
│ ├── __init__.py
│ └── agent.py
|-- .env # file with environment variables
└── pyproject.toml
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 to be included in the LangGraph application. The variable names will be used later when creating the LangGraph API configuration file.
Example agent.py file:
# my_agent/agent.py
from langchain_fireworks import ChatFireworks
from langgraph.graph import END, StateGraph, add_messages
from typing_extensions import TypedDict, Annotated
model = ChatFireworks(model="accounts/fireworks/models/firefunction-v2", temperature=0)
class State(TypedDict):
messages: Annotated[list, add_messages]
graph_workflow = StateGraph(State)
graph_workflow.add_node("agent", model)
graph_workflow.add_edge("agent", END)
graph_workflow.set_entry_point("agent")
agent = graph_workflow.compile()
Assign CompiledGraph to Variable
The build process for LangGraph Cloud requires that the CompiledGraph object be assigned to a variable at the top-level of a Python module.
Example file directory:
my-app/
├── my_agent
│ ├── __init__.py
│ └── agent.py # code for your graph
|-- .env
└── pyproject.toml
Create LangGraph API Config¶
Create a LangGraph API configuration file called langgraph.json. See the LangGraph CLI reference for detailed explanations of each key in the JSON object of the configuration file.
Example langgraph.json file:
{
"dependencies": ["."],
"graphs": {
"my_fantastic_agent": "./my_agent/agent.py:agent"
},
"env": "./.env"
}
Note that the variable name of the CompiledGraph appears at the end of the value of each subkey in the top-level graphs key (i.e. :<variable_name>).
Example file directory:
my-app/
├── my_agent
│ ├── __init__.py
│ └── agent.py # code for your graph
│-- .env
│-- langgraph.json # configuration file for LangGraph
└── pyproject.toml
Upload to GitHub¶
To deploy the LangGraph application to LangGraph Cloud, the code must be uploaded to a GitHub repository.
Next¶
After you setup your repo, it's time to deploy your app.