Deploy Langflow on Docker
Running applications in Docker containers ensures consistent behavior across different systems and eliminates dependency conflicts.
You can use the Langflow Docker image to start a Langflow container.
This guide demonstrates several ways to deploy Langflow with Docker and Docker Compose:
- Quickstart: Start a Langflow container with default values.
- Use Docker Compose: Clone the Langflow repo, and then use Docker Compose to build the Langflow Docker container. This option provides more control over the configuration, including a persistent PostgreSQL database service, while still using the base Langflow Docker image.
- Create a custom flow image: Use a Dockerfile to package a flow as a Docker image.
- Create a custom Langflow image: Use a Dockerfile to package a custom Langflow Docker image that includes your own code, custom dependencies, or other modifications.
Quickstart: Start a Langflow container with default values
With Docker installed and running on your system, run the following command:
_10docker run -p 7860:7860 langflowai/langflow:latest
Then, access Langflow at http://localhost:7860/
.
This container runs a pre-built Docker image with default settings. For more control over the configuration, see Clone the repo and run the Langflow Docker container.
Clone the repo and run the Langflow Docker container
Cloning the Langflow repository and using Docker Compose gives you more control over your configuration, allowing you to customize environment variables, use a persistent PostgreSQL database service (instead of the default SQLite database), and include custom dependencies.
The default deployment with Docker Compose includes the following:
- Langflow service: Runs the latest Langflow image with PostgreSQL as the database.
- PostgreSQL service: Provides persistent data storage for flows, users, and settings.
- Persistent volumes: Ensures your data survives container restarts.
The complete Docker Compose configuration is available in docker_example/docker-compose.yml
.
-
Clone the Langflow repository:
_10git clone https://github.com/langflow-ai/langflow.git -
Navigate to the
docker_example
directory:_10cd langflow/docker_example -
Run the Docker Compose file:
_10docker compose up -
Access Langflow at
http://localhost:7860/
.
Customize your deployment
You can customize the Docker Compose configuration to fit your specific deployment.
For example, to configure the container's database credentials using a .env
file, do the following:
-
Create a
.env
file with your database credentials in the same directory asdocker-compose.yml
:_10# Database credentials_10POSTGRES_USER=myuser_10POSTGRES_PASSWORD=mypassword_10POSTGRES_DB=langflow_10_10# Langflow configuration_10LANGFLOW_DATABASE_URL=postgresql://myuser:mypassword@postgres:5432/langflow_10LANGFLOW_CONFIG_DIR=/app/langflow -
Modify the
docker-compose.yml
file to reference the.env
file for both thelangflow
andpostgres
services:_10services:_10langflow:_10environment:_10- LANGFLOW_DATABASE_URL=${LANGFLOW_DATABASE_URL}_10- LANGFLOW_CONFIG_DIR=${LANGFLOW_CONFIG_DIR}_10postgres:_10environment:_10- POSTGRES_USER=${POSTGRES_USER}_10- POSTGRES_PASSWORD=${POSTGRES_PASSWORD}_10- POSTGRES_DB=${POSTGRES_DB}
For a complete list of available environment variables, see Langflow environment variables.
For more customization options, see Customize the Langflow Docker image with your own code.
Package your flow as a Docker image
This section shows you how to create a Dockerfile that builds a Docker image containing your Langflow flow. This approach is useful when you want to distribute a specific flow as a standalone container or deploy it to environments like Kubernetes.
Unlike the previous sections that use pre-built images, this method builds a custom image with your flow embedded inside it.
-
Create a project directory, and change directory into it.
_10mkdir langflow-custom && cd langflow-custom -
Add your flow's JSON file to the directory. You can download an example, or use your own:
_10# Download an example flow_10wget https://raw.githubusercontent.com/langflow-ai/langflow-helm-charts/refs/heads/main/examples/flows/basic-prompting-hello-world.json_10_10# Or copy your own flow file_10cp /path/to/your/flow.json . -
Create a Dockerfile to build your custom image:
_10FROM langflowai/langflow:latest_10RUN mkdir /app/flows_10COPY ./*.json /app/flows/_10ENV LANGFLOW_LOAD_FLOWS_PATH=/app/flows
This Dockerfile uses the official Langflow image as the base, creates a directory for your flows, copies your JSON flow files into the directory, and sets the environment variable to tell Langflow where to find the flows.
-
Build and test your custom image:
_10docker build -t myuser/langflow-custom:1.0.0 ._10docker run -p 7860:7860 myuser/langflow-custom:1.0.0 -
Push your image to Docker Hub (optional):
_10docker push myuser/langflow-custom:1.0.0
Your custom image now contains your flow and can be deployed anywhere Docker runs. For Kubernetes deployment, see Deploy the Langflow production environment on Kubernetes.
Customize the Langflow Docker image with your own code
While the previous section showed how to package a flow with a Docker image, this section shows how to customize the Langflow application itself. This is useful when you need to add custom Python packages or dependencies, modify Langflow's configuration or settings, include custom components or tools, or add your own code to extend Langflow's functionality.
This example demonstrates how to customize the Message History component, but the same approach can be used for any code modifications.
_27FROM langflowai/langflow:latest_27_27# Set working directory_27WORKDIR /app_27_27# Copy your modified memory component_27COPY src/backend/base/langflow/components/helpers/memory.py /tmp/memory.py_27_27# Find the site-packages directory where langflow is installed_27RUN python -c "import site; print(site.getsitepackages()[0])" > /tmp/site_packages.txt_27_27# Replace the file in the site-packages location_27RUN SITE_PACKAGES=$(cat /tmp/site_packages.txt) && \_27 echo "Site packages at: $SITE_PACKAGES" && \_27 mkdir -p "$SITE_PACKAGES/langflow/components/helpers" && \_27 cp /tmp/memory.py "$SITE_PACKAGES/langflow/components/helpers/"_27_27# Clear Python cache in the site-packages directory only_27RUN SITE_PACKAGES=$(cat /tmp/site_packages.txt) && \_27 find "$SITE_PACKAGES" -name "*.pyc" -delete && \_27 find "$SITE_PACKAGES" -name "__pycache__" -type d -exec rm -rf {} +_27_27# Expose the default Langflow port_27EXPOSE 7860_27_27# Command to run Langflow_27CMD ["python", "-m", "langflow", "run", "--host", "0.0.0.0", "--port", "7860"]
To use this custom Dockerfile, do the following:
-
Create a directory for your custom Langflow setup:
_10mkdir langflow-custom && cd langflow-custom -
Create the necessary directory structure for your custom code. In this example, Langflow expects
memory.py
to exist in the/helpers
directory, so you create a directory in that location._10mkdir -p src/backend/base/langflow/components/helpers -
Place your modified
memory.py
file in the/helpers
directory. -
Create a new file named
Dockerfile
in yourlangflow-custom
directory, and then copy the Dockerfile contents shown above into it. -
Build and run the image:
_10docker build -t myuser/langflow-custom:1.0.0 ._10docker run -p 7860:7860 myuser/langflow-custom:1.0.0
This approach can be adapted for any other components or custom code you want to add to Langflow by modifying the file paths and component names.