2.3.32 Satellite: LangFlow
Handle:
langflow
URL: http://localhost:34291
Integration author: @ZacharyKehlGEAppliances
Langflow is a low-code app builder for RAG and multi-agent AI applications. It’s Python-based and agnostic to any model, API, or database.
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LangFlow is a powerful visual workflow builder, similar to Dify, Flowise, and omnichain. It’s Python-based and agnostic to any model, API, or database.
# [Optional] Pre-pull the image
harbor pull langflow
# Start the service [--open is optional, to auto open in browser]
harbor up langflow --openIf everything is expected, you should see LangFlow UI open in your browser. See troubleshooting if you encounter any issues.
Most of the configuration/connections are done in the LangFlow own UI, including the connections to other services included in Harbor.
When running alongside other services in Harbor - use their internal URLs. For example:
# Ollama URL for the LangFlow
# Default is http://ollama:11434
harbor url -i ollamaHere's an example of a simple workflow that does QA over Harbor's CLI reference:
Other than that, LangFlow is an extremely feature-rich tool with a lot of capabilities, please see the official documentation to get started.
Official environment variables reference. To set them, see Harbor's environment configuration guide.
# Example: see DO_NOT_TRACK env variable value
harbor env langflow DO_NOT_TRACK
# Example: set LANGFLOW_SUPERUSER_PASSWORD env variable
harbor env langflow LANGFLOW_SUPERUSER_PASSWORD spi-4523l-kn-LK99Apart from that, you can configure the following via harbor config with the following options supported:
# The port on the host machine to access
# the LangFlow service when it is running
LANGFLOW_HOST_PORT
# The Docker image to use for LangFlow service
LANGFLOW_IMAGE
# The tag of the Docker image to use for LangFlow service
LANGFLOW_VERSION
# Location of the workspace directory on the host machine,
# relative to $(harbor home), but can be global as well
LANGFLOW_WORKSPACE