langflow-lib

This is a collection of custom components for Langflow.

Components

General

Component	Description
Data If-Else	Routes a Data object to a corresponding output based on a boolean expression.
First row	Takes the first row of a Dataframe and converts it to a Data object
JSON to Data	Converts a JSON string to a Data object.
Logger	Logs the passed in object and then passes it on unchanged. Useful for debugging.

Confluence

Component	Description
Confluence Get Page	Fetches the content of a Confluence page by its page ID.
Confluence Search Pages	Returns the matching pages in Confluence based on the provided CQL search query.
Confluence Update Page	Updates the content of a Confluence page.

GitHub

Component	Description
Github Get PR Changes	Returns the title, description, file names and the diffs of a pull request from a GitHub repository.

Jira

Component	Description
Jira Add comment	Adds a comment to a Jira issue.
Jira Add label to issue	Adds a label to a Jira issue.
Jira Search Issues	Returns issues in Jira based on the provided JQL query.

How to Use

Via prebuilt docker image

You can use the prebuilt docker image that is based on the official langflow image but include the ClearPoint langflow-lib and the required dependencies.

docker run --rm -it -p 7860:7860 ghcr.io/clearpointnz/langflow-lib:v0.2.0

Via Bundle URLs

Components can be pulled into your Langflow instance by setting the LANGFLOW_BUNDLE_URLS environment variable to the URL of this repository.

For example:

docker run --rm -it -p 7860:7860 -e LANGFLOW_BUNDLE_URLS="https://github.com/ClearPointNZ/langflow-lib" langflowai/langflow

Note: The command above will not persist any workflows or configuration. Use for testing only

Many of these components require additional Python packages to be installed. These will need to be available in your Langflow instance. See the comps_requirements.txt file for a list of dependencies.

Via custom docker image

Alternatively you can build a custom docker container with the dependencies and the components installed. For example:

FROM langflowai/langflow:latest

# add 3rd party libaries
COPY comps_requirements.txt /tmp/requirements.txt

RUN /app/.venv/bin/python -m ensurepip --upgrade && \
    /app/.venv/bin/python -m pip install --upgrade pip && \
    /app/.venv/bin/python -m pip install wheel 

RUN /app/.venv/bin/python -m pip install --no-cache-dir -r /tmp/requirements.txt

# add components
COPY components/ /app/components/
ENV LANGFLOW_COMPONENTS_PATH=/app/components

CMD ["langflow", "run"]

Development

You can use the included Docker compose file to build and run langflow with the components for testing and development. It includes creation of a volume for persisting data and configuration.