This new feature will ensure that any changes made to a template will be
automatically reflected in all nodes related to that template. This will
save time and effort, as users will no longer need to manually update
each node individually. Additionally, this feature will help to reduce
the risk of errors and inconsistencies across nodes and flows.
To implement this feature, I have created a new function that checks the
last template related to each node and compares it with the current
template version. If there is a difference, the node will be
automatically updated with the latest version of the template.
refactor(langflow): set advanced flag to False for LLMFrontendNode class' api key field
feat(langflow): add show flag to LLMFrontendNode class' model_kwargs field
refactor(langflow): set advanced flag to False and show flag to True for LLMFrontendNode class' model_name and temperature fields
This commit modifies run.py to use type hinting and avoid circular imports by changing the import for NotEnoughElementsException to use type: ignore. Specifically, the code now imports from chromadb.errors instead of chromadb.exceptions.
This commit refactors the code for the ImportModal component to use hooks like useState and useContext, resulting in improved readability and maintainability. It also adds functionality to load prebuilt examples and handle local file uploads.
This pull request adds a new feature to the flow editor that allows
users to easily import example flows from the
[logspace-ai/langflow_examples](https://github.com/logspace-ai/langflow_examples)
repository on GitHub. The feature is accessible via the import example
button
Clicking on the "Import Examples" button opens a dialog box that
displays a list of available example flows from the GitHub repository.
Users can select one example to import, and the flow editor will
automatically add the selected flow to the user's current project.
This feature saves users time and effort by providing a convenient way
to explore and utilize pre-built flows.
Additionally, this feature promotes collaboration and community
involvement by encouraging users to contribute their own flows to the
repository for others to use and benefit from.
