- Added a new `DeleteConfirmationDialog` component for confirming deletions.
- Updated `KnowledgeDropdown` to include a loading state and improved user feedback during file operations.
- Enhanced the search page to support bulk deletion of documents with confirmation dialog.
- Integrated event dispatching for knowledge updates after file operations.
- Refactored various components for better readability and maintainability.
This commit updates the ingestion flow to include user metadata such as owner ID, name, and email, enhancing the context for downstream services. It also refines the handling of tweaks in the LangflowFileService to incorporate this metadata, ensuring better tracking and clarity in the ingestion process. These changes align with best practices for robust async development and improve the overall functionality of the ingestion flow.
This commit simplifies the handling of the JWT token in the upload_user_file and run_ingestion functions by removing unnecessary lines and ensuring the token is passed correctly to downstream services. This change enhances code readability and maintains the focus on robust async coding practices and well-documented code.
This commit introduces a new combined endpoint for uploading files and running ingestion in Langflow. The frontend component is updated to utilize this endpoint, streamlining the process by eliminating separate upload and ingestion calls. The response structure is adjusted to include deletion status and other relevant information, enhancing error handling and logging practices throughout the codebase.
This commit replaces the print statement for error traceback with a structured logging approach using the logger. This change enhances error visibility and aligns with best practices for robust and well-documented async code.
This commit adds functionality to retrieve and set ingestion-specific defaults from the Langflow API based on the flow configuration. It includes error handling for the API call and updates the settings with values for chunk size, chunk overlap, separator, and embedding model based on the flow data. This enhancement improves the flexibility and robustness of the ingestion process.
