Fix: empty HTML content not always detected in _process_html_content#42
Open
dar326 wants to merge 2 commits intosentient-agi:mainfrom
Open
Fix: empty HTML content not always detected in _process_html_content#42dar326 wants to merge 2 commits intosentient-agi:mainfrom
dar326 wants to merge 2 commits intosentient-agi:mainfrom
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
1 participant
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
I have encountered some scenarios where attempts to check for empty html content in the _process_html_content function in src/opendeepsearch/context_building/process_sources_pro.py are failing. If the html content is not an empty string but consists solely of white space, the html content will continue to be processed. This causes a bug downstream where embeddings for an empty documents list are requested and reranking fails due to an invalid matrix multiplication attempt between the query embeddings and document embeddings.