Slack Federated Search v0 #4962
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PR Summary
Introduces federated search capabilities by integrating Slack messages alongside document index search, running keyword-based Slack retrieval in parallel with main document search.
- Added new federated search module in
/onyx/context/search/federated/implementing Slack message search with parallel execution and source filtering - Added Pydantic models in
models.pyfor structured handling of Slack messages and elements - Modified
search_runner.pyto coordinate parallel execution of document and federated searches with source-based filtering - Slack search uses basic keyword matching which may limit effectiveness on complex queries
- Zero scoring of Slack results means they'll always appear after regular search results unless explicitly marked relevant
6 files reviewed, 3 comments
Edit PR Review Bot Settings | Greptile
Orbital-Web
commented
Jun 29, 2025
| @@ -115,34 +114,6 @@ def combine_retrieval_results( | |||
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| def get_query_embedding(query: str, db_session: Session) -> Embedding: | |||
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moved it into utils as I might play around with embedding the query and chunks in slack_search.py to score the chunks (if it's here, it'll lead to circular imports).
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Merged as part of #4969 (comment) |
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Description
Current apporach:
slack_retrievalin parallel withdoc_index_retrievalto get slack documentsNUM_FEDERATED_SECTIONSsections returned from federated search. The sections are sorted by score so the slack documents will always appear at the end as they have 0 score (unlesssection_relevance_listis provided, in which case sections marked not relevant will appear even lower)Notes:
How Has This Been Tested?
Locally, could write test cases
Backporting (check the box to trigger backport action)
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