feat: Compute edges from tags rather than storing #500
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In dense graphs, there may be `O(node^2)` edges for tags with high connectivity. Storing the tags alone (`O(tags)`) allows for faster writes. We can further address dense graphs by using queries with similarity bounds and filters. Other changes: - refactor: Introduce `Link` as interface for `LinkTag` This allows non-tag based links to be added in the future. - refactor: remove unused code Future improvements - Further performance tuning of queries, including denormalization to allow for fewer queries during traversal. - Consider / experiment with single key queries rather than `IN`.
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cbornet reviewed Jun 18, 2024
cbornet reviewed Jun 18, 2024
cbornet reviewed Jun 18, 2024
cbornet reviewed Jun 18, 2024
cbornet reviewed Jun 18, 2024
cbornet reviewed Jun 18, 2024
cbornet reviewed Jun 18, 2024
kerinin reviewed Jun 18, 2024
libs/langchain/ragstack_langchain/graph_store/extractors/html_link_edge_extractor.py Outdated Show resolved Hide resolved
cbornet reviewed Jun 19, 2024
cbornet reviewed Jun 20, 2024
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In dense graphs, there may be
O(node^2)edges for tags with high connectivity. Storing the tags alone (O(tags)) allows for faster writes. We can further address dense graphs by using queries with similarity bounds and filters.Other changes:
Linkas interface forLinkTagThis allows non-tag based links to be added in the future.ragstack_langchainimportsFuture improvements
IN.