WIP: Feature Semantic Search #528
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travolin
commented
Nov 5, 2024
•
travolin
commented
- Add vector embedding table to store document embeddings
- Add model to calculate document embeddings
- Add search query embedding distance check and update document boosts accordingly
- Move embeddings into their own queue
- Merge with new GUI updates
added 14 commits
November 4, 2024 17:21
- Add sqlite plugin and table for embeddings - Add embedding model access via candle - Add embedding model to state - Add embeddings when documents are added and updated (and delete when deleted) - Embed query strings and check distance against vector embedding store. - Use query embedding distance calculate document boosts
- whisper rs conflicts with candle library - will be transitioning to use candle instead of whisper
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