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Just had a look at the code. It’s a cool project that’s clearly had a lot of thought put into it. If the devs are still around, I’d love to hear about your exp
by darkteflon 3y ago
Just had a look at the code. It’s a cool project that’s clearly had a lot of thought put into it.
If the devs are still around, I’d love to hear about your experiences with embeddings.
- 110 3y ago1. One of the reasons we created Khoj was being able to do natural language search with embeddings generated offline using open-source models! 2. We don't use any vector datastores (yet). You can do a lot in memory, it's faster and it does exact matches (no KNN, approx matching) Feel free to ask if you were looking for something more specific?
- darkteflon 3y agoThank you! I’d love to hear more about your experiences with: 1. content / question vector mismatch 2. what types of embedding you experimented with storing per-chunk (text only? Hypothetical question? Metadata?) 3. choice of embeddings model (eg OpenAI vs instructorEmbeddings or an alternative from the MTEB leaderboard) It’s a great project, going to have a deeper dig today.