Ftrea

8 ms·

1. 1.▲
   by Ftrea 11mo ago

   This is the sanity check we needed. We don't have a benchmark yet necessitating complex graph architectures. We will stick to 'Proven Stuffs' first: A solid Hybrid Search (Vector + Keyword) baseline. We'll collect usage
2. 2.▲
   by Ftrea 11mo ago

   Thanks for the tips. We are strictly doing offline processing (docs are already converted to Markdown stored in DB) to avoid any live OCR latency. Also 100% agreed on filtering—we plan to use metadata/keyword filters (Lucene style) to
3. 3.▲
   by Ftrea 11mo ago

   Agreed. Pure in-memory is too risky for us given the persistence requirements and monthly updates. We are definitely going with a 'proper' DB (likely Postgres+pgvector or Weaviate) to handle the state and updates reliably.
4. 4.▲
   by Ftrea 11mo ago

   This is extremely helpful. Our docs are indeed small (1-2 pages mostly), so distinct chunking might not even be needed—maybe one vector per doc or page. Since we are already on Postgres, pgvector + tsvector (for hybrid search) seems like th
5. 5.▲
   Ask HN: How would you architect a RAG system for 10M+ documents today?

   23 points by Ftrea 11mo ago|9 comments