I love reading battlefield notes like this for RAG/search systems. Anyone shooting for useful output is going to hit the same pain points but each article like this has a different set of solutions.
I’m leaning on OpenAI for my embedding needs but will be trying llama-server in the future. I stuck with Postgres because it was easy to run it on my Dokku installation. Great to know sqlite is an option there too. My corpus is too small for Postgres to elect to use an index so it’s running the full table scans that sqlite would. For seeding I use a msgpack file and ship that with the code when deploying.
This is my site: https://customelon.com (niche need of tariff and excise information for shipping to The Bahamas)
It’s built with ASP.NET, Postgres/pgvector, and OpenAI embedding/LLMs. Ingestion is via Textract with a lot of chunking helpers to preserve context layered on top.
alt Hacker News
I love reading battlefield notes like this for RAG/search systems. Anyone shooting for useful output is going to hit the same pain points but each article like this has a different set of solutions.
I’m leaning on OpenAI for my embedding needs but will be trying llama-server in the future. I stuck with Postgres because it was easy to run it on my Dokku installation. Great to know sqlite is an option there too. My corpus is too small for Postgres to elect to use an index so it’s running the full table scans that sqlite would. For seeding I use a msgpack file and ship that with the code when deploying.
This is my site: https://customelon.com (niche need of tariff and excise information for shipping to The Bahamas)
It’s built with ASP.NET, Postgres/pgvector, and OpenAI embedding/LLMs. Ingestion is via Textract with a lot of chunking helpers to preserve context layered on top.
Again, great article.