How to Build a RAG System with pgvector and LangChain: The Production Architecture
Most production AI failures are not model failures. They are retrieval failures.
If you want to understand why your Retrieval-Augmented Generation (RAG) system is hallucinating, stop looking at your p
digitpatrox.hashnode.dev6 min read
Digit Patrox
Transforming to New Generation
One quick tip I totally left out of the ingestion section: watch your API rate limits.
When you first move from the 'Toy' stage to a real database, it's really easy to just loop through 500k chunks and send them to OpenAI or Cohere. You will hit a 429 rate limit error almost immediately. Save yourself the headache and set up a simple queue with exponential backoff before you do your first massive ingestion run