Posts

#4141 PostgreSQL Database for RAG and KG

-
#4141  PostgreSQL Database for RAG and KG #4141  Discuss  PostgreSQL  database for RAG PostgreSQL has evolved from a traditional relational database into a powerhouse for Retrieval-Augmented Generation (RAG) . While specialized vector databases (like Pinecone or Milvus) exist, many developers are sticking with Postgres because it allows them to keep their structured data and vector embeddings in the same place. Here is how Postgres handles the RAG workflow and why it’s becoming a top choice. 1. The Secret Sauce: pgvector Standard Postgres doesn't "speak" vectors out of the box. The pgvector extension is the industry standard that adds vector capabilities. It allows you to: Store embeddings (arrays of numbers representing text/images) in a VECTOR column. Perform similarity searches using distances like Cosine Distance , L2 Distance , or Inner Product . Query your vectors using standard SQL. Example Query SELECT content, metadata FROM documents ORDER BY embed...
Post a Comment
Read more

#4140 Knowledge Graph Multi-Step Queries

-
#4140 Knowledge Graph Multi-Step Queries #4140  Describe the various Retrieval Augmented Generation (RAG) strategies applied within Python Implementing Retrieval-Augmented Generation (RAG) in Python has evolved from simple "vector search" to a sophisticated ecosystem of multi-stage pipelines. In 2026, the strategy you choose depends on the complexity of your data and the accuracy required. The various RAG strategies are generally categorized by where they intervene in the pipeline: Pre-Retrieval , Retrieval , and Post-Retrieval . 1. Pre-Retrieval & Ingestion Strategies These focus on how data is prepared before a user ever asks a question. Recursive Character Splitting: Instead of fixed-length chunks, Python libraries like LangChain use recursive splitters that look for natural boundaries (paragraphs, then sentences) to keep context intact. Semantic Chunking: Using models (like semantic-chunkers ) to split text based on changes in meaning rather than character count. H...
Post a Comment
Read more