examples

Why we included this project

Notebooks are often where retrieval concepts finally click, and this collection from Pinecone has plenty of them to work through. It splits into production-ready sample applications under docs, kept current by Pinecone's engineers, and learning-focused notebooks in learn that the developer advocacy team maintains. The learn side moves through the retrieval workflow, from embedding pipelines and hybrid search on to reranking and retrieval-augmented generation, with each example tied to a real scenario and runnable directly in Google Colab. That makes it handy both as a guided introduction to vector databases and as a source of working snippets when you are putting together your own retrieval stack. Teams evaluating Pinecone, or vector databases in general, will get oriented faster here than by scraping together scattered blog posts.