pinecone-io/examples resource

Health v2 · maintenance only

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Adoption not part of the score

3037 stars · 1071 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A collection of Jupyter Notebooks and sample applications from Pinecone for learning vector databases and common AI patterns like RAG and semantic search. It includes production-ready examples and learning-oriented notebooks maintained by Pinecone's Developer Advocacy team.

Use cases

• learn how to use a vector database for semantic search
• build a RAG pipeline example with jupyter notebooks
• hands-on tutorials for llm applications with embeddings
• sample code for semantic search over documents
• learn vector search patterns for ai agents
• experiment with rag in google colab

When to choose

• you want runnable notebooks to learn Pinecone and vector search concepts
• you need reference implementations of RAG and semantic search patterns
• you are evaluating how to integrate a vector database into an AI app

When to avoid

• you need a production vector database service itself rather than examples
• you want a maintained SDK or library instead of educational notebooks
• you use a different vector database and don't want Pinecone-specific code

Facets

learning-resource · maturity active

vector-database rag search-engine machine-learning nlp artificial-intelligence large-language-models databases tutorials python jvm jupyter-notebooks pinecone vector-search semantic-search sample-applications developer-advocacy llm retrieval-augmented-generation search

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