Pinecone
Pinecone is a managed cloud vector database service for storing, indexing, and querying vector embeddings, including through similarity search.
Build Python Web Apps with Streamlit
Pinecone is a managed vector database service optimized for scalable similarity search over vector representations.
- How it is used
- Supports RAG applications by storing embedded knowledge-base chunks and retrieving relevant passages for an AI chatbot.
- How deep it goes
- Explains index configuration, ingestion, chunking, retrieval, and prompt augmentation, but defers broader operational detail.
- Examples
- Uses customer-support articles, a VectorStore class, an ingestion script, and a chatbot retrieving fountain-pen guidance.
- What you can do after
- Build it from scratch by configuring an index, ingesting text files, and connecting similarity retrieval to a chatbot.
Read how Build Python Web Apps with Streamlit explains Pinecone →
Software Testing with Generative AI
Pinecone is a managed cloud platform for creating and operating vector databases and similarity-search indexes.
- How it is used
- Supports rapid trials of vector-database-backed retrieval-augmented generation through Canopy.
- How deep it goes
- Explains cloud indexes, installation, credentials, upgrading, data upload, and querying, while deferring lower-level implementation control.
- Examples
- Uses environment variables, Canopy upload commands, Pinecone indexes, and booking user stories as test data.
- What you can do after
- Apply Pinecone through Canopy to create an index, upload custom data, and test retrieval against practical queries.
Read how Software Testing with Generative AI explains Pinecone →
Building Reliable AI Systems
Pinecone is a managed vector database service for storing and searching vector embeddings.
- How it is used
- Supplies managed vector storage and filtered retrieval for a health-care policy assistant.
- How deep it goes
- Works through document preparation, embedding, index setup, upsert, and querying, but does not explain Pinecone's infrastructure internals.
- Examples
- Uses Python listings for a health-care policy assistant that indexes policy chunks and searches them with optional filters.
- What you can do after
- Apply it via Pinecone's Python API to index embedded policy chunks and retrieve filtered context for answers.
Related concepts
- vector databasekind of · A vector database is a data-management system that stores and indexes numerical vector representations and supports retrieval through similarity or distance searches.
- Canopyused by · Canopy is a framework for building retrieval-augmented generation applications with Pinecone's cloud vector database services.
- NumPy arrayalternative to · A NumPy array, or ndarray, is a multidimensional array object with a defined shape and element data type, designed for efficient numerical computation.
- LangChainused by · LangChain is an open-source software framework for building applications that compose language models with prompts, data sources, tools, and other components.
- Chroma DBalternative to · Chroma is an open-source vector database for storing and querying embeddings and associated data, such as documents and metadata.
These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.