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LlamaIndex

As explained in The Art of AI Product Development

An open-source software framework for connecting language-model applications with external data and computational capabilities.

LlamaIndex is an open-source framework for building search and retrieval applications around language models. It provides a simple interface for querying different models and retrieving relevant documents. section 9.2.3

For agent workflows, LlamaIndex offers a more focused alternative to broader frameworks such as LangChain, especially when applications process large amounts of data. The trade-off is strategic: abstractions can accelerate prototypes but may add overhead or lock-in, so teams should compare the framework with a custom implementation. section 9.2.3

Document retrieval workflow

An application can query a language model through LlamaIndex and retrieve relevant documents from a large data collection, supporting a search-oriented agent or workflow. section 9.2.3

How The Art of AI Product Development covers it

How deep it goes
Defines the framework’s retrieval role and trade-offs but does not explain implementation internals.
Examples
Uses querying different language models and retrieving relevant documents from large data collections.
What you can do after
Build search and retrieval applications that query language models and return relevant documents.
How it connects
Connects agents, language models, document retrieval, and framework abstraction.

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This explainer was generated by Manning's knowledge graph from the text of The Art of AI Product Development. The section links point to the parts of the book it draws on.