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Introduction

LlamaIndex is a framework for building search and retrieval LLM applications, such as asking questions over a large dataset or extracting information from complex datasets.

Combine a large and diversified set of data into a searchable experience requires a lot of work as you need to:

  • support a wide range of data types (PDF, Images, Websites)
  • orchestrate the transformation of a large dataset
  • index large chunks of data in a searchable index (vector database)

LlamaIndex, with LlamaHub, provides a wide range of libraries and tools to load various document types.

Browserbase provides a WebReader Document loader to:

  • Load web pages, including pages using JavaScript or dynamically rendered text.
  • Load images via screenshots.

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Add Browserbase to your LlamaIndex application

To get started, proceed to the quickstart guide to learn more about using Browserbase with LlamaIndex.

Browserbase for LlamaIndex (Python)

Add Browserbase Document Loader to your LlamaIndex application

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