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Building Data-Driven Applications with LlamaIndex

Building Data-Driven Applications with LlamaIndex

By : Andrei Gheorghiu
5 (10)
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Building Data-Driven Applications with LlamaIndex

Building Data-Driven Applications with LlamaIndex

5 (10)
By: Andrei Gheorghiu

Overview of this book

Discover the immense potential of Generative AI and Large Language Models (LLMs) with this comprehensive guide. Learn to overcome LLM limitations, such as contextual memory constraints, prompt size issues, real-time data gaps, and occasional ‘hallucinations’. Follow practical examples to personalize and launch your LlamaIndex projects, mastering skills in ingesting, indexing, querying, and connecting dynamic knowledge bases. From fundamental LLM concepts to LlamaIndex deployment and customization, this book provides a holistic grasp of LlamaIndex's capabilities and applications. By the end, you'll be able to resolve LLM challenges and build interactive AI-driven applications using best practices in prompt engineering and troubleshooting Generative AI projects.
Table of Contents (18 chapters)
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1
Part 1:Introduction to Generative AI and LlamaIndex
4
Part 2: Starting Your First LlamaIndex Project
8
Part 3: Retrieving and Working with Indexed Data
12
Part 4: Customization, Prompt Engineering, and Final Words

An overview of LlamaHub

LlamaHub is an extensive library of integrations that augments the capabilities of the core framework. Among many other types of integrations, LlamaHub contains numerous connectors – also known as data readers or data loaders – specially built to allow seamless integration of external data with LlamaIndex. There are over 180 readily available data readers spanning a wide range of data sources and formats, and the list is constantly increasing.

These connectors act as a standard way to ingest data, extracting data from sources such as databases, APIs, files, and websites and converting it into LlamaIndex Document objects. This relieves you from the burden of writing customized parsers and connectors for every new data source. But of course, if you’re not satisfied with the existing connectors, you can always build your own and contribute to the collection.

LlamaHub empowers you to tap into diverse data sources with just a few lines...

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