Video description
This course begins by introducing foundational concepts of Large Language Models (LLMs) and their applications, focusing on LlamaIndex. You'll set up your development environment and create your first LlamaIndex program, covering essential topics like advanced prompt engineering.
As you progress, you'll delve deeper into LlamaIndex functionalities, including formatting prompt templates, designing conversational prompts, and using semantic similarity evaluators. The course also covers language embeddings, vector databases, and integrating LlamaIndex with SQL and Chroma DB vector databases. You'll learn to set up various query pipelines, such as sequential, DAG, and dataframe pipelines, for efficient handling of complex queries.
In the final section, you'll apply your knowledge to practical scenarios. You'll build a calculator using a ReAct agent, develop a document agent with dynamically built tools, and construct a code checker with a Streamlit UI. Each module is designed to enhance your skills in creating versatile, AI-driven applications, preparing you to tackle real-world challenges in AI development.
What you will learn
- Develop and implement LlamaIndex programs
- Design and utilize advanced prompt templates
- Evaluate semantic similarities effectively
- Integrate LlamaIndex with various databases
- Set up and optimize different query pipelines
- Create dynamic agents and tools for AI applications
Audience
This course is designed for intermediate to advanced developers and AI enthusiasts with a basic understanding of Python programming and machine learning concepts. Familiarity with LLMs and natural language processing will be beneficial but is not mandatory.
About the Author
Manas Dasgupta: Manas Dasgupta, hailing from Bangalore, the Silicon Valley of India, is a seasoned expert in Generative AI and RAG application development. He holds a Master's Degree in AI from Liverpool John Moores University, UK. With over 20 years of IT development experience, primarily in the financial services sector, Manas has honed his expertise in machine learning, data science, and predictive analytics. His research spans Natural Language Processing using deep learning methods like Siamese Networks, encoder-decoder techniques, and BERT embeddings. As the founder of Teksands, he leads his team in developing Gen AI-rich applications in the talent space.
Table of contents
- Chapter 1 : Introduction
-
Chapter 2 : Getting Deeper into LlamaIndex
- Format Prompt Templates
- Conversational Prompts
- Semantic Similarity Evaluator
- Language Embeddings and Vector Databases
- Using a Chroma DB Vector Database
- LlamaIndex with SQL Database
- LlamaIndex Query Pipelines
- Setting up a Simple Sequential Query Pipeline
- Setting up a DAG Pipeline
- Setting up a Dataframe Pipeline
- Working with Agents and Tools
- Create a Calculator using a ReAct Agent
- Create a Document Agent with Dynamically built Tools
- Build a Code Checker with Streamlit UI
Product information
- Title: Gen AI - RAG Application Development using LlamaIndex
- Author(s):
- Release date: July 2024
- Publisher(s): Packt Publishing
- ISBN: 9781836640431
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