Programming Large Language Models with Azure Open AI: Conversational programming and prompt engineering with LLMs (Developer Reference)

Cover
Title Page
Copyright Page
Contents at a Glance
Contents
Acknowledgments
Introduction
Chapter 1 The genesis and an analysis of large language models
	LLMs at a glance
		History of LLMs
		Functioning basics
		Business use cases
	Facts of conversational programming
		The emerging power of natural language
		LLM topology
		Future perspective
	Summary
Chapter 2 Core prompt learning techniques
	What is prompt engineering?
		Prompts at a glance
		Alternative ways to alter output
		Setting up for code execution
	Basic techniques
		Zero-shot scenarios
		Few-shot scenarios
		Chain-of-thought scenarios
	Fundamental use cases
		Chatbots
		Translating
	LLM limitations
	Summary
Chapter 3 Engineering advanced learning prompts
	What’s beyond prompt engineering?
		Combining pieces
		Fine-tuning
	Function calling
		Homemade-style
		OpenAI-style
	Talking to (separated) data
		Connecting data to LLMs
		Embeddings
		Vector store
		Retrieval augmented generation
	Summary
Chapter 4 Mastering language frameworks
	The need for an orchestrator
		Cross-framework concepts
		Points to consider
	LangChain
		Models, prompt templates, and chains
		Agents
		Data connection
	Microsoft Semantic Kernel
		Plug-ins
		Data and planners
	Microsoft Guidance
		Configuration
		Main features
	Summary
Chapter 5 Security, privacy, and accuracy concerns
	Overview
		Responsible AI
		Red teaming
		Abuse and content filtering
		Hallucination and performances
		Bias and fairness
	Security and privacy
		Security
		Privacy
	Evaluation and content filtering
		Evaluation
		Content filtering
	Summary
Chapter 6 Building a personal assistant
	Overview of the chatbot web application
		Scope
		Tech stack
	The project
		Setting up the LLM
		Setting up the project
		Integrating the LLM
		Possible extensions
	Summary
Chapter 7 Chat with your data
	Overview
		Scope
		Tech stack
	What is Streamlit?
		A brief introduction to Streamlit
		Main UI features
		Pros and cons in production
	The project
		Setting up the project and base UI
		Data preparation
		LLM integration
	Progressing further
		Retrieval augmented generation versus fine-tuning
		Possible extensions
	Summary
Chapter 8 Conversational UI
	Overview
		Scope
		Tech stack
	The project
		Minimal API setup
		OpenAPI
		LLM integration
		Possible extensions
	Summary
Appendix: Inner functioning of LLMs
Index
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