LangChain Prompt Engineering Fundamentals
Master the art of prompt engineering with LangChain and unlock the power of Large Language Models for building innovative applications.
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Introduction to Prompt Engineering and LangChain
Unit 1: Understanding Prompt Engineering and LLMs
Welcome to the Course!
What is Prompting?
The Rise of LLMs
Prompting != Programming
Unit 2: Introduction to LangChain
What is LangChain?
LangChain's Core Values
LangChain Ecosystem
Unit 3: Setting Up Your Development Environment
Install Python & Pip
Create a Virtual Env
Install LangChain
API Keys
Unit 4: LangChain's Basic Components
Models: LLMs & Chat Models
What are Prompts?
Chains: Linking it Together
Crafting Effective Prompts with PromptTemplate
Unit 1: Introduction to PromptTemplate
What is PromptTemplate?
PromptTemplate Structure
Simple PromptTemplate
Multiple Input Variables
Default Values
Unit 2: Advanced PromptTemplate Features
Partial Formatting: Intro
Partial Formatting: Usage
Validation: Ensuring Inputs
Validation: Implementation
Template Formats
Unit 3: PromptTemplate for Different Tasks
Text Generation Prompts
Translation Prompts
Summarization Prompts
Prompt Security
Prompting Strategies: Zero-Shot, One-Shot, and Few-Shot Learning
Unit 1: Zero-Shot Learning
Intro to Zero-Shot
Crafting Zero-Shot Prompts
Zero-Shot Text Generation
Zero-Shot Translation
Zero-Shot Summarization
Unit 2: One-Shot Learning
Intro to One-Shot
Crafting One-Shot Prompts
One-Shot Text Generation
One-Shot Classification
One-Shot Reasoning
Unit 3: Few-Shot Learning
Intro to Few-Shot
Crafting Few-Shot Prompts
Few-Shot Question Answering
Unit 4: Comparing Prompting Strategies
Strategy Comparison
Structuring LLM Responses with Output Parsers
Unit 1: Introduction to Output Parsing
Why Structure Output?
Output Parsers: The Basics
Setting up Pydantic
Unit 2: Parsing into JSON
JSON Output Parser
JSON Schema Definition
Handling Complex JSON
Unit 3: Parsing into Lists and Other Structures
List Output Parser
Parsing into CSV
Other Data Structures
Unit 4: Error Handling and Data Integrity
Handling Parsing Errors
Data Validation
Repairing Invalid Output
Prompt Optimization
Putting it All Together
Building Complex Applications with Prompt Chaining
Unit 1: Introduction to Prompt Chaining
What is Prompt Chaining?
Chains and LLMs
LangChain for Chaining
Unit 2: Basic Prompt Chaining Techniques
Simple Sequential Chains
Sequential Chains: An Example
Transform Chains
Unit 3: Advanced Prompt Chaining Strategies
Conditional Chains
Chains with Memory
Chains and APIs
Unit 4: Applications of Prompt Chaining
Q&A Chains
Dialogue Generation Chains
Code Generation Chains
Chains for Summarization
Chains for Translation
Evaluating and Refining Prompts
Unit 1: Introduction to Prompt Evaluation
Why Evaluate Prompts?
Evaluation Metrics
Human vs. Automated Eval
Unit 2: LangChain's Evaluation Tools
Intro to LangChain Evals
String Distance Metrics
Q&A Evaluation
Context Relevance Eval
Unit 3: Prompt Refinement Techniques
Error Analysis
Iterative Refinement
Prompt Engineering Patterns
A/B Testing Prompts
Unit 4: Advanced Evaluation Strategies
Using LLMs for Eval
Human-in-the-Loop Eval
Real-World Considerations