目錄
Preface
Part I. Generative AI, Understanding Large Language Models, and LangChain
1. From Statistics to Generative AI in Life Sciences
Introduction
Application of Generative AI in Life Sciences
Audio and Visual
Text
Scientific Components
Research Studies
Drawbacks of Generative AI in Science
Summary
2. Introducing Large Language Models
Embedding Models
Chat and Large Language Models
Tokens
Text and Sequence Generation
Decoding Strategies
All Sorts of Language Models
Large Language Model Limitations
Summary
3. Introducing LangChain
Indexes
Indexing
Vector Search
Vector Stores
Chains
The LangChain Expression Language
LangGraph
Prompts
Memory
Tools
Agents
Creating Apps with LangChain
Summary
4. Hallucinations and RAG Systems
Hallucinations, Their Causes, and Consequences
Hallucinations and Possible Solutions
Retrieval-Augmented Generation
Indexing and Data Preparation
Query Translation and Understanding
Routing to Correct Database/Index
Query Construction
Data Retrieval
Data Augmentation and Response Generation
RAG Variations: Self-RAG, Tree-RAG, CAG, Agentic RAG
Evaluating RAGs
The Advantages of Hallucinating
Summary
5. Building Personal Assistants
Building Assistants with Chains
Building Assistants with Agents
Building Assistants with Multiple Agents
Model Context Protocol
Summary
Part II. Building AI Agents and Assistants Using LangChain and LangGraph
6. LangChain for Chemistry
Generative AI in Chemistry
Text-Based
Code-Generative
Chemistry-Generative
Creating Applications with External Packages
ChemCrow and CACTUS
LLMs
LCEL Chains
Custom LangChain Agent
RDKit Custom Agents
Using Chemistry-Based LLMs
Using Text-Based LLMs in Chemical Applications
Summary
7. LangChain for Biology
LLMs in Biology
Biological LangGraph Application
Creating Biological Tools
Fine-Tuning Large Language and Reasoning Models
Introduction to Large Reasoning Models
Summary
8. LangChain for Drug Discovery
In Silico Drug Discovery
Small Molecule Generation
Autoencoders
Knowledge Graphs
Neo4j Vectors
Summary
9. LangChain for Medicine and Healthcare
Generative AI for Healthcare
Creating a Generative Healthcare Application
Brainstorming Assistant
Advanced Brainstorming Scenario
Integrating Speech-to-Text
RAG over SQL
Summarization
Report Generation
Multi-Team Applications
Adopting AI in Healthcare and Medicine
Summary
10. LangChain for Enterprise
Guardrails, Enterprise Best Practices, and Policies
Data Security, Privacy, and Compliance
Prompt Injection
Fallbacks
Off-Topic Questions
Preventing the Generation of Harmful Content and Toxicity
Evaluating LLMs and Generative AI Applications
LangChain and LangGraph Alternatives and Add-Ons
Data Integration and Retrieval Frameworks
Low-Code/No-Code Platforms
LLM Observability and Debugging Tools
Langfuse
AI Agent and Workflow Frameworks, and Specialized LLM Tools
Multi-Agent Frameworks
Summary
Index
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