Module Overview
This module covers LangChain as the orchestration layer for production RAG. It spans the framework's architecture and ecosystem, the LCEL composition model, the building blocks of retrieval and memory, agentic and multimodal patterns, and the production concerns of observability, security, and evaluation.
Learning Objectives
- Describe LangChain's architecture and model-abstraction layer.
- Compose chains with LCEL and integrate the broader ecosystem.
- Apply prompting, structured output parsing, and tool calling.
- Build memory, retrieval, and agentic RAG pipelines.
- Trace, secure, and evaluate a LangChain application in production.
Topics Covered
Architecture, Integrations & LCEL
- Architecture and ecosystem (2026)
- LLM integrations and model abstraction
- LCEL deep dive
- Integrations ecosystem (2026)
Prompting, Output Parsing & Tool Calling
- Prompt engineering
- Structured output and output parsers
- Tool calling and function calling
Memory, Retrieval & RAG
- Memory and conversation history
- Document loaders and text splitters
- Embeddings and vector stores
- Retrieval and advanced RAG
- Agentic RAG and advanced pipelines
Agents, Multimodal & Text-to-SQL
- Agents — legacy and modern
- Multimodal — images, audio, documents
- Text-to-SQL and structured data
Production, Observability & Security
- Callbacks, tracing, and LangSmith
- Production patterns and best practices
- Building and deploying LangChain APIs
- Security, safety, and responsible AI
- Evaluation, testing, and LangSmith Evals
Key Concepts & Terminology
Runnable composition, retriever interface, conversation memory, agent executor, tracing spans, eval datasets, responsible-AI guardrails.
Tools & Frameworks Referenced
LangChain, LCEL, LangSmith.
Prerequisites
Module 14 (embeddings); Module 19 helps for tool calling.