Comprehensive lab covering 4 advanced LangChain retrieval strategies — from basic vector search to intelligent self-querying and parent-document context retrieval. Uses IBM Watsonx LLM with practical exercises on research papers and document collections.
Domain: Advanced RAG — LangChain Retrievers
LLM: IBM Watsonx
Framework: LangChain
| Retriever | How It Works | Best For |
|---|---|---|
| Vector Store-Backed | Semantic similarity search | General document search |
| Multi-Query | Generates multiple query variations | Comprehensive retrieval |
| Self-Querying | Auto-generates + refines queries | Structured data with metadata |
| Parent Document | Returns full parent context | Long documents needing context |
LangChain advanced retrievers · Multi-Query retrieval · Self-querying · Parent document context · IBM Watsonx · Vector store retrieval
