HyDE (Hypothetical Document Embeddings)

Generate hypothetical answer documents to bridge vocabulary gaps in semantic search.

The Problem

Direct query embedding often fails due to vocabulary mismatch:

Query: "scaling async data pipelines"
Docs use: "event-driven messaging", "Apache Kafka", "message brokers"
→ Low similarity scores despite high relevance

The Solution

Instead of embedding the query, generate a hypothetical answer document:

Query: "scaling async data pipelines"
→ LLM generates: "To scale asynchronous data pipelines, use event-driven