Breaking down the RAG pipeline
Think of the RAG pipeline as an assembly line in a library, where raw materials (documents) get transformed into a searchable knowledge base that can answer questions. Let us walk through how each component plays its part.
- Document processing – the foundation
Document processing is like preparing books for a library. When documents first enter the system, they need to be:
- Loaded using document loaders appropriate for their format (PDF, HTML, text, etc.)
- Transformed into a standard format that the system can work with
- Split into smaller, meaningful chunks that are easier to process and retrieve
For example, when processing a textbook, we might break it into chapter-sized or paragraph-sized chunks while preserving important context in metadata.
- Vector indexing – creating the card catalog
Once documents are processed, we need a way to make them searchable. This is where vector indexing...
