Intermediate Tier
Methodology Blueprint
Retrieval-Augmented Generation
Research.
RAG bridges the gap between static model weights and dynamic, proprietary data. It uses vector embeddings and semantic search to retrieve relevant context before passing it to the generator.
Core Concepts
Technical Node
Vector Databases
Technical Node
Chunking Strategies
Technical Node
Semantic Search
Technical Node
Context Injection
Blueprint Strategy
01
Step 01
Parse documents into clean Markdown or Text.
02
Step 02
Chunk data using overlapping windows to preserve context.
03
Step 03
Convert chunks into high-dimension vectors using an embedding model.
04
Step 04
Store vectors in a database (like Milvus, Weaviate, or Pinecone).
05
Step 05
Query the database using the user prompt vector to find matching chunks.
06
Step 06
Pass chunks as "Context" into the final LLM prompt.
Recommended Infrastructure