Practical RAG Implementation Patterns

An overview of practical patterns for implementing Retrieval Augmented Generation (RAG) in production systems.

Introduction

RAG has become a crucial pattern for enhancing LLM responses with contextual information. Let's explore some practical implementation patterns.

Key Implementation Patterns

1. Vector Store Selection

• Chroma for local development
• Pinecone for production workloads
• Qdrant for self-hosted solutions

2. Chunking Strategies

• Document-based chunking
• Semantic chunking
• Sliding window with overlap

3. Re-ranking Approaches

• Cross-encoder reranking
• Hybrid search
• Reciprocal rank fusion

Coming Soon

In future posts, we'll dive deeper into each of these patterns with code examples and benchmarks.