Originally published at claudeguide.io/build-rag-system-claude-python

Build a RAG System with Claude: Python Implementation Guide

RAG (Retrieval-Augmented Generation) lets Claude answer questions using your documents — product manuals, codebases, knowledge bases, or any text corpus in 2026. The pattern: embed documents as vectors, store them, retrieve the most relevant chunks when a question is asked, inject them into Claude's context, and get a grounded answer. This guide covers a complete working implementation from document ingestion to query response.

---

Why RAG instead of just stuffing documents into context

With Claude's 200K context window, you could theoretically put your entire knowledge base in every request. For small corpora (under 100 documents), this works fine. For larger corpora, RAG wins:

• Cost: at 100,000 tokens per request × 1,000 requests/day = 100M tokens/day = $300/day for Sonnet. RAG retrieves 5–10 relevant chunks (~5,000 tokens) instead.
• Quality: focused context produces better answers than overwhelming Claude with irrelevant content.
• Scale: a 10,000-document knowledge base doesn't fit in context; a retrieval system handles any size.

---

Architecture overview

Documents → Chunking → Embedding → Vector Store
                                          ↓
User Query → Embedding → Vector Search → Top-K chunks → Claude → Answer

---

Step 1: Install dependencies

pip install anthropic openai pgvector psycopg2-binary python-dotenv

We use:

• anthropic — Claude for answer generation
• openai — embeddings (text-embedding-3-small, cheapest + good quality)
• pgvector — vector similarity search in PostgreSQL
• Alternatively: replace with chromadb or pinecone for in-process or managed vector storage

---

Step 2: Document chunking

python
from typing import List
import re

def chunk_text(
    text: str,
    chunk_size: int = 1000,
    overlap: int = 200,
) -

[→ Get the Agent SDK Cookbook — $49](https://shoutfirst.gumroad.com/l/ogxhmy?utm_source=claudeguide&utm_medium=article&utm_campaign=build-rag-system-claude-python)

*30-day money-back guarantee. Instant download.*