Building a RAG Pipeline with LangChain and Next.js

RAG (Retrieval Augmented Generation) is the "Hello World" of 2026.

The Stack

• Frontend: Next.js 15 (App Router).
• Orchestration: LangChain.js.
• Vector DB: Pinecone.
• LLM: GPT-4o-mini.

Step 1: Chunking

Don't just feed the whole PDF.

const splitter = new RecursiveCharacterTextSplitter({
  chunkSize: 1000,
  chunkOverlap: 200,
});

Step 2: Visualization

The hardest part of RAG is debugging. "Why did it retrieve that chunk?" Use Vector AI to visualize your embedding space and debug clustering issues.

Debug RAG Pipelines