Build a PDF-based RAG system with OpenAI, Pinecone and Cohere reranking
Ready for 3.0Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 11 nodes and runs when someone submits an n8n form (“Upload RAG PDF”) (plus 1 other trigger). Along the way it connects Pinecone Vector Store, Embeddings OpenAI, OpenAI Chat Model and Reranker Cohere.
How it runs
Trigger: When someone submits an n8n form (“Upload RAG PDF”) (plus 1 other trigger).
- Pinecone Vector Store: stores documents in the Pinecone vector store, with embeddings: Embeddings OpenAI; document loader: Default Data Loader
- AI Agent: runs an AI agent, with model: OpenAI Chat Model; 1 tool (VectorDB); memory: Simple Memory
Services it uses
Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
Nodes used (10)
- n8n Form Trigger
n8n-nodes-base.formTrigger - Pinecone Vector Store
@n8n/n8n-nodes-langchain.vectorStorePinecone - Embeddings OpenAI
@n8n/n8n-nodes-langchain.embeddingsOpenAi - Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader - Recursive Character Text Splitter
@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter - AI Agent
@n8n/n8n-nodes-langchain.agent - Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow - Reranker Cohere
@n8n/n8n-nodes-langchain.rerankerCohere
From the author
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This workflow provides a complete, ready-to-use template for a Retrieval-Augmented Generation (RAG) system. It allows you to build a powerful AI chatbot that…