PDF RAG System: OpenAI, Pinecone & Cohere Reranking
Build a complete RAG chatbot for PDF documents using OpenAI embeddings, Pinecone vector store, and Cohere reranking for accurate Q&A.
This n8n workflow implements a full Retrieval-Augmented Generation (RAG) system tailored for PDF documents. It operates in two phases: data ingestion and conversational querying. In the ingestion phase, a PDF is uploaded via Form Trigger, processed by Default Data Loader, split into chunks with Recursive Character Text Splitter, embedded using OpenAI, and upserted into a Pinecone vector index for semantic search.
The conversational phase uses a Chat Trigger to receive user queries. An AI Agent
Platform
n8n
Category
IT & Development
Price
$24.99
Creator
Fred Garcia
RAG
PDF Processing
OpenAI
Pinecone
Cohere
AI Agent
Vector Store
Chatbot
Document QA
Embeddings
How to import this workflow into n8n
1Purchase or download the workflow to get the n8n workflow JSON file.
2In your n8n instance, open Workflows and choose "Import from File" (or paste the JSON with Ctrl+V on the canvas).
3Open each node marked with a credential warning and connect your own accounts and API keys.
4Run the workflow once manually to verify the data flow, then toggle it to Active.