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
- Development & IT
- 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.
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