Templates / Build a document-upload RAG chatbot with OpenAI, Pinecone and daily analytics

Build a document-upload RAG chatbot with OpenAI, Pinecone and daily analytics

Ready for 3.0

by ResilNext ✓ · 450 views · created 2026-03-14 · Internal Wiki, AI RAG

Ready 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 18 nodes and runs when someone submits an n8n form (“Document Upload for RAG”) (plus 2 other triggers). Along the way it connects Embeddings OpenAI, Pinecone Vector Store, OpenAI Chat Model and Gmail.

How it runs

Trigger: When someone submits an n8n form (“Document Upload for RAG”) (plus 2 other triggers).

  1. Workflow Configuration (Edit Fields (Set)): sets 5 fields: pineconeIndex, pineconeNamespace, chunkSize…
  2. RAG Chatbot Agent (AI Agent): runs an AI agent, with model: OpenAI Chat Model; 1 tool (Pinecone Vector Store); memory: Chat Memory
  3. Get Chat Logs (Data table): get
  4. Store Form Responses (Data table): uses Data table
  5. Pinecone Insert Documents (Pinecone Vector Store): stores documents in the Pinecone vector store, with embeddings: OpenAI Embeddings; document loader: Document Loader
  6. Prepare Chat Log (Edit Fields (Set)): sets 5 fields: userQuery, botResponse, timestamp…
  7. Analyze Chat Data (Code): runs custom JavaScript code
  8. Log Chat Interactions (Data table): uses Data table
  9. Send Daily Summary Email (Gmail): uses Gmail

Services it uses

Embeddings OpenAIPinecone Vector StoreOpenAI Chat ModelGmail

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 (14)

From the author

Overview This workflow implements a complete Retrieval-Augmented Generation (RAG) knowledge assistant with built-in document ingestion, conversational AI, and automated analytics using n8n, OpenAI, and Pinecone. The system allows users to upload documents,…

Excerpt from ResilNext's description on n8n.io.

View the original on n8n.io → Check your own copy

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