Document-based chatbot with memory using OpenAI, Pinecone and Google Drive
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 20 nodes and runs when a chat message arrives (plus 1 other trigger). Along the way it connects Airtable, Google Drive, Pinecone Vector Store and Embeddings OpenAI and 3 more.
How it runs
Trigger: When a chat message arrives (plus 1 other trigger).
- Get Memories (Airtable): search
- Merge: merges the data from its input branches
- Google Drive: work with file folder
- Aggregate: combines items into one
- AI Agent: runs an AI agent, with model: OpenRouter Chat Model; 2 tools (Save Memory, Answer questions with a vector store); memory: Simple Memory
- Get Content (Google Drive): download
- Loop Over Items (Loop Over Items (Split in Batches)): loops over the items in batches
- Pinecone Vector Store: stores documents in the Pinecone vector store, with embeddings: Embeddings OpenAI; document loader: Default Data Loader
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 (17)
- Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - AI Agent
@n8n/n8n-nodes-langchain.agent - Airtable Tool
n8n-nodes-base.airtableTool - Airtable
n8n-nodes-base.airtable - Aggregate
n8n-nodes-base.aggregate - Merge
n8n-nodes-base.merge - Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow - Manual Trigger
n8n-nodes-base.manualTrigger - Google Drive
n8n-nodes-base.googleDrive - Loop Over Items (Split in Batches)
n8n-nodes-base.splitInBatches - 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 - Vector Store Question Answer Tool
@n8n/n8n-nodes-langchain.toolVectorStore - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - OpenRouter Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenRouter
From the author
Who is This For? This is for normal people or people just starting off and wanting to have a AI chatbot that can process data to use when talking to the user. How to Use You will need to have your own OpenRouter (Free) and OpenAI APIs as well as Google Drive,…