Answer Instagram FAQ DMs using Google Gemini and Qdrant from Google Drive
UnknownUnknown. This template uses community nodes we can't verify statically. Uses community nodes that can't be verified statically (unverified community packages are off by default in 3.0). Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 17 nodes and runs on Instagram events (plus 2 other triggers). Along the way it connects Qdrant Vector Store, Embeddings Google Gemini, Google Drive and Google Gemini Chat Model and 1 more.
How it runs
Trigger: On Instagram events (plus 2 other triggers).
- If: checks a condition and branches into true / false
- If: checks a condition and branches into true / false
- Refresh Instagram Access Token (Instagram): work with auth
- AI Chat Response Agent (AI Agent): runs an AI agent, with model: Google Gemini Chat Model; 1 tool (Store Embeddings in Qdrant); memory: Chat Memory Buffer
- Loop Over Batches of (Loop Over Items (Split in Batches)): loops over the items in batches
- Send Instagram Direct Messages (Instagram): work with messaging
- Download File from Drive (Google Drive): download
- Update Qdrant Vector Store (Qdrant Vector Store): stores documents in the Qdrant vector store, with embeddings: Generate Embeddings with Gemini; document loader: Load Default Documents
Services it uses
Before you upgrade to n8n 3.0
We can't fully verify this one: it relies on 2 community packages, and n8n 3.0 turns unverified community packages off by default (N8N_UNVERIFIED_PACKAGES_ENABLED=false).
- Check that @mookielianhd/n8n-nodes-instagram is verified or supports 3.0 (used in Refresh Instagram Access Token, Send Instagram Direct Messages).
- Check that @mookielianhd/n8n-nodes-instagram is verified or supports 3.0 (used in Instagram Message Trigger).
Nodes used (14)
- AI Agent
@n8n/n8n-nodes-langchain.agent - Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow - Instagram
@mookielianhd/n8n-nodes-instagram.instagram - If
n8n-nodes-base.if - Qdrant Vector Store
@n8n/n8n-nodes-langchain.vectorStoreQdrant - Embeddings Google Gemini
@n8n/n8n-nodes-langchain.embeddingsGoogleGemini - Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader - Google Drive Trigger
n8n-nodes-base.googleDriveTrigger - Google Drive
n8n-nodes-base.googleDrive - Recursive Character Text Splitter
@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter - Schedule Trigger
n8n-nodes-base.scheduleTrigger - Loop Over Items (Split in Batches)
n8n-nodes-base.splitInBatches - Google Gemini Chat Model
@n8n/n8n-nodes-langchain.lmChatGoogleGemini - Instagram Trigger
@mookielianhd/n8n-nodes-instagram.instagramTrigger
From the author
Quick overview This workflow answers Instagram DMs using a Google Gemini RAG agent backed by a Qdrant vector store, while automatically ingesting new PDF files from Google Drive into the knowledge base and refreshing the Instagram access token on a schedule.…