🤖 AI powered RAG chatbot for your docs + Google Drive + Gemini + Qdrant
Needs changesNeeds changes. This template uses 2 thing(s) that n8n 3.0 removes: LangChain Code (legacy), AI Agent v1 (old agent modes). 2 breaking item(s) found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 35 nodes and runs when a chat message arrives (plus 2 other triggers). Along the way it connects Qdrant Vector Store, Google Gemini Chat Model, Google Drive and Embeddings OpenAI and 3 more.
How it runs
Trigger: When a chat message arrives (plus 2 other triggers).
- AI Agent: runs an AI agent, with model: Google Gemini Chat Model; 1 tool (Qdrant Vector Store); memory: Window Buffer Memory
- Google Folder ID (Edit Fields (Set)): sets 1 field: folder_id
- Update Chat History (Google Docs): update
- Respond to User (Edit Fields (Set)): sets 1 field: output
- Find File Ids in Google Drive Folder (Google Drive): work with file folder
- File Id List (Summarize): summarizes / groups the items
- Qdrant Collection Name (Edit Fields (Set)): sets 1 field: qdrant_collection_name
- Merge: merges the data from its input branches
- Merge: merges the data from its input branches
- Loop Over Items (Loop Over Items (Split in Batches)): loops over the items in batches
…plus 13 more steps. See the full node list below.
Services it uses
Before you upgrade to n8n 3.0
2 things in this workflow are removed in n8n 3.0. Fix them before you upgrade:
- LangChain Code (legacy) in Delete Qdrant Points by File ID: no direct replacement.
- AI Agent v1 (old agent modes) in AI Agent (v1.7): replace with Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent.
| Removed in 3.0 | Replace with |
|---|---|
| LangChain Code (legacy) Delete Qdrant Points by File ID | No direct replacement |
| AI Agent v1 (old agent modes) AI Agent (v1.7) | Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent. |
Nodes used (23)
- Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader - Token Splitter
@n8n/n8n-nodes-langchain.textSplitterTokenSplitter - Qdrant Vector Store
@n8n/n8n-nodes-langchain.vectorStoreQdrant - Loop Over Items (Split in Batches)
n8n-nodes-base.splitInBatches - Wait
n8n-nodes-base.wait - Manual Trigger
n8n-nodes-base.manualTrigger - Google Gemini Chat Model
@n8n/n8n-nodes-langchain.lmChatGoogleGemini - Merge
n8n-nodes-base.merge - Information Extractor
@n8n/n8n-nodes-langchain.informationExtractor - Extract from File
n8n-nodes-base.extractFromFile - Google Drive
n8n-nodes-base.googleDrive - Embeddings OpenAI
@n8n/n8n-nodes-langchain.embeddingsOpenAi - Edit Fields (Set)
n8n-nodes-base.set - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - LangChain Code
@n8n/n8n-nodes-langchain.code - Summarize
n8n-nodes-base.summarize - Telegram
n8n-nodes-base.telegram - If
n8n-nodes-base.if - Webhook
n8n-nodes-base.webhook - AI Agent
@n8n/n8n-nodes-langchain.agent - Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow - Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - Google Docs
n8n-nodes-base.googleDocs
From the author
🤖 AI-Powered RAG Chatbot with Google Drive Integration This workflow creates a powerful RAG (Retrieval-Augmented Generation) chatbot that can process, store, and interact with documents from Google Drive using Qdrant vector storage and Google's Gemini AI.…