Company knowledge base agent (RAG)
Needs changesWhat this workflow does
This AI workflow has 31 nodes and runs on Google Drive events (file created) (plus 2 other triggers). Along the way it connects Supabase Vector Store, Embeddings OpenAI, Google Drive and Supabase and 4 more.
How it runs
Trigger: On Google Drive events (file created) (plus 2 other triggers).
- Set ID (Edit Fields (Set)): sets 1 field: id
- Voice or Text (Switch): routes items into 2 branches
- Delete Row(s) (Supabase): delete
- Download File (Google Drive): download
- Download File (Telegram): work with file
- Text (Edit Fields (Set)): sets 1 field: text
- Get FIle ID (Edit Fields (Set)): sets 1 field: file_id
- Extract from File: extracts data from a file (text)
- Transcribe (OpenAI): transcribe (audio)
- RAG Agent (AI Agent): runs an AI agent, with model: OpenAI Chat Model; 1 tool (MarketingLadder); memory: Window Buffer Memory
…plus 6 more steps. See the full node list below.
Services it uses
Before you upgrade to n8n 3.0
1 thing in this workflow is removed in n8n 3.0. Fix it before you upgrade:
- AI Agent v1 (old agent modes) in RAG 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 |
|---|---|
| AI Agent v1 (old agent modes) RAG 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 (18)
- Edit Fields (Set)
n8n-nodes-base.set - Supabase Vector Store
@n8n/n8n-nodes-langchain.vectorStoreSupabase - Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader - Recursive Character Text Splitter
@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter - Embeddings OpenAI
@n8n/n8n-nodes-langchain.embeddingsOpenAi - Google Drive Trigger
n8n-nodes-base.googleDriveTrigger - Google Drive
n8n-nodes-base.googleDrive - Extract from File
n8n-nodes-base.extractFromFile - Supabase
n8n-nodes-base.supabase - Limit
n8n-nodes-base.limit - OpenAI
@n8n/n8n-nodes-langchain.openAi - Switch
n8n-nodes-base.switch - Telegram
n8n-nodes-base.telegram - AI Agent
@n8n/n8n-nodes-langchain.agent - Telegram Trigger
n8n-nodes-base.telegramTrigger - Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - Vector Store Question Answer Tool
@n8n/n8n-nodes-langchain.toolVectorStore
From the author
Overview Turn your docs into an AI-powered internal or public-facing assistant. This chatbot workflow uses RAG (Retrieval-Augmented Generation) with Supabase vector search to answer employee or customer questions based on your company documents—automatically…