AI agent to chat with files in Supabase Storage
Needs changesNeeds changes. This template uses 1 thing(s) that n8n 3.0 removes: AI Agent v1 (old agent modes). 1 breaking item(s) found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 22 nodes and runs when a chat message arrives (plus 1 other trigger). Along the way it connects Embeddings OpenAI, Supabase, OpenAI Chat Model and Vector Store Question Answer and 1 more.
How it runs
Trigger: When a chat message arrives (plus 1 other trigger).
- AI Agent: runs an AI agent, with model: OpenAI Chat Model; 1 tool (Vector Store Tool)
- Get All Files (Supabase): get many
- Aggregate: combines items into one
- Get All files (HTTP Request): calls an HTTP API (POST)
- Loop Over Items (Loop Over Items (Split in Batches)): loops over the items in batches
- If: checks a condition and branches into true / false
- Download (HTTP Request): calls an HTTP API
- Switch: routes items into 2 branches
- Merge: merges the data from its input branches
- Extract Document PDF (Extract from File): extracts data from a file (pdf)
…plus 2 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 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.
Rather not rewrite it? Many of these flows can be rebuilt in Make (free plan).
| Removed in 3.0 | Replace with |
|---|---|
| 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 (17)
- HTTP Request
n8n-nodes-base.httpRequest - Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader - Recursive Character Text Splitter
@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter - Extract from File
n8n-nodes-base.extractFromFile - Embeddings OpenAI
@n8n/n8n-nodes-langchain.embeddingsOpenAi - Supabase
n8n-nodes-base.supabase - If
n8n-nodes-base.if - Loop Over Items (Split in Batches)
n8n-nodes-base.splitInBatches - Manual Trigger
n8n-nodes-base.manualTrigger - Aggregate
n8n-nodes-base.aggregate - Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - Vector Store Question Answer Tool
@n8n/n8n-nodes-langchain.toolVectorStore - Switch
n8n-nodes-base.switch - Supabase Vector Store
@n8n/n8n-nodes-langchain.vectorStoreSupabase - Merge
n8n-nodes-base.merge - AI Agent
@n8n/n8n-nodes-langchain.agent
From the author
Video Guide I prepared a detailed guide explaining how to set up and implement this scenario, enabling you to chat with your documents stored in Supabase using n8n. Youtube Link Who is this for? This workflow is ideal for researchers, analysts, business…