🐋DeepSeek V3 chat & R1 reasoning quick start
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 8 nodes and runs when a chat message arrives. Along the way it connects OpenAI Chat Model and Ollama Chat Model. It also calls api.deepseek.com over HTTP.
How it runs
Trigger: When a chat message arrives.
- Basic LLM Chain: sends a prompt to an LLM, with model: Ollama DeepSeek
- AI Agent: runs an AI agent, with model: DeepSeek; memory: Window Buffer Memory
- DeepSeek Raw Body (HTTP Request): calls api.deepseek.com (POST)
- DeepSeek JSON Body (HTTP Request): calls api.deepseek.com (POST)
Services it uses
HTTP calls to: api.deepseek.com
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 (7)
- Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - AI Agent
@n8n/n8n-nodes-langchain.agent - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow - Basic LLM Chain
@n8n/n8n-nodes-langchain.chainLlm - Ollama Chat Model
@n8n/n8n-nodes-langchain.lmChatOllama - HTTP Request
n8n-nodes-base.httpRequest
From the author
This n8n workflow demonstrates multiple ways to harness DeepSeek's AI models in your automation pipeline! 🌟 Core Features Multiple Integration Methods 🔌 - Local deployment using Ollama for DeepSeek-R1 - Direct API integration with DeepSeek Chat V3 -…