🐋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 to replace before upgrading
| 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
What it does
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 - Conversational agent with memory buffer - HTTP request implementation with both raw and JSON formats Model Options 🧠 - DeepSeek Chat V3 for general conversation - DeepSeek-R1 for advanced reasoning - Memory-enabled agent for persistent context Quick Setup 🛠️ API Configuration - Base URL: https://api.deepseek.com - Get your API key from platform.deepseek.com/apikeys Local Setup 💻 - Install Ollama for local deployment - Set up DeepSeek-R1 via Ollama - Configure local credentials in n8n Implementation Details 🔧 Conversational Agent - Window Buffer Memory for context - Customizable system messages - Built-in error handling with retries API Endpoints 🌐 - Chat completions for V3 and R1 models - OpenAI API format compatibles