🐋DeepSeek V3 chat & R1 reasoning quick start

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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

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...

Best for

Engineering automation workflows
AI Chatbot automation workflows
advanced n8n builders looking for reusable templates

Tools used

@n8n/n8n-nodes-langchain.chattrigger, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.memorybufferwindow, @n8n/n8n-nodes-langchain.chainllm, n8n-nodes-base.stickynote, @n8n/n8n-nodes-langchain.lmchatollama, n8n-nodes-base.httprequest

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Joseph LePage.

Original n8n.io source

1.1 Workflow description

Title: 🐋DeepSeek V3 chat & R1 reasoning quick start
Workflow name: 🐋DeepSeek V3 chat & R1 reasoning quick start

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/api_keys

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

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - When chat message received

Type / Role: @n8n/n8n-nodes-langchain.chatTrigger - chatTrigger
Config choices: Version 1.1

Block 2 - AI Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 1.7

Block 3 - DeepSeek

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.1

Block 4 - Window Buffer Memory

Type / Role: @n8n/n8n-nodes-langchain.memoryBufferWindow - memoryBufferWindow
Config choices: Version 1.3

Block 5 - Basic LLM Chain2

Type / Role: @n8n/n8n-nodes-langchain.chainLlm - chainLlm
Config choices: Version 1.5

Block 6 - Sticky Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 7 - Sticky Note1

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 8 - Ollama DeepSeek

Type / Role: @n8n/n8n-nodes-langchain.lmChatOllama - lmChatOllama
Config choices: Version 1

Block 9 - Sticky Note2

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 10 - Sticky Note3

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 11 - DeepSeek JSON Body

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.2

Block 12 - DeepSeek Raw Body

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.2

Block 13 - Sticky Note4

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 14 - Sticky Note5

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 15 - Sticky Note6

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

3. Summary Table

Workflow	🐋DeepSeek V3 chat & R1 reasoning quick start
Complexity	advanced
Nodes	15
Categories	Engineering, AI Chatbot
Author	Joseph LePage
Published	22 Jan 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/2777/2777.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source Engineering workflows AI Chatbot workflows

Frequently asked questions

What does 🐋DeepSeek V3 chat & R1 reasoning quick start do?

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...

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Engineering, AI Chatbot use case.

Joseph LePage

33 workflows

Nodes

@n8n/n8n-nodes-langchain.chattrigger @n8n/n8n-nodes-langchain.agent @n8n/n8n-nodes-langchain.lmchatopenai @n8n/n8n-nodes-langchain.memorybufferwindow @n8n/n8n-nodes-langchain.chainllm n8n-nodes-base.stickynote @n8n/n8n-nodes-langchain.lmchatollama n8n-nodes-base.httprequest

Complexity

advanced

Published 22 Jan 2025

Likes 0

View on n8n.io Download Workflow

Install path: /data/workflows/2777/2777.json

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🐋DeepSeek V3 chat & R1 reasoning quick start

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

Core Features

Quick Setup 🛠️

Implementation Details 🔧

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - When chat message received

Block 2 - AI Agent

Block 3 - DeepSeek

Block 4 - Window Buffer Memory

Block 5 - Basic LLM Chain2

Block 6 - Sticky Note

Block 7 - Sticky Note1

Block 8 - Ollama DeepSeek

Block 9 - Sticky Note2

Block 10 - Sticky Note3

Block 11 - DeepSeek JSON Body

Block 12 - DeepSeek Raw Body

Block 13 - Sticky Note4

Block 14 - Sticky Note5

Block 15 - Sticky Note6

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions