deepseek-reasoner

n8n community node: DeepSeek R1/Reasoner Chat Model with proper reasoningcontent handling for tool calls. Fixes the 'Missing reasoningcontent field' error when using AI Agent with tools. Connect this as the Chat Model sub-node to your AI Agent.

Package Information

Downloads: 41 weekly / 1,225 monthly
Latest Version: 0.9.1
Author: adcom

Available Nodes

DeepSeek Reasoner Chat Model icon
DeepSeek Reasoner Chat Model
Chat model for DeepSeek R1/Reasoner with proper reasoning_content handling for tool calls. Fixes the missing reasoning_content error. Connect this to an AI Agent node as the Chat Model.

Documentation

n8n-nodes-deepseek-reasoner

DeepSeek R1/Reasoner Chat Model for n8n with proper
easoning_content handling for tool calls.

What This Fixes

When using DeepSeek R1 (deepseek-reasoner) with n8n's AI Agent node and tools, you get this error:

Missing reasoning_content field in the assistant message at message index 2

This happens because the built-in DeepSeek Chat Model node uses LangChain's ChatOpenAI, which doesn't preserve the
easoning_content field from DeepSeek's API responses. During multi-step tool-calling loops, LangChain converts messages back to API format but drops
easoning_content, causing the DeepSeek API to reject the request.

This node fixes that by implementing a custom LangChain BaseChatModel that:

  1. Captures
    easoning_content from DeepSeek API responses
  2. Stores it in the LangChain message's dditional_kwargs
  3. Re-includes it when converting messages back to API format on subsequent tool-call turns

How to Use

  1. Install this community node in your n8n instance
  2. In your workflow, use the AI Agent node as usual
  3. Instead of the built-in "DeepSeek Chat Model", connect DeepSeek Reasoner Chat Model as the Chat Model sub-node
  4. Configure your DeepSeek API credentials
  5. Connect your tools the reasoning_content error is now fixed!

Workflow Setup

[AI Agent] <-- Chat Model: [DeepSeek Reasoner Chat Model]
           <-- Tools: [Your Tool 1], [Your Tool 2], ...
           <-- Memory: [Optional Memory Node]

Credentials

Create a "DeepSeek Reasoner API" credential with:

Models

Model Description
deepseek-reasoner DeepSeek R1 always uses thinking/reasoning mode
deepseek-chat DeepSeek V3 standard chat model

Options

Option Default Description
Max Tokens 8192 Maximum tokens to generate (up to 65536)
Temperature 0.7 Controls randomness (ignored by deepseek-reasoner)
Top P 1 Nucleus sampling (ignored by deepseek-reasoner)
Frequency Penalty 0 Penalize repeated tokens
Presence Penalty 0 Penalize tokens already in text
Max Retries 2 Retry attempts on API failure

Technical Details

The core fix works by:

  • On API response: When DeepSeek returns
    easoning_content in an assistant message (during thinking/reasoning), the node stores it in dditional_kwargs.reasoning_content on the LangChain AIMessage
  • On next API call: When the AI Agent sends the conversation back for the next tool-call turn, the node's convertMessages method reads dditional_kwargs.reasoning_content and includes it as a top-level field in the API request body
  • Result: The DeepSeek API receives the required
    easoning_content field and processes the tool-call loop correctly

License

MIT

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