n8n-nodes-berget-ai-chat

n8n node for Berget AI chat/text models (Llama, Mistral, Qwen, GPT-OSS, etc.)

Installation

Community Nodes (Recommended)

1. Open n8n
2. Go to Settings > Community Nodes
3. Click Install a community node
4. Enter: @bergetai/n8n-nodes-berget-ai-chat
5. Click Install

Manual Installation

# In your n8n project
npm install @bergetai/n8n-nodes-berget-ai-chat

Local Development

# Clone this repo
git clone <repo-url>
cd n8n-nodes-berget-ai-chat

# Install dependencies
npm install

# Build project
npm run build

# Link locally for development
npm link
cd /path/to/your/n8n/project
npm link @bergetai/n8n-nodes-berget-ai-chat

Configuration

1. Add the node to your workflow
2. Configure API settings:
   • API Key: Your Berget AI API key
   • Base URL: https://api.berget.ai/v1 (default)
   • Model: Choose from available models

Available Models

• Llama 3.1 8B Instruct
• Llama 3.3 70B Instruct
• GLM-4.6
• DeepSeek-OCR (vision model for image analysis)
• Mistral Small 3.1 24B Instruct 2503
• Qwen3 32B
• GPT-OSS-120B

Features

• ✅ Chat completion
• ✅ Streaming support
• ✅ Function calling
• ✅ JSON mode
• ✅ Formatted output
• ✅ System and user messages
• ✅ Temperature and other parameters

Examples

See examples/ folder for examples of how to use the node in different scenarios.

Testing

Quick Test

# Test node structure
npm test

# Test with real API
BERGET_API_KEY=your-key npm test

# Link locally for n8n testing
npm run test:local

Example Usage

// Basic chat completion
{
  "operation": "chat",
  "model": "meta-llama/Llama-3.1-8B-Instruct",
  "messages": [
    {"role": "user", "content": "Hello!"}
  ],
  "options": {
    "temperature": 0.7,
    "max_tokens": 100
  }
}

Self-Hosted n8n

Interested in running n8n in Sweden without data leaving EU? Berget AI offers self-hosted n8n solutions in our Kubernetes clusters. Contact us at kontakt@berget.ai for more information.