Datasets:
license: mit
tags:
- n8n
- workflow
- automation
- no-code
- low-code
- axolotl
- fine-tuning
- text-generation
task_categories:
- text-generation
language:
- en
size_categories:
- 1K<n<10K
n8n Workflow Templates Dataset
A curated collection of n8n workflow automation templates formatted for LLM fine-tuning in multiple formats.
Dataset Description
This dataset contains 2,737 n8n workflow templates from the official n8n template library, formatted in multiple formats for fine-tuning LLMs to generate n8n workflows.
Available Formats
Alpaca Format (
trainsplit)- Traditional instruction-input-output format
- Compatible with Axolotl and other Alpaca-based training frameworks
OpenAI Messages Format (
train_openaisplit)- Chat-based format with role-based messages
- Compatible with OpenAI fine-tuning API and similar chat-based training
Data Fields
Alpaca Format
| Field | Description |
|---|---|
| instruction | System prompt for n8n workflow generation |
| input | User's workflow requirements/description |
| output | Complete n8n workflow JSON |
OpenAI Messages Format
| Field | Description |
|---|---|
| messages | Array of message objects with role and content |
Each message object contains:
role: "user" or "assistant"content: The message content (instruction or workflow JSON)
System Prompt
All records share the same instruction:
You are an expert n8n workflow generation assistant. Your goal is to create valid, efficient, and error-free n8n workflow JSONs based on the user's requirements. Always output ONLY the valid JSON workflow.
Dataset Structure
Alpaca Format Example
{
"instruction": "You are an expert n8n workflow generation assistant...",
"input": "Create a workflow that retrieves Google Analytics data...",
"output": "{"id": "...", "nodes": [...], "connections": {...}}"
}
OpenAI Messages Format Example
{
"messages": [
{
"role": "user",
"content": "You are an expert n8n workflow generation assistant...\n\nCreate a workflow that retrieves Google Analytics data..."
},
{
"role": "assistant",
"content": "{"id": "...", "nodes": [...], "connections": {...}}"
}
]
}
Loading the Dataset
Using Hugging Face Datasets
from datasets import load_dataset
# Load Alpaca format
alpaca_dataset = load_dataset("mbakgun/n8nbuilder-n8n-workflows-dataset", split="train")
# Load OpenAI format
openai_dataset = load_dataset("mbakgun/n8nbuilder-n8n-workflows-dataset", split="train_openai")
# Load both
full_dataset = load_dataset("mbakgun/n8nbuilder-n8n-workflows-dataset")
Using Hugging Face Hub
from huggingface_hub import hf_hub_download
import json
# Download Alpaca format
alpaca_file = hf_hub_download(
repo_id="mbakgun/n8nbuilder-n8n-workflows-dataset",
filename="train.jsonl",
repo_type="dataset"
)
# Download OpenAI format
openai_file = hf_hub_download(
repo_id="mbakgun/n8nbuilder-n8n-workflows-dataset",
filename="train_openai.jsonl",
repo_type="dataset"
)
Fine-tuning
With Axolotl (Alpaca Format)
datasets:
- path: mbakgun/n8nbuilder-n8n-workflows-dataset
type: alpaca
split: train
With OpenAI Fine-tuning API (OpenAI Format)
from openai import OpenAI
client = OpenAI()
# Prepare data from Hugging Face
dataset = load_dataset("mbakgun/n8nbuilder-n8n-workflows-dataset", split="train_openai")
# Convert to OpenAI format and upload
training_file = client.files.create(
file=open("training_data.jsonl", "rb"),
purpose="fine-tune"
)
With Other Frameworks
Both formats can be easily converted to other training formats as needed.
Use Cases
- Fine-tuning LLMs to generate n8n workflows from natural language
- Training models to understand workflow automation patterns
- Building AI assistants for no-code/low-code automation
- Research on code generation and workflow automation
Statistics
| Metric | Value |
|---|---|
| Total Workflows | 2,737 |
| Formats | 2 (Alpaca, OpenAI Messages) |
| Splits | train (Alpaca), train_openai (OpenAI) |
License
MIT License
Acknowledgments
This dataset is currently maintained by n8nbuilder.dev — an AI-powered n8n workflow generation tool.
Data Sources & Attribution
- Template Source: All workflow templates in this dataset are sourced from n8n's public template gallery. Template creators retain all rights to their workflows.
- Indexing: Templates were indexed using n8n-mcp by @czlonkowski.
- n8n: n8n is the workflow automation platform that powers these templates.
If you are a template creator and have concerns about your template being included, please open an issue.
Citation
If you use this dataset, please cite:
@dataset{n8nbuilder_n8n_workflows_dataset_2025,
title={n8nbuilder - n8n workflow automation templates dataset},
year={2025},
url={https://huggingface.co/datasets/mbakgun/n8nbuilder-n8n-workflows-dataset},
note={Curated by n8nbuilder.dev}
}