Use an open-source LLM (via HuggingFace)

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Important notice

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

1. Workflow Overview

This workflow demonstrates how to connect an open source model to a Basic LLM node. The workflow is triggered when a new manual chat message appears. The message is then run through a Language Mode...

Best for

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

Tools used

n8n-nodes-base.stickynote, @n8n/n8n-nodes-langchain.chattrigger, @n8n/n8n-nodes-langchain.chainllm, @n8n/n8n-nodes-langchain.lmopenhuggingfaceinference

Source and attribution

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

Original n8n.io source

1.1 Workflow description

Title: Use an open-source LLM (via HuggingFace)
Workflow name: Use an open-source LLM (via HuggingFace)

This workflow demonstrates how to connect an open-source model to a Basic LLM node.

The workflow is triggered when a new manual chat message appears. The message is then run through a Language Model Chain that is set up to process text with a specific prompt to guide the model's responses.

Note that open-source LLMs with a small number of parameters require slightly different prompting with more guidance to the model.

You can change the default Mistral-7B-Instruct-v0.1 model to any other LLM supported by HuggingFace. You can also connect other nodes, such as Ollama.

Note that to use this template, you need to be on n8n version 1.19.4 or later.

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 - Sticky Note

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

Block 2 - When chat message received

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

Block 3 - Basic LLM Chain

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

Block 4 - Hugging Face Inference Model

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

3. Summary Table

Workflow	Use an open-source LLM (via HuggingFace)
Complexity	beginner
Nodes	4
Categories	Engineering, AI Chatbot
Author	n8n Team
Published	16 Nov 2023

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/1980/1980.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 Use an open-source LLM (via HuggingFace) do?

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.

n8n Team

90 workflows

Nodes

n8n-nodes-base.stickynote @n8n/n8n-nodes-langchain.chattrigger @n8n/n8n-nodes-langchain.chainllm @n8n/n8n-nodes-langchain.lmopenhuggingfaceinference

Complexity

beginner

Published 16 Nov 2023

Likes 0

View on n8n.io Download Workflow

Install path: /data/workflows/1980/1980.json

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Use an open-source LLM (via HuggingFace)

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Sticky Note

Block 2 - When chat message received

Block 3 - Basic LLM Chain

Block 4 - Hugging Face Inference Model

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