Custom LangChain agent written in JavaScript

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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 has multiple functionalities. It starts with a manual trigger, "When clicking 'Execute Workflow'", that activates two separate paths. The first path takes a preset string "Tell me a j...

Best for

Engineering automation workflows
AI RAG automation workflows
intermediate n8n builders looking for reusable templates

Tools used

n8n-nodes-base.stickynote, n8n-nodes-base.manualtrigger, n8n-nodes-base.set, @n8n/n8n-nodes-langchain.code, @n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.toolcode

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: Custom LangChain agent written in JavaScript
Workflow name: Custom LangChain agent written in JavaScript

This workflow has multiple functionalities. It starts with a manual trigger, "When clicking 'Execute Workflow'", that activates two separate paths.

The first path takes a preset string "Tell me a joke" and processes it through a custom Language Learning Model (LLM) chain node. This node interacts with an OpenAI node for query processing.

The second path takes another preset string "What year was Einstein born?" and passes it to an "Agent" node. This agent further interacts with a Chat OpenAI node and a custom Wikipedia node to produce the required information.

The workflow uses both built-in and custom nodes, and integrates with OpenAI for both paths. It's built for experimenting with language models, specifically in the context of conversational agents and information retrieval.

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 clicking "Execute Workflow"

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

Block 3 - Sticky Note1

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

Block 4 - Set2

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 5 - Custom - LLM Chain Node1

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

Block 6 - OpenAI Chat Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.2

Block 7 - Set3

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 8 - AI Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 1.8

Block 9 - OpenAI Chat Model1

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.2

Block 10 - Custom - Wikipedia1

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

3. Summary Table

Workflow	Custom LangChain agent written in JavaScript
Complexity	intermediate
Nodes	10
Categories	Engineering, AI RAG
Author	n8n Team
Published	03 Oct 2023

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/1955/1955.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 RAG workflows

Frequently asked questions

What does Custom LangChain agent written in JavaScript 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 RAG use case.

n8n Team

90 workflows

Nodes

n8n-nodes-base.stickynote n8n-nodes-base.manualtrigger n8n-nodes-base.set @n8n/n8n-nodes-langchain.code @n8n/n8n-nodes-langchain.lmchatopenai @n8n/n8n-nodes-langchain.agent @n8n/n8n-nodes-langchain.toolcode

Complexity

intermediate

Published 03 Oct 2023

Likes 0

View on n8n.io Download Workflow

Install path: /data/workflows/1955/1955.json

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Custom LangChain agent written in JavaScript

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 clicking "Execute Workflow"

Block 3 - Sticky Note1

Block 4 - Set2

Block 5 - Custom - LLM Chain Node1

Block 6 - OpenAI Chat Model

Block 7 - Set3

Block 8 - AI Agent

Block 9 - OpenAI Chat Model1

Block 10 - Custom - Wikipedia1

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