LangChain - Example - Code Node Example

Automated workflow on LangChain that integrates with Sticky Note, enabling users to generate responses from OpenAI based on custom prompts. Triggered manually, it efficiently processes queries like jokes and historical questions, enhancing user interaction and providing instant information retrieval.

7/8/2025
10 nodes
Medium
snf16n0p2urgp838manualmediumlangchainsticky note
Categories:
Manual TriggeredMedium Workflow
Integrations:
LangChainSticky Note

Target Audience

  • Developers looking to automate tasks using LangChain and n8n.
    - Data Scientists who want to integrate AI models into their workflows.
    - Product Managers seeking to streamline processes and make data-driven decisions.
    - Researchers needing a quick way to query information from various sources.
    - Educators who want to create interactive learning experiences using AI.

    • Problem Solved

    This workflow addresses the challenge of integrating AI-driven functionalities into automated processes. It allows users to easily trigger and execute queries, retrieve information, and utilize AI models without extensive coding knowledge. By leveraging LangChain and n8n, it simplifies the interaction with complex AI tools and enhances productivity.

    Workflow Steps

  • Step 1: The workflow begins with a manual trigger, allowing users to execute it at their convenience.
    - Step 2: Two Set nodes are used to define specific queries: one for a joke and another for Einstein's birth year.
    - Step 3: The queries are passed to a Custom - LLM Chain Node, which processes the input using a language model, generating responses based on the prompts provided.
    - Step 4: The OpenAI node is connected to the LLM Chain Node to enhance the processing capabilities with advanced AI functionalities.
    - Step 5: The Chat OpenAI node and Custom - Wikipedia node are integrated to provide additional AI tools and resources, allowing for broader queries.
    - Step 6: Finally, the Agent node coordinates the various components, ensuring smooth interactions and outputs from the AI tools, enhancing the overall workflow efficiency.

    • Customization Guide

  • To customize the workflow, users can modify the Set nodes to include different queries or tasks relevant to their needs.
    - Users can replace the Custom - LLM Chain Node code to implement specific logic or use different AI models.
    - The Sticky Note nodes can be adjusted to display different content or instructions for users, enhancing usability.
    - Users can integrate additional nodes or external APIs to expand the functionality of the workflow, tailoring it to their unique requirements.