Unlock Advanced AI with Custom LangChain Code Nodes
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Empower your automation with custom LangChain agents and tools using n8n's powerful Code node. This example demonstrates building self-coded LLM chains and AI tools for sophisticated AI interactions.
About This Workflow
This n8n workflow showcases the advanced capabilities of integrating LangChain directly into your automation processes using the code node. You can now go beyond pre-built nodes to craft custom Language Model (LLM) chains and define your own AI tools. The example illustrates how to create a self-coded LLM chain by defining a PromptTemplate and connecting it to an OpenAI language model. Furthermore, it demonstrates the creation of a custom AI tool, such as a Wikipedia query tool, enabling your AI agents to leverage external information. This empowers you to build highly specialized and intelligent AI-driven workflows tailored to your unique needs.
Key Features
- Custom LLM Chains: Define and execute your own LLM chain logic using JavaScript and LangChain.
- Custom AI Tools: Create bespoke tools that your AI agents can utilize for specific tasks.
- Direct LangChain Integration: Seamlessly embed LangChain functionalities within your n8n workflows.
- Leverage OpenAI: Connect with OpenAI models for powerful language generation and understanding.
- Agent Orchestration: Build intelligent agents that can decide which tools to use to answer queries.
How To Use
- Trigger the Workflow: Initiate the workflow by clicking "Execute Workflow" via the
manualTriggernode. - Define LLM Chain Input: Use the
Setnode to define the input query for your custom LLM chain (e.g., "Tell me a joke"). - Create Custom LLM Chain: Configure the
Custom - LLM Chain Node(@n8n/n8n-nodes-langchain.code) by writing JavaScript code that defines aPromptTemplateand pipes it to an AI language model. Ensure you connect theOpenAInode'sai_languageModeloutput to theCustom - LLM Chain Node'sai_languageModelinput. - Set Agent Input: Use the
Set1node to define a separate input for the AI agent (e.g., "What year was Einstein born?"). - Define Custom AI Tool: Configure the
Custom - Wikipedianode (@n8n/n8n-nodes-langchain.code) to instantiate and return a LangChainWikipediaQueryRuntool. - Configure the Agent: Connect the
Set1node's output to theAgentnode. Also, connect theOpenAInode'sai_languageModeloutput and theCustom - Wikipedianode'sai_tooloutput to theAgentnode's respective inputs. - Execute and Observe: Run the workflow and observe the output generated by the custom LLM chain and the agent's interaction with the custom tool.
Apps Used
Workflow JSON
{
"id": "6a45d0c7-af3c-4df4-938a-72fa27b1f072",
"name": "Unlock Advanced AI with Custom LangChain Code Nodes",
"nodes": 20,
"category": "Marketing",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: 6a45d0c7-af3c...
About the Author
DevOps_Master_X
Infrastructure Expert
Specializing in CI/CD pipelines, Docker, and Kubernetes automations.
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