AI Agents

Build an intelligent agent processing inquiries with memory and tools

17 nodes 185 87 Automatic trigger
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Workflow Description

Advanced template creating an AI-powered agent that receives chat inquiries, processes them through intelligent language model chains, maintains conversation context, searches Wikipedia for accurate answers, and handles multiple requests in parallel batches.

How it works

  1. 1.Receive messages through real-time chat trigger
  2. 2.Process queries via collaborative language model chain
  3. 3.Search Wikipedia and retrieve relevant information
  4. 4.Maintain conversation context in memory buffer
  5. 5.Handle multiple requests in parallel batches
  6. 6.Deliver intelligent responses directly to users

Use cases

  • Smart assistant answering employee questions with current information
  • Customer support bot preserving conversation history and context
  • Internal search engine gathering data from reliable sources

Requirements

  • Configure OpenRouter API key for language model access
  • Enable Wikipedia search tool integration
  • Understand basic intelligent agent design and memory management

Service Value

Ideal as a smart automation service combining integrations and AI to produce ready-to-use results.

Apps Used

Chat Trigger LLM Chain Lm Chat Open Router AI Agent Split In Batches Memory Tool

Details

Trigger Automatic trigger
Nodes 17
Apps 7
Views 185
Downloads 87

How to Use

  1. 1.Click "Download Template"
  2. 2.Open your n8n dashboard
  3. 3.Go to Workflows > Import from File
  4. 4.Select downloaded file and configure credentials

Nodes Used (17)

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Chat Message Trigger

Chat Trigger

#1

Generate Search Queries using LLM

LLM Chain

#2

LLM Response Provider (OpenRouter)

Lm Chat Open Router

#3

Parse and Chunk JSON Data

Code

#4

Perform SerpAPI Search Request

HTTP Request

#5

Perform Jina AI Analysis Request

HTTP Request

#6

Format SerpAPI Organic Results

Code

#7

Extract Relevant Context via LLM

Agent

#8

Generate Comprehensive Research Report

Agent

#9

Split Data for SerpAPI Batching

Split In Batches

#10

Split Data for Jina AI Batching

Split In Batches

#11

LLM Memory Buffer (Input Context)

Memory Buffer Window

#12

LLM Memory Buffer (Report Context)

Memory Buffer Window

#13

Fetch Wikipedia Information

Tool Wikipedia

#14

Sticky Note: SerpAPI Setup

Sticky Note

#15

Sticky Note: Jina AI Setup

Sticky Note

#16

Sticky Note: OpenRouter API Setup

Sticky Note

#17