Automated workflow
Workflow Description
An intelligent workflow that combines chat triggers with LLM chains and an AI agent to handle complex queries intelligently. It processes large requests in batches while maintaining context through memory buffers and integrates external tools for enhanced responses.
How it works
- 1.Receive incoming chat messages via trigger
- 2.Pass input to LLM chain using Open Router model
- 3.Process tasks through intelligent AI agent
- 4.Split large queries into manageable batches
- 5.Maintain conversation context using memory buffer
- 6.Retrieve supplementary information from Wikipedia tool
Use cases
- Automated handling of complex customer inquiries
- Processing high-volume requests while preserving conversation history
- Intelligent search and information aggregation from external sources
Requirements
- Open Router API key configured
- n8n chat platform integration enabled
- Memory and context settings for extended sessions
Service Value
Ideal as a smart automation service combining integrations and AI to produce ready-to-use results.
Apps Used
Details
How to Use
- 1.Click "Download Template"
- 2.Open your n8n dashboard
- 3.Go to Workflows > Import from File
- 4.Select downloaded file and configure credentials
Nodes Used (17)
Chat Message Trigger
Chat Trigger
Generate Search Queries using LLM
LLM Chain
LLM Response Provider (OpenRouter)
Lm Chat Open Router
Parse and Chunk JSON Data
Code
Perform SerpAPI Search Request
HTTP Request
Perform Jina AI Analysis Request
HTTP Request
Format SerpAPI Organic Results
Code
Extract Relevant Context via LLM
Agent
Generate Comprehensive Research Report
Agent
Split Data for SerpAPI Batching
Split In Batches
Split Data for Jina AI Batching
Split In Batches
LLM Memory Buffer (Input Context)
Memory Buffer Window
LLM Memory Buffer (Report Context)
Memory Buffer Window
Fetch Wikipedia Information
Tool Wikipedia
Sticky Note: SerpAPI Setup
Sticky Note
Sticky Note: Jina AI Setup
Sticky Note
Sticky Note: OpenRouter API Setup
Sticky Note