Automated workflow
Workflow Description
Advanced automation system combining intelligent agents with document processing and persistent memory. Splits and transforms text into embeddings, stores them in a vector database, then answers queries using a smart agent with continuous conversation context.
How it works
- 1.Trigger workflow manually or via chat interface
- 2.Load and process documents by splitting them into chunks
- 3.Convert text to embeddings using Mistral language models
- 4.Store embeddings in Qdrant vector database for semantic search
- 5.Process user queries through an intelligent agent with memory and tools
- 6.Deliver responses via Twitter/X or other channels
Use cases
- Build a smart assistant that answers questions based on organized documents
- Automate responses to inquiries on social media while maintaining conversation context
- Process large volumes of documents and convert them into a searchable knowledge base
Requirements
- OpenAI and Mistral Cloud API keys
- Qdrant server for vector storage
- Twitter/X account for automated publishing (optional)
- Documents in supported formats (PDF, TXT, DOCX, etc.)
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 (38)
When clicking ‘Test workflow’
Manual Trigger
Embeddings Mistral Cloud
Embeddings Mistral Cloud
Default Data Loader
Document Default Data Loader
Recursive Character Text Splitter
Text Splitter Recursive Character Text Splitter
Get Tax Code Zip File
HTTP Request
Extract Zip Files
Compression
Files as Items
Split Out
Extract PDF Contents
Extract From File
Extract From Chapter
Set
Map To Sections
Set
Execute Workflow Trigger
Execute Workflow Trigger
Get Mistral Embeddings
HTTP Request
Content Chunking @ 50k Chars
Set
Split Out Chunks
Split Out
For Each Section...
Split In Batches
Sections To List
Split Out
Only Valid Sections
Filter
Use Qdrant Search API1
HTTP Request
Use Qdrant Scroll API
HTTP Request
Get Search Response
Set
Sticky Note
Sticky Note
Sticky Note1
Sticky Note
Sticky Note2
Sticky Note
Qdrant Vector Store
Vector Store Qdrant
Sticky Note3
Sticky Note
Sticky Note4
Sticky Note
AI Agent
Agent
Window Buffer Memory
Memory Buffer Window
When chat message received
Chat Trigger
Window Buffer Memory1
Memory Buffer Window
OpenAI Chat Model
OpenAI
1sec
Wait
Ask Tool
Tool Workflow
Search Tool
Tool Workflow
Switch
Switch
Get Ask Response
Set
Sticky Note5
Sticky Note
Sticky Note6
Sticky Note