Insert and retrieve documents with AI-powered search
Workflow Description
Automation that accepts documents via manual trigger or HTTP request, splits them into text chunks, converts them to OpenAI embeddings, stores them in Milvus vector database, then retrieves relevant sections for accurate AI-powered answers using language models.
How it works
- 1.Receive documents through manual trigger or HTTP endpoint
- 2.Split documents into smaller text chunks using recursive character splitting
- 3.Convert each chunk into numerical vectors via OpenAI embeddings
- 4.Store vectors and original text in Milvus vector database
- 5.Retrieve most relevant chunks when a question is submitted
- 6.Generate answers using OpenAI language model based on retrieved context
Use cases
- Build an intelligent search engine for internal company documents
- Create a question-answering system based on organizational knowledge base
- Analyze PDF files or HTML content and extract specific information on demand
- Develop an AI assistant that answers employee queries from stored documents
Requirements
- Valid OpenAI API key
- Access to Milvus vector database server or local instance
- Manual trigger or HTTP endpoint configured to receive documents
- Full access permissions in n8n platform
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 (25)
When clicking "Execute Workflow"
Manual Trigger
Fetch Essay List
HTTP Request
Extract essay names
HTML Page
Split out into items
Split Out
Fetch essay texts
HTTP Request
Limit to first 3
Limit
Extract Text Only
HTML Page
Sticky Note3
Sticky Note
Sticky Note5
Sticky Note
Recursive Character Text Splitter1
Text Splitter Recursive Character Text Splitter
Generate response
Set
Compose citations
Set
Answer the query based on chunks
Information Extractor
Prepare chunks
Code
Set max chunks to send to model
Set
Embeddings OpenAI2
OpenAI
When chat message received
Chat Trigger
Sticky Note1
Sticky Note
Milvus Vector Store in retrieval
Vector Store Milvus
Milvus Vector Store
Vector Store Milvus
Sticky Note
Sticky Note
Sticky Note2
Sticky Note
Embeddings OpenAI
OpenAI
Default Data Loader
Document Default Data Loader
OpenAI Chat Model
OpenAI