Knowledge Management
D.Hub's Knowledge module is a platform that transforms unstructured data into searchable knowledge.
Core Features
The Knowledge module provides the following features:
- Document Collection: Collect data from various sources including web crawling, file uploads, and manual input
- AI Chat: Have conversations with AI about collected knowledge using RAG (Retrieval-Augmented Generation)
- Search Test: Validate knowledge quality using Vector, Full-Text, and Hybrid search modes
- Knowledge Settings: Manage storage targets, embedding models, and metadata
Data Sources
Knowledge can collect data through three methods:
| Source | Description | Supported Formats |
|---|---|---|
| Web Crawling | Automatically collect web pages based on URLs | HTML, dynamic pages (JS rendering) |
| File Upload | Upload document files directly for processing | PDF, DOCX, PPTX, XLSX, HTML, TXT, MD |
| Manual Input | Write and register text chunks directly | Free-form text |
Multi-Store Architecture
Collected data is simultaneously stored in up to three stores depending on the purpose:
| Store | Engine | Purpose |
|---|---|---|
| Vector DB | Vector search engine | Semantic similarity search (embedding vectors) |
| Text DB | Text search engine | Keyword-based full-text search (BM25) |
| Graph DB | Graph database | Entity/relationship-based graph exploration |
tip
You can select storage targets when creating a Knowledge. In most cases, the Vector + Text combination is most effective.
Knowledge Detail Screen
When you select a Knowledge, a detail screen with the following 4 tabs is displayed:
| Tab | Description |
|---|---|
| Documents | Manage collected document list and add new documents |
| Chat | Ask questions about knowledge via RAG-based AI chat |
| Search | Test search queries and verify result quality |
| Settings | Manage metadata, storage options, and embedding models |
Next Steps
- Managing Knowledges - Create, list, and delete Knowledges
- Web Crawling - Automatic web page collection
- File Upload - Document file upload and processing
- Manual Documents - Write text chunks directly
- AI Chat - RAG-based conversation
- Search Test - Search quality validation
- Settings - Knowledge settings management
- Chunking and Options - Chunking strategies and embedding model reference