Uploading documents
Add documents to a collection to make them searchable. Documents are automatically chunked and embedded using the collection’s configured model.
Document format
Section titled “Document format”Each document contains the following fields:
| Field | Required | Description |
|---|---|---|
content | Yes | The text content (10—10,000 characters) |
metadata | No | Key-value pairs for filtering and context |
searchableFields | No | Additional fields to include in search |
Uploading documents
Section titled “Uploading documents”Navigate to a collection from the Vector Database page, then use the upload interface to add documents. You can upload individual documents or batches.
Auto-chunking
Section titled “Auto-chunking”Large documents are automatically split into smaller chunks for more precise search results. You can configure chunking behaviour with the following settings:
| Setting | Default | Range | Description |
|---|---|---|---|
autoChunk | true | — | Enable automatic chunking |
chunkSize | 1000 | 500—2000 | Target characters per chunk |
chunkOverlap | 200 | 0—500 | Overlap between consecutive chunks |
Batch upload
Section titled “Batch upload”Upload up to 100 documents in a single request. Each document’s content must be between 10 and 10,000 characters.
Metadata
Section titled “Metadata”Attach key-value metadata to documents for additional context. Metadata is returned with search results and can help agents understand the source and context of retrieved documents.
{ "content": "Your document text here...", "metadata": { "source": "knowledge-base", "category": "security", "lastUpdated": "2025-01-15" }}Next steps
Section titled “Next steps”- Semantic search — query your documents using natural language or vectors
- Agent configuration — assign collections to agents for retrieval-augmented generation