Skip to main content
The Knowledge Base lets you upload documents that your agents can reference during conversations. Using vector search and RAG (Retrieval-Augmented Generation), agents find relevant information from your documents to provide accurate, grounded responses.

​
How It Works

  1. Upload documents (PDF, TXT, MD, DOCX)
  2. Processing — Documents are chunked and converted into vector embeddings
  3. Storage — Embeddings are stored in PostgreSQL with pgvector
  4. Retrieval — When relevant, agents search your knowledge base and include findings in their responses

​
Adding Documents

1

Navigate to Knowledge

Go to your agent’s settings and select the Knowledge tab.
2

Upload files

Drag and drop files or click to browse. Supported formats:
FormatExtensions
PDF.pdf
Text.txt, .md
Documents.docx
Spreadsheets.csv, .xlsx
3

Wait for processing

Documents are automatically chunked and embedded. This may take a few moments for large files.
4

Verify

Your documents appear in the knowledge list. You can preview chunks and test search queries.

​
How Agents Use Knowledge

When you ask a question, the agent:
  1. Converts your question into a vector embedding
  2. Searches the knowledge base for semantically similar chunks
  3. Includes the most relevant chunks as context
  4. Generates a response grounded in your documents
For best results, upload well-structured documents with clear headings and sections. The chunking algorithm preserves document structure.

​
Managing Knowledge

  • Add new documents at any time
  • Remove outdated documents
  • Re-sync to update embeddings after document changes
  • Test search queries to verify retrieval quality