Knowledge Base

Train your agent with documents and content

Overview

The Knowledge Base uses RAG (Retrieval-Augmented Generation) to give your agent access to your business content. Documents are split into chunks, converted to vector embeddings, and stored for semantic search.

Navigate to the Knowledge Base tab in the agent panel. Here you choose which data the agent will use for its responses.

Adding Content

Documents

Upload files in supported formats:

• PDF
• DOCX
• TXT

URLs

Provide web page URLs. Revol will scrape the content and add it to the knowledge base.

Text

Add content directly as text blocks.

How RAG Works

1. Upload

   You upload a document or add content.

2. Chunking

   Content is split into manageable chunks.

3. Embedding

   Each chunk is converted to a vector embedding using OpenAI’s text-embedding-3-small model.

4. Storage

   Embeddings are stored in PostgreSQL with pgvector extension.

5. Retrieval

   When a user asks a question, the most similar chunks are retrieved using cosine similarity.

6. Generation

   Retrieved chunks are injected into the LLM prompt as context.

Storage Limits

Plan	Knowledge Docs	Embedding Tokens
Free	10	100,000
Premium	100	1,000,000
Professional	1,000	5,000,000