Requirements for RAG in Ollamac

To use RAG features in Ollamac, you need to have an embedding model installed and configured:

Installing an Embedding Model

  1. Install via Ollama: Choose an embedding model from the Ollama embedding models library

  2. Popular Options:

    • nomic-embed-text - Good general-purpose embedding model
    • mxbai-embed-large - High-quality embeddings for better accuracy
    • all-minilm - Lightweight option for faster processing

  3. Installation Command: Run in terminal:

    ollama pull nomic-embed-text

Enabling in Ollamac Settings

  1. Open Ollamac Settings
  2. Navigate to the RAG/Documents section
  3. Select your installed embedding model from the dropdown
  4. Enable RAG functionality

Once configured, you can start uploading documents and asking questions that will be answered using your specific content combined with the AI's general knowledge.

Common Use Cases

  • Research: Query academic papers, reports, and research documents
  • Business: Analyze company documents, policies, and procedures
  • Learning: Study from textbooks, notes, and educational materials
  • Legal: Reference contracts, regulations, and legal documents
  • Technical: Search through documentation, manuals, and specifications