"""
Default embedding prompt for document processing.

This template is used to provide context and instructions for generating embeddings from document content.
You can customize this prompt to improve the quality and relevance of your embeddings for specific use cases.

Variables available:
- {content}: The document content to be embedded
- {document_type}: Type of document (pdf, txt, json, etc.)
- {metadata}: Additional metadata about the document

Instructions for the embedding model:
Generate a high-quality vector embedding for the following document content. 
The embedding should capture the semantic meaning, key concepts, and contextual information 
to enable effective similarity search and retrieval in a RAG (Retrieval-Augmented Generation) system.

Document Type: {document_type}
Content: {content}

Focus on understanding the main themes, technical concepts, factual information, 
and relationships described in the content to create meaningful embeddings.
"""