Embeddings¶

Generate and manage vector embeddings.

📚 Documentation¶

• Local GGUF Models - Run models locally
• Ollama Integration - Use Ollama for embeddings
• OpenAI Integration - Use OpenAI API
• OrcaRouter Integration - Use OrcaRouter's OpenAI-compatible API
• Voyage AI - Use Voyage embeddings, contextualized chunking, and reranking

🎯 What are Embeddings?¶

Embeddings are vector representations of text that capture semantic meaning, enabling: - Semantic search - Similarity comparison - K-Means clustering - Classification

Quick Start¶

With Ollama¶

# Start Ollama
ollama pull mxbai-embed-large

# Configure NornicDB
export NORNICDB_EMBEDDING_PROVIDER=ollama
export NORNICDB_EMBEDDING_MODEL=mxbai-embed-large

With OpenAI¶

# Configure NornicDB
export NORNICDB_EMBEDDING_PROVIDER=openai
export NORNICDB_EMBEDDING_API_KEY=your-api-key
export NORNICDB_EMBEDDING_MODEL=text-embedding-3-small

With OrcaRouter¶

export NORNICDB_EMBEDDING_PROVIDER=orca
export NORNICDB_EMBEDDING_API_KEY=your-orca-key

### With Voyage AI

```bash
 export NORNICDB_EMBEDDING_PROVIDER=voyage
export NORNICDB_EMBEDDING_API_KEY=pa-...
export NORNICDB_EMBEDDING_MODEL=voyage-4-large
export NORNICDB_EMBEDDING_DIMENSIONS=1024

📖 Learn More¶

• Local GGUF - Run models offline
• Ollama Setup - Easy local embeddings
• OpenAI API - Cloud embeddings
• OrcaRouter - Routed hosted embeddings
• Voyage AI - Managed embeddings and reranking

Get started → Ollama Integration