IndexConfig

Number of dimensions in the embedding vectors.

Common embedding model dimensions:

• OpenAI text-embedding-3-large: 256, 1024, or 3072
• OpenAI text-embedding-3-small: 512 or 1536
• OpenAI text-embedding-ada-002: 1536
• Cohere embed-english-v3.0: 1024
• Cohere embed-english-light-v3.0: 384
• Cohere embed-multilingual-v3.0: 1024
• Cohere embed-multilingual-light-v3.0: 384

The embeddings model to use for generating vectors. This should be a LangChain Embeddings implementation.

Fields to extract text from for embedding generation.

Path syntax supports:

• Simple field access: "field"
• Nested fields: "metadata.title"
• Array indexing:
  • All elements: "chapters[*].content"
  • Specific index: "authors[0].name"
  • Last element: "array[-1]"