Search branch content using a pre-computed embedding vector. Generate embeddings client-side using OpenAI, Anthropic, or another embedding provider.
Documentation Index
Fetch the complete documentation index at: https://veryfront.com/docs/llms.txt
Use this file to discover all available pages before exploring further.
Use a JWT bearer token or a Veryfront API key in the Authorization header.
Project ID, slug, or domain from the authenticated context.
Branch name or ID. Use main to search the default project state.
Pre-computed query embedding vector.
768 - 4096 elementsEmbedding vector dimension: 768, 1024, 1536, 3072, or 4096.
768 Maximum search results to return, from 1 to 100.
1 <= x <= 100Opaque cursor returned from page_info.next.
Minimum similarity score for returned semantic matches.
0 <= x <= 1Search results.