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API Basics

The core types you’ll use most:

Index​

Create, configure, and query the vector index.

let dims = 768;
let mut idx = Index::new(dims, Metric::Cosine)?;

Key methods (common subset):​

  • insert(InsertItem) – insert if new id; error if exists
  • upsert(InsertItem) – insert or replace by id
  • delete(&str) – soft delete by id (tombstone)
  • search(&[f32], k) – top-k nearest neighbors
  • batch_search(&[&[f32]], k) – multiple queries in one call
  • size() – approximate number of active vectors
  • contains(&str) – check by id

InsertItem​

InsertItem::new("id", embedding)            // bare minimum
InsertItem::with_ttl("id", embedding, secs) // optional TTL on item

Similarity Metric​

  • 'Metric::Cosine'
  • 'Metric::Dot'

Choose Cosine for typical embedding models; Dot if your pipeline expects it.

Errors​

Most methods return VcalResult<T> = Result<T, VcalError>.

Errors cover invalid dims, missing ids, or internal index issues.