Context

What is a flat vector search index?

• A flat vector search index is a new indexingMethod option on MongoDB Vector Search indexes that lets you choose between hnsw (default) and flat per vector field in the index definition.
  https://docs.google.com/document/d/1PFVMMq6W7m2ofaPw6U4KRCf2o9JQyKz_xrFsjzuVLFY https://www.mongodb.com/docs/atlas/atlas-vector-search/vector-search-type/
• When indexingMethod: "flat" is used, MongoDB performs an exhaustive search over the (typically filtered) subset of vectors instead of traversing an HNSW graph, which is specifically optimized for multitenant workloads with many tenants but relatively few vectors per tenant (≈<10K) where queries are always filtered by tenant/namespace.

What ODMs or Frameworks do we need to ensure support of this tool?

Django MongoDB / Atlas Vector Search integration must allow configuring indexingMethod on vector fields in index definitions (either as a first-class option or via pass-through kwargs).

Acceptance Criteria

• API support in the Django Integration with documentation and a reach out to PM team for a potential GTM push