feat(ts-sdk): add Vertex AI Vector Search vector store

Summary

The Python SDK supports Vertex AI Vector Search as a vector store provider, but the TypeScript OSS SDK (mem0ai/oss) does not. Add it to bring the TS SDK to parity.

Python reference	mem0/vector_stores/vertex_ai_vector_search.py
Registered in (Python)	mem0/utils/factory.py (VectorStoreFactory)
Target file (TypeScript)	mem0-ts/src/oss/src/vector_stores/vertex_ai_vector_search.ts
Suggested implementation	Use @google-cloud/aiplatform (index + deployed index endpoint).

Requirements

• Implement VertexAIVectorSearch in mem0-ts/src/oss/src/vector_stores/vertex_ai_vector_search.ts, extending VectorStore (mem0-ts/src/oss/src/vector_stores/base.ts) and mirroring the Python provider's behavior (insert / search / get / update / delete / list / reset).
• Register the "vertex_ai_vector_search" provider in mem0-ts/src/oss/src/utils/factory.ts (VectorStoreFactory).
• Add config typing in mem0-ts/src/oss/src/types/.
• Add a unit test under mem0-ts/src/oss/src/tests/.
• Add @google-cloud/aiplatform to mem0-ts/package.json (optional/peer dependency, lazy-imported like other providers).
• Update docs under docs/ if this provider is user-facing.

Reference pattern

Mirror an existing TS provider: vector_stores/qdrant.ts.

Notes

Heaviest vector store — requires a created index and a deployed index endpoint. Mirror mem0/vector_stores/vertex_ai_vector_search.py. GCP auth.

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Part of the TypeScript ↔ Python SDK provider-parity effort. One provider per issue (atomic).