feat(adk): add vector memory support for psqlpy and PostgreSQL ADBC

[cofin]

Summary

The psqlpy and ADBC ADK memory stores accept StoredMemory.embedding and an embedding search argument through the shared public contract, but currently ignore both.

• PsqlpyADKMemoryStore creates no vector column, omits embeddings from inserts, and performs text-only searches.
• AdbcADKMemoryStore is multi-dialect and reduced-scope; its PostgreSQL path likewise has no vector column or search branch and returns embedding=None.

This makes PostgreSQL vector-memory behavior inconsistent across SQLSpec adapters and silently discards caller data.

Proposed behavior

Add PostgreSQL ADK vector-memory support for psqlpy and the PostgreSQL ADBC backend while preserving reduced-scope behavior for non-PostgreSQL ADBC drivers.

• Persist nullable embeddings in owner and non-owner insert paths.
• Add vector-only nearest-neighbor search with null embeddings excluded.
• Use codec-independent parameter binding. Psqlpy supports explicit SQL casts; determine and document the portable ADBC PostgreSQL binding representation rather than assuming native pgvector codecs.
• Return stored embeddings when the backend exposes them.
• Do not silently ignore a supplied embedding on an unsupported ADBC backend; fail clearly or expose an explicit capability boundary.
• Decide whether pg_textsearch BM25/hybrid search should reach parity in the same implementation or remain a separately declared capability.

Acceptance criteria

• Unit tests cover SQL, nullable embeddings, owner-column parameter ordering, and vector query operands for both adapters.
• PostgreSQL integrations insert via the public memory-store API and assert nearest-neighbor IDs/order with client pgvector codecs disabled.
• ADBC tests cover PostgreSQL vector decoding and unsupported non-PostgreSQL behavior.
• Adapter documentation and the ADK backend matrix accurately describe vector and BM25 capabilities.
• No public method signatures or shared record types change.

Related: #726, #727