two queue filtered search with max effort

[hailangx]

Summary

• Introduces a new two-queue search algorithm for graph-based vector search that decouples exploration from
  filter evaluation, improving recall for low-selectivity filtered queries
• Adds a callback-based filter (GarnetFilterProvider) to diskann-garnet alongside the existing bitmap filter, enabling
  per-candidate FFI filter evaluation from Garnet/C#

Motivation

The existing beta-filtered search works well when filters are moderately selective, but struggles with low-selectivity
filters where most candidates are rejected. In those cases, the search converges prematurely because pruning is based
on distance to filtered results that haven't been found yet. The two-queue approach keeps exploration broad until
enough filtered results are accumulated.

Design

Two-Queue Search (two_queue_search.rs)

• Maintains two separate queues: a min-heap (candidates) for exploration ordered by distance, and a max-heap
  (filtered_results) for filter-passing neighbors
• All graph neighbors are explored regardless of filter status; only filter-passing nodes are added to filtered_results
• Convergence: terminates when filtered_results has enough results and the closest unexplored candidate is farther than
  the worst filtered result
• Supports a max_candidates hop limit as a safety cap and result_size_factor (default 10) to control result queue
  capacity (k * result_size_factor)
• Reports termination reason via TwoQueueTermination enum (Exhausted, MaxCandidates, Converged, FilterTerminated)

Benchmark

• Todo