feat: make diskann runnable

packages/leann-backend-hnsw/leann_backend_hnsw/hnsw_backend.py

@@ -142,12 +142,12 @@ class HNSWSearcher(BaseSearcher):
         self,
         query: np.ndarray,
         top_k: int,
+        zmq_port: Optional[int] = None,
         complexity: int = 64,
         beam_width: int = 1,
         prune_ratio: float = 0.0,
         recompute_embeddings: bool = True,
         pruning_strategy: Literal["global", "local", "proportional"] = "global",
-        expected_zmq_port: Optional[int] = None,
         batch_size: int = 0,
         **kwargs,
     ) -> Dict[str, Any]:
@@ -165,7 +165,7 @@ class HNSWSearcher(BaseSearcher):
                 - "global": Use global PQ queue size for selection (default)
                 - "local": Local pruning, sort and select best candidates
                 - "proportional": Base selection on new neighbor count ratio
-            expected_zmq_port: ZMQ port for embedding server
+            zmq_port: ZMQ port for embedding server communication. Must be provided if recompute_embeddings is True.
             batch_size: Neighbor processing batch size, 0=disabled (HNSW-specific)
             **kwargs: Additional HNSW-specific parameters (for legacy compatibility)
 
@@ -177,6 +177,11 @@ class HNSWSearcher(BaseSearcher):
         if not recompute_embeddings:
             if self.is_pruned:
                 raise RuntimeError("Recompute is required for pruned index.")
+        if recompute_embeddings:
+            if zmq_port is None:
+                raise ValueError(
+                    "zmq_port must be provided if recompute_embeddings is True"
+                )
 
         if query.dtype != np.float32:
             query = query.astype(np.float32)
@@ -184,7 +189,10 @@ class HNSWSearcher(BaseSearcher):
             faiss.normalize_L2(query)
 
         params = faiss.SearchParametersHNSW()
-        params.zmq_port = expected_zmq_port
+        if zmq_port is not None:
+            params.zmq_port = (
+                zmq_port  # C++ code won't use this if recompute_embeddings is False
+            )
         params.efSearch = complexity
         params.beam_size = beam_width