merge: finalize compat resolution (delegate to PassageManager; keep relative hints in meta); resolve conflicts

packages/leann-backend-diskann/leann_backend_diskann/__init__.py

@@ -1 +1,7 @@
 from . import diskann_backend as diskann_backend
+from . import graph_partition
+
+# Export main classes and functions
+from .graph_partition import GraphPartitioner, partition_graph
+
+__all__ = ["GraphPartitioner", "diskann_backend", "graph_partition", "partition_graph"]

packages/leann-backend-diskann/leann_backend_diskann/diskann_backend.py

@@ -22,6 +22,11 @@ logger = logging.getLogger(__name__)
 @contextlib.contextmanager
 def suppress_cpp_output_if_needed():
     """Suppress C++ stdout/stderr based on LEANN_LOG_LEVEL"""
+    # In CI we avoid fiddling with low-level file descriptors to prevent aborts
+    if os.getenv("CI") == "true":
+        yield
+        return
+
     log_level = os.getenv("LEANN_LOG_LEVEL", "WARNING").upper()
 
     # Only suppress if log level is WARNING or higher (ERROR, CRITICAL)
@@ -137,6 +142,71 @@ class DiskannBuilder(LeannBackendBuilderInterface):
     def __init__(self, **kwargs):
         self.build_params = kwargs
 
+    def _safe_cleanup_after_partition(self, index_dir: Path, index_prefix: str):
+        """
+        Safely cleanup files after partition.
+        In partition mode, C++ doesn't read _disk.index content,
+        so we can delete it if all derived files exist.
+        """
+        disk_index_file = index_dir / f"{index_prefix}_disk.index"
+        beam_search_file = index_dir / f"{index_prefix}_disk_beam_search.index"
+
+        # Required files that C++ partition mode needs
+        # Note: C++ generates these with _disk.index suffix
+        disk_suffix = "_disk.index"
+        required_files = [
+            f"{index_prefix}{disk_suffix}_medoids.bin",  # Critical: assert fails if missing
+            # Note: _centroids.bin is not created in single-shot build - C++ handles this automatically
+            f"{index_prefix}_pq_pivots.bin",  # PQ table
+            f"{index_prefix}_pq_compressed.bin",  # PQ compressed vectors
+        ]
+
+        # Check if all required files exist
+        missing_files = []
+        for filename in required_files:
+            file_path = index_dir / filename
+            if not file_path.exists():
+                missing_files.append(filename)
+
+        if missing_files:
+            logger.warning(
+                f"Cannot safely delete _disk.index - missing required files: {missing_files}"
+            )
+            logger.info("Keeping all original files for safety")
+            return
+
+        # Calculate space savings
+        space_saved = 0
+        files_to_delete = []
+
+        if disk_index_file.exists():
+            space_saved += disk_index_file.stat().st_size
+            files_to_delete.append(disk_index_file)
+
+        if beam_search_file.exists():
+            space_saved += beam_search_file.stat().st_size
+            files_to_delete.append(beam_search_file)
+
+        # Safe to delete!
+        for file_to_delete in files_to_delete:
+            try:
+                os.remove(file_to_delete)
+                logger.info(f"✅ Safely deleted: {file_to_delete.name}")
+            except Exception as e:
+                logger.warning(f"Failed to delete {file_to_delete.name}: {e}")
+
+        if space_saved > 0:
+            space_saved_mb = space_saved / (1024 * 1024)
+            logger.info(f"💾 Space saved: {space_saved_mb:.1f} MB")
+
+            # Show what files are kept
+            logger.info("📁 Kept essential files for partition mode:")
+            for filename in required_files:
+                file_path = index_dir / filename
+                if file_path.exists():
+                    size_mb = file_path.stat().st_size / (1024 * 1024)
+                    logger.info(f"  - {filename} ({size_mb:.1f} MB)")
+
     def build(self, data: np.ndarray, ids: list[str], index_path: str, **kwargs):
         path = Path(index_path)
         index_dir = path.parent
@@ -151,6 +221,17 @@ class DiskannBuilder(LeannBackendBuilderInterface):
         _write_vectors_to_bin(data, index_dir / data_filename)
 
         build_kwargs = {**self.build_params, **kwargs}
+
+        # Extract is_recompute from nested backend_kwargs if needed
+        is_recompute = build_kwargs.get("is_recompute", False)
+        if not is_recompute and "backend_kwargs" in build_kwargs:
+            is_recompute = build_kwargs["backend_kwargs"].get("is_recompute", False)
+
+        # Flatten all backend_kwargs parameters to top level for compatibility
+        if "backend_kwargs" in build_kwargs:
+            nested_params = build_kwargs.pop("backend_kwargs")
+            build_kwargs.update(nested_params)
+
         metric_enum = _get_diskann_metrics().get(
             build_kwargs.get("distance_metric", "mips").lower()
         )
@@ -185,6 +266,30 @@ class DiskannBuilder(LeannBackendBuilderInterface):
                     build_kwargs.get("pq_disk_bytes", 0),
                     "",
                 )
+
+            # Auto-partition if is_recompute is enabled
+            if build_kwargs.get("is_recompute", False):
+                logger.info("is_recompute=True, starting automatic graph partitioning...")
+                from .graph_partition import partition_graph
+
+                # Partition the index using absolute paths
+                # Convert to absolute paths to avoid issues with working directory changes
+                absolute_index_dir = Path(index_dir).resolve()
+                absolute_index_prefix_path = str(absolute_index_dir / index_prefix)
+                disk_graph_path, partition_bin_path = partition_graph(
+                    index_prefix_path=absolute_index_prefix_path,
+                    output_dir=str(absolute_index_dir),
+                    partition_prefix=index_prefix,
+                )
+
+                # Safe cleanup: In partition mode, C++ doesn't read _disk.index content
+                # but still needs the derived files (_medoids.bin, _centroids.bin, etc.)
+                self._safe_cleanup_after_partition(index_dir, index_prefix)
+
+                logger.info("✅ Graph partitioning completed successfully!")
+                logger.info(f"  - Disk graph: {disk_graph_path}")
+                logger.info(f"  - Partition file: {partition_bin_path}")
+
         finally:
             temp_data_file = index_dir / data_filename
             if temp_data_file.exists():
@@ -213,7 +318,26 @@ class DiskannSearcher(BaseSearcher):
 
             # For DiskANN, we need to reinitialize the index when zmq_port changes
             # Store the initialization parameters for later use
-            full_index_prefix = str(self.index_dir / self.index_path.stem)
+            # Note: C++ load method expects the BASE path (without _disk.index suffix)
+            # C++ internally constructs: index_prefix + "_disk.index"
+            index_name = self.index_path.stem  # "simple_test.leann" -> "simple_test"
+            diskann_index_prefix = str(self.index_dir / index_name)  # /path/to/simple_test
+            full_index_prefix = diskann_index_prefix  # /path/to/simple_test (base path)
+
+            # Auto-detect partition files and set partition_prefix
+            partition_graph_file = self.index_dir / f"{index_name}_disk_graph.index"
+            partition_bin_file = self.index_dir / f"{index_name}_partition.bin"
+
+            partition_prefix = ""
+            if partition_graph_file.exists() and partition_bin_file.exists():
+                # C++ expects full path prefix, not just filename
+                partition_prefix = str(self.index_dir / index_name)  # /path/to/simple_test
+                logger.info(
+                    f"✅ Detected partition files, using partition_prefix='{partition_prefix}'"
+                )
+            else:
+                logger.debug("No partition files detected, using standard index files")
+
             self._init_params = {
                 "metric_enum": metric_enum,
                 "full_index_prefix": full_index_prefix,
@@ -221,8 +345,14 @@ class DiskannSearcher(BaseSearcher):
                 "num_nodes_to_cache": kwargs.get("num_nodes_to_cache", 0),
                 "cache_mechanism": 1,
                 "pq_prefix": "",
-                "partition_prefix": "",
+                "partition_prefix": partition_prefix,
             }
+
+            # Log partition configuration for debugging
+            if partition_prefix:
+                logger.info(
+                    f"✅ Detected partition files, using partition_prefix='{partition_prefix}'"
+                )
             self._diskannpy = diskannpy
             self._current_zmq_port = None
             self._index = None

packages/leann-backend-diskann/leann_backend_diskann/diskann_embedding_server.py

@@ -81,7 +81,8 @@ def create_diskann_embedding_server(
     with open(passages_file) as f:
         meta = json.load(f)
 
-    passages = PassageManager(meta["passage_sources"])
+    logger.info(f"Loading PassageManager with metadata_file_path: {passages_file}")
+    passages = PassageManager(meta["passage_sources"], metadata_file_path=passages_file)
     logger.info(
         f"Loaded PassageManager with {len(passages.global_offset_map)} passages from metadata"
     )
@@ -102,8 +103,9 @@ def create_diskann_embedding_server(
         socket.bind(f"tcp://*:{zmq_port}")
         logger.info(f"DiskANN ZMQ REP server listening on port {zmq_port}")
 
-        socket.setsockopt(zmq.RCVTIMEO, 300000)
-        socket.setsockopt(zmq.SNDTIMEO, 300000)
+        socket.setsockopt(zmq.RCVTIMEO, 1000)
+        socket.setsockopt(zmq.SNDTIMEO, 1000)
+        socket.setsockopt(zmq.LINGER, 0)
 
         while True:
             try:
@@ -220,30 +222,217 @@ def create_diskann_embedding_server(
                 traceback.print_exc()
                 raise
 
-    zmq_thread = threading.Thread(target=zmq_server_thread, daemon=True)
+    def zmq_server_thread_with_shutdown(shutdown_event):
+        """ZMQ server thread that respects shutdown signal.
+
+        This creates its own REP socket, binds to zmq_port, and periodically
+        checks shutdown_event using recv timeouts to exit cleanly.
+        """
+        logger.info("DiskANN ZMQ server thread started with shutdown support")
+
+        context = zmq.Context()
+        rep_socket = context.socket(zmq.REP)
+        rep_socket.bind(f"tcp://*:{zmq_port}")
+        logger.info(f"DiskANN ZMQ REP server listening on port {zmq_port}")
+
+        # Set receive timeout so we can check shutdown_event periodically
+        rep_socket.setsockopt(zmq.RCVTIMEO, 1000)  # 1 second timeout
+        rep_socket.setsockopt(zmq.SNDTIMEO, 1000)
+        rep_socket.setsockopt(zmq.LINGER, 0)
+
+        try:
+            while not shutdown_event.is_set():
+                try:
+                    e2e_start = time.time()
+                    # REP socket receives single-part messages
+                    message = rep_socket.recv()
+
+                    # Check for empty messages - REP socket requires response to every request
+                    if not message:
+                        logger.warning("Received empty message, sending empty response")
+                        rep_socket.send(b"")
+                        continue
+
+                    # Try protobuf first (same logic as original)
+                    texts = []
+                    is_text_request = False
+
+                    try:
+                        req_proto = embedding_pb2.NodeEmbeddingRequest()
+                        req_proto.ParseFromString(message)
+                        node_ids = list(req_proto.node_ids)
+
+                        # Look up texts by node IDs
+                        for nid in node_ids:
+                            try:
+                                passage_data = passages.get_passage(str(nid))
+                                txt = passage_data["text"]
+                                if not txt:
+                                    raise RuntimeError(f"FATAL: Empty text for passage ID {nid}")
+                                texts.append(txt)
+                            except KeyError:
+                                raise RuntimeError(f"FATAL: Passage with ID {nid} not found")
+
+                        logger.info(f"ZMQ received protobuf request for {len(node_ids)} node IDs")
+                    except Exception:
+                        # Fallback to msgpack for text requests
+                        try:
+                            import msgpack
+
+                            request = msgpack.unpackb(message)
+                            if isinstance(request, list) and all(
+                                isinstance(item, str) for item in request
+                            ):
+                                texts = request
+                                is_text_request = True
+                                logger.info(
+                                    f"ZMQ received msgpack text request for {len(texts)} texts"
+                                )
+                            else:
+                                raise ValueError("Not a valid msgpack text request")
+                        except Exception:
+                            logger.error("Both protobuf and msgpack parsing failed!")
+                            # Send error response
+                            resp_proto = embedding_pb2.NodeEmbeddingResponse()
+                            rep_socket.send(resp_proto.SerializeToString())
+                            continue
+
+                    # Process the request
+                    embeddings = compute_embeddings(texts, model_name, mode=embedding_mode)
+                    logger.info(f"Computed embeddings shape: {embeddings.shape}")
+
+                    # Validation
+                    if np.isnan(embeddings).any() or np.isinf(embeddings).any():
+                        logger.error("NaN or Inf detected in embeddings!")
+                        # Send error response
+                        if is_text_request:
+                            import msgpack
+
+                            response_data = msgpack.packb([])
+                        else:
+                            resp_proto = embedding_pb2.NodeEmbeddingResponse()
+                            response_data = resp_proto.SerializeToString()
+                        rep_socket.send(response_data)
+                        continue
+
+                    # Prepare response based on request type
+                    if is_text_request:
+                        # For direct text requests, return msgpack
+                        import msgpack
+
+                        response_data = msgpack.packb(embeddings.tolist())
+                    else:
+                        # For protobuf requests, return protobuf
+                        resp_proto = embedding_pb2.NodeEmbeddingResponse()
+                        hidden_contiguous = np.ascontiguousarray(embeddings, dtype=np.float32)
+
+                        resp_proto.embeddings_data = hidden_contiguous.tobytes()
+                        resp_proto.dimensions.append(hidden_contiguous.shape[0])
+                        resp_proto.dimensions.append(hidden_contiguous.shape[1])
+
+                        response_data = resp_proto.SerializeToString()
+
+                    # Send response back to the client
+                    rep_socket.send(response_data)
+
+                    e2e_end = time.time()
+                    logger.info(f"⏱️  ZMQ E2E time: {e2e_end - e2e_start:.6f}s")
+
+                except zmq.Again:
+                    # Timeout - check shutdown_event and continue
+                    continue
+                except Exception as e:
+                    if not shutdown_event.is_set():
+                        logger.error(f"Error in ZMQ server loop: {e}")
+                        try:
+                            # Send error response for REP socket
+                            resp_proto = embedding_pb2.NodeEmbeddingResponse()
+                            rep_socket.send(resp_proto.SerializeToString())
+                        except Exception:
+                            pass
+                    else:
+                        logger.info("Shutdown in progress, ignoring ZMQ error")
+                        break
+        finally:
+            try:
+                rep_socket.close(0)
+            except Exception:
+                pass
+            try:
+                context.term()
+            except Exception:
+                pass
+
+        logger.info("DiskANN ZMQ server thread exiting gracefully")
+
+    # Add shutdown coordination
+    shutdown_event = threading.Event()
+
+    def shutdown_zmq_server():
+        """Gracefully shutdown ZMQ server."""
+        logger.info("Initiating graceful shutdown...")
+        shutdown_event.set()
+
+        if zmq_thread.is_alive():
+            logger.info("Waiting for ZMQ thread to finish...")
+            zmq_thread.join(timeout=5)
+            if zmq_thread.is_alive():
+                logger.warning("ZMQ thread did not finish in time")
+
+        # Clean up ZMQ resources
+        try:
+            # Note: socket and context are cleaned up by thread exit
+            logger.info("ZMQ resources cleaned up")
+        except Exception as e:
+            logger.warning(f"Error cleaning ZMQ resources: {e}")
+
+        # Clean up other resources
+        try:
+            import gc
+
+            gc.collect()
+            logger.info("Additional resources cleaned up")
+        except Exception as e:
+            logger.warning(f"Error cleaning additional resources: {e}")
+
+        logger.info("Graceful shutdown completed")
+        sys.exit(0)
+
+    # Register signal handlers within this function scope
+    import signal
+
+    def signal_handler(sig, frame):
+        logger.info(f"Received signal {sig}, shutting down gracefully...")
+        shutdown_zmq_server()
+
+    signal.signal(signal.SIGTERM, signal_handler)
+    signal.signal(signal.SIGINT, signal_handler)
+
+    # Start ZMQ thread (NOT daemon!)
+    zmq_thread = threading.Thread(
+        target=lambda: zmq_server_thread_with_shutdown(shutdown_event),
+        daemon=False,  # Not daemon - we want to wait for it
+    )
     zmq_thread.start()
     logger.info(f"Started DiskANN ZMQ server thread on port {zmq_port}")
 
     # Keep the main thread alive
     try:
-        while True:
-            time.sleep(1)
+        while not shutdown_event.is_set():
+            time.sleep(0.1)  # Check shutdown more frequently
     except KeyboardInterrupt:
         logger.info("DiskANN Server shutting down...")
+        shutdown_zmq_server()
         return
 
+    # If we reach here, shutdown was triggered by signal
+    logger.info("Main loop exited, process should be shutting down")
+
 
 if __name__ == "__main__":
-    import signal
     import sys
 
-    def signal_handler(sig, frame):
-        logger.info(f"Received signal {sig}, shutting down gracefully...")
-        sys.exit(0)
-
-    # Register signal handlers for graceful shutdown
-    signal.signal(signal.SIGTERM, signal_handler)
-    signal.signal(signal.SIGINT, signal_handler)
+    # Signal handlers are now registered within create_diskann_embedding_server
 
     parser = argparse.ArgumentParser(description="DiskANN Embedding service")
     parser.add_argument("--zmq-port", type=int, default=5555, help="ZMQ port to run on")

packages/leann-backend-diskann/leann_backend_diskann/graph_partition.py

@@ -0,0 +1,299 @@
+#!/usr/bin/env python3
+"""
+Graph Partition Module for LEANN DiskANN Backend
+
+This module provides Python bindings for the graph partition functionality
+of DiskANN, allowing users to partition disk-based indices for better
+performance.
+"""
+
+import os
+import shutil
+import subprocess
+import tempfile
+from pathlib import Path
+from typing import Optional
+
+
+class GraphPartitioner:
+    """
+    A Python interface for DiskANN's graph partition functionality.
+
+    This class provides methods to partition disk-based indices for improved
+    search performance and memory efficiency.
+    """
+
+    def __init__(self, build_type: str = "release"):
+        """
+        Initialize the GraphPartitioner.
+
+        Args:
+            build_type: Build type for the executables ("debug" or "release")
+        """
+        self.build_type = build_type
+        self._ensure_executables()
+
+    def _get_executable_path(self, name: str) -> str:
+        """Get the path to a graph partition executable."""
+        # Get the directory where this Python module is located
+        module_dir = Path(__file__).parent
+        # Navigate to the graph_partition directory
+        graph_partition_dir = module_dir.parent / "third_party" / "DiskANN" / "graph_partition"
+        executable_path = graph_partition_dir / "build" / self.build_type / "graph_partition" / name
+
+        if not executable_path.exists():
+            raise FileNotFoundError(f"Executable {name} not found at {executable_path}")
+
+        return str(executable_path)
+
+    def _ensure_executables(self):
+        """Ensure that the required executables are built."""
+        try:
+            self._get_executable_path("partitioner")
+            self._get_executable_path("index_relayout")
+        except FileNotFoundError:
+            # Try to build the executables automatically
+            print("Executables not found, attempting to build them...")
+            self._build_executables()
+
+    def _build_executables(self):
+        """Build the required executables."""
+        graph_partition_dir = (
+            Path(__file__).parent.parent / "third_party" / "DiskANN" / "graph_partition"
+        )
+        original_dir = os.getcwd()
+
+        try:
+            os.chdir(graph_partition_dir)
+
+            # Clean any existing build
+            if (graph_partition_dir / "build").exists():
+                shutil.rmtree(graph_partition_dir / "build")
+
+            # Run the build script
+            cmd = ["./build.sh", self.build_type, "split_graph", "/tmp/dummy"]
+            subprocess.run(cmd, capture_output=True, text=True, cwd=graph_partition_dir)
+
+            # Check if executables were created
+            partitioner_path = self._get_executable_path("partitioner")
+            relayout_path = self._get_executable_path("index_relayout")
+
+            print(f"✅ Built partitioner: {partitioner_path}")
+            print(f"✅ Built index_relayout: {relayout_path}")
+
+        except Exception as e:
+            raise RuntimeError(f"Failed to build executables: {e}")
+        finally:
+            os.chdir(original_dir)
+
+    def partition_graph(
+        self,
+        index_prefix_path: str,
+        output_dir: Optional[str] = None,
+        partition_prefix: Optional[str] = None,
+        **kwargs,
+    ) -> tuple[str, str]:
+        """
+        Partition a disk-based index for improved performance.
+
+        Args:
+            index_prefix_path: Path to the index prefix (e.g., "/path/to/index")
+            output_dir: Output directory for results (defaults to parent of index_prefix_path)
+            partition_prefix: Prefix for output files (defaults to basename of index_prefix_path)
+            **kwargs: Additional parameters for graph partitioning:
+                - gp_times: Number of LDG partition iterations (default: 10)
+                - lock_nums: Number of lock nodes (default: 10)
+                - cut: Cut adjacency list degree (default: 100)
+                - scale_factor: Scale factor (default: 1)
+                - data_type: Data type (default: "float")
+                - thread_nums: Number of threads (default: 10)
+
+        Returns:
+            Tuple of (disk_graph_index_path, partition_bin_path)
+
+        Raises:
+            RuntimeError: If the partitioning process fails
+        """
+        # Set default parameters
+        params = {
+            "gp_times": 10,
+            "lock_nums": 10,
+            "cut": 100,
+            "scale_factor": 1,
+            "data_type": "float",
+            "thread_nums": 10,
+            **kwargs,
+        }
+
+        # Determine output directory
+        if output_dir is None:
+            output_dir = str(Path(index_prefix_path).parent)
+
+        # Create output directory if it doesn't exist
+        Path(output_dir).mkdir(parents=True, exist_ok=True)
+
+        # Determine partition prefix
+        if partition_prefix is None:
+            partition_prefix = Path(index_prefix_path).name
+
+        # Get executable paths
+        partitioner_path = self._get_executable_path("partitioner")
+        relayout_path = self._get_executable_path("index_relayout")
+
+        # Create temporary directory for processing
+        with tempfile.TemporaryDirectory() as temp_dir:
+            # Change to the graph_partition directory for temporary files
+            graph_partition_dir = (
+                Path(__file__).parent.parent / "third_party" / "DiskANN" / "graph_partition"
+            )
+            original_dir = os.getcwd()
+
+            try:
+                os.chdir(graph_partition_dir)
+
+                # Create temporary data directory
+                temp_data_dir = Path(temp_dir) / "data"
+                temp_data_dir.mkdir(parents=True, exist_ok=True)
+
+                # Set up paths for temporary files
+                graph_path = temp_data_dir / "starling" / "_M_R_L_B" / "GRAPH"
+                graph_gp_path = (
+                    graph_path
+                    / f"GP_TIMES_{params['gp_times']}_LOCK_{params['lock_nums']}_GP_USE_FREQ0_CUT{params['cut']}_SCALE{params['scale_factor']}"
+                )
+                graph_gp_path.mkdir(parents=True, exist_ok=True)
+
+                # Find input index file
+                old_index_file = f"{index_prefix_path}_disk_beam_search.index"
+                if not os.path.exists(old_index_file):
+                    old_index_file = f"{index_prefix_path}_disk.index"
+
+                if not os.path.exists(old_index_file):
+                    raise RuntimeError(f"Index file not found: {old_index_file}")
+
+                # Run partitioner
+                gp_file_path = graph_gp_path / "_part.bin"
+                partitioner_cmd = [
+                    partitioner_path,
+                    "--index_file",
+                    old_index_file,
+                    "--data_type",
+                    params["data_type"],
+                    "--gp_file",
+                    str(gp_file_path),
+                    "-T",
+                    str(params["thread_nums"]),
+                    "--ldg_times",
+                    str(params["gp_times"]),
+                    "--scale",
+                    str(params["scale_factor"]),
+                    "--mode",
+                    "1",
+                ]
+
+                print(f"Running partitioner: {' '.join(partitioner_cmd)}")
+                result = subprocess.run(
+                    partitioner_cmd, capture_output=True, text=True, cwd=graph_partition_dir
+                )
+
+                if result.returncode != 0:
+                    raise RuntimeError(
+                        f"Partitioner failed with return code {result.returncode}.\n"
+                        f"stdout: {result.stdout}\n"
+                        f"stderr: {result.stderr}"
+                    )
+
+                # Run relayout
+                part_tmp_index = graph_gp_path / "_part_tmp.index"
+                relayout_cmd = [
+                    relayout_path,
+                    old_index_file,
+                    str(gp_file_path),
+                    params["data_type"],
+                    "1",
+                ]
+
+                print(f"Running relayout: {' '.join(relayout_cmd)}")
+                result = subprocess.run(
+                    relayout_cmd, capture_output=True, text=True, cwd=graph_partition_dir
+                )
+
+                if result.returncode != 0:
+                    raise RuntimeError(
+                        f"Relayout failed with return code {result.returncode}.\n"
+                        f"stdout: {result.stdout}\n"
+                        f"stderr: {result.stderr}"
+                    )
+
+                # Copy results to output directory
+                disk_graph_path = Path(output_dir) / f"{partition_prefix}_disk_graph.index"
+                partition_bin_path = Path(output_dir) / f"{partition_prefix}_partition.bin"
+
+                shutil.copy2(part_tmp_index, disk_graph_path)
+                shutil.copy2(gp_file_path, partition_bin_path)
+
+                print(f"Results copied to: {output_dir}")
+                return str(disk_graph_path), str(partition_bin_path)
+
+            finally:
+                os.chdir(original_dir)
+
+    def get_partition_info(self, partition_bin_path: str) -> dict:
+        """
+        Get information about a partition file.
+
+        Args:
+            partition_bin_path: Path to the partition binary file
+
+        Returns:
+            Dictionary containing partition information
+        """
+        if not os.path.exists(partition_bin_path):
+            raise FileNotFoundError(f"Partition file not found: {partition_bin_path}")
+
+        # For now, return basic file information
+        # In the future, this could parse the binary file for detailed info
+        stat = os.stat(partition_bin_path)
+        return {
+            "file_size": stat.st_size,
+            "file_path": partition_bin_path,
+            "modified_time": stat.st_mtime,
+        }
+
+
+def partition_graph(
+    index_prefix_path: str,
+    output_dir: Optional[str] = None,
+    partition_prefix: Optional[str] = None,
+    build_type: str = "release",
+    **kwargs,
+) -> tuple[str, str]:
+    """
+    Convenience function to partition a graph index.
+
+    Args:
+        index_prefix_path: Path to the index prefix
+        output_dir: Output directory (defaults to parent of index_prefix_path)
+        partition_prefix: Prefix for output files (defaults to basename of index_prefix_path)
+        build_type: Build type for executables ("debug" or "release")
+        **kwargs: Additional parameters for graph partitioning
+
+    Returns:
+        Tuple of (disk_graph_index_path, partition_bin_path)
+    """
+    partitioner = GraphPartitioner(build_type=build_type)
+    return partitioner.partition_graph(index_prefix_path, output_dir, partition_prefix, **kwargs)
+
+
+# Example usage:
+if __name__ == "__main__":
+    # Example: partition an index
+    try:
+        disk_graph_path, partition_bin_path = partition_graph(
+            "/path/to/your/index_prefix", gp_times=10, lock_nums=10, cut=100
+        )
+        print("Partitioning completed successfully!")
+        print(f"Disk graph index: {disk_graph_path}")
+        print(f"Partition binary: {partition_bin_path}")
+    except Exception as e:
+        print(f"Partitioning failed: {e}")

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

@@ -1,5 +1,6 @@
 import argparse
 import gc  # Import garbage collector interface
+import logging
 import os
 import struct
 import sys
@@ -7,6 +8,12 @@ import time
 
 import numpy as np
 
+# Set up logging to avoid print buffer issues
+logger = logging.getLogger(__name__)
+LOG_LEVEL = os.getenv("LEANN_LOG_LEVEL", "WARNING").upper()
+log_level = getattr(logging, LOG_LEVEL, logging.WARNING)
+logger.setLevel(log_level)
+
 # --- FourCCs (add more if needed) ---
 INDEX_HNSW_FLAT_FOURCC = int.from_bytes(b"IHNf", "little")
 # Add other HNSW fourccs if you expect different storage types inside HNSW
@@ -243,6 +250,8 @@ def convert_hnsw_graph_to_csr(input_filename, output_filename, prune_embeddings=
         output_filename: Output CSR index file
         prune_embeddings: Whether to prune embedding storage (write NULL storage marker)
     """
+    # Keep prints simple; rely on CI runner to flush output as needed
+
     print(f"Starting conversion: {input_filename} -> {output_filename}")
     start_time = time.time()
     original_hnsw_data = {}

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

@@ -10,7 +10,7 @@ import sys
 import threading
 import time
 from pathlib import Path
-from typing import Union
+from typing import Optional
 
 import msgpack
 import numpy as np
@@ -34,7 +34,7 @@ if not logger.handlers:
 
 
 def create_hnsw_embedding_server(
-    passages_file: Union[str, None] = None,
+    passages_file: Optional[str] = None,
     zmq_port: int = 5555,
     model_name: str = "sentence-transformers/all-mpnet-base-v2",
     distance_metric: str = "mips",
@@ -82,217 +82,317 @@ def create_hnsw_embedding_server(
     with open(passages_file) as f:
         meta = json.load(f)
 
-    # Resolve passage files for cross-machine portability
-    metadata_dir = Path(passages_file).parent  # Same directory as meta.json
-    passage_sources = []
-    for source in meta["passage_sources"]:
-        src = dict(source)
-        # Absolute candidates from meta
-        cand_path = Path(src.get("path", ""))
-        cand_idx = Path(src.get("index_path", ""))
-        # Relative hints if provided
-        rel_path = src.get("path_relative")
-        rel_idx = src.get("index_path_relative")
-        # Defaults (siblings of meta)
-        default_path = metadata_dir / "documents.leann.passages.jsonl"
-        default_idx = metadata_dir / "documents.leann.passages.idx"
-
-        # Normalize path
-        if not cand_path.exists():
-            if rel_path and (metadata_dir / rel_path).exists():
-                src["path"] = str(metadata_dir / rel_path)
-            elif default_path.exists():
-                src["path"] = str(default_path)
-        # Normalize index_path
-        if not cand_idx.exists():
-            if rel_idx and (metadata_dir / rel_idx).exists():
-                src["index_path"] = str(metadata_dir / rel_idx)
-            elif default_idx.exists():
-                src["index_path"] = str(default_idx)
-
-        passage_sources.append(src)
-
-    passages = PassageManager(passage_sources)
+    # Let PassageManager handle path resolution uniformly. It supports fallback order:
+    # 1) path/index_path; 2) *_relative; 3) standard siblings next to meta
+    passages = PassageManager(meta["passage_sources"], metadata_file_path=passages_file)
+    # Dimension from metadata for shaping responses
+    try:
+        embedding_dim: int = int(meta.get("dimensions", 0))
+    except Exception:
+        embedding_dim = 0
     logger.info(
         f"Loaded PassageManager with {len(passages.global_offset_map)} passages from metadata"
     )
 
-    def zmq_server_thread():
-        """ZMQ server thread"""
+    # (legacy ZMQ thread removed; using shutdown-capable server only)
+
+    def zmq_server_thread_with_shutdown(shutdown_event):
+        """ZMQ server thread that respects shutdown signal.
+
+        Creates its own REP socket bound to zmq_port and polls with timeouts
+        to allow graceful shutdown.
+        """
+        logger.info("ZMQ server thread started with shutdown support")
+
         context = zmq.Context()
-        socket = context.socket(zmq.REP)
-        socket.bind(f"tcp://*:{zmq_port}")
-        logger.info(f"HNSW ZMQ server listening on port {zmq_port}")
+        rep_socket = context.socket(zmq.REP)
+        rep_socket.bind(f"tcp://*:{zmq_port}")
+        logger.info(f"HNSW ZMQ REP server listening on port {zmq_port}")
+        rep_socket.setsockopt(zmq.RCVTIMEO, 1000)
+        # Keep sends from blocking during shutdown; fail fast and drop on close
+        rep_socket.setsockopt(zmq.SNDTIMEO, 1000)
+        rep_socket.setsockopt(zmq.LINGER, 0)
 
-        socket.setsockopt(zmq.RCVTIMEO, 300000)
-        socket.setsockopt(zmq.SNDTIMEO, 300000)
+        # Track last request type/length for shape-correct fallbacks
+        last_request_type = "unknown"  # 'text' | 'distance' | 'embedding' | 'unknown'
+        last_request_length = 0
 
-        while True:
-            try:
-                message_bytes = socket.recv()
-                logger.debug(f"Received ZMQ request of size {len(message_bytes)} bytes")
+        try:
+            while not shutdown_event.is_set():
+                try:
+                    e2e_start = time.time()
+                    logger.debug("🔍 Waiting for ZMQ message...")
+                    request_bytes = rep_socket.recv()
 
-                e2e_start = time.time()
-                request_payload = msgpack.unpackb(message_bytes)
+                    # Rest of the processing logic (same as original)
+                    request = msgpack.unpackb(request_bytes)
 
-                # Handle direct text embedding request
-                if isinstance(request_payload, list) and len(request_payload) > 0:
-                    # Check if this is a direct text request (list of strings)
-                    if all(isinstance(item, str) for item in request_payload):
-                        logger.info(
-                            f"Processing direct text embedding request for {len(request_payload)} texts in {embedding_mode} mode"
-                        )
+                    if len(request) == 1 and request[0] == "__QUERY_MODEL__":
+                        response_bytes = msgpack.packb([model_name])
+                        rep_socket.send(response_bytes)
+                        continue
 
-                        # Use unified embedding computation (now with model caching)
-                        embeddings = compute_embeddings(
-                            request_payload, model_name, mode=embedding_mode
-                        )
-
-                        response = embeddings.tolist()
-                        socket.send(msgpack.packb(response))
+                    # Handle direct text embedding request
+                    if (
+                        isinstance(request, list)
+                        and request
+                        and all(isinstance(item, str) for item in request)
+                    ):
+                        last_request_type = "text"
+                        last_request_length = len(request)
+                        embeddings = compute_embeddings(request, model_name, mode=embedding_mode)
+                        rep_socket.send(msgpack.packb(embeddings.tolist()))
                         e2e_end = time.time()
                         logger.info(f"⏱️  Text embedding E2E time: {e2e_end - e2e_start:.6f}s")
                         continue
 
-                # Handle distance calculation requests
-                if (
-                    isinstance(request_payload, list)
-                    and len(request_payload) == 2
-                    and isinstance(request_payload[0], list)
-                    and isinstance(request_payload[1], list)
-                ):
-                    node_ids = request_payload[0]
-                    query_vector = np.array(request_payload[1], dtype=np.float32)
+                    # Handle distance calculation request: [[ids], [query_vector]]
+                    if (
+                        isinstance(request, list)
+                        and len(request) == 2
+                        and isinstance(request[0], list)
+                        and isinstance(request[1], list)
+                    ):
+                        node_ids = request[0]
+                        # Handle nested [[ids]] shape defensively
+                        if len(node_ids) == 1 and isinstance(node_ids[0], list):
+                            node_ids = node_ids[0]
+                        query_vector = np.array(request[1], dtype=np.float32)
+                        last_request_type = "distance"
+                        last_request_length = len(node_ids)
 
-                    logger.debug("Distance calculation request received")
-                    logger.debug(f"    Node IDs: {node_ids}")
-                    logger.debug(f"    Query vector dim: {len(query_vector)}")
+                        logger.debug("Distance calculation request received")
+                        logger.debug(f"    Node IDs: {node_ids}")
+                        logger.debug(f"    Query vector dim: {len(query_vector)}")
 
-                    # Get embeddings for node IDs
-                    texts = []
-                    for nid in node_ids:
+                        # Gather texts for found ids
+                        texts: list[str] = []
+                        found_indices: list[int] = []
+                        for idx, nid in enumerate(node_ids):
+                            try:
+                                passage_data = passages.get_passage(str(nid))
+                                txt = passage_data.get("text", "")
+                                if isinstance(txt, str) and len(txt) > 0:
+                                    texts.append(txt)
+                                    found_indices.append(idx)
+                                else:
+                                    logger.error(f"Empty text for passage ID {nid}")
+                            except KeyError:
+                                logger.error(f"Passage ID {nid} not found")
+                            except Exception as e:
+                                logger.error(f"Exception looking up passage ID {nid}: {e}")
+
+                        # Prepare full-length response with large sentinel values
+                        large_distance = 1e9
+                        response_distances = [large_distance] * len(node_ids)
+
+                        if texts:
+                            try:
+                                embeddings = compute_embeddings(
+                                    texts, model_name, mode=embedding_mode
+                                )
+                                logger.info(
+                                    f"Computed embeddings for {len(texts)} texts, shape: {embeddings.shape}"
+                                )
+                                if distance_metric == "l2":
+                                    partial = np.sum(
+                                        np.square(embeddings - query_vector.reshape(1, -1)), axis=1
+                                    )
+                                else:  # mips or cosine
+                                    partial = -np.dot(embeddings, query_vector)
+
+                                for pos, dval in zip(found_indices, partial.flatten().tolist()):
+                                    response_distances[pos] = float(dval)
+                            except Exception as e:
+                                logger.error(f"Distance computation error, using sentinels: {e}")
+
+                        # Send response in expected shape [[distances]]
+                        rep_socket.send(msgpack.packb([response_distances], use_single_float=True))
+                        e2e_end = time.time()
+                        logger.info(f"⏱️  Distance calculation E2E time: {e2e_end - e2e_start:.6f}s")
+                        continue
+
+                    # Fallback: treat as embedding-by-id request
+                    if (
+                        isinstance(request, list)
+                        and len(request) == 1
+                        and isinstance(request[0], list)
+                    ):
+                        node_ids = request[0]
+                    elif isinstance(request, list):
+                        node_ids = request
+                    else:
+                        node_ids = []
+                    last_request_type = "embedding"
+                    last_request_length = len(node_ids)
+                    logger.info(f"ZMQ received {len(node_ids)} node IDs for embedding fetch")
+
+                    # Preallocate zero-filled flat data for robustness
+                    if embedding_dim <= 0:
+                        dims = [0, 0]
+                        flat_data: list[float] = []
+                    else:
+                        dims = [len(node_ids), embedding_dim]
+                        flat_data = [0.0] * (dims[0] * dims[1])
+
+                    # Collect texts for found ids
+                    texts: list[str] = []
+                    found_indices: list[int] = []
+                    for idx, nid in enumerate(node_ids):
                         try:
                             passage_data = passages.get_passage(str(nid))
-                            txt = passage_data["text"]
-                            texts.append(txt)
+                            txt = passage_data.get("text", "")
+                            if isinstance(txt, str) and len(txt) > 0:
+                                texts.append(txt)
+                                found_indices.append(idx)
+                            else:
+                                logger.error(f"Empty text for passage ID {nid}")
                         except KeyError:
-                            logger.error(f"Passage ID {nid} not found")
-                            raise RuntimeError(f"FATAL: Passage with ID {nid} not found")
+                            logger.error(f"Passage with ID {nid} not found")
                         except Exception as e:
                             logger.error(f"Exception looking up passage ID {nid}: {e}")
-                            raise
 
-                    # Process embeddings
-                    embeddings = compute_embeddings(texts, model_name, mode=embedding_mode)
-                    logger.info(
-                        f"Computed embeddings for {len(texts)} texts, shape: {embeddings.shape}"
-                    )
+                    if texts:
+                        try:
+                            embeddings = compute_embeddings(texts, model_name, mode=embedding_mode)
+                            logger.info(
+                                f"Computed embeddings for {len(texts)} texts, shape: {embeddings.shape}"
+                            )
 
-                    # Calculate distances
-                    if distance_metric == "l2":
-                        distances = np.sum(
-                            np.square(embeddings - query_vector.reshape(1, -1)), axis=1
-                        )
-                    else:  # mips or cosine
-                        distances = -np.dot(embeddings, query_vector)
+                            if np.isnan(embeddings).any() or np.isinf(embeddings).any():
+                                logger.error(
+                                    f"NaN or Inf detected in embeddings! Requested IDs: {node_ids[:5]}..."
+                                )
+                                dims = [0, embedding_dim]
+                                flat_data = []
+                            else:
+                                emb_f32 = np.ascontiguousarray(embeddings, dtype=np.float32)
+                                flat = emb_f32.flatten().tolist()
+                                for j, pos in enumerate(found_indices):
+                                    start = pos * embedding_dim
+                                    end = start + embedding_dim
+                                    if end <= len(flat_data):
+                                        flat_data[start:end] = flat[
+                                            j * embedding_dim : (j + 1) * embedding_dim
+                                        ]
+                        except Exception as e:
+                            logger.error(f"Embedding computation error, returning zeros: {e}")
 
-                    response_payload = distances.flatten().tolist()
-                    response_bytes = msgpack.packb([response_payload], use_single_float=True)
-                    logger.debug(f"Sending distance response with {len(distances)} distances")
+                    response_payload = [dims, flat_data]
+                    response_bytes = msgpack.packb(response_payload, use_single_float=True)
 
-                    socket.send(response_bytes)
+                    rep_socket.send(response_bytes)
                     e2e_end = time.time()
-                    logger.info(f"⏱️  Distance calculation E2E time: {e2e_end - e2e_start:.6f}s")
+                    logger.info(f"⏱️  ZMQ E2E time: {e2e_end - e2e_start:.6f}s")
+
+                except zmq.Again:
+                    # Timeout - check shutdown_event and continue
                     continue
+                except Exception as e:
+                    if not shutdown_event.is_set():
+                        logger.error(f"Error in ZMQ server loop: {e}")
+                        # Shape-correct fallback
+                        try:
+                            if last_request_type == "distance":
+                                large_distance = 1e9
+                                fallback_len = max(0, int(last_request_length))
+                                safe = [[large_distance] * fallback_len]
+                            elif last_request_type == "embedding":
+                                bsz = max(0, int(last_request_length))
+                                dim = max(0, int(embedding_dim))
+                                safe = (
+                                    [[bsz, dim], [0.0] * (bsz * dim)] if dim > 0 else [[0, 0], []]
+                                )
+                            elif last_request_type == "text":
+                                safe = []  # direct text embeddings expectation is a flat list
+                            else:
+                                safe = [[0, int(embedding_dim) if embedding_dim > 0 else 0], []]
+                            rep_socket.send(msgpack.packb(safe, use_single_float=True))
+                        except Exception:
+                            pass
+                    else:
+                        logger.info("Shutdown in progress, ignoring ZMQ error")
+                        break
+        finally:
+            try:
+                rep_socket.close(0)
+            except Exception:
+                pass
+            try:
+                context.term()
+            except Exception:
+                pass
 
-                # Standard embedding request (passage ID lookup)
-                if (
-                    not isinstance(request_payload, list)
-                    or len(request_payload) != 1
-                    or not isinstance(request_payload[0], list)
-                ):
-                    logger.error(
-                        f"Invalid MessagePack request format. Expected [[ids...]] or [texts...], got: {type(request_payload)}"
-                    )
-                    socket.send(msgpack.packb([[], []]))
-                    continue
+        logger.info("ZMQ server thread exiting gracefully")
 
-                node_ids = request_payload[0]
-                logger.debug(f"Request for {len(node_ids)} node embeddings")
+    # Add shutdown coordination
+    shutdown_event = threading.Event()
 
-                # Look up texts by node IDs
-                texts = []
-                for nid in node_ids:
-                    try:
-                        passage_data = passages.get_passage(str(nid))
-                        txt = passage_data["text"]
-                        if not txt:
-                            raise RuntimeError(f"FATAL: Empty text for passage ID {nid}")
-                        texts.append(txt)
-                    except KeyError:
-                        raise RuntimeError(f"FATAL: Passage with ID {nid} not found")
-                    except Exception as e:
-                        logger.error(f"Exception looking up passage ID {nid}: {e}")
-                        raise
+    def shutdown_zmq_server():
+        """Gracefully shutdown ZMQ server."""
+        logger.info("Initiating graceful shutdown...")
+        shutdown_event.set()
 
-                # Process embeddings
-                embeddings = compute_embeddings(texts, model_name, mode=embedding_mode)
-                logger.info(
-                    f"Computed embeddings for {len(texts)} texts, shape: {embeddings.shape}"
-                )
+        if zmq_thread.is_alive():
+            logger.info("Waiting for ZMQ thread to finish...")
+            zmq_thread.join(timeout=5)
+            if zmq_thread.is_alive():
+                logger.warning("ZMQ thread did not finish in time")
 
-                # Serialization and response
-                if np.isnan(embeddings).any() or np.isinf(embeddings).any():
-                    logger.error(
-                        f"NaN or Inf detected in embeddings! Requested IDs: {node_ids[:5]}..."
-                    )
-                    raise AssertionError()
+        # Clean up ZMQ resources
+        try:
+            # Note: socket and context are cleaned up by thread exit
+            logger.info("ZMQ resources cleaned up")
+        except Exception as e:
+            logger.warning(f"Error cleaning ZMQ resources: {e}")
 
-                hidden_contiguous_f32 = np.ascontiguousarray(embeddings, dtype=np.float32)
-                response_payload = [
-                    list(hidden_contiguous_f32.shape),
-                    hidden_contiguous_f32.flatten().tolist(),
-                ]
-                response_bytes = msgpack.packb(response_payload, use_single_float=True)
+        # Clean up other resources
+        try:
+            import gc
 
-                socket.send(response_bytes)
-                e2e_end = time.time()
-                logger.info(f"⏱️  ZMQ E2E time: {e2e_end - e2e_start:.6f}s")
+            gc.collect()
+            logger.info("Additional resources cleaned up")
+        except Exception as e:
+            logger.warning(f"Error cleaning additional resources: {e}")
 
-            except zmq.Again:
-                logger.debug("ZMQ socket timeout, continuing to listen")
-                continue
-            except Exception as e:
-                logger.error(f"Error in ZMQ server loop: {e}")
-                import traceback
+        logger.info("Graceful shutdown completed")
+        sys.exit(0)
 
-                traceback.print_exc()
-                socket.send(msgpack.packb([[], []]))
+    # Register signal handlers within this function scope
+    import signal
 
-    zmq_thread = threading.Thread(target=zmq_server_thread, daemon=True)
+    def signal_handler(sig, frame):
+        logger.info(f"Received signal {sig}, shutting down gracefully...")
+        shutdown_zmq_server()
+
+    signal.signal(signal.SIGTERM, signal_handler)
+    signal.signal(signal.SIGINT, signal_handler)
+
+    # Pass shutdown_event to ZMQ thread
+    zmq_thread = threading.Thread(
+        target=lambda: zmq_server_thread_with_shutdown(shutdown_event),
+        daemon=False,  # Not daemon - we want to wait for it
+    )
     zmq_thread.start()
     logger.info(f"Started HNSW ZMQ server thread on port {zmq_port}")
 
     # Keep the main thread alive
     try:
-        while True:
-            time.sleep(1)
+        while not shutdown_event.is_set():
+            time.sleep(0.1)  # Check shutdown more frequently
     except KeyboardInterrupt:
         logger.info("HNSW Server shutting down...")
+        shutdown_zmq_server()
         return
 
+    # If we reach here, shutdown was triggered by signal
+    logger.info("Main loop exited, process should be shutting down")
+
 
 if __name__ == "__main__":
-    import signal
     import sys
 
-    def signal_handler(sig, frame):
-        logger.info(f"Received signal {sig}, shutting down gracefully...")
-        sys.exit(0)
-
-    # Register signal handlers for graceful shutdown
-    signal.signal(signal.SIGTERM, signal_handler)
-    signal.signal(signal.SIGINT, signal_handler)
+    # Signal handlers are now registered within create_hnsw_embedding_server
 
     parser = argparse.ArgumentParser(description="HNSW Embedding service")
     parser.add_argument("--zmq-port", type=int, default=5555, help="ZMQ port to run on")

packages/leann-core/src/leann/api.py

@@ -115,20 +115,62 @@ class SearchResult:
 
 
 class PassageManager:
-    def __init__(self, passage_sources: list[dict[str, Any]]):
+    def __init__(
+        self, passage_sources: list[dict[str, Any]], metadata_file_path: Optional[str] = None
+    ):
         self.offset_maps = {}
         self.passage_files = {}
         self.global_offset_map = {}  # Combined map for fast lookup
 
+        # Derive index base name for standard sibling fallbacks, e.g., <index_name>.passages.*
+        index_name_base = None
+        if metadata_file_path:
+            meta_name = Path(metadata_file_path).name
+            if meta_name.endswith(".meta.json"):
+                index_name_base = meta_name[: -len(".meta.json")]
+
         for source in passage_sources:
             assert source["type"] == "jsonl", "only jsonl is supported"
-            passage_file = source["path"]
-            index_file = source["index_path"]  # .idx file
+            passage_file = source.get("path", "")
+            index_file = source.get("index_path", "")  # .idx file
 
-            # Fix path resolution for Colab and other environments
-            if not Path(index_file).is_absolute():
-                # If relative path, try to resolve it properly
-                index_file = str(Path(index_file).resolve())
+            # Fix path resolution - relative paths should be relative to metadata file directory
+            def _resolve_candidates(
+                primary: str,
+                relative_key: str,
+                default_name: Optional[str],
+                source_dict: dict[str, Any],
+            ) -> list[Path]:
+                candidates: list[Path] = []
+                # 1) Primary as-is (absolute or relative)
+                if primary:
+                    p = Path(primary)
+                    candidates.append(p if p.is_absolute() else (Path.cwd() / p))
+                # 2) metadata-relative explicit relative key
+                if metadata_file_path and source_dict.get(relative_key):
+                    candidates.append(Path(metadata_file_path).parent / source_dict[relative_key])
+                # 3) metadata-relative standard sibling filename
+                if metadata_file_path and default_name:
+                    candidates.append(Path(metadata_file_path).parent / default_name)
+                return candidates
+
+            # Build candidate lists and pick first existing; otherwise keep last candidate for error message
+            idx_default = f"{index_name_base}.passages.idx" if index_name_base else None
+            idx_candidates = _resolve_candidates(
+                index_file, "index_path_relative", idx_default, source
+            )
+            pas_default = f"{index_name_base}.passages.jsonl" if index_name_base else None
+            pas_candidates = _resolve_candidates(passage_file, "path_relative", pas_default, source)
+
+            def _pick_existing(cands: list[Path]) -> str:
+                for c in cands:
+                    if c.exists():
+                        return str(c.resolve())
+                # Fallback to last candidate (best guess) even if not exists; will error below
+                return str(cands[-1].resolve()) if cands else ""
+
+            index_file = _pick_existing(idx_candidates)
+            passage_file = _pick_existing(pas_candidates)
 
             if not Path(index_file).exists():
                 raise FileNotFoundError(f"Passage index file not found: {index_file}")
@@ -326,11 +368,12 @@ class LeannBuilder:
             "passage_sources": [
                 {
                     "type": "jsonl",
-                    "path": str(passages_file),
-                    "index_path": str(offset_file),
-                    # Relative hints for cross-machine portability (non-breaking addition)
-                    "path_relative": f"{index_name}.passages.jsonl",
-                    "index_path_relative": f"{index_name}.passages.idx",
+                    # Preserve existing relative file names (backward-compatible)
+                    "path": passages_file.name,
+                    "index_path": offset_file.name,
+                    # Add optional redundant relative keys for remote build portability (non-breaking)
+                    "path_relative": passages_file.name,
+                    "index_path_relative": offset_file.name,
                 }
             ],
         }
@@ -445,11 +488,12 @@ class LeannBuilder:
             "passage_sources": [
                 {
                     "type": "jsonl",
-                    "path": str(passages_file),
-                    "index_path": str(offset_file),
-                    # Relative hints for cross-machine portability (non-breaking addition)
-                    "path_relative": f"{index_name}.passages.jsonl",
-                    "index_path_relative": f"{index_name}.passages.idx",
+                    # Preserve existing relative file names (backward-compatible)
+                    "path": passages_file.name,
+                    "index_path": offset_file.name,
+                    # Add optional redundant relative keys for remote build portability (non-breaking)
+                    "path_relative": passages_file.name,
+                    "index_path_relative": offset_file.name,
                 }
             ],
             "built_from_precomputed_embeddings": True,
@@ -491,43 +535,10 @@ class LeannSearcher:
         self.embedding_model = self.meta_data["embedding_model"]
         # Support both old and new format
         self.embedding_mode = self.meta_data.get("embedding_mode", "sentence-transformers")
-        # Best-effort portability: if meta contains absolute paths from another machine,
-        # and those paths do not exist locally, try relative hints or fallback sibling filenames.
-        try:
-            idx_path_obj = Path(self.meta_path_str).with_suffix("").with_suffix("")
-            index_dir = idx_path_obj.parent
-            index_name = idx_path_obj.name
-            default_passages = index_dir / f"{index_name}.passages.jsonl"
-            default_offsets = index_dir / f"{index_name}.passages.idx"
-
-            sources = self.meta_data.get("passage_sources", [])
-            normalized_sources: list[dict[str, Any]] = []
-            for src in sources:
-                new_src = dict(src)
-                raw_path = Path(new_src.get("path", ""))
-                raw_idx = Path(new_src.get("index_path", ""))
-                rel_path = new_src.get("path_relative")
-                rel_idx = new_src.get("index_path_relative")
-
-                # Normalize path
-                if not raw_path.exists():
-                    cand = index_dir / rel_path if rel_path else default_passages
-                    if cand.exists():
-                        new_src["path"] = str(cand)
-                # Normalize idx
-                if not raw_idx.exists():
-                    cand = index_dir / rel_idx if rel_idx else default_offsets
-                    if cand.exists():
-                        new_src["index_path"] = str(cand)
-
-                normalized_sources.append(new_src)
-
-            # Only override in-memory view; do not rewrite meta file (non-destructive)
-            self.meta_data["passage_sources"] = normalized_sources
-        except Exception:
-            pass
-
-        self.passage_manager = PassageManager(self.meta_data.get("passage_sources", []))
+        # Delegate portability handling to PassageManager
+        self.passage_manager = PassageManager(
+            self.meta_data.get("passage_sources", []), metadata_file_path=self.meta_path_str
+        )
         backend_factory = BACKEND_REGISTRY.get(backend_name)
         if backend_factory is None:
             raise ValueError(f"Backend '{backend_name}' not found.")
@@ -600,13 +611,13 @@ class LeannSearcher:
             zmq_port=zmq_port,
             **kwargs,
         )
-        time.time() - start_time
         # logger.info(f"  Search time: {search_time} seconds")
         logger.info(f"  Backend returned: labels={len(results.get('labels', [[]])[0])} results")
 
         enriched_results = []
         if "labels" in results and "distances" in results:
             logger.info(f"  Processing {len(results['labels'][0])} passage IDs:")
+            # Python 3.9 does not support zip(strict=...); lengths are expected to match
             for i, (string_id, dist) in enumerate(
                 zip(results["labels"][0], results["distances"][0])
             ):
@@ -634,13 +645,26 @@ class LeannSearcher:
                     )
                 except KeyError:
                     RED = "\033[91m"
+                    RESET = "\033[0m"
                     logger.error(
                         f"   {RED}✗{RESET} [{i + 1:2d}] ID: '{string_id}' -> {RED}ERROR: Passage not found!{RESET}"
                     )
 
+        # Define color codes outside the loop for final message
+        GREEN = "\033[92m"
+        RESET = "\033[0m"
         logger.info(f"  {GREEN}✓ Final enriched results: {len(enriched_results)} passages{RESET}")
         return enriched_results
 
+    def cleanup(self):
+        """Explicitly cleanup embedding server resources.
+
+        This method should be called after you're done using the searcher,
+        especially in test environments or batch processing scenarios.
+        """
+        if hasattr(self.backend_impl, "embedding_server_manager"):
+            self.backend_impl.embedding_server_manager.stop_server()
+
 
 class LeannChat:
     def __init__(
@@ -710,3 +734,12 @@ class LeannChat:
             except (KeyboardInterrupt, EOFError):
                 print("\nGoodbye!")
                 break
+
+    def cleanup(self):
+        """Explicitly cleanup embedding server resources.
+
+        This method should be called after you're done using the chat interface,
+        especially in test environments or batch processing scenarios.
+        """
+        if hasattr(self.searcher, "cleanup"):
+            self.searcher.cleanup()

packages/leann-core/src/leann/embedding_server_manager.py

@@ -8,7 +8,7 @@ import time
 from pathlib import Path
 from typing import Optional
 
-import psutil
+# Lightweight, self-contained server manager with no cross-process inspection
 
 # Set up logging based on environment variable
 LOG_LEVEL = os.getenv("LEANN_LOG_LEVEL", "WARNING").upper()
@@ -43,130 +43,7 @@ def _check_port(port: int) -> bool:
         return s.connect_ex(("localhost", port)) == 0
 
 
-def _check_process_matches_config(
-    port: int, expected_model: str, expected_passages_file: str
-) -> bool:
-    """
-    Check if the process using the port matches our expected model and passages file.
-    Returns True if matches, False otherwise.
-    """
-    try:
-        for proc in psutil.process_iter(["pid", "cmdline"]):
-            if not _is_process_listening_on_port(proc, port):
-                continue
-
-            cmdline = proc.info["cmdline"]
-            if not cmdline:
-                continue
-
-            return _check_cmdline_matches_config(
-                cmdline, port, expected_model, expected_passages_file
-            )
-
-        logger.debug(f"No process found listening on port {port}")
-        return False
-
-    except Exception as e:
-        logger.warning(f"Could not check process on port {port}: {e}")
-        return False
-
-
-def _is_process_listening_on_port(proc, port: int) -> bool:
-    """Check if a process is listening on the given port."""
-    try:
-        connections = proc.net_connections()
-        for conn in connections:
-            if conn.laddr.port == port and conn.status == psutil.CONN_LISTEN:
-                return True
-        return False
-    except (psutil.NoSuchProcess, psutil.AccessDenied, psutil.ZombieProcess):
-        return False
-
-
-def _check_cmdline_matches_config(
-    cmdline: list, port: int, expected_model: str, expected_passages_file: str
-) -> bool:
-    """Check if command line matches our expected configuration."""
-    cmdline_str = " ".join(cmdline)
-    logger.debug(f"Found process on port {port}: {cmdline_str}")
-
-    # Check if it's our embedding server
-    is_embedding_server = any(
-        server_type in cmdline_str
-        for server_type in [
-            "embedding_server",
-            "leann_backend_diskann.embedding_server",
-            "leann_backend_hnsw.hnsw_embedding_server",
-        ]
-    )
-
-    if not is_embedding_server:
-        logger.debug(f"Process on port {port} is not our embedding server")
-        return False
-
-    # Check model name
-    model_matches = _check_model_in_cmdline(cmdline, expected_model)
-
-    # Check passages file if provided
-    passages_matches = _check_passages_in_cmdline(cmdline, expected_passages_file)
-
-    result = model_matches and passages_matches
-    logger.debug(
-        f"model_matches: {model_matches}, passages_matches: {passages_matches}, overall: {result}"
-    )
-    return result
-
-
-def _check_model_in_cmdline(cmdline: list, expected_model: str) -> bool:
-    """Check if the command line contains the expected model."""
-    if "--model-name" not in cmdline:
-        return False
-
-    model_idx = cmdline.index("--model-name")
-    if model_idx + 1 >= len(cmdline):
-        return False
-
-    actual_model = cmdline[model_idx + 1]
-    return actual_model == expected_model
-
-
-def _check_passages_in_cmdline(cmdline: list, expected_passages_file: str) -> bool:
-    """Check if the command line contains the expected passages file."""
-    if "--passages-file" not in cmdline:
-        return False  # Expected but not found
-
-    passages_idx = cmdline.index("--passages-file")
-    if passages_idx + 1 >= len(cmdline):
-        return False
-
-    actual_passages = cmdline[passages_idx + 1]
-    expected_path = Path(expected_passages_file).resolve()
-    actual_path = Path(actual_passages).resolve()
-    return actual_path == expected_path
-
-
-def _find_compatible_port_or_next_available(
-    start_port: int, model_name: str, passages_file: str, max_attempts: int = 100
-) -> tuple[int, bool]:
-    """
-    Find a port that either has a compatible server or is available.
-    Returns (port, is_compatible) where is_compatible indicates if we found a matching server.
-    """
-    for port in range(start_port, start_port + max_attempts):
-        if not _check_port(port):
-            # Port is available
-            return port, False
-
-        # Port is in use, check if it's compatible
-        if _check_process_matches_config(port, model_name, passages_file):
-            logger.info(f"Found compatible server on port {port}")
-            return port, True
-        else:
-            logger.info(f"Port {port} has incompatible server, trying next port...")
-
-    raise RuntimeError(
-        f"Could not find compatible or available port in range {start_port}-{start_port + max_attempts}"
-    )
+# Note: All cross-process scanning helpers removed for simplicity
 
 
 class EmbeddingServerManager:
@@ -185,7 +62,16 @@ class EmbeddingServerManager:
         self.backend_module_name = backend_module_name
         self.server_process: Optional[subprocess.Popen] = None
         self.server_port: Optional[int] = None
+        # Track last-started config for in-process reuse only
+        self._server_config: Optional[dict] = None
         self._atexit_registered = False
+        # Also register a weakref finalizer to ensure cleanup when manager is GC'ed
+        try:
+            import weakref
+
+            self._finalizer = weakref.finalize(self, self._finalize_process)
+        except Exception:
+            self._finalizer = None
 
     def start_server(
         self,
@@ -195,26 +81,24 @@ class EmbeddingServerManager:
         **kwargs,
     ) -> tuple[bool, int]:
         """Start the embedding server."""
-        passages_file = kwargs.get("passages_file")
+        # passages_file may be present in kwargs for server CLI, but we don't need it here
 
-        # Check if we have a compatible server already running
-        if self._has_compatible_running_server(model_name, passages_file):
-            logger.info("Found compatible running server!")
-            return True, port
+        # If this manager already has a live server, just reuse it
+        if self.server_process and self.server_process.poll() is None and self.server_port:
+            logger.info("Reusing in-process server")
+            return True, self.server_port
 
         # For Colab environment, use a different strategy
         if _is_colab_environment():
             logger.info("Detected Colab environment, using alternative startup strategy")
             return self._start_server_colab(port, model_name, embedding_mode, **kwargs)
 
-        # Find a compatible port or next available
-        actual_port, is_compatible = _find_compatible_port_or_next_available(
-            port, model_name, passages_file
-        )
-
-        if is_compatible:
-            logger.info(f"Found compatible server on port {actual_port}")
-            return True, actual_port
+        # Always pick a fresh available port
+        try:
+            actual_port = _get_available_port(port)
+        except RuntimeError:
+            logger.error("No available ports found")
+            return False, port
 
         # Start a new server
         return self._start_new_server(actual_port, model_name, embedding_mode, **kwargs)
@@ -247,17 +131,7 @@ class EmbeddingServerManager:
             logger.error(f"Failed to start embedding server in Colab: {e}")
             return False, actual_port
 
-    def _has_compatible_running_server(self, model_name: str, passages_file: str) -> bool:
-        """Check if we have a compatible running server."""
-        if not (self.server_process and self.server_process.poll() is None and self.server_port):
-            return False
-
-        if _check_process_matches_config(self.server_port, model_name, passages_file):
-            logger.info(f"Existing server process (PID {self.server_process.pid}) is compatible")
-            return True
-
-        logger.info("Existing server process is incompatible. Should start a new server.")
-        return False
+    # Note: No compatibility check needed; manager is per-searcher and configs are stable per instance
 
     def _start_new_server(
         self, port: int, model_name: str, embedding_mode: str, **kwargs
@@ -304,22 +178,61 @@ class EmbeddingServerManager:
         project_root = Path(__file__).parent.parent.parent.parent.parent
         logger.info(f"Command: {' '.join(command)}")
 
-        # Let server output go directly to console
-        # The server will respect LEANN_LOG_LEVEL environment variable
+        # In CI environment, redirect stdout to avoid buffer deadlock but keep stderr for debugging
+        # Embedding servers use many print statements that can fill stdout buffers
+        is_ci = os.environ.get("CI") == "true"
+        if is_ci:
+            stdout_target = subprocess.DEVNULL
+            stderr_target = None  # Keep stderr for error debugging in CI
+            logger.info(
+                "CI environment detected, redirecting embedding server stdout to DEVNULL, keeping stderr"
+            )
+        else:
+            stdout_target = None  # Direct to console for visible logs
+            stderr_target = None  # Direct to console for visible logs
+
+        # Start embedding server subprocess
         self.server_process = subprocess.Popen(
             command,
             cwd=project_root,
-            stdout=None,  # Direct to console
-            stderr=None,  # Direct to console
+            stdout=stdout_target,
+            stderr=stderr_target,
         )
         self.server_port = port
+        # Record config for in-process reuse
+        try:
+            self._server_config = {
+                "model_name": command[command.index("--model-name") + 1]
+                if "--model-name" in command
+                else "",
+                "passages_file": command[command.index("--passages-file") + 1]
+                if "--passages-file" in command
+                else "",
+                "embedding_mode": command[command.index("--embedding-mode") + 1]
+                if "--embedding-mode" in command
+                else "sentence-transformers",
+            }
+        except Exception:
+            self._server_config = {
+                "model_name": "",
+                "passages_file": "",
+                "embedding_mode": "sentence-transformers",
+            }
         logger.info(f"Server process started with PID: {self.server_process.pid}")
 
         # Register atexit callback only when we actually start a process
         if not self._atexit_registered:
-            # Use a lambda to avoid issues with bound methods
-            atexit.register(lambda: self.stop_server() if self.server_process else None)
+            # Always attempt best-effort finalize at interpreter exit
+            atexit.register(self._finalize_process)
             self._atexit_registered = True
+        # Touch finalizer so it knows there is a live process
+        if getattr(self, "_finalizer", None) is not None and not self._finalizer.alive:
+            try:
+                import weakref
+
+                self._finalizer = weakref.finalize(self, self._finalize_process)
+            except Exception:
+                pass
 
     def _wait_for_server_ready(self, port: int) -> tuple[bool, int]:
         """Wait for the server to be ready."""
@@ -344,22 +257,26 @@ class EmbeddingServerManager:
         if not self.server_process:
             return
 
-        if self.server_process.poll() is not None:
+        if self.server_process and self.server_process.poll() is not None:
             # Process already terminated
             self.server_process = None
+            self.server_port = None
+            self._server_config = None
             return
 
         logger.info(
             f"Terminating server process (PID: {self.server_process.pid}) for backend {self.backend_module_name}..."
         )
+
+        # Use simple termination - our improved server shutdown should handle this properly
         self.server_process.terminate()
 
         try:
-            self.server_process.wait(timeout=3)
-            logger.info(f"Server process {self.server_process.pid} terminated.")
+            self.server_process.wait(timeout=5)  # Give more time for graceful shutdown
+            logger.info(f"Server process {self.server_process.pid} terminated gracefully.")
         except subprocess.TimeoutExpired:
             logger.warning(
-                f"Server process {self.server_process.pid} did not terminate gracefully within 3 seconds, killing it."
+                f"Server process {self.server_process.pid} did not terminate within 5 seconds, force killing..."
             )
             self.server_process.kill()
             try:
@@ -369,15 +286,33 @@ class EmbeddingServerManager:
                 logger.error(
                     f"Failed to kill server process {self.server_process.pid} - it may be hung"
                 )
-                # Don't hang indefinitely
 
-        # Clean up process resources to prevent resource tracker warnings
+        # Clean up process resources with timeout to avoid CI hang
         try:
-            self.server_process.wait()  # Ensure process is fully cleaned up
+            # Use shorter timeout in CI environments
+            is_ci = os.environ.get("CI") == "true"
+            timeout = 3 if is_ci else 10
+            self.server_process.wait(timeout=timeout)
+            logger.info(f"Server process {self.server_process.pid} cleanup completed")
+        except subprocess.TimeoutExpired:
+            logger.warning(f"Process cleanup timeout after {timeout}s, proceeding anyway")
+        except Exception as e:
+            logger.warning(f"Error during process cleanup: {e}")
+        finally:
+            self.server_process = None
+            self.server_port = None
+            self._server_config = None
+
+    def _finalize_process(self) -> None:
+        """Best-effort cleanup used by weakref.finalize/atexit."""
+        try:
+            self.stop_server()
         except Exception:
             pass
 
-        self.server_process = None
+    def _adopt_existing_server(self, *args, **kwargs) -> None:
+        # Removed: cross-process adoption no longer supported
+        return
 
     def _launch_server_process_colab(self, command: list, port: int) -> None:
         """Launch the server process with Colab-specific settings."""
@@ -393,10 +328,16 @@ class EmbeddingServerManager:
         self.server_port = port
         logger.info(f"Colab server process started with PID: {self.server_process.pid}")
 
-        # Register atexit callback
+        # Register atexit callback (unified)
         if not self._atexit_registered:
-            atexit.register(lambda: self.stop_server() if self.server_process else None)
+            atexit.register(self._finalize_process)
             self._atexit_registered = True
+        # Record config for in-process reuse is best-effort in Colab mode
+        self._server_config = {
+            "model_name": "",
+            "passages_file": "",
+            "embedding_mode": "sentence-transformers",
+        }
 
     def _wait_for_server_ready_colab(self, port: int) -> tuple[bool, int]:
         """Wait for the server to be ready with Colab-specific timeout."""

packages/leann-core/src/leann/interface.py

@@ -1,5 +1,5 @@
 from abc import ABC, abstractmethod
-from typing import Any, Literal, Union
+from typing import Any, Literal, Optional
 
 import numpy as np
 
@@ -35,7 +35,7 @@ class LeannBackendSearcherInterface(ABC):
 
     @abstractmethod
     def _ensure_server_running(
-        self, passages_source_file: str, port: Union[int, None], **kwargs
+        self, passages_source_file: str, port: Optional[int], **kwargs
     ) -> int:
         """Ensure server is running"""
         pass
@@ -50,7 +50,7 @@ class LeannBackendSearcherInterface(ABC):
         prune_ratio: float = 0.0,
         recompute_embeddings: bool = False,
         pruning_strategy: Literal["global", "local", "proportional"] = "global",
-        zmq_port: Union[int, None] = None,
+        zmq_port: Optional[int] = None,
         **kwargs,
     ) -> dict[str, Any]:
         """Search for nearest neighbors
@@ -76,7 +76,7 @@ class LeannBackendSearcherInterface(ABC):
         self,
         query: str,
         use_server_if_available: bool = True,
-        zmq_port: Union[int, None] = None,
+        zmq_port: Optional[int] = None,
     ) -> np.ndarray:
         """Compute embedding for a query string
 

packages/leann-core/src/leann/mcp.py

@@ -116,7 +116,6 @@ def handle_request(request):
                     f"--top-k={args.get('top_k', 5)}",
                     f"--complexity={args.get('complexity', 32)}",
                 ]
-
                 result = subprocess.run(cmd, capture_output=True, text=True)
 
             elif tool_name == "leann_status":