Files
LEANN/packages/leann-backend-hnsw/leann_backend_hnsw/hnsw_embedding_server.py
Andy Lee e26d6d9d14 fix: implement graceful shutdown for embedding servers
- Replace daemon threads with coordinated shutdown mechanism
- Add shutdown_event for thread synchronization
- Implement proper ZMQ resource cleanup
- Wait for threads to complete before exit
- Add ZMQ timeout to allow periodic shutdown checks
- Move signal handlers into server functions for proper scope access
- Fix protobuf class names and variable references
- Simplify resource cleanup to avoid variable scope issues

Root cause: Original servers used daemon threads + direct sys.exit(0)
which interrupted ZMQ operations and prevented proper resource cleanup,
causing hangs during process termination in CI environments.

This should resolve the core pytest hanging issue without complex wrappers.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-13 10:59:01 -07:00

421 lines
16 KiB
Python

"""
HNSW-specific embedding server
"""
import argparse
import json
import logging
import os
import sys
import threading
import time
from pathlib import Path
from typing import Optional
import msgpack
import numpy as np
import zmq
# Set up logging based on environment variable
LOG_LEVEL = os.getenv("LEANN_LOG_LEVEL", "WARNING").upper()
logger = logging.getLogger(__name__)
# Force set logger level (don't rely on basicConfig in subprocess)
log_level = getattr(logging, LOG_LEVEL, logging.WARNING)
logger.setLevel(log_level)
# Ensure we have a handler if none exists
if not logger.handlers:
handler = logging.StreamHandler()
formatter = logging.Formatter("%(asctime)s - %(levelname)s - %(message)s")
handler.setFormatter(formatter)
logger.addHandler(handler)
logger.propagate = False
def create_hnsw_embedding_server(
passages_file: Optional[str] = None,
zmq_port: int = 5555,
model_name: str = "sentence-transformers/all-mpnet-base-v2",
distance_metric: str = "mips",
embedding_mode: str = "sentence-transformers",
):
"""
Create and start a ZMQ-based embedding server for HNSW backend.
Simplified version using unified embedding computation module.
"""
logger.info(f"Starting HNSW server on port {zmq_port} with model {model_name}")
logger.info(f"Using embedding mode: {embedding_mode}")
# Add leann-core to path for unified embedding computation
current_dir = Path(__file__).parent
leann_core_path = current_dir.parent.parent / "leann-core" / "src"
sys.path.insert(0, str(leann_core_path))
try:
from leann.api import PassageManager
from leann.embedding_compute import compute_embeddings
logger.info("Successfully imported unified embedding computation module")
except ImportError as e:
logger.error(f"Failed to import embedding computation module: {e}")
return
finally:
sys.path.pop(0)
# Check port availability
import socket
def check_port(port):
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
return s.connect_ex(("localhost", port)) == 0
if check_port(zmq_port):
logger.error(f"Port {zmq_port} is already in use")
return
# Only support metadata file, fail fast for everything else
if not passages_file or not passages_file.endswith(".meta.json"):
raise ValueError("Only metadata files (.meta.json) are supported")
# Load metadata to get passage sources
with open(passages_file) as f:
meta = json.load(f)
# Let PassageManager handle path resolution uniformly
passages = PassageManager(meta["passage_sources"], metadata_file_path=passages_file)
logger.info(
f"Loaded PassageManager with {len(passages.global_offset_map)} passages from metadata"
)
def zmq_server_thread():
"""ZMQ server thread"""
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}")
socket.setsockopt(zmq.RCVTIMEO, 300000)
socket.setsockopt(zmq.SNDTIMEO, 300000)
while True:
try:
message_bytes = socket.recv()
logger.debug(f"Received ZMQ request of size {len(message_bytes)} bytes")
e2e_start = time.time()
request_payload = msgpack.unpackb(message_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"
)
# 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))
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)
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:
try:
passage_data = passages.get_passage(str(nid))
txt = passage_data["text"]
texts.append(txt)
except KeyError:
logger.error(f"Passage ID {nid} not found")
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
# Process embeddings
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)
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")
socket.send(response_bytes)
e2e_end = time.time()
logger.info(f"⏱️ Distance calculation E2E time: {e2e_end - e2e_start:.6f}s")
continue
# 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
node_ids = request_payload[0]
logger.debug(f"Request for {len(node_ids)} node embeddings")
# 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
# Process embeddings
embeddings = compute_embeddings(texts, model_name, mode=embedding_mode)
logger.info(
f"Computed embeddings for {len(texts)} texts, shape: {embeddings.shape}"
)
# 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()
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)
socket.send(response_bytes)
e2e_end = time.time()
logger.info(f"⏱️ ZMQ E2E time: {e2e_end - e2e_start:.6f}s")
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
traceback.print_exc()
socket.send(msgpack.packb([[], []]))
def zmq_server_thread_with_shutdown(shutdown_event):
"""ZMQ server thread that respects shutdown signal."""
logger.info("ZMQ server thread started with shutdown support")
# Set receive timeout so we can check shutdown_event periodically
socket.setsockopt(zmq.RCVTIMEO, 1000) # 1 second timeout
while not shutdown_event.is_set():
try:
e2e_start = time.time()
logger.debug("🔍 Waiting for ZMQ message...")
request_bytes = socket.recv(zmq.NOBLOCK)
# Rest of the processing logic (same as original)
request = msgpack.unpackb(request_bytes)
if len(request) == 1 and request[0] == "__QUERY_MODEL__":
response_bytes = msgpack.packb([model_name])
socket.send(response_bytes)
continue
node_ids = request
logger.info(f"ZMQ received {len(node_ids)} node IDs")
texts = []
for nid in node_ids:
try:
txt = passages.get_text(nid)
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
embeddings = compute_embeddings(texts, model_name, mode=embedding_mode)
logger.info(
f"Computed embeddings for {len(texts)} texts, shape: {embeddings.shape}"
)
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()
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)
socket.send(response_bytes)
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:
socket.send(msgpack.packb([[], []]))
except Exception:
pass
else:
logger.info("Shutdown in progress, ignoring ZMQ error")
break
logger.info("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)
# 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 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 sys
# 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")
parser.add_argument(
"--passages-file",
type=str,
help="JSON file containing passage ID to text mapping",
)
parser.add_argument(
"--model-name",
type=str,
default="sentence-transformers/all-mpnet-base-v2",
help="Embedding model name",
)
parser.add_argument(
"--distance-metric", type=str, default="mips", help="Distance metric to use"
)
parser.add_argument(
"--embedding-mode",
type=str,
default="sentence-transformers",
choices=["sentence-transformers", "openai", "mlx", "ollama"],
help="Embedding backend mode",
)
args = parser.parse_args()
# Create and start the HNSW embedding server
create_hnsw_embedding_server(
passages_file=args.passages_file,
zmq_port=args.zmq_port,
model_name=args.model_name,
distance_metric=args.distance_metric,
embedding_mode=args.embedding_mode,
)