fix: Added @synchronized to EphemeralClient

- Added a multi-treaded synchronization test

chromadb/__init__.py

@@ -91,6 +91,7 @@ def get_settings() -> Settings:
     return __settings
 
 
+@synchronized
 def EphemeralClient(settings: Settings = Settings()) -> API:
     """
     Creates an in-memory instance of Chroma. This is useful for testing and

chromadb/test/test_multithreaded.py

@@ -1,10 +1,11 @@
 import multiprocessing
 from concurrent.futures import Future, ThreadPoolExecutor, wait
 import random
+import uuid
 import threading
 from typing import Any, Dict, List, Optional, Set, Tuple, cast
 import numpy as np
-
+import chromadb
 from chromadb.api import API
 import chromadb.test.property.invariants as invariants
 from chromadb.test.property.strategies import RecordSet
@@ -64,7 +65,8 @@ def _test_multithreaded_add(api: API, N: int, D: int, num_workers: int) -> None:
                 coll.add,
                 ids=ids[start:end],
                 embeddings=embeddings[start:end] if embeddings is not None else None,
-                metadatas=metadatas[start:end] if metadatas is not None else None,  # type: ignore
+                # type: ignore
+                metadatas=metadatas[start:end] if metadatas is not None else None,
                 documents=documents[start:end] if documents is not None else None,
             )
             futures.append(future)
@@ -141,7 +143,8 @@ def perform_operation(
             n_results = 5
             with lock:
                 currently_added_ids = list(added_ids.copy())
-            currently_added_indices = [ids.index(id) for id in currently_added_ids]
+            currently_added_indices = [
+                ids.index(id) for id in currently_added_ids]
             if (
                 len(currently_added_ids) == 0
                 or len(currently_added_indices) < n_results
@@ -173,7 +176,8 @@ def perform_operation(
                 to_send = min(batch_size, len(ids) - total_sent)
                 start = total_sent + 1
                 end = total_sent + to_send + 1
-                future = executor.submit(perform_operation, operation, ids[start:end])
+                future = executor.submit(
+                    perform_operation, operation, ids[start:end])
                 futures.append(future)
                 total_sent += to_send
             elif operation == 1:
@@ -219,3 +223,73 @@ def test_interleaved_add_query(api: API) -> None:
         num_workers = random.randint(2, multiprocessing.cpu_count() * 2)
         N, D = generate_data_shape()
         _test_interleaved_add_query(api, N, D, num_workers)
+
+
+def _test_serialized_access(N: int, D: int, num_workers: int) -> None:
+    records_set = generate_record_set(N, D)
+    ids = records_set["ids"]
+    embeddings = records_set["embeddings"]
+    metadatas = records_set["metadatas"]
+    documents = records_set["documents"]
+
+    print(f"Adding {N} records with {D} dimensions on {num_workers} workers")
+
+    # TODO: batch_size and sync_threshold should be configurable
+    def _create_client_and_add(**add_args) -> None:
+        # api = chromadb.PersistentClient(path="./test-db")
+        api = chromadb.EphemeralClient()
+        coll = api.create_collection(
+            name=f"test-{uuid.uuid4()}", metadata=test_hnsw_config)
+        coll.add(**add_args)
+        _t_record_set = RecordSet(**add_args)
+        # Check that invariants hold
+        invariants.count(coll, _t_record_set)
+        invariants.ids_match(coll, _t_record_set)
+        invariants.metadatas_match(coll, _t_record_set)
+        invariants.no_duplicates(coll)
+        # Check that the ANN accuracy is good
+        # On a random subset of the dataset
+        query_indices = random.sample([i for i in range(N)], 10)
+        n_results = 5
+        invariants.ann_accuracy(
+            coll,
+            records_set,
+            n_results=n_results,
+            query_indices=query_indices,
+        )
+    with ThreadPoolExecutor(max_workers=num_workers) as executor:
+
+        futures: List[Future[Any]] = []
+        total_sent = -1
+        while total_sent < len(ids):
+            # Randomly grab up to 10% of the dataset and send it to the executor
+            batch_size = random.randint(1, N // 10)
+            to_send = min(batch_size, len(ids) - total_sent)
+            start = total_sent + 1
+            end = total_sent + to_send + 1
+            if embeddings is not None and len(embeddings[start:end]) == 0:
+                break
+            future = executor.submit(
+                _create_client_and_add,
+                ids=ids[start:end],
+                embeddings=embeddings[start:end] if embeddings is not None else None,
+                # type: ignore
+                metadatas=metadatas[start:end] if metadatas is not None else None,
+                documents=documents[start:end] if documents is not None else None,
+            )
+            futures.append(future)
+            total_sent += to_send
+
+    wait(futures)
+
+    for future in futures:
+        exception = future.exception()
+        if exception is not None:
+            raise exception
+
+
+def test_serialized_access() -> None:
+    for i in range(3):
+        num_workers = random.randint(2, multiprocessing.cpu_count() * 2)
+        N, D = generate_data_shape()
+        _test_serialized_access(N, D, num_workers)