Test memory leak on MPS device when generating vector embeddings

Slope threshold of 2.0 determined qualitatively on local Mac device
Minor unused import and clean-up

pyproject.toml

@@ -92,6 +92,7 @@ test = [
     "factory-boy >= 3.2.1",
     "trio >= 0.22.0",
     "pytest-xdist",
+    "psutil >= 5.8.0",
 ]
 dev = [
     "khoj-assistant[test]",

src/database/adapters/__init__.py

@@ -1,4 +1,3 @@
-import secrets
 from typing import Type, TypeVar, List
 from datetime import date
 import secrets
@@ -36,9 +35,6 @@ from database.models import (
     OfflineChatProcessorConversationConfig,
 )
 from khoj.utils.helpers import generate_random_name
-from khoj.utils.rawconfig import (
-    ConversationProcessorConfig as UserConversationProcessorConfig,
-)
 from khoj.search_filter.word_filter import WordFilter
 from khoj.search_filter.file_filter import FileFilter
 from khoj.search_filter.date_filter import DateFilter

src/khoj/processor/embeddings.py

@@ -8,10 +8,10 @@ from khoj.utils.rawconfig import SearchResponse
 
 class EmbeddingsModel:
     def __init__(self):
-        self.model_name = "thenlper/gte-small"
         self.encode_kwargs = {"normalize_embeddings": True}
-        model_kwargs = {"device": get_device()}
-        self.embeddings_model = SentenceTransformer(self.model_name, **model_kwargs)
+        self.model_kwargs = {"device": get_device()}
+        self.model_name = "thenlper/gte-small"
+        self.embeddings_model = SentenceTransformer(self.model_name, **self.model_kwargs)
 
     def embed_query(self, query):
         return self.embeddings_model.encode([query], show_progress_bar=False, **self.encode_kwargs)[0]

tests/test_helpers.py

@@ -1,3 +1,14 @@
+# Standard Packages
+import numpy as np
+import psutil
+from scipy.stats import linregress
+import secrets
+
+# External Packages
+import pytest
+
+# Internal Packages
+from khoj.processor.embeddings import EmbeddingsModel
 from khoj.utils import helpers
 
 
@@ -44,3 +55,29 @@ def test_lru_cache():
     cache["b"]  # accessing 'b' makes it the most recently used item
     cache["d"] = 4  # so 'c' is deleted from the cache instead of 'b'
     assert cache == {"b": 2, "d": 4}
+
+
+@pytest.mark.skip(reason="Memory leak exists on GPU, MPS devices")
+def test_encode_docs_memory_leak():
+    # Arrange
+    iterations = 50
+    batch_size = 20
+    embeddings_model = EmbeddingsModel()
+    memory_usage_trend = []
+
+    # Act
+    # Encode random strings repeatedly and record memory usage trend
+    for iteration in range(iterations):
+        random_docs = [" ".join(secrets.token_hex(5) for _ in range(10)) for _ in range(batch_size)]
+        a = [embeddings_model.embed_documents(random_docs)]
+        memory_usage_trend += [psutil.Process().memory_info().rss / (1024 * 1024)]
+        print(f"{iteration:02d}, {memory_usage_trend[-1]:.2f}", flush=True)
+
+    # Calculate slope of line fitting memory usage history
+    memory_usage_trend = np.array(memory_usage_trend)
+    slope, _, _, _, _ = linregress(np.arange(len(memory_usage_trend)), memory_usage_trend)
+
+    # Assert
+    # If slope is positive memory utilization is increasing
+    # Positive threshold of 2, from observing memory usage trend on MPS vs CPU device
+    assert slope < 2, f"Memory usage increasing at ~{slope:.2f} MB per iteration"