chore: import upstream snapshot with attribution

test/python/testvectors/testdense/testexternal.py

@@ -0,0 +1,54 @@
+"""
+External module tests
+"""
+
+import os
+import unittest
+
+import numpy as np
+
+from txtai.vectors import External, VectorsFactory
+
+
+class TestExternal(unittest.TestCase):
+    """
+    External vectors tests
+    """
+
+    @classmethod
+    def setUpClass(cls):
+        """
+        Create External vectors instance.
+        """
+
+        cls.model = VectorsFactory.create({"method": "external"}, None)
+
+    def testIndex(self):
+        """
+        Test indexing with external vectors
+        """
+
+        # Generate dummy data
+        data = np.random.rand(1000, 768).astype(np.float32)
+
+        # Generate enough volume to test batching
+        documents = [(x, data[x], None) for x in range(1000)]
+
+        ids, dimension, batches, stream = self.model.index(documents)
+
+        self.assertEqual(len(ids), 1000)
+        self.assertEqual(dimension, 768)
+        self.assertEqual(batches, 2)
+        self.assertIsNotNone(os.path.exists(stream))
+
+        # Test shape of serialized embeddings
+        with open(stream, "rb") as queue:
+            self.assertEqual(np.load(queue).shape, (500, 768))
+
+    def testMethod(self):
+        """
+        Test method is derived when transform function passed
+        """
+
+        model = VectorsFactory.create({"transform": lambda x: x}, None)
+        self.assertTrue(isinstance(model, External))