TxtAI MCP Server

""" Model2Vec module tests """ import os import unittest import numpy as np from txtai.vectors import VectorsFactory class TestModel2Vec(unittest.TestCase): """ Model2vec vectors tests """ @classmethod def setUpClass(cls): """ Create Model2Vec instance. """ cls.model = VectorsFactory.create({"path": "minishlab/potion-base-8M"}, None) def testIndex(self): """ Test indexing with Model2Vec vectors """ ids, dimension, batches, stream = self.model.index([(0, "test", None)]) self.assertEqual(len(ids), 1) self.assertEqual(dimension, 256) self.assertEqual(batches, 1) self.assertIsNotNone(os.path.exists(stream)) # Test shape of serialized embeddings with open(stream, "rb") as queue: self.assertEqual(np.load(queue).shape, (1, 256))