TxtAI MCP Server

""" Sparse Sentence Transformers module tests """ import os import unittest from txtai.vectors import SparseVectorsFactory from txtai.util import SparseArray class TestSparseSTVectors(unittest.TestCase): """ SparseSTVectors tests """ def testIndex(self): """ Test indexing with sentence-transformers vectors """ model = SparseVectorsFactory.create({"method": "sentence-transformers", "path": "sparse-encoder-testing/splade-bert-tiny-nq"}) ids, dimension, batches, stream = model.index([(0, "test", None)]) self.assertEqual(len(ids), 1) self.assertEqual(dimension, 30522) self.assertEqual(batches, 1) self.assertIsNotNone(os.path.exists(stream)) # Test shape of serialized embeddings with open(stream, "rb") as queue: self.assertEqual(SparseArray().load(queue).shape, (1, 30522))