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332 lines
11 KiB
Python
332 lines
11 KiB
Python
"""
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Graph module tests
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"""
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import os
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import itertools
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import tempfile
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import unittest
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from txtai.embeddings import Embeddings
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from txtai.graph import Graph, GraphFactory
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class TestGraph(unittest.TestCase):
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"""
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Graph tests.
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"""
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@classmethod
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def setUpClass(cls):
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"""
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Initialize test data.
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"""
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cls.data = [
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"US tops 5 million confirmed virus cases",
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"Canada's last fully intact ice shelf has suddenly collapsed, forming a Manhattan-sized iceberg",
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"Beijing mobilises invasion craft along coast as Taiwan tensions escalate",
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"The National Park Service warns against sacrificing slower friends in a bear attack",
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"Maine man wins $1M from $25 lottery ticket",
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"Make huge profits without work, earn up to $100,000 a day",
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]
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cls.config = {
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"path": "sentence-transformers/nli-mpnet-base-v2",
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"content": True,
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"functions": [{"name": "graph", "function": "graph.attribute"}],
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"expressions": [
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{"name": "category", "expression": "graph(indexid, 'category')"},
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{"name": "topic", "expression": "graph(indexid, 'topic')"},
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{"name": "topicrank", "expression": "graph(indexid, 'topicrank')"},
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],
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"graph": {"limit": 5, "minscore": 0.2, "batchsize": 4, "approximate": False, "topics": {"categories": ["News"], "stopwords": ["the"]}},
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}
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# Create embeddings instance
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cls.embeddings = Embeddings(cls.config)
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def testAnalysis(self):
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"""
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Test analysis methods
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"""
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# Create an index for the list of text
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self.embeddings.index([(uid, text, None) for uid, text in enumerate(self.data)])
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# Graph centrality
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graph = self.embeddings.graph
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centrality = graph.centrality()
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self.assertEqual(list(centrality.keys())[0], 5)
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# Page Rank
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pagerank = graph.pagerank()
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self.assertEqual(list(pagerank.keys())[0], 5)
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# Path between nodes
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path = graph.showpath(4, 5)
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self.assertEqual(len(path), 2)
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def testCommunity(self):
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"""
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Test community detection
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"""
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# Create an index for the list of text
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self.embeddings.index([(uid, text, None) for uid, text in enumerate(self.data)])
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# Get graph reference
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graph = self.embeddings.graph
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# Rebuild topics with updated graph settings
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graph.config = {"topics": {"algorithm": "greedy"}}
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graph.addtopics()
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self.assertEqual(sum((len(graph.topics[x]) for x in graph.topics)), 6)
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graph.config = {"topics": {"algorithm": "lpa"}}
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graph.addtopics()
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self.assertEqual(sum((len(graph.topics[x]) for x in graph.topics)), 4)
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def testCustomBackend(self):
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"""
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Test resolving a custom backend
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"""
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graph = GraphFactory.create({"backend": "txtai.graph.NetworkX"})
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graph.initialize()
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self.assertIsNotNone(graph)
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def testCustomBackendNotFound(self):
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"""
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Test resolving an unresolvable backend
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"""
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with self.assertRaises(ImportError):
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graph = GraphFactory.create({"backend": "notfound.graph"})
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graph.initialize()
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def testDelete(self):
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"""
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Test delete
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"""
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# Create an index for the list of text
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self.embeddings.index([(uid, text, None) for uid, text in enumerate(self.data)])
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# Delete row
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self.embeddings.delete([4])
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# Validate counts
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graph = self.embeddings.graph
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self.assertEqual(graph.count(), 5)
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self.assertEqual(graph.edgecount(), 1)
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self.assertEqual(sum((len(graph.topics[x]) for x in graph.topics)), 5)
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self.assertEqual(len(graph.categories), 6)
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def testFunction(self):
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"""
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Test running graph functions with SQL
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"""
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# Create an index for the list of text
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self.embeddings.index([(uid, text, None) for uid, text in enumerate(self.data)])
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# Test function
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result = self.embeddings.search("select category, topic, topicrank from txtai where id = 0", 1)[0]
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# Check columns have a value
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self.assertIsNotNone(result["category"])
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self.assertIsNotNone(result["topic"])
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self.assertIsNotNone(result["topicrank"])
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def testFunctionReindex(self):
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"""
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Test running graph functions with SQL after reindex
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"""
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# Create an index for the list of text
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self.embeddings.index([(uid, text, None) for uid, text in enumerate(self.data)])
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# Test functions reset with a reindex
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self.embeddings.reindex(self.embeddings.config)
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# Test function
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result = self.embeddings.search("select category, topic, topicrank from txtai where id = 0", 1)[0]
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# Check columns have a value
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self.assertIsNotNone(result["category"])
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self.assertIsNotNone(result["topic"])
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self.assertIsNotNone(result["topicrank"])
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def testIndex(self):
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"""
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Test index
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"""
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# Create an index for the list of text
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self.embeddings.index([(uid, text, None) for uid, text in enumerate(self.data)])
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# Validate counts
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graph = self.embeddings.graph
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self.assertEqual(graph.count(), 6)
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self.assertEqual(graph.edgecount(), 2)
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self.assertEqual(len(graph.topics), 6)
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self.assertEqual(len(graph.categories), 6)
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def testNotImplemented(self):
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"""
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Test exceptions for non-implemented methods
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"""
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graph = Graph({})
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self.assertRaises(NotImplementedError, graph.create)
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self.assertRaises(NotImplementedError, graph.count)
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self.assertRaises(NotImplementedError, graph.scan, None)
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self.assertRaises(NotImplementedError, graph.node, None)
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self.assertRaises(NotImplementedError, graph.addnode, None)
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self.assertRaises(NotImplementedError, graph.removenode, None)
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self.assertRaises(NotImplementedError, graph.hasnode, None)
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self.assertRaises(NotImplementedError, graph.attribute, None, None)
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self.assertRaises(NotImplementedError, graph.addattribute, None, None, None)
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self.assertRaises(NotImplementedError, graph.removeattribute, None, None)
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self.assertRaises(NotImplementedError, graph.edgecount)
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self.assertRaises(NotImplementedError, graph.edges, None)
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self.assertRaises(NotImplementedError, graph.addedge, None, None)
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self.assertRaises(NotImplementedError, graph.hasedge, None, None)
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self.assertRaises(NotImplementedError, graph.centrality)
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self.assertRaises(NotImplementedError, graph.pagerank)
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self.assertRaises(NotImplementedError, graph.showpath, None, None)
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self.assertRaises(NotImplementedError, graph.communities, None)
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self.assertRaises(NotImplementedError, graph.loadgraph, None)
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self.assertRaises(NotImplementedError, graph.savegraph, None)
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def testResetTopics(self):
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"""
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Test resetting of topics
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"""
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# Create an index for the list of text
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self.embeddings.index([(1, "text", None)])
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self.embeddings.upsert([(1, "graph", None)])
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self.assertEqual(list(self.embeddings.graph.topics.keys()), ["graph"])
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def testSave(self):
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"""
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Test save
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"""
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# Create an index for the list of text
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self.embeddings.index([(uid, text, None) for uid, text in enumerate(self.data)])
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# Generate temp file path
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index = os.path.join(tempfile.gettempdir(), "graph")
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# Save and reload index
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self.embeddings.save(index)
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self.embeddings.load(index)
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# Validate counts
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graph = self.embeddings.graph
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self.assertEqual(graph.count(), 6)
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self.assertEqual(graph.edgecount(), 2)
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self.assertEqual(sum((len(graph.topics[x]) for x in graph.topics)), 6)
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self.assertEqual(len(graph.categories), 6)
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def testSimple(self):
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"""
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Test creating a simple graph
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"""
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graph = GraphFactory.create({"topics": {}})
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# Initialize the graph
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graph.initialize()
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for x in range(5):
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graph.addnode(x)
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for x, y in itertools.combinations(range(5), 2):
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graph.addedge(x, y)
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# Validate counts
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self.assertEqual(graph.count(), 5)
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self.assertEqual(graph.edgecount(), 10)
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# Test missing edge
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self.assertIsNone(graph.edges(100))
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# Test topics with no text
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graph.addtopics()
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self.assertEqual(len(graph.topics), 5)
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def testSubindex(self):
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"""
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Test subindex
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"""
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# Build data array
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data = [(uid, text, None) for uid, text in enumerate(self.data)]
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embeddings = Embeddings(
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{
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"content": True,
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"functions": [{"name": "graph", "function": "indexes.index1.graph.attribute"}],
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"expressions": [
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{"name": "category", "expression": "graph(indexid, 'category')"},
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{"name": "topic", "expression": "graph(indexid, 'topic')"},
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{"name": "topicrank", "expression": "graph(indexid, 'topicrank')"},
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],
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"indexes": {
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"index1": {
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"path": "sentence-transformers/nli-mpnet-base-v2",
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"graph": {
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"limit": 5,
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"minscore": 0.2,
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"batchsize": 4,
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"approximate": False,
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"topics": {"categories": ["News"], "stopwords": ["the"]},
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},
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}
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},
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}
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)
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# Create an index for the list of text
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embeddings.index(data)
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# Test function
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result = embeddings.search("select id, category, topic, topicrank from txtai where id = 0", 1)[0]
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# Check columns have a value
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self.assertIsNotNone(result["category"])
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self.assertIsNotNone(result["topic"])
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self.assertIsNotNone(result["topicrank"])
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# Update data
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data[0] = (0, "Feel good story: lottery winner announced", None)
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embeddings.upsert([data[0]])
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# Test function
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result = embeddings.search("select id, category, topic, topicrank from txtai where id = 0", 1)[0]
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# Check columns have a value
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self.assertIsNotNone(result["category"])
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self.assertIsNotNone(result["topic"])
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self.assertIsNotNone(result["topicrank"])
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def testUpsert(self):
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"""
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Test upsert
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"""
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# Update data
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self.embeddings.upsert([(0, {"text": "Canadian ice shelf collapses".split()}, None)])
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# Validate counts
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graph = self.embeddings.graph
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self.assertEqual(graph.count(), 6)
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self.assertEqual(graph.edgecount(), 2)
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self.assertEqual(sum((len(graph.topics[x]) for x in graph.topics)), 6)
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self.assertEqual(len(graph.categories), 6)
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