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| 1 | +"""Tests for memory embedding dimension consistency.""" |
| 2 | +from unittest.mock import MagicMock, patch |
| 3 | +from runtime.node.agent.memory.memory_base import MemoryContentSnapshot, MemoryItem |
| 4 | +from runtime.node.agent.memory.simple_memory import SimpleMemory |
| 5 | + |
| 6 | +def _make_store(memory_path=None): |
| 7 | + """Build a minimal MemoryStoreConfig mock for SimpleMemory.""" |
| 8 | + simple_cfg = MagicMock() |
| 9 | + simple_cfg.memory_path = memory_path |
| 10 | + simple_cfg.embedding = None # We'll set embedding manually |
| 11 | + |
| 12 | + store = MagicMock() |
| 13 | + store.name = "test_store" |
| 14 | + store.as_config.return_value = simple_cfg |
| 15 | + return store |
| 16 | + |
| 17 | + |
| 18 | +def _make_embedding(dim: int): |
| 19 | + """Create a mock EmbeddingBase that produces vectors of the given dimension.""" |
| 20 | + emb = MagicMock() |
| 21 | + emb.get_embedding.return_value = [0.1] * dim |
| 22 | + return emb |
| 23 | + |
| 24 | + |
| 25 | +def _make_memory_item(item_id: str, dim: int): |
| 26 | + """Create a MemoryItem with an embedding of the specified dimension.""" |
| 27 | + return MemoryItem( |
| 28 | + id=item_id, |
| 29 | + content_summary=f"content for {item_id}", |
| 30 | + metadata={}, |
| 31 | + embedding=[float(i) for i in range(dim)], |
| 32 | + ) |
| 33 | + |
| 34 | + |
| 35 | +class TestSimpleMemoryRetrieveMixedDimensions: |
| 36 | + |
| 37 | + def test_mixed_dimensions_does_not_crash(self): |
| 38 | + """Retrieve with mixed-dimensional embeddings MUST not raise.""" |
| 39 | + store = _make_store() |
| 40 | + memory = SimpleMemory(store) |
| 41 | + memory.embedding = _make_embedding(dim=768) |
| 42 | + |
| 43 | + # 3 items with correct dim, 2 with wrong dim |
| 44 | + memory.contents = [ |
| 45 | + _make_memory_item("ok_1", 768), |
| 46 | + _make_memory_item("bad_1", 1536), |
| 47 | + _make_memory_item("ok_2", 768), |
| 48 | + _make_memory_item("bad_2", 256), |
| 49 | + _make_memory_item("ok_3", 768), |
| 50 | + ] |
| 51 | + |
| 52 | + query = MemoryContentSnapshot(text="test query") |
| 53 | + # Should NOT raise ValueError / numpy error |
| 54 | + results = memory.retrieve( |
| 55 | + agent_role="tester", |
| 56 | + query=query, |
| 57 | + top_k=5, |
| 58 | + similarity_threshold=-1.0, |
| 59 | + ) |
| 60 | + # Only the 3 correct-dimension items should be candidates |
| 61 | + assert len(results) <= 3 |
| 62 | + |
| 63 | + def test_all_same_dimension_returns_results(self): |
| 64 | + """When all embeddings share the correct dimension, all are candidates.""" |
| 65 | + store = _make_store() |
| 66 | + memory = SimpleMemory(store) |
| 67 | + memory.embedding = _make_embedding(dim=768) |
| 68 | + |
| 69 | + memory.contents = [ |
| 70 | + _make_memory_item("a", 768), |
| 71 | + _make_memory_item("b", 768), |
| 72 | + ] |
| 73 | + |
| 74 | + query = MemoryContentSnapshot(text="test query") |
| 75 | + results = memory.retrieve( |
| 76 | + agent_role="tester", |
| 77 | + query=query, |
| 78 | + top_k=5, |
| 79 | + similarity_threshold=-1.0, |
| 80 | + ) |
| 81 | + assert len(results) == 2 |
| 82 | + |
| 83 | + def test_all_wrong_dimension_returns_empty(self): |
| 84 | + """When every stored embedding has a wrong dimension, return empty.""" |
| 85 | + store = _make_store() |
| 86 | + memory = SimpleMemory(store) |
| 87 | + memory.embedding = _make_embedding(dim=768) |
| 88 | + |
| 89 | + memory.contents = [ |
| 90 | + _make_memory_item("x", 1536), |
| 91 | + _make_memory_item("y", 1536), |
| 92 | + ] |
| 93 | + |
| 94 | + query = MemoryContentSnapshot(text="test query") |
| 95 | + results = memory.retrieve( |
| 96 | + agent_role="tester", |
| 97 | + query=query, |
| 98 | + top_k=5, |
| 99 | + similarity_threshold=-1.0, |
| 100 | + ) |
| 101 | + assert results == [] |
| 102 | + |
| 103 | + |
| 104 | +class TestOpenAIEmbeddingDynamicFallback: |
| 105 | + |
| 106 | + def test_fallback_uses_model_dimension_after_success(self): |
| 107 | + """After a successful call the fallback dimension MUST match the model.""" |
| 108 | + from runtime.node.agent.memory.embedding import OpenAIEmbedding |
| 109 | + |
| 110 | + cfg = MagicMock() |
| 111 | + cfg.base_url = "http://localhost:11434/v1" |
| 112 | + cfg.api_key = "test" |
| 113 | + cfg.model = "test-model" |
| 114 | + cfg.params = {} |
| 115 | + |
| 116 | + emb = OpenAIEmbedding(cfg) |
| 117 | + assert emb._fallback_dim == 1536 # default before any call |
| 118 | + |
| 119 | + # Simulate a successful 768-dim response |
| 120 | + mock_data = MagicMock() |
| 121 | + mock_data.embedding = [0.1] * 768 |
| 122 | + mock_response = MagicMock() |
| 123 | + mock_response.data = [mock_data] |
| 124 | + |
| 125 | + with patch.object(emb.client.embeddings, "create", return_value=mock_response): |
| 126 | + result = emb.get_embedding("hello world") |
| 127 | + |
| 128 | + assert len(result) == 768 |
| 129 | + assert emb._fallback_dim == 768 # updated after success |
| 130 | + |
| 131 | + def test_fallback_zero_vector_matches_cached_dim(self): |
| 132 | + """After caching dim, fallback zero-vectors MUST use that dim.""" |
| 133 | + from runtime.node.agent.memory.embedding import OpenAIEmbedding |
| 134 | + |
| 135 | + cfg = MagicMock() |
| 136 | + cfg.base_url = "http://localhost:11434/v1" |
| 137 | + cfg.api_key = "test" |
| 138 | + cfg.model = "test-model" |
| 139 | + cfg.params = {} |
| 140 | + |
| 141 | + emb = OpenAIEmbedding(cfg) |
| 142 | + |
| 143 | + # Simulate successful 512-dim call |
| 144 | + mock_data = MagicMock() |
| 145 | + mock_data.embedding = [0.1] * 512 |
| 146 | + mock_response = MagicMock() |
| 147 | + mock_response.data = [mock_data] |
| 148 | + |
| 149 | + with patch.object(emb.client.embeddings, "create", return_value=mock_response): |
| 150 | + emb.get_embedding("first call") |
| 151 | + |
| 152 | + # Now simulate a failure — fallback should be 512-dim |
| 153 | + with patch.object(emb.client.embeddings, "create", side_effect=Exception("API down")): |
| 154 | + fallback = emb.get_embedding("failing call") |
| 155 | + |
| 156 | + assert len(fallback) == 512 |
| 157 | + assert all(v == 0.0 for v in fallback) |
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