42 lines
1.5 KiB
Python
42 lines
1.5 KiB
Python
import pytest
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from unittest.mock import Mock, patch
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from mem0.embeddings.lmstudio import LMStudioEmbedding
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from mem0.configs.embeddings.base import BaseEmbedderConfig
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@pytest.fixture
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def mock_lm_studio_client():
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with patch("mem0.embeddings.lmstudio.Client") as mock_lm_studio:
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mock_client = Mock()
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mock_client.list.return_value = {"models": [{"name": "nomic-embed-text-v1.5-GGUF/nomic-embed-text-v1.5.f16.gguf"}]}
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mock_lm_studio.return_value = mock_client
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yield mock_client
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def test_embed_text(mock_lm_studio_client):
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config = BaseEmbedderConfig(model="nomic-embed-text-v1.5-GGUF/nomic-embed-text-v1.5.f16.gguf", embedding_dims=512)
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embedder = LMStudioEmbedding(config)
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mock_response = {"embedding": [0.1, 0.2, 0.3, 0.4, 0.5]}
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mock_lm_studio_client.embeddings.return_value = mock_response
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text = "Sample text to embed."
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embedding = embedder.embed(text)
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mock_lm_studio_client.embeddings.assert_called_once_with(model="nomic-embed-text-v1.5-GGUF/nomic-embed-text-v1.5.f16.gguf", prompt=text)
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assert embedding == [0.1, 0.2, 0.3, 0.4, 0.5]
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def test_ensure_model_exists(mock_lm_studio_client):
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config = BaseEmbedderConfig(model="nomic-embed-text-v1.5-GGUF/nomic-embed-text-v1.5.f16.gguf", embedding_dims=512)
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embedder = LMStudioEmbedding(config)
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mock_lm_studio_client.pull.assert_not_called()
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mock_lm_studio_client.list.return_value = {"models": []}
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embedder._ensure_model_exists()
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mock_lm_studio_client.pull.assert_called_once_with("nomic-embed-text")
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