Atharva Jaiswal
110 lines
4.0 KiB
Python
110 lines
4.0 KiB
Python
from unittest.mock import Mock, patch
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import pytest
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from mem0.configs.embeddings.base import BaseEmbedderConfig
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from mem0.embeddings.openai import OpenAIEmbedding
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@pytest.fixture
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def mock_openai_client():
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with patch("mem0.embeddings.openai.OpenAI") as mock_openai:
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mock_client = Mock()
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mock_openai.return_value = mock_client
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yield mock_client
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def test_embed_default_model(mock_openai_client):
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config = BaseEmbedderConfig()
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embedder = OpenAIEmbedding(config)
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mock_response = Mock()
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mock_response.data = [Mock(embedding=[0.1, 0.2, 0.3])]
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mock_openai_client.embeddings.create.return_value = mock_response
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result = embedder.embed("Hello world")
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mock_openai_client.embeddings.create.assert_called_once_with(
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input=["Hello world"], model="text-embedding-3-small", dimensions=1536, encoding_format="float"
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)
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assert result == [0.1, 0.2, 0.3]
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def test_embed_custom_model(mock_openai_client):
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config = BaseEmbedderConfig(model="text-embedding-2-medium", embedding_dims=1024)
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embedder = OpenAIEmbedding(config)
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mock_response = Mock()
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mock_response.data = [Mock(embedding=[0.4, 0.5, 0.6])]
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mock_openai_client.embeddings.create.return_value = mock_response
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result = embedder.embed("Test embedding")
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mock_openai_client.embeddings.create.assert_called_once_with(
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input=["Test embedding"], model="text-embedding-2-medium", dimensions=1024, encoding_format="float"
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)
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assert result == [0.4, 0.5, 0.6]
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def test_embed_removes_newlines(mock_openai_client):
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config = BaseEmbedderConfig()
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embedder = OpenAIEmbedding(config)
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mock_response = Mock()
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mock_response.data = [Mock(embedding=[0.7, 0.8, 0.9])]
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mock_openai_client.embeddings.create.return_value = mock_response
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result = embedder.embed("Hello\nworld")
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mock_openai_client.embeddings.create.assert_called_once_with(
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input=["Hello world"], model="text-embedding-3-small", dimensions=1536, encoding_format="float"
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)
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assert result == [0.7, 0.8, 0.9]
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def test_embed_without_api_key_env_var(mock_openai_client):
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config = BaseEmbedderConfig(api_key="test_key")
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embedder = OpenAIEmbedding(config)
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mock_response = Mock()
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mock_response.data = [Mock(embedding=[1.0, 1.1, 1.2])]
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mock_openai_client.embeddings.create.return_value = mock_response
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result = embedder.embed("Testing API key")
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mock_openai_client.embeddings.create.assert_called_once_with(
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input=["Testing API key"], model="text-embedding-3-small", dimensions=1536, encoding_format="float"
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)
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assert result == [1.0, 1.1, 1.2]
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def test_embed_uses_environment_api_key(mock_openai_client, monkeypatch):
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monkeypatch.setenv("OPENAI_API_KEY", "env_key")
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config = BaseEmbedderConfig()
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embedder = OpenAIEmbedding(config)
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mock_response = Mock()
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mock_response.data = [Mock(embedding=[1.3, 1.4, 1.5])]
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mock_openai_client.embeddings.create.return_value = mock_response
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result = embedder.embed("Environment key test")
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mock_openai_client.embeddings.create.assert_called_once_with(
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input=["Environment key test"], model="text-embedding-3-small", dimensions=1536, encoding_format="float"
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)
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assert result == [1.3, 1.4, 1.5]
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def test_embed_passes_encoding_format_float(mock_openai_client):
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"""Verify encoding_format='float' is always passed to prevent base64 issues with proxies.
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The OpenAI SDK defaults to encoding_format='base64' when not specified,
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which breaks OpenAI-compatible proxies (OpenRouter, LiteLLM, vLLM, etc.)
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that don't support base64 decoding. See #4057.
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"""
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config = BaseEmbedderConfig()
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embedder = OpenAIEmbedding(config)
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mock_response = Mock()
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mock_response.data = [Mock(embedding=[0.1, 0.2, 0.3])]
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mock_openai_client.embeddings.create.return_value = mock_response
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embedder.embed("Proxy compatibility test")
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call_kwargs = mock_openai_client.embeddings.create.call_args
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assert call_kwargs.kwargs.get("encoding_format") == "float" or call_kwargs[1].get("encoding_format") == "float"
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