Rename embedchain to mem0 and open sourcing code for long term memory (#1474)

Co-authored-by: Deshraj Yadav <deshrajdry@gmail.com>

embedchain/tests/evaluation/test_context_relevancy_metric.py

@@ -0,0 +1,100 @@
+import pytest
+
+from embedchain.config.evaluation.base import ContextRelevanceConfig
+from embedchain.evaluation.metrics import ContextRelevance
+from embedchain.utils.evaluation import EvalData, EvalMetric
+
+
+@pytest.fixture
+def mock_data():
+    return [
+        EvalData(
+            contexts=[
+                "This is a test context 1.",
+            ],
+            question="This is a test question 1.",
+            answer="This is a test answer 1.",
+        ),
+        EvalData(
+            contexts=[
+                "This is a test context 2-1.",
+                "This is a test context 2-2.",
+            ],
+            question="This is a test question 2.",
+            answer="This is a test answer 2.",
+        ),
+    ]
+
+
+@pytest.fixture
+def mock_context_relevance_metric(monkeypatch):
+    monkeypatch.setenv("OPENAI_API_KEY", "test_api_key")
+    metric = ContextRelevance()
+    return metric
+
+
+def test_context_relevance_init(monkeypatch):
+    monkeypatch.setenv("OPENAI_API_KEY", "test_api_key")
+    metric = ContextRelevance()
+    assert metric.name == EvalMetric.CONTEXT_RELEVANCY.value
+    assert metric.config.model == "gpt-4"
+    assert metric.config.api_key is None
+    assert metric.config.language == "en"
+    monkeypatch.delenv("OPENAI_API_KEY")
+
+
+def test_context_relevance_init_with_config():
+    metric = ContextRelevance(config=ContextRelevanceConfig(api_key="test_api_key"))
+    assert metric.name == EvalMetric.CONTEXT_RELEVANCY.value
+    assert metric.config.model == "gpt-4"
+    assert metric.config.api_key == "test_api_key"
+    assert metric.config.language == "en"
+
+
+def test_context_relevance_init_without_api_key(monkeypatch):
+    monkeypatch.delenv("OPENAI_API_KEY", raising=False)
+    with pytest.raises(ValueError):
+        ContextRelevance()
+
+
+def test_sentence_segmenter(mock_context_relevance_metric):
+    text = "This is a test sentence. This is another sentence."
+    assert mock_context_relevance_metric._sentence_segmenter(text) == [
+        "This is a test sentence. ",
+        "This is another sentence.",
+    ]
+
+
+def test_compute_score(mock_context_relevance_metric, mock_data, monkeypatch):
+    monkeypatch.setattr(
+        mock_context_relevance_metric.client.chat.completions,
+        "create",
+        lambda model, messages: type(
+            "obj",
+            (object,),
+            {
+                "choices": [
+                    type("obj", (object,), {"message": type("obj", (object,), {"content": "This is a test reponse."})})
+                ]
+            },
+        )(),
+    )
+    assert mock_context_relevance_metric._compute_score(mock_data[0]) == 1.0
+    assert mock_context_relevance_metric._compute_score(mock_data[1]) == 0.5
+
+
+def test_evaluate(mock_context_relevance_metric, mock_data, monkeypatch):
+    monkeypatch.setattr(
+        mock_context_relevance_metric.client.chat.completions,
+        "create",
+        lambda model, messages: type(
+            "obj",
+            (object,),
+            {
+                "choices": [
+                    type("obj", (object,), {"message": type("obj", (object,), {"content": "This is a test reponse."})})
+                ]
+            },
+        )(),
+    )
+    assert mock_context_relevance_metric.evaluate(mock_data) == 0.75