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

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

embedchain/tests/embedder/test_embedder.py

@@ -0,0 +1,49 @@
+import pytest
+from chromadb.api.types import Documents, Embeddings
+
+from embedchain.config.embedder.base import BaseEmbedderConfig
+from embedchain.embedder.base import BaseEmbedder
+
+
+@pytest.fixture
+def base_embedder():
+    return BaseEmbedder()
+
+
+def test_initialization(base_embedder):
+    assert isinstance(base_embedder.config, BaseEmbedderConfig)
+    # not initialized
+    assert not hasattr(base_embedder, "embedding_fn")
+    assert not hasattr(base_embedder, "vector_dimension")
+
+
+def test_set_embedding_fn(base_embedder):
+    def embedding_function(texts: Documents) -> Embeddings:
+        return [f"Embedding for {text}" for text in texts]
+
+    base_embedder.set_embedding_fn(embedding_function)
+    assert hasattr(base_embedder, "embedding_fn")
+    assert callable(base_embedder.embedding_fn)
+    embeddings = base_embedder.embedding_fn(["text1", "text2"])
+    assert embeddings == ["Embedding for text1", "Embedding for text2"]
+
+
+def test_set_embedding_fn_when_not_a_function(base_embedder):
+    with pytest.raises(ValueError):
+        base_embedder.set_embedding_fn(None)
+
+
+def test_set_vector_dimension(base_embedder):
+    base_embedder.set_vector_dimension(256)
+    assert hasattr(base_embedder, "vector_dimension")
+    assert base_embedder.vector_dimension == 256
+
+
+def test_set_vector_dimension_type_error(base_embedder):
+    with pytest.raises(TypeError):
+        base_embedder.set_vector_dimension(None)
+
+
+def test_embedder_with_config():
+    embedder = BaseEmbedder(BaseEmbedderConfig())
+    assert isinstance(embedder.config, BaseEmbedderConfig)

embedchain/tests/embedder/test_huggingface_embedder.py

@@ -0,0 +1,18 @@
+
+from unittest.mock import patch
+from embedchain.config import BaseEmbedderConfig
+from embedchain.embedder.huggingface import HuggingFaceEmbedder
+
+
+def test_huggingface_embedder_with_model(monkeypatch):
+    config = BaseEmbedderConfig(model="test-model", model_kwargs={"param": "value"})
+    with patch('embedchain.embedder.huggingface.HuggingFaceEmbeddings') as mock_embeddings:
+        embedder = HuggingFaceEmbedder(config=config)
+        assert embedder.config.model == "test-model"
+        assert embedder.config.model_kwargs == {"param": "value"}
+        mock_embeddings.assert_called_once_with(
+            model_name="test-model",
+            model_kwargs={"param": "value"}
+        )
+
+