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

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

embedchain/tests/llm/test_huggingface.py

@@ -0,0 +1,83 @@
+import importlib
+import os
+
+import pytest
+
+from embedchain.config import BaseLlmConfig
+from embedchain.llm.huggingface import HuggingFaceLlm
+
+
+@pytest.fixture
+def huggingface_llm_config():
+    os.environ["HUGGINGFACE_ACCESS_TOKEN"] = "test_access_token"
+    config = BaseLlmConfig(model="google/flan-t5-xxl", max_tokens=50, temperature=0.7, top_p=0.8)
+    yield config
+    os.environ.pop("HUGGINGFACE_ACCESS_TOKEN")
+
+
+@pytest.fixture
+def huggingface_endpoint_config():
+    os.environ["HUGGINGFACE_ACCESS_TOKEN"] = "test_access_token"
+    config = BaseLlmConfig(endpoint="https://api-inference.huggingface.co/models/gpt2", model_kwargs={"device": "cpu"})
+    yield config
+    os.environ.pop("HUGGINGFACE_ACCESS_TOKEN")
+
+
+def test_init_raises_value_error_without_api_key(mocker):
+    mocker.patch.dict(os.environ, clear=True)
+    with pytest.raises(ValueError):
+        HuggingFaceLlm()
+
+
+def test_get_llm_model_answer_raises_value_error_for_system_prompt(huggingface_llm_config):
+    llm = HuggingFaceLlm(huggingface_llm_config)
+    llm.config.system_prompt = "system_prompt"
+    with pytest.raises(ValueError):
+        llm.get_llm_model_answer("prompt")
+
+
+def test_top_p_value_within_range():
+    config = BaseLlmConfig(top_p=1.0)
+    with pytest.raises(ValueError):
+        HuggingFaceLlm._get_answer("test_prompt", config)
+
+
+def test_dependency_is_imported():
+    importlib_installed = True
+    try:
+        importlib.import_module("huggingface_hub")
+    except ImportError:
+        importlib_installed = False
+    assert importlib_installed
+
+
+def test_get_llm_model_answer(huggingface_llm_config, mocker):
+    mocker.patch("embedchain.llm.huggingface.HuggingFaceLlm._get_answer", return_value="Test answer")
+
+    llm = HuggingFaceLlm(huggingface_llm_config)
+    answer = llm.get_llm_model_answer("Test query")
+
+    assert answer == "Test answer"
+
+
+def test_hugging_face_mock(huggingface_llm_config, mocker):
+    mock_llm_instance = mocker.Mock(return_value="Test answer")
+    mock_hf_hub = mocker.patch("embedchain.llm.huggingface.HuggingFaceHub")
+    mock_hf_hub.return_value.invoke = mock_llm_instance
+
+    llm = HuggingFaceLlm(huggingface_llm_config)
+    answer = llm.get_llm_model_answer("Test query")
+    assert answer == "Test answer"
+    mock_llm_instance.assert_called_once_with("Test query")
+
+
+def test_custom_endpoint(huggingface_endpoint_config, mocker):
+    mock_llm_instance = mocker.Mock(return_value="Test answer")
+    mock_hf_endpoint = mocker.patch("embedchain.llm.huggingface.HuggingFaceEndpoint")
+    mock_hf_endpoint.return_value.invoke = mock_llm_instance
+
+    llm = HuggingFaceLlm(huggingface_endpoint_config)
+    answer = llm.get_llm_model_answer("Test query")
+
+    assert answer == "Test answer"
+    mock_llm_instance.assert_called_once_with("Test query")