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- 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")
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