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61 lines
2.0 KiB
Python
61 lines
2.0 KiB
Python
"""Test HuggingFace API wrapper."""
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import unittest
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from pathlib import Path
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import pytest
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from langchain.llms.huggingface_endpoint import HuggingFaceEndpoint
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from langchain.llms.loading import load_llm
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from tests.integration_tests.llms.utils import assert_llm_equality
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@unittest.skip(
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"This test requires an inference endpoint. Tested with Hugging Face endpoints"
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)
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def test_huggingface_endpoint_text_generation() -> None:
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"""Test valid call to HuggingFace text generation model."""
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llm = HuggingFaceEndpoint(
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endpoint_url="", task="text-generation", model_kwargs={"max_new_tokens": 10}
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)
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output = llm("Say foo:")
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print(output)
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assert isinstance(output, str)
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@unittest.skip(
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"This test requires an inference endpoint. Tested with Hugging Face endpoints"
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)
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def test_huggingface_endpoint_text2text_generation() -> None:
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"""Test valid call to HuggingFace text2text model."""
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llm = HuggingFaceEndpoint(endpoint_url="", task="text2text-generation")
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output = llm("The capital of New York is")
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assert output == "Albany"
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@unittest.skip(
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"This test requires an inference endpoint. Tested with Hugging Face endpoints"
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)
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def test_huggingface_endpoint_summarization() -> None:
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"""Test valid call to HuggingFace summarization model."""
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llm = HuggingFaceEndpoint(endpoint_url="", task="summarization")
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output = llm("Say foo:")
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assert isinstance(output, str)
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def test_huggingface_endpoint_call_error() -> None:
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"""Test valid call to HuggingFace that errors."""
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llm = HuggingFaceEndpoint(model_kwargs={"max_new_tokens": -1})
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with pytest.raises(ValueError):
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llm("Say foo:")
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def test_saving_loading_endpoint_llm(tmp_path: Path) -> None:
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"""Test saving/loading an HuggingFaceHub LLM."""
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llm = HuggingFaceEndpoint(
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endpoint_url="", task="text-generation", model_kwargs={"max_new_tokens": 10}
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)
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llm.save(file_path=tmp_path / "hf.yaml")
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loaded_llm = load_llm(tmp_path / "hf.yaml")
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assert_llm_equality(llm, loaded_llm)
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