From b6d26d3f9f7fba4bb96d6bed26cef8e7bc86f749 Mon Sep 17 00:00:00 2001 From: Amyh102 Date: Fri, 1 Dec 2023 15:42:31 -0500 Subject: [PATCH] infra[patch]: Add unit tests for Huggingface dataset loader (#14053) - **Description:** Add unit tests for huggingface dataset loader and sample huggingface dataset for future tests. Updates dependencies for `datasets` module. - Adds coverage for [previous pull request](https://github.com/langchain-ai/langchain/pull/13864) - **Tag maintainer:** @hwchase17 --------- Co-authored-by: Amy Han Co-authored-by: Amy Han Co-authored-by: Bagatur --- libs/langchain/poetry.lock | 179 +++++++++++++++++- libs/langchain/pyproject.toml | 2 + .../sample_hugging_face_dataset.py | 109 +++++++++++ .../document_loaders/test_hugging_face.py | 101 ++++++++++ 4 files changed, 389 insertions(+), 2 deletions(-) create mode 100644 libs/langchain/tests/unit_tests/document_loaders/sample_documents/sample_hugging_face_dataset.py create mode 100644 libs/langchain/tests/unit_tests/document_loaders/test_hugging_face.py diff --git a/libs/langchain/poetry.lock b/libs/langchain/poetry.lock index 22bb32298a5..fba4c548736 100644 --- a/libs/langchain/poetry.lock +++ b/libs/langchain/poetry.lock @@ -1855,6 +1855,49 @@ files = [ marshmallow = ">=3.18.0,<4.0.0" typing-inspect = ">=0.4.0,<1" +[[package]] 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b/libs/langchain/tests/unit_tests/document_loaders/sample_documents/sample_hugging_face_dataset.py @@ -0,0 +1,109 @@ +from typing import Any, Generator, List, Tuple + +import datasets + + +class SampleHuggingface(datasets.GeneratorBasedBuilder): + """Sample huggingface dataset with two different versions for testing.""" + + BUILDER_CONFIGS = [ + datasets.BuilderConfig( + name="v1", + version=datasets.Version("1.0.0"), + description="Sample v1 description", + ), + datasets.BuilderConfig( + name="v2", + version=datasets.Version("1.0.0"), + description="Sample v2 description", + ), + ] + + def _info(self) -> datasets.DatasetInfo: + """This function defines the structure of the dataset""" + return datasets.DatasetInfo( + description="Sample Huggingface dataset", + features=datasets.Features( + { + "split": datasets.Value("string"), + "text": datasets.Value("string"), + "list": datasets.features.Sequence(datasets.Value("string")), + "dict": datasets.features.Sequence( + { + "dict_text": datasets.Value("string"), + "dict_int": datasets.Value("int32"), + } + ), + } + ), + ) + + def _split_generators( + self, dl_manager: datasets.DownloadManager + ) -> List[datasets.SplitGenerator]: + """ + This function defines how the dataset's splits will be generated. + Args: + dl_manager (`DownloadManager`): + Helper for downloading datasets from files and online sources. + This is not being used for this test file. + """ + return [ + datasets.SplitGenerator( + name=datasets.Split.TRAIN, + gen_kwargs={"split": "train", "name": self.config.name}, + ), + datasets.SplitGenerator( + name=datasets.Split.TEST, + gen_kwargs={"split": "test", "name": self.config.name}, + ), + ] + + def _generate_examples( + self, split: str, name: str + ) -> Generator[Tuple[int, object], Any, None]: + """This function returns the examples. + Args: + split (`string`): + Split to process + name (`string`): + Name of dataset, as defined in the BuilderConfig + """ + if name == "v1": + yield ( + 1, + { + "split": split, + "text": "This is text in version 1", + "list": ["List item 1", "List item 2", "List item 3"], + "dict": [ + { + "dict_text": "Object text 1", + "dict_int": "1", + }, + { + "dict_text": "Object text 2", + "dict_int": str(000), + }, + ], + }, + ) + elif name == "v2": + yield ( + 2, + { + "split": split, + "text": "This is text in version 2", + "list": ["Hello", "Bonjour", "Hola"], + "dict": [ + { + "dict_text": "Hello world!", + "dict_int": "2", + }, + { + "dict_text": "langchain is cool", + "dict_int": str(123), + }, + ], + }, + ) diff --git a/libs/langchain/tests/unit_tests/document_loaders/test_hugging_face.py b/libs/langchain/tests/unit_tests/document_loaders/test_hugging_face.py new file mode 100644 index 00000000000..6c4fd6288ab --- /dev/null +++ b/libs/langchain/tests/unit_tests/document_loaders/test_hugging_face.py @@ -0,0 +1,101 @@ +from pathlib import Path + +import pytest + +from langchain.document_loaders import HuggingFaceDatasetLoader + +HUGGING_FACE_EXAMPLE_DATASET = str( + Path(__file__).parent / "sample_documents" / "sample_hugging_face_dataset.py" +) + + +@pytest.mark.requires("datasets") +@pytest.fixture +def test_load_string() -> None: + """Loads page_content of type string""" + page_content_column = "text" + name = "v1" + + loader = HuggingFaceDatasetLoader( + HUGGING_FACE_EXAMPLE_DATASET, page_content_column, name + ) + docs = loader.load() + + # Length should be number of splits for specified `name` + assert len(docs) == 2 + doc = docs[0] + assert doc.page_content == '"This is text in version 1"' + assert doc.metadata.keys() == { + "split", + "list", + "dict", + } + + +@pytest.mark.requires("datasets") +@pytest.fixture +def test_load_list() -> None: + """Loads page_content of type List""" + page_content_column = "list" + name = "v1" + + loader = HuggingFaceDatasetLoader( + HUGGING_FACE_EXAMPLE_DATASET, page_content_column, name + ) + doc = loader.load()[0] + assert doc.page_content == '["List item 1", "List item 2", "List item 3"]' + assert doc.metadata.keys() == { + "split", + "text", + "dict", + } + + +@pytest.mark.requires("datasets") +@pytest.fixture +def test_load_object() -> None: + """Loads page_content of type Object""" + page_content_column = "dict" + name = "v2" + + loader = HuggingFaceDatasetLoader( + HUGGING_FACE_EXAMPLE_DATASET, page_content_column, name + ) + doc = loader.load()[0] + assert ( + doc.page_content + == '{"dict_text": ["Hello world!", "langchain is cool"], "dict_int": [2, 123]}' + ) + assert doc.metadata.keys() == { + "split", + "text", + "list", + } + + +@pytest.mark.requires("datasets") +@pytest.fixture +def test_load_nonexistent_dataset() -> None: + """Tests that ValueError is thrown for nonexistent dataset name""" + page_content_column = "text" + name = "v3" + + loader = HuggingFaceDatasetLoader( + HUGGING_FACE_EXAMPLE_DATASET, page_content_column, name + ) + with pytest.raises(ValueError): + loader.load() + + +@pytest.mark.requires("datasets") +@pytest.fixture +def test_load_nonexistent_feature() -> None: + """Tests that KeyError is thrown for nonexistent feature/key in dataset""" + page_content_column = "langchain" + name = "v2" + + loader = HuggingFaceDatasetLoader( + HUGGING_FACE_EXAMPLE_DATASET, page_content_column, name + ) + with pytest.raises(KeyError): + loader.load()