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refactor!: rename TextDocumentSplitter to DocumentSplitter (#6223)

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* rename TextDocumentSplitter to DocumentSplitter

* reno

* fix init
This commit is contained in:
Stefano Fiorucci 2023-11-03 11:33:20 +01:00 committed by GitHub
parent 6e2dbdc320
commit 063d27c522
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8 changed files with 36 additions and 30 deletions
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4
e2e/preview/pipelines/test_preprocessing_pipeline.py
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@ -3,7 +3,7 @@ import json
from haystack.preview import Pipeline
from haystack.preview.components.embedders import SentenceTransformersDocumentEmbedder
from haystack.preview.components.file_converters import TextFileToDocument
from haystack.preview.components.preprocessors import TextDocumentSplitter, DocumentCleaner, DocumentLanguageClassifier
from haystack.preview.components.preprocessors import DocumentSplitter, DocumentCleaner, DocumentLanguageClassifier
from haystack.preview.components.routers import FileTypeRouter
from haystack.preview.components.writers import DocumentWriter
from haystack.preview.document_stores import InMemoryDocumentStore
@ -18,7 +18,7 @@ def test_preprocessing_pipeline(tmp_path):
preprocessing_pipeline.add_component(instance=DocumentLanguageClassifier(), name="language_classifier")
preprocessing_pipeline.add_component(instance=DocumentCleaner(), name="cleaner")
preprocessing_pipeline.add_component(
instance=TextDocumentSplitter(split_by="sentence", split_length=1), name="splitter"
instance=DocumentSplitter(split_by="sentence", split_length=1), name="splitter"
)
preprocessing_pipeline.add_component(
instance=SentenceTransformersDocumentEmbedder(model_name_or_path="sentence-transformers/all-MiniLM-L6-v2"),

6
haystack/preview/components/preprocessors/__init__.py
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@ -1,6 +1,6 @@
from haystack.preview.components.preprocessors.text_document_cleaner import DocumentCleaner
from haystack.preview.components.preprocessors.text_document_splitter import TextDocumentSplitter
from haystack.preview.components.preprocessors.document_cleaner import DocumentCleaner
from haystack.preview.components.preprocessors.document_splitter import DocumentSplitter
from haystack.preview.components.preprocessors.document_language_classifier import DocumentLanguageClassifier
from haystack.preview.components.preprocessors.text_language_classifier import TextLanguageClassifier
__all__ = ["TextDocumentSplitter", "DocumentCleaner", "TextLanguageClassifier", "DocumentLanguageClassifier"]
__all__ = ["DocumentSplitter", "DocumentCleaner", "TextLanguageClassifier", "DocumentLanguageClassifier"]

0
haystack/preview/components/preprocessors/text_document_cleaner.py → haystack/preview/components/preprocessors/document_cleaner.py
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8
haystack/preview/components/preprocessors/text_document_splitter.py → haystack/preview/components/preprocessors/document_splitter.py
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@ -7,7 +7,7 @@ from haystack.preview import component, Document
@component
class TextDocumentSplitter:
class DocumentSplitter:
"""
Splits a list of text documents into a list of text documents with shorter texts.
This is useful for splitting documents with long texts that otherwise would not fit into the maximum text length of language models.
@ -45,13 +45,13 @@ class TextDocumentSplitter:
"""
if not isinstance(documents, list) or (documents and not isinstance(documents[0], Document)):
raise TypeError("TextDocumentSplitter expects a List of Documents as input.")
raise TypeError("DocumentSplitter expects a List of Documents as input.")
split_docs = []
for doc in documents:
if doc.content is None:
raise ValueError(
f"TextDocumentSplitter only works with text documents but document.content for document ID {doc.id} is None."
f"DocumentSplitter only works with text documents but document.content for document ID {doc.id} is None."
)
units = self._split_into_units(doc.content, self.split_by)
text_splits = self._concatenate_units(units, self.split_length, self.split_overlap)
@ -69,7 +69,7 @@ class TextDocumentSplitter:
split_at = " "
else:
raise NotImplementedError(
"TextDocumentSplitter only supports 'passage', 'sentence' or 'word' split_by options."
"DocumentSplitter only supports 'passage', 'sentence' or 'word' split_by options."
)
units = text.split(split_at)
# Add the delimiter back to all units except the last one

2
pyproject.toml
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@ -98,7 +98,7 @@ preview = [
"Jinja2",
"openai",
"pyyaml",
"more-itertools", # TextDocumentSplitter
"more-itertools", # DocumentSplitter
]
inference = [
"transformers[torch,sentencepiece]==4.34.1",

6
releasenotes/notes/rename-text-document-splitter-1e9fcd292c4591dd.yaml Normal file
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@ -0,0 +1,6 @@
---
preview:
- |
rename `TextDocumentSplitter` to `DocumentSplitter`, to allow a better
distinction between Components that operate on text and those that operate
on Documents.

6
test/preview/components/preprocessors/test_text_document_cleaner.py → test/preview/components/preprocessors/test_document_cleaner.py
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@ -10,9 +10,9 @@ class TestDocumentCleaner:
@pytest.mark.unit
def test_init(self):
cleaner = DocumentCleaner()
assert cleaner.remove_empty_lines == True
assert cleaner.remove_extra_whitespaces == True
assert cleaner.remove_repeated_substrings == False
assert cleaner.remove_empty_lines is True
assert cleaner.remove_extra_whitespaces is True
assert cleaner.remove_repeated_substrings is False
assert cleaner.remove_substrings is None
assert cleaner.remove_regex is None

34
test/preview/components/preprocessors/test_text_document_splitter.py → test/preview/components/preprocessors/test_document_splitter.py
View File

@ -1,48 +1,48 @@
import pytest
from haystack.preview import Document
from haystack.preview.components.preprocessors import TextDocumentSplitter
from haystack.preview.components.preprocessors import DocumentSplitter
class TestTextDocumentSplitter:
class TestDocumentSplitter:
@pytest.mark.unit
def test_non_text_document(self):
with pytest.raises(
ValueError, match="TextDocumentSplitter only works with text documents but document.content for document ID"
ValueError, match="DocumentSplitter only works with text documents but document.content for document ID"
):
splitter = TextDocumentSplitter()
splitter = DocumentSplitter()
splitter.run(documents=[Document()])
@pytest.mark.unit
def test_single_doc(self):
with pytest.raises(TypeError, match="TextDocumentSplitter expects a List of Documents as input."):
splitter = TextDocumentSplitter()
with pytest.raises(TypeError, match="DocumentSplitter expects a List of Documents as input."):
splitter = DocumentSplitter()
splitter.run(documents=Document())
@pytest.mark.unit
def test_empty_list(self):
splitter = TextDocumentSplitter()
splitter = DocumentSplitter()
res = splitter.run(documents=[])
assert res == {"documents": []}
@pytest.mark.unit
def test_unsupported_split_by(self):
with pytest.raises(ValueError, match="split_by must be one of 'word', 'sentence' or 'passage'."):
TextDocumentSplitter(split_by="unsupported")
DocumentSplitter(split_by="unsupported")
@pytest.mark.unit
def test_unsupported_split_length(self):
with pytest.raises(ValueError, match="split_length must be greater than 0."):
TextDocumentSplitter(split_length=0)
DocumentSplitter(split_length=0)
@pytest.mark.unit
def test_unsupported_split_overlap(self):
with pytest.raises(ValueError, match="split_overlap must be greater than or equal to 0."):
TextDocumentSplitter(split_overlap=-1)
DocumentSplitter(split_overlap=-1)
@pytest.mark.unit
def test_split_by_word(self):
splitter = TextDocumentSplitter(split_by="word", split_length=10)
splitter = DocumentSplitter(split_by="word", split_length=10)
result = splitter.run(
documents=[
Document(
@ -56,7 +56,7 @@ class TestTextDocumentSplitter:
@pytest.mark.unit
def test_split_by_word_multiple_input_docs(self):
splitter = TextDocumentSplitter(split_by="word", split_length=10)
splitter = DocumentSplitter(split_by="word", split_length=10)
result = splitter.run(
documents=[
Document(
@ -76,7 +76,7 @@ class TestTextDocumentSplitter:
@pytest.mark.unit
def test_split_by_sentence(self):
splitter = TextDocumentSplitter(split_by="sentence", split_length=1)
splitter = DocumentSplitter(split_by="sentence", split_length=1)
result = splitter.run(
documents=[
Document(
@ -91,7 +91,7 @@ class TestTextDocumentSplitter:
@pytest.mark.unit
def test_split_by_passage(self):
splitter = TextDocumentSplitter(split_by="passage", split_length=1)
splitter = DocumentSplitter(split_by="passage", split_length=1)
result = splitter.run(
documents=[
Document(
@ -106,7 +106,7 @@ class TestTextDocumentSplitter:
@pytest.mark.unit
def test_split_by_word_with_overlap(self):
splitter = TextDocumentSplitter(split_by="word", split_length=10, split_overlap=2)
splitter = DocumentSplitter(split_by="word", split_length=10, split_overlap=2)
result = splitter.run(
documents=[
Document(
@ -120,7 +120,7 @@ class TestTextDocumentSplitter:
@pytest.mark.unit
def test_source_id_stored_in_metadata(self):
splitter = TextDocumentSplitter(split_by="word", split_length=10)
splitter = DocumentSplitter(split_by="word", split_length=10)
doc1 = Document(content="This is a text with some words.")
doc2 = Document(content="This is a different text with some words.")
result = splitter.run(documents=[doc1, doc2])
@ -129,7 +129,7 @@ class TestTextDocumentSplitter:
@pytest.mark.unit
def test_copy_metadata(self):
splitter = TextDocumentSplitter(split_by="word", split_length=10)
splitter = DocumentSplitter(split_by="word", split_length=10)
documents = [
Document(content="Text.", meta={"name": "doc 0"}),
Document(content="Text.", meta={"name": "doc 1"}),