text-splitters[minor], langchain[minor], community[patch], templates, docs: langchain-text-splitters 0.0.1 (#18346)

libs/text-splitters/langchain_text_splitters/spacy.py

@@ -0,0 +1,55 @@
+from __future__ import annotations
+
+from typing import Any, List
+
+from langchain_text_splitters.base import TextSplitter
+
+
+class SpacyTextSplitter(TextSplitter):
+    """Splitting text using Spacy package.
+
+
+    Per default, Spacy's `en_core_web_sm` model is used and
+    its default max_length is 1000000 (it is the length of maximum character
+    this model takes which can be increased for large files). For a faster, but
+    potentially less accurate splitting, you can use `pipeline='sentencizer'`.
+    """
+
+    def __init__(
+        self,
+        separator: str = "\n\n",
+        pipeline: str = "en_core_web_sm",
+        max_length: int = 1_000_000,
+        **kwargs: Any,
+    ) -> None:
+        """Initialize the spacy text splitter."""
+        super().__init__(**kwargs)
+        self._tokenizer = _make_spacy_pipeline_for_splitting(
+            pipeline, max_length=max_length
+        )
+        self._separator = separator
+
+    def split_text(self, text: str) -> List[str]:
+        """Split incoming text and return chunks."""
+        splits = (s.text for s in self._tokenizer(text).sents)
+        return self._merge_splits(splits, self._separator)
+
+
+def _make_spacy_pipeline_for_splitting(
+    pipeline: str, *, max_length: int = 1_000_000
+) -> Any:  # avoid importing spacy
+    try:
+        import spacy
+    except ImportError:
+        raise ImportError(
+            "Spacy is not installed, please install it with `pip install spacy`."
+        )
+    if pipeline == "sentencizer":
+        from spacy.lang.en import English
+
+        sentencizer: Any = English()
+        sentencizer.add_pipe("sentencizer")
+    else:
+        sentencizer = spacy.load(pipeline, exclude=["ner", "tagger"])
+        sentencizer.max_length = max_length
+    return sentencizer