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Introduce Plugins (#13836)
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@@ -45,7 +45,7 @@ class TextSplitter(BaseDocumentTransformer, ABC):
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self,
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chunk_size: int = 4000,
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chunk_overlap: int = 200,
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length_function: Callable[[str], int] = len,
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length_function: Callable[[list[str]], list[int]] = lambda x: [len(x) for x in x],
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keep_separator: bool = False,
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add_start_index: bool = False,
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) -> None:
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@@ -106,7 +106,7 @@ class TextSplitter(BaseDocumentTransformer, ABC):
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def _merge_splits(self, splits: Iterable[str], separator: str, lengths: list[int]) -> list[str]:
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# We now want to combine these smaller pieces into medium size
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# chunks to send to the LLM.
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separator_len = self._length_function(separator)
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separator_len = self._length_function([separator])[0]
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docs = []
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current_doc: list[str] = []
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@@ -129,7 +129,9 @@ class TextSplitter(BaseDocumentTransformer, ABC):
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while total > self._chunk_overlap or (
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total + _len + (separator_len if len(current_doc) > 0 else 0) > self._chunk_size and total > 0
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):
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total -= self._length_function(current_doc[0]) + (separator_len if len(current_doc) > 1 else 0)
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total -= self._length_function([current_doc[0]])[0] + (
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separator_len if len(current_doc) > 1 else 0
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)
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current_doc = current_doc[1:]
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current_doc.append(d)
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total += _len + (separator_len if len(current_doc) > 1 else 0)
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@@ -155,7 +157,7 @@ class TextSplitter(BaseDocumentTransformer, ABC):
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raise ValueError(
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"Could not import transformers python package. Please install it with `pip install transformers`."
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)
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return cls(length_function=_huggingface_tokenizer_length, **kwargs)
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return cls(length_function=lambda x: [_huggingface_tokenizer_length(text) for text in x], **kwargs)
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@classmethod
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def from_tiktoken_encoder(
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@@ -199,7 +201,7 @@ class TextSplitter(BaseDocumentTransformer, ABC):
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}
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kwargs = {**kwargs, **extra_kwargs}
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return cls(length_function=_tiktoken_encoder, **kwargs)
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return cls(length_function=lambda x: [_tiktoken_encoder(text) for text in x], **kwargs)
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def transform_documents(self, documents: Sequence[Document], **kwargs: Any) -> Sequence[Document]:
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"""Transform sequence of documents by splitting them."""
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@@ -224,8 +226,8 @@ class CharacterTextSplitter(TextSplitter):
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splits = _split_text_with_regex(text, self._separator, self._keep_separator)
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_separator = "" if self._keep_separator else self._separator
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_good_splits_lengths = [] # cache the lengths of the splits
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for split in splits:
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_good_splits_lengths.append(self._length_function(split))
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if splits:
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_good_splits_lengths.extend(self._length_function(splits))
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return self._merge_splits(splits, _separator, _good_splits_lengths)
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@@ -478,9 +480,8 @@ class RecursiveCharacterTextSplitter(TextSplitter):
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_good_splits = []
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_good_splits_lengths = [] # cache the lengths of the splits
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_separator = "" if self._keep_separator else separator
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for s in splits:
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s_len = self._length_function(s)
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s_lens = self._length_function(splits)
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for s, s_len in zip(splits, s_lens):
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if s_len < self._chunk_size:
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_good_splits.append(s)
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_good_splits_lengths.append(s_len)
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