SentenceWindowNodeParser

pydantic model llama_index.node_parser.SentenceWindowNodeParser

Sentence window node parser.

Splits a document into Nodes, with each node being a sentence. Each node contains a window from the surrounding sentences in the metadata.

Parameters

• sentence_splitter (Optional[Callable]) – splits text into sentences

• include_metadata (bool) – whether to include metadata in nodes

• include_prev_next_rel (bool) – whether to include prev/next relationships

Show JSON schema

{
   "title": "SentenceWindowNodeParser",
   "description": "Sentence window node parser.\n\nSplits a document into Nodes, with each node being a sentence.\nEach node contains a window from the surrounding sentences in the metadata.\n\nArgs:\n    sentence_splitter (Optional[Callable]): splits text into sentences\n    include_metadata (bool): whether to include metadata in nodes\n    include_prev_next_rel (bool): whether to include prev/next relationships",
   "type": "object",
   "properties": {
      "include_metadata": {
         "title": "Include Metadata",
         "description": "Whether or not to consider metadata when splitting.",
         "default": true,
         "type": "boolean"
      },
      "include_prev_next_rel": {
         "title": "Include Prev Next Rel",
         "description": "Include prev/next node relationships.",
         "default": true,
         "type": "boolean"
      },
      "callback_manager": {
         "title": "Callback Manager"
      },
      "id_func": {
         "title": "Id Func"
      },
      "window_size": {
         "title": "Window Size",
         "description": "The number of sentences on each side of a sentence to capture.",
         "default": 3,
         "exclusiveMinimum": 0,
         "type": "integer"
      },
      "window_metadata_key": {
         "title": "Window Metadata Key",
         "description": "The metadata key to store the sentence window under.",
         "default": "window",
         "type": "string"
      },
      "original_text_metadata_key": {
         "title": "Original Text Metadata Key",
         "description": "The metadata key to store the original sentence in.",
         "default": "original_text",
         "type": "string"
      },
      "class_name": {
         "title": "Class Name",
         "type": "string",
         "default": "SentenceWindowNodeParser"
      }
   }
}

Config

• arbitrary_types_allowed: bool = True

Fields

• original_text_metadata_key (str)

• sentence_splitter (Callable[[str], List[str]])

• window_metadata_key (str)

• window_size (int)

field original_text_metadata_key: str = 'original_text'

The metadata key to store the original sentence in.

field sentence_splitter: Callable[[str], List[str]] [Optional]

The text splitter to use when splitting documents.

field window_metadata_key: str = 'window'

The metadata key to store the sentence window under.

field window_size: int = 3

The number of sentences on each side of a sentence to capture.

Constraints

• exclusiveMinimum = 0

build_window_nodes_from_documents(documents: Sequence[Document]) → List[BaseNode]

Build window nodes from documents.

classmethod class_name() → str

Get the class name, used as a unique ID in serialization.

This provides a key that makes serialization robust against actual class name changes.

classmethod from_defaults(sentence_splitter: Optional[Callable[[str], List[str]]] = None, window_size: int = 3, window_metadata_key: str = 'window', original_text_metadata_key: str = 'original_text', include_metadata: bool = True, include_prev_next_rel: bool = True, callback_manager: Optional[CallbackManager] = None, id_func: Optional[Callable[[int, Document], str]] = None) → SentenceWindowNodeParser