索引

节点解析器接口。

NodeParser

Bases: TransformComponent, ABC

节点解析器的基本接口。

参数

名称	类型	描述	默认值
include_metadata	布尔值	分割时是否考虑元数据。	True
include_prev_next_rel	布尔值	包含上一/下一节点关系。	True
callback_manager	CallbackManager		<llama_index.core.callbacks.base.CallbackManager object at 0x7e52a892a930>
id_func	Annotated[Callable, FieldInfo, BeforeValidator, WithJsonSchema, WithJsonSchema, PlainSerializer] | None	生成节点 ID 的函数。	None

源代码位于 llama-index-core/llama_index/core/node_parser/interface.py

class NodeParser(TransformComponent, ABC):
    """Base interface for node parser."""

    model_config = ConfigDict(arbitrary_types_allowed=True)
    include_metadata: bool = Field(
        default=True, description="Whether or not to consider metadata when splitting."
    )
    include_prev_next_rel: bool = Field(
        default=True, description="Include prev/next node relationships."
    )
    callback_manager: CallbackManager = Field(
        default_factory=lambda: CallbackManager([]), exclude=True
    )
    id_func: Optional[IdFuncCallable] = Field(
        default=None,
        description="Function to generate node IDs.",
    )

    @abstractmethod
    def _parse_nodes(
        self,
        nodes: Sequence[BaseNode],
        show_progress: bool = False,
        **kwargs: Any,
    ) -> List[BaseNode]:
        ...

    async def _aparse_nodes(
        self,
        nodes: Sequence[BaseNode],
        show_progress: bool = False,
        **kwargs: Any,
    ) -> List[BaseNode]:
        return self._parse_nodes(nodes, show_progress=show_progress, **kwargs)

    def _postprocess_parsed_nodes(
        self, nodes: List[BaseNode], parent_doc_map: Dict[str, Document]
    ) -> List[BaseNode]:
        for i, node in enumerate(nodes):
            parent_doc = parent_doc_map.get(node.ref_doc_id or "", None)
            parent_node = node.source_node

            if parent_doc is not None:
                if parent_doc.source_node is not None:
                    node.relationships.update(
                        {
                            NodeRelationship.SOURCE: parent_doc.source_node,
                        }
                    )
                start_char_idx = parent_doc.text.find(
                    node.get_content(metadata_mode=MetadataMode.NONE)
                )

                # update start/end char idx
                if start_char_idx >= 0 and isinstance(node, TextNode):
                    node.start_char_idx = start_char_idx
                    node.end_char_idx = start_char_idx + len(
                        node.get_content(metadata_mode=MetadataMode.NONE)
                    )

                # update metadata
                if self.include_metadata:
                    # Merge parent_doc.metadata into nodes.metadata, giving preference to node's values
                    node.metadata = {**parent_doc.metadata, **node.metadata}

            if parent_node is not None:
                if self.include_metadata:
                    parent_metadata = parent_node.metadata

                    combined_metadata = {**parent_metadata, **node.metadata}

                    # Merge parent_node.metadata into nodes.metadata, giving preference to node's values
                    node.metadata.update(combined_metadata)

            if self.include_prev_next_rel:
                # establish prev/next relationships if nodes share the same source_node
                if (
                    i > 0
                    and node.source_node
                    and nodes[i - 1].source_node
                    and nodes[i - 1].source_node.node_id == node.source_node.node_id  # type: ignore
                ):
                    node.relationships[NodeRelationship.PREVIOUS] = nodes[
                        i - 1
                    ].as_related_node_info()
                if (
                    i < len(nodes) - 1
                    and node.source_node
                    and nodes[i + 1].source_node
                    and nodes[i + 1].source_node.node_id == node.source_node.node_id  # type: ignore
                ):
                    node.relationships[NodeRelationship.NEXT] = nodes[
                        i + 1
                    ].as_related_node_info()

        return nodes

    def get_nodes_from_documents(
        self,
        documents: Sequence[Document],
        show_progress: bool = False,
        **kwargs: Any,
    ) -> List[BaseNode]:
        """
        Parse documents into nodes.

        Args:
            documents (Sequence[Document]): documents to parse
            show_progress (bool): whether to show progress bar

        """
        doc_id_to_document = {doc.id_: doc for doc in documents}

        with self.callback_manager.event(
            CBEventType.NODE_PARSING, payload={EventPayload.DOCUMENTS: documents}
        ) as event:
            nodes = self._parse_nodes(documents, show_progress=show_progress, **kwargs)
            nodes = self._postprocess_parsed_nodes(nodes, doc_id_to_document)

            event.on_end({EventPayload.NODES: nodes})

        return nodes

    async def aget_nodes_from_documents(
        self,
        documents: Sequence[Document],
        show_progress: bool = False,
        **kwargs: Any,
    ) -> List[BaseNode]:
        doc_id_to_document = {doc.id_: doc for doc in documents}

        with self.callback_manager.event(
            CBEventType.NODE_PARSING, payload={EventPayload.DOCUMENTS: documents}
        ) as event:
            nodes = await self._aparse_nodes(
                documents, show_progress=show_progress, **kwargs
            )
            nodes = self._postprocess_parsed_nodes(nodes, doc_id_to_document)

            event.on_end({EventPayload.NODES: nodes})

        return nodes

    def __call__(self, nodes: Sequence[BaseNode], **kwargs: Any) -> List[BaseNode]:
        return self.get_nodes_from_documents(nodes, **kwargs)  # type: ignore

    async def acall(self, nodes: Sequence[BaseNode], **kwargs: Any) -> List[BaseNode]:
        return await self.aget_nodes_from_documents(nodes, **kwargs)  # type: ignore

get_nodes_from_documents

get_nodes_from_documents(documents: Sequence[Document], show_progress: bool = False, **kwargs: Any) -> List[BaseNode]

将文档解析为节点。

参数

名称	类型	描述	默认值
documents	Sequence[Document]	要解析的文档	必需
show_progress	布尔值	是否显示进度条	False

源代码位于 llama-index-core/llama_index/core/node_parser/interface.py

def get_nodes_from_documents(
    self,
    documents: Sequence[Document],
    show_progress: bool = False,
    **kwargs: Any,
) -> List[BaseNode]:
    """
    Parse documents into nodes.

    Args:
        documents (Sequence[Document]): documents to parse
        show_progress (bool): whether to show progress bar

    """
    doc_id_to_document = {doc.id_: doc for doc in documents}

    with self.callback_manager.event(
        CBEventType.NODE_PARSING, payload={EventPayload.DOCUMENTS: documents}
    ) as event:
        nodes = self._parse_nodes(documents, show_progress=show_progress, **kwargs)
        nodes = self._postprocess_parsed_nodes(nodes, doc_id_to_document)

        event.on_end({EventPayload.NODES: nodes})

    return nodes

TextSplitter

Bases: NodeParser

源代码位于 llama-index-core/llama_index/core/node_parser/interface.py

class TextSplitter(NodeParser):
    @abstractmethod
    def split_text(self, text: str) -> List[str]:
        ...

    def split_texts(self, texts: List[str]) -> List[str]:
        nested_texts = [self.split_text(text) for text in texts]
        return [item for sublist in nested_texts for item in sublist]

    def _parse_nodes(
        self, nodes: Sequence[BaseNode], show_progress: bool = False, **kwargs: Any
    ) -> List[BaseNode]:
        all_nodes: List[BaseNode] = []
        nodes_with_progress = get_tqdm_iterable(nodes, show_progress, "Parsing nodes")
        for node in nodes_with_progress:
            splits = self.split_text(node.get_content())

            all_nodes.extend(
                build_nodes_from_splits(splits, node, id_func=self.id_func)
            )

        return all_nodes

MetadataAwareTextSplitter

Bases: TextSplitter

源代码位于 llama-index-core/llama_index/core/node_parser/interface.py

class MetadataAwareTextSplitter(TextSplitter):
    @abstractmethod
    def split_text_metadata_aware(self, text: str, metadata_str: str) -> List[str]:
        ...

    def split_texts_metadata_aware(
        self, texts: List[str], metadata_strs: List[str]
    ) -> List[str]:
        if len(texts) != len(metadata_strs):
            raise ValueError("Texts and metadata_strs must have the same length")
        nested_texts = [
            self.split_text_metadata_aware(text, metadata)
            for text, metadata in zip(texts, metadata_strs)
        ]
        return [item for sublist in nested_texts for item in sublist]

    def _get_metadata_str(self, node: BaseNode) -> str:
        """Helper function to get the proper metadata str for splitting."""
        embed_metadata_str = node.get_metadata_str(mode=MetadataMode.EMBED)
        llm_metadata_str = node.get_metadata_str(mode=MetadataMode.LLM)

        # use the longest metadata str for splitting
        if len(embed_metadata_str) > len(llm_metadata_str):
            metadata_str = embed_metadata_str
        else:
            metadata_str = llm_metadata_str

        return metadata_str

    def _parse_nodes(
        self, nodes: Sequence[BaseNode], show_progress: bool = False, **kwargs: Any
    ) -> List[BaseNode]:
        all_nodes: List[BaseNode] = []
        nodes_with_progress = get_tqdm_iterable(nodes, show_progress, "Parsing nodes")

        for node in nodes_with_progress:
            metadata_str = self._get_metadata_str(node)
            splits = self.split_text_metadata_aware(
                node.get_content(metadata_mode=MetadataMode.NONE),
                metadata_str=metadata_str,
            )
            all_nodes.extend(
                build_nodes_from_splits(splits, node, id_func=self.id_func)
            )

        return all_nodes