Source code for langchain_text_splitters.json

from __future__ import annotations

import copy
import json
from typing import Any, Dict, List, Optional

from langchain_core.documents import Document


[docs]class RecursiveJsonSplitter:
[docs] def __init__( self, max_chunk_size: int = 2000, min_chunk_size: Optional[int] = None ): super().__init__() self.max_chunk_size = max_chunk_size self.min_chunk_size = ( min_chunk_size if min_chunk_size is not None else max(max_chunk_size - 200, 50) )
@staticmethod def _json_size(data: Dict) -> int: """Calculate the size of the serialized JSON object.""" return len(json.dumps(data)) @staticmethod def _set_nested_dict(d: Dict, path: List[str], value: Any) -> None: """Set a value in a nested dictionary based on the given path.""" for key in path[:-1]: d = d.setdefault(key, {}) d[path[-1]] = value def _list_to_dict_preprocessing(self, data: Any) -> Any: if isinstance(data, dict): # Process each key-value pair in the dictionary return {k: self._list_to_dict_preprocessing(v) for k, v in data.items()} elif isinstance(data, list): # Convert the list to a dictionary with index-based keys return { str(i): self._list_to_dict_preprocessing(item) for i, item in enumerate(data) } else: # Base case: the item is neither a dict nor a list, so return it unchanged return data def _json_split( self, data: Dict[str, Any], current_path: Optional[List[str]] = None, chunks: Optional[List[Dict]] = None, ) -> List[Dict]: """ Split json into maximum size dictionaries while preserving structure. """ current_path = current_path or [] chunks = chunks or [{}] if isinstance(data, dict): for key, value in data.items(): new_path = current_path + [key] chunk_size = self._json_size(chunks[-1]) size = self._json_size({key: value}) remaining = self.max_chunk_size - chunk_size if size < remaining: # Add item to current chunk self._set_nested_dict(chunks[-1], new_path, value) else: if chunk_size >= self.min_chunk_size: # Chunk is big enough, start a new chunk chunks.append({}) # Iterate self._json_split(value, new_path, chunks) else: # handle single item self._set_nested_dict(chunks[-1], current_path, data) return chunks
[docs] def split_json( self, json_data: Dict[str, Any], convert_lists: bool = False, ) -> List[Dict]: """Splits JSON into a list of JSON chunks""" if convert_lists: chunks = self._json_split(self._list_to_dict_preprocessing(json_data)) else: chunks = self._json_split(json_data) # Remove the last chunk if it's empty if not chunks[-1]: chunks.pop() return chunks
[docs] def split_text( self, json_data: Dict[str, Any], convert_lists: bool = False, ensure_ascii: bool = True, ) -> List[str]: """Splits JSON into a list of JSON formatted strings""" chunks = self.split_json(json_data=json_data, convert_lists=convert_lists) # Convert to string return [json.dumps(chunk, ensure_ascii=ensure_ascii) for chunk in chunks]
[docs] def create_documents( self, texts: List[Dict], convert_lists: bool = False, ensure_ascii: bool = True, metadatas: Optional[List[dict]] = None, ) -> List[Document]: """Create documents from a list of json objects (Dict).""" _metadatas = metadatas or [{}] * len(texts) documents = [] for i, text in enumerate(texts): for chunk in self.split_text( json_data=text, convert_lists=convert_lists, ensure_ascii=ensure_ascii ): metadata = copy.deepcopy(_metadatas[i]) new_doc = Document(page_content=chunk, metadata=metadata) documents.append(new_doc) return documents