langchain/libs/text-splitters/langchain_text_splitters/json.py

121 lines
4.1 KiB
Python

from __future__ import annotations
import copy
import json
from typing import Any, Dict, List, Optional
from langchain_core.documents import Document
class RecursiveJsonSplitter:
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: List[str] = [],
chunks: List[Dict] = [{}],
) -> List[Dict]:
"""
Split json into maximum size dictionaries while preserving structure.
"""
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
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
def split_text(
self, json_data: Dict[str, Any], convert_lists: bool = False
) -> 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) for chunk in chunks]
def create_documents(
self,
texts: List[Dict],
convert_lists: bool = False,
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):
metadata = copy.deepcopy(_metadatas[i])
new_doc = Document(page_content=chunk, metadata=metadata)
documents.append(new_doc)
return documents