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| import json |
| from typing import Any |
|
|
| from rag.nlp import find_codec |
| class RAGFlowJsonParser: |
| def __init__( |
| self, max_chunk_size: int = 2000, min_chunk_size: int | None = None |
| ): |
| super().__init__() |
| self.max_chunk_size = max_chunk_size * 2 |
| self.min_chunk_size = ( |
| min_chunk_size |
| if min_chunk_size is not None |
| else max(max_chunk_size - 200, 50) |
| ) |
|
|
| def __call__(self, binary): |
| encoding = find_codec(binary) |
| txt = binary.decode(encoding, errors="ignore") |
| json_data = json.loads(txt) |
| chunks = self.split_json(json_data, True) |
| sections = [json.dumps(line, ensure_ascii=False) for line in chunks if line] |
| return sections |
|
|
| @staticmethod |
| def _json_size(data: dict) -> int: |
| """Calculate the size of the serialized JSON object.""" |
| return len(json.dumps(data, ensure_ascii=False)) |
|
|
| @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): |
| |
| return {k: self._list_to_dict_preprocessing(v) for k, v in data.items()} |
| elif isinstance(data, list): |
| |
| return { |
| str(i): self._list_to_dict_preprocessing(item) |
| for i, item in enumerate(data) |
| } |
| else: |
| |
| return data |
| |
| def _json_split( |
| self, |
| data, |
| current_path: list[str] | None, |
| chunks: 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: |
| |
| self._set_nested_dict(chunks[-1], new_path, value) |
| else: |
| if chunk_size >= self.min_chunk_size: |
| |
| chunks.append({}) |
|
|
| |
| self._json_split(value, new_path, chunks) |
| else: |
| |
| self._set_nested_dict(chunks[-1], current_path, data) |
| return chunks |
|
|
| def split_json( |
| self, |
| json_data, |
| convert_lists: bool = False, |
| ) -> list[dict]: |
| """Splits JSON into a list of JSON chunks""" |
|
|
| if convert_lists: |
| preprocessed_data = self._list_to_dict_preprocessing(json_data) |
| chunks = self._json_split(preprocessed_data, None, None) |
| else: |
| chunks = self._json_split(json_data, None, None) |
|
|
| |
| if not chunks[-1]: |
| chunks.pop() |
| return chunks |
|
|
| 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) |
|
|
| |
| return [json.dumps(chunk, ensure_ascii=ensure_ascii) for chunk in chunks] |
|
|