Split JSON data - text splitter 集成

使用 LangChain Python 集成 the Split JSON data text splitter。

This json splitter splits json data while allowing control over chunk sizes. It traverses json data depth first and builds smaller json chunks. It attempts to keep nested json objects whole but will split them if needed to keep chunks between a min_chunk_size and the max_chunk_size.

If the value is not a nested json, but rather a very large string the string will not be split. If you need a hard cap on the chunk size consider composing this with a Recursive Text splitter on those chunks. There is an optional pre-processing step to split lists, by first converting them to json (dict) and then splitting them as such.

1. 如何分割文本：按 JSON 值。
2. 如何衡量分块大小：按字符数。

pip install -qU langchain-text-splitters

First we load some json data:

import json

import requests

# This is a large nested json object and will be loaded as a python dict
json_data = requests.get("https://api.smith.langchain.com/openapi.json").json()

Basic usage

Specify max_chunk_size to constrain chunk sizes:

from langchain_text_splitters import RecursiveJsonSplitter

splitter = RecursiveJsonSplitter(max_chunk_size=300)

To obtain json chunks, use the .split_json method:

# Recursively split json data - If you need to access/manipulate the smaller json chunks
json_chunks = splitter.split_json(json_data=json_data)

for chunk in json_chunks[:3]:
    print(chunk)

{'openapi': '3.1.0', 'info': {'title': 'LangSmith', 'version': '0.1.0'}, 'servers': [{'url': 'https://api.smith.langchain.com', 'description': 'LangSmith API endpoint.'}]}
{'paths': {'/api/v1/sessions/{session_id}': {'get': {'tags': ['tracer-sessions'], 'summary': 'Read Tracer Session', 'description': 'Get a specific session.', 'operationId': 'read_tracer_session_api_v1_sessions__session_id__get'}}}}
{'paths': {'/api/v1/sessions/{session_id}': {'get': {'security': [{'API Key': []}, {'Tenant ID': []}, {'Bearer Auth': []}]}}}}

To obtain LangChain Document objects, use the .create_documents method:

# The splitter can also output documents
docs = splitter.create_documents(texts=[json_data])

for doc in docs[:3]:
    print(doc)

page_content='{"openapi": "3.1.0", "info": {"title": "LangSmith", "version": "0.1.0"}, "servers": [{"url": "https://api.smith.langchain.com", "description": "LangSmith API endpoint."}]}'
page_content='{"paths": {"/api/v1/sessions/{session_id}": {"get": {"tags": ["tracer-sessions"], "summary": "Read Tracer Session", "description": "Get a specific session.", "operationId": "read_tracer_session_api_v1_sessions__session_id__get"}}}}'
page_content='{"paths": {"/api/v1/sessions/{session_id}": {"get": {"security": [{"API Key": []}, {"Tenant ID": []}, {"Bearer Auth": []}]}}}}'

Or use .split_text to obtain string content directly:

texts = splitter.split_text(json_data=json_data)

print(texts[0])
print(texts[1])

{"openapi": "3.1.0", "info": {"title": "LangSmith", "version": "0.1.0"}, "servers": [{"url": "https://api.smith.langchain.com", "description": "LangSmith API endpoint."}]}
{"paths": {"/api/v1/sessions/{session_id}": {"get": {"tags": ["tracer-sessions"], "summary": "Read Tracer Session", "description": "Get a specific session.", "operationId": "read_tracer_session_api_v1_sessions__session_id__get"}}}}

How to manage chunk sizes from list content

Note that one of the chunks in this example is larger than the specified max_chunk_size of 300. Reviewing one of these chunks that was bigger we see there is a list object there:

print([len(text) for text in texts][:10])
print()
print(texts[3])

[171, 231, 126, 469, 210, 213, 237, 271, 191, 232]

{"paths": {"/api/v1/sessions/{session_id}": {"get": {"parameters": [{"name": "session_id", "in": "path", "required": true, "schema": {"type": "string", "format": "uuid", "title": "Session Id"}}, {"name": "include_stats", "in": "query", "required": false, "schema": {"type": "boolean", "default": false, "title": "Include Stats"}}, {"name": "accept", "in": "header", "required": false, "schema": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Accept"}}]}}}}

The json splitter by default does not split lists.

Specify convert_lists=True to preprocess the json, converting list content to dicts with index:item as key:val pairs:

texts = splitter.split_text(json_data=json_data, convert_lists=True)

Let’s look at the size of the chunks. Now they are all under the max

print([len(text) for text in texts][:10])

[176, 236, 141, 203, 212, 221, 210, 213, 242, 291]

The list has been converted to a dict, but retains all the needed contextual information even if split into many chunks:

print(texts[1])

{"paths": {"/api/v1/sessions/{session_id}": {"get": {"tags": {"0": "tracer-sessions"}, "summary": "Read Tracer Session", "description": "Get a specific session.", "operationId": "read_tracer_session_api_v1_sessions__session_id__get"}}}}

# We can also look at the documents
docs[1]

Document(page_content='{"paths": {"/api/v1/sessions/{session_id}": {"get": {"tags": ["tracer-sessions"], "summary": "Read Tracer Session", "description": "Get a specific session.", "operationId": "read_tracer_session_api_v1_sessions__session_id__get"}}}}')

---

通过 MCP 将这些文档连接到 Claude、VSCode 等工具以获取实时答案。

在 GitHub 上编辑此页面 或 提交 issue。