Pricing

from $0.0001 / chunk created

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Text Splitter & Chunker for RAG / LLM Embeddings

Try for free

Split long text into clean overlapping chunks for RAG, vector embeddings and LLM pipelines. Recursive boundary-aware or fixed-size splitting, by characters, words or approx tokens, with adjustable overlap. Each chunk includes char/word/token counts and offset. Output JSON, CSV or Excel.

Pricing

from $0.0001 / chunk created

Rating

0.0

(0)

Developer

hiper soft

Actor stats

Bookmarked

Total users

Monthly active users

8 days ago

Last modified

Categories

You can access the Text Splitter & Chunker for RAG / LLM Embeddings programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in API & Integrations in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

1from apify_client import ApifyClient
2
3# Initialize the ApifyClient with your Apify API token
4# Replace '<YOUR_API_TOKEN>' with your token.
5client = ApifyClient("<YOUR_API_TOKEN>")
6
7# Prepare the Actor input
8run_input = {
9    "text": "Apify is a cloud platform for web scraping and browser automation. Developers build Actors that extract structured data from websites, monitor prices, and feed machine learning pipelines. In 2024 the company expanded its Store with thousands of ready-made tools used by businesses in Europe, North America and Asia.Apify is a cloud platform for web scraping and browser automation. Developers build Actors that extract structured data from websites, monitor prices, and feed machine learning pipelines. In 2024 the company expanded its Store with thousands of ready-made tools used by businesses in Europe, North America and Asia.Apify is a cloud platform for web scraping and browser automation. Developers build Actors that extract structured data from websites, monitor prices, and feed machine learning pipelines. In 2024 the company expanded its Store with thousands of ready-made tools used by businesses in Europe, North America and Asia.",
10    "texts": [],
11}
12
13# Run the Actor and wait for it to finish
14run = client.actor("hipersoft/text-splitter-chunker").call(run_input=run_input)
15
16# Fetch and print Actor results from the run's dataset (if there are any)
17print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
18for item in client.dataset(run.default_dataset_id).iterate_items():
19    print(item)
20
21# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

Text Splitter & Chunker for RAG / LLM Embeddings API in Python

The Apify API client for Python is the official library that allows you to use Text Splitter & Chunker for RAG / LLM Embeddings API in Python, providing convenience functions and automatic retries on errors.

Install the apify-client

$pip install apify-client

Other API clients include:

Text Splitter & Chunker for RAG / LLM Embeddings API in JavaScript

Text Splitter & Chunker for RAG / LLM Embeddings API through CLI

Text Splitter & Chunker for RAG / LLM Embeddings OpenAPI definition

Text Splitter & Chunker for RAG / LLM Embeddings API

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