You can access the Text Cleaner For RAG 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 Integrations settings in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

1import { ApifyClient } from 'apify-client';
2
3// Initialize the ApifyClient with your Apify API token
4// Replace the '<YOUR_API_TOKEN>' with your token
5const client = new ApifyClient({
6    token: '<YOUR_API_TOKEN>',
7});
8
9// Prepare Actor input
10const input = {
11    "text": "Cookie settings\\nSubscribe to our newsletter\\n# Product Documentation\\nThis guide explains how to configure the API for production workloads.\\nThis guide explains how to configure the API for production workloads.\\nContact sales\\nUse retries, idempotency keys, and structured logs when integrating."
12};
13
14// Run the Actor and wait for it to finish
15const run = await client.actor("junipr/text-cleaner-for-rag").call(input);
16
17// Fetch and print Actor results from the run's dataset (if any)
18console.log('Results from dataset');
19console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
20const { items } = await client.dataset(run.defaultDatasetId).listItems();
21items.forEach((item) => {
22    console.dir(item);
23});
24
25// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

Text Cleaner For RAG — fast deterministic data utility API in JavaScript

The Apify API client for JavaScript is the official library that allows you to use Text Cleaner For RAG API in JavaScript or TypeScript, providing convenience functions and automatic retries on errors.

Install the apify-client

$npm install apify-client

Other API clients include:

Text Cleaner For RAG API in Python

Text Cleaner For RAG API through CLI

Text Cleaner For RAG OpenAPI definition

Text Cleaner For RAG API

RAG Post Processor - Text Cleaner & Chunker for LLM Pipelines

jalicia/rag-post-processor

Clean and chunk scraped text for RAG and LLM pipelines. Strips HTML, collapses whitespace, splits into overlapping chunks ready for embedding. Works standalone or chained after any scraper. Per-row billing.

Jordan Wagner

Web Search API for RAG — Search & Extract

tugelbay/rag-web-browser

Web search API for RAG and AI agents. Search Google or fetch public URLs and return clean Markdown, text, or HTML with sources. Guide: https://konabayev.com/tools/rag-web-browser/?utm_source=apify_info&utm_medium=referral&utm_campaign=rag-web-browser

Tugelbay Konabayev

AI Context Fetcher: Clean Text for RAG

sarvesh_bijawe/ai-context-fetcher-clean-text-for-rag

Instantly extracts clean, ad-free text from any URL. Designed for AI Agents, RAG pipelines, and LLM context windows.

Sarvesh Bijawe

RAG Web Extractor — Clean Markdown, HTML & Chunks

junipr/rag-web-extractor

Extract clean website content for RAG and AI search. Crawl pages, remove boilerplate, preserve structure, and export markdown, HTML, text, JSON, and chunks.

junipr

Website Content Crawler - Markdown & Text for LLM / RAG

pear_fight/website-content-crawler-markdown-text-for-llm-rag

Crawl any website and extract clean article text and Markdown, ready to feed into LLMs, ChatGPT, vector databases and RAG pipelines. Removes navigation, ads and boilerplate. Configurable crawl depth and page limits. Export to JSON, CSV, Excel.

Harald

AI / RAG Web Crawler

groupoject/ai-rag-web-crawler

Crawl any website and extract clean, LLM-ready Markdown chunks to feed AI agents, chatbots, and RAG pipelines. One row per embeddable chunk.

Group Oject

Reddit RAG Dataset — LLM Training Data from Posts & Comments

blackfalcondata/reddit-rag-dataset

Build clean LLM and RAG datasets from Reddit. Export posts with full comment threads as ready-to-chunk text, HTML and Markdown — only text-bearing records with parent/child thread structure. No login or developer token needed.

Black Falcon Data

Web Text Extractor

rl1987/web-text-extractor

R.L.

RAG Web Browser

scrapier/rag-web-browser

🌐 RAG Web Browser (rag-web-browser) is an intelligent tool for retrieving and generating answers from web sources with RAG. ⚡ Speed up research, get accurate citations, and streamline workflows for developers & analysts.

Scrapier

Webpage Text Extractor

maximedupre/webpage-text-extractor

Extract clean text, article text, and Markdown from public web pages. Get titles, metadata, headings, links, word counts, final URLs, and timestamps for LLM prompts, RAG inputs, reviews, and exports.