Docs › Language and text

Text tools API

Chunk documents, redact Indian identifiers, count tokens, detect language.

Tools for working with text, especially in AI and retrieval pipelines. Send short text as ?text=, or POST it as text/plain, or as JSON {"text": ...} with the options beside it. Nothing you send is logged or kept. Each request counts as 10 against the rate limit.

Base URL https://api.dharun.devNo API key600 requests a minuteThis page as Markdown

Split a document into chunks

GET/v1/text/chunkPOST

Splits at headings, paragraphs, sentences and words, in that order of preference, so chunks stay readable. Markdown chunks never cross a heading and carry their heading path. Each chunk is an exact slice of the input with its character offsets.

Also takes POST: The document, plain text or Markdown. Send it as text/plain, or as JSON {"text": "..."} with the other options beside it, up to 256 KB.

What you send here is never written to the log, and the answer is not cached.

Parameter	Description
`text`query	The text (or POST it).
`size`query	Largest chunk in characters, overlap included, 100 to 20000. Default 1000.
`overlap`query	Characters repeated from the previous chunk, up to half the size. Default a tenth of the size.
`format`query	Default auto: Markdown if the text has headings or code fences. One of: auto, markdown, text.

curl

curl "https://api.dharun.dev/v1/text/chunk?size=200&overlap=20&text=%23+Setup%0A%0AInstall+Go.+Clone+the+repository.%0A%0A%23+Deploy%0A%0APush+to+main."

JavaScript

const response = await fetch("https://api.dharun.dev/v1/text/chunk?size=200&overlap=20&text=%23+Setup%0A%0AInstall+Go.+Clone+the+repository.%0A%0A%23+Deploy%0A%0APush+to+main.");
const body = await response.json();
if (!response.ok) throw new Error(body.error.message);
console.log(body.data);

Python

import requests

response = requests.get("https://api.dharun.dev/v1/text/chunk?size=200&overlap=20&text=%23+Setup%0A%0AInstall+Go.+Clone+the+repository.%0A%0A%23+Deploy%0A%0APush+to+main.", timeout=10)
body = response.json()
if not response.ok:
    raise RuntimeError(body["error"]["message"])
print(body["data"])

Response

{
  "data": {
    "format": "markdown",
    "size": 200,
    "chunks": [
      {
        "index": 0,
        "text": "# Setup\n\nInstall Go. Clone the repository.",
        "start": 0,
        "end": 42,
        "chars": 42,
        "heading": "Setup"
      },
      {
        "index": 1,
        "text": "# Deploy\n\nPush to main.",
        "start": 44,
        "end": 67,
        "chars": 23,
        "heading": "Deploy"
      }
    ]
  },
  "meta": {
    "total": 2,
    "note": "Sizes and offsets count characters (Unicode code points). Each chunk is exactly text[start:end]."
  }
}

Redact Indian personal identifiers

GET/v1/text/redactPOST

Masks Aadhaar numbers (Verhoeff-checked), PAN, GSTIN (checksum-checked), card numbers (Luhn-checked), Indian mobile numbers, email addresses, UPI IDs, vehicle numbers, voter IDs, passport numbers and IP addresses. Returns where each was found, never the values. Names and addresses are not detected.

Also takes POST: The text to redact. Send it as text/plain, or as JSON {"text": "..."} with the other options beside it, up to 256 KB.

What you send here is never written to the log, and the answer is not cached.

Parameter	Description
`text`query	The text (or POST it).
`types`query	Comma-separated kinds to redact; default all. Kinds: email, upi, gstin, card, aadhaar, pan, phone, vehicle, voter_id, passport, ip.
`style`query	label replaces with [PAN]; partial keeps the last digits, as on a bank statement. Default label. One of: label, partial.

curl

curl "https://api.dharun.dev/v1/text/redact?text=Call+98765+43210%2C+PAN+ABCPK1234F"

JavaScript

const response = await fetch("https://api.dharun.dev/v1/text/redact?text=Call+98765+43210%2C+PAN+ABCPK1234F");
const body = await response.json();
if (!response.ok) throw new Error(body.error.message);
console.log(body.data);

Python

import requests

response = requests.get("https://api.dharun.dev/v1/text/redact?text=Call+98765+43210%2C+PAN+ABCPK1234F", timeout=10)
body = response.json()
if not response.ok:
    raise RuntimeError(body["error"]["message"])
print(body["data"])

Response

{
  "data": {
    "text": "Call [PHONE], PAN [PAN]",
    "findings": [
      {
        "type": "phone",
        "start": 5,
        "end": 16
      },
      {
        "type": "pan",
        "start": 22,
        "end": 32
      }
    ],
    "counts": {
      "pan": 1,
      "phone": 1
    }
  },
  "meta": {
    "note": "Finds identifiers by their structure and check digits. Names and street addresses are not detected."
  }
}

Count tokens

GET/v1/text/tokensPOST

Exact token counts with OpenAI tokenizers, by encoding or model name. Other vendors do not publish their tokenizers, so their counts are not offered.

Also takes POST: The text to count. Send it as text/plain, or as JSON {"text": "..."} with the other options beside it, up to 256 KB.

What you send here is never written to the log, and the answer is not cached.

Parameter	Description
`text`query	The text (or POST it).
`model`query	Model name, such as gpt-4o or gpt-4, or an encoding: o200k_base, cl100k_base, p50k_base. Default o200k_base.

curl

curl "https://api.dharun.dev/v1/text/tokens?model=gpt-4o&text=%E0%AE%B5%E0%AE%A3%E0%AE%95%E0%AF%8D%E0%AE%95%E0%AE%AE%E0%AF%8D%2C+how+many+tokens+is+this%3F"

JavaScript

const response = await fetch("https://api.dharun.dev/v1/text/tokens?model=gpt-4o&text=%E0%AE%B5%E0%AE%A3%E0%AE%95%E0%AF%8D%E0%AE%95%E0%AE%AE%E0%AF%8D%2C+how+many+tokens+is+this%3F");
const body = await response.json();
if (!response.ok) throw new Error(body.error.message);
console.log(body.data);

Python

import requests

response = requests.get("https://api.dharun.dev/v1/text/tokens?model=gpt-4o&text=%E0%AE%B5%E0%AE%A3%E0%AE%95%E0%AF%8D%E0%AE%95%E0%AE%AE%E0%AF%8D%2C+how+many+tokens+is+this%3F", timeout=10)
body = response.json()
if not response.ok:
    raise RuntimeError(body["error"]["message"])
print(body["data"])

Response, with lists and long text shortened

{
  "data": {
    "tokens": 10,
    "encoding": "o200k_base",
    "models": [
      "gpt-4o",
      "gpt-4o-mini",
      "gpt-4.1"
    ],
    "characters": 33,
    "words": 6,
    "bytes": 47
  },
  "meta": {
    "note": "Counted with OpenAI's vocabulary for the encoding, treating special tokens as text. Chat requests add a few tokens per message on top."
  }
}

Detect the language

GET/v1/text/languagePOST

Language and script, with a confidence. Covers about 80 languages including Hindi, Bengali, Marathi, Gujarati, Punjabi, Tamil, Telugu, Kannada, Malayalam, Odia and Urdu. Romanised Indian text (Hinglish, Tanglish) is flagged as such.

Also takes POST: The text. Send it as text/plain, or as JSON {"text": "..."} with the other options beside it, up to 256 KB.

What you send here is never written to the log, and the answer is not cached.

Parameter	Description
`text`query	The text (or POST it).

curl

curl "https://api.dharun.dev/v1/text/language?text=%E0%AE%85%E0%AE%95%E0%AE%B0+%E0%AE%AE%E0%AF%81%E0%AE%A4%E0%AE%B2+%E0%AE%8E%E0%AE%B4%E0%AF%81%E0%AE%A4%E0%AF%8D%E0%AE%A4%E0%AF%86%E0%AE%B2%E0%AF%8D%E0%AE%B2%E0%AE%BE%E0%AE%AE%E0%AF%8D+%E0%AE%86%E0%AE%A4%E0%AE%BF+%E0%AE%AA%E0%AE%95%E0%AE%B5%E0%AE%A9%E0%AF%8D+%E0%AE%AE%E0%AF%81%E0%AE%A4%E0%AE%B1%E0%AF%8D%E0%AE%B1%E0%AF%87+%E0%AE%89%E0%AE%B2%E0%AE%95%E0%AF%81"

JavaScript

const response = await fetch("https://api.dharun.dev/v1/text/language?text=%E0%AE%85%E0%AE%95%E0%AE%B0+%E0%AE%AE%E0%AF%81%E0%AE%A4%E0%AE%B2+%E0%AE%8E%E0%AE%B4%E0%AF%81%E0%AE%A4%E0%AF%8D%E0%AE%A4%E0%AF%86%E0%AE%B2%E0%AF%8D%E0%AE%B2%E0%AE%BE%E0%AE%AE%E0%AF%8D+%E0%AE%86%E0%AE%A4%E0%AE%BF+%E0%AE%AA%E0%AE%95%E0%AE%B5%E0%AE%A9%E0%AF%8D+%E0%AE%AE%E0%AF%81%E0%AE%A4%E0%AE%B1%E0%AF%8D%E0%AE%B1%E0%AF%87+%E0%AE%89%E0%AE%B2%E0%AE%95%E0%AF%81");
const body = await response.json();
if (!response.ok) throw new Error(body.error.message);
console.log(body.data);

Python

import requests

response = requests.get("https://api.dharun.dev/v1/text/language?text=%E0%AE%85%E0%AE%95%E0%AE%B0+%E0%AE%AE%E0%AF%81%E0%AE%A4%E0%AE%B2+%E0%AE%8E%E0%AE%B4%E0%AF%81%E0%AE%A4%E0%AF%8D%E0%AE%A4%E0%AF%86%E0%AE%B2%E0%AF%8D%E0%AE%B2%E0%AE%BE%E0%AE%AE%E0%AF%8D+%E0%AE%86%E0%AE%A4%E0%AE%BF+%E0%AE%AA%E0%AE%95%E0%AE%B5%E0%AE%A9%E0%AF%8D+%E0%AE%AE%E0%AF%81%E0%AE%A4%E0%AE%B1%E0%AF%8D%E0%AE%B1%E0%AF%87+%E0%AE%89%E0%AE%B2%E0%AE%95%E0%AF%81", timeout=10)
body = response.json()
if not response.ok:
    raise RuntimeError(body["error"]["message"])
print(body["data"])

Response

{
  "data": {
    "code": "tam",
    "code2": "ta",
    "name": "Tamil",
    "script": "Tamil",
    "confidence": 1,
    "reliable": true
  },
  "meta": {
    "note": "About 80 languages from their letters. Short texts are uncertain; Romanised Indian languages are flagged but not identified."
  }
}

Guides

Remove Aadhaar, PAN and phone numbers before sending text to an LLM

Using an AI assistant? Connect the MCP server and it can call this API by itself.