Text Similarity

Overview

Text Similarity works by comparing the two texts and calculating the similarity score based on various factors. It returns the similarity score in a structured format.

Endpoint

One host, one path per API. The block below shows this call in four languages; every one of them is the same HTTP request. Making requests covers the timeouts, retries and parameter rules that apply to all of them. The SDKs wrap the same call in a typed client.

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curl -X POST https://api.apiverve.com/v1/textsimilarity \
  -H "x-api-key: your_api_key_here" \
  -H "Content-Type: application/json" \
  -d '{
  "text1": "I'm so excited that tomorrow is going to be sunny! Can't wait!",
  "text2": "We're pretty excited about the weather tomorrow. It's going to be sunny!"
}'

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const res = await fetch('https://api.apiverve.com/v1/textsimilarity', {
  method: 'POST',
  headers: {
    'x-api-key': 'your_api_key_here',
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
  "text1": "I'm so excited that tomorrow is going to be sunny! Can't wait!",
  "text2": "We're pretty excited about the weather tomorrow. It's going to be sunny!"
}),
});

if (!res.ok) throw new Error(`${res.status} ${await res.text()}`);

const { data } = await res.json();
console.log(data);

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import requests

res = requests.post(
    "https://api.apiverve.com/v1/textsimilarity",
    headers={"x-api-key": "your_api_key_here"},
    json={
    "text1": "I'm so excited that tomorrow is going to be sunny! Can't wait!",
    "text2": "We're pretty excited about the weather tomorrow. It's going to be sunny!"
},
    timeout=15,
)
res.raise_for_status()

print(res.json()["data"])

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package main

import (
	"fmt"
	"io"
	"net/http"
	"strings"
)

func main() {
	body := strings.NewReader(`{
  "text1": "I'm so excited that tomorrow is going to be sunny! Can't wait!",
  "text2": "We're pretty excited about the weather tomorrow. It's going to be sunny!"
}`)
	req, _ := http.NewRequest("POST", "https://api.apiverve.com/v1/textsimilarity", body)
	req.Header.Set("Content-Type", "application/json")
	req.Header.Set("x-api-key", "your_api_key_here")

	res, err := http.DefaultClient.Do(req)
	if err != nil {
		panic(err)
	}
	defer res.Body.Close()

	out, _ := io.ReadAll(res.Body)
	fmt.Println(string(out))
}

Replace your_api_key_here with the key from your dashboard. When the inputs arrive as a list rather than one at a time, batch requests run up to 200 of them through this same API in a single call.

Authentication

Send your key in the x-api-key header. That is the only auth step — there is no token exchange and no per-endpoint scope to configure. Authentication covers creating, rotating and revoking keys.

Parameters

Sent as JSON in the request body. Premium parameters are accepted on every plan but only take effect on plans that include them.

Response

Every API returns the same three top-level keys, so one response handler covers your whole integration: status, error and data. Only data changes shape. Response format covers the envelope, the other output formats and how premium fields are withheld.

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{
  "status": "ok",
  "error": null,
  "data": {
    "simiarity": 45.83,
    "similarityCaseSensitive": 47.22,
    "difference": {
      "count": 7,
      "percentage": 58.33
    }
  }
}

Response fields

Paths are relative to data. Premium fields are absent rather than zeroed on plans that do not include them, so check for presence instead of comparing to 0.

Errors

Read the HTTP status first, then error for the specific reason. The body names the parameter that has to change. Error handling covers the full status list and which of them are worth retrying.

Use cases

Plagiarism Screening

Educators check student assignment submissions against reference essays to catch paraphrased or near-identical passages using case-insensitive similarity scores.

Catalog Deduplication

To merge duplicate inventory listings, marketplace operators evaluate difference percentages across submitted product titles.

Support Ticket Clustering

Helpdesk systems group incoming user inquiries with existing knowledge base answers when match percentages cross predefined thresholds.

Translation Revision Tracking

When editors revise translated copy, localization teams compute case-sensitive similarity to track how much phrasing changed between drafts.

Other ways to use Text Similarity

Set up Text Similarity on APIVerve, or reach the same source a different way. Your APIVerve account and credits work on all of them — one key, one balance.

Related

More in Text Processing: