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Text Summariser

Condense long documents to their key sentences using extractive TF-IDF summarisation

POST 1 credit /v1/text/summarize
curl -X POST "https://textanalysis.toolkitapi.io/v1/text/summarize" \
  -H "X-API-Key: YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{"text": "Your long article text here...", "num_sentences": 3}'
import httpx

resp = httpx.post(
    "https://textanalysis.toolkitapi.io/v1/text/summarize",
    json={"text": "Your long article text here...", "num_sentences": 3},
)
print(resp.json())
const resp = await fetch("https://textanalysis.toolkitapi.io/v1/text/summarize", {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
  },
  body: JSON.stringify({"text": "Your long article text here...", "num_sentences": 3}),
});
const data = await resp.json();
console.log(data);
# See curl example
Response 200 OK
{
  "summary": "The first most important sentence. The second key insight. The third critical point.",
  "sentences_in_summary": 3,
  "original_sentence_count": 12
}

Try It Live

Live Demo

Description

Condense long documents to their key sentences using extractive TF-IDF summarisation

How to Use

1

1. Send a POST request to `/v1/text/summarize` with the `text` to summarise. 2. Set `num_sentences` to control the summary length (default: 3). 3. The response includes the `summary` string and the `original_sentence_count` for context. 4. For best results, provide at least 5 sentences of source text.

About This Tool

The Summarise endpoint uses extractive summarisation to condense long documents to a configurable number of key sentences. It uses TF-IDF scoring to rank sentences by importance — no LLM or external service required.

Unlike abstractive summarisation (which generates new text), extractive summarisation selects the most relevant sentences directly from the source — making it fast, deterministic, and free from hallucination.

Why Use This Tool

Start using Text Summariser now

Get your free API key and make your first request in under a minute.