Web Summary

About this API

In an era of information overload, the Summary API offers a powerful solution to content surplus. It utilizes advanced Artificial Intelligence (AI) and Natural Language Processing (NLP) to read and understand any text, from news articles to academic papers, and distill it into key points. Designed for developers, students, researchers, and analysts who need to process large volumes of text efficiently, this API is more than a summarization tool. It's a content pre-processor that transforms unstructured web pages or text into clean, valuable, and structured JSON data objects.

Key Features

• Intelligent AI Summarization: Automatically generates two types of summaries based on the text's core ideas: a highly condensed "TL;DR" (Too Long; Didn't Read) version and a more detailed paragraph-style summary that retains context.
• Rich Metadata Extraction: In addition to the summary, the API automatically extracts and returns the article's title, author, publication date, and cover image, providing a complete, ready-to-use data package.
• URL and Plain Text Support: Offers high flexibility by processing both web page links (URLs) and direct input of large blocks of plain text.
• Distraction-Free Content Processing: Intelligently strips away ads, pop-ups, and navigation bars by parsing only the core content of an article, ensuring the summary is focused and clean.
• Relevance-First Algorithm: Smartly identifies and filters out filler content, weak arguments, and clickbait, ensuring the generated summary is high-quality and informative.

Use Cases

Scenario 1: Power a News Aggregator or "Read-it-Later" App

Situation: A developer is building an application similar to Pocket or Feedly to help users collect and manage online articles. Implementation: When a user saves an article link, the backend service calls the Summary API. The API returns a structured JSON object containing the article's title, summary, author, and main image. The application uses this data to generate a clean, uniformly formatted article card in the user's reading list. This provides a consistent experience and allows users to quickly grasp the article's main points before deciding to read it in full, greatly improving information-filtering efficiency.

Scenario 2: Create an AI-Powered Academic or Market Research Assistant

Situation: A platform for academics or market analysts needs to help users quickly process vast amounts of literature and reports. Implementation: The platform allows users to upload a list of URLs pointing to relevant research papers or industry reports. A background service then calls the Summary API for each link. The user is presented with a dashboard displaying concise summaries of all source articles. This enables researchers to evaluate the relevance of dozens of documents in hours instead of days, dramatically shortening the research cycle.

Scenario 3: Build an Internal Competitive and Media Monitoring System

Situation: A large corporation needs to keep its executive team informed about industry trends, competitor news, and media coverage. Implementation: An internal service can be set up to monitor specific news sites via RSS feeds or scheduled tasks. When a relevant article is found, its URL is sent to the Summary API. The returned summary is then formatted and pushed to a dedicated Slack channel or compiled into a daily email briefing. This automated workflow ensures decision-makers receive key intelligence promptly without being overwhelmed by the volume of original articles.

How it Works: Endpoints & Response

The API's core function is to receive input via a simple endpoint and return an information-rich JSON object.

Endpoint Example: https://hub.juheapi.com/summary/v1/abstractive

The response provides value far beyond the summary itself. As shown in the example, developers get not only the summary_text but also structured fields like article_title, article_authors, and article_image. This means developers no longer need to write complex web scrapers to parse and extract this metadata, as the API handles the most tedious work, greatly simplifying the development process.