Eden AIWhat is Summarization API?
Text summarization is an NLP process that auto-generates a brief summary of lengthy documents or text. The primary objective is to condense vast amounts of data into a more manageable format while retaining the crucial and relevant details.
News articles, research papers, customer feedback, and other writing forms can be summarised using summarization APIs. They can be incorporated into diverse systems and platforms, including content management, customer relationship management (CRM), and information retrieval.
Top Open Source (Free) Summarization models on the market
For users seeking a cost-effective engine, opting for an open-source model is the recommended choice. Here is the list of best Summarization Open Source Models:
1. Text Summarizer
Text Summarizer is a complimentary and straightforward web application founded on Python and HTML that enables the user to condense any text to its fundamental key points. The application incorporates an advanced Natural Language Processing algorithm for optimum results, giving you the freedom to decide on the length of your summary.
2. SumEval
SumEval is a Python framework for text summarisation that is free and open-source. It also supports multiple languages, including Japanese and Chinese. The framework provides a well-structured JSON output that includes relevant details such as options, averages, and scores.
3. Summary
Summary is a web-based open-source application that offers extractive text summarization utilizing the frameworks of TextRank and RAKE. TypeScript and Vue were the languages employed in its creation.
4. ParaSum
ParaSum is a free, open-source, web-based tool for summarising text written in Python. It utilizes the Streamlit package to paraphrase and summarise text.
5. Sumy
Sumy is a basic library designed to extract summaries from both HTML pages and plain text documents while providing support for numerous algorithms like LSA, LexRank, Luhn, and others.
6. BERT Extractive Summarizer
This library utilizes pre-trained BERT models to carry out extractive summarization. It can be customized to specific summarization tasks, thus heightening its efficiency. This tool employs the HuggingFace Pytorch transformers library to generate extractive summaries.
The process involves embedding the sentences and subsequently applying a clustering algorithm to identify the sentences closest to the cluster's centroids.
7. Transformers
Hugging Face's Transformers library offers pre-trained models for various NLP tasks, such as summarization. BART, T5 and GPT-2 models can be utilized for both extractive and abstractive summarisation.
Cons of Using Open Source AI models
While open source models offer many advantages, they also come with some potential drawbacks and challenges. Here are some cons of using open source models:
- Not Entirely Cost Free: Open-source models, while providing valuable resources to users, may not always be entirely free of cost. Users often need to bear expenses related to hosting and server usage, especially when dealing with large or resource-intensive data sets.
- Lack of Support: Open source models may not have official support channels or dedicated customer support teams. If you encounter issues or need assistance, you might have to rely on community forums or the goodwill of volunteers, which can be less reliable than commercial support.
- Limited Documentation: Some open source models may have incomplete or poorly maintained documentation. This can make it difficult for developers to understand how to use the model effectively, leading to frustration and wasted time.
- Security Concerns: Security vulnerabilities can exist in open source models, and it may take longer for these issues to be addressed compared to commercially supported models. Users of open source models may need to monitor for security updates and patches actively.
- Scalability and Performance: Open source models may not be as optimized for performance and scalability as commercial models. If your application requires high performance or needs to handle a large number of requests, you may need to invest more time in optimization.
Why choose Eden AI?
Given the potential costs and challenges related to open-source models, one cost-effective solution is to use APIs. Eden AI smoothens the incorporation and implementation of AI technologies with its API, connecting to multiple AI engines.
Eden AI presents a broad range of AI APIs on its platform, customized to suit your specific needs and financial limitations. These technologies include data parsing, language identification, sentiment analysis, logo recognition, question answering, data anonymization, speech recognition, and numerous other capabilities.
To get started, we offer free $10 credits for you to explore our APIs.
Access Summarization providers with one API
Our standardized API enables you to integrate Summarization APIs into your system with ease by utilizing various providers on Eden AI. Here is the list (in alphabetical order):
- AlephAlpha
- Cohere
- Connexun
- Emvista
- Microsoft
- OpenAI
1. AlephAlpha- Available on EdenAI
Aleph Alpha's objective is to facilitate the accessibility, usability and integration of extensive European multilingual and multimodal AI models, in line with GPT-3 and DALL-E, to promote innovation in the areas of explainability, alignment and integration. The text summarization API shall use a precise model to give reliable outcomes.
2. Cohere- Available on Eden AI
Cohere's API is recognized for generating precise and concise summaries that encapsulate the key elements of a given content. Cohere utilizes Advanced Machine Learning techniques to create informative and comprehensible summaries that engage the readers.
3. Connexun- Available on Eden AI
Connexun provides a highly effective summarization API for generating concise and informative summaries of media content, including news articles. The API utilizes over 13,000 human-written summaries to identify dependencies and produce the summaries.
4. Emvista- Available on Eden AI
With Emvista's advanced NLP techniques, complex text structures such as scientific papers, legal documents, and technical reports can be confidently handled whilst retaining the original meaning and context. Integrating Emvista's summarization capabilities into their own products and services enables developers to save time and resources whilst enhancing overall quality.
5. Microsoft- Available on Eden AI
This software is a component of Microsoft's group of cognitive tools. Its primary function is to create briefs of news articles and other media items using extractive and abstractive methods. The software is also capable of producing briefs in various languages.
6. OpenAI- Available on Eden AI
OpenAI provides the GPT-3 Summarization API, which creates concise summaries that go beyond basic selection and combination of sentences from the original text. This API can produce high-quality summaries that resemble those created by humans, even for extensive text collections.
Pricing Structure for Summarization API Providers
Eden AI offers a user-friendly platform for evaluating pricing information from diverse API providers and monitoring price changes over time. As a result, keeping up-to-date with the latest pricing is crucial. The pricing chart below outlines the rates for smaller quantities for October 2023, as well as you can get discounts for potentially large volumes.
Check the current prices on Eden AI
How Eden AI can help you?
Eden AI is the future of AI usage in companies: our app allows you to call multiple AI APIs.
- Centralized and fully monitored billing on Eden AI for Summarization APIs
- Unified API for all providers: simple and standard to use, quick switch between providers, access to the specific features of each provider
- Standardized response format: the JSON output format is the same for all suppliers thanks to Eden AI's standardization work. The response elements are also standardized thanks to Eden AI's powerful matching algorithms.
- The best Artificial Intelligence APIs in the market are available: big cloud providers (Google, AWS, Microsoft, and more specialized engines)
- Data protection: Eden AI will not store or use any data. Possibility to filter to use only GDPR engines.
You can see Eden AI documentation here.
Next step in your project
The Eden AI team can help you with your Summarization integration project. This can be done by :
- Organizing a product demo and a discussion to better understand your needs. You can book a time slot on this link: Contact
- By testing the public version of Eden AI for free: however, not all providers are available on this version. Some are only available on the Enterprise version.
- By benefiting from the support and advice of a team of experts to find the optimal combination of providers according to the specifics of your needs
- Having the possibility to integrate on a third-party platform: we can quickly develop connectors.
