An NLP API is a tool that allows developers to add advanced language processing to their applications without creating it all from the beginning. NLP APIs provide pre-made features and models for tasks like analyzing emotions, interpreting text, translating languages, finding named entities, and summarizing text.
These tools help developers process and understand written data, gathering insights to improve natural language understanding in applications such as chatbots, virtual assistants, and tools for analyzing sentiment.
For users seeking a cost-effective engine, opting for an open-source model is the recommended choice. Here is the list of the best NLP Open Source Models:
Rasa Open Source offers open-source natural language processing to break down complex user messages into intents and entities that chatbots can interpret. Using lower-level machine learning libraries such as Tensorflow and spaCy, Rasa Open Source provides highly customisable natural language processing software that is both approachable and precise.
Flair offers cutting-edge natural language processing (NLP) models to enhance your text. Our models include named entity recognition (NER), sentiment analysis, and part-of-speech tagging (PoS). We also provide special support for biomedical data, sense disambiguation, and classification. Our models are available for an expanding range of languages.
spaCy is an advanced library that utilizes Natural Language Processing in Python and Cython. Developed using cutting-edge research, it was specifically designed for commercial use from its inception.
PyText is a deep-learning-based NLP modeling framework constructed on PyTorch. Its goal is to fulfill the two concurrent demands of enabling swift experimentation and serving models at scale, which often conflict with each other. This is accomplished by providing uncomplicated and scalable interfaces and abstracts for model components, and by utilizing PyTorch's ability to export models for inferences via the optimized Caffe2 execution engine.
An open-source NLP research library.
While open source models offer many advantages, they also have potential drawbacks and challenges. Here are some cons of using open source models:
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.
Our standardized API enables you to integrate NLP APIs into your system with ease by utilizing various providers on Eden AI. Here is the list of one of NLP tasks, NER (in alphabetical order):
AWS's NER solution is very popular because it's very precise and can be customized. It's easy to teach it about different categories and languages, and it works well with many other AWS tools. Additionally, Amazon's security and compliance measures make it reliable and scalable.
The API can detect phone numbers and addresses with accuracy in the chosen language it supports. It identifies entities precisely and forms meaningful connections between them, augmenting contextual insights of the extracted information and boosting its overall quality.
IBM Watson offers a highly adaptable and advanced NER solution made for identifying entities. It can handle numerous languages proficiently and accurately recognize entities from diverse contexts.
Lettria's NER API achieves a perfect balance between accuracy and speed, making it fitting for several NLP-related applications. The company also allows you to customize the NER API for specific use cases, which enables greater flexibility.
Moreover, the API has an easy-to-use RESTful interface, simplifying its integration into present applications.
Azure offers NER API services as a component of its Microsoft Azure Cognitive Services package. These services are hosted on the dependable Microsoft Azure infrastructure, ensuring increased scalability and reliability.
Utilizing the NER API is simple with access to thorough SDKs and APIs. Additionally, the API is compatible with multiple languages, making it appropriate for a diverse range of worldwide applications.
Neural Space's NER API is ideal for businesses that need accurate text processing for specific languages or fields. The API is highly customizable and accurate. It supports over 36 different entities and 87 languages, enabling it to be used in a wide variety of contexts.
NLP Cloud's NER API provides elevated entity recognition with customization choices, multilingual compatibility, and pre-trained models to ensure precise identification of names, locations, organizations, and other entities. Its user-friendly interface supports smooth implementation into current applications.
Open AI's state-of-the-art technology applies advanced machine learning models to precisely identify and extract entities from text data. Customers can tailor the API's functionality to their distinct needs, fine-tuning for domain-specific entity identification. Additionally, the API can handle multiple languages, facilitating text processing in various languages.
Tenstorrent's NER API provides a remarkable blend of accuracy, multi-language support, scalability, and seamless integration. It proves to be an optimum choice for businesses that manage extensive text data in different languages, owing to its efficient handling of diverse processing requirements.
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 November 2023, as well as you can get discounts for potentially large volumes.
Eden AI is the future of AI usage in companies: our app allows you to call multiple AI APIs.
You can see Eden AI documentation here.
The Eden AI team can help you with your NLP integration project. This can be done by :