The following is a list of terms used throughout the documentation.
|An agent is a program or entity that can make decisions, and take actions to achieve specific goals or objectives. The concept of an agent is central to the field of artificial intelligence, particularly in the study of agent-based systems and autonomous agents. An AI agent is a central concept in artificial intelligence, representing an entity with the ability to perceive, reason, and act to achieve specific goals or objectives.
|API stands for Application Programming Interface. It is a set of rules and protocols that allows different software applications to communicate and interact with each other. APIs define the methods and data formats that applications can use to request and exchange information, enabling them to work together and perform specific tasks seamlessly.
|Batch requests refer to a technique where multiple individual HTTP requests are combined into a single request. Instead of sending each request separately, a client can bundle multiple requests into one batch request and send them to the server in a single round-trip. The server then processes each request in the batch and returns a combined response containing the results for each individual request.
|A Large Language Model (LLM) refers to a class of artificial intelligence models that are designed to understand and generate human language. These models are typically based on deep learning techniques, particularly neural networks, and they have a vast number of parameters, making them capable of processing and generating text at an impressive scale.
|Named Entity Recognition (NER) is a natural language processing (NLP) technique used to identify and classify named entities within a text into predefined categories. Named entities are specific words or phrases that refer to real-world objects such as people, organizations, locations, dates, quantities, and other named entities that have distinct and well-defined names. The primary goal of Named Entity Recognition is to recognize and extract these named entities from unstructured text, such as articles, social media posts, or research papers, and assign them to appropriate categories. By identifying named entities, NER helps in extracting valuable information and understanding the context of the text, which is particularly useful in information retrieval, text analysis, sentiment analysis, question-answering systems, and more.
|Binding is the process of extracting data from websites which involves an automated methods to gather information from web pages by navigating through the site's structure, locate relevant data, and extract it for further processing or analysis.
|In the context of AI, "sentiments" refer to the emotions, opinions, or attitudes expressed in a piece of text or speech. Sentiment analysis, also known as opinion mining, is a natural language processing (NLP) technique used to determine the sentiment conveyed by a given text, such as a review, tweet, customer feedback, or news article.
|WYSIWYG is an acronym that stands for "What You See Is What You Get." It is a term commonly used in the context of computer software and applications, particularly in web page editors. The content displayed on the screen during the editing process is a close representation of how it will appear in the final output.