MIAPI

MIAPI is an AI application programmed to deliver answers based on real-time web search. It is specifically designed for developers and it is compatible with OpenAI. This tool has impressive features such as providing answers with inline citations, sources, and confidence scores. These features allow developers to create applications that can provide responses that are verifiable and dependable.

MIAPI offers a broad range of impressive features aimed at enhancing user experience and functionality. These include real-time server-sent events streaming which show generated answers, a knowledge mode that allows developers to pass their own documents, and a search-only mode for raw search results without LLM processing. MIAPI also provides developers with SDKs for Python, JavaScript, and cURL, dedicated news and image search endpoints, and the ability to create applications that yield verifiable and trustworthy responses.

MIAPI generates answers based on real-time web search through a likely combination of machine learning and natural language processing algorithms. It processes the search query input and performs a web search to fetch relevant data. This data is then processed, distilled, and structured into a cogent response. Supplementary information such as inline citations, sources, and confidence scores are also generated and attached to the response.

MIAPI provides Software Development Kits (SDKs) compatible with Python, JavaScript, and cURL programming languages. These SDKs offer guides and libraries that simplify the process of integrating MIAPI into a developer's application.

Developers can integrate MIAPI into their applications using JavaScript through an API call. They create an instance of the Fetch API, using the desired MIAPI endpoint as the URL. POST is set as the HTTP method, and the headers object contains 'Content-Type' and 'Authorization', with a bearer access token. The question and citation requirements are added to the body of the request stringified into JSON format. The returned response is processed into JSON format for use in the application.