Jina, which is open sourced by Jina.AI, is a multimodal data search engine using deep learning technology. It not only implements some functions for search, but also includes the entire system that can be easily applied to the service, and supports effective indexing and search for various data such as images, videos, music, and source codes as well as text. Here is a link to the Jina github repository:
Thanks to the active use of deep learning technology, content-based searches for multimedia data such as images and videos are also possible, as well as natural language-based queries. In addition, since it has various types of interfaces such as Rest API, gRPC, and WebSocket, it has the advantage that it can be easily used in a cloud or distributed storage environment.
The Jina github repository introduces several demo examples, and you can download the demo code and necessary datasets using pip. For example, using Fashion-MNIST, which is composed of various clothes images, a demo to find similar clothes images by querying the image, and when a question in natural language is used using the CovidQA dataset, which is a collection of questions and answers about Corona 19, relevant information is provided. It contains very useful demos, such as a chatbot demo that informs you, and a demo that performs a search from multiple documents including various data types, so it can be considered very useful. Below is a demo of a chatbot from examples in the Jina github repository:
Although various AI technologies are open sourced, most of them are limited to specific module technologies in many cases. In the case of Jina, I think one of the biggest advantages is that it is an all-in-one open source package that can be easily installed and tested immediately.