If you've registered on ourai.applicloud.com and tried semantic search at SemanticDemo, you may have noticed that its usage is quite different from traditional full-text search. Understanding how to use it effectively requires a bit of learning.

In previous articles, we demonstrated how to prepare a large document for vectorization, perform the vectorization process, and now it's time to search within a vector database.

When dealing with extensive PDF files—like operating system documentation for Red Hat 7, which can span thousands of pages—you may want to add semantic search functionality. Unlike traditional full-text search, semantic search can return relevant text passages even when the search query itself doesn't explicitly appear in the document. Instead,...

Whether you're working with a simple open-source AI model or the most advanced systems for processing and generating text, they all share one fundamental principle: converting text into a vector matrix and searching for similarities within their database. The result is then further processed into "human language."

The easiest way is through the OpenAI Dashboard:
OpenAI Usage
Here, you can view your monthly spending and set a monthly limit.

n typical chat applications, users exchange questions and answers within a continuous conversation—artificial intelligence remembers what has been said and adapts responses based on the previous context. However, this approach is not always desirable. There are situations where it is more beneficial for each question to be processed independently,...

f you already have a basic understanding of any programming language, you can easily tap into the power of the OpenAI API with just a few lines of code. All you need is:

When it comes to integrating anything in IT, the answer is always API. Every robust system comes with an API—and AI systems are no exception; in fact, they're typically top-notch systems!