The internet is built on search engines where you enter what information you want and the web fetches it for you from the database. Searching is the most basic functionality that is seen in almost all applications. But it can be challenging when you have a large amount of data or documents and you need faster results. This is where natural language processing can be useful to us. With the development of new models in NLP, quicker computation and more accurate results are possible. One such development is a library called txtai. This enables a smarter way to apply natural language processing on search bars.
In this article, we will see the different applications of the txtai and implement them in Python.
What is Txtai?
Txtai is an AI-powered search engine that is built based on indexing over text sections. It is built using sentence transformers, python and libraries like faiss and annoy. Txtai performs a similarity search between the sections of the text and the query typed in the search bar. It can not only do this but also be used to build an interactive question and answer machine. It has already been used in platforms like :
- Paperai: to build AI-based indexing over science and medical papers
- Cord19q: an analysis of COVID 19
- Neuspo: a news and sports site
- Codequestion: allows you to ask questions about coding from your terminal.
Let us now understand how the txtai works by implementing a few small projects.
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