Introducing txtai, the all-in-one embeddings database
<p>Search is the base of many applications. Once data starts to pile up, users want to be able to find it. It’s the foundation of the internet and an ever-growing challenge that is never solved or done.</p>
<p>The field of Natural Language Processing (NLP) is rapidly evolving with a number of new developments. Large-scale general language models are an exciting new capability allowing us to add amazing functionality. Innovation continues with new models and advancements coming in at what seems a weekly basis.</p>
<p>This article introduces txtai, an all-in-one embeddings database that enables Natural Language Understanding (NLU) based search in any application.</p>
<h1>Introducing txtai</h1>
<p><img alt="" src="https://miro.medium.com/v2/resize:fit:700/1*cBxmgtJEZsgk2sbUAYyMOw.png" style="height:147px; width:700px" /></p>
<p><a href="https://github.com/neuml/txtai" rel="noopener ugc nofollow" target="_blank">txtai</a> is an all-in-one embeddings database for semantic search, LLM orchestration and language model workflows.</p>
<p>Embeddings databases are a union of vector indexes (sparse and dense), graph networks and relational databases. This enables vector search with SQL, topic modeling, retrieval augmented generation and more.</p>
<p><a href="https://medium.com/neuml/introducing-txtai-the-all-in-one-embeddings-database-c721f4ff91ad"><strong>Learn More</strong></a></p>