What’s New in txtai 5.0
Semantic graph, external integrations and more
txtai is an open-source platform for semantic search and workflows powered by language models.
The following articles have previously covered txtai.
txtai 5.0 brings a number of major feature enhancements, most importantly the semantic graph. This article will cover all the changes.
Semantic Graph
Semantic graphs, also known as knowledge graphs or semantic networks, build a graph network with semantic relationships connecting the nodes. In txtai, they can take advantage of the relationships inherently learned within an embeddings index. This opens exciting possibilities for exploring relationships, such as topics and interconnections in a dataset.
Semantic graphs in txtai can be used for topic modeling, graph traversal and analysis. Check out the following links for more.
External integrations
Want to run Weaviate as your txtai vector database, PostgreSQL for database storage and Neo4j for graphs? 5.0 makes it easier to integrate external vector engines, databases and graph stores.
Check out the following links to explore how modular embeddings index components can be connected together.
Wrapping up
This article gave a quick overview of txtai 5.0. There are also a number of improvements and bug fixes. See the following links for more information.