💡 What's new in txtai 9.0
The 9.0 release adds first class support for sparse vector models (i.e. SPLADE), late interaction models (i.e. ColBERT), fixed dimensional encoding (i.e. MUVERA) and reranking pipelines ✨
The embeddings framework was overhauled to seamlessly support ...
neuml.hashnode.dev6 min read
Anik Sikder
Turning bugs into features since forever
This release really puts txtai in the same conversation as top-tier retrieval frameworks. The addition of SPLADE and ColBERT support is huge especially for anyone working on high-precision semantic search or RAG pipelines. MUVERA’s fixed dimensional encoding feels like the missing piece for scaling multi-vector models without sacrificing performance. Curious to see how this impacts latency and recall in real-world use cases.