Manticore Search 28.4.4: Faster KNN, better conversational search, easier installs and more faceting controls

Manticore Search released version 28.4.4 with faster KNN rescoring through batched distance calculations, conversational search now available via the JSON API, and a simplified install/upgrade path using a single curl command. The update also adds zero-count facet buckets for faceted search, per-table relevance defaults, and a server-level cap on embedding threads, along with 17 bug fixes.

Manticore Search 28.4.4 https://manticoresearch.com/install/ has been released. This release brings faster KNN rescoring, more flexible conversational search, a simpler install and upgrade path, better faceting controls, per-table relevance defaults, and fixes across authentication, replication, SQL compatibility, distributed queries, and columnar/KNN internals. This post is a catch-up for everything shipped from 27.2.0 through 28.4.4 . Please review these before upgrading: SPH UDF VERSION to 12. dict=keywords 32k embeddings threads KNN search https://manual.manticoresearch.com/Searching/KNN KNN-vector-search now batches distance calculations during the rescore pass. After HNSW returns the candidate set, Manticore recomputes final full-precision distances and re-sorts the results. Batching that work reduces per-candidate overhead in the final stage of vector search. For vector-heavy workloads, this takes work out of the part of the query that runs after candidate selection. Results do not change; the final ranking pass just has less overhead when many candidates are rescored. Conversational search https://manual.manticoresearch.com/Searching/Conversational search is now available through the /search JSON API as well as SQL CALL CHAT . That makes it easier to use Manticore's chat flow from applications that already talk to the HTTP API and do not want to add a separate SQL path just for chat requests. CREATE CHAT MODEL also gained custom prompt support, so answers can follow application-specific instructions such as citation rules, tone, response length, or formatting. The feature is still built on the same Manticore Search flow: retrieve relevant documents from an existing vectorized table, build context, keep conversation history, and return an answer with supporting sources. The quick-start install path is now simpler: curl https://manticoresearch.com | sh The same installer can also upgrade an existing installation, list available versions, switch between stable and development repositories, and install a selected version. Package managers still remain the source of truth for installed files, repositories, services, and dependencies; the new path just removes the manual setup steps around them. For all options, run: curl https://manticoresearch.com | sh -s help Faceted search https://manual.manticoresearch.com/Searching/Faceted search now supports zero-count facet buckets through SQL ZEROES and JSON "zeroes": true . This is a small but important UI feature. In e-commerce-style filtering, you often want to keep an option visible even when the current filter combination gives it a count of 0 . Combined with max -mode facet behavior, zero-count buckets make it easier to show selected, available, and currently unavailable choices without hiding part of the filter vocabulary from the user. Manticore now supports CREATE TABLE ... profile='relevance' https://manual.manticoresearch.com/Creating a table/Local tables/Plain and real-time table settings profile , plus stored per-table defaults for ranker boolean mode Based on our search quality tests, profile='relevance' and the ranking settings it enables improve relevance in many cases. The application also no longer needs to repeat the same ranking parameters in every request. embeddings threads https://manual.manticoresearch.com/Server settings/Searchd embeddings threads caps the CPU threads used for auto-embedding inserts, ALTER TABLE ... REBUILD KNN , and text-to-vector KNN queries.This matters on shared hosts and mixed workloads. Embedding generation and KNN rebuilds can be CPU-heavy; a server-level cap makes those jobs easier to schedule without letting them take over the whole machine. This release includes 17 bug fixes . The most important ones are: COUNT DISTINCT ... GETFIELD fetch errors or malformed replies instead of returning apparently successful rows with empty or untrusted stored-field values. .tmp.spc. files from breaking later table rename, attach, or drop operations. SELECT queries. SET statements no longer fail under auth. здоров'ям match здоров'я under lemmatize uk all . blend mode , restoring separator-stripped variants consistently for indexing and keyword extraction. percentiles aggregations together with terms aggregations in the same /search request on multi-chunk RT tables was fixed.For the complete list, see the changelog https://manual.manticoresearch.com/Changelog Version-28.4.4 .