10 docs tagged with "Search"

Query Elasticsearch indexes as SQL tables in Spice, including kNN vector search, full-text search, and hybrid search.

Operating guide for the Elasticsearch data connector in production: authentication, TLS, resilience, and operational tuning.

Describes how embedding models are used in Spice to convert text into numerical vectors for machine learning and search applications.

Learn how Spice can perform full text search

Embed list-of-strings columns as a column of vectors and use ColBERT-style late-interaction search in Spice.

Rerank search results using dedicated reranker models or LLM-as-reranker for improved relevance.

Learn how Spice can search across datasets using database-native and vector-search methods.

Reduce per-turn token cost and improve LLM tool selection accuracy by replacing individual tool definitions with searchable tool_search and tool_invoke meta-tools backed by hybrid full-text, keyword, schema, and vector search.

Learn how Spice can perform searches using vector-based methods.

Learn how Spice can perform web search