Search
Perform semantic search that understands meaning rather than just keywords. Uses advanced multimodal embedding models to find relevant content based on context and intent with sub-second response times. Search across text chunks within vector stores using natural language queries like "comfortable running shoes" to find "cushioned athletic sneakers".
Command
Options
--top-k <n>
- Number of results to return (default:10
, range:1
-100
)--threshold <score>
- Minimum similarity score (range:0.0
-1.0
)--return-metadata
- Include file metadata in results--rerank
- Enable result reranking for better relevance (default:false
)--file-search
- Search files instead of chunks
Note: Default values for --top-k
and --rerank
can be configured using mxbai config
. See the Configuration Guide for details.
Examples
File Management
Upload files and manage files within vector stores.
Question Answering
Ask questions about content in your vector stores and get AI-powered answers.
Last updated: July 5, 2025