semantic_search
Search indexed documents with natural language queries to find relevant chunks ranked by semantic similarity, returning source paths and scores. Use hybrid mode for keyword plus vector matching.
Instructions
Search indexed documents using natural language.
Finds the most relevant document chunks matching the query using semantic similarity. Returns ranked results with source file paths and relevance scores.
Use mode='hybrid' to combine vector search with full-text search via Reciprocal Rank Fusion for better keyword + semantic matching.
The folder must be indexed first with index_folder.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| mode | No | Search mode: 'vector' (default) or 'hybrid' (vector + full-text via RRF) | vector |
| query | Yes | Natural language search query | |
| top_k | No | Number of results to return | |
| file_type | No | Filter results by file extension, e.g. '.pdf' | |
| folder_path | No | Limit search to a specific indexed folder. If omitted, searches all indexed folders. |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||