semantic_search
Find news articles based on meaning, not just keywords. Ask a natural-language question and get results ranked by relevance.
Instructions
Meaning-based search over the SIP news index (vector similarity).
Unlike search_news (exact keywords), this matches by meaning, so it handles
natural-language questions and wording that differs from the article. Each
result includes a `similarity` score in [0, 1].
Set `top_k` to control how many results come back (default 10). Requires the
index to have been built with build_semantic_index and an OPENROUTER_API_KEY
in the server environment. If the index is empty or the key is missing, the
response says so.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | A natural-language question or topic, e.g. 'military cooperation with Belgium'. | |
| top_k | No | How many of the most relevant results to return (1-50). | |
| language | No | Restrict to one content language: de, fr or en. | |
| since | No | Only items on/after this date (YYYY-MM-DD). | |
| until | No | Only items on/before this date (YYYY-MM-DD). | |
| category | No | Restrict to a category key (see list_categories). |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||