Run a semantic search

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Prerequisites

• A dataset whose semantic search is ready. Check readiness first; semantic indexing completes after text indexing.

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Search by meaning

curl https://api.withsplendor.com/v1/search \
  -H "Authorization: Bearer $SPLENDOR_TOKEN" \
  -H "X-Splendor-Tenant-Id: $SPLENDOR_TENANT_ID" \
  -H "Content-Type: application/json" \
  -d '{
    "text": "users cannot log in",
    "datasets": ["support-tickets"],
    "semantic": true,
    "limit": 20
  }'

envelope = client.post("/v1/search", json={
    "text": "users cannot log in",
    "datasets": ["support-tickets"],
    "semantic": True,
    "limit": 20,
}).json()

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What is different from text search

• Totals are approximate. Semantic search is top-K retrieval, so total is reported as { "value": null, "relation": "unknown" }. Do not treat it as an exact count.
• Scores are vector (or hybrid when blended with text).
• Modalities. Use content_filter to choose what to search: text (default), images, or all to search both and merge. images matches on visual similarity, including images referenced by a record field — so a metadata where filter and a visual query can select the same record.

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