Search API

Search

post

Perform a vector similarity search (VSS) operation on a dataset.

The search operation will return the most relevant matches based on cosine similarity with the input text. The datasets queries should have an embedding column, and the appropriate embedding model loaded.

Authorizations

ApiKeyAuth

Body

application/json

anyOptional

Responses

200

Search completed successfully

application/json

Responseany

400

Invalid request parameters

application/json

500

Internal server error

application/json

post

HTTPcURLJavaScriptPython

POST /v1/search HTTP/1.1
Host: data.spiceai.io
X-API-KEY: YOUR_API_KEY
Content-Type: application/json
Accept: */*
Content-Length: 157

{
  "datasets": [
    "app_messages"
  ],
  "text": "Tokyo plane tickets",
  "where": "user=1234321",
  "additional_columns": [
    "timestamp"
  ],
  "limit": 3,
  "keywords": [
    "plane",
    "tickets"
  ]
}

{
  "results": [
    {
      "matches": {
        "message": "I booked use some tickets"
      },
      "dataset": "app_messages",
      "primary_key": {
        "id": "6fd5a215-0881-421d-ace0-b293b83452b5"
      },
      "data": {
        "timestamp": 1724716542
      },
      "score": 0.914321
    },
    {
      "matches": {
        "message": "direct to Narata"
      },
      "dataset": "app_messages",
      "primary_key": {
        "id": "8a25595f-99fb-4404-8c82-e1046d8f4c4b"
      },
      "data": {
        "timestamp": 1724715881
      },
      "score": 0.83221
    },
    {
      "matches": {
        "message": "Yes, we're sitting together"
      },
      "dataset": "app_messages",
      "primary_key": {
        "id": "8421ed84-b86d-4b10-b4da-7a432e8912c0"
      },
      "data": {
        "timestamp": 1724716123
      },
      "score": 0.787654321
    }
  ],
  "duration_ms": 42
}