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v1

latestOpenAPI 3.0.02026-07-1329122146.2 KB
QueryService

Search for relevant results, highlight relevant snippets, and do Retrieval Augmented Generation (RAG).

Some tips for this API:

  • This operation authenticates with either an API Key or OAuth 2.0 (in a JWT "Bearer Token"). You can find details of how to set up an API key or use OAuth 2.0 here.
  • By default, Vectara only uses its neural/semantic retrieval model, and does not attempt to use keyword matching. To enable hybrid search with a mix of both keyword and neural results, edit the lambda value. Additional documentation on hybrid search is here.
  • Vectara can automatically provide a generative summary with the query results for Retrieval Augmented Generation (RAG). Additional details on RAG in Vectara can be found here.
  • The Query API takes an array of queries, since you can have Vectara perform more than 1 query in a single API call. The results that are returned are thus in an array as well, with each element in the response array corresponding to the input query array.
  • Custom dimensions (the dim array) is a feature that is only available to Scale accounts.
  • Reranking enhances search accuracy and variety and more details can be found here.
post/v1/query

Headers

customer-idinteger required

Enter the Customer ID to use for the request.

timeoutstring

(Optional) Enter the timeout value of the request in seconds, such as 10S or 30S.

Request body

Example request

{
  "query": [
    {
      "query": "What is the answer to the life, the universe, and everything?",
      "start": 0,
      "numResults": 10,
      "contextConfig": {
        "sentencesBefore": 3,
        "sentencesAfter": 3,
        "startTag": "<b>",
        "endTag": "</b>"
      },
      "corpusKey": [
        {
          "customerId": 12345,
          "corpusId": 12
        }
      ],
      "summary": [
        {
          "maxSummarizedResults": 10,
          "responseLang": "en"
        }
      ]
    }
  ]
}

Response

A successful response.

Example response

{
  "responseSet": [
    {
      "response": [
        {
          "corpusKey": {
            "corpus_id": 12
          }
        }
      ]
    }
  ]
}