Enable Exact Keyword Text Matching

By default, Vectara disables exact and Boolean text matching, which is similar to a traditional, keyword-based search. You enable exact keyword matching, which disables neural retrieval, by specifying the lambda value as 1 at query time, specifically under the corpusKey:

      "corpusKey": [
        {
          "customerId": 123456789,
          "corpusId": 5,
          "semantics": 0,
          "metadataFilter": "",
          "lexicalInterpolationConfig": {
            "lambda": 1.0
          },
          "dim": []
        }

Enable Exact Keyword Matching in the Console UI

You can also set this value in the Console UI:

The default value of lambda is 0, which disables exact and Boolean text matching.

Example Query with Exact Keyword Search Enabled

The following example shows the full query with the lambda value set to 1:

curl -X POST \
-H "Authorization: <Bearer Token>" \
-H "customer-id: 1234567899" \
https://api.vectara.io:443/v1/query \
-d @- <<END;
{
  "query": [
    {
      "query": "What is offsides?",
      "queryContext": "",
      "start": 0,
      "numResults": 10,
      "contextConfig": {
        "charsBefore": 0,
        "charsAfter": 0,
        "sentencesBefore": 2,
        "sentencesAfter": 2,
        "startTag": "%START_SNIPPET%",
        "endTag": "%END_SNIPPET%"
      },
      "corpusKey": [
        {
          "customerId": 123456789,
          "corpusId": 5,
          "semantics": 0,
          "metadataFilter": "",
          "lexicalInterpolationConfig": {
            "lambda": 1.0
          },
          "dim": []
        }
      ],
      "summary": [
        {
          "maxSummarizedResults": 5,
          "responseLang": "eng",
          "summarizerPromptName": "vectara-summary-ext-v1.2.0"
        }
      ]
    }
  ]
}
END
        

Experimenting with the lambda value is useful if you're trying to evaluate how a keyword system like one based on Elasticsearch or Solr may compare to Vectara.