RagContexts

Relevant contexts for one query.

Fields
contexts[] object (Context)

All its contexts.

JSON representation 
{
  "contexts": [
    {
      object (Context)
    }
  ]
}

Context

A context of the query.

Fields
sourceUri string

If the file is imported from Cloud Storage or Google Drive, sourceUri will be original file URI in Cloud Storage or Google Drive; if file is uploaded, sourceUri will be file display name.

sourceDisplayName string

The file display name.

text string

The text chunk.

distance
(deprecated) number

The distance between the query dense embedding vector and the context text vector.

sparseDistance
(deprecated) number

The distance between the query sparse embedding vector and the context text vector.

chunk object (RagChunk)

Context of the retrieved chunk.

score number

According to the underlying Vector DB and the selected metric type, the score can be either the distance or the similarity between the query and the context and its range depends on the metric type.

For example, if the metric type is COSINE_DISTANCE, it represents the distance between the query and the context. The larger the distance, the less relevant the context is to the query. The range is [0, 2], while 0 means the most relevant and 2 means the least relevant.

JSON representation 
{
  "sourceUri": string,
  "sourceDisplayName": string,
  "text": string,
  "distance": number,
  "sparseDistance": number,
  "chunk": {
    object (RagChunk)
  },
  "score": number
}