io.cequence.pineconescala.service.PineconeInferenceService.scala Maven / Gradle / Ivy

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package io.cequence.pineconescala.service

import io.cequence.pineconescala.domain.response.{EvaluateResponse, GenerateEmbeddingsResponse, RerankResponse}
import io.cequence.pineconescala.domain.settings.{GenerateEmbeddingsSettings, RerankSettings}
import io.cequence.wsclient.service.CloseableService

import scala.concurrent.Future

/**
 * Pinecone inference operations as defined at the API ref. page
 *
 * The following services are supported:
 *
 *   - createEmbeddings
 *   - rerank
 *   - evaluate
 *
 * @since May
 *   2024
 */
trait PineconeInferenceService extends CloseableService with PineconeServiceConsts {

  /**
   * Uses the specified model to generate embeddings for the input sequence.
   *
   * @param inputs
   *   Input sequence for which to generate embeddings.
   * @param settings
   * @return
   *   list of embeddings inside an envelope
   *
   * @see
   *   Pinecone
   *   Doc
   */
  // TODO: rename to embedData to be consistent with the API
  def createEmbeddings(
    inputs: Seq[String],
    settings: GenerateEmbeddingsSettings = DefaultSettings.GenerateEmbeddings
  ): Future[GenerateEmbeddingsResponse]

  /**
   * Using a reranker to rerank a list of items for a query.
   *
   * @param query
   *   The query to rerank documents against (required)
   * @param documents
   *   The documents to rerank (required)
   * @param settings
   * @return
   *
   * @see
   *   Pinecone
   *   Doc
   */
  def rerank(
    query: String,
    documents: Seq[Map[String, Any]],
    settings: RerankSettings = DefaultSettings.Rerank
  ): Future[RerankResponse]

  /**
   * Evaluate an answer
   *
   * The metrics_alignment endpoint evaluates the correctness, completeness, and alignment of a
   * generated answer with respect to a question and a ground truth answer. The correctness and
   * completeness are evaluated based on the precision and recall of the generated answer with
   * respect to the ground truth answer facts. Alignment is the harmonic mean of correctness
   * and completeness.
   *
   * Note: Originally in the Pinecone API this function is part of Assistant API.
   *
   * @param question
   *   The question for which the answer was generated.
   * @param answer
   *   The generated answer.
   * @param groundTruthAnswer
   *   The ground truth answer to the question.
   * @return
   */
  def evaluate(
    question: String,
    answer: String,
    groundTruthAnswer: String
  ): Future[EvaluateResponse]
}