package com.twitter.representationscorer.scorestore

import com.twitter.simclusters_v2.score.WeightedSumAggregatedScoreStore
import com.twitter.simclusters_v2.score.WeightedSumAggregatedScoreStore.WeightedSumAggregatedScoreParameter
import com.twitter.simclusters_v2.thriftscala.{EmbeddingType, ModelVersion, ScoringAlgorithm}

object TopicTweetRankingScoreStore {
  val producerEmbeddingScoreMultiplier = 1.0
  val consumerEmbeddingScoreMultiplier = 1.0

  /**
   * Build the scoring store for TopicTweet Ranking based on Default Multipliers.
   * If you want to compare the ranking between different multipliers, register a new
   * ScoringAlgorithm and let the upstream uses different scoringAlgorithm by params.
   */
  def buildTopicTweetRankingStore(
    consumerEmbeddingType: EmbeddingType,
    producerEmbeddingType: EmbeddingType,
    tweetEmbeddingType: EmbeddingType,
    modelVersion: ModelVersion,
    consumerEmbeddingMultiplier: Double = consumerEmbeddingScoreMultiplier,
    producerEmbeddingMultiplier: Double = producerEmbeddingScoreMultiplier
  ): WeightedSumAggregatedScoreStore = {
    WeightedSumAggregatedScoreStore(
      List(
        WeightedSumAggregatedScoreParameter(
          ScoringAlgorithm.PairEmbeddingCosineSimilarity,
          consumerEmbeddingMultiplier,
          WeightedSumAggregatedScoreStore.genericPairScoreIdToSimClustersEmbeddingPairScoreId(
            consumerEmbeddingType,
            tweetEmbeddingType,
            modelVersion
          )
        ),
        WeightedSumAggregatedScoreParameter(
          ScoringAlgorithm.PairEmbeddingCosineSimilarity,
          producerEmbeddingMultiplier,
          WeightedSumAggregatedScoreStore.genericPairScoreIdToSimClustersEmbeddingPairScoreId(
            producerEmbeddingType,
            tweetEmbeddingType,
            modelVersion
          )
        )
      )
    )
  }

}