574400 AI User Metrics

What does this MR do and why?

Expanding on AI Metrics we provide for user

Technical changes:

• Refactors AiUserMetricsService to use a single ClickHouse query with dynamic filtering
• Updates GraphQL type to dynamically generate fields for all AI tracking events
• Implements lookahead optimization to query only requested metrics

References

Screenshots or screen recordings

Before	After

How to set up and validate locally

query getUserAiUserMetrics(
  $fullPath: ID!
  $startDate: Date!
  $endDate: Date!
) {
  group(fullPath: $fullPath) {
    id
    aiUserMetrics(
      startDate: $startDate
      endDate: $endDate
    ) {
      nodes {
        user {
          id
          name
          username
          avatarUrl
          webUrl
          lastDuoActivityOn
        }
        codeSuggestionsAcceptedCount
        duoChatInteractionsCount
        codeSuggestionRejectedInIdeCount
        codeSuggestionsRequestedCount
        troubleshootJobCount
        agentPlatformSessionCreatedCount
        agentPlatformSessionStartedCount
        agentPlatformSessionFinishedCount
        agentPlatformSessionDroppedCount
        agentPlatformSessionStoppedCount
        encounterDuoCodeReviewErrorDuringReviewCount
        findNoIssuesDuoCodeReviewAfterReviewCount
        findNothingToReviewDuoCodeReviewOnMrCount
        postCommentDuoCodeReviewOnDiffCount
        reactThumbsUpOnDuoCodeReviewCommentCount
        reactThumbsDownOnDuoCodeReviewCommentCount
        requestReviewDuoCodeReviewOnMrByAuthorCount
        requestReviewDuoCodeReviewOnMrByNonAuthorCount
        excludedFilesFromDuoCodeReviewCount
      }
    }
  }
}

MR acceptance checklist

Evaluate this MR against the MR acceptance checklist. It helps you analyze changes to reduce risks in quality, performance, reliability, security, and maintainability.

Related to #574400