gemini chat msg and summary

Author: amychisholm03

lib/llm-events-new/chat-summary.js

@@ -45,8 +45,8 @@ class LlmChatCompletionSummary extends LlmEvent {
     this['request.max_tokens'] = maxTokens
     this['request.temperature'] = temperature
     this['response.number_of_messages'] = numMsgs
-    this['response.choices.finish_reason'] = finishReason
-    this['response.organization'] = responseOrg
+    if (finishReason) this['response.choices.finish_reason'] = finishReason
+    if (responseOrg) this['response.organization'] = responseOrg
     this.timestamp = segment.timer.start
     this.duration = segment.getDurationInMillis()
   }

lib/llm-events-new/embedding.js

@@ -34,7 +34,7 @@ class LlmEmbedding extends LlmEvent {
   constructor({ agent, segment, transaction, requestId, requestInput, requestModel, responseModel, responseOrg, vendor, error }) {
     super({ agent, segment, requestId, responseModel, transaction, vendor, error })
     if (requestModel) this['request.model'] = requestModel
-    if (responseModel) this['response.organization'] = responseOrg
+    if (responseOrg) this['response.organization'] = responseOrg
     this.duration = segment.getDurationInMillis()
 
     if (agent.config.ai_monitoring.record_content.enabled === true) {

lib/llm-events-new/google-genai/chat-message.js

@@ -0,0 +1,66 @@
+/*
+ * Copyright 2026 New Relic Corporation. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ */
+
+const LlmChatCompletionMessage = require('../chat-message')
+const { getUsageTokens } = require('./utils')
+
+/**
+ * Encapsulates a Google Gen AI LlmChatCompletionMessage.
+ */
+class GoogleGenAiLlmChatCompletionMessage extends LlmChatCompletionMessage {
+  constructor({ agent,
+    segment,
+    transaction,
+    request = {},
+    response = {},
+    sequence = 0,
+    content, role,
+    completionId,
+    isResponse }) {
+    super({ agent,
+      segment,
+      transaction,
+      vendor: 'gemini',
+      sequence,
+      content,
+      role,
+      completionId,
+      isResponse,
+      responseModel: response?.modelVersion })
+
+    this.setTokenCount(agent, request, response)
+  }
+
+  setTokenCount(agent, request, response) {
+    const tokenCB = agent.llm?.tokenCountCallback
+
+    if (tokenCB) {
+      const promptContent = typeof request?.contents === 'string'
+        ? request?.contents
+        : request?.contents?.join(' ')
+
+      const responseContent = response?.candidates?.[0]?.content?.parts
+      const completionContent = responseContent?.map((content) => content.text).join(' ')
+
+      if (promptContent && completionContent) {
+        this.setTokenFromCallback(
+          {
+            tokenCB,
+            reqModel: request.model,
+            resModel: this['response.model'],
+            promptContent,
+            completionContent
+          }
+        )
+      }
+      return
+    }
+
+    const tokens = getUsageTokens(response)
+    this.setTokenInCompletionMessage(tokens)
+  }
+}
+
+module.exports = GoogleGenAiLlmChatCompletionMessage

lib/llm-events-new/google-genai/chat-summary.js

@@ -0,0 +1,67 @@
+/*
+ * Copyright 2026 New Relic Corporation. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ */
+
+const LlmChatCompletionSummary = require('../chat-summary')
+const { getUsageTokens } = require('./utils')
+
+/**
+ * Encapsulates a Google Gen AI LlmChatCompletionSummary.
+ */
+class GoogleGenAiLlmChatCompletionSummary extends LlmChatCompletionSummary {
+  constructor({ agent, segment, transaction, request, response, error }) {
+    super({ agent,
+      segment,
+      transaction,
+      responseModel: response?.modelVersion,
+      requestModel: request?.model,
+      finishReason: response?.candidates?.[0]?.finishReason,
+      maxTokens: request.config?.maxOutputTokens,
+      temperature: request.config?.temperature,
+      vendor: 'gemini',
+      error })
+
+    let requestMessagesLength = 0
+    if (Array.isArray(request?.contents)) {
+      requestMessagesLength = request.contents.length
+    } else if (typeof request?.contents === 'string') {
+      requestMessagesLength = 1
+    }
+    this['response.number_of_messages'] = requestMessagesLength + (response?.candidates?.length || 0)
+
+    this.setTokens(agent, request, response)
+  }
+
+  setTokens(agent, request, response) {
+    const tokenCB = agent.llm?.tokenCountCallback
+
+    // Prefer callback for prompt and completion tokens; if unavailable, fall back to response data.
+    if (tokenCB) {
+      const promptContent = typeof request?.contents === 'string'
+        ? request?.contents
+        : request?.contents?.join(' ')
+
+      const responseContent = response?.candidates?.[0]?.content?.parts
+      const completionContent = responseContent?.map((content) => content.text).join(' ')
+
+      if (promptContent && completionContent) {
+        this.setTokenUsageFromCallback(
+          {
+            tokenCB,
+            reqModel: request.model,
+            resModel: this['response.model'],
+            promptContent,
+            completionContent
+          }
+        )
+      }
+      return
+    }
+
+    const tokens = getUsageTokens(response)
+    this.setTokensInResponse(tokens)
+  }
+}
+
+module.exports = GoogleGenAiLlmChatCompletionSummary

lib/llm-events-new/google-genai/embedding.js

@@ -5,13 +5,17 @@
 
 const LlmEmbedding = require('../embedding')
 
+/**
+ * Encapsulates a Google Gen AI LlmEmbedding.
+ */
 class GoogleGenAiLlmEmbedding extends LlmEmbedding {
   constructor({ agent, segment, transaction, request = {}, response = {}, error }) {
     super({ agent,
       segment,
       transaction,
       requestInput: request?.contents,
       requestModel: request?.model,
+      responseModel: response?.modelVersion,
       vendor: 'gemini',
       error })
   }

lib/llm-events-new/google-genai/index.js

@@ -5,12 +5,12 @@
 
 'use strict'
 
-// const LlmChatCompletionMessage = require('./chat-message')
-// const LlmChatCompletionSummary = require('./chat-summary')
+const LlmChatCompletionMessage = require('./chat-message')
+const LlmChatCompletionSummary = require('./chat-summary')
 const LlmEmbedding = require('./embedding')
 
 module.exports = {
-  // LlmChatCompletionMessage,
-  // LlmChatCompletionSummary,
+  LlmChatCompletionMessage,
+  LlmChatCompletionSummary,
   LlmEmbedding
 }

lib/llm-events-new/google-genai/utils.js

@@ -0,0 +1,13 @@
+/*
+ * Copyright 2026 New Relic Corporation. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ */
+
+function getUsageTokens(response) {
+  const promptTokens = Number(response?.usageMetadata?.promptTokenCount)
+  const completionTokens = Number(response?.usageMetadata?.candidatesTokenCount)
+  const totalTokens = Number(response?.usageMetadata?.totalTokenCount)
+  return { promptTokens, completionTokens, totalTokens }
+}
+
+module.exports = { getUsageTokens }

lib/subscribers/google-genai/generate-content.js

@@ -6,7 +6,7 @@
 const { AiMonitoringChatSubscriber } = require('../ai-monitoring')
 const { AI } = require('../../metrics/names')
 const { GEMINI } = AI
-const { LlmChatCompletionSummary, LlmChatCompletionMessage } = require('#agentlib/llm-events/google-genai/index.js')
+const { LlmChatCompletionSummary, LlmChatCompletionMessage } = require('#agentlib/llm-events-new/google-genai/index.js')
 
 class GoogleGenAIGenerateContentSubscriber extends AiMonitoringChatSubscriber {
   constructor({ agent, logger, channelName = 'nr_generateContentInternal' }) {
@@ -27,13 +27,26 @@ class GoogleGenAIGenerateContentSubscriber extends AiMonitoringChatSubscriber {
     })
   }
 
+  /**
+   * Gets the request/input and response messages from the
+   * Google Gen AI request and response objects.
+   * @param {object} params function parameters
+   * @param {object} params.request Google Gen AI request object
+   * @param {object} params.response Google Gen AI response object
+   * @returns {object[]} an array of messages like { content, role }
+   */
   getMessages({ request, response }) {
-    // Only take the first response message and append to input messages
     // request.contents can be a string or an array of strings
-    // response.candidates is an array of candidates (choices); we only take the first one
-    const inputMessages = Array.isArray(request.contents) ? request.contents : [request.contents]
-    const responseMessage = response?.candidates?.[0]?.content
-    return responseMessage !== undefined ? [...inputMessages, responseMessage] : inputMessages
+    const contents = Array.isArray(request.contents) ? request.contents : [request.contents]
+    const messages = contents.map((item) => {
+      return { content: item, role: 'user' }
+    })
+    const responseContent = response?.text ?? response?.candidates?.[0]?.content?.parts?.[0]?.text
+    if (responseContent) {
+      // Do not push an empty response (likely from an error)
+      messages.push({ content: responseContent, role: 'assistant' })
+    }
+    return messages
   }
 
   createCompletionSummary({ ctx, request, response = {}, err }) {
@@ -44,21 +57,26 @@ class GoogleGenAIGenerateContentSubscriber extends AiMonitoringChatSubscriber {
       transaction,
       request,
       response,
-      withError: !!err
+      error: !!err
     })
   }
 
   createCompletionMessage({ ctx, request, response, index, completionId, message }) {
     const { segment, transaction } = ctx
+
+    const isResponse = message?.content === response?.text
+
     return new LlmChatCompletionMessage({
       agent: this.agent,
       segment,
       transaction,
       request,
       response,
-      index,
+      sequence: index,
       completionId,
-      message
+      content: message.content,
+      role: message.role,
+      isResponse
     })
   }
 }