refactor: Google Gen AI LLM event refactor

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

@@ -1,42 +1,36 @@
 /*
- * Copyright 2025 New Relic Corporation. All rights reserved.
+ * Copyright 2026 New Relic Corporation. All rights reserved.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 'use strict'
-const LlmEvent = require('./event')
-const { makeId } = require('../../util/hashes')
 
-module.exports = class LlmChatCompletionMessage extends LlmEvent {
-  constructor({
-    agent,
+const LlmChatCompletionMessage = require('../chat-completion-message')
+const getUsageTokens = require('./get-usage-tokens')
+
+/**
+ * Encapsulates a Google Gen AI LlmChatCompletionMessage.
+ */
+module.exports = class GoogleGenAiLlmChatCompletionMessage extends LlmChatCompletionMessage {
+  constructor({ agent,
     segment,
+    transaction,
     request = {},
     response = {},
-    index = 0,
-    message,
+    sequence = 0,
+    content, role,
     completionId,
-    transaction
-  }) {
-    super({ agent, segment, request, response, transaction })
-    this.id = makeId(36)
-    // message?.role is only defined if the message is
-    // a response and it is always 'model'.
-    // request messages do not have a role
-    this.role = message?.role ?? 'user'
-    this.sequence = index
-    this.completion_id = completionId
-    const responseText = response?.text ?? response?.candidates?.[0]?.content?.parts?.[0]?.text
-    this.is_response = responseText === message?.parts?.[0]?.text
-
-    if (agent.config.ai_monitoring.record_content.enabled === true) {
-      this.content = this.is_response ? message?.parts?.[0]?.text : message
-    }
-
-    // only add timestamp for request/input messages
-    if (this.is_response === false) {
-      this.timestamp = segment.timer.start
-    }
+    isResponse }) {
+    super({ agent,
+      segment,
+      transaction,
+      vendor: 'gemini',
+      sequence,
+      content,
+      role,
+      completionId,
+      isResponse,
+      responseModel: response?.modelVersion })
 
     this.setTokenCount(agent, request, response)
   }
@@ -66,7 +60,7 @@ module.exports = class LlmChatCompletionMessage extends LlmEvent {
       return
     }
 
-    const tokens = this.getUsageTokens(response)
+    const tokens = getUsageTokens(response)
     this.setTokenInCompletionMessage(tokens)
   }
 }

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

@@ -1,27 +1,47 @@
 /*
- * Copyright 2025 New Relic Corporation. All rights reserved.
+ * Copyright 2026 New Relic Corporation. All rights reserved.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 'use strict'
-const LlmEvent = require('./event')
 
-module.exports = class LlmChatCompletionSummary extends LlmEvent {
-  constructor({ agent, segment, request = {}, response = {}, withError = false, transaction }) {
-    super({ agent, segment, request, response, responseAttrs: true, transaction })
-    this.error = withError
+const LlmChatCompletionSummary = require('../chat-completion-summary')
+const getUsageTokens = require('./get-usage-tokens')
+
+/**
+ * Encapsulates a Google Gen AI LlmChatCompletionSummary.
+ */
+module.exports = class GoogleGenAiLlmChatCompletionSummary extends LlmChatCompletionSummary {
+  /**
+   *
+   * @param {object} params Constructor parameters
+   * @param {Agent} params.agent New Relic agent instance
+   * @param {TraceSegment} params.segment Current segment
+   * @param {Transaction} params.transaction Current and active transaction
+   * @param {object} params.request Google Gen AI request object
+   * @param {object} params.response Google Gen AI response object
+   * @param {boolean} [params.error] Set to `true` if an error occurred
+   */
+  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['response.choices.finish_reason'] = response?.candidates?.[0]?.finishReason
-    this['request.max_tokens'] = request.config?.maxOutputTokens
-    this['request.temperature'] = request.config?.temperature
 
-    this.timestamp = segment.timer.start
     this.setTokens(agent, request, response)
   }
 
@@ -51,7 +71,7 @@ module.exports = class LlmChatCompletionSummary extends LlmEvent {
       return
     }
 
-    const tokens = this.getUsageTokens(response)
+    const tokens = getUsageTokens(response)
     this.setTokensInResponse(tokens)
   }
 }

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

@@ -1,21 +1,34 @@
 /*
- * Copyright 2025 New Relic Corporation. All rights reserved.
+ * Copyright 2026 New Relic Corporation. All rights reserved.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 'use strict'
 
-const LlmEvent = require('./event')
+const LlmEmbedding = require('../embedding')
 
-class LlmEmbedding extends LlmEvent {
-  constructor({ agent, segment, request = {}, response = {}, withError = false, transaction }) {
-    super({ agent, segment, request, response, responseAttrs: true, transaction })
-    this.error = withError
-
-    if (agent.config.ai_monitoring.record_content.enabled === true) {
-      this.input = request.contents?.toString()
-    }
+/**
+ * Encapsulates a Google Gen AI LlmEmbedding.
+ */
+module.exports = class GoogleGenAiLlmEmbedding extends LlmEmbedding {
+  /**
+   *
+   * @param {object} params Constructor params
+   * @param {Agent} params.agent New Relic agent instance
+   * @param {TraceSegment} params.segment Current segment
+   * @param {Transaction} params.transaction Current and active transaction
+   * @param {object} params.request Google Gen AI request object
+   * @param {object} params.response Google Gen AI response object
+   * @param {boolean} [params.error] Set to true if an error occurred
+   */
+  constructor({ agent, segment, transaction, request = {}, response = {}, error }) {
+    super({ agent,
+      segment,
+      transaction,
+      requestInput: request?.contents,
+      requestModel: request?.model,
+      responseModel: response?.modelVersion,
+      vendor: 'gemini',
+      error })
   }
 }
-
-module.exports = LlmEmbedding

lib/llm-events/google-genai/get-usage-tokens.js

@@ -0,0 +1,26 @@
+/*
+ * Copyright 2026 New Relic Corporation. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ */
+
+'use strict'
+
+module.exports = getUsageTokens
+
+/**
+ * Grabs the prompt, completion, and total token count from the
+ * given response object.
+ * @param {object} response Google Gen AI response object
+ * @returns {object} { promptTokens, completionTokens, totalTokens }
+ */
+function getUsageTokens(response) {
+  const { usageMetadata } = response
+  if (!usageMetadata) {
+    return { promptTokens: 0, completionTokens: 0, totalTokens: 0 }
+  }
+  return {
+    promptTokens: Number(usageMetadata.promptTokenCount),
+    completionTokens: Number(usageMetadata.candidatesTokenCount),
+    totalTokens: Number(usageMetadata.totalTokenCount)
+  }
+}

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

@@ -1,18 +1,10 @@
 /*
- * Copyright 2025 New Relic Corporation. All rights reserved.
+ * Copyright 2026 New Relic Corporation. All rights reserved.
  * SPDX-License-Identifier: Apache-2.0
  */
 
-'use strict'
-
-const LlmChatCompletionSummary = require('./chat-completion-summary')
-const LlmChatCompletionMessage = require('./chat-completion-message')
-const LlmEmbedding = require('./embedding')
-const LlmErrorMessage = require('../error-message')
-
 module.exports = {
-  LlmChatCompletionMessage,
-  LlmChatCompletionSummary,
-  LlmEmbedding,
-  LlmErrorMessage
+  LlmChatCompletionMessage: require('./chat-completion-message'),
+  LlmChatCompletionSummary: require('./chat-completion-summary'),
+  LlmEmbedding: require('./embedding')
 }

lib/subscribers/ai-monitoring/embedding.js

@@ -30,7 +30,7 @@ class AiMonitoringEmbeddingSubscriber extends AiMonitoringSubscriber {
    * @param {Context} params.ctx active context
    * @param {object} params.request request made to method on a given llm library
    * @param {object} params.response response from method on a given llm library
-   * @param {object} params.err error if present
+   * @param {object} params.err error object if present
    * returns {object} a llm embedding instance for the given LLM
    */
   createEmbedding({ ctx, request, response, err }) {

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

@@ -14,6 +14,16 @@ class GoogleGenAIEmbedContentSubscriber extends AiMonitoringEmbeddingSubscriber
     this.events = ['asyncEnd']
   }
 
+  /**
+   * Creates a Google Gen AI LlmEmbedding instance.
+   *
+   * @param {object} params to function
+   * @param {Context} params.ctx active context
+   * @param {object} params.request request made to method on a given llm library
+   * @param {object} params.response response from method on a given llm library
+   * @param {object} params.err error object if present
+   * @returns {LlmEmbedding} a llm embedding instance for Google Gen AI
+   */
   createEmbedding({ ctx, request, response = {}, err }) {
     const { segment, transaction } = ctx
     return new LlmEmbedding({
@@ -22,7 +32,7 @@ class GoogleGenAIEmbedContentSubscriber extends AiMonitoringEmbeddingSubscriber
       transaction,
       request,
       response,
-      withError: !!err
+      error: !!err
     })
   }
 

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

@@ -27,15 +27,38 @@ class GoogleGenAIGenerateContentSubscriber extends AiMonitoringChatSubscriber {
     })
   }
 
-  getMessages({ request, response }) {
-    // Only take the first response message and append to input messages
+  /**
+   * 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 = {} }) {
     // 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
   }
 
+  /**
+   * Creates a Google Gen AI LlmChatCompletionSummary instance.
+   *
+   * @param {object} params to function
+   * @param {Context} params.ctx active context
+   * @param {object} params.request request made to method
+   * @param {object} params.response response from method
+   * @param {object} [params.err] error object if present
+   * @returns {object} a llm completion summary instance for Google Gen AI
+   */
   createCompletionSummary({ ctx, request, response = {}, err }) {
     const { transaction, segment } = ctx
     return new LlmChatCompletionSummary({
@@ -44,21 +67,26 @@ 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
     })
   }
 }