simplify

Author: nicohrubec

dev-packages/browser-integration-tests/suites/tracing/ai-providers/google-genai/mocks.js

@@ -53,15 +53,8 @@ export class MockGoogleGenAI {
           embeddings: [
             {
               values: [0.1, 0.2, 0.3, 0.4, 0.5],
-              statistics: {
-                tokenCount: 8,
-                truncated: false,
-              },
             },
           ],
-          metadata: {
-            billableCharacterCount: 30,
-          },
         };
       },
       generateContentStream: async () => {

dev-packages/node-integration-tests/suites/tracing/google-genai/scenario-embeddings.mjs

@@ -20,10 +20,6 @@ function startMockGoogleGenAIServer() {
           values: [0.1, 0.2, 0.3, 0.4, 0.5],
         },
       ],
-      usageMetadata: {
-        promptTokenCount: 8,
-        totalTokenCount: 8,
-      },
     });
   });
 

dev-packages/node-integration-tests/suites/tracing/google-genai/test.ts

@@ -614,8 +614,6 @@ describe('Google GenAI integration', () => {
           [SEMANTIC_ATTRIBUTE_SENTRY_ORIGIN]: 'auto.ai.google_genai',
           [GEN_AI_SYSTEM_ATTRIBUTE]: 'google_genai',
           [GEN_AI_REQUEST_MODEL_ATTRIBUTE]: 'text-embedding-004',
-          [GEN_AI_USAGE_INPUT_TOKENS_ATTRIBUTE]: 8,
-          [GEN_AI_USAGE_TOTAL_TOKENS_ATTRIBUTE]: 8,
         },
         description: 'embeddings text-embedding-004',
         op: 'gen_ai.embeddings',
@@ -644,8 +642,6 @@ describe('Google GenAI integration', () => {
           [SEMANTIC_ATTRIBUTE_SENTRY_ORIGIN]: 'auto.ai.google_genai',
           [GEN_AI_SYSTEM_ATTRIBUTE]: 'google_genai',
           [GEN_AI_REQUEST_MODEL_ATTRIBUTE]: 'text-embedding-004',
-          [GEN_AI_USAGE_INPUT_TOKENS_ATTRIBUTE]: 8,
-          [GEN_AI_USAGE_TOTAL_TOKENS_ATTRIBUTE]: 8,
         },
         description: 'embeddings text-embedding-004',
         op: 'gen_ai.embeddings',
@@ -667,8 +663,6 @@ describe('Google GenAI integration', () => {
           [GEN_AI_SYSTEM_ATTRIBUTE]: 'google_genai',
           [GEN_AI_REQUEST_MODEL_ATTRIBUTE]: 'text-embedding-004',
           [GEN_AI_EMBEDDINGS_INPUT_ATTRIBUTE]: 'What is the capital of France?',
-          [GEN_AI_USAGE_INPUT_TOKENS_ATTRIBUTE]: 8,
-          [GEN_AI_USAGE_TOTAL_TOKENS_ATTRIBUTE]: 8,
         },
         description: 'embeddings text-embedding-004',
         op: 'gen_ai.embeddings',
@@ -699,8 +693,6 @@ describe('Google GenAI integration', () => {
           [GEN_AI_SYSTEM_ATTRIBUTE]: 'google_genai',
           [GEN_AI_REQUEST_MODEL_ATTRIBUTE]: 'text-embedding-004',
           [GEN_AI_EMBEDDINGS_INPUT_ATTRIBUTE]: expect.any(String),
-          [GEN_AI_USAGE_INPUT_TOKENS_ATTRIBUTE]: 8,
-          [GEN_AI_USAGE_TOTAL_TOKENS_ATTRIBUTE]: 8,
         },
         description: 'embeddings text-embedding-004',
         op: 'gen_ai.embeddings',

packages/core/src/tracing/google-genai/embeddings.ts

@@ -1,10 +1,5 @@
-import {
-  GEN_AI_EMBEDDINGS_INPUT_ATTRIBUTE,
-  GEN_AI_USAGE_INPUT_TOKENS_ATTRIBUTE,
-  GEN_AI_USAGE_TOTAL_TOKENS_ATTRIBUTE,
-} from '../ai/gen-ai-attributes';
+import { GEN_AI_EMBEDDINGS_INPUT_ATTRIBUTE } from '../ai/gen-ai-attributes';
 import type { Span } from '../../types-hoist/span';
-import type { GoogleGenAIEmbedContentResponse } from './types';
 
 /**
  * Add private request attributes for embeddings methods.
@@ -35,43 +30,3 @@ export function addEmbeddingsRequestAttributes(span: Span, params: Record<string
     typeof contents === 'string' ? contents : JSON.stringify(contents),
   );
 }
-
-/**
- * Add response attributes from the Google GenAI embedContent response.
- * Token counts come from usageMetadata (Gemini API) or embeddings[].statistics.tokenCount (Vertex AI).
- * @see https://ai.google.dev/api/embeddings#EmbedContentResponse
- */
-export function addEmbedContentResponseAttributes(span: Span, response: unknown): void {
-  if (!response || typeof response !== 'object') return;
-
-  const embedResponse = response as GoogleGenAIEmbedContentResponse;
-
-  // Try usageMetadata first (same shape as GenerateContentResponse)
-  if (embedResponse.usageMetadata && typeof embedResponse.usageMetadata === 'object') {
-    const usage = embedResponse.usageMetadata;
-    if (typeof usage.promptTokenCount === 'number') {
-      span.setAttribute(GEN_AI_USAGE_INPUT_TOKENS_ATTRIBUTE, usage.promptTokenCount);
-    }
-    if (typeof usage.totalTokenCount === 'number') {
-      span.setAttribute(GEN_AI_USAGE_TOTAL_TOKENS_ATTRIBUTE, usage.totalTokenCount);
-    }
-    return;
-  }
-
-  // Fallback: sum token counts from individual embedding statistics (Vertex AI)
-  if (Array.isArray(embedResponse.embeddings)) {
-    let totalTokenCount = 0;
-    for (const embedding of embedResponse.embeddings) {
-      if (embedding.statistics && typeof embedding.statistics.tokenCount === 'number') {
-        totalTokenCount += embedding.statistics.tokenCount;
-      }
-    }
-
-    if (totalTokenCount > 0) {
-      span.setAttributes({
-        [GEN_AI_USAGE_INPUT_TOKENS_ATTRIBUTE]: totalTokenCount,
-        [GEN_AI_USAGE_TOTAL_TOKENS_ATTRIBUTE]: totalTokenCount,
-      });
-    }
-  }
-}

packages/core/src/tracing/google-genai/index.ts

@@ -29,7 +29,7 @@ import {
 import { truncateGenAiMessages } from '../ai/messageTruncation';
 import { buildMethodPath, extractSystemInstructions, getFinalOperationName, getSpanOperation } from '../ai/utils';
 import { CHAT_PATH, CHATS_CREATE_METHOD, GOOGLE_GENAI_SYSTEM_NAME } from './constants';
-import { addEmbedContentResponseAttributes, addEmbeddingsRequestAttributes } from './embeddings';
+import { addEmbeddingsRequestAttributes } from './embeddings';
 import { instrumentStream } from './streaming';
 import type {
   Candidate,
@@ -324,12 +324,9 @@ function instrumentMethod<T extends unknown[], R>(
             () => {},
             result => {
               // Only add response attributes for content-producing methods, not for chats.create
-              if (!isSyncCreate) {
-                if (isEmbeddings) {
-                  addEmbedContentResponseAttributes(span, result);
-                } else {
-                  addResponseAttributes(span, result, options.recordOutputs);
-                }
+              // Note: embeddings responses don't include usage metadata or model version
+              if (!isSyncCreate && !isEmbeddings) {
+                addResponseAttributes(span, result, options.recordOutputs);
               }
             },
           );

packages/core/src/tracing/google-genai/types.ts

@@ -181,43 +181,5 @@ export interface GoogleGenAIChat {
 
 export type GoogleGenAIIstrumentedMethod = (typeof GOOGLE_GENAI_INSTRUMENTED_METHODS)[number];
 
-/**
- * Google GenAI Content Embedding
- * @see https://googleapis.github.io/js-genai/release_docs/classes/types.ContentEmbedding.html
- */
-type ContentEmbeddingType = {
-  /** The embedding values. */
-  values?: number[];
-  /** Statistics about the embedding. */
-  statistics?: {
-    /** The number of tokens in the content. */
-    tokenCount?: number;
-    /** Whether the content was truncated. */
-    truncated?: boolean;
-  };
-};
-
-/**
- * Google GenAI Embed Content Response
- * @see https://ai.google.dev/api/embeddings#EmbedContentResponse
- */
-export type GoogleGenAIEmbedContentResponse = {
-  [key: string]: unknown;
-  /** The generated embeddings. */
-  embeddings?: ContentEmbeddingType[];
-  /** Metadata about the embeddings. */
-  metadata?: {
-    /** Billable character count. */
-    billableCharacterCount?: number;
-  };
-  /** Usage metadata (same shape as GenerateContentResponse). */
-  usageMetadata?: {
-    /** Number of tokens in the request. */
-    promptTokenCount?: number;
-    /** Total token count. */
-    totalTokenCount?: number;
-  };
-};
-
 // Export the response type for use in instrumentation
 export type GoogleGenAIResponse = GenerateContentResponse;