fix(core): Fix and add cache attributes in Vercel AI

Author: RulaKhaled

packages/core/src/utils/ai/gen-ai-attributes.ts

@@ -129,6 +129,16 @@ export const GEN_AI_RESPONSE_STREAMING_ATTRIBUTE = 'gen_ai.response.streaming';
  */
 export const GEN_AI_RESPONSE_TOOL_CALLS_ATTRIBUTE = 'gen_ai.response.tool_calls';
 
+/**
+ * The number of cache write input tokens used
+ */
+export const GEN_AI_USAGE_INPUT_TOKENS_CACHE_WRITE_ATTRIBUTE = 'gen_ai.usage.input_tokens.cache_write';
+
+/**
+ * The number of cached input tokens that were used
+ */
+export const GEN_AI_USAGE_INPUT_TOKENS_CACHED_ATTRIBUTE = 'gen_ai.usage.input_tokens.cached';
+
 // =============================================================================
 // OPENAI-SPECIFIC ATTRIBUTES
 // =============================================================================

packages/core/src/utils/vercel-ai/index.ts

@@ -2,6 +2,10 @@ import type { Client } from '../../client';
 import { SEMANTIC_ATTRIBUTE_SENTRY_OP, SEMANTIC_ATTRIBUTE_SENTRY_ORIGIN } from '../../semanticAttributes';
 import type { Event } from '../../types-hoist/event';
 import type { Span, SpanAttributes, SpanAttributeValue, SpanJSON, SpanOrigin } from '../../types-hoist/span';
+import {
+  GEN_AI_USAGE_INPUT_TOKENS_CACHE_WRITE_ATTRIBUTE,
+  GEN_AI_USAGE_INPUT_TOKENS_CACHED_ATTRIBUTE,
+} from '../ai/gen-ai-attributes';
 import { spanToJSON } from '../spanUtils';
 import { toolCallSpanMap } from './constants';
 import type { TokenSummary } from './types';
@@ -23,6 +27,7 @@ import {
   AI_TOOL_CALL_ID_ATTRIBUTE,
   AI_TOOL_CALL_NAME_ATTRIBUTE,
   AI_TOOL_CALL_RESULT_ATTRIBUTE,
+  AI_USAGE_CACHED_INPUT_TOKENS_ATTRIBUTE,
   AI_USAGE_COMPLETION_TOKENS_ATTRIBUTE,
   AI_USAGE_PROMPT_TOKENS_ATTRIBUTE,
   GEN_AI_RESPONSE_MODEL_ATTRIBUTE,
@@ -107,6 +112,7 @@ function processEndedVercelAiSpan(span: SpanJSON): void {
 
   renameAttributeKey(attributes, AI_USAGE_COMPLETION_TOKENS_ATTRIBUTE, GEN_AI_USAGE_OUTPUT_TOKENS_ATTRIBUTE);
   renameAttributeKey(attributes, AI_USAGE_PROMPT_TOKENS_ATTRIBUTE, GEN_AI_USAGE_INPUT_TOKENS_ATTRIBUTE);
+  renameAttributeKey(attributes, AI_USAGE_CACHED_INPUT_TOKENS_ATTRIBUTE, GEN_AI_USAGE_INPUT_TOKENS_CACHED_ATTRIBUTE);
 
   if (
     typeof attributes[GEN_AI_USAGE_OUTPUT_TOKENS_ATTRIBUTE] === 'number' &&
@@ -287,7 +293,7 @@ function addProviderMetadataToAttributes(attributes: SpanAttributes): void {
       if (providerMetadataObject.openai) {
         setAttributeIfDefined(
           attributes,
-          'gen_ai.usage.input_tokens.cached',
+          GEN_AI_USAGE_INPUT_TOKENS_CACHED_ATTRIBUTE,
           providerMetadataObject.openai.cachedPromptTokens,
         );
         setAttributeIfDefined(
@@ -309,35 +315,34 @@ function addProviderMetadataToAttributes(attributes: SpanAttributes): void {
       }
 
       if (providerMetadataObject.anthropic) {
-        setAttributeIfDefined(
-          attributes,
-          'gen_ai.usage.input_tokens.cached',
-          providerMetadataObject.anthropic.cacheReadInputTokens,
-        );
-        setAttributeIfDefined(
-          attributes,
-          'gen_ai.usage.input_tokens.cache_write',
-          providerMetadataObject.anthropic.cacheCreationInputTokens,
-        );
+        const cachedInputTokens =
+          providerMetadataObject.anthropic.usage?.cache_read_input_tokens ??
+          providerMetadataObject.anthropic.cacheCreationInputTokens;
+        setAttributeIfDefined(attributes, GEN_AI_USAGE_INPUT_TOKENS_CACHED_ATTRIBUTE, cachedInputTokens);
+
+        const cacheWriteInputTokens =
+          providerMetadataObject.anthropic.usage?.cache_creation_input_tokens ??
+          providerMetadataObject.anthropic.cacheCreationInputTokens;
+        setAttributeIfDefined(attributes, GEN_AI_USAGE_INPUT_TOKENS_CACHE_WRITE_ATTRIBUTE, cacheWriteInputTokens);
       }
 
       if (providerMetadataObject.bedrock?.usage) {
         setAttributeIfDefined(
           attributes,
-          'gen_ai.usage.input_tokens.cached',
+          GEN_AI_USAGE_INPUT_TOKENS_CACHED_ATTRIBUTE,
           providerMetadataObject.bedrock.usage.cacheReadInputTokens,
         );
         setAttributeIfDefined(
           attributes,
-          'gen_ai.usage.input_tokens.cache_write',
+          GEN_AI_USAGE_INPUT_TOKENS_CACHE_WRITE_ATTRIBUTE,
           providerMetadataObject.bedrock.usage.cacheWriteInputTokens,
         );
       }
 
       if (providerMetadataObject.deepseek) {
         setAttributeIfDefined(
           attributes,
-          'gen_ai.usage.input_tokens.cached',
+          GEN_AI_USAGE_INPUT_TOKENS_CACHED_ATTRIBUTE,
           providerMetadataObject.deepseek.promptCacheHitTokens,
         );
         setAttributeIfDefined(

packages/core/src/utils/vercel-ai/vercel-ai-attributes.ts

@@ -288,6 +288,14 @@ export const AI_RESPONSE_PROVIDER_METADATA_ATTRIBUTE = 'ai.response.providerMeta
  */
 export const AI_SETTINGS_MAX_RETRIES_ATTRIBUTE = 'ai.settings.maxRetries';
 
+/**
+ * Basic LLM span information
+ * Multiple spans
+ *
+ * The number of cached input tokens that were used
+ * @see https://ai-sdk.dev/docs/ai-sdk-core/telemetry#basic-llm-span-information
+ */
+export const AI_USAGE_CACHED_INPUT_TOKENS_ATTRIBUTE = 'ai.usage.cachedInputTokens';
 /**
  * Basic LLM span information
  * Multiple spans
@@ -863,6 +871,21 @@ interface AnthropicProviderMetadata {
    * @see https://ai-sdk.dev/providers/ai-sdk-providers/anthropic#cache-control
    */
   cacheReadInputTokens?: number;
+
+  /**
+   * Usage metrics for the Anthropic model.
+   */
+  usage?: {
+    input_tokens: number;
+    cache_creation_input_tokens?: number;
+    cache_read_input_tokens?: number;
+    cache_creation?: {
+      ephemeral_5m_input_tokens?: number;
+      ephemeral_1h_input_tokens?: number;
+    };
+    output_tokens?: number;
+    service_tier?: string;
+  };
 }
 
 /**