Marc Mintel
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{"version":3,"file":"index.js","sources":["../../../../src/tracing/openai/index.ts"],"sourcesContent":["import { getClient } from '../../currentScopes';\nimport { DEBUG_BUILD } from '../../debug-build';\nimport { captureException } from '../../exports';\nimport { SEMANTIC_ATTRIBUTE_SENTRY_ORIGIN } from '../../semanticAttributes';\nimport { SPAN_STATUS_ERROR } from '../../tracing';\nimport { startSpan, startSpanManual } from '../../tracing/trace';\nimport type { Span, SpanAttributeValue } from '../../types-hoist/span';\nimport { debug } from '../../utils/debug-logger';\nimport { isThenable } from '../../utils/is';\nimport {\n GEN_AI_EMBEDDINGS_INPUT_ATTRIBUTE,\n GEN_AI_INPUT_MESSAGES_ATTRIBUTE,\n GEN_AI_INPUT_MESSAGES_ORIGINAL_LENGTH_ATTRIBUTE,\n GEN_AI_OPERATION_NAME_ATTRIBUTE,\n GEN_AI_REQUEST_AVAILABLE_TOOLS_ATTRIBUTE,\n GEN_AI_REQUEST_MODEL_ATTRIBUTE,\n GEN_AI_RESPONSE_TEXT_ATTRIBUTE,\n GEN_AI_SYSTEM_ATTRIBUTE,\n GEN_AI_SYSTEM_INSTRUCTIONS_ATTRIBUTE,\n OPENAI_OPERATIONS,\n} from '../ai/gen-ai-attributes';\nimport { extractSystemInstructions, getTruncatedJsonString } from '../ai/utils';\nimport { instrumentStream } from './streaming';\nimport type {\n ChatCompletionChunk,\n InstrumentedMethod,\n OpenAiOptions,\n OpenAiResponse,\n OpenAIStream,\n ResponseStreamingEvent,\n} from './types';\nimport {\n addChatCompletionAttributes,\n addConversationAttributes,\n addEmbeddingsAttributes,\n addResponsesApiAttributes,\n buildMethodPath,\n extractRequestParameters,\n getOperationName,\n getSpanOperation,\n isChatCompletionResponse,\n isConversationResponse,\n isEmbeddingsResponse,\n isResponsesApiResponse,\n shouldInstrument,\n} from './utils';\n\n/**\n * Extract available tools from request parameters\n */\nfunction extractAvailableTools(params: Record<string, unknown>): string | undefined {\n const tools = Array.isArray(params.tools) ? params.tools : [];\n const hasWebSearchOptions = params.web_search_options && typeof params.web_search_options === 'object';\n const webSearchOptions = hasWebSearchOptions\n ? [{ type: 'web_search_options', ...(params.web_search_options as Record<string, unknown>) }]\n : [];\n\n const availableTools = [...tools, ...webSearchOptions];\n if (availableTools.length === 0) {\n return undefined;\n }\n\n try {\n return JSON.stringify(availableTools);\n } catch (error) {\n DEBUG_BUILD && debug.error('Failed to serialize OpenAI tools:', error);\n return undefined;\n }\n}\n\n/**\n * Extract request attributes from method arguments\n */\nfunction extractRequestAttributes(args: unknown[], methodPath: string): Record<string, unknown> {\n const attributes: Record<string, unknown> = {\n [GEN_AI_SYSTEM_ATTRIBUTE]: 'openai',\n [GEN_AI_OPERATION_NAME_ATTRIBUTE]: getOperationName(methodPath),\n [SEMANTIC_ATTRIBUTE_SENTRY_ORIGIN]: 'auto.ai.openai',\n };\n\n if (args.length > 0 && typeof args[0] === 'object' && args[0] !== null) {\n const params = args[0] as Record<string, unknown>;\n\n const availableTools = extractAvailableTools(params);\n if (availableTools) {\n attributes[GEN_AI_REQUEST_AVAILABLE_TOOLS_ATTRIBUTE] = availableTools;\n }\n\n Object.assign(attributes, extractRequestParameters(params));\n } else {\n attributes[GEN_AI_REQUEST_MODEL_ATTRIBUTE] = 'unknown';\n }\n\n return attributes;\n}\n\n/**\n * Add response attributes to spans\n * This supports Chat Completion, Responses API, Embeddings, and Conversations API responses\n */\nfunction addResponseAttributes(span: Span, result: unknown, recordOutputs?: boolean): void {\n if (!result || typeof result !== 'object') return;\n\n const response = result as OpenAiResponse;\n\n if (isChatCompletionResponse(response)) {\n addChatCompletionAttributes(span, response, recordOutputs);\n if (recordOutputs && response.choices?.length) {\n const responseTexts = response.choices.map(choice => choice.message?.content || '');\n span.setAttributes({ [GEN_AI_RESPONSE_TEXT_ATTRIBUTE]: JSON.stringify(responseTexts) });\n }\n } else if (isResponsesApiResponse(response)) {\n addResponsesApiAttributes(span, response, recordOutputs);\n if (recordOutputs && response.output_text) {\n span.setAttributes({ [GEN_AI_RESPONSE_TEXT_ATTRIBUTE]: response.output_text });\n }\n } else if (isEmbeddingsResponse(response)) {\n addEmbeddingsAttributes(span, response);\n } else if (isConversationResponse(response)) {\n addConversationAttributes(span, response);\n }\n}\n\n// Extract and record AI request inputs, if present. This is intentionally separate from response attributes.\nfunction addRequestAttributes(span: Span, params: Record<string, unknown>, operationName: string): void {\n // Store embeddings input on a separate attribute and do not truncate it\n if (operationName === OPENAI_OPERATIONS.EMBEDDINGS && 'input' in params) {\n const input = params.input;\n\n // No input provided\n if (input == null) {\n return;\n }\n\n // Empty input string\n if (typeof input === 'string' && input.length === 0) {\n return;\n }\n\n // Empty array input\n if (Array.isArray(input) && input.length === 0) {\n return;\n }\n\n // Store strings as-is, arrays/objects as JSON\n span.setAttribute(GEN_AI_EMBEDDINGS_INPUT_ATTRIBUTE, typeof input === 'string' ? input : JSON.stringify(input));\n return;\n }\n\n const src = 'input' in params ? params.input : 'messages' in params ? params.messages : undefined;\n\n if (!src) {\n return;\n }\n\n if (Array.isArray(src) && src.length === 0) {\n return;\n }\n\n const { systemInstructions, filteredMessages } = extractSystemInstructions(src);\n\n if (systemInstructions) {\n span.setAttribute(GEN_AI_SYSTEM_INSTRUCTIONS_ATTRIBUTE, systemInstructions);\n }\n\n const truncatedInput = getTruncatedJsonString(filteredMessages);\n span.setAttribute(GEN_AI_INPUT_MESSAGES_ATTRIBUTE, truncatedInput);\n\n if (Array.isArray(filteredMessages)) {\n span.setAttribute(GEN_AI_INPUT_MESSAGES_ORIGINAL_LENGTH_ATTRIBUTE, filteredMessages.length);\n } else {\n span.setAttribute(GEN_AI_INPUT_MESSAGES_ORIGINAL_LENGTH_ATTRIBUTE, 1);\n }\n}\n\n/**\n * Creates a wrapped version of .withResponse() that replaces the data field\n * with the instrumented result while preserving metadata (response, request_id).\n */\nasync function createWithResponseWrapper<T>(\n originalWithResponse: Promise<unknown>,\n instrumentedPromise: Promise<T>,\n): Promise<unknown> {\n // Attach catch handler to originalWithResponse immediately to prevent unhandled rejection\n // If instrumentedPromise rejects first, we still need this handled\n const safeOriginalWithResponse = originalWithResponse.catch(error => {\n captureException(error, {\n mechanism: {\n handled: false,\n type: 'auto.ai.openai',\n },\n });\n throw error;\n });\n\n const instrumentedResult = await instrumentedPromise;\n const originalWrapper = await safeOriginalWithResponse;\n\n // Combine instrumented result with original metadata\n if (originalWrapper && typeof originalWrapper === 'object' && 'data' in originalWrapper) {\n return {\n ...originalWrapper,\n data: instrumentedResult,\n };\n }\n return instrumentedResult;\n}\n\n/**\n * Wraps a promise-like object to preserve additional methods (like .withResponse())\n */\nfunction wrapPromiseWithMethods<R>(originalPromiseLike: Promise<R>, instrumentedPromise: Promise<R>): Promise<R> {\n // If the original result is not thenable, return the instrumented promise\n // Should not happen with current OpenAI SDK instrumented methods, but just in case.\n if (!isThenable(originalPromiseLike)) {\n return instrumentedPromise;\n }\n\n // Create a proxy that forwards Promise methods to instrumentedPromise\n // and preserves additional methods from the original result\n return new Proxy(originalPromiseLike, {\n get(target: object, prop: string | symbol): unknown {\n // For standard Promise methods (.then, .catch, .finally, Symbol.toStringTag),\n // use instrumentedPromise to preserve Sentry instrumentation.\n // For custom methods (like .withResponse()), use the original target.\n const useInstrumentedPromise = prop in Promise.prototype || prop === Symbol.toStringTag;\n const source = useInstrumentedPromise ? instrumentedPromise : target;\n\n const value = Reflect.get(source, prop) as unknown;\n\n // Special handling for .withResponse() to preserve instrumentation\n // .withResponse() returns { data: T, response: Response, request_id: string }\n if (prop === 'withResponse' && typeof value === 'function') {\n return function wrappedWithResponse(this: unknown): unknown {\n const originalWithResponse = (value as (...args: unknown[]) => unknown).call(target);\n return createWithResponseWrapper(originalWithResponse, instrumentedPromise);\n };\n }\n\n return typeof value === 'function' ? value.bind(source) : value;\n },\n }) as Promise<R>;\n}\n\n/**\n * Instrument a method with Sentry spans\n * Following Sentry AI Agents Manual Instrumentation conventions\n * @see https://docs.sentry.io/platforms/javascript/guides/node/tracing/instrumentation/ai-agents-module/#manual-instrumentation\n */\nfunction instrumentMethod<T extends unknown[], R>(\n originalMethod: (...args: T) => Promise<R>,\n methodPath: InstrumentedMethod,\n context: unknown,\n options: OpenAiOptions,\n): (...args: T) => Promise<R> {\n return function instrumentedMethod(...args: T): Promise<R> {\n const requestAttributes = extractRequestAttributes(args, methodPath);\n const model = (requestAttributes[GEN_AI_REQUEST_MODEL_ATTRIBUTE] as string) || 'unknown';\n const operationName = getOperationName(methodPath);\n\n const params = args[0] as Record<string, unknown> | undefined;\n const isStreamRequested = params && typeof params === 'object' && params.stream === true;\n\n const spanConfig = {\n name: `${operationName} ${model}${isStreamRequested ? 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