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@sentry/core

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import { getClient } from '../../currentScopes.js'; import { captureException } from '../../exports.js'; import { SEMANTIC_ATTRIBUTE_SENTRY_ORIGIN } from '../../semanticAttributes.js'; import { SPAN_STATUS_ERROR } from '../spanstatus.js'; import { startSpanManual, startSpan } from '../trace.js'; import { GEN_AI_OPERATION_NAME_ATTRIBUTE, GEN_AI_REQUEST_AVAILABLE_TOOLS_ATTRIBUTE, GEN_AI_REQUEST_MODEL_ATTRIBUTE, GEN_AI_REQUEST_TEMPERATURE_ATTRIBUTE, GEN_AI_REQUEST_TOP_P_ATTRIBUTE, GEN_AI_REQUEST_FREQUENCY_PENALTY_ATTRIBUTE, GEN_AI_REQUEST_PRESENCE_PENALTY_ATTRIBUTE, GEN_AI_REQUEST_STREAM_ATTRIBUTE, GEN_AI_REQUEST_ENCODING_FORMAT_ATTRIBUTE, GEN_AI_REQUEST_DIMENSIONS_ATTRIBUTE, GEN_AI_REQUEST_MESSAGES_ATTRIBUTE, GEN_AI_RESPONSE_TEXT_ATTRIBUTE, GEN_AI_SYSTEM_ATTRIBUTE } from '../ai/gen-ai-attributes.js'; import { getTruncatedJsonString } from '../ai/utils.js'; import { instrumentStream } from './streaming.js'; import { shouldInstrument, getOperationName, getSpanOperation, isChatCompletionResponse, addChatCompletionAttributes, isResponsesApiResponse, addResponsesApiAttributes, isEmbeddingsResponse, addEmbeddingsAttributes, buildMethodPath } from './utils.js'; /** * Extract request attributes from method arguments */ function extractRequestAttributes(args, methodPath) { const attributes = { [GEN_AI_SYSTEM_ATTRIBUTE]: 'openai', [GEN_AI_OPERATION_NAME_ATTRIBUTE]: getOperationName(methodPath), [SEMANTIC_ATTRIBUTE_SENTRY_ORIGIN]: 'auto.ai.openai', }; // Chat completion API accepts web_search_options and tools as parameters // we append web search options to the available tools to capture all tool calls if (args.length > 0 && typeof args[0] === 'object' && args[0] !== null) { const params = args[0] ; const tools = Array.isArray(params.tools) ? params.tools : []; const hasWebSearchOptions = params.web_search_options && typeof params.web_search_options === 'object'; const webSearchOptions = hasWebSearchOptions ? [{ type: 'web_search_options', ...(params.web_search_options ) }] : []; const availableTools = [...tools, ...webSearchOptions]; if (availableTools.length > 0) { attributes[GEN_AI_REQUEST_AVAILABLE_TOOLS_ATTRIBUTE] = JSON.stringify(availableTools); } } if (args.length > 0 && typeof args[0] === 'object' && args[0] !== null) { const params = args[0] ; attributes[GEN_AI_REQUEST_MODEL_ATTRIBUTE] = params.model ?? 'unknown'; if ('temperature' in params) attributes[GEN_AI_REQUEST_TEMPERATURE_ATTRIBUTE] = params.temperature; if ('top_p' in params) attributes[GEN_AI_REQUEST_TOP_P_ATTRIBUTE] = params.top_p; if ('frequency_penalty' in params) attributes[GEN_AI_REQUEST_FREQUENCY_PENALTY_ATTRIBUTE] = params.frequency_penalty; if ('presence_penalty' in params) attributes[GEN_AI_REQUEST_PRESENCE_PENALTY_ATTRIBUTE] = params.presence_penalty; if ('stream' in params) attributes[GEN_AI_REQUEST_STREAM_ATTRIBUTE] = params.stream; if ('encoding_format' in params) attributes[GEN_AI_REQUEST_ENCODING_FORMAT_ATTRIBUTE] = params.encoding_format; if ('dimensions' in params) attributes[GEN_AI_REQUEST_DIMENSIONS_ATTRIBUTE] = params.dimensions; } else { attributes[GEN_AI_REQUEST_MODEL_ATTRIBUTE] = 'unknown'; } return attributes; } /** * Add response attributes to spans * This currently supports both Chat Completion and Responses API responses */ function addResponseAttributes(span, result, recordOutputs) { if (!result || typeof result !== 'object') return; const response = result ; if (isChatCompletionResponse(response)) { addChatCompletionAttributes(span, response, recordOutputs); if (recordOutputs && response.choices?.length) { const responseTexts = response.choices.map(choice => choice.message?.content || ''); span.setAttributes({ [GEN_AI_RESPONSE_TEXT_ATTRIBUTE]: JSON.stringify(responseTexts) }); } } else if (isResponsesApiResponse(response)) { addResponsesApiAttributes(span, response, recordOutputs); if (recordOutputs && response.output_text) { span.setAttributes({ [GEN_AI_RESPONSE_TEXT_ATTRIBUTE]: response.output_text }); } } else if (isEmbeddingsResponse(response)) { addEmbeddingsAttributes(span, response); } } // Extract and record AI request inputs, if present. This is intentionally separate from response attributes. function addRequestAttributes(span, params) { if ('messages' in params) { const truncatedMessages = getTruncatedJsonString(params.messages); span.setAttributes({ [GEN_AI_REQUEST_MESSAGES_ATTRIBUTE]: truncatedMessages }); } if ('input' in params) { const truncatedInput = getTruncatedJsonString(params.input); span.setAttributes({ [GEN_AI_REQUEST_MESSAGES_ATTRIBUTE]: truncatedInput }); } } /** * Instrument a method with Sentry spans * Following Sentry AI Agents Manual Instrumentation conventions * @see https://docs.sentry.io/platforms/javascript/guides/node/tracing/instrumentation/ai-agents-module/#manual-instrumentation */ function instrumentMethod( originalMethod, methodPath, context, options, ) { return async function instrumentedMethod(...args) { const requestAttributes = extractRequestAttributes(args, methodPath); const model = (requestAttributes[GEN_AI_REQUEST_MODEL_ATTRIBUTE] ) || 'unknown'; const operationName = getOperationName(methodPath); const params = args[0] ; const isStreamRequested = params && typeof params === 'object' && params.stream === true; if (isStreamRequested) { // For streaming responses, use manual span management to properly handle the async generator lifecycle return startSpanManual( { name: `${operationName} ${model} stream-response`, op: getSpanOperation(methodPath), attributes: requestAttributes , }, async (span) => { try { if (options.recordInputs && params) { addRequestAttributes(span, params); } const result = await originalMethod.apply(context, args); return instrumentStream( result , span, options.recordOutputs ?? false, ) ; } catch (error) { // For streaming requests that fail before stream creation, we still want to record // them as streaming requests but end the span gracefully span.setStatus({ code: SPAN_STATUS_ERROR, message: 'internal_error' }); captureException(error, { mechanism: { handled: false, type: 'auto.ai.openai.stream', data: { function: methodPath, }, }, }); span.end(); throw error; } }, ); } else { // Non-streaming responses return startSpan( { name: `${operationName} ${model}`, op: getSpanOperation(methodPath), attributes: requestAttributes , }, async (span) => { try { if (options.recordInputs && params) { addRequestAttributes(span, params); } const result = await originalMethod.apply(context, args); addResponseAttributes(span, result, options.recordOutputs); return result; } catch (error) { captureException(error, { mechanism: { handled: false, type: 'auto.ai.openai', data: { function: methodPath, }, }, }); throw error; } }, ); } }; } /** * Create a deep proxy for OpenAI client instrumentation */ function createDeepProxy(target, currentPath = '', options) { return new Proxy(target, { get(obj, prop) { const value = (obj )[prop]; const methodPath = buildMethodPath(currentPath, String(prop)); if (typeof value === 'function' && shouldInstrument(methodPath)) { return instrumentMethod(value , methodPath, obj, options); } if (typeof value === 'function') { // Bind non-instrumented functions to preserve the original `this` context, // which is required for accessing private class fields (e.g. #baseURL) in OpenAI SDK v5. return value.bind(obj); } if (value && typeof value === 'object') { return createDeepProxy(value, methodPath, options); } return value; }, }) ; } /** * Instrument an OpenAI client with Sentry tracing * Can be used across Node.js, Cloudflare Workers, and Vercel Edge */ function instrumentOpenAiClient(client, options) { const sendDefaultPii = Boolean(getClient()?.getOptions().sendDefaultPii); const _options = { recordInputs: sendDefaultPii, recordOutputs: sendDefaultPii, ...options, }; return createDeepProxy(client, '', _options); } export { instrumentOpenAiClient }; //# sourceMappingURL=index.js.map