DMleadgen
46d973904b
Next.js website for Rocky Mountain Vending company featuring: - Product catalog with Stripe integration - Service areas and parts pages - Admin dashboard with Clerk authentication - SEO optimized pages with JSON-LD structured data Co-authored-by: Cursor <cursoragent@cursor.com>
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{"version":3,"file":"index.js","sources":["../../../../src/utils/openai/index.ts"],"sourcesContent":["import { getCurrentScope } from '../../currentScopes';\nimport { captureException } from '../../exports';\nimport { startSpan } from '../../tracing/trace';\nimport type { Span, SpanAttributeValue } from '../../types-hoist/span';\nimport {\n GEN_AI_OPERATION_NAME_ATTRIBUTE,\n GEN_AI_REQUEST_FREQUENCY_PENALTY_ATTRIBUTE,\n GEN_AI_REQUEST_MESSAGES_ATTRIBUTE,\n GEN_AI_REQUEST_MODEL_ATTRIBUTE,\n GEN_AI_REQUEST_PRESENCE_PENALTY_ATTRIBUTE,\n GEN_AI_REQUEST_TEMPERATURE_ATTRIBUTE,\n GEN_AI_REQUEST_TOP_P_ATTRIBUTE,\n GEN_AI_RESPONSE_FINISH_REASONS_ATTRIBUTE,\n GEN_AI_RESPONSE_ID_ATTRIBUTE,\n GEN_AI_RESPONSE_MODEL_ATTRIBUTE,\n GEN_AI_RESPONSE_TEXT_ATTRIBUTE,\n GEN_AI_SYSTEM_ATTRIBUTE,\n GEN_AI_USAGE_INPUT_TOKENS_ATTRIBUTE,\n GEN_AI_USAGE_OUTPUT_TOKENS_ATTRIBUTE,\n GEN_AI_USAGE_TOTAL_TOKENS_ATTRIBUTE,\n OPENAI_RESPONSE_ID_ATTRIBUTE,\n OPENAI_RESPONSE_MODEL_ATTRIBUTE,\n OPENAI_RESPONSE_TIMESTAMP_ATTRIBUTE,\n OPENAI_USAGE_COMPLETION_TOKENS_ATTRIBUTE,\n OPENAI_USAGE_PROMPT_TOKENS_ATTRIBUTE,\n} from '../gen-ai-attributes';\nimport { OPENAI_INTEGRATION_NAME } from './constants';\nimport type {\n InstrumentedMethod,\n OpenAiChatCompletionObject,\n OpenAiClient,\n OpenAiIntegration,\n OpenAiOptions,\n OpenAiResponse,\n OpenAIResponseObject,\n} from './types';\nimport {\n buildMethodPath,\n getOperationName,\n getSpanOperation,\n isChatCompletionResponse,\n isResponsesApiResponse,\n shouldInstrument,\n} from './utils';\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 };\n\n if (args.length > 0 && typeof args[0] === 'object' && args[0] !== null) {\n const params = args[0] as Record<string, unknown>;\n\n attributes[GEN_AI_REQUEST_MODEL_ATTRIBUTE] = params.model ?? 'unknown';\n if ('temperature' in params) attributes[GEN_AI_REQUEST_TEMPERATURE_ATTRIBUTE] = params.temperature;\n if ('top_p' in params) attributes[GEN_AI_REQUEST_TOP_P_ATTRIBUTE] = params.top_p;\n if ('frequency_penalty' in params)\n attributes[GEN_AI_REQUEST_FREQUENCY_PENALTY_ATTRIBUTE] = params.frequency_penalty;\n if ('presence_penalty' in params) attributes[GEN_AI_REQUEST_PRESENCE_PENALTY_ATTRIBUTE] = params.presence_penalty;\n } else {\n attributes[GEN_AI_REQUEST_MODEL_ATTRIBUTE] = 'unknown';\n }\n\n return attributes;\n}\n\n/**\n * Helper function to set token usage attributes\n */\nfunction setTokenUsageAttributes(\n span: Span,\n promptTokens?: number,\n completionTokens?: number,\n totalTokens?: number,\n): void {\n if (promptTokens !== undefined) {\n span.setAttributes({\n [OPENAI_USAGE_PROMPT_TOKENS_ATTRIBUTE]: promptTokens,\n [GEN_AI_USAGE_INPUT_TOKENS_ATTRIBUTE]: promptTokens,\n });\n }\n if (completionTokens !== undefined) {\n span.setAttributes({\n [OPENAI_USAGE_COMPLETION_TOKENS_ATTRIBUTE]: completionTokens,\n [GEN_AI_USAGE_OUTPUT_TOKENS_ATTRIBUTE]: completionTokens,\n });\n }\n if (totalTokens !== undefined) {\n span.setAttributes({\n [GEN_AI_USAGE_TOTAL_TOKENS_ATTRIBUTE]: totalTokens,\n });\n }\n}\n\n/**\n * Helper function to set common response attributes (ID, model, timestamp)\n */\nfunction setCommonResponseAttributes(span: Span, id?: string, model?: string, timestamp?: number): void {\n if (id) {\n span.setAttributes({\n [OPENAI_RESPONSE_ID_ATTRIBUTE]: id,\n [GEN_AI_RESPONSE_ID_ATTRIBUTE]: id,\n });\n }\n if (model) {\n span.setAttributes({\n [OPENAI_RESPONSE_MODEL_ATTRIBUTE]: model,\n [GEN_AI_RESPONSE_MODEL_ATTRIBUTE]: model,\n });\n }\n if (timestamp) {\n span.setAttributes({\n [OPENAI_RESPONSE_TIMESTAMP_ATTRIBUTE]: new Date(timestamp * 1000).toISOString(),\n });\n }\n}\n\n/**\n * Add attributes for Chat Completion responses\n */\nfunction addChatCompletionAttributes(span: Span, response: OpenAiChatCompletionObject): void {\n setCommonResponseAttributes(span, response.id, response.model, response.created);\n if (response.usage) {\n setTokenUsageAttributes(\n span,\n response.usage.prompt_tokens,\n response.usage.completion_tokens,\n response.usage.total_tokens,\n );\n }\n if (Array.isArray(response.choices)) {\n const finishReasons = response.choices\n .map(choice => choice.finish_reason)\n .filter((reason): reason is string => reason !== null);\n if (finishReasons.length > 0) {\n span.setAttributes({\n [GEN_AI_RESPONSE_FINISH_REASONS_ATTRIBUTE]: JSON.stringify(finishReasons),\n });\n }\n }\n}\n\n/**\n * Add attributes for Responses API responses\n */\nfunction addResponsesApiAttributes(span: Span, response: OpenAIResponseObject): void {\n setCommonResponseAttributes(span, response.id, response.model, response.created_at);\n if (response.status) {\n span.setAttributes({\n [GEN_AI_RESPONSE_FINISH_REASONS_ATTRIBUTE]: JSON.stringify([response.status]),\n });\n }\n if (response.usage) {\n setTokenUsageAttributes(\n span,\n response.usage.input_tokens,\n response.usage.output_tokens,\n response.usage.total_tokens,\n );\n }\n}\n\n/**\n * Add response attributes to spans\n * This currently supports both Chat Completion and Responses 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);\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);\n if (recordOutputs && response.output_text) {\n span.setAttributes({ [GEN_AI_RESPONSE_TEXT_ATTRIBUTE]: response.output_text });\n }\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>): void {\n if ('messages' in params) {\n span.setAttributes({ [GEN_AI_REQUEST_MESSAGES_ATTRIBUTE]: JSON.stringify(params.messages) });\n }\n if ('input' in params) {\n span.setAttributes({ [GEN_AI_REQUEST_MESSAGES_ATTRIBUTE]: JSON.stringify(params.input) });\n }\n}\n\nfunction getOptionsFromIntegration(): OpenAiOptions {\n const scope = getCurrentScope();\n const client = scope.getClient();\n const integration = client?.getIntegrationByName(OPENAI_INTEGRATION_NAME) as OpenAiIntegration | undefined;\n const shouldRecordInputsAndOutputs = integration ? Boolean(client?.getOptions().sendDefaultPii) : false;\n\n return {\n recordInputs: integration?.options?.recordInputs ?? shouldRecordInputsAndOutputs,\n recordOutputs: integration?.options?.recordOutputs ?? shouldRecordInputsAndOutputs,\n };\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 async function instrumentedMethod(...args: T): Promise<R> {\n const finalOptions = options || getOptionsFromIntegration();\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 return startSpan(\n {\n name: `${operationName} ${model}`,\n op: getSpanOperation(methodPath),\n attributes: requestAttributes as Record<string, SpanAttributeValue>,\n },\n async (span: Span) => {\n try {\n if (finalOptions.recordInputs && args[0] && typeof args[0] === 'object') {\n addRequestAttributes(span, args[0] as Record<string, unknown>);\n }\n\n const result = await originalMethod.apply(context, args);\n // TODO: Add streaming support\n addResponseAttributes(span, result, finalOptions.recordOutputs);\n return result;\n } catch (error) {\n captureException(error);\n throw error;\n }\n },\n );\n };\n}\n\n/**\n * Create a deep proxy for OpenAI client instrumentation\n */\nfunction createDeepProxy(target: object, currentPath = '', options?: OpenAiOptions): OpenAiClient {\n return new Proxy(target, {\n get(obj: object, prop: string): unknown {\n const value = (obj as Record<string, unknown>)[prop];\n const methodPath = buildMethodPath(currentPath, String(prop));\n\n if (typeof value === 'function' && shouldInstrument(methodPath)) {\n return instrumentMethod(value as (...args: unknown[]) => Promise<unknown>, methodPath, obj, options);\n }\n\n if (typeof value === 'function') {\n // Bind non-instrumented functions to preserve the original `this` context,\n // which is required for accessing private class fields (e.g. #baseURL) in OpenAI SDK v5.\n return value.bind(obj);\n }\n\n if (value && typeof value === 'object') {\n return createDeepProxy(value as object, methodPath, options);\n }\n\n return value;\n },\n });\n}\n\n/**\n * Instrument an OpenAI client with Sentry tracing\n * Can be used across Node.js, Cloudflare Workers, and Vercel Edge\n */\nexport function instrumentOpenAiClient(client: OpenAiClient, options?: OpenAiOptions): OpenAiClient {\n return createDeepProxy(client, '', 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