Marc Mintel
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{"version":3,"file":"streaming.js","sources":["../../../../src/tracing/openai/streaming.ts"],"sourcesContent":["import { captureException } from '../../exports';\nimport { SPAN_STATUS_ERROR } from '../../tracing';\nimport type { Span } from '../../types-hoist/span';\nimport {\n GEN_AI_RESPONSE_FINISH_REASONS_ATTRIBUTE,\n GEN_AI_RESPONSE_STREAMING_ATTRIBUTE,\n GEN_AI_RESPONSE_TEXT_ATTRIBUTE,\n GEN_AI_RESPONSE_TOOL_CALLS_ATTRIBUTE,\n} from '../ai/gen-ai-attributes';\nimport { RESPONSE_EVENT_TYPES } from './constants';\nimport type {\n ChatCompletionChunk,\n ChatCompletionToolCall,\n OpenAIResponseObject,\n ResponseFunctionCall,\n ResponseStreamingEvent,\n} from './types';\nimport {\n isChatCompletionChunk,\n isResponsesApiStreamEvent,\n setCommonResponseAttributes,\n setTokenUsageAttributes,\n} from './utils';\n\n/**\n * State object used to accumulate information from a stream of OpenAI events/chunks.\n */\ninterface StreamingState {\n /** Types of events encountered in the stream. */\n eventTypes: string[];\n /** Collected response text fragments (for output recording). */\n responseTexts: string[];\n /** Reasons for finishing the response, as reported by the API. */\n finishReasons: string[];\n /** The response ID. */\n responseId: string;\n /** The model name. */\n responseModel: string;\n /** The timestamp of the response. */\n responseTimestamp: number;\n /** Number of prompt/input tokens used. */\n promptTokens: number | undefined;\n /** Number of completion/output tokens used. */\n completionTokens: number | undefined;\n /** Total number of tokens used (prompt + completion). */\n totalTokens: number | undefined;\n /**\n * Accumulated tool calls from Chat Completion streaming, indexed by tool call index.\n * @see https://platform.openai.com/docs/guides/function-calling?api-mode=chat#streaming\n */\n chatCompletionToolCalls: Record<number, ChatCompletionToolCall>;\n /**\n * Accumulated function calls from Responses API streaming.\n * @see https://platform.openai.com/docs/guides/function-calling?api-mode=responses#streaming\n */\n responsesApiToolCalls: Array<ResponseFunctionCall | unknown>;\n}\n\n/**\n * Processes tool calls from a chat completion chunk delta.\n * Follows the pattern: accumulate by index, then convert to array at the end.\n *\n * @param toolCalls - Array of tool calls from the delta.\n * @param state - The current streaming state to update.\n *\n * @see https://platform.openai.com/docs/guides/function-calling#streaming\n */\nfunction processChatCompletionToolCalls(toolCalls: ChatCompletionToolCall[], state: StreamingState): void {\n for (const toolCall of toolCalls) {\n const index = toolCall.index;\n if (index === undefined || !toolCall.function) continue;\n\n // Initialize tool call if this is the first chunk for this index\n if (!(index in state.chatCompletionToolCalls)) {\n state.chatCompletionToolCalls[index] = {\n ...toolCall,\n function: {\n name: toolCall.function.name,\n arguments: toolCall.function.arguments || '',\n },\n };\n } else {\n // Accumulate function arguments from subsequent chunks\n const existingToolCall = state.chatCompletionToolCalls[index];\n if (toolCall.function.arguments && existingToolCall?.function) {\n existingToolCall.function.arguments += toolCall.function.arguments;\n }\n }\n }\n}\n\n/**\n * Processes a single OpenAI ChatCompletionChunk event, updating the streaming state.\n *\n * @param chunk - The ChatCompletionChunk event to process.\n * @param state - The current streaming state to update.\n * @param recordOutputs - Whether to record output text fragments.\n */\nfunction processChatCompletionChunk(chunk: ChatCompletionChunk, state: StreamingState, recordOutputs: boolean): void {\n state.responseId = chunk.id ?? state.responseId;\n state.responseModel = chunk.model ?? state.responseModel;\n state.responseTimestamp = chunk.created ?? state.responseTimestamp;\n\n if (chunk.usage) {\n // For stream responses, the input tokens remain constant across all events in the stream.\n // Output tokens, however, are only finalized in the last event.\n // Since we can't guarantee that the last event will include usage data or even be a typed event,\n // we update the output token values on every event that includes them.\n // This ensures that output token usage is always set, even if the final event lacks it.\n state.promptTokens = chunk.usage.prompt_tokens;\n state.completionTokens = chunk.usage.completion_tokens;\n state.totalTokens = chunk.usage.total_tokens;\n }\n\n for (const choice of chunk.choices ?? []) {\n if (recordOutputs) {\n if (choice.delta?.content) {\n state.responseTexts.push(choice.delta.content);\n }\n\n // Handle tool calls from delta\n if (choice.delta?.tool_calls) {\n processChatCompletionToolCalls(choice.delta.tool_calls, state);\n }\n }\n if (choice.finish_reason) {\n state.finishReasons.push(choice.finish_reason);\n }\n }\n}\n\n/**\n * Processes a single OpenAI Responses API streaming event, updating the streaming state and span.\n *\n * @param streamEvent - The event to process (may be an error or unknown object).\n * @param state - The current streaming state to update.\n * @param recordOutputs - Whether to record output text fragments.\n * @param span - The span to update with error status if needed.\n */\nfunction processResponsesApiEvent(\n streamEvent: ResponseStreamingEvent | unknown | Error,\n state: StreamingState,\n recordOutputs: boolean,\n span: Span,\n): void {\n if (!(streamEvent && typeof streamEvent === 'object')) {\n state.eventTypes.push('unknown:non-object');\n return;\n }\n if (streamEvent instanceof Error) {\n span.setStatus({ code: SPAN_STATUS_ERROR, message: 'internal_error' });\n captureException(streamEvent, {\n mechanism: {\n handled: false,\n type: 'auto.ai.openai.stream-response',\n },\n });\n return;\n }\n\n if (!('type' in streamEvent)) return;\n const event = streamEvent as ResponseStreamingEvent;\n\n if (!RESPONSE_EVENT_TYPES.includes(event.type)) {\n state.eventTypes.push(event.type);\n return;\n }\n\n // Handle output text delta\n if (recordOutputs) {\n // Handle tool call events for Responses API\n if (event.type === 'response.output_item.done' && 'item' in event) {\n state.responsesApiToolCalls.push(event.item);\n }\n\n if (event.type === 'response.output_text.delta' && 'delta' in event && event.delta) {\n state.responseTexts.push(event.delta);\n return;\n }\n }\n\n if ('response' in event) {\n const { response } = event as { response: OpenAIResponseObject };\n state.responseId = response.id ?? state.responseId;\n state.responseModel = response.model ?? state.responseModel;\n state.responseTimestamp = response.created_at ?? state.responseTimestamp;\n\n if (response.usage) {\n // For stream responses, the input tokens remain constant across all events in the stream.\n // Output tokens, however, are only finalized in the last event.\n // Since we can't guarantee that the last event will include usage data or even be a typed event,\n // we update the output token values on every event that includes them.\n // This ensures that output token usage is always set, even if the final event lacks it.\n state.promptTokens = response.usage.input_tokens;\n state.completionTokens = response.usage.output_tokens;\n state.totalTokens = response.usage.total_tokens;\n }\n\n if (response.status) {\n state.finishReasons.push(response.status);\n }\n\n if (recordOutputs && response.output_text) {\n state.responseTexts.push(response.output_text);\n }\n }\n}\n\n/**\n * Instruments a stream of OpenAI events, updating the provided span with relevant attributes and\n * optionally recording output text. This function yields each event from the input stream as it is processed.\n *\n * @template T - The type of events in the stream.\n * @param stream - The async iterable stream of events to instrument.\n * @param span - The span to add attributes to and to finish at the end of the stream.\n * @param recordOutputs - Whether to record output text fragments in the span.\n * @returns An async generator yielding each event from the input stream.\n */\nexport async function* instrumentStream<T>(\n stream: AsyncIterable<T>,\n span: Span,\n recordOutputs: boolean,\n): AsyncGenerator<T, void, unknown> {\n const state: StreamingState = {\n eventTypes: [],\n responseTexts: [],\n finishReasons: [],\n responseId: '',\n responseModel: '',\n responseTimestamp: 0,\n promptTokens: undefined,\n completionTokens: undefined,\n totalTokens: undefined,\n chatCompletionToolCalls: {},\n responsesApiToolCalls: [],\n };\n\n try {\n for await (const event of stream) {\n if (isChatCompletionChunk(event)) {\n processChatCompletionChunk(event as ChatCompletionChunk, state, recordOutputs);\n } else if (isResponsesApiStreamEvent(event)) {\n processResponsesApiEvent(event as ResponseStreamingEvent, state, recordOutputs, span);\n }\n yield event;\n }\n } finally {\n setCommonResponseAttributes(span, state.responseId, state.responseModel, state.responseTimestamp);\n setTokenUsageAttributes(span, state.promptTokens, state.completionTokens, state.totalTokens);\n\n span.setAttributes({\n [GEN_AI_RESPONSE_STREAMING_ATTRIBUTE]: true,\n });\n\n if (state.finishReasons.length) {\n span.setAttributes({\n [GEN_AI_RESPONSE_FINISH_REASONS_ATTRIBUTE]: JSON.stringify(state.finishReasons),\n });\n }\n\n if (recordOutputs && state.responseTexts.length) {\n span.setAttributes({\n [GEN_AI_RESPONSE_TEXT_ATTRIBUTE]: state.responseTexts.join(''),\n });\n }\n\n // Set tool calls attribute if any were accumulated\n const chatCompletionToolCallsArray = Object.values(state.chatCompletionToolCalls);\n const allToolCalls = [...chatCompletionToolCallsArray, ...state.responsesApiToolCalls];\n\n if (allToolCalls.length > 0) {\n span.setAttributes({\n [GEN_AI_RESPONSE_TOOL_CALLS_ATTRIBUTE]: JSON.stringify(allToolCalls),\n });\n }\n\n span.end();\n 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