Marc Mintel
5397309103
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336 lines
11 KiB
Plaintext
336 lines
11 KiB
Plaintext
import { OPENAI_OPERATIONS, 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_CONVERSATION_ID_ATTRIBUTE, GEN_AI_RESPONSE_ID_ATTRIBUTE, OPENAI_RESPONSE_ID_ATTRIBUTE, GEN_AI_RESPONSE_MODEL_ATTRIBUTE, OPENAI_RESPONSE_MODEL_ATTRIBUTE, OPENAI_RESPONSE_TIMESTAMP_ATTRIBUTE, GEN_AI_RESPONSE_FINISH_REASONS_ATTRIBUTE, GEN_AI_RESPONSE_TOOL_CALLS_ATTRIBUTE, GEN_AI_USAGE_INPUT_TOKENS_ATTRIBUTE, OPENAI_USAGE_PROMPT_TOKENS_ATTRIBUTE, GEN_AI_USAGE_OUTPUT_TOKENS_ATTRIBUTE, OPENAI_USAGE_COMPLETION_TOKENS_ATTRIBUTE, GEN_AI_USAGE_TOTAL_TOKENS_ATTRIBUTE } from '../ai/gen-ai-attributes.js';
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import { INSTRUMENTED_METHODS } from './constants.js';
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/**
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* Maps OpenAI method paths to OpenTelemetry semantic convention operation names
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* @see https://opentelemetry.io/docs/specs/semconv/gen-ai/gen-ai-spans/#llm-request-spans
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*/
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function getOperationName(methodPath) {
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if (methodPath.includes('chat.completions')) {
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return OPENAI_OPERATIONS.CHAT;
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}
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if (methodPath.includes('responses')) {
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return OPENAI_OPERATIONS.CHAT;
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}
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if (methodPath.includes('embeddings')) {
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return OPENAI_OPERATIONS.EMBEDDINGS;
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}
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if (methodPath.includes('conversations')) {
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return OPENAI_OPERATIONS.CHAT;
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}
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return methodPath.split('.').pop() || 'unknown';
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}
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/**
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* Get the span operation for OpenAI methods
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* Following Sentry's convention: "gen_ai.{operation_name}"
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*/
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function getSpanOperation(methodPath) {
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return `gen_ai.${getOperationName(methodPath)}`;
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}
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/**
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* Check if a method path should be instrumented
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*/
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function shouldInstrument(methodPath) {
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return INSTRUMENTED_METHODS.includes(methodPath );
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}
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/**
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* Build method path from current traversal
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*/
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function buildMethodPath(currentPath, prop) {
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return currentPath ? `${currentPath}.${prop}` : prop;
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}
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/**
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* Check if response is a Chat Completion object
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*/
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function isChatCompletionResponse(response) {
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return (
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response !== null &&
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typeof response === 'object' &&
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'object' in response &&
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(response ).object === 'chat.completion'
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);
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}
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/**
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* Check if response is a Responses API object
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*/
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function isResponsesApiResponse(response) {
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return (
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response !== null &&
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typeof response === 'object' &&
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'object' in response &&
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(response ).object === 'response'
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);
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}
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/**
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* Check if response is an Embeddings API object
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*/
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function isEmbeddingsResponse(response) {
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if (response === null || typeof response !== 'object' || !('object' in response)) {
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return false;
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}
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const responseObject = response ;
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return (
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responseObject.object === 'list' &&
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typeof responseObject.model === 'string' &&
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responseObject.model.toLowerCase().includes('embedding')
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);
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}
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/**
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* Check if response is a Conversations API object
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* @see https://platform.openai.com/docs/api-reference/conversations
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*/
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function isConversationResponse(response) {
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return (
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response !== null &&
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typeof response === 'object' &&
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'object' in response &&
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(response ).object === 'conversation'
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);
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}
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/**
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* Check if streaming event is from the Responses API
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*/
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function isResponsesApiStreamEvent(event) {
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return (
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event !== null &&
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typeof event === 'object' &&
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'type' in event &&
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typeof (event ).type === 'string' &&
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((event ).type ).startsWith('response.')
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);
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}
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/**
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* Check if streaming event is a chat completion chunk
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*/
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function isChatCompletionChunk(event) {
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return (
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event !== null &&
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typeof event === 'object' &&
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'object' in event &&
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(event ).object === 'chat.completion.chunk'
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);
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}
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/**
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* Add attributes for Chat Completion responses
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*/
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function addChatCompletionAttributes(
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span,
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response,
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recordOutputs,
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) {
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setCommonResponseAttributes(span, response.id, response.model, response.created);
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if (response.usage) {
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setTokenUsageAttributes(
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span,
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response.usage.prompt_tokens,
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response.usage.completion_tokens,
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response.usage.total_tokens,
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);
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}
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if (Array.isArray(response.choices)) {
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const finishReasons = response.choices
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.map(choice => choice.finish_reason)
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.filter((reason) => reason !== null);
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if (finishReasons.length > 0) {
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span.setAttributes({
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[GEN_AI_RESPONSE_FINISH_REASONS_ATTRIBUTE]: JSON.stringify(finishReasons),
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});
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}
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// Extract tool calls from all choices (only if recordOutputs is true)
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if (recordOutputs) {
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const toolCalls = response.choices
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.map(choice => choice.message?.tool_calls)
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.filter(calls => Array.isArray(calls) && calls.length > 0)
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.flat();
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if (toolCalls.length > 0) {
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span.setAttributes({
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[GEN_AI_RESPONSE_TOOL_CALLS_ATTRIBUTE]: JSON.stringify(toolCalls),
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});
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}
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}
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}
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}
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/**
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* Add attributes for Responses API responses
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*/
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function addResponsesApiAttributes(span, response, recordOutputs) {
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setCommonResponseAttributes(span, response.id, response.model, response.created_at);
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if (response.status) {
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span.setAttributes({
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[GEN_AI_RESPONSE_FINISH_REASONS_ATTRIBUTE]: JSON.stringify([response.status]),
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});
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}
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if (response.usage) {
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setTokenUsageAttributes(
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span,
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response.usage.input_tokens,
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response.usage.output_tokens,
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response.usage.total_tokens,
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);
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}
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// Extract function calls from output (only if recordOutputs is true)
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if (recordOutputs) {
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const responseWithOutput = response ;
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if (Array.isArray(responseWithOutput.output) && responseWithOutput.output.length > 0) {
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// Filter for function_call type objects in the output array
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const functionCalls = responseWithOutput.output.filter(
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(item) =>
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typeof item === 'object' && item !== null && (item ).type === 'function_call',
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);
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if (functionCalls.length > 0) {
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span.setAttributes({
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[GEN_AI_RESPONSE_TOOL_CALLS_ATTRIBUTE]: JSON.stringify(functionCalls),
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});
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}
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}
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}
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}
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/**
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* Add attributes for Embeddings API responses
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*/
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function addEmbeddingsAttributes(span, response) {
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span.setAttributes({
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[OPENAI_RESPONSE_MODEL_ATTRIBUTE]: response.model,
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[GEN_AI_RESPONSE_MODEL_ATTRIBUTE]: response.model,
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});
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if (response.usage) {
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setTokenUsageAttributes(span, response.usage.prompt_tokens, undefined, response.usage.total_tokens);
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}
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}
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/**
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* Add attributes for Conversations API responses
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* @see https://platform.openai.com/docs/api-reference/conversations
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*/
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function addConversationAttributes(span, response) {
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const { id, created_at } = response;
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span.setAttributes({
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[OPENAI_RESPONSE_ID_ATTRIBUTE]: id,
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[GEN_AI_RESPONSE_ID_ATTRIBUTE]: id,
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// The conversation id is used to link messages across API calls
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[GEN_AI_CONVERSATION_ID_ATTRIBUTE]: id,
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});
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if (created_at) {
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span.setAttributes({
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[OPENAI_RESPONSE_TIMESTAMP_ATTRIBUTE]: new Date(created_at * 1000).toISOString(),
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});
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}
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}
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/**
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* Set token usage attributes
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* @param span - The span to add attributes to
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* @param promptTokens - The number of prompt tokens
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* @param completionTokens - The number of completion tokens
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* @param totalTokens - The number of total tokens
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*/
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function setTokenUsageAttributes(
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span,
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promptTokens,
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completionTokens,
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totalTokens,
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) {
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if (promptTokens !== undefined) {
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span.setAttributes({
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[OPENAI_USAGE_PROMPT_TOKENS_ATTRIBUTE]: promptTokens,
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[GEN_AI_USAGE_INPUT_TOKENS_ATTRIBUTE]: promptTokens,
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});
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}
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if (completionTokens !== undefined) {
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span.setAttributes({
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[OPENAI_USAGE_COMPLETION_TOKENS_ATTRIBUTE]: completionTokens,
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[GEN_AI_USAGE_OUTPUT_TOKENS_ATTRIBUTE]: completionTokens,
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});
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}
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if (totalTokens !== undefined) {
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span.setAttributes({
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[GEN_AI_USAGE_TOTAL_TOKENS_ATTRIBUTE]: totalTokens,
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});
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}
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}
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/**
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* Set common response attributes
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* @param span - The span to add attributes to
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* @param id - The response id
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* @param model - The response model
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* @param timestamp - The response timestamp
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*/
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function setCommonResponseAttributes(span, id, model, timestamp) {
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span.setAttributes({
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[OPENAI_RESPONSE_ID_ATTRIBUTE]: id,
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[GEN_AI_RESPONSE_ID_ATTRIBUTE]: id,
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});
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span.setAttributes({
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[OPENAI_RESPONSE_MODEL_ATTRIBUTE]: model,
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[GEN_AI_RESPONSE_MODEL_ATTRIBUTE]: model,
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});
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span.setAttributes({
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[OPENAI_RESPONSE_TIMESTAMP_ATTRIBUTE]: new Date(timestamp * 1000).toISOString(),
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});
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}
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/**
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* Extract conversation ID from request parameters
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* Supports both Conversations API and previous_response_id chaining
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* @see https://platform.openai.com/docs/guides/conversation-state
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*/
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function extractConversationId(params) {
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// Conversations API: conversation parameter (e.g., "conv_...")
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if ('conversation' in params && typeof params.conversation === 'string') {
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return params.conversation;
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}
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// Responses chaining: previous_response_id links to parent response
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if ('previous_response_id' in params && typeof params.previous_response_id === 'string') {
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return params.previous_response_id;
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}
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return undefined;
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}
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/**
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* Extract request parameters including model settings and conversation context
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*/
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function extractRequestParameters(params) {
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const attributes = {
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[GEN_AI_REQUEST_MODEL_ATTRIBUTE]: params.model ?? 'unknown',
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};
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if ('temperature' in params) attributes[GEN_AI_REQUEST_TEMPERATURE_ATTRIBUTE] = params.temperature;
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if ('top_p' in params) attributes[GEN_AI_REQUEST_TOP_P_ATTRIBUTE] = params.top_p;
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if ('frequency_penalty' in params) attributes[GEN_AI_REQUEST_FREQUENCY_PENALTY_ATTRIBUTE] = params.frequency_penalty;
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if ('presence_penalty' in params) attributes[GEN_AI_REQUEST_PRESENCE_PENALTY_ATTRIBUTE] = params.presence_penalty;
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if ('stream' in params) attributes[GEN_AI_REQUEST_STREAM_ATTRIBUTE] = params.stream;
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if ('encoding_format' in params) attributes[GEN_AI_REQUEST_ENCODING_FORMAT_ATTRIBUTE] = params.encoding_format;
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if ('dimensions' in params) attributes[GEN_AI_REQUEST_DIMENSIONS_ATTRIBUTE] = params.dimensions;
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// Capture conversation ID for linking messages across API calls
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const conversationId = extractConversationId(params);
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if (conversationId) {
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attributes[GEN_AI_CONVERSATION_ID_ATTRIBUTE] = conversationId;
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}
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return attributes;
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}
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export { addChatCompletionAttributes, addConversationAttributes, addEmbeddingsAttributes, addResponsesApiAttributes, buildMethodPath, extractRequestParameters, getOperationName, getSpanOperation, isChatCompletionChunk, isChatCompletionResponse, isConversationResponse, isEmbeddingsResponse, isResponsesApiResponse, isResponsesApiStreamEvent, setCommonResponseAttributes, setTokenUsageAttributes, shouldInstrument };
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//# sourceMappingURL=utils.js.map
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