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* Provider-specific usage recording helpers.
*
* Each helper knows how to extract cost-relevant metrics from a specific
* provider's response shape. Call sites use a one-liner instead of manually
* constructing the full record.
*/
import type { AiFeatureValue } from './features'
import { recordAiUsage } from './record'
/** Context required for every usage record */
export interface UsageContext {
userId: string
feature: AiFeatureValue
backgroundTaskId?: string
}
// ---------------------------------------------------------------------------
// OpenAI Chat Completions API
// Response shape: { usage: { prompt_tokens, completion_tokens, total_tokens } }
// ---------------------------------------------------------------------------
export function recordOpenAiChatUsage(
response: {
usage?: { prompt_tokens?: number; completion_tokens?: number; total_tokens?: number }
model?: string
},
context: UsageContext
): void {
recordAiUsage({
...context,
provider: 'openai',
model: response.model ?? 'unknown',
apiType: 'chat_completions',
inputTokens: response.usage?.prompt_tokens ?? null,
outputTokens: response.usage?.completion_tokens ?? null,
})
}
// ---------------------------------------------------------------------------
// OpenAI Responses API (non-streaming)
// Response shape: { usage: { input_tokens, output_tokens }, model }
// ---------------------------------------------------------------------------
export function recordOpenAiResponsesUsage(
response: {
usage?: {
input_tokens?: number
output_tokens?: number
// reasoning is nested inside output_tokens_details in the raw API
}
model?: string
},
context: UsageContext
): void {
recordAiUsage({
...context,
provider: 'openai',
model: response.model ?? 'unknown',
apiType: 'responses',
inputTokens: response.usage?.input_tokens ?? null,
outputTokens: response.usage?.output_tokens ?? null,
})
}
// ---------------------------------------------------------------------------
// OpenAI Responses API (streaming SSE)
// Called with extracted usage from the response.completed event
// ---------------------------------------------------------------------------
export function recordOpenAiResponsesStreamUsage(
usage: { input_tokens?: number; output_tokens?: number; reasoning_tokens?: number },
model: string,
context: UsageContext
): void {
recordAiUsage({
...context,
provider: 'openai',
model,
apiType: 'responses_streaming',
inputTokens: usage.input_tokens ?? null,
outputTokens: usage.output_tokens ?? null,
reasoningTokens: usage.reasoning_tokens ?? null,
})
}
// ---------------------------------------------------------------------------
// @soroban/llm-client call() response
// Response shape: { usage: { promptTokens, completionTokens, totalTokens }, provider, model }
// ---------------------------------------------------------------------------
export function recordLlmClientUsage(
response: {
usage: { promptTokens: number; completionTokens: number; totalTokens?: number }
provider: string
model: string
},
context: UsageContext
): void {
recordAiUsage({
...context,
provider: response.provider,
model: response.model,
apiType: 'responses',
inputTokens: response.usage.promptTokens,
outputTokens: response.usage.completionTokens,
})
}
// ---------------------------------------------------------------------------
// @soroban/llm-client stream() complete event
// Event shape: { usage: { promptTokens, completionTokens, reasoningTokens? } }
// ---------------------------------------------------------------------------
export function recordLlmClientStreamUsage(
usage: { promptTokens: number; completionTokens: number; reasoningTokens?: number },
provider: string,
model: string,
context: UsageContext
): void {
recordAiUsage({
...context,
provider,
model,
apiType: 'responses_streaming',
inputTokens: usage.promptTokens,
outputTokens: usage.completionTokens,
reasoningTokens: usage.reasoningTokens ?? null,
})
}
// ---------------------------------------------------------------------------
// @soroban/llm-client embed() response
// Response shape: { usage: { promptTokens, totalTokens }, model }
// ---------------------------------------------------------------------------
export function recordEmbeddingUsage(
response: { usage: { promptTokens: number; totalTokens: number }; model: string },
context: UsageContext
): void {
recordAiUsage({
...context,
provider: 'openai',
model: response.model,
apiType: 'embedding',
inputTokens: response.usage.promptTokens,
outputTokens: response.usage.totalTokens - response.usage.promptTokens,
})
}
// ---------------------------------------------------------------------------
// Image generation (OpenAI gpt-image-1, Gemini)
// ---------------------------------------------------------------------------
export function recordImageGenUsage(
provider: 'openai' | 'gemini',
model: string,
context: UsageContext,
metadata?: Record<string, unknown>
): void {
recordAiUsage({
...context,
provider,
model,
apiType: 'image',
imageCount: 1,
metadata: metadata ?? null,
})
}
// ---------------------------------------------------------------------------
// TTS (OpenAI gpt-4o-mini-tts)
// ---------------------------------------------------------------------------
export function recordTtsUsage(text: string, model: string, context: UsageContext): void {
recordAiUsage({
...context,
provider: 'openai',
model,
apiType: 'tts',
inputCharacters: text.length,
})
}
// ---------------------------------------------------------------------------
// Realtime voice session heartbeat (interim client-reported metrics)
// ---------------------------------------------------------------------------
export function recordRealtimeHeartbeat(
report: {
durationSeconds: number
turnCount: number
modelCharacters: number
userCharacters: number
toolCallCount: number
endReason?: 'user' | 'timeout' | 'network' | 'error'
final?: boolean
},
model: string,
context: UsageContext
): void {
recordAiUsage({
...context,
provider: 'openai',
model,
apiType: 'realtime',
audioDurationSeconds: report.durationSeconds,
inputCharacters: report.userCharacters,
outputTokens: report.modelCharacters,
metadata: {
turnCount: report.turnCount,
toolCallCount: report.toolCallCount,
endReason: report.endReason ?? null,
final: report.final ?? false,
},
})
}
// ---------------------------------------------------------------------------
// ElevenLabs music generation
// ---------------------------------------------------------------------------
export function recordElevenLabsUsage(
compositionPlan: { sections: Array<{ duration_ms: number }> },
context: UsageContext
): void {
const totalDurationMs = compositionPlan.sections.reduce((sum, s) => sum + s.duration_ms, 0)
recordAiUsage({
...context,
provider: 'elevenlabs',
model: 'music_v1',
apiType: 'music',
audioDurationSeconds: totalDurationMs / 1000,
})
}
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