Files
OmniRoute/open-sse/handlers/usageExtractor.ts
Diego Rodrigues de Sa e Souza 5cf9a33d85 feat(usage): surface Claude thinking token counts to clients (#9214)
Validated in local merge-train (devbox-vm-06-dev002) @ combined-tip (FAST gates — only pre-existing audit.test.ts flake).
2026-08-05 22:40:19 -03:00

109 lines
4.5 KiB
TypeScript

/**
* Extract usage from non-streaming response body
* Handles different provider response formats
*/
export function extractUsageFromResponse(responseBody, provider) {
if (!responseBody || typeof responseBody !== "object") return null;
const providerId = typeof provider === "string" ? provider.toLowerCase() : "";
const isClaudeProvider =
providerId === "claude" ||
providerId === "anthropic" ||
providerId.startsWith("anthropic-compatible");
// OpenAI format (has prompt_tokens / completion_tokens)
if (
responseBody.usage &&
typeof responseBody.usage === "object" &&
responseBody.usage.prompt_tokens !== undefined
) {
return {
prompt_tokens: responseBody.usage.prompt_tokens || 0,
completion_tokens: responseBody.usage.completion_tokens || 0,
// DeepSeek native API uses flat prompt_cache_hit_tokens (NOT
// prompt_tokens_details.cached_tokens). Fall back to it so V4 cache
// gets surfaced into kanban call_logs alongside the OpenAI/Claude paths.
cached_tokens:
responseBody.usage.prompt_tokens_details?.cached_tokens ??
responseBody.usage.input_tokens_details?.cached_tokens ??
responseBody.usage.prompt_cache_hit_tokens ??
responseBody.usage.cached_tokens,
reasoning_tokens:
responseBody.usage.completion_tokens_details?.reasoning_tokens ??
responseBody.usage.output_tokens_details?.reasoning_tokens ??
responseBody.usage.reasoning_tokens,
// xAI's exact provider-reported cost (port of decolua/9router#2453, capability A —
// @ryanngit). Only set the key when present so non-xAI OpenAI-shaped usage
// (Codex, DeepSeek, etc.) is unaffected. Ticks → USD conversion happens in
// costCalculator.ts, not here.
...(typeof responseBody.usage.cost_in_usd_ticks === "number" &&
Number.isFinite(responseBody.usage.cost_in_usd_ticks) &&
responseBody.usage.cost_in_usd_ticks >= 0
? { cost_in_usd_ticks: responseBody.usage.cost_in_usd_ticks }
: {}),
};
}
// Claude format
if (
isClaudeProvider &&
responseBody.usage &&
typeof responseBody.usage === "object" &&
(responseBody.usage.input_tokens !== undefined ||
responseBody.usage.output_tokens !== undefined)
) {
const inputTokens = responseBody.usage.input_tokens || 0;
const cacheRead = responseBody.usage.cache_read_input_tokens || 0;
const cacheCreation = responseBody.usage.cache_creation_input_tokens || 0;
// Total prompt tokens = input + cache_read + cache_creation (per Claude API docs)
const promptTokens = inputTokens + cacheRead + cacheCreation;
return {
prompt_tokens: promptTokens,
completion_tokens: responseBody.usage.output_tokens || 0,
cache_read_input_tokens: cacheRead,
cache_creation_input_tokens: cacheCreation,
...(typeof responseBody.usage.output_tokens_details?.thinking_tokens === "number"
? { reasoning_tokens: responseBody.usage.output_tokens_details.thinking_tokens }
: {}),
};
}
// OpenAI Responses API format (input_tokens / output_tokens)
const responsesUsage = responseBody.response?.usage || responseBody.usage;
if (
responsesUsage &&
typeof responsesUsage === "object" &&
(responsesUsage.input_tokens !== undefined || responsesUsage.output_tokens !== undefined)
) {
return {
prompt_tokens: responsesUsage.input_tokens || 0,
completion_tokens: responsesUsage.output_tokens || 0,
cache_read_input_tokens: responsesUsage.cache_read_input_tokens,
cached_tokens:
responsesUsage.input_tokens_details?.cached_tokens ??
responsesUsage.prompt_tokens_details?.cached_tokens ??
responsesUsage.cache_read_input_tokens,
cache_creation_input_tokens: responsesUsage.cache_creation_input_tokens,
reasoning_tokens:
responsesUsage.output_tokens_details?.reasoning_tokens ??
responsesUsage.completion_tokens_details?.reasoning_tokens ??
responsesUsage.reasoning_tokens,
};
}
// Gemini format
if (responseBody.usageMetadata && typeof responseBody.usageMetadata === "object") {
// Gemini reports thoughts outside candidates. Fold them into completion so
// every provider keeps reasoning as a subset of completion tokens.
const thoughts = responseBody.usageMetadata.thoughtsTokenCount || 0;
return {
prompt_tokens: responseBody.usageMetadata.promptTokenCount || 0,
completion_tokens: (responseBody.usageMetadata.candidatesTokenCount || 0) + thoughts,
reasoning_tokens: thoughts,
};
}
return null;
}