From 8273aa0c98dfdb0e6fef91c414787c7e8794efab Mon Sep 17 00:00:00 2001 From: Yuan Date: Mon, 12 Oct 2026 13:34:01 +0800 Subject: [PATCH] fix: fix token usage accounting in OpenAI and Anthropic conversions --- src/converter/anthropic2gemini.py | 43 +++++++++++++++++-------------- src/converter/openai2gemini.py | 15 ++++++----- 2 files changed, 32 insertions(+), 26 deletions(-) diff --git a/src/converter/anthropic2gemini.py b/src/converter/anthropic2gemini.py index 5c537b11c..936d445a5 100644 --- a/src/converter/anthropic2gemini.py +++ b/src/converter/anthropic2gemini.py @@ -196,26 +196,27 @@ def _anthropic_debug_enabled() -> bool: return str(os.getenv("ANTHROPIC_DEBUG", "true")).strip().lower() in _DEBUG_TRUE -def _cached_content_token_count(usage_metadata: Any) -> int: - if not isinstance(usage_metadata, dict): - return 0 - return int(usage_metadata.get("cachedContentTokenCount", 0) or 0) - - -def _anthropic_usage_from_metadata(usage_metadata: Any) -> Dict[str, int]: +def _anthropic_usage_from_metadata(usage_metadata: Any) -> Dict[str, Any]: if not isinstance(usage_metadata, dict): return {"input_tokens": 0, "output_tokens": 0} prompt_tokens_total = int(usage_metadata.get("promptTokenCount", 0) or 0) - cached_tokens = _cached_content_token_count(usage_metadata) - usage = { + cached_tokens = int(usage_metadata.get("cachedContentTokenCount", 0) or 0) + reasoning_tokens = int(usage_metadata.get("thoughtsTokenCount", 0) or 0) + usage: Dict[str, Any] = { "input_tokens": max(prompt_tokens_total - cached_tokens, 0), - "output_tokens": int(usage_metadata.get("candidatesTokenCount", 0) or 0), + "output_tokens": ( + int(usage_metadata.get("candidatesTokenCount", 0) or 0) + + reasoning_tokens + ), } if cached_tokens > 0: usage["cache_read_input_tokens"] = cached_tokens + if reasoning_tokens > 0: + usage["output_tokens_details"] = {"thinking_tokens": reasoning_tokens} + return usage @@ -954,6 +955,9 @@ async def gemini_stream_to_anthropic_stream( has_tool_use = False input_tokens = 0 output_tokens = 0 + prompt_tokens_total = 0 + candidates_tokens = 0 + reasoning_tokens = 0 cached_input_tokens = 0 finish_reason: Optional[str] = None @@ -974,10 +978,12 @@ def _close_block() -> Optional[bytes]: current_block_type = None return event - def _usage_payload() -> Dict[str, int]: - usage = {"input_tokens": input_tokens, "output_tokens": output_tokens} + def _usage_payload(include_output_details: bool = False) -> Dict[str, Any]: + usage: Dict[str, Any] = {"input_tokens": input_tokens, "output_tokens": output_tokens} if cached_input_tokens > 0: usage["cache_read_input_tokens"] = cached_input_tokens + if include_output_details and reasoning_tokens > 0: + usage["output_tokens_details"] = {"thinking_tokens": reasoning_tokens} return usage # 处理流式数据 @@ -1028,15 +1034,14 @@ def _usage_payload() -> Dict[str, int]: if isinstance(usage, dict): if "promptTokenCount" in usage: prompt_tokens_total = int(usage.get("promptTokenCount", 0) or 0) - input_tokens = max(prompt_tokens_total - cached_input_tokens, 0) if "candidatesTokenCount" in usage: - output_tokens = int(usage.get("candidatesTokenCount", 0) or 0) + candidates_tokens = int(usage.get("candidatesTokenCount", 0) or 0) + if "thoughtsTokenCount" in usage: + reasoning_tokens = int(usage.get("thoughtsTokenCount", 0) or 0) if "cachedContentTokenCount" in usage: cached_input_tokens = int(usage.get("cachedContentTokenCount", 0) or 0) - input_tokens = max( - int(usage.get("promptTokenCount", 0) or 0) - cached_input_tokens, - 0, - ) + input_tokens = max(prompt_tokens_total - cached_input_tokens, 0) + output_tokens = candidates_tokens + reasoning_tokens # 发送 message_start（仅一次） if not message_start_sent: @@ -1256,7 +1261,7 @@ def _usage_payload() -> Dict[str, int]: { "type": "message_delta", "delta": {"stop_reason": stop_reason, "stop_sequence": None}, - "usage": _usage_payload(), + "usage": _usage_payload(include_output_details=True), }, ) diff --git a/src/converter/openai2gemini.py b/src/converter/openai2gemini.py index 99acabc7f..0c84bc806 100644 --- a/src/converter/openai2gemini.py +++ b/src/converter/openai2gemini.py @@ -55,14 +55,16 @@ def _convert_usage_metadata(usage_metadata: Dict[str, Any]) -> Optional[Dict[str if not usage_metadata: return None - prompt_tokens_total = int(usage_metadata.get("promptTokenCount", 0) or 0) + prompt_tokens = int(usage_metadata.get("promptTokenCount", 0) or 0) cached_tokens = int(usage_metadata.get("cachedContentTokenCount", 0) or 0) - prompt_tokens = max(prompt_tokens_total - cached_tokens, 0) - completion_tokens = int(usage_metadata.get("candidatesTokenCount", 0) or 0) - raw_total_tokens = int( + reasoning_tokens = int(usage_metadata.get("thoughtsTokenCount", 0) or 0) + completion_tokens = ( + int(usage_metadata.get("candidatesTokenCount", 0) or 0) + reasoning_tokens + ) + total_tokens = int( usage_metadata.get( "totalTokenCount", - prompt_tokens_total + completion_tokens + int(usage_metadata.get("thoughtsTokenCount", 0) or 0), + prompt_tokens + completion_tokens, ) or 0 ) @@ -70,13 +72,12 @@ def _convert_usage_metadata(usage_metadata: Dict[str, Any]) -> Optional[Dict[str usage = { "prompt_tokens": prompt_tokens, "completion_tokens": completion_tokens, - "total_tokens": max(raw_total_tokens - cached_tokens, prompt_tokens + completion_tokens), + "total_tokens": total_tokens, } if cached_tokens > 0: usage["prompt_tokens_details"] = {"cached_tokens": cached_tokens} - reasoning_tokens = int(usage_metadata.get("thoughtsTokenCount", 0) or 0) if reasoning_tokens > 0: usage["completion_tokens_details"] = {"reasoning_tokens": reasoning_tokens}