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fix(llm): 兼容处理部分模型缺失的token用量字段

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部分模型（如 embedding 模型）的 API 响应中可能不包含 `completion_tokens` 等完整的用量字段。

此前的直接属性访问会导致 `AttributeError`，从而中断使用记录和统计更新流程。

通过改用 `getattr(usage, "...", 0)` 的方式为缺失的字段提供默认值 0，增强了代码的健壮性，确保系统能够稳定处理来自不同类型模型的响应。
This commit is contained in:
tt-P607
2025-10-29 19:19:30 +08:00
committed by Windpicker-owo
parent 4fb56e5b87
commit 8a08d1b9f2
4 changed files with 25 additions and 18 deletions
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18
src/llm_models/utils.py
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@@ -155,8 +155,12 @@ class LLMUsageRecorder:
endpoint: str,
time_cost: float = 0.0,
):
input_cost = (model_usage.prompt_tokens / 1000000) * model_info.price_in
output_cost = (model_usage.completion_tokens / 1000000) * model_info.price_out
prompt_tokens = getattr(model_usage, "prompt_tokens", 0)
completion_tokens = getattr(model_usage, "completion_tokens", 0)
total_tokens = getattr(model_usage, "total_tokens", 0)
input_cost = (prompt_tokens / 1000000) * model_info.price_in
output_cost = (completion_tokens / 1000000) * model_info.price_out
round(input_cost + output_cost, 6)
session = None
@@ -170,9 +174,9 @@ class LLMUsageRecorder:
user_id=user_id,
request_type=request_type,
endpoint=endpoint,
prompt_tokens=model_usage.prompt_tokens or 0,
completion_tokens=model_usage.completion_tokens or 0,
total_tokens=model_usage.total_tokens or 0,
prompt_tokens=prompt_tokens,
completion_tokens=completion_tokens,
total_tokens=total_tokens,
cost=1.0,
time_cost=round(time_cost or 0.0, 3),
status="success",
@@ -185,8 +189,8 @@ class LLMUsageRecorder:
logger.debug(
f"Token使用情况 - 模型: {model_usage.model_name}, "
f"用户: {user_id}, 类型: {request_type}, "
f"提示词: {model_usage.prompt_tokens}, 完成: {model_usage.completion_tokens}, "
f"总计: {model_usage.total_tokens}"
f"提示词: {prompt_tokens}, 完成: {completion_tokens}, "
f"总计: {total_tokens}"
)
except Exception as e:
logger.error(f"记录token使用情况失败: {e!s}")