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https://github.com/fawney19/Aether.git
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perf: cherry-pick PR #172 性能优化(不含 orjson)
- tiktoken 编码器改为 @lru_cache 全局缓存,避免多实例重复初始化 - 前缀匹配按长度排序,避免短前缀抢先匹配 - AuthService 更新 last_used_at 时临时关闭 expire_on_commit,减少额外 SELECT - UsageService.record_usage_batch 改用 bulk_insert_mappings 批量插入 - 已有记录查询增加 selectinload 预加载,避免 N+1 - Gemini normalizer 长行格式化 Co-Authored-By: AAEE86 <33052466+AAEE86@users.noreply.github.com>
This commit is contained in:
@@ -692,10 +692,18 @@ class GeminiNormalizer(FormatNormalizer):
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# 关闭前面的 thinking/text block(如果还开着)
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if ss.get("thinking_block_started") and not ss.get("thinking_block_stopped"):
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ss["thinking_block_stopped"] = True
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events.append(ContentBlockStopEvent(block_index=_reserve_block_index("thinking_block_index")))
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events.append(
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ContentBlockStopEvent(
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block_index=_reserve_block_index("thinking_block_index")
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)
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)
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if ss.get("text_block_started") and not ss.get("text_block_stopped"):
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ss["text_block_stopped"] = True
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events.append(ContentBlockStopEvent(block_index=_reserve_block_index("text_block_index")))
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events.append(
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ContentBlockStopEvent(
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block_index=_reserve_block_index("text_block_index")
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)
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)
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name = str(func_call.get("name") or "")
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args = func_call.get("args")
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@@ -766,10 +774,14 @@ class GeminiNormalizer(FormatNormalizer):
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# 先补齐 content_block_stop(所有已开启的 block),再发送 MessageStop
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if ss.get("thinking_block_started") and not ss.get("thinking_block_stopped"):
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ss["thinking_block_stopped"] = True
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events.append(ContentBlockStopEvent(block_index=_reserve_block_index("thinking_block_index")))
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events.append(
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ContentBlockStopEvent(block_index=_reserve_block_index("thinking_block_index"))
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)
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if ss.get("text_block_started") and not ss.get("text_block_stopped"):
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ss["text_block_stopped"] = True
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events.append(ContentBlockStopEvent(block_index=_reserve_block_index("text_block_index")))
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events.append(
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ContentBlockStopEvent(block_index=_reserve_block_index("text_block_index"))
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)
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events.append(MessageStopEvent(stop_reason=stop_reason, usage=usage_info))
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if "error" in chunk:
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@@ -5,6 +5,7 @@ Tiktoken Token计数插件
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from __future__ import annotations
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from functools import lru_cache
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from typing import Any
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from src.core.logger import logger
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@@ -16,11 +17,39 @@ try:
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import tiktoken
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TIKTOKEN_AVAILABLE = True
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except ImportError:
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except ImportError: # pragma: no cover
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TIKTOKEN_AVAILABLE = False
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tiktoken = None
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@lru_cache(maxsize=256)
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def _get_encoder_cached(model: str) -> Any:
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"""全局编码器缓存。
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目的:避免在多实例/多请求场景下重复初始化 tiktoken 编码器。
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"""
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if not TIKTOKEN_AVAILABLE:
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raise RuntimeError("tiktoken not installed")
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mapping = TiktokenCounterPlugin.MODEL_ENCODINGS
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# 1) 完全匹配
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if model in mapping:
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return tiktoken.get_encoding(mapping[model])
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# 2) 前缀匹配(按前缀长度从长到短,避免短前缀抢先匹配)
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for model_prefix, enc_name in TiktokenCounterPlugin.MODEL_ENCODINGS_PREFIXES:
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if model.startswith(model_prefix):
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return tiktoken.get_encoding(enc_name)
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# 3) 尝试使用模型名称
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try:
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return tiktoken.encoding_for_model(model)
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except Exception:
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# 默认使用 cl100k_base
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return tiktoken.get_encoding("cl100k_base")
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class TiktokenCounterPlugin(TokenCounterPlugin):
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"""
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使用tiktoken库计算Token数量
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@@ -49,6 +78,13 @@ class TiktokenCounterPlugin(TokenCounterPlugin):
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"text-embedding-3-large": "cl100k_base",
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}
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# 前缀匹配顺序(从长到短)
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MODEL_ENCODINGS_PREFIXES = sorted(
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MODEL_ENCODINGS.items(),
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key=lambda kv: len(kv[0]),
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reverse=True,
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)
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# 每个消息的额外Token数
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MESSAGE_OVERHEAD = {
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"gpt-3.5-turbo": 4, # 每条消息
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@@ -84,42 +120,20 @@ class TiktokenCounterPlugin(TokenCounterPlugin):
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)
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def _get_encoder(self, model: str) -> Any:
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"""获取模型的编码器"""
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if model in self._encoders:
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return self._encoders[model]
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# 获取编码名称
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encoding_name = None
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# 完全匹配
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if model in self.MODEL_ENCODINGS:
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encoding_name = self.MODEL_ENCODINGS[model]
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else:
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# 前缀匹配
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for model_prefix, enc_name in self.MODEL_ENCODINGS.items():
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if model.startswith(model_prefix):
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encoding_name = enc_name
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break
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# 如果找不到,尝试使用模型名称
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if not encoding_name:
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try:
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encoder = tiktoken.encoding_for_model(model)
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self._encoders[model] = encoder
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return encoder
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except:
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# 默认使用cl100k_base
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encoding_name = "cl100k_base"
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# 创建编码器
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encoder = tiktoken.get_encoding(encoding_name)
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self._encoders[model] = encoder
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return encoder
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"""获取模型的编码器(全局缓存)"""
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return _get_encoder_cached(model)
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def supports_model(self, model: str) -> bool:
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"""检查是否支持指定模型"""
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# 支持所有OpenAI模型和一些兼容模型
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openai_models = ["gpt-4", "gpt-3.5", "text-davinci", "text-embedding", "code-davinci", "o1"]
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openai_models = [
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"gpt-4",
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"gpt-3.5",
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"text-davinci",
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"text-embedding",
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"code-davinci",
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"o1",
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]
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return any(model.startswith(prefix) for prefix in openai_models)
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async def count_tokens(self, text: str, model: str | None = None) -> int:
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@@ -263,6 +277,9 @@ class TiktokenCounterPlugin(TokenCounterPlugin):
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"""获取统计信息"""
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stats = await super().get_stats()
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stats.update(
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{"encoders_cached": len(self._encoders), "tiktoken_available": TIKTOKEN_AVAILABLE}
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{
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"encoders_cached": _get_encoder_cached.cache_info().currsize,
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"tiktoken_available": TIKTOKEN_AVAILABLE,
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}
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)
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return stats
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@@ -477,7 +477,20 @@ class AuthService:
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# 更新最后使用时间(使用节流策略,减少数据库写入)
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if _should_update_last_used(key_record.id):
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key_record.last_used_at = datetime.now(timezone.utc)
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db.commit() # 立即提交事务,释放数据库锁,避免阻塞后续请求
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# 这里需要 commit 来尽快释放锁,但默认 expire_on_commit=True 会让已加载对象过期,
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# 导致同一请求后续访问 user/api_key 字段时触发额外 SELECT。
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original_expire_on_commit = getattr(db, "expire_on_commit", None)
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try:
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if original_expire_on_commit is not None:
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db.expire_on_commit = False
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db.commit() # 立即提交事务,释放数据库锁,避免阻塞后续请求
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except Exception:
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db.rollback()
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raise
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finally:
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if original_expire_on_commit is not None:
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db.expire_on_commit = original_expire_on_commit
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api_key_fp = hashlib.sha256(api_key.encode()).hexdigest()[:12]
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logger.debug("API认证成功: 用户 {} (api_key_fp={})", user.email, api_key_fp)
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@@ -1450,7 +1450,17 @@ class UsageService:
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if request_ids:
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# 查询已存在的 Usage 记录(包括 pending/streaming 状态)
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existing_records = db.query(Usage).filter(Usage.request_id.in_(request_ids)).all()
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from sqlalchemy.orm import selectinload
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existing_records = (
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db.query(Usage)
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.options(
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selectinload(Usage.user),
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selectinload(Usage.api_key),
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)
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.filter(Usage.request_id.in_(request_ids))
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.all()
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)
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existing_usages = {u.request_id: u for u in existing_records}
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for record in records:
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@@ -1643,7 +1653,10 @@ class UsageService:
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logger.warning("批量记录中更新失败: {}, request_id={}", e, request_id)
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continue
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# 2. 处理需要新建的记录
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# 2. 处理需要新建的记录(批量插入)
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insert_mappings: list[dict[str, Any]] = []
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insert_request_ids: list[str] = []
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for i, (record, request_id, params) in enumerate(insert_params_list):
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try:
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usage_params, total_cost, exc = insert_results[i]
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@@ -1653,16 +1666,17 @@ class UsageService:
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user = params.user
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api_key = params.api_key
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# 创建 Usage 记录
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usage = Usage(**usage_params)
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# 新建记录默认 billing_status=settled,但补齐 finalized_at,便于审计与幂等判断
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if usage_params.get("status") in terminal_statuses:
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if getattr(usage, "billing_status", None) in (None, "pending"):
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usage.billing_status = "settled"
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if getattr(usage, "finalized_at", None) is None:
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usage.finalized_at = finalized_at
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db.add(usage)
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usages.append(usage)
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# 终态记录:补齐 settled/finalized_at;非终态:确保 billing_status=pending
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status = usage_params.get("status")
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if status in terminal_statuses:
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if usage_params.get("billing_status") in (None, "pending"):
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usage_params["billing_status"] = "settled"
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usage_params.setdefault("finalized_at", finalized_at)
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elif usage_params.get("billing_status") is None:
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usage_params["billing_status"] = "pending"
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insert_mappings.append(usage_params)
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insert_request_ids.append(request_id)
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# 聚合统计
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model_name = record.get("model") or "unknown"
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@@ -1689,6 +1703,24 @@ class UsageService:
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logger.warning("批量记录中跳过无效记录: {}, request_id={}", e, request_id)
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continue
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if insert_mappings:
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try:
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db.bulk_insert_mappings(Usage, insert_mappings)
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# 仅用于保持返回值语义:将新建记录读回为 ORM 对象
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inserted_records = (
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db.query(Usage).filter(Usage.request_id.in_(insert_request_ids)).all()
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)
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inserted_map = {u.request_id: u for u in inserted_records}
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for rid in insert_request_ids:
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inserted_usage = inserted_map.get(rid)
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if inserted_usage is not None:
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usages.append(inserted_usage)
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except Exception as e:
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logger.error("批量插入 Usage 记录时出错: {}", e)
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db.rollback()
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raise
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# 统计跳过的记录,失败率超过 10% 时提升日志级别
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if skipped_count > 0:
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skip_ratio = skipped_count / total_count if total_count > 0 else 0
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@@ -1763,13 +1795,14 @@ class UsageService:
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# 单次提交所有更改
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try:
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db.commit()
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inserted_count = len(usages) - updated_count
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inserted_count = len(insert_mappings)
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total_written = updated_count + inserted_count
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if updated_count > 0:
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logger.debug(f"批量记录成功: 更新 {updated_count} 条, 新建 {inserted_count} 条")
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logger.debug("批量记录成功: 更新 {} 条, 新建 {} 条", updated_count, inserted_count)
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else:
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logger.debug(f"批量记录 {len(usages)} 条使用记录成功")
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logger.debug("批量记录 {} 条使用记录成功", total_written)
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except Exception as e:
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logger.error(f"批量提交使用记录时出错: {e}")
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logger.error("批量提交使用记录时出错: {}", e)
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db.rollback()
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raise
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