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Aether/_deprecated_py_src/services/task/execute/sync_execute.py

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from __future__ import annotations
from collections.abc import Callable
from typing import Any
from uuid import uuid4
from src.core.logger import logger
from src.models.database import ApiKey, User
from src.services.candidate.failover import FailoverEngine
from src.services.candidate.policy import FailoverAction, RetryPolicy, SkipPolicy
from src.services.candidate.resolver import CandidateResolver
from src.services.orchestration.error_classifier import ErrorClassifier
from src.services.orchestration.request_dispatcher import RequestDispatcher
from src.services.provider.format import normalize_endpoint_signature
from src.services.request.candidate import RequestCandidateService
from src.services.scheduling.aware_scheduler import (
CacheAwareScheduler,
get_cache_aware_scheduler,
)
from src.services.system.config import SystemConfigService
from src.services.task.core.protocol import AttemptKind, AttemptResult
from src.services.task.core.schema import ExecutionResult
from src.services.task.execute.error_handler import TaskErrorOperationsService
from src.services.task.execute.exception_classification import (
CandidateErrorAction,
classify_candidate_error_action,
)
from src.services.task.execute.failure import TaskFailureOperationsService
from src.services.task.execute.pool import TaskPoolOperationsService
from src.services.task.execute.state_transition import (
SyncExecutionState,
resolve_execution_error_transition,
)
from src.services.task.request_state import RequestBodyState
from src.services.usage.service import UsageService
class SyncTaskExecutionService:
"""同步任务执行服务(候选遍历 + 错误处理 + 结果聚合)。"""
def __init__(
self,
db: Any,
redis_client: Any | None,
*,
recorder: Any,
pool_ops: TaskPoolOperationsService,
error_ops: TaskErrorOperationsService,
failure_ops: TaskFailureOperationsService,
) -> None:
self.db = db
self.redis = redis_client
self._recorder = recorder
self._pool_ops = pool_ops
self._error_ops = error_ops
self._failure_ops = failure_ops
async def execute_sync_unified(
self,
*,
api_format: str,
model_name: str,
user_api_key: ApiKey,
request_func: Callable[..., Any],
request_id: str | None,
is_stream: bool,
capability_requirements: dict[str, bool] | None,
preferred_key_ids: list[str] | None,
request_body_state: RequestBodyState | None,
request_headers: dict[str, Any] | None,
request_body: dict[str, Any] | None,
feat: 流式空闲超时、健康监控查询优化、限流桶内存上限与维护清理修复 Close #233 Co-authored-by: AAEE86 <ppk0227@hotmail.com> - cli_monitor_mixin: 引入 STREAM_IDLE_TIMEOUT_SECONDS(可通过环境变量配置), 流传输开始后若超出空闲窗口无新 chunk 则提前取消并返回 504,避免长时间挂起 - stream_context: 新增 managed_recorded_bodies 上下文管理器,确保 chunks 在 telemetry 完成后及时释放;stream_telemetry 使用该接口统一管理 response body 构建 - health endpoint: 将状态聚合改为 GROUP BY 直接统计,事件列表按 api_format 单独查询,避免单次 limit 拉取大量记录导致的遗漏与性能问题;同时过滤不活跃 provider/endpoint,与公开健康接口保持一致 - endpoint health service: 修正时间线数据按 endpoint_id 而非 key_id 聚合 - token_bucket: 引入 max_buckets/bucket_expiry 上限与定时清理,防止内存无限增长; 修复 refill_rate=0 时 get_reset_time 除零异常;新增 _is_unlimited_rate_limit 判断 - maintenance_scheduler: 调整清理顺序(先删整行再按窗口清理),新增 newer_than 边界参数,避免同一行在同一轮中被重复改写 - sync_execute: 新增 create_pending_usage 开关,允许已预创建记录的调用方跳过重复创建 - quota_reader / provider_ops balance: 小幅修复与健壮性提升 - Dockerfile: 添加 MALLOC_ARENA_MAX=2 环境变量以降低 gunicorn worker RSS - 补充相关测试覆盖
2026-03-18 23:38:26 +08:00
create_pending_usage: bool = True,
) -> ExecutionResult:
"""
Unified candidate traversal loop for SYNC.
This intentionally reuses existing components for parity:
- CandidateResolver fetch + record creation
- RequestDispatcher execution
- Error classification/rectify logic ported from the previous SYNC implementation
"""
from src.services.rate_limit.adaptive_rpm import get_adaptive_rpm_manager
from src.services.rate_limit.concurrency_manager import get_concurrency_manager
from src.services.request.executor import RequestExecutor
if not request_id:
request_id = str(uuid4())
# IMPORTANT:
# This SYNC path awaits upstream HTTP work while the failover engine may commit
# candidate audit rows between attempts. SQLAlchemy's default
# expire_on_commit=True would expire provider/endpoint/key ORM objects and can
# trigger an unexpected lazy DB reload later in error handling (for example when
# reading candidate.provider.config for failover_rules after a timeout).
#
# Keep already-loaded candidate objects resident in memory for the duration of
# the request, mirroring the async submit path.
original_expire_on_commit = getattr(self.db, "expire_on_commit", True)
self.db.expire_on_commit = False
try:
# Build execution components (mirrors pre-Phase-3 initialization)
priority_mode = SystemConfigService.get_config(
self.db,
"provider_priority_mode",
CacheAwareScheduler.PRIORITY_MODE_PROVIDER,
)
scheduling_mode = SystemConfigService.get_config(
self.db,
"scheduling_mode",
CacheAwareScheduler.SCHEDULING_MODE_CACHE_AFFINITY,
)
cache_scheduler = await get_cache_aware_scheduler(
self.redis,
priority_mode=priority_mode,
scheduling_mode=scheduling_mode,
)
# Ensure cache_scheduler inner state is ready
await cache_scheduler._ensure_initialized()
concurrency_manager = await get_concurrency_manager()
adaptive_manager = get_adaptive_rpm_manager()
request_executor = RequestExecutor(
db=self.db,
concurrency_manager=concurrency_manager,
adaptive_manager=adaptive_manager,
)
candidate_resolver = CandidateResolver(
db=self.db,
cache_scheduler=cache_scheduler,
)
error_classifier = ErrorClassifier(
db=self.db,
cache_scheduler=cache_scheduler,
adaptive_manager=adaptive_manager,
)
request_dispatcher = RequestDispatcher(
db=self.db,
request_executor=request_executor,
cache_scheduler=cache_scheduler,
)
affinity_key = str(user_api_key.id)
user_id = str(user_api_key.user_id)
api_format_norm = normalize_endpoint_signature(api_format)
feat: 流式空闲超时、健康监控查询优化、限流桶内存上限与维护清理修复 Close #233 Co-authored-by: AAEE86 <ppk0227@hotmail.com> - cli_monitor_mixin: 引入 STREAM_IDLE_TIMEOUT_SECONDS(可通过环境变量配置), 流传输开始后若超出空闲窗口无新 chunk 则提前取消并返回 504,避免长时间挂起 - stream_context: 新增 managed_recorded_bodies 上下文管理器,确保 chunks 在 telemetry 完成后及时释放;stream_telemetry 使用该接口统一管理 response body 构建 - health endpoint: 将状态聚合改为 GROUP BY 直接统计,事件列表按 api_format 单独查询,避免单次 limit 拉取大量记录导致的遗漏与性能问题;同时过滤不活跃 provider/endpoint,与公开健康接口保持一致 - endpoint health service: 修正时间线数据按 endpoint_id 而非 key_id 聚合 - token_bucket: 引入 max_buckets/bucket_expiry 上限与定时清理,防止内存无限增长; 修复 refill_rate=0 时 get_reset_time 除零异常;新增 _is_unlimited_rate_limit 判断 - maintenance_scheduler: 调整清理顺序(先删整行再按窗口清理),新增 newer_than 边界参数,避免同一行在同一轮中被重复改写 - sync_execute: 新增 create_pending_usage 开关,允许已预创建记录的调用方跳过重复创建 - quota_reader / provider_ops balance: 小幅修复与健壮性提升 - Dockerfile: 添加 MALLOC_ARENA_MAX=2 环境变量以降低 gunicorn worker RSS - 补充相关测试覆盖
2026-03-18 23:38:26 +08:00
user: User | None = None
username_snapshot = None
api_key_name_snapshot = getattr(user_api_key, "name", None)
try:
user = self.db.query(User).filter(User.id == user_api_key.user_id).first()
username_snapshot = getattr(user, "username", None) if user else None
except Exception as exc:
feat: 流式空闲超时、健康监控查询优化、限流桶内存上限与维护清理修复 Close #233 Co-authored-by: AAEE86 <ppk0227@hotmail.com> - cli_monitor_mixin: 引入 STREAM_IDLE_TIMEOUT_SECONDS(可通过环境变量配置), 流传输开始后若超出空闲窗口无新 chunk 则提前取消并返回 504,避免长时间挂起 - stream_context: 新增 managed_recorded_bodies 上下文管理器,确保 chunks 在 telemetry 完成后及时释放;stream_telemetry 使用该接口统一管理 response body 构建 - health endpoint: 将状态聚合改为 GROUP BY 直接统计,事件列表按 api_format 单独查询,避免单次 limit 拉取大量记录导致的遗漏与性能问题;同时过滤不活跃 provider/endpoint,与公开健康接口保持一致 - endpoint health service: 修正时间线数据按 endpoint_id 而非 key_id 聚合 - token_bucket: 引入 max_buckets/bucket_expiry 上限与定时清理,防止内存无限增长; 修复 refill_rate=0 时 get_reset_time 除零异常;新增 _is_unlimited_rate_limit 判断 - maintenance_scheduler: 调整清理顺序(先删整行再按窗口清理),新增 newer_than 边界参数,避免同一行在同一轮中被重复改写 - sync_execute: 新增 create_pending_usage 开关,允许已预创建记录的调用方跳过重复创建 - quota_reader / provider_ops balance: 小幅修复与健壮性提升 - Dockerfile: 添加 MALLOC_ARENA_MAX=2 环境变量以降低 gunicorn worker RSS - 补充相关测试覆盖
2026-03-18 23:38:26 +08:00
# username 仅用于审计快照,不应阻塞主请求链路。
logger.warning("查询用户快照失败: {}", str(exc))
# 默认由 TaskService 创建 pending 使用记录;已预创建的调用方可关闭。
if create_pending_usage:
try:
UsageService.create_pending_usage(
db=self.db,
request_id=request_id,
user=user,
api_key=user_api_key,
model=model_name,
is_stream=is_stream,
api_format=api_format_norm,
request_headers=request_headers,
request_body=request_body,
)
except Exception as exc:
logger.warning("创建 pending 使用记录失败: {}", str(exc))
all_candidates, global_model_id = await candidate_resolver.fetch_candidates(
api_format=api_format_norm,
model_name=model_name,
affinity_key=affinity_key,
user_api_key=user_api_key,
request_id=request_id,
is_stream=is_stream,
capability_requirements=capability_requirements,
preferred_key_ids=preferred_key_ids,
request_body=request_body,
)
# 号池排序涉及大量 Redis 操作,提前释放 DB 连接避免连接池压力
from src.services.scheduling.utils import release_db_connection_before_await
release_db_connection_before_await(self.db)
# Account Pool: reorder candidates for claude_code providers.
all_candidates, pool_traces = await self._pool_ops.apply_pool_reorder(
all_candidates, request_body=request_body
)
candidate_record_map = await candidate_resolver.create_candidate_records_async(
all_candidates=all_candidates,
request_id=request_id,
user_id=user_id,
user_api_key=user_api_key,
required_capabilities=capability_requirements,
)
max_attempts = candidate_resolver.count_total_attempts(all_candidates)
# Keep behavior consistent with previous behavior: last_candidate is updated even if skipped.
execution_state = SyncExecutionState(
candidate_record_map=candidate_record_map,
request_body_state=request_body_state,
last_candidate=all_candidates[-1] if all_candidates else None,
)
async def _attempt(candidate: Any) -> AttemptResult:
execution_state.touch_candidate(candidate)
candidate_index = int(getattr(candidate, "_utf_candidate_index", -1))
retry_index = int(getattr(candidate, "_utf_retry_index", 0))
candidate_record_id = str(getattr(candidate, "_utf_candidate_record_id", "") or "")
attempt_counter = int(getattr(candidate, "_utf_attempt_count", 0))
max_attempts_local = int(getattr(candidate, "_utf_max_attempts", max_attempts))
# Safety net: if record_id missing, create an "available" record on-demand.
if not candidate_record_id:
from src.services.scheduling.schemas import PoolCandidate
pool_extra = (
getattr(candidate.key, "_pool_extra_data", None)
if isinstance(getattr(candidate.key, "_pool_extra_data", None), dict)
else {}
)
extra_data: dict[str, Any] = {
"needs_conversion": bool(getattr(candidate, "needs_conversion", False)),
"provider_api_format": getattr(candidate, "provider_api_format", None)
or None,
"mapping_matched_model": getattr(candidate, "mapping_matched_model", None)
or None,
**pool_extra,
}
if isinstance(candidate, PoolCandidate):
extra_data["pool_group_id"] = str(candidate.provider.id)
extra_data["pool_key_index"] = int(
getattr(candidate, "_pool_key_index", 0) or 0
)
created = RequestCandidateService.create_candidate(
db=self.db,
request_id=request_id,
candidate_index=candidate_index,
retry_index=retry_index,
user_id=user_id,
api_key_id=str(user_api_key.id),
username=username_snapshot,
api_key_name=api_key_name_snapshot,
provider_id=str(candidate.provider.id),
endpoint_id=str(candidate.endpoint.id),
key_id=str(candidate.key.id),
status="available",
is_cached=bool(getattr(candidate, "is_cached", False)),
extra_data=extra_data,
)
candidate_record_id = str(created.id)
execution_state.candidate_record_map[(candidate_index, retry_index)] = (
candidate_record_id
)
(
response,
_provider_name,
attempt_id,
_provider_id,
_endpoint_id,
_key_id,
_first_byte_time_ms,
) = await request_dispatcher.dispatch(
candidate=candidate,
candidate_index=candidate_index,
retry_index=retry_index,
candidate_record_id=candidate_record_id,
user_api_key=user_api_key,
user_id=user_id,
request_func=request_func,
request_id=request_id,
api_format=api_format_norm,
model_name=model_name,
affinity_key=affinity_key,
global_model_id=global_model_id,
attempt_counter=attempt_counter,
max_attempts=max_attempts_local,
is_stream=is_stream,
)
_ = (
attempt_id,
_provider_name,
_provider_id,
_endpoint_id,
_key_id,
_first_byte_time_ms,
)
# Account Pool: on success, update sticky binding + LRU.
await self._pool_ops.pool_on_success(candidate, request_body)
if is_stream:
return AttemptResult(
kind=AttemptKind.STREAM,
http_status=200,
http_headers={},
stream_iterator=response,
)
return AttemptResult(
kind=AttemptKind.SYNC_RESPONSE,
http_status=200,
http_headers={},
response_body=response,
)
async def _handle_exec_err(
*,
exec_err: Any,
candidate: Any,
candidate_index: int,
retry_index: int,
max_retries_for_candidate: int,
record_id: str | None,
attempt_count: int,
max_attempts: int | None,
) -> tuple[FailoverAction, int | None]:
execution_state.track_execution_error(exec_err=exec_err, candidate=candidate)
# Fall back to retry 0 record if needed (rectify may extend retries).
candidate_record_id = execution_state.resolve_candidate_record_id(
candidate_index=candidate_index,
record_id=record_id,
)
raw_action = await self._error_ops.handle_candidate_error(
exec_err=exec_err,
candidate=candidate,
candidate_record_id=candidate_record_id,
retry_index=retry_index,
max_retries_for_candidate=max_retries_for_candidate,
affinity_key=affinity_key,
api_format=api_format_norm,
global_model_id=global_model_id,
request_id=request_id,
attempt=attempt_count,
max_attempts=int(max_attempts or 0),
request_body_state=request_body_state,
error_classifier=error_classifier,
)
action = classify_candidate_error_action(raw_action)
if action == CandidateErrorAction.RAISE_ERROR:
execution_state.raise_classified_error(
fallback_error=exec_err,
failure_ops=self._failure_ops,
model_name=model_name,
api_format=api_format_norm,
)
return resolve_execution_error_transition(
action=action,
state=execution_state,
max_retries_for_candidate=max_retries_for_candidate,
retry_index=retry_index,
).as_failover_tuple()
engine = FailoverEngine(
self.db,
error_classifier=error_classifier,
recorder=self._recorder,
)
result = await engine.execute(
candidates=all_candidates,
attempt_func=_attempt,
retry_policy=RetryPolicy.for_sync_task(),
skip_policy=SkipPolicy(),
request_id=request_id,
user_id=user_id,
api_key_id=str(user_api_key.id),
username=username_snapshot,
api_key_name=api_key_name_snapshot,
candidate_record_map=candidate_record_map,
max_attempts=max_attempts,
execution_error_handler=_handle_exec_err,
)
if result.success:
# Build pool scheduling summary from traces collected during reorder.
if pool_traces and result.key_id:
try:
attempted_key_ids: set[str] = set()
for ck in result.candidate_keys or []:
status = str(getattr(ck, "status", "") or "").strip().lower()
if status in {"", "available", "pending", "skipped", "unused"}:
continue
kid = getattr(ck, "key_id", None)
if isinstance(kid, str) and kid:
attempted_key_ids.add(kid)
if not attempted_key_ids:
attempted_key_ids.add(str(result.key_id))
for pt in pool_traces:
summary = pt.build_summary(
result.key_id,
attempted_key_ids=attempted_key_ids,
)
if summary:
result.pool_summary = summary
break
except Exception:
pass
return result
self._failure_ops.raise_all_failed_exception(
request_id,
max_attempts,
execution_state.last_candidate,
model_name,
api_format_norm,
execution_state.last_error,
)
finally:
self.db.expire_on_commit = original_expire_on_commit