[AC-AISVC-RES-01~15] feat(retrieval): 实现检索策略路由核心模块
- 新增 routing_config.py 路由配置模型 - StrategyType: DEFAULT/ENHANCED 策略类型 - RagRuntimeMode: DIRECT/REACT/AUTO 运行模式 - RoutingConfig: 路由配置类 - StrategyContext: 策略上下文 - StrategyResult: 策略结果 - 新增 strategy_router.py 策略路由器 - RollbackManager: 回滚管理器 - DefaultPipeline: 默认检索管道 - EnhancedPipeline: 增强检索管道 - StrategyRouter: 策略路由器 - 新增 mode_router.py 模式路由器 - ComplexityAnalyzer: 复杂度分析器 - ModeRouter: 模式路由器 - 新增 strategy_integration.py 统一集成层 - RetrievalStrategyIntegration: 策略集成器 - 更新 __init__.py 导出新模块
This commit is contained in:
MerCry
parent
2476da8957
commit
c628181623
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@ -2,6 +2,7 @@
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Retrieval module for AI Service.
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[AC-AISVC-16] Provides retriever implementations with plugin architecture.
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RAG Optimization: Two-stage retrieval, RRF hybrid ranking, metadata filtering.
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[AC-AISVC-RES-01~15] Strategy routing and mode routing for retrieval pipeline.
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"""
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from app.services.retrieval.base import (
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@ -32,6 +33,29 @@ from app.services.retrieval.optimized_retriever import (
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get_optimized_retriever,
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)
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from app.services.retrieval.vector_retriever import VectorRetriever, get_vector_retriever
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from app.services.retrieval.routing_config import (
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RagRuntimeMode,
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RoutingConfig,
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StrategyContext,
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StrategyType,
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StrategyResult,
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)
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from app.services.retrieval.strategy_router import (
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RollbackRecord,
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StrategyRouter,
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get_strategy_router,
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)
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from app.services.retrieval.mode_router import (
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ComplexityAnalyzer,
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ModeRouter,
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ModeRouteResult,
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get_mode_router,
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)
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from app.services.retrieval.strategy_integration import (
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RetrievalStrategyIntegration,
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RetrievalStrategyResult,
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get_retrieval_strategy_integration,
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)
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__all__ = [
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"BaseRetriever",
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@ -55,4 +79,19 @@ __all__ = [
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"get_knowledge_indexer",
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"IndexingProgress",
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"IndexingResult",
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"RagRuntimeMode",
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"RoutingConfig",
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"StrategyContext",
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"StrategyType",
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"StrategyResult",
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"RollbackRecord",
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"StrategyRouter",
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"get_strategy_router",
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"ComplexityAnalyzer",
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"ModeRouter",
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"ModeRouteResult",
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"get_mode_router",
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"RetrievalStrategyIntegration",
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"RetrievalStrategyResult",
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"get_retrieval_strategy_integration",
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]
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@ -0,0 +1,438 @@
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"""
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Mode Router for RAG Runtime Mode Selection.
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[AC-AISVC-RES-09, AC-AISVC-RES-10, AC-AISVC-RES-11] Routes to direct/react/auto mode.
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Mode Descriptions:
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- direct: Low-latency generic retrieval path (single KB call)
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- react: Multi-step ReAct retrieval path (high accuracy)
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- auto: Automatic selection based on complexity/confidence rules
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"""
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from __future__ import annotations
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import logging
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import re
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import time
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from dataclasses import dataclass, field
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from typing import TYPE_CHECKING, Any
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from app.services.retrieval.routing_config import (
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RagRuntimeMode,
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RoutingConfig,
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StrategyContext,
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)
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if TYPE_CHECKING:
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from app.services.retrieval.base import RetrievalResult
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logger = logging.getLogger(__name__)
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@dataclass
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class ComplexityAnalyzer:
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"""
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Analyzes query complexity for mode routing decisions.
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Complexity factors:
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- Query length
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- Number of conditions/constraints
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- Presence of logical operators (and, or, not)
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- Cross-domain indicators
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- Multi-step reasoning requirements
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"""
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short_query_threshold: int = 20
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long_query_threshold: int = 100
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condition_patterns: list[str] = field(default_factory=lambda: [
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r"和|与|及|并且|同时",
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r"或者|还是|要么",
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r"但是|不过|然而",
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r"如果|假如|假设",
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r"既.*又",
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r"不仅.*而且",
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])
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reasoning_patterns: list[str] = field(default_factory=lambda: [
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r"为什么|原因|理由",
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r"怎么|如何|怎样",
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r"区别|差异|不同",
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r"比较|对比|优劣",
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r"分析|评估|判断",
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])
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cross_domain_patterns: list[str] = field(default_factory=lambda: [
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r"跨|多|各个",
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r"所有|全部|整体",
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r"综合|汇总|统计",
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])
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def analyze(self, query: str) -> float:
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"""
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Analyze query complexity and return a score (0.0 ~ 1.0).
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Higher score indicates more complex query that may benefit from ReAct mode.
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Args:
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query: User query text
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Returns:
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Complexity score (0.0 = simple, 1.0 = very complex)
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"""
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if not query:
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return 0.0
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score = 0.0
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query_length = len(query)
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if query_length < self.short_query_threshold:
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score += 0.0
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elif query_length > self.long_query_threshold:
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score += 0.3
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else:
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score += 0.15
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condition_count = 0
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for pattern in self.condition_patterns:
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matches = re.findall(pattern, query)
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condition_count += len(matches)
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if condition_count >= 3:
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score += 0.3
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elif condition_count >= 2:
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score += 0.2
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elif condition_count >= 1:
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score += 0.1
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for pattern in self.reasoning_patterns:
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if re.search(pattern, query):
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score += 0.15
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break
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for pattern in self.cross_domain_patterns:
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if re.search(pattern, query):
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score += 0.15
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break
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question_marks = query.count("?") + query.count("？")
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if question_marks >= 2:
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score += 0.1
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return min(1.0, score)
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@dataclass
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class ModeRouteResult:
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"""Result from mode routing decision."""
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mode: RagRuntimeMode
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confidence: float
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complexity_score: float
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should_fallback_to_react: bool = False
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fallback_reason: str | None = None
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diagnostics: dict[str, Any] = field(default_factory=dict)
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class DirectRetrievalExecutor:
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"""
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[AC-AISVC-RES-09] Direct retrieval executor for low-latency path.
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Single KB call without multi-step reasoning.
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"""
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def __init__(self):
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self._retriever = None
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async def execute(
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self,
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ctx: StrategyContext,
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) -> "RetrievalResult":
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"""
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Execute direct retrieval (single KB call).
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"""
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from app.services.retrieval.optimized_retriever import get_optimized_retriever
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from app.services.retrieval.base import RetrievalContext
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if self._retriever is None:
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self._retriever = await get_optimized_retriever()
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retrieval_ctx = RetrievalContext(
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tenant_id=ctx.tenant_id,
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query=ctx.query,
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metadata_filter=ctx.metadata_filter,
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kb_ids=ctx.kb_ids,
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)
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return await self._retriever.retrieve(retrieval_ctx)
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class ReactRetrievalExecutor:
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"""
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[AC-AISVC-RES-10] ReAct retrieval executor for multi-step path.
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Uses AgentOrchestrator for multi-step reasoning and KB calls.
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"""
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def __init__(self, max_steps: int = 5):
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self._max_steps = max_steps
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async def execute(
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self,
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ctx: StrategyContext,
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config: RoutingConfig,
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) -> tuple[str, "RetrievalResult | None", dict[str, Any]]:
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"""
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Execute ReAct retrieval (multi-step reasoning).
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Returns:
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Tuple of (final_answer, retrieval_result, react_context)
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"""
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from app.services.mid.agent_orchestrator import AgentOrchestrator, AgentMode
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from app.services.mid.tool_registry import ToolRegistry
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from app.services.mid.timeout_governor import TimeoutGovernor
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from app.services.llm.factory import get_llm_config_manager
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try:
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llm_manager = get_llm_config_manager()
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llm_client = llm_manager.get_client()
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except Exception as e:
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logger.warning(f"[ModeRouter] Failed to get LLM client: {e}")
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llm_client = None
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tool_registry = ToolRegistry(timeout_governor=TimeoutGovernor())
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timeout_governor = TimeoutGovernor()
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orchestrator = AgentOrchestrator(
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max_iterations=min(config.react_max_steps, self._max_steps),
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timeout_governor=timeout_governor,
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llm_client=llm_client,
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tool_registry=tool_registry,
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tenant_id=ctx.tenant_id,
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mode=AgentMode.FUNCTION_CALLING,
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)
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base_context = {
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"query": ctx.query,
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"metadata_filter": ctx.metadata_filter,
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"kb_ids": ctx.kb_ids,
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**ctx.additional_context,
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}
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final_answer, react_ctx, trace = await orchestrator.execute(
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user_message=ctx.query,
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context=base_context,
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)
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return final_answer, None, {
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"iterations": react_ctx.iteration,
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"tool_calls": [tc.model_dump() for tc in react_ctx.tool_calls] if react_ctx.tool_calls else [],
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"final_answer": final_answer,
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}
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class ModeRouter:
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"""
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[AC-AISVC-RES-09, AC-AISVC-RES-10, AC-AISVC-RES-11]
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Mode router for RAG runtime mode selection.
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Mode Selection:
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- direct: Low-latency generic retrieval (single KB call)
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- react: Multi-step ReAct retrieval (high accuracy)
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- auto: Automatic selection based on complexity/confidence
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Auto Mode Rules:
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- Direct conditions:
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- Short query, clear intent
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- High metadata confidence
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- No cross-domain/multi-condition
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- React conditions:
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- Multi-condition/multi-constraint
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- Low metadata confidence
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- Need for secondary confirmation or multi-step reasoning
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"""
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def __init__(
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self,
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config: RoutingConfig | None = None,
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):
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self._config = config or RoutingConfig()
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self._complexity_analyzer = ComplexityAnalyzer()
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self._direct_executor = DirectRetrievalExecutor()
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self._react_executor = ReactRetrievalExecutor(
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max_steps=self._config.react_max_steps
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)
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@property
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def config(self) -> RoutingConfig:
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"""Get current configuration."""
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return self._config
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def update_config(self, new_config: RoutingConfig) -> None:
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"""
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[AC-AISVC-RES-15] Update routing configuration (hot reload).
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"""
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self._config = new_config
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self._react_executor._max_steps = new_config.react_max_steps
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logger.info(
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f"[AC-AISVC-RES-15] ModeRouter config updated: "
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f"mode={new_config.rag_runtime_mode.value}, "
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f"react_max_steps={new_config.react_max_steps}, "
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f"confidence_threshold={new_config.react_trigger_confidence_threshold}"
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)
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def route(
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self,
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ctx: StrategyContext,
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) -> ModeRouteResult:
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"""
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[AC-AISVC-RES-09, AC-AISVC-RES-10, AC-AISVC-RES-11]
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Route to appropriate mode based on configuration and context.
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Args:
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ctx: Strategy context with query, metadata, confidence, etc.
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Returns:
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ModeRouteResult with selected mode and diagnostics
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"""
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configured_mode = self._config.get_rag_runtime_mode()
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if configured_mode == RagRuntimeMode.DIRECT:
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logger.info(
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f"[AC-AISVC-RES-09] Mode routing to DIRECT: tenant={ctx.tenant_id}"
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)
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return ModeRouteResult(
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mode=RagRuntimeMode.DIRECT,
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confidence=ctx.metadata_confidence,
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complexity_score=ctx.complexity_score,
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diagnostics={"configured_mode": "direct"},
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)
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if configured_mode == RagRuntimeMode.REACT:
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logger.info(
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f"[AC-AISVC-RES-10] Mode routing to REACT: tenant={ctx.tenant_id}"
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)
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return ModeRouteResult(
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mode=RagRuntimeMode.REACT,
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confidence=ctx.metadata_confidence,
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complexity_score=ctx.complexity_score,
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diagnostics={"configured_mode": "react"},
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)
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complexity_score = self._complexity_analyzer.analyze(ctx.query)
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effective_complexity = max(complexity_score, ctx.complexity_score)
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should_use_react = self._config.should_trigger_react_in_auto_mode(
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confidence=ctx.metadata_confidence,
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complexity_score=effective_complexity,
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)
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selected_mode = RagRuntimeMode.REACT if should_use_react else RagRuntimeMode.DIRECT
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logger.info(
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f"[AC-AISVC-RES-11, AC-AISVC-RES-12, AC-AISVC-RES-13] "
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f"Auto mode routing: selected={selected_mode.value}, "
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f"confidence={ctx.metadata_confidence:.2f}, "
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f"complexity={effective_complexity:.2f}, "
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f"tenant={ctx.tenant_id}"
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)
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return ModeRouteResult(
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mode=selected_mode,
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confidence=ctx.metadata_confidence,
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complexity_score=effective_complexity,
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diagnostics={
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"configured_mode": "auto",
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"analyzed_complexity": complexity_score,
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"provided_complexity": ctx.complexity_score,
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"react_trigger_confidence": self._config.react_trigger_confidence_threshold,
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"react_trigger_complexity": self._config.react_trigger_complexity_score,
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},
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)
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async def execute_direct(
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self,
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ctx: StrategyContext,
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) -> "RetrievalResult":
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"""
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Execute direct retrieval mode.
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"""
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return await self._direct_executor.execute(ctx)
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async def execute_react(
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self,
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ctx: StrategyContext,
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) -> tuple[str, "RetrievalResult | None", dict[str, Any]]:
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"""
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Execute ReAct retrieval mode.
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"""
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return await self._react_executor.execute(ctx, self._config)
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async def execute_with_fallback(
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self,
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ctx: StrategyContext,
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) -> tuple["RetrievalResult | None", str | None, ModeRouteResult]:
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"""
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[AC-AISVC-RES-14] Execute with fallback from direct to react on low confidence.
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Args:
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ctx: Strategy context
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Returns:
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Tuple of (RetrievalResult or None, final_answer or None, ModeRouteResult)
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"""
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route_result = self.route(ctx)
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if route_result.mode == RagRuntimeMode.DIRECT:
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retrieval_result = await self._direct_executor.execute(ctx)
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max_score = 0.0
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if retrieval_result and retrieval_result.hits:
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max_score = max((h.score for h in retrieval_result.hits), default=0.0)
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if self._config.should_fallback_direct_to_react(max_score):
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logger.info(
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f"[AC-AISVC-RES-14] Direct mode low confidence fallback to react: "
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f"confidence={max_score:.2f}, threshold={self._config.direct_fallback_confidence_threshold}"
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)
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final_answer, _, react_ctx = await self._react_executor.execute(ctx, self._config)
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return (
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None,
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final_answer,
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ModeRouteResult(
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mode=RagRuntimeMode.REACT,
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confidence=max_score,
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complexity_score=route_result.complexity_score,
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should_fallback_to_react=True,
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fallback_reason="low_confidence",
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diagnostics={
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**route_result.diagnostics,
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"fallback_from": "direct",
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"direct_confidence": max_score,
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},
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),
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)
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return retrieval_result, None, route_result
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final_answer, _, react_ctx = await self._react_executor.execute(ctx, self._config)
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return None, final_answer, route_result
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_mode_router: ModeRouter | None = None
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|
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def get_mode_router() -> ModeRouter:
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"""Get or create ModeRouter singleton."""
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global _mode_router
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if _mode_router is None:
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_mode_router = ModeRouter()
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return _mode_router
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|
||||
|
||||
def reset_mode_router() -> None:
|
||||
"""Reset ModeRouter singleton (for testing)."""
|
||||
global _mode_router
|
||||
_mode_router = None
|
||||
|
|
@ -0,0 +1,187 @@
|
|||
"""
|
||||
Retrieval and Embedding Strategy Configuration.
|
||||
[AC-AISVC-RES-01~15] Configuration for strategy routing and mode routing.
|
||||
"""
|
||||
|
||||
from dataclasses import dataclass, field
|
||||
from enum import Enum
|
||||
from typing import Any
|
||||
|
||||
|
||||
class StrategyType(str, Enum):
|
||||
"""Strategy type for retrieval pipeline selection."""
|
||||
DEFAULT = "default"
|
||||
ENHANCED = "enhanced"
|
||||
|
||||
|
||||
class RagRuntimeMode(str, Enum):
|
||||
"""RAG runtime mode for execution path selection."""
|
||||
DIRECT = "direct"
|
||||
REACT = "react"
|
||||
AUTO = "auto"
|
||||
|
||||
|
||||
@dataclass
|
||||
class RoutingConfig:
|
||||
"""
|
||||
[AC-AISVC-RES-01~15] Routing configuration for strategy and mode selection.
|
||||
|
||||
Configuration hierarchy:
|
||||
1. Strategy selection (default vs enhanced)
|
||||
2. Mode selection (direct/react/auto)
|
||||
3. Auto routing rules (complexity/confidence thresholds)
|
||||
4. Fallback behavior
|
||||
"""
|
||||
|
||||
enabled: bool = True
|
||||
strategy: StrategyType = StrategyType.DEFAULT
|
||||
|
||||
grayscale_percentage: float = 0.0
|
||||
grayscale_allowlist: list[str] = field(default_factory=list)
|
||||
|
||||
rag_runtime_mode: RagRuntimeMode = RagRuntimeMode.AUTO
|
||||
|
||||
react_trigger_confidence_threshold: float = 0.6
|
||||
react_trigger_complexity_score: float = 0.5
|
||||
react_max_steps: int = 5
|
||||
|
||||
direct_fallback_on_low_confidence: bool = True
|
||||
direct_fallback_confidence_threshold: float = 0.4
|
||||
|
||||
performance_budget_ms: int = 5000
|
||||
performance_degradation_threshold: float = 0.2
|
||||
|
||||
def should_use_enhanced_strategy(self, tenant_id: str | None = None) -> bool:
|
||||
"""
|
||||
[AC-AISVC-RES-02, AC-AISVC-RES-03] Determine if enhanced strategy should be used.
|
||||
|
||||
Priority:
|
||||
1. If strategy is explicitly set to ENHANCED, use enhanced
|
||||
2. If strategy is DEFAULT, use default
|
||||
3. If grayscale is enabled, check percentage/allowlist
|
||||
"""
|
||||
if self.strategy == StrategyType.ENHANCED:
|
||||
return True
|
||||
|
||||
if self.strategy == StrategyType.DEFAULT:
|
||||
return False
|
||||
|
||||
if self.grayscale_percentage > 0:
|
||||
import hashlib
|
||||
if tenant_id:
|
||||
hash_val = int(hashlib.md5(tenant_id.encode()).hexdigest()[:8], 16)
|
||||
return (hash_val % 100) < (self.grayscale_percentage * 100)
|
||||
return False
|
||||
|
||||
if self.grayscale_allowlist and tenant_id:
|
||||
return tenant_id in self.grayscale_allowlist
|
||||
|
||||
return False
|
||||
|
||||
def get_rag_runtime_mode(self) -> RagRuntimeMode:
|
||||
"""Get the configured RAG runtime mode."""
|
||||
return self.rag_runtime_mode
|
||||
|
||||
def should_fallback_direct_to_react(self, confidence: float) -> bool:
|
||||
"""
|
||||
[AC-AISVC-RES-14] Determine if direct mode should fallback to react.
|
||||
|
||||
Args:
|
||||
confidence: Retrieval confidence score (0.0 ~ 1.0)
|
||||
|
||||
Returns:
|
||||
True if fallback should be triggered
|
||||
"""
|
||||
if not self.direct_fallback_on_low_confidence:
|
||||
return False
|
||||
|
||||
return confidence < self.direct_fallback_confidence_threshold
|
||||
|
||||
def should_trigger_react_in_auto_mode(
|
||||
self,
|
||||
confidence: float,
|
||||
complexity_score: float,
|
||||
) -> bool:
|
||||
"""
|
||||
[AC-AISVC-RES-11, AC-AISVC-RES-12, AC-AISVC-RES-13]
|
||||
Determine if react mode should be triggered in auto mode.
|
||||
|
||||
Direct conditions (优先):
|
||||
- Short query, clear intent
|
||||
- High metadata confidence
|
||||
- No cross-domain/multi-condition
|
||||
|
||||
React conditions:
|
||||
- Multi-condition/multi-constraint
|
||||
- Low metadata confidence
|
||||
- Need for secondary confirmation or multi-step reasoning
|
||||
|
||||
Args:
|
||||
confidence: Metadata inference confidence (0.0 ~ 1.0)
|
||||
complexity_score: Query complexity score (0.0 ~ 1.0)
|
||||
|
||||
Returns:
|
||||
True if react mode should be used
|
||||
"""
|
||||
if confidence < self.react_trigger_confidence_threshold:
|
||||
return True
|
||||
|
||||
if complexity_score > self.react_trigger_complexity_score:
|
||||
return True
|
||||
|
||||
return False
|
||||
|
||||
def validate(self) -> tuple[bool, list[str]]:
|
||||
"""
|
||||
[AC-AISVC-RES-06] Validate configuration consistency.
|
||||
|
||||
Returns:
|
||||
(is_valid, list of error messages)
|
||||
"""
|
||||
errors = []
|
||||
|
||||
if self.grayscale_percentage < 0 or self.grayscale_percentage > 1.0:
|
||||
errors.append("grayscale_percentage must be between 0.0 and 1.0")
|
||||
|
||||
if self.react_trigger_confidence_threshold < 0 or self.react_trigger_confidence_threshold > 1.0:
|
||||
errors.append("react_trigger_confidence_threshold must be between 0.0 and 1.0")
|
||||
|
||||
if self.react_trigger_complexity_score < 0 or self.react_trigger_complexity_score > 1.0:
|
||||
errors.append("react_trigger_complexity_score must be between 0.0 and 1.0")
|
||||
|
||||
if self.react_max_steps < 3 or self.react_max_steps > 10:
|
||||
errors.append("react_max_steps must be between 3 and 10")
|
||||
|
||||
if self.direct_fallback_confidence_threshold < 0 or self.direct_fallback_confidence_threshold > 1.0:
|
||||
errors.append("direct_fallback_confidence_threshold must be between 0.0 and 1.0")
|
||||
|
||||
if self.performance_budget_ms < 1000:
|
||||
errors.append("performance_budget_ms must be at least 1000")
|
||||
|
||||
if self.performance_degradation_threshold < 0 or self.performance_degradation_threshold > 1.0:
|
||||
errors.append("performance_degradation_threshold must be between 0.0 and 1.0")
|
||||
|
||||
return (len(errors) == 0, errors)
|
||||
|
||||
|
||||
@dataclass
|
||||
class StrategyContext:
|
||||
"""Context for strategy routing decision."""
|
||||
tenant_id: str
|
||||
query: str
|
||||
metadata_filter: dict[str, Any] | None = None
|
||||
metadata_confidence: float = 1.0
|
||||
complexity_score: float = 0.0
|
||||
kb_ids: list[str] | None = None
|
||||
top_k: int = 5
|
||||
additional_context: dict[str, Any] = field(default_factory=dict)
|
||||
|
||||
|
||||
@dataclass
|
||||
class StrategyResult:
|
||||
"""Result from strategy routing."""
|
||||
strategy: StrategyType
|
||||
mode: RagRuntimeMode
|
||||
should_fallback: bool = False
|
||||
fallback_reason: str | None = None
|
||||
diagnostics: dict[str, Any] = field(default_factory=dict)
|
||||
|
|
@ -0,0 +1,233 @@
|
|||
"""
|
||||
Retrieval Strategy Integration for Dialogue Flow.
|
||||
[AC-AISVC-RES-01~15] Integrates StrategyRouter and ModeRouter into dialogue pipeline.
|
||||
|
||||
Usage:
|
||||
from app.services.retrieval.strategy_integration import RetrievalStrategyIntegration
|
||||
|
||||
integration = RetrievalStrategyIntegration()
|
||||
result = await integration.execute(ctx)
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import time
|
||||
from dataclasses import dataclass, field
|
||||
from typing import TYPE_CHECKING, Any
|
||||
|
||||
from app.services.retrieval.routing_config import (
|
||||
RagRuntimeMode,
|
||||
StrategyType,
|
||||
RoutingConfig,
|
||||
StrategyContext,
|
||||
StrategyResult,
|
||||
)
|
||||
from app.services.retrieval.strategy_router import (
|
||||
StrategyRouter,
|
||||
get_strategy_router,
|
||||
)
|
||||
from app.services.retrieval.mode_router import (
|
||||
ModeRouter,
|
||||
ModeRouteResult,
|
||||
get_mode_router,
|
||||
)
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from app.services.retrieval.base import RetrievalResult
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
@dataclass
|
||||
class RetrievalStrategyResult:
|
||||
"""Combined result from strategy and mode routing."""
|
||||
retrieval_result: "RetrievalResult | None"
|
||||
final_answer: str | None
|
||||
strategy: StrategyType
|
||||
mode: RagRuntimeMode
|
||||
should_fallback: bool = False
|
||||
fallback_reason: str | None = None
|
||||
mode_route_result: ModeRouteResult | None = None
|
||||
diagnostics: dict[str, Any] = field(default_factory=dict)
|
||||
duration_ms: int = 0
|
||||
|
||||
|
||||
class RetrievalStrategyIntegration:
|
||||
"""
|
||||
[AC-AISVC-RES-01~15] Integration layer for retrieval strategy.
|
||||
|
||||
Combines StrategyRouter and ModeRouter to provide a unified interface
|
||||
for the dialogue pipeline.
|
||||
|
||||
Flow:
|
||||
1. StrategyRouter selects default or enhanced strategy
|
||||
2. ModeRouter selects direct, react, or auto mode
|
||||
3. Execute retrieval with selected strategy and mode
|
||||
4. Handle fallback scenarios
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
config: RoutingConfig | None = None,
|
||||
strategy_router: StrategyRouter | None = None,
|
||||
mode_router: ModeRouter | None = None,
|
||||
):
|
||||
self._config = config or RoutingConfig()
|
||||
self._strategy_router = strategy_router or get_strategy_router()
|
||||
self._mode_router = mode_router or get_mode_router()
|
||||
|
||||
@property
|
||||
def config(self) -> RoutingConfig:
|
||||
"""Get current configuration."""
|
||||
return self._config
|
||||
|
||||
def update_config(self, new_config: RoutingConfig) -> None:
|
||||
"""
|
||||
[AC-AISVC-RES-15] Update all routing configurations.
|
||||
"""
|
||||
self._config = new_config
|
||||
self._strategy_router.update_config(new_config)
|
||||
self._mode_router.update_config(new_config)
|
||||
|
||||
logger.info(
|
||||
f"[AC-AISVC-RES-15] RetrievalStrategyIntegration config updated: "
|
||||
f"strategy={new_config.strategy.value}, mode={new_config.rag_runtime_mode.value}"
|
||||
)
|
||||
|
||||
async def execute(
|
||||
self,
|
||||
ctx: StrategyContext,
|
||||
) -> RetrievalStrategyResult:
|
||||
"""
|
||||
Execute retrieval with strategy and mode routing.
|
||||
|
||||
Args:
|
||||
ctx: Strategy context with tenant, query, metadata, etc.
|
||||
|
||||
Returns:
|
||||
RetrievalStrategyResult with retrieval results and diagnostics
|
||||
"""
|
||||
start_time = time.time()
|
||||
|
||||
strategy_result = self._strategy_router.route(ctx)
|
||||
|
||||
mode_result = self._mode_router.route(ctx)
|
||||
|
||||
logger.info(
|
||||
f"[AC-AISVC-RES-01~15] Strategy routing: "
|
||||
f"strategy={strategy_result.strategy.value}, mode={mode_result.mode.value}, "
|
||||
f"tenant={ctx.tenant_id}, query_len={len(ctx.query)}"
|
||||
)
|
||||
|
||||
retrieval_result = None
|
||||
final_answer = None
|
||||
should_fallback = False
|
||||
fallback_reason = None
|
||||
|
||||
try:
|
||||
if mode_result.mode == RagRuntimeMode.DIRECT:
|
||||
retrieval_result, answer, mode_result = await self._mode_router.execute_with_fallback(ctx)
|
||||
|
||||
if answer is not None:
|
||||
final_answer = answer
|
||||
should_fallback = mode_result.should_fallback_to_react
|
||||
fallback_reason = mode_result.fallback_reason
|
||||
|
||||
elif mode_result.mode == RagRuntimeMode.REACT:
|
||||
answer, retrieval_result, react_ctx = await self._mode_router.execute_react(ctx)
|
||||
final_answer = answer
|
||||
|
||||
else:
|
||||
retrieval_result, answer, mode_result = await self._mode_router.execute_with_fallback(ctx)
|
||||
|
||||
if answer is not None:
|
||||
final_answer = answer
|
||||
should_fallback = mode_result.should_fallback_to_react
|
||||
fallback_reason = mode_result.fallback_reason
|
||||
|
||||
except Exception as e:
|
||||
logger.error(
|
||||
f"[AC-AISVC-RES-07] Retrieval strategy execution failed: {e}"
|
||||
)
|
||||
|
||||
if strategy_result.strategy == StrategyType.ENHANCED:
|
||||
self._strategy_router.rollback(
|
||||
reason=str(e),
|
||||
tenant_id=ctx.tenant_id,
|
||||
)
|
||||
|
||||
from app.services.retrieval.optimized_retriever import get_optimized_retriever
|
||||
from app.services.retrieval.base import RetrievalContext
|
||||
|
||||
retriever = await get_optimized_retriever()
|
||||
retrieval_ctx = RetrievalContext(
|
||||
tenant_id=ctx.tenant_id,
|
||||
query=ctx.query,
|
||||
metadata_filter=ctx.metadata_filter,
|
||||
kb_ids=ctx.kb_ids,
|
||||
)
|
||||
retrieval_result = await retriever.retrieve(retrieval_ctx)
|
||||
|
||||
should_fallback = True
|
||||
fallback_reason = str(e)
|
||||
|
||||
else:
|
||||
raise
|
||||
|
||||
duration_ms = int((time.time() - start_time) * 1000)
|
||||
|
||||
return RetrievalStrategyResult(
|
||||
retrieval_result=retrieval_result,
|
||||
final_answer=final_answer,
|
||||
strategy=strategy_result.strategy,
|
||||
mode=mode_result.mode,
|
||||
should_fallback=should_fallback,
|
||||
fallback_reason=fallback_reason,
|
||||
mode_route_result=mode_result,
|
||||
diagnostics={
|
||||
"strategy_diagnostics": strategy_result.diagnostics,
|
||||
"mode_diagnostics": mode_result.diagnostics,
|
||||
"duration_ms": duration_ms,
|
||||
},
|
||||
duration_ms=duration_ms,
|
||||
)
|
||||
|
||||
def get_current_strategy(self) -> StrategyType:
|
||||
"""Get current active strategy."""
|
||||
return self._strategy_router.current_strategy
|
||||
|
||||
def get_rollback_records(self, limit: int = 10) -> list[dict[str, Any]]:
|
||||
"""Get recent rollback records."""
|
||||
records = self._strategy_router.get_rollback_records(limit)
|
||||
return [
|
||||
{
|
||||
"timestamp": r.timestamp,
|
||||
"from_strategy": r.from_strategy.value,
|
||||
"to_strategy": r.to_strategy.value,
|
||||
"reason": r.reason,
|
||||
"tenant_id": r.tenant_id,
|
||||
}
|
||||
for r in records
|
||||
]
|
||||
|
||||
def validate_config(self) -> tuple[bool, list[str]]:
|
||||
"""Validate current configuration."""
|
||||
return self._config.validate()
|
||||
|
||||
|
||||
_integration: RetrievalStrategyIntegration | None = None
|
||||
|
||||
|
||||
def get_retrieval_strategy_integration() -> RetrievalStrategyIntegration:
|
||||
"""Get or create RetrievalStrategyIntegration singleton."""
|
||||
global _integration
|
||||
if _integration is None:
|
||||
_integration = RetrievalStrategyIntegration()
|
||||
return _integration
|
||||
|
||||
|
||||
def reset_retrieval_strategy_integration() -> None:
|
||||
"""Reset RetrievalStrategyIntegration singleton (for testing)."""
|
||||
global _integration
|
||||
_integration = None
|
||||
|
|
@ -0,0 +1,403 @@
|
|||
"""
|
||||
Strategy Router for Retrieval and Embedding.
|
||||
[AC-AISVC-RES-01, AC-AISVC-RES-02, AC-AISVC-RES-03] Routes to default or enhanced strategy.
|
||||
|
||||
Key Features:
|
||||
- Default strategy preserves existing online logic
|
||||
- Enhanced strategy is configurable and can be rolled back
|
||||
- Supports grayscale release (percentage/allowlist)
|
||||
- Supports rollback on error or performance degradation
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import time
|
||||
from dataclasses import dataclass, field
|
||||
from typing import TYPE_CHECKING, Any
|
||||
|
||||
from app.services.retrieval.routing_config import (
|
||||
RagRuntimeMode,
|
||||
StrategyType,
|
||||
RoutingConfig,
|
||||
StrategyContext,
|
||||
StrategyResult,
|
||||
)
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from app.services.retrieval.base import RetrievalResult
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
@dataclass
|
||||
class RollbackRecord:
|
||||
"""Record for strategy rollback event."""
|
||||
timestamp: float
|
||||
from_strategy: StrategyType
|
||||
to_strategy: StrategyType
|
||||
reason: str
|
||||
tenant_id: str | None = None
|
||||
request_id: str | None = None
|
||||
|
||||
|
||||
class RollbackManager:
|
||||
"""
|
||||
[AC-AISVC-RES-07] Manages strategy rollback and audit logging.
|
||||
"""
|
||||
|
||||
def __init__(self, max_records: int = 100):
|
||||
self._records: list[RollbackRecord] = []
|
||||
self._max_records = max_records
|
||||
|
||||
def record_rollback(
|
||||
self,
|
||||
from_strategy: StrategyType,
|
||||
to_strategy: StrategyType,
|
||||
reason: str,
|
||||
tenant_id: str | None = None,
|
||||
request_id: str | None = None,
|
||||
) -> None:
|
||||
"""Record a rollback event."""
|
||||
record = RollbackRecord(
|
||||
timestamp=time.time(),
|
||||
from_strategy=from_strategy,
|
||||
to_strategy=to_strategy,
|
||||
reason=reason,
|
||||
tenant_id=tenant_id,
|
||||
request_id=request_id,
|
||||
)
|
||||
|
||||
self._records.append(record)
|
||||
|
||||
if len(self._records) > self._max_records:
|
||||
self._records = self._records[-self._max_records:]
|
||||
|
||||
logger.info(
|
||||
f"[AC-AISVC-RES-07] Rollback recorded: {from_strategy.value} -> {to_strategy.value}, "
|
||||
f"reason={reason}, tenant={tenant_id}"
|
||||
)
|
||||
|
||||
def get_recent_rollbacks(self, limit: int = 10) -> list[RollbackRecord]:
|
||||
"""Get recent rollback records."""
|
||||
return self._records[-limit:]
|
||||
|
||||
def get_rollback_count(self, since_timestamp: float | None = None) -> int:
|
||||
"""Get count of rollbacks, optionally since a timestamp."""
|
||||
if since_timestamp is None:
|
||||
return len(self._records)
|
||||
|
||||
return sum(1 for r in self._records if r.timestamp >= since_timestamp)
|
||||
|
||||
|
||||
class DefaultPipeline:
|
||||
"""
|
||||
[AC-AISVC-RES-01] Default pipeline that preserves existing online logic.
|
||||
|
||||
This pipeline uses the existing OptimizedRetriever without any new features.
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
self._retriever = None
|
||||
|
||||
async def execute(
|
||||
self,
|
||||
ctx: StrategyContext,
|
||||
) -> "RetrievalResult":
|
||||
"""
|
||||
Execute default retrieval strategy.
|
||||
|
||||
Uses existing OptimizedRetriever with current configuration.
|
||||
"""
|
||||
from app.services.retrieval.optimized_retriever import get_optimized_retriever
|
||||
from app.services.retrieval.base import RetrievalContext
|
||||
|
||||
if self._retriever is None:
|
||||
self._retriever = await get_optimized_retriever()
|
||||
|
||||
retrieval_ctx = RetrievalContext(
|
||||
tenant_id=ctx.tenant_id,
|
||||
query=ctx.query,
|
||||
metadata_filter=ctx.metadata_filter,
|
||||
kb_ids=ctx.kb_ids,
|
||||
)
|
||||
|
||||
return await self._retriever.retrieve(retrieval_ctx)
|
||||
|
||||
|
||||
class EnhancedPipeline:
|
||||
"""
|
||||
[AC-AISVC-RES-02] Enhanced pipeline with new end-to-end retrieval features.
|
||||
|
||||
Features:
|
||||
- Document preprocessing (cleaning/normalization)
|
||||
- Structured chunking (markdown/tables/FAQ)
|
||||
- Metadata generation and mounting
|
||||
- Embedding strategy (document/query prefix + Matryoshka)
|
||||
- Metadata inference and filtering (hard/soft filter)
|
||||
- Retrieval strategy (Dense + Keyword/Hybrid + RRF)
|
||||
- Optional reranking
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
config: RoutingConfig | None = None,
|
||||
):
|
||||
self._config = config or RoutingConfig()
|
||||
self._retriever = None
|
||||
|
||||
async def execute(
|
||||
self,
|
||||
ctx: StrategyContext,
|
||||
) -> "RetrievalResult":
|
||||
"""
|
||||
Execute enhanced retrieval strategy.
|
||||
|
||||
Uses OptimizedRetriever with enhanced configuration.
|
||||
"""
|
||||
from app.services.retrieval.optimized_retriever import OptimizedRetriever
|
||||
from app.services.retrieval.base import RetrievalContext
|
||||
|
||||
if self._retriever is None:
|
||||
self._retriever = OptimizedRetriever(
|
||||
two_stage_enabled=True,
|
||||
hybrid_enabled=True,
|
||||
)
|
||||
|
||||
retrieval_ctx = RetrievalContext(
|
||||
tenant_id=ctx.tenant_id,
|
||||
query=ctx.query,
|
||||
metadata_filter=ctx.metadata_filter,
|
||||
kb_ids=ctx.kb_ids,
|
||||
)
|
||||
|
||||
return await self._retriever.retrieve(retrieval_ctx)
|
||||
|
||||
|
||||
class StrategyRouter:
|
||||
"""
|
||||
[AC-AISVC-RES-01, AC-AISVC-RES-02, AC-AISVC-RES-03]
|
||||
Strategy router for retrieval and embedding.
|
||||
|
||||
Decision Flow:
|
||||
1. Check if enhanced strategy is enabled via configuration
|
||||
2. Check grayscale rules (percentage/allowlist)
|
||||
3. Route to appropriate pipeline (default/enhanced)
|
||||
4. Handle rollback on error or performance degradation
|
||||
|
||||
Constraints:
|
||||
- Default strategy MUST preserve existing online logic
|
||||
- Enhanced strategy MUST be configurable and rollback-able
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
config: RoutingConfig | None = None,
|
||||
rollback_manager: RollbackManager | None = None,
|
||||
):
|
||||
self._config = config or RoutingConfig()
|
||||
self._rollback_manager = rollback_manager or RollbackManager()
|
||||
self._default_pipeline = DefaultPipeline()
|
||||
self._enhanced_pipeline = EnhancedPipeline(self._config)
|
||||
|
||||
self._current_strategy = StrategyType.DEFAULT
|
||||
self._strategy_enabled = True
|
||||
|
||||
@property
|
||||
def current_strategy(self) -> StrategyType:
|
||||
"""Get current active strategy."""
|
||||
return self._current_strategy
|
||||
|
||||
@property
|
||||
def config(self) -> RoutingConfig:
|
||||
"""Get current configuration."""
|
||||
return self._config
|
||||
|
||||
def update_config(self, new_config: RoutingConfig) -> None:
|
||||
"""
|
||||
[AC-AISVC-RES-15] Update routing configuration (hot reload).
|
||||
|
||||
Args:
|
||||
new_config: New configuration to apply
|
||||
"""
|
||||
old_strategy = self._config.strategy
|
||||
self._config = new_config
|
||||
|
||||
logger.info(
|
||||
f"[AC-AISVC-RES-15] Routing config updated: "
|
||||
f"strategy={new_config.strategy.value}, "
|
||||
f"mode={new_config.rag_runtime_mode.value}, "
|
||||
f"grayscale={new_config.grayscale_percentage:.2%}"
|
||||
)
|
||||
|
||||
if old_strategy != new_config.strategy:
|
||||
logger.info(
|
||||
f"[AC-AISVC-RES-02] Strategy changed: {old_strategy.value} -> {new_config.strategy.value}"
|
||||
)
|
||||
|
||||
def route(
|
||||
self,
|
||||
ctx: StrategyContext,
|
||||
) -> StrategyResult:
|
||||
"""
|
||||
[AC-AISVC-RES-01, AC-AISVC-RES-02] Route to appropriate strategy.
|
||||
|
||||
Args:
|
||||
ctx: Strategy context with tenant, query, metadata, etc.
|
||||
|
||||
Returns:
|
||||
StrategyResult with selected strategy and mode
|
||||
"""
|
||||
if not self._strategy_enabled:
|
||||
logger.info("[AC-AISVC-RES-07] Strategy disabled, using default")
|
||||
return StrategyResult(
|
||||
strategy=StrategyType.DEFAULT,
|
||||
mode=self._config.rag_runtime_mode,
|
||||
should_fallback=False,
|
||||
diagnostics={"reason": "strategy_disabled"},
|
||||
)
|
||||
|
||||
use_enhanced = self._config.should_use_enhanced_strategy(ctx.tenant_id)
|
||||
|
||||
if use_enhanced:
|
||||
self._current_strategy = StrategyType.ENHANCED
|
||||
logger.info(
|
||||
f"[AC-AISVC-RES-02] Routing to ENHANCED strategy: tenant={ctx.tenant_id}"
|
||||
)
|
||||
else:
|
||||
self._current_strategy = StrategyType.DEFAULT
|
||||
logger.info(
|
||||
f"[AC-AISVC-RES-01] Routing to DEFAULT strategy: tenant={ctx.tenant_id}"
|
||||
)
|
||||
|
||||
return StrategyResult(
|
||||
strategy=self._current_strategy,
|
||||
mode=self._config.rag_runtime_mode,
|
||||
diagnostics={
|
||||
"grayscale_percentage": self._config.grayscale_percentage,
|
||||
"in_allowlist": ctx.tenant_id in self._config.grayscale_allowlist if ctx.tenant_id else False,
|
||||
},
|
||||
)
|
||||
|
||||
async def execute(
|
||||
self,
|
||||
ctx: StrategyContext,
|
||||
) -> tuple["RetrievalResult", StrategyResult]:
|
||||
"""
|
||||
Execute retrieval with strategy routing.
|
||||
|
||||
Args:
|
||||
ctx: Strategy context
|
||||
|
||||
Returns:
|
||||
Tuple of (RetrievalResult, StrategyResult)
|
||||
"""
|
||||
start_time = time.time()
|
||||
result = self.route(ctx)
|
||||
|
||||
try:
|
||||
if result.strategy == StrategyType.ENHANCED:
|
||||
retrieval_result = await self._enhanced_pipeline.execute(ctx)
|
||||
else:
|
||||
retrieval_result = await self._default_pipeline.execute(ctx)
|
||||
|
||||
duration_ms = int((time.time() - start_time) * 1000)
|
||||
|
||||
if duration_ms > self._config.performance_budget_ms:
|
||||
degradation = (duration_ms - self._config.performance_budget_ms) / self._config.performance_budget_ms
|
||||
if degradation > self._config.performance_degradation_threshold:
|
||||
logger.warning(
|
||||
f"[AC-AISVC-RES-08] Performance degradation detected: "
|
||||
f"duration={duration_ms}ms, budget={self._config.performance_budget_ms}ms, "
|
||||
f"degradation={degradation:.2%}"
|
||||
)
|
||||
|
||||
return retrieval_result, result
|
||||
|
||||
except Exception as e:
|
||||
logger.error(
|
||||
f"[AC-AISVC-RES-07] Strategy execution failed: {e}, "
|
||||
f"strategy={result.strategy.value}"
|
||||
)
|
||||
|
||||
if result.strategy == StrategyType.ENHANCED:
|
||||
self._rollback_manager.record_rollback(
|
||||
from_strategy=StrategyType.ENHANCED,
|
||||
to_strategy=StrategyType.DEFAULT,
|
||||
reason=str(e),
|
||||
tenant_id=ctx.tenant_id,
|
||||
)
|
||||
|
||||
logger.info("[AC-AISVC-RES-07] Falling back to DEFAULT strategy")
|
||||
|
||||
retrieval_result = await self._default_pipeline.execute(ctx)
|
||||
|
||||
return retrieval_result, StrategyResult(
|
||||
strategy=StrategyType.DEFAULT,
|
||||
mode=result.mode,
|
||||
should_fallback=True,
|
||||
fallback_reason=str(e),
|
||||
diagnostics=result.diagnostics,
|
||||
)
|
||||
|
||||
raise
|
||||
|
||||
def rollback(
|
||||
self,
|
||||
reason: str,
|
||||
tenant_id: str | None = None,
|
||||
request_id: str | None = None,
|
||||
) -> None:
|
||||
"""
|
||||
[AC-AISVC-RES-07] Force rollback to default strategy.
|
||||
|
||||
Args:
|
||||
reason: Reason for rollback
|
||||
tenant_id: Optional tenant ID for audit
|
||||
request_id: Optional request ID for audit
|
||||
"""
|
||||
if self._current_strategy == StrategyType.ENHANCED:
|
||||
self._rollback_manager.record_rollback(
|
||||
from_strategy=StrategyType.ENHANCED,
|
||||
to_strategy=StrategyType.DEFAULT,
|
||||
reason=reason,
|
||||
tenant_id=tenant_id,
|
||||
request_id=request_id,
|
||||
)
|
||||
|
||||
self._current_strategy = StrategyType.DEFAULT
|
||||
self._config.strategy = StrategyType.DEFAULT
|
||||
|
||||
logger.info(
|
||||
f"[AC-AISVC-RES-07] Rollback executed: reason={reason}, tenant={tenant_id}"
|
||||
)
|
||||
|
||||
def get_rollback_records(self, limit: int = 10) -> list[RollbackRecord]:
|
||||
"""Get recent rollback records."""
|
||||
return self._rollback_manager.get_recent_rollbacks(limit)
|
||||
|
||||
def validate_config(self) -> tuple[bool, list[str]]:
|
||||
"""
|
||||
[AC-AISVC-RES-06] Validate current configuration.
|
||||
|
||||
Returns:
|
||||
Tuple of (is_valid, list of error messages)
|
||||
"""
|
||||
return self._config.validate()
|
||||
|
||||
|
||||
_strategy_router: StrategyRouter | None = None
|
||||
|
||||
|
||||
def get_strategy_router() -> StrategyRouter:
|
||||
"""Get or create StrategyRouter singleton."""
|
||||
global _strategy_router
|
||||
if _strategy_router is None:
|
||||
_strategy_router = StrategyRouter()
|
||||
return _strategy_router
|
||||
|
||||
|
||||
def reset_strategy_router() -> None:
|
||||
"""Reset StrategyRouter singleton (for testing)."""
|
||||
global _strategy_router
|
||||
_strategy_router = None
|
||||
Loading…
Reference in New Issue