袁聪的第二次提交，项目已完整

app/service/agent/bootstrap.py

@@ -1,22 +1,109 @@
+import logging
 from functools import lru_cache
 from typing import Any, cast
 
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from app.core.config import get_settings
+from app.core.errors import RecoverableAgentError
 from app.core.fund_contracts import FundQuoteQuery
 from app.core.nl2sql_contracts import FinancialNL2SQLInput
+from app.infrastructure.fund_quote_cache import FundQuoteCache
+from app.infrastructure.memory_cache import MemoryCacheAdapter
+from app.infrastructure.vector_memory import VectorMemoryAdapter
 from app.service.agent.factory import AgentFactory
+from app.service.agent.governance import PlatformGovernance
 from app.service.agent.offsite_fund_agent import OffsiteFundAgent
+from app.service.agent.promotion_material_agent import PromotionMaterialAgent
 from app.service.financial_nl2sql_service import query_financial_data_tool
 from app.service.fund_quote_service import query_fund_quote_tool
 from app.service.intent_classifier import IntentClassifier
+from app.service.memory_recall_service import MemoryRecallService
 from app.service.model_gateway import (
     DatabaseModelEndpointResolver,
     DatabaseModelGateway,
     ModelDispatchService,
+    ModelEmbeddingService,
     ModelGenerationService,
 )
+from app.service.runtime_config_service import load_active_intent_configs
 from app.service.suitability_service import SuitabilityToolInput, suitability_tool_handler
 from app.service.tool_executor import ToolDefinition, ToolExecutor, ToolRegistry
 
+logger = logging.getLogger(__name__)
+
+
+@lru_cache(maxsize=1)
+def get_model_service() -> ModelGenerationService:
+    """模型生成的统一装配入口，HTTP 与 Worker 共用。"""
+    return ModelGenerationService(ModelDispatchService(DatabaseModelGateway()))
+
+
+@lru_cache(maxsize=1)
+def get_memory_cache_adapter() -> MemoryCacheAdapter | None:
+    """Redis 不可用时降级为无缓存，不能阻塞业务调用。"""
+    try:
+        from redis.asyncio import Redis
+
+        settings = get_settings()
+        client = Redis.from_url(
+            settings.redis_url,
+            socket_connect_timeout=settings.redis_connect_timeout_seconds,
+            socket_timeout=settings.redis_connect_timeout_seconds,
+            decode_responses=True,
+        )
+        return MemoryCacheAdapter(client)
+    except Exception:
+        logger.warning("memory cache adapter unavailable; recall runs without cache",
+                       exc_info=True)
+        return None
+
+
+@lru_cache(maxsize=1)
+def get_fund_quote_cache() -> FundQuoteCache | None:
+    """行情缓存与记忆缓存共用 Redis 连接配置，故障时透明降级。"""
+    adapter = get_memory_cache_adapter()
+    return FundQuoteCache(adapter) if adapter is not None else None
+
+
+@lru_cache(maxsize=1)
+def get_vector_memory_adapter() -> VectorMemoryAdapter | None:
+    """Milvus 语义召回适配器不可用时关闭语义通道，保留结构化召回。"""
+    try:
+        from pymilvus import MilvusClient  # type: ignore[import-untyped]
+
+        settings = get_settings()
+        client = MilvusClient(uri=settings.milvus_uri, token=settings.milvus_token or None)
+        return VectorMemoryAdapter(client, settings.milvus_collection)
+    except Exception:
+        logger.warning("vector memory adapter unavailable; semantic recall disabled",
+                       exc_info=True)
+        return None
+
+
+@lru_cache(maxsize=1)
+def get_memory_embedding_service() -> ModelEmbeddingService:
+    return ModelEmbeddingService(ModelDispatchService(DatabaseModelGateway()))
+
+
+async def _embed_text(text: str) -> list[float]:
+    endpoints = await DatabaseModelEndpointResolver().resolve(
+        agent_type="memory_recall", task_type="embedding"
+    )
+    if not endpoints:
+        raise RecoverableAgentError("没有可用的 embedding 端点")
+    return (await get_memory_embedding_service().embed(endpoints, text)).vector
+
+
+def build_memory_recall_service(session: AsyncSession) -> MemoryRecallService:
+    vector = get_vector_memory_adapter()
+    return MemoryRecallService(
+        session,
+        vector=vector,
+        cache=get_memory_cache_adapter(),
+        embed=_embed_text if vector is not None else None,
+    )
+
 
 @lru_cache(maxsize=1)
 def get_agent_factory() -> AgentFactory:
@@ -35,7 +122,7 @@ def get_agent_factory() -> AgentFactory:
         handler=cast(Any, query_fund_quote_tool),
         required_permission="fund:quote:read",
         allowed_roles=("customer", "advisor", "operator", "risk_operator", "admin"),
-        timeout_seconds=5,
+        timeout_seconds=15,
     ))
     registry.register(ToolDefinition(
         name="query_financial_data",
@@ -45,16 +132,29 @@ def get_agent_factory() -> AgentFactory:
         allowed_roles=("advisor", "operator", "admin", "super_admin"),
         timeout_seconds=10,
     ))
-    model_service = ModelGenerationService(ModelDispatchService(DatabaseModelGateway()))
+
+    model_service = get_model_service()
     endpoint_resolver = DatabaseModelEndpointResolver()
     factory = AgentFactory(
+        governance=PlatformGovernance(recall_factory=build_memory_recall_service),
         model_service=model_service,
         tool_executor=ToolExecutor(registry),
-        intent_classifier=IntentClassifier(model_service),
+        intent_classifier=IntentClassifier(
+            model_service, config_loader=load_active_intent_configs
+        ),
         intent_endpoint_resolver=endpoint_resolver,
     )
+    register_business_agents(factory)
+    return factory
+
+
+def register_business_agents(factory: AgentFactory) -> None:
+    """业务 Agent 仍由本项目统一注册，基座只负责提供公共治理链。"""
     factory.register(
         OffsiteFundAgent.definition,
         lambda _context: OffsiteFundAgent(OffsiteFundAgent.definition),
     )
-    return factory
+    factory.register(
+        PromotionMaterialAgent.definition,
+        lambda _context: PromotionMaterialAgent(PromotionMaterialAgent.definition),
+    )