feat(flywheel): 抽公共 EmbeddingProvider 并新增 FewShotSample 模型

- 从 knowledge_rag_runtime 抽出 embedding 调用逻辑为独立 EmbeddingProvider，
  复用现有 HTTP 纯函数，RAG 路径零回归
- 新增 FewShotSample 表模型（样本池），注册到 db/base.py 和 models/__init__.py
  供 few-shot 飞轮沉淀已确认风险观测

server/src/app/models/__init__.py

@@ -8,6 +8,7 @@ from app.models.budget import BudgetAllocation, BudgetReservation, BudgetTransac
 from app.models.employee_change_log import EmployeeChangeLog
 from app.models.employee_behavior_profile import EmployeeBehaviorProfileSnapshot
 from app.models.employee import Employee
+from app.models.few_shot_sample import FewShotSample
 from app.models.financial_record import (
     AccountsPayableRecord,
     AccountsReceivableRecord,
@@ -49,6 +50,7 @@ __all__ = [
     "EmployeeChangeLog",
     "ExpenseClaim",
     "ExpenseClaimItem",
+    "FewShotSample",
     "HermesTaskConfig",
     "HermesTaskExecutionLog",
     "HermesRiskReport",

server/src/app/models/few_shot_sample.py

@@ -0,0 +1,54 @@
+from __future__ import annotations
+
+import uuid
+from datetime import datetime
+from typing import Any
+
+from sqlalchemy import DateTime, ForeignKey, Index, String, Text, func
+from sqlalchemy.orm import Mapped, mapped_column
+from sqlalchemy.types import JSON
+
+from app.db.base_class import Base
+
+
+class FewShotSample(Base):
+    """已确认的风险观测样本，供 few-shot 检索注入使用。
+
+    数据来源是 ``RiskObservation`` 上人工确认为 confirmed / false_positive 的观测，
+    入库后同时写一份向量到 Qdrant 的 ``few_shot_samples`` collection。
+    """
+
+    __tablename__ = "few_shot_samples"
+    __table_args__ = (
+        Index("ix_few_shot_samples_scene_label", "scene", "label"),
+        Index("ix_few_shot_samples_domain_risk_type", "domain", "risk_type"),
+    )
+
+    id: Mapped[str] = mapped_column(String(36), primary_key=True, default=lambda: str(uuid.uuid4()))
+    sample_key: Mapped[str] = mapped_column(String(160), unique=True, index=True)
+    source_observation_id: Mapped[str | None] = mapped_column(
+        ForeignKey("risk_observations.id"),
+        nullable=True,
+        index=True,
+    )
+
+    scene: Mapped[str] = mapped_column(String(50), default="risk_rule_generation", index=True)
+    domain: Mapped[str] = mapped_column(String(50), default="", index=True)
+    risk_type: Mapped[str] = mapped_column(String(80), default="", index=True)
+    risk_level: Mapped[str] = mapped_column(String(20), default="")
+
+    label: Mapped[str] = mapped_column(String(30), default="confirmed", index=True)
+    case_text: Mapped[str] = mapped_column(Text(), default="")
+    conclusion_text: Mapped[str] = mapped_column(Text(), default="")
+    payload_json: Mapped[dict[str, Any]] = mapped_column(JSON, default=dict)
+
+    vector_id: Mapped[str | None] = mapped_column(String(100), nullable=True)
+    status: Mapped[str] = mapped_column(String(20), default="active", index=True)
+
+    created_at: Mapped[datetime] = mapped_column(DateTime, default=func.now(), server_default=func.now())
+    updated_at: Mapped[datetime] = mapped_column(
+        DateTime,
+        default=func.now(),
+        onupdate=func.now(),
+        server_default=func.now(),
+    )