feat:新增投顾agent和nl2sqlagent

service/advisor_agent/context.py

@@ -0,0 +1,177 @@
+"""从现有业务表聚合投顾意图所需的本地上下文。"""
+from __future__ import annotations
+
+from decimal import Decimal, InvalidOperation
+
+from common.common_const import (
+    CUSTOMER_REL_STATUS_SIGNED,
+    SYS_KEY_REBALANCE_DEVIATION_THRESHOLD,
+)
+from repositories.fin_customer_profile import FinCustomerProfileRepo
+from repositories.fin_holdings import FinHoldingsRepo
+from repositories.fin_product import FinProductRepo
+from repositories.portfolio_benchmark import PortfolioBenchmarkRepo
+from repositories.risk_assessment import RiskAssessmentRepo
+from repositories.sys_config import SysConfigRepo
+from model.fin_product import FinProduct
+from service.advisor_agent.data import to_holding_input, to_product_candidate
+from service.advisor_agent.data import to_fund_performance_row
+
+
+async def _load_customer_risk(db, customer_id: int, profile_repo_cls, risk_repo_cls):
+    assessment = await risk_repo_cls(db).get_current_by_customer(customer_id)
+    if assessment is not None and assessment.risk_level:
+        return assessment.risk_level
+    profile = await profile_repo_cls(db).get_by_customer_id(customer_id)
+    return profile.risk_level if profile is not None else None
+
+
+async def load_customer_risk(
+    db,
+    *,
+    customer_id: int,
+    profile_repo_cls=FinCustomerProfileRepo,
+    risk_repo_cls=RiskAssessmentRepo,
+) -> str | None:
+    return await _load_customer_risk(db, customer_id, profile_repo_cls, risk_repo_cls)
+
+
+async def load_rebalance_context(
+    db,
+    *,
+    customer_id: int,
+    profile_repo_cls=FinCustomerProfileRepo,
+    risk_repo_cls=RiskAssessmentRepo,
+    holdings_repo_cls=FinHoldingsRepo,
+    product_repo_cls=FinProductRepo,
+    benchmark_repo_cls=PortfolioBenchmarkRepo,
+    sys_config_repo_cls=SysConfigRepo,
+) -> dict | None:
+    """聚合画像、持仓、在售产品和组合基准，供调仓引擎使用。
+
+    关系签约状态由调用方读取并校验，本函数只负责客户投资数据。
+    """
+    customer_risk = await _load_customer_risk(
+        db, customer_id, profile_repo_cls, risk_repo_cls
+    )
+    if not customer_risk:
+        return None
+
+    benchmark = await benchmark_repo_cls(db).get_active_by_risk(customer_risk)
+    if benchmark is None:
+        return None
+
+    threshold = benchmark.drift_threshold
+    if threshold is None:
+        raw_threshold = await sys_config_repo_cls(db).get_value(
+            SYS_KEY_REBALANCE_DEVIATION_THRESHOLD
+        )
+        try:
+            threshold = Decimal(str(raw_threshold))
+        except (InvalidOperation, TypeError, ValueError):
+            return None
+        if not threshold.is_finite() or threshold < 0:
+            return None
+
+    product_repo = product_repo_cls(db)
+    products = await product_repo.list(
+        where=[FinProduct.status == "在售"],
+        limit=1000,
+    )
+    products_by_id = {product.id: product for product in products}
+
+    holdings = await holdings_repo_cls(db).list_by_customer(customer_id, status="持有中")
+    holding_inputs = []
+    for holding in holdings:
+        product = products_by_id.get(holding.product_id)
+        if product is None:
+            product = await product_repo.get(holding.product_id)
+        if product is not None:
+            holding_inputs.append(to_holding_input(holding, product))
+
+    return {
+        "customer_id": customer_id,
+        "customer_risk": customer_risk,
+        "relation_status": CUSTOMER_REL_STATUS_SIGNED,
+        "holdings": holding_inputs,
+        "target_allocation": benchmark.target_allocation,
+        "threshold": threshold,
+        "candidates": [to_product_candidate(product) for product in products],
+    }
+
+
+async def load_fund_analysis_context(
+    db,
+    *,
+    fund_codes: list[str],
+    product_repo_cls=FinProductRepo,
+    performance_repo_cls=None,
+) -> list[dict]:
+    if performance_repo_cls is None:
+        from repositories.fund_performance import FundPerformanceRepo
+
+        performance_repo_cls = FundPerformanceRepo
+
+    product_repo = product_repo_cls(db)
+    performance_repo = performance_repo_cls(db)
+    result = []
+    for code in fund_codes:
+        product = await product_repo.get_by_code(code)
+        if product is None:
+            continue
+        performance = await performance_repo.list_for_product(product.id)
+        result.append(
+            {
+                "fund": {
+                    "fund_code": product.product_code,
+                    "fund_name": product.product_name,
+                    "risk_level": product.risk_level,
+                },
+                "performance": [to_fund_performance_row(row) for row in performance],
+            }
+        )
+    return result
+
+
+async def load_recommendation_context(
+    db,
+    *,
+    customer_id: int,
+    profile_repo_cls=FinCustomerProfileRepo,
+    product_repo_cls=FinProductRepo,
+    performance_repo_cls=None,
+    risk_repo_cls=RiskAssessmentRepo,
+) -> dict | None:
+    customer_risk = await _load_customer_risk(
+        db, customer_id, profile_repo_cls, risk_repo_cls
+    )
+    if not customer_risk:
+        return None
+
+    products = await product_repo_cls(db).list(
+        where=[FinProduct.status == "在售"],
+        limit=1000,
+    )
+    if performance_repo_cls is None:
+        from repositories.fund_performance import FundPerformanceRepo
+
+        performance_repo_cls = FundPerformanceRepo
+    performance_repo = performance_repo_cls(db)
+    candidates = []
+    for product in products:
+        candidate = to_product_candidate(product)
+        latest = None
+        if hasattr(performance_repo, "get_latest_for_product"):
+            latest = await performance_repo.get_latest_for_product(product.id)
+        else:
+            rows = await performance_repo.list_for_product(product.id)
+            latest = rows[-1] if rows else None
+        return_rate = getattr(latest, "return_rate", None)
+        if return_rate is not None:
+            candidate["performance_score"] = float(return_rate)
+        candidates.append(candidate)
+    return {
+        "customer_id": customer_id,
+        "customer_risk": customer_risk,
+        "candidates": candidates,
+    }