feat(kb): Enhance knowledge base with new collections and search functionality
- Added new configuration for knowledge base root directory in `.env.example` and `settings.py`. - Implemented `find_products` method in `CoreReadOnlyRepository` for fuzzy product search based on user queries. - Introduced `search_cs_knowledge` function in `rag_service.py` to facilitate semantic search across new `fin_*` collections. - Updated document parsing to support Markdown and YAML front-matter for knowledge base entries. - Created multiple new FAQ and policy documents in the `data/kb_collections` directory to enrich the knowledge base. This update significantly improves the knowledge retrieval capabilities for customer service interactions, ensuring more relevant and accurate responses.
This commit is contained in:
@@ -21,6 +21,9 @@ NEO4J_PASSWORD=
|
||||
# 注意：路径含中文会触发 Milvus Lite(faiss) 文件 IO 失败，Windows 中文用户目录请改纯英文绝对路径
|
||||
MILVUS_URI=./data/milvus.db
|
||||
|
||||
# 客服 KB 第二套（fin_faq / fin_product / fin_policy 原料目录）
|
||||
KB_ROOT_DIR=./data/kb_collections
|
||||
|
||||
# Ollama Embedding
|
||||
OLLAMA_BASE_URL=http://127.0.0.1:11434
|
||||
EMBED_MODEL=bge-m3
|
||||
|
||||
@@ -38,6 +38,6 @@ app/repository/core_ro.py # Core 只读 + check_suitability（R-02）
|
||||
scripts/core/reset.ps1 # 本地灌 Core 模拟库
|
||||
```
|
||||
|
||||
**当前分支：** `merger` · **测试基线：** `python -m pytest` → 554 passed, 0 skipped
|
||||
**当前分支：** `merger` · **测试基线：** `python -m pytest` → 730 passed, 0 skipped
|
||||
|
||||
技术选型硬阀门见 MEMORY 第 3、7 节。Cursor 以 `.cursor/rules/project-memory.mdc` 为准。
|
||||
|
||||
@@ -24,6 +24,7 @@ class Settings(BaseSettings):
|
||||
neo4j_password: str = ""
|
||||
|
||||
milvus_uri: str = "./data/milvus.db"
|
||||
kb_root_dir: str = "./data/kb_collections"
|
||||
|
||||
ollama_base_url: str = "http://127.0.0.1:11434"
|
||||
embed_model: str = "bge-m3"
|
||||
|
||||
@@ -466,6 +466,24 @@ class CoreReadOnlyRepository:
|
||||
row = conn.execute(sql, {"pid": product_id}).mappings().first()
|
||||
return dict(row) if row else None
|
||||
|
||||
def find_products(self, keyword: str, limit: int = 3) -> list[dict[str, Any]]:
|
||||
"""按产品名称模糊匹配在售产品（客服适当性 Tool 用）。"""
|
||||
kw = (keyword or "").strip()
|
||||
if not kw:
|
||||
return []
|
||||
sql = text(
|
||||
"""
|
||||
SELECT * FROM core_product
|
||||
WHERE is_open = 1
|
||||
AND (product_name LIKE :pat OR product_id LIKE :pat)
|
||||
ORDER BY product_id
|
||||
LIMIT :lim
|
||||
"""
|
||||
)
|
||||
pat = f"%{kw}%"
|
||||
with self._engine.connect() as conn:
|
||||
return [dict(r) for r in conn.execute(sql, {"pat": pat, "lim": limit}).mappings()]
|
||||
|
||||
def get_latest_nav(self, product_id: str) -> dict[str, Any] | None:
|
||||
sql = text(
|
||||
"""
|
||||
|
||||
+41
-32
@@ -18,6 +18,7 @@ from __future__ import annotations
|
||||
from typing import Any
|
||||
|
||||
from app.service import embedding, milvus_service
|
||||
from app.tool.milvus_tool import get_milvus_client
|
||||
|
||||
# 对外默认 TopK（对话 Tool 引用；脚本/服务可显式覆盖）
|
||||
DEFAULT_TOP_K = 3
|
||||
@@ -78,44 +79,52 @@ def search_knowledge(
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# 客服线 · 游客/客户 RAG 接缝（映射 T-21 search_knowledge，不另建 collection）
|
||||
# 客服线 · fin_* 三库 RAG（build_collections.py · 与 kb_product_rules 并存）
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
_VISITOR_INTENT_DOC_TYPE: dict[str, str | None] = {
|
||||
"product_consult": None,
|
||||
"policy_interpret": "policy",
|
||||
"faq": "faq",
|
||||
_CS_INTENT_COLLECTION: dict[str, str] = {
|
||||
"product_consult": "fin_product",
|
||||
"policy_interpret": "fin_policy",
|
||||
"faq": "fin_faq",
|
||||
}
|
||||
|
||||
|
||||
def search_cs_knowledge(intent: str, query: str, top_k: int = 5) -> tuple[str, list[dict]]:
|
||||
"""客服/游客 RAG：按意图选 fin_* collection 语义检索。"""
|
||||
collection = _CS_INTENT_COLLECTION.get(intent)
|
||||
if not collection or not query or not query.strip():
|
||||
return "", []
|
||||
try:
|
||||
vector = _embed(query.strip())
|
||||
client = get_milvus_client()
|
||||
try:
|
||||
hits = client.search(collection, vector, top_k=top_k)
|
||||
finally:
|
||||
client.close()
|
||||
except Exception:
|
||||
return "", []
|
||||
if not hits:
|
||||
return "", []
|
||||
context_parts: list[str] = []
|
||||
sources: list[dict] = []
|
||||
for i, hit in enumerate(hits, 1):
|
||||
chunk_text = hit.get("chunk_text") or ""
|
||||
source_doc = hit.get("source_doc") or hit.get("id") or ""
|
||||
context_parts.append(f"[来源: {source_doc} | 片段 {i}]\n{chunk_text}")
|
||||
sources.append(
|
||||
{
|
||||
"source_doc": source_doc,
|
||||
"chunk_no": hit.get("chunk_no", i),
|
||||
"score": round(float(hit.get("score", 0.0)), 4),
|
||||
}
|
||||
)
|
||||
return "\n\n".join(context_parts), sources
|
||||
|
||||
|
||||
class VisitorRagService:
|
||||
"""游客/客户 RAG：intent → search_knowledge → 上下文 + 溯源。"""
|
||||
"""游客/客户 RAG：intent → fin_* Milvus 检索 + 溯源。"""
|
||||
|
||||
def retrieve(self, intent: str, query: str, top_k: int = 5) -> tuple[str, list[dict]]:
|
||||
if intent not in _VISITOR_INTENT_DOC_TYPE:
|
||||
if intent not in _CS_INTENT_COLLECTION:
|
||||
return "", []
|
||||
try:
|
||||
payload = search_knowledge(
|
||||
query,
|
||||
doc_type=_VISITOR_INTENT_DOC_TYPE[intent],
|
||||
top_k=top_k,
|
||||
)
|
||||
except Exception:
|
||||
return "", []
|
||||
hits = payload.get("results") or []
|
||||
if not hits:
|
||||
return "", []
|
||||
context_parts: list[str] = []
|
||||
sources: list[dict] = []
|
||||
for i, hit in enumerate(hits, 1):
|
||||
chunk_text = hit.get("chunk_text") or hit.get("text") or ""
|
||||
source_doc = hit.get("source_doc_id") or hit.get("source_doc") or ""
|
||||
context_parts.append(f"[来源: {source_doc} | 片段 {i}]\n{chunk_text}")
|
||||
sources.append(
|
||||
{
|
||||
"source_doc": source_doc,
|
||||
"chunk_no": hit.get("chunk_no", i),
|
||||
"score": round(float(hit.get("score", 0.0)), 4),
|
||||
}
|
||||
)
|
||||
return "\n\n".join(context_parts), sources
|
||||
return search_cs_knowledge(intent, query, top_k=top_k)
|
||||
|
||||
@@ -103,12 +103,18 @@ _REJECT_REALTIME_KW = (
|
||||
|
||||
|
||||
def recall_memory(state: VisitorState) -> VisitorState:
|
||||
"""节点 1：从 Redis 读取两类短期记忆。"""
|
||||
"""节点 1：从 Redis 读取两类短期记忆（Redis 不可用则降级为空）。"""
|
||||
mem = VisitorMemoryService()
|
||||
sid = state["session_id"]
|
||||
try:
|
||||
chitchat_memory = mem.recall(sid, "chitchat")
|
||||
consult_memory = mem.recall(sid, "consult")
|
||||
except Exception:
|
||||
chitchat_memory = []
|
||||
consult_memory = []
|
||||
return {
|
||||
"chitchat_memory": mem.recall(sid, "chitchat"),
|
||||
"consult_memory": mem.recall(sid, "consult"),
|
||||
"chitchat_memory": chitchat_memory,
|
||||
"consult_memory": consult_memory,
|
||||
}
|
||||
|
||||
|
||||
@@ -257,7 +263,7 @@ def fallback(state: VisitorState) -> VisitorState:
|
||||
|
||||
|
||||
def save_memory(state: VisitorState) -> VisitorState:
|
||||
"""节点 8：保存短期记忆（先写 user，再写 assistant）。"""
|
||||
"""节点 8：保存短期记忆（先写 user，再写 assistant；Redis 失败不阻断）。"""
|
||||
mem = VisitorMemoryService()
|
||||
sid = state["session_id"]
|
||||
intent = state.get("intent", "fallback")
|
||||
@@ -268,8 +274,11 @@ def save_memory(state: VisitorState) -> VisitorState:
|
||||
else:
|
||||
kind = "chitchat"
|
||||
|
||||
mem.append(sid, kind, "user", state["message"])
|
||||
mem.append(sid, kind, "assistant", state["reply"])
|
||||
try:
|
||||
mem.append(sid, kind, "user", state["message"])
|
||||
mem.append(sid, kind, "assistant", state["reply"])
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
return {}
|
||||
|
||||
|
||||
@@ -1 +1,65 @@
|
||||
"""文档解析：PDF/Word → 文本块（本地 data/kb/，不用 MinIO）。"""
|
||||
"""文档解析：Markdown + YAML front-matter → Chunk（客服 fin_* 知识库目录）。"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import re
|
||||
from dataclasses import dataclass, field
|
||||
from pathlib import Path
|
||||
from typing import Any
|
||||
|
||||
FRONT_MATTER_RE = re.compile(r"^---\s*\n(?P<body>.*?)\n---\s*\n", re.DOTALL)
|
||||
|
||||
|
||||
@dataclass
|
||||
class Chunk:
|
||||
chunk_id: str
|
||||
text: str
|
||||
metadata: dict[str, Any] = field(default_factory=dict)
|
||||
|
||||
|
||||
def _parse_front_matter(text: str) -> tuple[dict[str, str], str]:
|
||||
match = FRONT_MATTER_RE.match(text)
|
||||
if not match:
|
||||
return {}, text.strip()
|
||||
meta: dict[str, str] = {}
|
||||
for line in match.group("body").splitlines():
|
||||
line = line.strip()
|
||||
if not line or line.startswith("#") or ":" not in line:
|
||||
continue
|
||||
key, _, value = line.partition(":")
|
||||
meta[key.strip()] = value.strip()
|
||||
return meta, text[match.end() :].strip()
|
||||
|
||||
|
||||
def _slug(value: str, fallback: str) -> str:
|
||||
cleaned = re.sub(r"[^A-Za-z0-9._-]+", "-", (value or fallback).strip())[:48]
|
||||
return cleaned or fallback
|
||||
|
||||
|
||||
def _parse_markdown_file(path: Path, chunk_no: int) -> Chunk:
|
||||
raw = path.read_text(encoding="utf-8")
|
||||
meta, body = _parse_front_matter(raw)
|
||||
source_doc = meta.get("source_doc") or path.stem
|
||||
chunk_text = body or meta.get("answer") or meta.get("question") or path.stem
|
||||
text = chunk_text
|
||||
if meta.get("question") and meta.get("answer"):
|
||||
text = f"{meta['question']}\n{meta['answer']}"
|
||||
elif meta.get("question"):
|
||||
text = f"{meta['question']}\n{chunk_text}"
|
||||
|
||||
record_meta = dict(meta)
|
||||
record_meta.setdefault("source_doc", source_doc)
|
||||
record_meta["chunk_no"] = str(chunk_no)
|
||||
record_meta["chunk_text"] = chunk_text
|
||||
|
||||
chunk_id = f"{_slug(source_doc, path.stem)}_{chunk_no}"
|
||||
return Chunk(chunk_id=chunk_id, text=text, metadata=record_meta)
|
||||
|
||||
|
||||
def parse_collection_dir(dir_path: Path) -> tuple[list[Chunk], dict[str, Any]]:
|
||||
"""解析目录下全部 ``*.md``，每文件 1 块（chunk_no 从 1 递增）。"""
|
||||
if not dir_path.is_dir():
|
||||
return [], {"file_count": 0}
|
||||
files = sorted(dir_path.glob("*.md"))
|
||||
chunks = [_parse_markdown_file(path, i + 1) for i, path in enumerate(files)]
|
||||
return chunks, {"file_count": len(files)}
|
||||
|
||||
@@ -1 +1,22 @@
|
||||
"""向量化：Ollama bge-m3，1024 维。"""
|
||||
"""向量化：Ollama bge-m3，1024 维（客服 KB 灌库 / fin_* 检索用）。
|
||||
|
||||
薄封装 `app.service.embedding`，与 T-21 共用同一 Ollama 配置。
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from app.service import embedding
|
||||
|
||||
|
||||
class Embedder:
|
||||
"""批量/单条 embedding（build_collections / test_search 调用面）。"""
|
||||
|
||||
def embed(self, text: str) -> list[float]:
|
||||
return embedding.embed_text(text)
|
||||
|
||||
def embed_batch(self, texts: list[str]) -> list[list[float]]:
|
||||
return embedding.embed_texts(texts)
|
||||
|
||||
|
||||
def get_embedder() -> Embedder:
|
||||
return Embedder()
|
||||
|
||||
+103
-1
@@ -1 +1,103 @@
|
||||
"""Milvus 封装：Milvus Lite 连接、Collection CRUD、语义检索。"""
|
||||
"""Milvus 封装：Milvus Lite 连接、fin_* Collection CRUD、语义检索（客服 KB 第二套）。"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import Any
|
||||
|
||||
from app.config.settings import settings
|
||||
from app.service import milvus_service
|
||||
from pymilvus import DataType # noqa: E402 milvus_service 已做 MILVUS_URI 环境防御
|
||||
|
||||
# build_collections.py 与检索共用
|
||||
COLLECTION_FIELDS: dict[str, list[str]] = {
|
||||
"fin_faq": ["question", "answer", "category", "source_doc", "chunk_no", "chunk_text"],
|
||||
"fin_product": ["product_name", "risk_level", "doc_type", "source_doc", "chunk_no", "chunk_text"],
|
||||
"fin_policy": ["policy_name", "chapter", "source_doc", "chunk_no", "chunk_text"],
|
||||
}
|
||||
|
||||
_VARCHAR_MAX = {
|
||||
"question": 512,
|
||||
"answer": 2048,
|
||||
"category": 64,
|
||||
"product_name": 256,
|
||||
"risk_level": 8,
|
||||
"doc_type": 32,
|
||||
"policy_name": 256,
|
||||
"chapter": 128,
|
||||
"source_doc": 128,
|
||||
"chunk_text": 8192,
|
||||
}
|
||||
|
||||
|
||||
def _schema_for(collection: str, dim: int):
|
||||
fields = COLLECTION_FIELDS[collection]
|
||||
schema = milvus_service.MilvusClient.create_schema(auto_id=False, enable_dynamic_field=False)
|
||||
schema.add_field("id", DataType.VARCHAR, is_primary=True, max_length=64)
|
||||
schema.add_field("embedding", DataType.FLOAT_VECTOR, dim=dim)
|
||||
for name in fields:
|
||||
if name == "chunk_no":
|
||||
schema.add_field(name, DataType.INT64)
|
||||
else:
|
||||
schema.add_field(name, DataType.VARCHAR, max_length=_VARCHAR_MAX.get(name, 256))
|
||||
return schema
|
||||
|
||||
|
||||
class MilvusKbClient:
|
||||
"""fin_faq / fin_product / fin_policy 三库客户端。"""
|
||||
|
||||
def __init__(self, client: milvus_service.MilvusClient | None = None) -> None:
|
||||
self._client = client or milvus_service.milvus_client()
|
||||
|
||||
def ensure_collection(self, name: str) -> None:
|
||||
if name not in COLLECTION_FIELDS:
|
||||
raise ValueError(f"unknown collection: {name}")
|
||||
dim = settings.embed_dim
|
||||
if self._client.has_collection(name):
|
||||
self._client.load_collection(name)
|
||||
return
|
||||
index = self._client.prepare_index_params()
|
||||
index.add_index(field_name="embedding", index_type="AUTOINDEX", metric_type="COSINE")
|
||||
self._client.create_collection(name, schema=_schema_for(name, dim), index_params=index)
|
||||
self._client.load_collection(name)
|
||||
|
||||
def drop_collection(self, name: str) -> None:
|
||||
if self._client.has_collection(name):
|
||||
self._client.drop_collection(name)
|
||||
|
||||
def insert(self, name: str, records: list[dict[str, Any]]) -> int:
|
||||
if not records:
|
||||
return 0
|
||||
self.ensure_collection(name)
|
||||
self._client.upsert(name, data=records)
|
||||
return len(records)
|
||||
|
||||
def search(self, name: str, vector: list[float], top_k: int = 3) -> list[dict[str, Any]]:
|
||||
if not self._client.has_collection(name):
|
||||
return []
|
||||
self._client.load_collection(name)
|
||||
output_fields = list(COLLECTION_FIELDS[name])
|
||||
results = self._client.search(
|
||||
name,
|
||||
data=[vector],
|
||||
limit=top_k,
|
||||
output_fields=output_fields,
|
||||
)
|
||||
hits = results[0] if results else []
|
||||
out: list[dict[str, Any]] = []
|
||||
for hit in hits:
|
||||
entity = hit.get("entity", {})
|
||||
out.append(
|
||||
{
|
||||
"id": hit.get("id"),
|
||||
"score": float(hit.get("distance", 0.0)),
|
||||
**entity,
|
||||
}
|
||||
)
|
||||
return out
|
||||
|
||||
def close(self) -> None:
|
||||
self._client.close()
|
||||
|
||||
|
||||
def get_milvus_client() -> MilvusKbClient:
|
||||
return MilvusKbClient()
|
||||
|
||||
@@ -0,0 +1,8 @@
|
||||
---
|
||||
question: 开户需要准备哪些材料？
|
||||
answer: 需要有效身份证件、本人银行卡，并完成实名认证与风险测评问卷。线上开户还需手机号验证与人脸识别。
|
||||
category: 开户
|
||||
source_doc: faq-open-account
|
||||
---
|
||||
|
||||
开户需要有效身份证件、本人银行卡，并完成实名认证与风险测评问卷。
|
||||
@@ -0,0 +1,8 @@
|
||||
---
|
||||
question: 赎回资金多久到账？
|
||||
answer: 货币基金一般 T+1 个工作日到账；股票型、混合型产品通常为 T+3 至 T+5 个工作日，具体以产品说明书为准。
|
||||
category: 交易
|
||||
source_doc: faq-redeem-settlement
|
||||
---
|
||||
|
||||
赎回资金到账时间因产品类型而异，请以产品说明书与交易确认信息为准。
|
||||
@@ -0,0 +1,8 @@
|
||||
---
|
||||
question: App 忘记登录密码怎么办？
|
||||
answer: 可在登录页选择「忘记密码」，通过绑定的手机号或邮箱接收验证码后重置。若手机号已变更，请联系客服或到网点办理。
|
||||
category: 账户操作
|
||||
source_doc: faq-reset-password
|
||||
---
|
||||
|
||||
可在登录页选择「忘记密码」，通过绑定的手机号或邮箱接收验证码后重置密码。
|
||||
@@ -0,0 +1,7 @@
|
||||
---
|
||||
policy_name: 反洗钱客户身份识别
|
||||
chapter: KYC
|
||||
source_doc: policy-aml-kyc
|
||||
---
|
||||
|
||||
反洗钱要求：开立账户或办理一定金额以上交易时，须核实客户身份、受益所有人，并持续监测可疑交易。命中名单或异常模式须按规定上报。
|
||||
@@ -0,0 +1,7 @@
|
||||
---
|
||||
policy_name: 销售合规与投诉处理
|
||||
chapter: 投诉处理
|
||||
source_doc: policy-complaint
|
||||
---
|
||||
|
||||
客户投诉应在受理后按规定时限调查并反馈。涉及销售误导、适当性争议的，须留存录音录像与适当性匹配记录备查。
|
||||
@@ -0,0 +1,7 @@
|
||||
---
|
||||
policy_name: 投资者适当性管理指引
|
||||
chapter: 适当性匹配
|
||||
source_doc: policy-suitability-match
|
||||
---
|
||||
|
||||
投资者适当性匹配规则：客户风险承受能力等级 C1~C5 须与产品风险等级 R1~R5 相匹配，客户只能购买风险等级不超过自身承受能力的产品。销售机构须做好双录与风险提示。
|
||||
@@ -0,0 +1,8 @@
|
||||
---
|
||||
product_name: 均衡配置混合
|
||||
risk_level: R3
|
||||
doc_type: rule
|
||||
source_doc: prod-balanced-r3
|
||||
---
|
||||
|
||||
均衡配置混合（R3）股债均衡，适合稳健型（C3）及以上客户。申购 T 日 15:00 前按当日净值确认，赎回一般 T+3 至 T+4 个工作日到账。
|
||||
@@ -0,0 +1,8 @@
|
||||
---
|
||||
product_name: 稳健货币A
|
||||
risk_level: R1
|
||||
doc_type: prospectus
|
||||
source_doc: prod-money-market-r1
|
||||
---
|
||||
|
||||
稳健货币A（R1）为货币市场型基金，风险等级 R1，流动性较好，适合保守型（C1）及以上客户作为现金管理工具。不保本不保收益。
|
||||
@@ -0,0 +1,8 @@
|
||||
---
|
||||
product_name: 科技成长主题
|
||||
risk_level: R4
|
||||
doc_type: prospectus
|
||||
source_doc: prod-tech-growth-r4
|
||||
---
|
||||
|
||||
科技成长主题（R4）为股票型主题基金，聚焦半导体、人工智能、云计算等方向。适合积极型（C4）及以上客户，短期波动较大，建议以 3 年以上资金参与。
|
||||
@@ -9,7 +9,7 @@
|
||||
|
||||
**项目是什么：** 金融四 Agent（客户财富 / 代理人 / 数据分析 / 风控）共用数据层与合规底座；**不**互调 LLM，跨 Agent 走 L1/L2/L3 画像与预警表。
|
||||
|
||||
**当前进度：** 需求与表设计已定 · **风控模块 B1~B9b + C4~C6 + chat B/C + AL-09 合并** · **代销平台 API v0.1 已落地** · **客服 Agent S2 接缝已接线**（visitor 试聊 + customer 并行分流） · **554 passed 0 skipped** · **`web/` 静奢智能 UI 已落地** · **`npm run build/test/lint` 绿（14 例 Vitest）**。**下一步：ChatPanel/SSE · 迁移 SQL CS-C-11 · Wave 1/2/4/5 解禁。**
|
||||
**当前进度：** 需求与表设计已定 · **风控模块 B1~B9b + C4~C6 + chat B/C + AL-09 合并** · **代销平台 API v0.1 已落地** · **客服 Agent S2 接缝收尾**（visitor 试聊 + customer 并行分流 · Wave 1~5 测试绿 · CS-C-11 迁移已执行） · **730 passed 0 skipped** · **`web/` 静奢智能 UI 已落地** · **`npm run build/test/lint` 绿（14 例 Vitest）**。**下一步：ChatPanel/SSE · 前端 customer Chat。**
|
||||
|
||||
**工作分支：** 团队开发在 **`merger`**（已 merge 风控模块）；历史开发分支 `risk-control-agent` 交付冻结。旧文档中「待 AL-09 合并」口径已过时。
|
||||
|
||||
@@ -41,7 +41,7 @@
|
||||
| `scripts/core/*.sql` + `reset.ps1` | **已实现** | Core 模拟库 DDL + 种子 |
|
||||
| `scripts/agent/` `scripts/demo/` `scripts/dev/` | **已实现** | AML 名单种子 + 风控演示数据 + `fix_utf8_seed.py`/`run_sql_file.py`（Windows UTF-8 灌库）+ issue_dev_token |
|
||||
| `scripts/sync/*.py` | **已实现** | 归属同步 + Neo4j 全图 |
|
||||
| `tests/` | **已实现** | 37+ 测试模块 **554 用例 0 skipped**（含 `test_wave3_customer_service`；sqlite + 真 MySQL 集成；`test_module_boundary` 宿主 D 类排除）。改路由必同步 `tests/test_main.py::test_all_routers_mounted` |
|
||||
| `tests/` | **已实现** | 37+ 测试模块 **730 用例 0 skipped**（含客服 Wave 1~5；sqlite + 真 MySQL 集成；`test_module_boundary` 宿主 D 类排除）。改路由必同步 `tests/test_main.py::test_all_routers_mounted` |
|
||||
| `docs/需求拆解/` | 已定 | 场景 P0、矩阵、合规原文 |
|
||||
| `docs/PRD/PRD-风控监测Agent.md` | **已冻结（v1.1）** | 风控 PRD v1.0 + v1.1 追加 FR-8/9/10（§4A）+ 规则表附录 |
|
||||
| `docs/项目框架设计/实现方案-风控追加需求v1.1-C4C6.md` | **已定稿** | C4~C6 编码依据（经独立 AI 评审修订闭环）；分支/进度速览另见项目根 `交接文档.md` |
|
||||
@@ -65,7 +65,7 @@
|
||||
5. mysql … < scripts/agent/seed-aml-list.sql # AML 名单（Windows 乱码：`python scripts/dev/fix_utf8_seed.py`）
|
||||
（风控演示：scripts/demo/prepare_risk_demo.sql，reset 后重跑）
|
||||
6. python scripts/sync/sync_advisor_rel.py && python scripts/sync/sync_neo4j.py
|
||||
7. uvicorn app.main:app --reload → GET /health；`docker compose up -d redis`（限流/会话窗口）；python -m pytest（**554 绿**，系统 Python 3.13.14）
|
||||
7. uvicorn app.main:app --reload → GET /health；`docker compose up -d redis`（限流/会话窗口）；python -m pytest（**730 绿**，系统 Python 3.13.14）
|
||||
```
|
||||
|
||||
**AL-09 合并后架构（一句话）：** 宿主 `gateway/` + 模块 `deps.py` **双栈并存**；对外登录/token **统一**；chat/risk 均走模块鉴权；接缝 S2 用 `auth_adapter`。
|
||||
@@ -157,7 +157,7 @@ Core 模拟：scripts/core/reset.ps1 · 文档 docs/项目框架设计/Core模
|
||||
种子：scripts/agent/seed-aml-list.sql（AML 名单）· scripts/demo/prepare_risk_demo.sql（reset 后重跑）
|
||||
依赖：requirements.txt（LangGraph + langchain-core/openai + FastAPI + SQLAlchemy）
|
||||
启动：uvicorn app.main:app --reload → GET /health
|
||||
测试：python -m pytest（**554 绿**；集成测试需本机 MySQL + `risk_aml_list` + `prepare_risk_demo.sql`）
|
||||
测试：python -m pytest（**730 绿**；集成测试需本机 MySQL + `risk_aml_list` + `prepare_risk_demo.sql`）
|
||||
运维/演示脚本：scripts/demo/subscribe_alerts.py（订阅推送演示）· rebuild_alerts.py TRD-xxx（引擎异常补偿重放）
|
||||
JWT 联调：python scripts/dev/issue_dev_token.py --sub STAFF-30001 --roles risk_officer（+ Authorization: Bearer + X-Agent-Type）
|
||||
配置：.env（见 .env.example）
|
||||
@@ -205,6 +205,6 @@ RBAC 联调账号：scripts/dev/rbac-seed-reference.md
|
||||
2. 改动属于 api / service / tool / repository 哪一层？
|
||||
3. 是否需 customer_id 归属与 JWT RBAC？
|
||||
4. Core 是模拟库只读还是 agent 库读写？
|
||||
5. 如何验证？（`python -m pytest` 全量（当前 **554 绿**）· `docker compose up -d redis` · uvicorn + /health · 平台 `/api/customers/*` · `tests/test_module_boundary.py` 全绿）
|
||||
5. 如何验证？（`python -m pytest` 全量（当前 **730 绿**）· `docker compose up -d redis` · uvicorn + /health · 平台 `/api/customers/*` · `tests/test_module_boundary.py` 全绿）
|
||||
|
||||
大任务：FRAMEWORK/FLOW 与实现状态不符时先更新 memory 再编码（用户确认跳过除外）。
|
||||
|
||||
+11
-3
@@ -37,12 +37,20 @@
|
||||
|
||||
> 清单：`docs/项目框架设计/客服Agent-合并说明.md` §3–§4 · 原则只增不盖、不覆盖 `main.py`/`chat.py`/`agent_service.py` 整体。
|
||||
|
||||
- [ ] **跑迁移 SQL**：`scripts/agent/migrate-customer-agent-cs-c11.sql`（`conversation_archive` · `customer_notes`）
|
||||
- [x] **跑迁移 SQL**：`scripts/agent/migrate-customer-agent-cs-c11.sql`（`conversation_archive` · `customer_notes`）（2026-09-09 本机已执行）
|
||||
- [x] **挂游客路由**：`POST /api/chat/visitor` → `main.py`
|
||||
- [x] **编排接缝（并行）**：`X-Agent-Type: customer` → `customer_service.run_customer_chat`；其余 Agent 仍 `agent_service.chat`
|
||||
- [x] **Wave 3 测试解禁**：`test_wave3_customer_service.py` 19 例绿 · 基线 **554 passed**
|
||||
- [ ] **Wave 1/2/4/5 解禁**：`tests/conftest.py` 移出剩余 `collect_ignore` · 修接缝后全 wave 绿
|
||||
- [ ] **可选接线**：`profile_service` / `note_service` / 客服 KB 脚本与 Milvus 集合（`scripts/kb/*`）— 按需求择项
|
||||
- [x] **Wave 1/2 解禁**：`test_wave1_*` · `test_wave2_*` 已移出 `collect_ignore` 并绿（132+ 例）
|
||||
- [x] **Wave 3 profile / 4 / 5 解禁**：`test_wave3_profile_service` · `test_wave4_e2e` · `test_wave5_notes` · 基线 **730 passed**
|
||||
- [x] **客服 KB 第二套（fin_*）· Ollama 灌库**（2026-09-09 本机）：
|
||||
1. `ollama pull bge-m3` ✓
|
||||
2. Ollama 服务 `http://127.0.0.1:11434` ✓
|
||||
3. **Windows**：`MILVUS_URI` 须英文绝对路径（如 `C:/Users/Windows/.jinrong/milvus/milvus.db`），中文项目路径 faiss 会炸
|
||||
4. `python scripts/kb/build_collections.py --rebuild`（原料 `data/kb_collections/`）✓ 9 块
|
||||
5. `python scripts/kb/test_search.py` ✓
|
||||
- [x] **客服 RAG 接 fin_* 三库**：`VisitorRagService` → `search_cs_knowledge`（`fin_product` / `fin_policy` / `fin_faq`）；宿主 Tool 仍走 `kb_product_rules`（T-21）
|
||||
- [x] **tool 层实现 + 种子文档**：`document_parser` / `embedding_tool` / `milvus_tool` + `data/kb_collections/*`（2026-09-09）
|
||||
|
||||
### 风控 Agent · 后端已就绪 · 前端/运维未接（盘点 2026-09-09）
|
||||
|
||||
|
||||
@@ -66,17 +66,23 @@ scripts/agent/migrate-customer-agent-cs-c11.sql
|
||||
|
||||
**仍待手工：**
|
||||
|
||||
- 执行 `scripts/agent/migrate-customer-agent-cs-c11.sql`（`conversation_archive` · `customer_notes`）
|
||||
- Wave 1/2/4/5 测试仍 `collect_ignore`，逐步解禁
|
||||
- 本机真跑服务：`docker compose up -d redis`（游客/客服短期记忆与限流；无 Redis 时客服/游客对话可降级，但无跨轮记忆）
|
||||
|
||||
**RAG 双轨（2026-09-09）：**
|
||||
|
||||
| 链路 | Milvus | 灌库 |
|
||||
| --- | --- | --- |
|
||||
| 客服/游客 RAG | `fin_faq` / `fin_product` / `fin_policy` | `scripts/kb/build_collections.py` · 原料 `data/kb_collections/` |
|
||||
| 宿主 Tool | `kb_product_rules` | `scripts/kb/build_kb.py` · 原料 `data/kb/` |
|
||||
|
||||
---
|
||||
|
||||
## 4. 测试预期
|
||||
|
||||
- 基线 `python -m pytest` → **554 passed**（含 `test_wave3_customer_service.py` 19 例）
|
||||
- Wave 1/2/4/5 仍在 `tests/conftest.py` `collect_ignore`，接线验证后逐步移出
|
||||
- 基线 `python -m pytest` → **730 passed**（Wave 1~5 客服测试已全部解禁）
|
||||
- `tests/conftest.py` `collect_ignore` 已清空
|
||||
- 新增 `pytest.ini`：`testpaths = tests`（避免 `scripts/kb/test_*.py` 被误收集）
|
||||
- 客服线全量（剩余 wave 解禁后）：`pytest tests/test_wave1_data_masker.py … test_wave5_notes.py`
|
||||
- 客服线全量：`pytest tests/test_wave1_data_masker.py … test_wave5_notes.py`
|
||||
|
||||
---
|
||||
|
||||
@@ -84,4 +90,5 @@ scripts/agent/migrate-customer-agent-cs-c11.sql
|
||||
|
||||
| 日期 | 说明 |
|
||||
| --- | --- |
|
||||
| 2026-09-09 | Wave 1~5 解禁 · 迁移 SQL 已执行 · pytest **730 passed** · Scope B 冒烟（customer 200 · visitor Redis 降级） |
|
||||
| 2026-09-09 | S2 接缝接线：visitor 路由 + customer 分流 + wave3 测试绿 · pytest 554 passed |
|
||||
|
||||
+25
-26
@@ -1,6 +1,11 @@
|
||||
"""快速测试 Milvus 检索是否正常工作。"""
|
||||
"""快速测试 fin_* Milvus 检索（需先 build_collections 灌库）。"""
|
||||
from __future__ import annotations
|
||||
|
||||
import sys
|
||||
sys.path.insert(0, "d:/金融系统")
|
||||
from pathlib import Path
|
||||
|
||||
ROOT = Path(__file__).resolve().parents[2]
|
||||
sys.path.insert(0, str(ROOT))
|
||||
|
||||
from app.tool.embedding_tool import get_embedder
|
||||
from app.tool.milvus_tool import get_milvus_client
|
||||
@@ -8,29 +13,23 @@ from app.tool.milvus_tool import get_milvus_client
|
||||
e = get_embedder()
|
||||
m = get_milvus_client()
|
||||
|
||||
# 测试产品检索
|
||||
v = e.embed("R3中风险产品有哪些")
|
||||
hits = m.search("fin_product", v, top_k=3)
|
||||
print("=== 产品检索 ===")
|
||||
for h in hits:
|
||||
score = h.get("score", 0)
|
||||
text = h.get("chunk_text", "")[:100]
|
||||
print(f"score={score:.4f} | {text}")
|
||||
try:
|
||||
v = e.embed("R3中风险产品有哪些")
|
||||
hits = m.search("fin_product", v, top_k=3)
|
||||
print("=== 产品检索 ===")
|
||||
for h in hits:
|
||||
print(f"score={h.get('score', 0):.4f} | {(h.get('chunk_text') or '')[:100]}")
|
||||
|
||||
# 测试 FAQ 检索
|
||||
v2 = e.embed("开户需要什么材料")
|
||||
hits2 = m.search("fin_faq", v2, top_k=3)
|
||||
print("\n=== FAQ 检索 ===")
|
||||
for h in hits2:
|
||||
score = h.get("score", 0)
|
||||
text = h.get("chunk_text", "")[:100]
|
||||
print(f"score={score:.4f} | {text}")
|
||||
v2 = e.embed("开户需要什么材料")
|
||||
hits2 = m.search("fin_faq", v2, top_k=3)
|
||||
print("\n=== FAQ 检索 ===")
|
||||
for h in hits2:
|
||||
print(f"score={h.get('score', 0):.4f} | {(h.get('chunk_text') or '')[:100]}")
|
||||
|
||||
# 测试政策检索
|
||||
v3 = e.embed("投资者适当性匹配规则")
|
||||
hits3 = m.search("fin_policy", v3, top_k=3)
|
||||
print("\n=== 政策检索 ===")
|
||||
for h in hits3:
|
||||
score = h.get("score", 0)
|
||||
text = h.get("chunk_text", "")[:100]
|
||||
print(f"score={score:.4f} | {text}")
|
||||
v3 = e.embed("投资者适当性匹配规则")
|
||||
hits3 = m.search("fin_policy", v3, top_k=3)
|
||||
print("\n=== 政策检索 ===")
|
||||
for h in hits3:
|
||||
print(f"score={h.get('score', 0):.4f} | {(h.get('chunk_text') or '')[:100]}")
|
||||
finally:
|
||||
m.close()
|
||||
|
||||
+64
-10
@@ -74,22 +74,76 @@ class FakeRedis:
|
||||
def hgetall(self, key):
|
||||
return dict(self.hashes.get(key, {}))
|
||||
|
||||
def scan_iter(self, match=None):
|
||||
import fnmatch
|
||||
|
||||
pat = match or "*"
|
||||
keys = set(self.strings) | set(self.lists) | set(self.hashes)
|
||||
for key in keys:
|
||||
if fnmatch.fnmatch(key, pat):
|
||||
yield key
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def _wave_customer_fake_redis(request, monkeypatch):
|
||||
"""Wave 4/5：无本机 Redis 时用 FakeRedis（与 test_wave3 口径一致）。"""
|
||||
nodeid = request.node.nodeid
|
||||
if "test_wave4_e2e" not in nodeid and "test_wave5_notes" not in nodeid:
|
||||
yield
|
||||
return
|
||||
r = FakeRedis()
|
||||
monkeypatch.setattr("app.config.database.get_redis_client", lambda: r)
|
||||
from app.service.risk import redis_gateway
|
||||
|
||||
monkeypatch.setattr(redis_gateway, "_gateway", r)
|
||||
from app.service import customer_service as cs
|
||||
|
||||
monkeypatch.setattr(cs, "_spawn", lambda fn, *a: fn(*a))
|
||||
yield r
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def _wave_customer_test_session(request):
|
||||
"""Wave 4/5：在 agent_session 预建测试会话（merger chat 续聊须 SessionGuard 命中）。"""
|
||||
nodeid = request.node.nodeid
|
||||
if "test_wave4_e2e" not in nodeid and "test_wave5_notes" not in nodeid:
|
||||
yield
|
||||
return
|
||||
|
||||
from app.config.database import get_agent_engine
|
||||
from app.repository.session_repository import SessionRepository
|
||||
|
||||
session_id = "sess-e2e-001" if "test_wave4_e2e" in nodeid else "sess-note-001"
|
||||
cust = "CUST-9527"
|
||||
engine = get_agent_engine()
|
||||
with engine.begin() as conn:
|
||||
conn.execute(
|
||||
text("DELETE FROM agent_session WHERE session_id = :sid"),
|
||||
{"sid": session_id},
|
||||
)
|
||||
SessionRepository(engine=engine).create_session(
|
||||
session_id=session_id,
|
||||
trace_id="trc-wave-customer-test",
|
||||
agent_type="customer",
|
||||
actor_id=cust,
|
||||
actor_role="customer",
|
||||
customer_id=cust,
|
||||
)
|
||||
yield
|
||||
with engine.begin() as conn:
|
||||
conn.execute(
|
||||
text("DELETE FROM agent_session WHERE session_id = :sid"),
|
||||
{"sid": session_id},
|
||||
)
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def fake_redis():
|
||||
return FakeRedis()
|
||||
|
||||
|
||||
# 客服 Agent 线测试：接缝接线后逐步移出 ignore（见 客服Agent-合并说明.md）
|
||||
collect_ignore = [
|
||||
"test_wave1_data_masker.py",
|
||||
"test_wave2_core_ro_tool.py",
|
||||
"test_wave2_profile_slots.py",
|
||||
"test_wave2_prompts.py",
|
||||
"test_wave3_profile_service.py",
|
||||
"test_wave4_e2e.py",
|
||||
"test_wave5_notes.py",
|
||||
]
|
||||
# 客服 Agent Wave 测试已全部解禁（见 客服Agent-合并说明.md）
|
||||
collect_ignore: list[str] = []
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
|
||||
@@ -9,6 +9,8 @@
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from datetime import date, timedelta
|
||||
|
||||
import pytest
|
||||
|
||||
from app.repository.core_ro import CoreReadOnlyRepository
|
||||
@@ -75,13 +77,18 @@ def test_holdings_empty(ro):
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def test_trades_default_3_months(ro):
|
||||
since = date.today() - timedelta(days=90)
|
||||
rows = ro.list_trades("CUST-9527", since=since, limit=50)
|
||||
confirmed = [r for r in rows if r.get("trade_status") == "confirmed"]
|
||||
|
||||
r = query_trades("CUST-9527", repo=ro)
|
||||
assert r["ok"] is True
|
||||
assert r["tool"] == "transaction_query"
|
||||
assert "近 3 个月" in r["fact_text"]
|
||||
assert "2 笔" in r["fact_text"]
|
||||
assert f"{len(confirmed)} 笔" in r["fact_text"]
|
||||
assert "申购" in r["fact_text"]
|
||||
assert len(r["facts"]) == 2
|
||||
assert len(r["facts"]) == len(rows)
|
||||
assert len(confirmed) >= 2 # Wave 0 种子至少 2 笔；联调库可能更多
|
||||
|
||||
|
||||
def test_trades_custom_months(ro):
|
||||
|
||||
+43
-44
@@ -16,7 +16,8 @@ from unittest.mock import patch
|
||||
import pytest
|
||||
from fastapi.testclient import TestClient
|
||||
|
||||
from app.config.database import get_agent_engine, get_core_engine, get_redis_client
|
||||
from app.config import database as db
|
||||
from app.config.database import get_agent_engine, get_core_engine
|
||||
from app.gateway.jwt_service import issue_token
|
||||
from app.main import app
|
||||
from app.service import customer_service
|
||||
@@ -75,7 +76,7 @@ def _clean_redis():
|
||||
conftest mock 的 session_repo.ensure_session 返回 'sess-test-001'，
|
||||
所以实际 Redis key 用的是 'sess-test-001' 而非 body.session_id。
|
||||
"""
|
||||
r = get_redis_client()
|
||||
r = db.get_redis_client()
|
||||
patterns = [
|
||||
"customer:sess-e2e-001:*",
|
||||
"customer:sess-test-001:*",
|
||||
@@ -129,7 +130,9 @@ def _chat(client: TestClient, message: str, *, token: str | None = None,
|
||||
"X-Agent-Type": "customer",
|
||||
},
|
||||
)
|
||||
return resp.json()
|
||||
assert resp.status_code == 200, resp.text
|
||||
raw = resp.json()
|
||||
return raw.get("data", raw)
|
||||
|
||||
|
||||
def _core_scalar(sql: str, params: dict | None = None):
|
||||
@@ -148,10 +151,8 @@ def test_01_holding_query(client):
|
||||
fake = _make_fake_invoke({"意图分类器": "holding_query",
|
||||
"事实数据": "您的持仓包括以下产品。"})
|
||||
with patch.object(customer_service, "_invoke", side_effect=fake):
|
||||
body = _chat(client, "我的持仓有哪些", token=_customer_token())
|
||||
data = _chat(client, "我的持仓有哪些", token=_customer_token())
|
||||
|
||||
assert body["code"] == 0
|
||||
data = body["data"]
|
||||
assert data["intent"] == "holding_query"
|
||||
assert data["reply"]
|
||||
assert data["agent_type"] == "customer"
|
||||
@@ -172,11 +173,10 @@ def test_02_transaction_query(client):
|
||||
"事实数据": "近3个月交易记录如下。",
|
||||
})
|
||||
with patch.object(customer_service, "_invoke", side_effect=fake):
|
||||
body = _chat(client, "最近3个月交易记录", token=_customer_token())
|
||||
data = _chat(client, "最近3个月交易记录", token=_customer_token())
|
||||
|
||||
assert body["code"] == 0
|
||||
assert body["data"]["intent"] == "transaction_query"
|
||||
assert body["data"]["reply"]
|
||||
assert data["intent"] == "transaction_query"
|
||||
assert data["reply"]
|
||||
# 交叉验证：近 3 月 confirmed 交易数
|
||||
db_count = _core_scalar(
|
||||
"SELECT COUNT(*) FROM core_trade "
|
||||
@@ -199,10 +199,9 @@ def test_03_risk_assessment_query(client):
|
||||
"事实数据": "您的风险评级为C3，有效期至...",
|
||||
})
|
||||
with patch.object(customer_service, "_invoke", side_effect=fake):
|
||||
body = _chat(client, "我的风险等级是什么", token=_customer_token())
|
||||
data = _chat(client, "我的风险等级是什么", token=_customer_token())
|
||||
|
||||
assert body["code"] == 0
|
||||
assert body["data"]["intent"] == "risk_assessment_query"
|
||||
assert data["intent"] == "risk_assessment_query"
|
||||
# 交叉验证：DB 中的风评等级
|
||||
risk_code = _core_scalar(
|
||||
"SELECT risk_code FROM core_customer_risk "
|
||||
@@ -211,7 +210,7 @@ def test_03_risk_assessment_query(client):
|
||||
{"cid": CUST},
|
||||
)
|
||||
assert risk_code is not None
|
||||
assert f"C{risk_code[-1]}" in body["data"]["reply"] or risk_code is not None
|
||||
assert f"C{risk_code[-1]}" in data["reply"] or risk_code is not None
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
@@ -233,10 +232,9 @@ def test_04_suitability_check_readonly(client):
|
||||
"事实数据": "根据适当性匹配，您的C3评级可购买R3及以下产品。",
|
||||
})
|
||||
with patch.object(customer_service, "_invoke", side_effect=fake):
|
||||
body = _chat(client, "我能买R3产品吗", token=_customer_token())
|
||||
data = _chat(client, "我能买R3产品吗", token=_customer_token())
|
||||
|
||||
assert body["code"] == 0
|
||||
assert body["data"]["intent"] == "suitability_check"
|
||||
assert data["intent"] == "suitability_check"
|
||||
# 验证 risk_suitability_log 无新记录
|
||||
with agent_engine.connect() as conn:
|
||||
after = conn.execute(text(
|
||||
@@ -258,12 +256,11 @@ def test_05_rag_product_consult(client):
|
||||
})
|
||||
with patch.object(customer_service, "_invoke", side_effect=fake), \
|
||||
patch.object(VisitorRagService, "retrieve", return_value=fake_rag):
|
||||
body = _chat(client, "货币基金A是什么产品", token=_customer_token())
|
||||
data = _chat(client, "货币基金A是什么产品", token=_customer_token())
|
||||
|
||||
assert body["code"] == 0
|
||||
assert body["data"]["intent"] == "product_consult"
|
||||
assert body["data"]["reply"]
|
||||
assert body["data"]["has_disclaimer"] is True
|
||||
assert data["intent"] == "product_consult"
|
||||
assert data["reply"]
|
||||
assert data.get("has_disclaimer") is True
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
@@ -273,12 +270,11 @@ def test_05_rag_product_consult(client):
|
||||
def test_06_reject_investment_advice(client):
|
||||
"""说「推荐稳赚基金」→ reject 拒绝话术，不转人工。"""
|
||||
# 不 mock LLM（keyword_route 直接命中）
|
||||
body = _chat(client, "推荐稳赚的基金", token=_customer_token())
|
||||
data = _chat(client, "推荐稳赚的基金", token=_customer_token())
|
||||
|
||||
assert body["code"] == 0
|
||||
assert body["data"]["intent"] == "reject"
|
||||
assert body["data"]["transfer_to_human"] is False
|
||||
assert body["data"]["reply"] # 非空拒绝话术
|
||||
assert data["intent"] == "reject"
|
||||
assert data["transfer_to_human"] is False
|
||||
assert data["reply"]
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
@@ -287,11 +283,10 @@ def test_06_reject_investment_advice(client):
|
||||
|
||||
def test_07_transfer_human_complaint(client):
|
||||
"""说「我要投诉」→ transfer_human。"""
|
||||
body = _chat(client, "我要投诉你们的服务", token=_customer_token())
|
||||
data = _chat(client, "我要投诉你们的服务", token=_customer_token())
|
||||
|
||||
assert body["code"] == 0
|
||||
assert body["data"]["intent"] == "transfer_human"
|
||||
assert body["data"]["transfer_to_human"] is True
|
||||
assert data["intent"] == "transfer_human"
|
||||
assert data["transfer_to_human"] is True
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
@@ -369,7 +364,7 @@ def test_09_profile_injection_next_day(client):
|
||||
})})
|
||||
|
||||
# 刷新 Redis 热缓存（手动写入空 dict 触发 DB 回源）
|
||||
r = get_redis_client()
|
||||
r = db.get_redis_client()
|
||||
r.delete(f"profile:l1:{CUST}")
|
||||
|
||||
captured = {}
|
||||
@@ -386,9 +381,8 @@ def test_09_profile_injection_next_day(client):
|
||||
return "好的"
|
||||
|
||||
with patch.object(customer_service, "_invoke", side_effect=capturing_invoke):
|
||||
body = _chat(client, "今天天气怎么样", token=_customer_token())
|
||||
data = _chat(client, "今天天气怎么样", token=_customer_token())
|
||||
|
||||
assert body["code"] == 0
|
||||
# 验证画像上下文注入了 LLM prompt
|
||||
user_prompt = captured.get("last_user", "")
|
||||
assert "指数基金" in user_prompt or "上海" in user_prompt, \
|
||||
@@ -451,13 +445,19 @@ def test_11_cross_customer_forbidden(client):
|
||||
assert_customer_access(ctx, CUST_B)
|
||||
assert "403" in str(exc_info.value.error_code) or "NOT_OWNER" in exc_info.value.error_code
|
||||
|
||||
# 端到端：body 传别人 ID，但 resolve 忽略，数据仍是自己的
|
||||
fake = _make_fake_invoke({"意图分类器": "holding_query",
|
||||
"事实数据": "您的持仓如下。"})
|
||||
with patch.object(customer_service, "_invoke", side_effect=fake):
|
||||
body = _chat(client, "我的持仓", token=_customer_token(), customer_id=CUST_B)
|
||||
|
||||
assert body["code"] == 0 # 不报错（resolve 忽略 body.customer_id）
|
||||
# 端到端：customer token 传他人 customer_id → merger chat 层 403
|
||||
tok = _customer_token()
|
||||
resp = client.post(
|
||||
"/api/chat",
|
||||
json={"message": "我的持仓", "session_id": SESSION_ID, "customer_id": CUST_B},
|
||||
headers={
|
||||
"Authorization": f"Bearer {tok}",
|
||||
"X-Agent-Type": "customer",
|
||||
},
|
||||
)
|
||||
assert resp.status_code == 403
|
||||
err = resp.json()
|
||||
assert err.get("error_code") == "AUTH_403_NOT_OWNER"
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
@@ -484,9 +484,8 @@ def test_12_redis_down_degrade(client):
|
||||
patch("app.service.customer_service.ProfileHotCache") as mock_hc:
|
||||
mock_hc_instance = mock_hc.return_value
|
||||
mock_hc_instance.get_style_tags.return_value = {}
|
||||
body = _chat(client, "你好", token=_customer_token())
|
||||
data = _chat(client, "你好", token=_customer_token())
|
||||
|
||||
assert body["code"] == 0
|
||||
assert body["data"]["reply"]
|
||||
assert data["reply"]
|
||||
|
||||
|
||||
|
||||
@@ -16,7 +16,8 @@ import pytest
|
||||
from fastapi.testclient import TestClient
|
||||
from sqlalchemy import text
|
||||
|
||||
from app.config.database import get_agent_engine, get_redis_client
|
||||
from app.config import database as db
|
||||
from app.config.database import get_agent_engine
|
||||
from app.gateway.jwt_service import issue_token
|
||||
from app.repository.note_repository import CustomerNoteRepository
|
||||
from app.service import customer_service, note_service
|
||||
@@ -57,7 +58,7 @@ class FakeLLM:
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def _clean_env():
|
||||
r = get_redis_client()
|
||||
r = db.get_redis_client()
|
||||
for pattern in (
|
||||
f"customer:{SESSION_ID}:*",
|
||||
f"customer:sess-test-001:*",
|
||||
@@ -93,15 +94,16 @@ def _customer_token() -> str:
|
||||
|
||||
|
||||
def _chat(client: TestClient, message: str) -> dict:
|
||||
raw = client.post(
|
||||
resp = client.post(
|
||||
"/api/chat",
|
||||
json={"message": message, "session_id": SESSION_ID},
|
||||
headers={
|
||||
"Authorization": f"Bearer {_customer_token()}",
|
||||
"X-Agent-Type": "customer",
|
||||
},
|
||||
).json()
|
||||
# 响应包了一层 {code, message, data: {...}, trace_id}，测试用 data 字段
|
||||
)
|
||||
assert resp.status_code == 200, resp.text
|
||||
raw = resp.json()
|
||||
return raw.get("data", raw)
|
||||
|
||||
|
||||
|
||||
Reference in New Issue
Block a user