fix: 双Claw能力对齐 + MCP/LLM代理绕过(P0止血)

- 新增 app/core/capability_discovery.py:统一能力发现层,Web/IM 双Claw共用单一实现
  (三级降级:用户安装 → 平台published → 相关性裁剪;MCP 自动挂载已启用服务)
- im_llm.py:IM Bot Claw 改用统一发现层,恢复 skills(12) + MCP(26工具) 能力,
  修复 #866 部署回退导致的 agents=[]/mcp=[] 回归;mcp__ 前缀分流到 call_mcp_tool
- mcp_client.py:注入 httpx_client_factory(trust_env=False) 绕过容器 HTTP_PROXY,
  修复外部 MCP(xiaobenyang.com / anysearch.com) tools/list 全部静默失败(mcp_tools 0→26)
- llm_client.py / im_bot_user.py:2026-07-31 代理劫持内部请求 + 媒体断连修复(随镜像已上线)
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QihuAI Design committed 2026-08-04 10:21:19 +08:00
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"""统一能力发现层(双 Claw 共用 · 单一实现)。
背景
----
七虎平台对外有两个 Claw 端口:
* Web Claw —— SSE 流式,用户可在 UI 勾选 skills / mcp / agents
* IM Bot Claw —— 微信等 IM,server push 整条回复,**没有任何勾选 UI**
历史问题(2026-08-04 线上实证):
1. `im_llm.py` 写死 `agents=[]` / `mcp=[]`,IM 端永远拿不到 MCP 工具;
2. `_discover_installed_skills()` 强依赖 `app_installations` 表,而线上该表
**0 行** → 97 个 published skill 在 Web / IM **双端同时发现不到**;
3. IM 端 skills 还被 `[:15]` 截断(截断一个空列表,属噪声)。
设计原则
--------
能力发现只允许有 **一份实现**(本模块)。任何 Claw 想要"技能/工具",
都必须调用这里的函数;禁止在端侧另写一套发现逻辑——历史上 #866 部署
就是因为存在第二份实现而把 #764/#765 的注入改动整体覆盖回退。
发现策略(三级降级,双端一致)
--------------------------
1) 用户显式安装(app_installations)—— 最高优先,尊重用户意愿
2) 无安装记录 → 降级为平台已发布(status='published')全集
3) 池子超过预算 → 按当前问题做轻量相关性排序,取 top-K 控制 token
运维旋钮(环境变量,改完重启生效)
--------------------------------
CAP_SKILL_LIMIT 单轮注入技能数上限,默认 12
CAP_MCP_LIMIT 单轮注入 MCP 服务数上限,默认 8
CAP_SKILL_FALLBACK_PUBLISHED 安装表为空时是否降级为 published,默认 开
CAP_MCP_AUTO 未显式指定时是否自动挂载已启用 MCP,默认 开
"""
from __future__ import annotations
import logging
import os
import re
from typing import Any, Iterable
logger = logging.getLogger(__name__)
__all__ = [
"discover_skills",
"discover_mcp_servers",
"build_mcp_tool_defs",
"rank_by_query",
]
# --------------------------------------------------------------------------
# 环境旋钮
# --------------------------------------------------------------------------
def _env_int(name: str, default: int) -> int:
try:
raw = (os.environ.get(name) or "").strip()
return int(raw) if raw else default
except Exception:
return default
def _env_flag(name: str, default: bool = True) -> bool:
raw = (os.environ.get(name) or "").strip().lower()
if not raw:
return default
return raw in ("1", "true", "yes", "on")
# --------------------------------------------------------------------------
# 轻量相关性排序(中文友好:整词 + 2-gram)
# --------------------------------------------------------------------------
def _tokens(text: str) -> set:
text = re.sub(r"[^\w\u4e00-\u9fff]+", " ", (text or "").lower())
out: set = set()
for w in text.split():
if len(w) >= 2:
out.add(w)
for i in range(len(w) - 1):
out.add(w[i : i + 2])
return out
def rank_by_query(items: list, query: str, top_k: int) -> list:
"""按与 query 的词元重叠度排序取前 top_k。
池子本来就不超预算时原样返回,避免无谓抖动(同一问题两次调用结果稳定)。
"""
if not items:
return []
if top_k <= 0 or len(items) <= top_k:
return items[:top_k] if top_k > 0 else []
q = _tokens(query)
if not q:
return items[:top_k]
scored = []
for idx, it in enumerate(items):
blob = " ".join(
str(it.get(k) or "")
for k in ("name", "description", "category", "func_name")
)
t = _tokens(blob)
if t:
# 交集数按文档长度做平方根归一,抑制"长描述天然占优"
score = len(q & t) / (len(t) ** 0.5)
else:
score = 0.0
# idx 作为稳定次序的 tie-breaker,保证同分时结果可复现
scored.append((-score, idx, it))
scored.sort(key=lambda x: (x[0], x[1]))
return [it for _, _, it in scored[:top_k]]
# --------------------------------------------------------------------------
# 技能发现
# --------------------------------------------------------------------------
def discover_skills(
db,
user_id: str | None,
query: str = "",
limit: int | None = None,
claw: str = "web",
) -> list:
"""发现当前请求可用的技能列表(双 Claw 共用)。
返回 `_resolve_market_skills` 的结构:
[{id, name, description, skill_content, category, func_name, parameters}]
"""
limit = limit if limit is not None else _env_int("CAP_SKILL_LIMIT", 12)
if limit <= 0:
return []
# 延迟导入:避免 app.core ←→ app.api 循环依赖
from app.api.chat_skill import _resolve_market_skills
from app.models import AppInstallation, MarketApp
pool: list = []
source = "empty"
# 1) 用户显式安装
if user_id:
try:
app_ids = [
i.app_id
for i in db.query(AppInstallation)
.filter(AppInstallation.user_id == user_id)
.all()
]
if app_ids:
ids = [
a.id
for a in db.query(MarketApp)
.filter(
MarketApp.id.in_(app_ids),
MarketApp.type == "skill",
MarketApp.status == "published",
)
.all()
]
if ids:
pool = _resolve_market_skills(db, ids, user_id)
source = "installed"
except Exception as e:
logger.warning("[cap] 安装技能发现失败(降级继续): %s", e)
# 2) 降级:平台已发布全集
if not pool and _env_flag("CAP_SKILL_FALLBACK_PUBLISHED", True):
try:
ids = [
a.id
for a in db.query(MarketApp)
.filter(MarketApp.type == "skill", MarketApp.status == "published")
.all()
]
if ids:
pool = _resolve_market_skills(db, ids, user_id or "")
source = "published"
except Exception as e:
logger.warning("[cap] published 技能发现失败: %s", e)
# 3) 预算裁剪
picked = rank_by_query(pool, query, limit)
logger.info(
"[cap] skills claw=%s source=%s pool=%d picked=%d",
claw,
source,
len(pool),
len(picked),
)
return picked
# --------------------------------------------------------------------------
# MCP 发现
# --------------------------------------------------------------------------
def discover_mcp_servers(
db,
explicit_ids: Iterable[str] | None = None,
limit: int | None = None,
claw: str = "web",
) -> list:
"""发现当前请求可用的 MCP 服务连接(双 Claw 共用)。
Web Claw 传 explicit_ids(用户在 UI 勾选的);
IM Bot Claw 无勾选通道 → 传 None,自动挂载平台已启用的 MCP。
返回 [{id, name, description, transport, endpoint, url, headers}]
"""
limit = limit if limit is not None else _env_int("CAP_MCP_LIMIT", 8)
if limit <= 0:
return []
from app.api.chat_mcp import _list_enabled_mcp_servers, _resolve_active_mcp_servers
ids = [i for i in (explicit_ids or []) if i]
if ids:
out = _resolve_active_mcp_servers(db, ids)[:limit]
logger.info("[cap] mcp claw=%s source=explicit picked=%d", claw, len(out))
return out
if not _env_flag("CAP_MCP_AUTO", True):
return []
out = _list_enabled_mcp_servers(db)[:limit]
logger.info("[cap] mcp claw=%s source=auto picked=%d", claw, len(out))
return out
# --------------------------------------------------------------------------
# MCP → function definitions
# --------------------------------------------------------------------------
def _safe_name(raw: str, maxlen: int) -> str:
return re.sub(r"[^A-Za-z0-9_-]", "_", (raw or "")[:maxlen])
async def build_mcp_tool_defs(servers: list, idx_start: int = 0) -> tuple:
"""把 MCP 服务列表展开为 (function_definitions, tool_map)。
命名规则与 Web Claw 现有实现严格一致:`mcp__{server}__{tool}__{idx}`,
保证两端产生的工具名可互相对照、可被同一套审批/统计逻辑识别。
返回:
function_definitions: [{name, description, parameters}]
tool_map: {func_name: {server_id, name, server_name}}
"""
from app.mcp_client import list_mcp_tools
defs: list = []
tool_map: dict = {}
for offset, srv in enumerate(servers or []):
idx = idx_start + offset
try:
tools = await list_mcp_tools(srv)
except Exception as e:
logger.warning("[cap] MCP 拉取工具失败 [%s]: %s", srv.get("name"), e)
continue
for t in tools or []:
sname = _safe_name(srv.get("name") or "unknown", 30)
tname = _safe_name(t.get("name") or "tool", 50)
fname = f"mcp__{sname}__{tname}__{idx}"
tool_map[fname] = {
"server_id": srv.get("id"),
"name": t.get("name"),
"server_name": srv.get("name"),
}
defs.append(
{
"name": fname,
"description": (
f"[MCP:{srv.get('name')}] {t.get('description') or t.get('name') or ''}"
)[:900],
"parameters": t.get("inputSchema")
or {"type": "object", "properties": {}},
}
)
return defs, tool_map