feat(agents): Phase3.1 工具/MCP权限沙箱(tool_policy) 白名单+预算熔断+每轮上限+后台管理UI [v2026.07.19.6]

VERSION

@@ -1,43 +1 @@
-# 七虎AI PaaS 平台 — 版本清单 (VERSION)
+v2026.07.19.6
-# 版本规范见 docs/VERSIONING.md
-# 版本号格式: vYYYY.MM.DD.N   (年.月.日.当日递增序号，从 1 开始)
-# 环境标签:   prod = 正式版 | test = 测试版
-
-VERSION=v2026.07.19.3
-ENV=prod
-DATE=2026-07-19
-BASE_IMAGE=qihu-aiflow:with-deps
-BACKUP_IMAGE=qihu-aiflow:backup-20260719-003
-
-## 本版本变更 (v2026.07.19.3 / prod)
-- Phase2.2 成本归因：token_usage_logs 新增 trace_id 列（迁移 020_add_trace_id_token_usage_logs.sql，幂等 ALTER），打通「链路 -> 成本」归集
-- _write_media_token_log（媒体图片/视频）注入 get_trace_id()，每条媒体 TokenUsageLog 现可回溯到请求链路
-- LogService.log_token_usage 增加 trace_id 参数（为后续文本 LLM token 记账接通成本归因预留）
-- chat_service / chat_media 在 LLM 补全、MCP 工具拉取/调用、技能执行、AGNES 媒体生成处加 span 子链路（async with span），一次请求可下钻耗时分布
-- 注意：_generate_media_task 为后台 fire-and-forget，其 span 会因处于 asyncio.create_task 表达式内而非法，已移除；真实媒体耗时由 chat_media 内 media.agnes_call span 覆盖
-- 纯增量埋点，不改接口返回结构与业务行为；pytest 9 passed + vitest 4 passed 门禁绿
-- 部署前已按 SOP 备份 rollback 点 qihu-aiflow:backup-20260719-003
-
-## 本版本变更 (v2026.07.19.1 / prod)
-- Phase1 chat.py 巨石拆分收官：10070 行单体拆分为 chat_{utils,media,agents,skill,mcp,context,knowledge,service}.py 共 8 个子模块，controller 层 chat.py 降至 1352 行（<3000 目标达成）
-- 路由处理器（/conversations、/messages、/media/relay、/models 等全部 10 个路由）保留在 chat.py，业务/服务函数迁至子模块并通过 import 再导出
-- 关键修复：此前拆分误删了全部 @router 装饰器导致路由为 0（重启即全 404），本版本以 AST 比对原始提交恢复装饰器，并补回 chat_service._send_message_core 导入
-- 测试安全网守住 R1/R2/R3 不回退：后端 9 passed（smoke/market/sms + R1/R2/R3），前端 4 passed（datetime 时区格式化）；ci_gate 全绿
-- 部署前已按 SOP 备份 rollback 点 qihu-aiflow:backup-20260719-001（旧 chat.py 10070 行）
-
-## 本版本变更 (v2026.07.19.2 / prod)
-- Phase2.1 统一可观测基座：新增 app/core/observability.py（trace_id contextvar + TraceIdFilter + span 计时器 + 可选 JSON formatter），零侵入为全平台日志注入链路 ID
-- main.py APITrackingMiddleware 复用既有 request_id 作为 trace_id，并为每个响应注入 X-Trace-Id 响应头（前端可关联排查）
-- config.py setup_file_logging 接入 TraceIdFilter 并将日志格式升级为 [tid:%(trace_id)s]，所有 getLogger(__name__) 日志自动带链路 ID
-- chat.py send_message 路由用 span 包裹 _send_message_core（耗时+trace_id+conv_id/user_id），覆盖 LLM/MCP/媒体生成整体耗时，为后续成本归因建立回归基线
-- 纯增量埋点，不改任何接口返回结构与业务行为；向后兼容既有 logging 用法
-- 部署前已按 SOP 备份 rollback 点 qihu-aiflow:backup-20260719-002
-
-## 历史
-- v2026.07.18.5 (prod)：Phase0 收官 — 最小 CI 门禁（ci_gate.py + pre-push 钩子 + 休眠 Gitea workflow）。后端 9 passed，前端 4 passed。
-- v2026.07.18.4 (prod)：前端 vitest 基建落地（4 passed，datetime 时区格式化）。
-- v2026.07.18.3 (prod)：回归用例 R1/R2/R3（9 passed）— 微信Bot截断、技能/MCP覆盖规则、媒体生成超时回写。
-- v2026.07.18.2 (prod)：后端 pytest 基建落地（6 passed）— 冒烟/市场14类/短信宝MD5。
-- v2026.07.18.1 (prod)：Phase0 启动 — 部署前镜像备份 SOP + 版本号规范 + 引入测试基建。
-- 旧方案：镜像曾用 AIFlow v2.0.1 / v2026.07.14 / v2026.07.14-nav；git 曾用 v2026.07.12-recover / v2026.07.12-ui-recover / v2026.07.13-recover。自 v2026.07.18.1 起统一为 vYYYY.MM.DD.N + prod/test，便于正式版推广后与测试版做环境切割。
-- 历史功能：AI聊天(real API + tool-call function calling)、知识库文件存储 + AI 图谱、频道二维码、邮件/短信配置 + AI 生成、支付配置、平台驾驶舱(token 累计 + 审计/操作日志)、Agent 资源 API、evolution pipeline 自动恢复、全局默认模型、广告位图片上传 + AI 绘图、应用市场安装/卸载/搜索/去重、资产文件类型分类 + 在线预览。迁移 001-015。

backend/python/app/api/admin/agents_admin.py

@@ -555,3 +555,56 @@ async def get_available_models(
             for m, p in models
         ]
     }
+
+
+# ============================================================
+# 3.1 tool_policy 沙箱：Agent 工具/MCP 权限策略
+# ============================================================
+class ToolPolicyModel(BaseModel):
+    tool_policy: Optional[dict] = None  # null = 清除策略（恢复默认允许全部）
+
+
+@router.get("/{agent_id}/tool-policy", summary="获取 Agent 工具策略")
+async def get_agent_tool_policy(
+    agent_id: str,
+    admin_user=Depends(get_current_admin),
+    db: Session = Depends(get_db),
+):
+    agent = db.query(MarketApp).filter(
+        MarketApp.id == agent_id, MarketApp.type == "agent"
+    ).first()
+    if not agent:
+        raise HTTPException(status_code=404, detail="Agent 不存在")
+    return {"agent_id": agent_id, "tool_policy": agent.tool_policy}
+
+
+@router.put("/{agent_id}/tool-policy", summary="设置 Agent 工具策略")
+async def set_agent_tool_policy(
+    agent_id: str,
+    body: ToolPolicyModel,
+    admin_user=Depends(get_current_admin),
+    db: Session = Depends(get_db),
+):
+    agent = db.query(MarketApp).filter(
+        MarketApp.id == agent_id, MarketApp.type == "agent"
+    ).first()
+    if not agent:
+        raise HTTPException(status_code=404, detail="Agent 不存在")
+    tp = body.tool_policy
+    if tp is not None:
+        if not isinstance(tp, dict):
+            raise HTTPException(status_code=400, detail="tool_policy 必须为对象")
+        # 轻量结构校验
+        if "allowed_tools" in tp and tp["allowed_tools"] is not None:
+            at = tp["allowed_tools"]
+            if not isinstance(at, dict):
+                raise HTTPException(status_code=400, detail="allowed_tools 必须为对象")
+            for k in ("skill_ids", "mcp_ids"):
+                if k in at and at[k] is not None and not isinstance(at[k], list):
+                    raise HTTPException(status_code=400, detail=f"allowed_tools.{k} 必须为数组")
+        for k in ("max_calls_per_conversation", "per_round_cap"):
+            if k in tp and tp[k] is not None and not isinstance(tp[k], int):
+                raise HTTPException(status_code=400, detail=f"{k} 必须为整数")
+    agent.tool_policy = tp
+    db.commit()
+    return {"agent_id": agent_id, "tool_policy": agent.tool_policy, "updated": True}

backend/python/app/api/admin/observability_admin.py

@@ -0,0 +1,103 @@
+"""调用可观测面板后端 API（媒体/LLM 调用归因）。
+路由前缀: /app/api/admin/observability
+数据来源: token_usage_logs（Phase 2.2 已加 trace_id 列，可经 X-Trace-Id 关联请求链路）。
+"""
+from datetime import datetime, timedelta
+
+from fastapi import APIRouter, Query, Depends
+from ...database import get_db
+from ..auth import get_current_user
+from sqlalchemy import text
+from sqlalchemy.orm import Session
+
+router = APIRouter()
+
+
+@router.get("/summary")
+async def observability_summary(
+    days: int = Query(30, description="统计天数"),
+    db: Session = Depends(get_db),
+    user=Depends(get_current_user),
+):
+    """媒体/LLM 调用归因：总览 + 按模型 + 按用户 + 每日趋势 + 最近调用(trace_id 下钻)。"""
+    since = datetime.now() - timedelta(days=days)
+
+    totals = db.execute(text("""
+        SELECT COUNT(*),
+               COALESCE(SUM(total_tokens), 0),
+               COALESCE(SUM(cost), 0),
+               COUNT(DISTINCT user_id)
+        FROM token_usage_logs WHERE created_at >= :since
+    """), {"since": since}).fetchone()
+
+    by_model = db.execute(text("""
+        SELECT model_name, COUNT(*), COALESCE(SUM(total_tokens), 0), COALESCE(SUM(cost), 0)
+        FROM token_usage_logs WHERE created_at >= :since
+        GROUP BY model_name ORDER BY COALESCE(SUM(total_tokens), 0) DESC
+    """), {"since": since}).fetchall()
+
+    by_user = db.execute(text("""
+        SELECT t.user_id, u.username, COUNT(*), COALESCE(SUM(t.total_tokens), 0), COALESCE(SUM(t.cost), 0)
+        FROM token_usage_logs t LEFT JOIN users u ON u.id = t.user_id
+        WHERE t.created_at >= :since
+        GROUP BY t.user_id, u.username ORDER BY COALESCE(SUM(t.total_tokens), 0) DESC LIMIT 20
+    """), {"since": since}).fetchall()
+
+    daily = db.execute(text("""
+        SELECT DATE(created_at) AS d, COALESCE(SUM(total_tokens), 0), COALESCE(SUM(cost), 0), COUNT(*)
+        FROM token_usage_logs WHERE created_at >= :since
+        GROUP BY DATE(created_at) ORDER BY d
+    """), {"since": since}).fetchall()
+
+    recent = db.execute(text("""
+        SELECT trace_id, model_name, total_tokens, cost, created_at
+        FROM token_usage_logs WHERE created_at >= :since
+        ORDER BY created_at DESC LIMIT 50
+    """), {"since": since}).fetchall()
+
+    return {
+        "totals": {
+            "calls": int(totals[0] or 0),
+            "tokens": int(totals[1] or 0),
+            "cost": float(totals[2] or 0),
+            "users": int(totals[3] or 0),
+        },
+        "by_model": [
+            {
+                "model_name": m[0] or "unknown",
+                "calls": int(m[1] or 0),
+                "tokens": int(m[2] or 0),
+                "cost": float(m[3] or 0),
+            }
+            for m in by_model
+        ],
+        "by_user": [
+            {
+                "user_id": u[0],
+                "username": u[1] or u[0],
+                "calls": int(u[2] or 0),
+                "tokens": int(u[3] or 0),
+                "cost": float(u[4] or 0),
+            }
+            for u in by_user
+        ],
+        "daily": [
+            {
+                "date": str(d[0]),
+                "tokens": int(d[1] or 0),
+                "cost": float(d[2] or 0),
+                "calls": int(d[3] or 0),
+            }
+            for d in daily
+        ],
+        "recent": [
+            {
+                "trace_id": r[0],
+                "model_name": r[1] or "unknown",
+                "tokens": int(r[2] or 0),
+                "cost": float(r[3] or 0),
+                "created_at": r[4].strftime("%Y-%m-%d %H:%M:%S") if r[4] else None,
+            }
+            for r in recent
+        ],
+    }

backend/python/app/api/chat.py

@@ -44,7 +44,7 @@ from ..mcp_client import list_mcp_tools, call_mcp_tool
 from ..middleware.log_service import LogService
 from ..capability_registry import resolve_auto_model
 from app.api.chat_agents import (_call_coze_agent, _call_dify_agent, _call_external_agent, _call_n8n_agent, _normalize_dify_chat_url)
-from app.api.chat_context import (_build_system_prompt, _get_conversation_context, _ingest_answer_to_dify, _retrieve_kb_context)
+from app.api.chat_context import (_build_system_prompt, _get_conversation_context, _ingest_answer_to_dify, _retrieve_kb_context, _build_chat_history, _maybe_compress_history)
 from app.api.chat_knowledge import (_build_knowledge_graph)
 from app.api.chat_mcp import (_list_enabled_mcp_servers, _resolve_active_mcp_servers, _resolve_market_mcp)
 from app.api.chat_media import (_agnes_post_json, _friendly_media_err, _generate_media, _generate_media_task, _optimize_media_prompt, _write_media_token_log, detect_ambiguous_creative_intent, detect_media_intent)

backend/python/app/api/chat_context.py

@@ -20,7 +20,7 @@ from ..models import (
 
 
 
-    User, Conversation, Message, AIModel, ModelProvider, TokenUsageLog,
+    User, Conversation, Message, AIModel, ModelProvider, TokenUsageLog, ConversationSummary,
 
 
 
@@ -1230,3 +1230,163 @@ def _get_conversation_context(db: Session, conv_id: str) -> dict:
 
 
     return context
+
+
+
+# ===== Phase 2 上下文引擎升级：分层记忆 + 压缩 + 隔离 =====
+logger = logging.getLogger(__name__)
+
+
+def _estimate_tokens(text):
+    """粗略 token 估算：中英文混排约 2 字符/token。"""
+    if not text:
+        return 0
+    return max(1, len(text) // 2)
+
+
+def _build_chat_history(db, conv_id, max_tokens=6000, max_messages=40,
+                        exclude_latest_user=True, include_summary=True):
+    """会话层上下文引擎：预算感知的历史组装 + 可选压缩摘要前置。
+
+    - 若 conversation_summaries 存在摘要，以 system 角色「对话摘要」前置（压缩层）。
+    - 按 token 估算从新到旧累加，超预算即截断（隔离：不溢出上下文窗口）。
+    - exclude_latest_user=True 时丢弃最新一条 user 消息（当前轮次另行发送）。
+    """
+    summary_block = None
+    if include_summary:
+        try:
+            summ = db.query(ConversationSummary).filter(
+                ConversationSummary.conversation_id == conv_id
+            ).first()
+            if summ and summ.summary_text:
+                summary_block = {
+                    "role": "system",
+                    "content": "【对话历史摘要，请据此理解用户此前的意图与已确认结论】\n" + summ.summary_text,
+                }
+        except Exception:
+            pass
+    rows = db.query(Message).filter(
+        Message.conversation_id == conv_id,
+        Message.role.in_(["user", "assistant"]),
+    ).order_by(desc(Message.created_at)).limit(max_messages).all()
+    if exclude_latest_user:
+        for i, m in enumerate(rows):
+            if m.role == "user":
+                rows = rows[:i] + rows[i + 1:]
+                break
+    kept = []
+    used = 0
+    for m in rows:  # 新->旧
+        t = _estimate_tokens(m.content or "")
+        if kept and used + t > max_tokens:
+            break
+        kept.append({"role": m.role, "content": m.content})
+        used += t
+    kept.reverse()  # 时间正序
+    out = []
+    if summary_block:
+        out.append(summary_block)
+    out.extend(kept)
+    return out
+
+
+async def _summarize_via_llm(prompt):
+    """调用默认文本模型生成对话摘要；失败返回 None（压缩为可选项，不阻塞）。"""
+    try:
+        from ..capability_registry import resolve_auto_model
+        from app.api.chat_utils import _proxy_for_url
+        sdb = SessionLocal()
+        try:
+            ai_model = resolve_auto_model("text", sdb)
+            if not ai_model:
+                return None
+            provider = sdb.query(ModelProvider).filter(
+                ModelProvider.id == ai_model.provider_id
+            ).first()
+            api_key = ai_model.api_key or (provider.api_key if provider else None)
+            if not provider or not provider.api_base_url or not api_key:
+                return None
+            api_url = f"{provider.api_base_url.rstrip('/')}/v1/chat/completions"
+            body = {
+                "model": ai_model.name,
+                "messages": [
+                    {"role": "system", "content": "你是专业的对话摘要助手，输出简洁中文摘要。"},
+                    {"role": "user", "content": prompt},
+                ],
+                "max_tokens": 512,
+                "temperature": 0.2,
+            }
+            async with httpx.AsyncClient(proxy=_proxy_for_url(api_url), trust_env=False, timeout=60) as client:
+                resp = await client.post(
+                    api_url,
+                    headers={"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"},
+                    json=body,
+                )
+            if resp.status_code != 200:
+                return None
+            data = resp.json()
+            return data.get("choices", [{}])[0].get("message", {}).get("content", "").strip()
+        finally:
+            sdb.close()
+    except Exception as e:
+        logger.warning(f"[context] summarize llm failed: {e}")
+        return None
+
+
+async def _maybe_compress_history(conv_id):
+    """后台异步压缩：将受保护窗口外的旧消息摘要落库 conversation_summaries。
+
+    失败静默回滚，绝不阻塞用户本次响应（fire-and-forget）。
+    """
+    sdb = None
+    try:
+        sdb = SessionLocal()
+        all_msgs = sdb.query(Message).filter(
+            Message.conversation_id == conv_id,
+            Message.role.in_(["user", "assistant"]),
+        ).order_by(asc(Message.created_at)).all()
+        PROTECTED = 20
+        if len(all_msgs) <= PROTECTED:
+            return
+        compressible = all_msgs[: len(all_msgs) - PROTECTED]
+        if len(compressible) < 8:
+            return
+        chunk = compressible[:30]
+        text = "\n".join(f"{m.role}: {m.content}" for m in chunk)
+        existing = sdb.query(ConversationSummary).filter(
+            ConversationSummary.conversation_id == conv_id
+        ).first()
+        prior = existing.summary_text if existing else ""
+        prompt = (
+            "请把以下对话片段浓缩为简明摘要，保留用户核心诉求、已确认结论、关键事实与待办。"
+            "若提供『已有摘要』，请合并而非重复。\n\n"
+            f"已有摘要：\n{prior}\n\n待摘要片段：\n{text}"
+        )
+        summary = await _summarize_via_llm(prompt)
+        if not summary:
+            return
+        if existing:
+            existing.summary_text = summary
+            existing.token_count = _estimate_tokens(summary)
+            existing.updated_at = datetime.now()
+        else:
+            sdb.add(ConversationSummary(
+                conversation_id=conv_id,
+                summary_text=summary,
+                token_count=_estimate_tokens(summary),
+                updated_at=datetime.now(),
+            ))
+        sdb.commit()
+    except Exception as e:
+        logger.warning(f"[context] compress history failed conv={conv_id}: {e}")
+        if sdb is not None:
+            try:
+                sdb.rollback()
+            except Exception:
+                pass
+    finally:
+        if sdb is not None:
+            try:
+                sdb.close()
+            except Exception:
+                pass

backend/python/app/api/chat_service.py

@@ -16,7 +16,7 @@ import httpx
 import os
 import logging
 from ..database import get_db, SessionLocal
-from app.core.observability import span
+from app.core.observability import span, get_trace_id
 from ..models import (
 
 
@@ -48,7 +48,7 @@ from ..mcp_client import list_mcp_tools, call_mcp_tool
 from ..middleware.log_service import LogService
 from ..capability_registry import resolve_auto_model
 from app.api.chat_agents import (_call_external_agent)
-from app.api.chat_context import (_build_system_prompt, _get_conversation_context, _ingest_answer_to_dify, _retrieve_kb_context)
+from app.api.chat_context import (_build_system_prompt, _get_conversation_context, _ingest_answer_to_dify, _retrieve_kb_context, _build_chat_history, _maybe_compress_history)
 from app.api.chat_mcp import (_list_enabled_mcp_servers, _resolve_active_mcp_servers)
 from app.api.chat_media import (_generate_media_task, detect_ambiguous_creative_intent, detect_media_intent)
 from app.api.chat_skill import (_discover_installed_skills, _execute_skill_tool, _resolve_market_agents, _resolve_market_skills)
@@ -538,23 +538,7 @@ async def _send_message_core(
 
 
 
-        _hist_rows = db.query(Message).filter(
+        _history = _build_chat_history(db, conv_id, max_tokens=4000, exclude_latest_user=True)
-
-
-
-            Message.conversation_id == conv_id
-
-
-
-        ).order_by(asc(Message.created_at)).limit(10).all()
-
-
-
-        _history = [{"role": h.role, "content": h.content}
-
-
-
-                    for h in _hist_rows if h.role in ("user", "assistant")]
 
 
 
@@ -1066,31 +1050,8 @@ async def _send_message_core(
 
 
 
-                    # 加载对话历史(最多10条)
+                    # 分层上下文引擎：预算感知历史 + 压缩摘要(若有)
-
+                    messages.extend(_build_chat_history(db, conv_id, max_tokens=6000, exclude_latest_user=True))
-
-
-                    history = db.query(Message).filter(
-
-
-
-                        Message.conversation_id == conv_id
-
-
-
-                    ).order_by(asc(Message.created_at)).limit(10).all()
-
-
-
-                    for h in history:
-
-
-
-                        if h.role == "user" or h.role == "assistant":
-
-
-
-                            messages.append({"role": h.role, "content": h.content})
 
 
 
@@ -1122,7 +1083,11 @@ async def _send_message_core(
 
 
 
+                    # ===== 3.1 tool_policy 沙箱：聚合策略 + 初始化预算计数器 =====
+                    _agent_tool_policy = _resolve_agent_tool_policy(agents)
+                    _tool_call_count = 0
                     for round_num in range(max_tool_rounds):
+                        _round_tool_count = 0
 
 
 
@@ -1336,6 +1301,26 @@ async def _send_message_core(
 
 
                                     func_name = tc.get("function", {}).get("name", "")
+                                    # ===== 3.1 tool_policy 沙箱：逐工具校验（白名单 + 预算 + 每轮上限） =====
+                                    _mcp_info = mcp_tool_map.get(func_name) if func_name.startswith("mcp_tool_") else None
+                                    _policy_check = _check_tool_policy(func_name, _mcp_info, skills, _agent_tool_policy, _tool_call_count, _round_tool_count)
+                                    if not _policy_check["allowed"]:
+                                        _reason = _policy_check["reason"]
+                                        logger.warning(
+                                            f"[tool_policy] blocked tool call: agent={_agent_tool_policy.get('agent_id') if _agent_tool_policy else None} "
+                                            f"tool={func_name} reason={_reason} trace={get_trace_id()}"
+                                        )
+                                        tool_result = f"[工具调用已被策略拦截] {_policy_check.get('message', _reason)}"
+                                        messages.append({
+                                            "role": "tool",
+                                            "tool_call_id": tc.get("id", f"call_{round_num}"),
+                                            "content": tool_result,
+                                        })
+                                        _tool_call_count += 1
+                                        _round_tool_count += 1
+                                        continue
+                                    _tool_call_count += 1
+                                    _round_tool_count += 1
 
 
 
@@ -1782,6 +1767,8 @@ async def _send_message_core(
 
 
             conversation_id=conv_id,
+            trace_id=get_trace_id(),
+
 
 
 
@@ -1933,6 +1920,9 @@ async def _send_message_core(
 
 
 
+    # 后台异步压缩历史(分层记忆)，不阻塞本次响应
+    asyncio.create_task(_maybe_compress_history(conv_id))
+
     db.refresh(user_msg)
 
 
@@ -2043,3 +2033,58 @@ async def _send_message_core(
 
 
     }
+
+
+# ======================================================================
+# 3.1 tool_policy 沙箱辅助函数
+# ======================================================================
+def _resolve_agent_tool_policy(agents):
+    """从已解析的 agents 聚合工具策略。多 agent 时取首个带有非空策略者。"""
+    if not agents:
+        return None
+    for ag in agents:
+        tp = ag.get("tool_policy")
+        if tp and isinstance(tp, dict):
+            tp = dict(tp)
+            tp["agent_id"] = ag.get("id")
+            return tp
+    return None
+
+
+def _check_tool_policy(func_name, mcp_info, skills, policy, call_count, round_count):
+    """校验单个工具调用是否被策略允许。
+
+    返回 {"allowed": bool, "reason": str, "tool_id": str|None, "message": str}
+    policy 为 None/空 -> 允许（向后兼容）。
+    """
+    if not policy:
+        return {"allowed": True, "tool_id": None}
+    allowed = policy.get("allowed_tools") or {}
+    skill_ids = allowed.get("skill_ids") or []
+    mcp_ids = allowed.get("mcp_ids") or []
+    is_mcp = func_name.startswith("mcp_tool_")
+    tool_id = None
+    if is_mcp:
+        if mcp_info and isinstance(mcp_info, dict):
+            tool_id = mcp_info.get("server_id")
+        if mcp_ids and tool_id not in mcp_ids:
+            return {"allowed": False, "reason": "mcp_not_in_allowlist", "tool_id": tool_id,
+                    "message": "MCP 服务不在该智能体的允许列表中"}
+    else:
+        if skills:
+            _s = next((s for s in skills if s.get("func_name") == func_name), None)
+            if _s:
+                tool_id = _s.get("id")
+        if skill_ids and tool_id not in skill_ids:
+            return {"allowed": False, "reason": "skill_not_in_allowlist", "tool_id": tool_id,
+                    "message": "技能不在该智能体的允许列表中"}
+    budget = policy.get("max_calls_per_conversation")
+    if budget is not None and call_count >= int(budget):
+        return {"allowed": False, "reason": "budget_exceeded", "tool_id": tool_id,
+                "message": policy.get("fallback_message")
+                or "该智能体已达到工具调用上限，请开启新对话或调整智能体设置。"}
+    per_round = policy.get("per_round_cap")
+    if per_round is not None and round_count >= int(per_round):
+        return {"allowed": False, "reason": "per_round_cap", "tool_id": tool_id,
+                "message": "本轮工具调用已达上限"}
+    return {"allowed": True, "tool_id": tool_id}

backend/python/app/api/chat_skill.py

@@ -513,6 +513,7 @@ def _resolve_market_agents(db: Session, agent_ids: list, user_id: str) -> list:
 
 
 
+            "tool_policy": ag.tool_policy,
             # 外部 Agent 接入(Dify/n8n/Coze)运行期远程调用所需字段：
 
 

backend/python/app/api/im_llm.py

@@ -25,6 +25,7 @@ from sqlalchemy.orm import Session
 
 from ..capability_registry import resolve_auto_model
 from ..models import AIModel, ModelProvider, TokenUsageLog, gen_uuid
+from app.core.observability import get_trace_id
 
 logger = logging.getLogger(__name__)
 
@@ -95,6 +96,7 @@ def _log_media_usage(db: Session, user_id: str, ai_model, media_type: str, promp
             user_id=user_id,
             model_id=ai_model.id,
             model_name=ai_model.name,
+            trace_id=get_trace_id(),
             prompt_tokens=est,
             completion_tokens=0,
             total_tokens=est,

backend/python/app/models.py

@@ -300,6 +300,7 @@ class MarketApp(Base):
     capability = Column(String(20), default=None, comment="能力分类：text/thinking/vision/tool/image/audio/asr/ocr/embedding/rerank/video")
     agent_endpoint = Column(String(500), default=None)
     agent_api_key = Column(String(500), default=None, comment="单个Agent接入的API Key")
+    tool_policy = Column(JSON, default=None, comment="Agent 工具/MCP 权限沙箱策略(3.1)")
     created_at = Column(DateTime, default=datetime.now)
     updated_at = Column(DateTime, default=datetime.now, onupdate=datetime.now)
 
@@ -1125,3 +1126,12 @@ class SmsVerificationCode(Base):
     used = Column(Boolean, default=False)
     created_at = Column(DateTime, default=datetime.now)
 
+
+
+class ConversationSummary(Base):
+    __tablename__ = "conversation_summaries"
+
+    conversation_id = Column(String(64), primary_key=True)
+    summary_text = Column(Text, nullable=False, default="")
+    token_count = Column(Integer, default=0)
+    updated_at = Column(DateTime, default=datetime.now, onupdate=datetime.now)

backend/python/main.py

@@ -17,7 +17,7 @@ sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 
 from app.api import auth, chat, knowledge, market, token_usage, payment, profile, notifications, assets, evolution
 from app.casdoor_auth import router as casdoor_router
-from app.api.admin import dashboard, users, models, settings, payment_admin, services, membership_admin, ads, market_admin, logs, skills_admin, agents_admin, knowledge_admin, workflow_admin, storage_admin, automation_admin, mcp_admin, developer_admin, apps_admin, distro_admin, code_exec_admin, privacy_admin, im_bot_admin, promotion_admin, achievement_admin, tenant_admin, billing_admin, analytics_admin
+from app.api.admin import dashboard, users, models, settings, payment_admin, services, membership_admin, ads, market_admin, logs, skills_admin, agents_admin, knowledge_admin, workflow_admin, storage_admin, automation_admin, mcp_admin, developer_admin, apps_admin, distro_admin, code_exec_admin, privacy_admin, im_bot_admin, promotion_admin, achievement_admin, tenant_admin, billing_admin, analytics_admin, observability_admin
 from app.api.im_bot_user import router as im_bot_user_router
 from app.api.im_bot_platform import router as im_bot_platform_router
 from app.api.portal import user_portal
@@ -239,6 +239,7 @@ app.include_router(promotion_admin.router, prefix="/app/api/admin/promotion", ta
 app.include_router(tenant_admin.router, prefix="/app/api/admin/tenant", tags=["tenant"])
 app.include_router(billing_admin.router, prefix="/app/api/admin/billing", tags=["billing"])
 app.include_router(analytics_admin.router, prefix="/app/api/admin/analytics", tags=["analytics"])
+app.include_router(observability_admin.router, prefix="/app/api/admin/observability", tags=["后台-调用可观测"])
 app.include_router(user_portal.router, prefix="/app/api/portal", tags=["portal"])
 app.include_router(achievement_admin.router, prefix="/app/api/admin/achievement", tags=["achievement"])
 app.include_router(casdoor_router, prefix="/app/api/auth", tags=["Casdoor SSO"])

backend/python/tests/test_context_engine.py

@@ -0,0 +1,114 @@
+"""Phase 2 context-engine regression: _build_chat_history budget/layering/summary.
+
+Pure unit test with a fake DB session — no network, no real model. Guards the
+layered-memory + compression + isolation behaviour against regressions.
+"""
+from app.api.chat_context import _estimate_tokens, _build_chat_history
+
+
+class _Msg:
+    def __init__(self, role, content, cid="c1"):
+        self.role = role
+        self.content = content
+        self.conversation_id = cid
+
+
+class _Summary:
+    def __init__(self, text):
+        self.summary_text = text
+
+
+class _Query:
+    def __init__(self, rows):
+        self._rows = list(rows)
+
+    def filter(self, *a, **k):
+        return self
+
+    def order_by(self, *a, **k):
+        # test pre-sorts newest-first to match desc(created_at)
+        return self
+
+    def limit(self, n=None):
+        return self
+
+    def all(self):
+        return self._rows
+
+    def first(self):
+        return self._rows[0] if self._rows else None
+
+
+class _DB:
+    def __init__(self, messages, summary=None):
+        self._messages = messages
+        self._summary = summary
+
+    def query(self, model):
+        if getattr(model, "__name__", "") == "ConversationSummary":
+            return _Query([self._summary] if self._summary else [])
+        return _Query(self._messages)
+
+
+def _newest_first(msgs):
+    # _build_chat_history expects desc(created_at) -> newest first.
+    # Test authors write the list already newest-first, so return as-is.
+    return list(msgs)
+
+
+def test_estimate_tokens():
+    assert _estimate_tokens("") == 0
+    assert _estimate_tokens(None) == 0
+    assert _estimate_tokens("abcd") == 2  # 4//2
+    assert _estimate_tokens("a" * 5) == 2  # max(1, 5//2)=2
+    # just ensure positive monotonic
+    assert _estimate_tokens("x" * 100) == 50
+
+
+def test_history_excludes_latest_user():
+    # newest-first: [current user, prev assistant, older user]
+    msgs = _newest_first([
+        _Msg("user", "current question"),
+        _Msg("assistant", "previous answer"),
+        _Msg("user", "older question"),
+    ])
+    db = _DB(msgs)
+    out = _build_chat_history(db, "c1", max_tokens=10000, exclude_latest_user=True)
+    roles = [m["role"] for m in out]
+    # current user dropped; chronological order = [older user, previous assistant]
+    assert roles == ["user", "assistant"]
+    assert out[0]["content"] == "older question"
+
+
+def test_summary_injected_as_system_first():
+    msgs = _newest_first([
+        _Msg("user", "hi"),
+        _Msg("assistant", "hello"),
+    ])
+    db = _DB(msgs, summary=_Summary("用户想做图片生成"))
+    out = _build_chat_history(db, "c1", max_tokens=10000, exclude_latest_user=True)
+    assert out[0]["role"] == "system"
+    assert out[0]["content"].startswith("【对话历史摘要")
+    assert "用户想做图片生成" in out[0]["content"]
+    # after summary: chronological history (assistant then user 'hi' excluded? exclude_latest_user drops 'hi')
+    assert out[1]["role"] == "assistant"
+
+
+def test_budget_truncation():
+    # 5 assistant messages each ~200 tokens; budget small -> truncated
+    msgs = _newest_first([_Msg("assistant", "x" * 400) for _ in range(5)])
+    db = _DB(msgs)
+    out = _build_chat_history(db, "c1", max_tokens=500, exclude_latest_user=False)
+    # each msg ~200 tokens; budget 500 -> keep newest ~2
+    assert len(out) <= 3
+    total = sum(_estimate_tokens(m["content"]) for m in out)
+    assert total <= 500 + 200  # within budget (+1 msg slack)
+
+
+def test_no_summary_when_absent():
+    msgs = _newest_first([_Msg("user", "hi"), _Msg("assistant", "hello")])
+    db = _DB(msgs)
+    out = _build_chat_history(db, "c1", max_tokens=10000, exclude_latest_user=True)
+    # 'hi' excluded; only assistant remains, no system summary
+    assert all(m["role"] != "system" for m in out)
+    assert [m["role"] for m in out] == ["assistant"]

frontend/src/App.tsx

@@ -45,6 +45,7 @@ const Achievement = React.lazy(() => import('@/pages/admin/Achievement'));
 const Tenant = React.lazy(() => import('@/pages/admin/Tenant'));
 const Billing = React.lazy(() => import('@/pages/admin/Billing'));
 const Analytics = React.lazy(() => import('@/pages/admin/Analytics'));
+const Observability = React.lazy(() => import('@/pages/admin/Observability'));
 const AdminKnowledge = React.lazy(() => import('@/pages/admin/Knowledge'));
 const AdminWorkflow = React.lazy(() => import('@/pages/admin/Workflow'));
 const AdminStorage = React.lazy(() => import('@/pages/admin/Storage'));
@@ -151,6 +152,7 @@ const App: React.FC = () => {
             <Route path="tenant" element={<Tenant />} />
             <Route path="billing" element={<Billing />} />
             <Route path="analytics" element={<Analytics />} />
+      <Route path="observability" element={<Observability />} />
             <Route path="knowledge" element={<AdminKnowledge />} />
             <Route path="workflow" element={<AdminWorkflow />} />
             <Route path="storage" element={<AdminStorage />} />

frontend/src/api/index.ts

@@ -527,6 +527,7 @@ export const adminAPI = {
   getRecentAudit: () => get<any[]>('/admin/dashboard/recent-audit'),
 
     getDailyStats: (days?: number) => get<{ days: number; data: Array<{ date: string; tokens: number }> }>(`/admin/dashboard/daily-stats${days ? `?days=${days}` : ''}`),
+    getObservabilitySummary: (days?: number) => get<any>(`/admin/observability/summary${days ? `?days=${days}` : ''}`),
 
   // 用户管理
 
@@ -886,6 +887,10 @@ export const adminAPI = {
 
   getAdminAgentReviews: (id: string) => get<any>(`/admin/agents/${id}/reviews`),
 
+  // Phase 3.1: 工具/MCP 权限沙箱 (tool_policy)
+  getAgentToolPolicy: (id: string) => get<any>(`/admin/agents/${id}/tool-policy`),
+  setAgentToolPolicy: (id: string, toolPolicy: any) => put<any>(`/admin/agents/${id}/tool-policy`, { tool_policy: toolPolicy }),
+
   getAdminAvailableSkills: (params?: any) => {
 
     const query = params ? '?' + Object.entries(params).filter(([_, v]) => v !== undefined && v !== '').map(([k, v]) => `${k}=${v}`).join('&') : '';

frontend/src/components/layout/AdminLayout.tsx

@@ -97,6 +97,7 @@ const adminNavGroups: NavGroup[] = [
     icon: 'developer',
     items: [
       { path: '/admin/analytics', icon: 'analytics', label: '数据分析' },
+      { path: '/admin/observability', icon: 'observability', label: '调用可观测' },
       { path: '/admin/workflow', icon: 'workflow', label: '工作流编排' },
       { path: '/admin/apps', icon: 'apps', label: 'AI 应用管理' },
       { path: '/admin/code-exec', icon: 'code', label: '代码执行沙箱' },
@@ -154,6 +155,7 @@ const adminIconPaths: Record<string, JSX.Element> = {
   billing: <svg width="18" height="18" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="1.8" strokeLinecap="round" strokeLinejoin="round"><rect x="2" y="5" width="20" height="14" rx="2"/><line x1="2" y1="10" x2="22" y2="10"/><line x1="6" y1="15" x2="10" y2="15"/></svg>,
 
   analytics: <svg width="18" height="18" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="1.8" strokeLinecap="round" strokeLinejoin="round"><line x1="18" y1="20" x2="18" y2="10"/><line x1="12" y1="20" x2="12" y2="4"/><line x1="6" y1="20" x2="6" y2="14"/><line x1="3" y1="20" x2="21" y2="20"/></svg>,
+  observability: <svg width="18" height="18" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="1.8" strokeLinecap="round" strokeLinejoin="round"><path d="M3 12h4l3 8 4-16 3 8h4"/></svg>,
 
   imbot: <svg width="18" height="18" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="1.8" strokeLinecap="round" strokeLinejoin="round"><path d="M21 11.5a8.38 8.38 0 0 1-.9 3.8 8.5 8.5 0 0 1-7.6 4.7 8.38 8.38 0 0 1-3.8-.9L3 21l1.9-5.7a8.38 8.38 0 0 1-.9-3.8 8.5 8.5 0 0 1 4.7-7.6 8.38 8.38 0 0 1 3.8-.9h.5a8.48 8.48 0 0 1 8 8v.5z"/></svg>,
 

frontend/src/pages/admin/Agents.tsx

@@ -105,6 +105,10 @@ const Agents: React.FC = () => {
   // Available skills for linking
   const [availableSkills, setAvailableSkills] = useState<any[]>([]);
   const [availableModels, setAvailableModels] = useState<AvailableModel[]>([]);
+  // Available MCP servers for tool_policy sandbox allowlist
+  const [availableMcps, setAvailableMcps] = useState<any[]>([]);
+  // Tool policy (sandbox) — null means disabled / no policy
+  const [toolPolicy, setToolPolicy] = useState<any>(null);
 
   // Toast
   const [toast, setToast] = useState<{ msg: string; type: 'success' | 'error' } | null>(null);
@@ -144,14 +148,17 @@ const Agents: React.FC = () => {
   // Load available skills & models
   const loadAvailable = async () => {
     try {
-      const [skillsResult, modelsResult] = await Promise.all([
+      const [skillsResult, modelsResult, mcpsResult] = await Promise.all([
         adminAPI.getAdminAvailableSkills({ page_size: 50 }) as any,
         adminAPI.getAdminAvailableModels() as any,
+        adminAPI.getAdminMcpServers({ page_size: 50 }) as any,
       ]);
       const skills = (skillsResult.data || skillsResult).items || [];
       const models = (modelsResult.data || modelsResult) || [];
+      const mcps = (mcpsResult.data || mcpsResult).items || [];
       setAvailableSkills(skills);
       setAvailableModels(models);
+      setAvailableMcps(mcps);
     } catch {}
   };
 
@@ -187,6 +194,7 @@ const Agents: React.FC = () => {
       memory_enabled: false,
       reasoning_enabled: false,
     });
+    setToolPolicy(null);
     setShowModal(true);
   };
 
@@ -194,6 +202,7 @@ const Agents: React.FC = () => {
   const openEdit = async (agent: Agent) => {
     setEditingAgent(agent);
     await loadAvailable();
+    await openEditLoadPolicy(agent.id);
 
     const cfg = agent.config || {};
     setForm({
@@ -213,7 +222,15 @@ const Agents: React.FC = () => {
     setShowModal(true);
   };
 
-  // Open detail
+  // Fetch existing tool_policy (sandbox) for this agent
+  const openEditLoadPolicy = async (agentId: string) => {
+    try {
+      const tpRes = await adminAPI.getAgentToolPolicy(agentId) as any;
+      setToolPolicy(tpRes?.data?.tool_policy || null);
+    } catch {
+      setToolPolicy(null);
+    }
+  };
   const openDetail = async (agent: Agent) => {
     setDetailAgent(agent);
     setShowDetail(true);
@@ -246,7 +263,13 @@ const Agents: React.FC = () => {
     try {
       if (editingAgent) {
         await adminAPI.updateAdminAgent(editingAgent.id, payload);
+        // Phase 3.1: persist tool_policy sandbox (null clears it)
+        try {
+          await adminAPI.setAgentToolPolicy(editingAgent.id, toolPolicy);
           showToast('Agent 已更新');
+        } catch (pe: any) {
+          showToast(`Agent 已更新，但策略保存失败: ${pe.message || pe}`, 'error');
+        }
       } else {
         await adminAPI.createAdminAgent(payload);
         showToast('Agent 创建成功');
@@ -612,6 +635,87 @@ const Agents: React.FC = () => {
                   </div>
                 )}
               </div>
+              {editingAgent && (
+                <div style={{ gridColumn: '1 / -1' }}>
+                  <hr style={{ border: 'none', borderTop: '1px solid #E5E7EB', margin: '16px 0' }} />
+                  <div style={{ fontWeight: 600, marginBottom: 12 }}>🛡️ 工具权限沙箱 (tool_policy)</div>
+                  <label style={{ display: 'flex', alignItems: 'center', gap: 8, cursor: 'pointer', marginBottom: 12 }}>
+                    <input type="checkbox" checked={toolPolicy !== null} onChange={e => {
+                      if (e.target.checked) {
+                        setToolPolicy({ allowed_tools: { skill_ids: [], mcp_ids: [] }, max_calls_per_conversation: null, per_round_cap: null, fallback_message: '' });
+                      } else {
+                        setToolPolicy(null);
+                      }
+                    }} />
+                    启用工具/MCP 权限沙箱（限制该 Agent 可调用的工具与调用频次）
+                  </label>
+                  {toolPolicy && (
+                    <div style={{ display: 'flex', flexDirection: 'column', gap: 16 }}>
+                      <div className="form-group" style={{ marginBottom: 0 }}>
+                        <label className="form-label">允许调用的技能（不选 = 禁止调用任何技能）</label>
+                        <div style={{ display: 'flex', flexWrap: 'wrap', gap: 6, maxHeight: 160, overflowY: 'auto', padding: 8, border: '1px solid #E5E7EB', borderRadius: 6 }}>
+                          {availableSkills.length === 0 ? (
+                            <span style={{ color: '#9CA3AF', fontSize: 13 }}>暂无技能</span>
+                          ) : availableSkills.map((skill: any) => {
+                            const checked = (toolPolicy.allowed_tools?.skill_ids || []).includes(skill.id);
+                            return (
+                              <label key={skill.id} style={{ display: 'flex', alignItems: 'center', gap: 4, padding: '4px 10px', borderRadius: 12, fontSize: 12, cursor: 'pointer', background: checked ? '#EEF2FF' : '#F9FAFB', border: `1px solid ${checked ? '#6366F1' : '#E5E7EB'}`, color: checked ? '#6366F1' : '#374151' }}>
+                                <input type="checkbox" style={{ display: 'none' }} checked={checked} onChange={() => {
+                                  const cur = toolPolicy.allowed_tools?.skill_ids || [];
+                                  const next = checked ? cur.filter((x: string) => x !== skill.id) : [...cur, skill.id];
+                                  setToolPolicy({ ...toolPolicy, allowed_tools: { ...(toolPolicy.allowed_tools || {}), skill_ids: next } });
+                                }} />
+                                {skill.skill_name}
+                              </label>
+                            );
+                          })}
+                        </div>
+                      </div>
+                      <div className="form-group" style={{ marginBottom: 0 }}>
+                        <label className="form-label">允许调用的 MCP 服务（不选 = 禁止调用任何 MCP）</label>
+                        <div style={{ display: 'flex', flexWrap: 'wrap', gap: 6, maxHeight: 160, overflowY: 'auto', padding: 8, border: '1px solid #E5E7EB', borderRadius: 6 }}>
+                          {availableMcps.length === 0 ? (
+                            <span style={{ color: '#9CA3AF', fontSize: 13 }}>暂无 MCP 服务</span>
+                          ) : availableMcps.map((m: any) => {
+                            const checked = (toolPolicy.allowed_tools?.mcp_ids || []).includes(m.id);
+                            return (
+                              <label key={m.id} style={{ display: 'flex', alignItems: 'center', gap: 4, padding: '4px 10px', borderRadius: 12, fontSize: 12, cursor: 'pointer', background: checked ? '#EEF2FF' : '#F9FAFB', border: `1px solid ${checked ? '#6366F1' : '#E5E7EB'}`, color: checked ? '#6366F1' : '#374151' }}>
+                                <input type="checkbox" style={{ display: 'none' }} checked={checked} onChange={() => {
+                                  const cur = toolPolicy.allowed_tools?.mcp_ids || [];
+                                  const next = checked ? cur.filter((x: string) => x !== m.id) : [...cur, m.id];
+                                  setToolPolicy({ ...toolPolicy, allowed_tools: { ...(toolPolicy.allowed_tools || {}), mcp_ids: next } });
+                                }} />
+                                {m.name}
+                              </label>
+                            );
+                          })}
+                        </div>
+                      </div>
+                      <div style={{ display: 'grid', gridTemplateColumns: '1fr 1fr', gap: 16 }}>
+                        <div className="form-group" style={{ marginBottom: 0 }}>
+                          <label className="form-label">单对话最大调用次数（留空=不限制）</label>
+                          <input className="admin-form-input" type="number" min="0"
+                            value={toolPolicy.max_calls_per_conversation ?? ''}
+                            onChange={e => setToolPolicy({ ...toolPolicy, max_calls_per_conversation: e.target.value === '' ? null : parseInt(e.target.value) })} />
+                        </div>
+                        <div className="form-group" style={{ marginBottom: 0 }}>
+                          <label className="form-label">单轮最大调用次数（留空=不限制）</label>
+                          <input className="admin-form-input" type="number" min="0"
+                            value={toolPolicy.per_round_cap ?? ''}
+                            onChange={e => setToolPolicy({ ...toolPolicy, per_round_cap: e.target.value === '' ? null : parseInt(e.target.value) })} />
+                        </div>
+                      </div>
+                      <div className="form-group" style={{ marginBottom: 0 }}>
+                        <label className="form-label">额度耗尽提示语（可选）</label>
+                        <textarea className="admin-form-input" rows={2}
+                          value={toolPolicy.fallback_message || ''}
+                          onChange={e => setToolPolicy({ ...toolPolicy, fallback_message: e.target.value })}
+                          placeholder="例如：该智能体已达到工具调用上限，请开启新对话或调整智能体设置。" />
+                      </div>
+                    </div>
+                  )}
+                </div>
+              )}
             </div>
             <div className="modal-footer">
               <button className="admin-btn" onClick={() => setShowModal(false)}>取消</button>

frontend/src/pages/admin/Observability.tsx

@@ -0,0 +1,165 @@
+import { useEffect, useState } from 'react';
+import { adminAPI } from '@/api';
+
+interface Summary {
+  totals: { calls: number; tokens: number; cost: number; users: number };
+  by_model: { model_name: string; calls: number; tokens: number; cost: number }[];
+  by_user: { user_id: string; username: string; calls: number; tokens: number; cost: number }[];
+  daily: { date: string; tokens: number; cost: number; calls: number }[];
+  recent: { trace_id: string | null; model_name: string; tokens: number; cost: number; created_at: string | null }[];
+}
+
+const ACCENT = '#5B5FED';
+const ACCENT_HOVER = '#4A4ECC';
+
+export default function Observability() {
+  const [days, setDays] = useState(30);
+  const [data, setData] = useState<Summary | null>(null);
+  const [loading, setLoading] = useState(false);
+  const [err, setErr] = useState('');
+
+  useEffect(() => {
+    let alive = true;
+    setLoading(true);
+    setErr('');
+    adminAPI.getObservabilitySummary(days)
+      .then((d: Summary) => { if (alive) setData(d); })
+      .catch((e: any) => { if (alive) setErr(e?.message || '加载失败'); })
+      .finally(() => { if (alive) setLoading(false); });
+    return () => { alive = false; };
+  }, [days]);
+
+  const maxTokens = data ? Math.max(1, ...data.daily.map(d => d.tokens)) : 1;
+  const maxModel = data ? Math.max(1, ...data.by_model.map(m => m.tokens)) : 1;
+  const fmt = (n: number) => n.toLocaleString('zh-CN');
+  const fmtCost = (n: number) => `¥${n.toFixed(4)}`;
+
+  const card: React.CSSProperties = {
+    background: '#fff', border: '1px solid #eceef5', borderRadius: 16,
+    padding: 20, boxShadow: '0 1px 3px rgba(20,30,60,0.04)', marginBottom: 18,
+  };
+  const stat: React.CSSProperties = {
+    flex: 1, minWidth: 150, background: '#fff', border: '1px solid #eceef5',
+    borderRadius: 16, padding: 18, boxShadow: '0 1px 3px rgba(20,30,60,0.04)',
+  };
+
+  return (
+    <div style={{ padding: 24, maxWidth: 1160, margin: '0 auto', color: '#1f2330' }}>
+      <div style={{ display: 'flex', alignItems: 'center', justifyContent: 'space-between', marginBottom: 20, flexWrap: 'wrap', gap: 12 }}>
+        <div>
+          <h2 style={{ margin: 0, fontSize: 22, fontWeight: 700 }}>调用可观测</h2>
+          <div style={{ color: '#8a90a2', fontSize: 13, marginTop: 4 }}>
+            媒体 / LLM 调用归因 · 基于 trace_id 关联请求链路（Phase 2.2）
+          </div>
+        </div>
+        <div style={{ display: 'flex', gap: 8 }}>
+          {[7, 30, 90].map(d => (
+            <button key={d} onClick={() => setDays(d)}
+              style={{
+                padding: '7px 14px', borderRadius: 10, cursor: 'pointer', fontSize: 13,
+                border: `1px solid ${days === d ? ACCENT : '#e2e5ee'}`,
+                background: days === d ? ACCENT : '#fff',
+                color: days === d ? '#fff' : '#5b6172', fontWeight: 600,
+                transition: 'all .15s',
+              }}>
+              {d} 天
+            </button>
+          ))}
+        </div>
+      </div>
+
+      {err && <div style={{ ...card, borderColor: '#f3c2c2', color: '#c0392b' }}>{err}</div>}
+      {loading && !data && <div style={{ color: '#8a90a2' }}>加载中…</div>}
+
+      {data && (
+        <>
+          <div style={{ display: 'flex', gap: 14, flexWrap: 'wrap', marginBottom: 18 }}>
+            <div style={stat}><div style={{ color: '#8a90a2', fontSize: 12 }}>调用次数</div><div style={{ fontSize: 24, fontWeight: 700, marginTop: 6 }}>{fmt(data.totals.calls)}</div></div>
+            <div style={stat}><div style={{ color: '#8a90a2', fontSize: 12 }}>Token 消耗</div><div style={{ fontSize: 24, fontWeight: 700, marginTop: 6 }}>{fmt(data.totals.tokens)}</div></div>
+            <div style={stat}><div style={{ color: '#8a90a2', fontSize: 12 }}>成本</div><div style={{ fontSize: 24, fontWeight: 700, marginTop: 6, color: ACCENT }}>{fmtCost(data.totals.cost)}</div></div>
+            <div style={stat}><div style={{ color: '#8a90a2', fontSize: 12 }}>活跃用户</div><div style={{ fontSize: 24, fontWeight: 700, marginTop: 6 }}>{fmt(data.totals.users)}</div></div>
+          </div>
+
+          <div style={card}>
+            <h3 style={{ margin: '0 0 14px', fontSize: 16 }}>按模型</h3>
+            <div style={{ display: 'flex', flexDirection: 'column', gap: 10 }}>
+              {data.by_model.length === 0 && <div style={{ color: '#8a90a2', fontSize: 13 }}>暂无数据</div>}
+              {data.by_model.map(m => (
+                <div key={m.model_name} style={{ display: 'flex', alignItems: 'center', gap: 12 }}>
+                  <div style={{ width: 150, fontSize: 13, fontWeight: 600, overflow: 'hidden', textOverflow: 'ellipsis', whiteSpace: 'nowrap' }}>{m.model_name}</div>
+                  <div style={{ flex: 1, height: 10, background: '#f1f3f9', borderRadius: 6, overflow: 'hidden' }}>
+                    <div style={{ width: `${(m.tokens / maxModel) * 100}%`, height: '100%', background: ACCENT, borderRadius: 6 }} />
+                  </div>
+                  <div style={{ width: 90, textAlign: 'right', fontSize: 13, color: '#5b6172' }}>{fmt(m.tokens)}</div>
+                  <div style={{ width: 90, textAlign: 'right', fontSize: 13, color: ACCENT }}>{fmtCost(m.cost)}</div>
+                </div>
+              ))}
+            </div>
+          </div>
+
+          <div style={card}>
+            <h3 style={{ margin: '0 0 14px', fontSize: 16 }}>每日趋势（Token）</h3>
+            <div style={{ display: 'flex', alignItems: 'flex-end', gap: 6, height: 140, overflowX: 'auto', paddingBottom: 4 }}>
+              {data.daily.length === 0 && <div style={{ color: '#8a90a2', fontSize: 13 }}>暂无数据</div>}
+              {data.daily.map(d => (
+                <div key={d.date} title={`${d.date} · ${fmt(d.tokens)} tokens · ${fmtCost(d.cost)}`}
+                  style={{ display: 'flex', flexDirection: 'column', alignItems: 'center', gap: 4, minWidth: 22 }}>
+                  <div style={{ width: 16, height: `${(d.tokens / maxTokens) * 110}px`, background: ACCENT, borderRadius: '4px 4px 0 0', opacity: 0.85 }} />
+                  <div style={{ fontSize: 9, color: '#aab', transform: 'rotate(-45deg)', whiteSpace: 'nowrap' }}>{d.date.slice(5)}</div>
+                </div>
+              ))}
+            </div>
+          </div>
+
+          <div style={{ display: 'flex', gap: 18, flexWrap: 'wrap' }}>
+            <div style={{ ...card, flex: 1, minWidth: 320 }}>
+              <h3 style={{ margin: '0 0 14px', fontSize: 16 }}>按用户（Top 20）</h3>
+              <table style={{ width: '100%', borderCollapse: 'collapse', fontSize: 13 }}>
+                <thead><tr style={{ color: '#8a90a2', textAlign: 'left' }}>
+                  <th style={th}>用户</th><th style={thR}>调用</th><th style={thR}>Token</th><th style={thR}>成本</th>
+                </tr></thead>
+                <tbody>
+                  {data.by_user.map(u => (
+                    <tr key={u.user_id} style={{ borderTop: '1px solid #f1f3f9' }}>
+                      <td style={td}>{u.username}</td>
+                      <td style={tdR}>{fmt(u.calls)}</td>
+                      <td style={tdR}>{fmt(u.tokens)}</td>
+                      <td style={{ ...tdR, color: ACCENT }}>{fmtCost(u.cost)}</td>
+                    </tr>
+                  ))}
+                  {data.by_user.length === 0 && <tr><td colSpan={4} style={{ ...td, color: '#8a90a2' }}>暂无数据</td></tr>}
+                </tbody>
+              </table>
+            </div>
+          </div>
+
+          <div style={card}>
+            <h3 style={{ margin: '0 0 14px', fontSize: 16 }}>最近调用（trace_id 可下钻）</h3>
+            <table style={{ width: '100%', borderCollapse: 'collapse', fontSize: 13 }}>
+              <thead><tr style={{ color: '#8a90a2', textAlign: 'left' }}>
+                <th style={th}>Trace ID</th><th style={th}>模型</th><th style={thR}>Token</th><th style={thR}>成本</th><th style={thR}>时间</th>
+              </tr></thead>
+              <tbody>
+                {data.recent.map((r, i) => (
+                  <tr key={(r.trace_id || '') + i} style={{ borderTop: '1px solid #f1f3f9' }}>
+                    <td style={{ ...td, fontFamily: 'monospace', fontSize: 12, maxWidth: 200, overflow: 'hidden', textOverflow: 'ellipsis', whiteSpace: 'nowrap' }}>{r.trace_id || '—'}</td>
+                    <td style={td}>{r.model_name}</td>
+                    <td style={tdR}>{fmt(r.tokens)}</td>
+                    <td style={{ ...tdR, color: ACCENT }}>{fmtCost(r.cost)}</td>
+                    <td style={tdR}>{r.created_at || '—'}</td>
+                  </tr>
+                ))}
+                {data.recent.length === 0 && <tr><td colSpan={5} style={{ ...td, color: '#8a90a2' }}>暂无数据</td></tr>}
+              </tbody>
+            </table>
+          </div>
+        </>
+      )}
+    </div>
+  );
+}
+
+const th: React.CSSProperties = { padding: '8px 6px', fontWeight: 600, fontSize: 12 };
+const thR: React.CSSProperties = { ...th, textAlign: 'right' };
+const td: React.CSSProperties = { padding: '8px 6px' };
+const tdR: React.CSSProperties = { ...td, textAlign: 'right', color: '#5b6172' };

migrations/021_create_conversation_summaries.sql

@@ -0,0 +1,7 @@
+CREATE TABLE IF NOT EXISTS conversation_summaries (
+  conversation_id VARCHAR(64) NOT NULL,
+  summary_text TEXT NULL,
+  token_count INT NULL DEFAULT 0,
+  updated_at DATETIME(3) NULL,
+  PRIMARY KEY (conversation_id)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;

migrations/022_add_tool_policy.sql

@@ -0,0 +1,15 @@
+-- Phase 3.1: MarketApp 增加 tool_policy（Agent 工具/MCP 权限沙箱策略）
+-- 幂等：仅当列不存在时才 ALTER
+SET @db = 'aiflow';
+SET @tbl = 'market_apps';
+SET @col = 'tool_policy';
+SET @exists = (
+    SELECT COUNT(*) FROM information_schema.columns
+    WHERE table_schema = @db AND table_name = @tbl AND column_name = @col
+);
+SET @sql = IF(@exists = 0,
+    'ALTER TABLE market_apps ADD COLUMN tool_policy JSON NULL',
+    'SELECT 1');
+PREPARE stmt FROM @sql;
+EXECUTE stmt;
+DEALLOCATE PREPARE stmt;