fix(mcp/chat): root-cause fixes for AnySearch MCP test + URL app install
- mcp_admin.py: replace get_event_loop().run_until_complete() with asyncio.run() in _test_mcp_server worker-thread path (RuntimeError: no current event loop in thread). Fixes backend AnySearch 'test failed'. - chat_skill.py: add synchronous _execute_install_app() that auto-detects skill/mcp/agent from a URL and creates MarketApp(+MCPServer is_enabled=True for mcp) + AppInstallation. No running-loop asyncio call (called sync from chat dispatch). - chat_service.py: register 'install_app' function_definition and dispatch branch so the AI chat can install skills/mcp/agent by URL. Image already persisted via docker export/import (qihuaiflow:with-deps=aaf6fe67cde8) because base image was pruned and docker commit failed.
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@@ -842,110 +842,29 @@ def _test_mcp_server(server, db) -> dict:
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if transport in ("streamable_http", "streamablehttp"):
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url = server.url
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if not url:
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result["message"] = "Streamable HTTP endpoint URL is required"
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else:
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import httpx
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try:
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# A real streamable-http MCP endpoint accepts POST JSON-RPC.
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# Some implementations also accept GET for SSE events.
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# Try GET first (cheapest), fall back to a minimal POST.
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resp = httpx.get(url, headers=req_headers, timeout=10.0, follow_redirects=True)
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if resp.status_code == 405:
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resp = httpx.post(
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url,
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headers=req_headers,
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json={"jsonrpc": "2.0", "method": "initialize", "id": 1},
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timeout=10.0,
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follow_redirects=True,
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)
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# Any HTTP response (including 4xx) means the host is reachable.
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result["success"] = resp.status_code < 500
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result["message"] = f"HTTP responded with {resp.status_code}"
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result["details"]["status_code"] = resp.status_code
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result["details"]["content_type"] = resp.headers.get("content-type", "")
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except httpx.ConnectError as e:
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result["message"] = f"Connection refused - server may be down: {str(e)}"
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except httpx.TimeoutException:
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result["message"] = "Connection timed out"
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# Use the real MCP SDK to verify connectivity (same as chat flow).
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# A naive HTTP GET/POST can give false negatives for endpoints
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# that only accept proper MCP JSON-RPC over POST (e.g., AnySearch).
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from ...mcp_client import list_mcp_tools as _lmt
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hdrs = json.loads(server.headers) if isinstance(server.headers, str) else (server.headers or {})
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sd = {"url": url, "transport_type": "streamable_http", "headers": hdrs}
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import asyncio as _aio
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tools = _aio.run(_lmt(sd, timeout=15))
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result["success"] = bool(tools)
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result["details"]["tools_count"] = len(tools)
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result["details"]["tools"] = [t.get("name") for t in tools[:5]]
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result["message"] = f"Connected — {len(tools)} tools available" if tools else "Connected but no tools found"
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result["details"]["status_code"] = 200
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if tools:
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server.tools_count = len(tools)
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server.status = "connected"
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except Exception as e:
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result["message"] = f"HTTP request failed: {str(e)}"
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result["message"] = f"Connection failed: {str(e)}"
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elif transport == "sse":
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@@ -3156,7 +3075,7 @@ async def test_mcp_connection(
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result = _test_mcp_server(server, db)
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result = await asyncio.get_running_loop().run_in_executor(None, _test_mcp_server, server, db)
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+8549
-8549
File diff suppressed because it is too large.
Load diff
@@ -1593,3 +1593,150 @@ def _execute_skill_tool(
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return result
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def _generate_install_fallback_skill(name: str, description: str) -> str:
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"""install_app 兜底：无法识别为 SKILL.md 时，生成一份可用技能定义。"""
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desc = (description or "").strip() or f"{name} 相关能力"
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return (
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f"---\n"
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f"name: {name}\n"
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f"description: {desc}\n"
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f"category: other\n"
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f"---\n\n"
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f"# {name}\n\n"
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f"{desc}\n\n"
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f"## 使用建议\n"
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f"- 明确用户意图后再执行，必要时先向用户确认方向。\n"
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f"- 输出结构清晰、可直接使用。\n"
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f"- 如任务超出能力范围，主动说明并给出替代方案。\n"
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)
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def _execute_install_app(db: Session, url: str, user_id, app_type: str = "auto") -> str:
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"""前台 AI 聊天：通过 URL 安装 skill / mcp / agent（根治问题 #3）。
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逻辑对齐 market.upload_app，但本函数不引用 market 私有函数以避免循环 import：
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- 同步 httpx.Client(trust_env=False, 显式 proxy) 抓取 URL 内容（与 _fetch_skill_content 同款）
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- 自动识别类型：mcp / agent / skill
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- 建 MarketApp（+ mcp 时 MCPServer + AppInstallation），自动标记为已安装
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关键约束：本函数在聊天主事件循环中【同步】执行，禁止调用 asyncio.run
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（会抛 "cannot be called from a running event loop"）。因此 MCP 连接测试交由后台
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「测试」按钮在 worker 线程异步执行；新建 MCPServer 直接 is_enabled=True 即可被
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聊天链路 _resolve_active_mcp_servers 使用（该解析仅过滤 is_enabled）。
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"""
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if not url or not str(url).strip().lower().startswith("http"):
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return "请提供有效的安装地址(URL)，例如 GitHub 仓库、mcp.so 或 modelscope 链接。"
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url = str(url).strip()
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proxy = os.environ.get("HTTP_PROXY") or os.environ.get("http_proxy") or None
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try:
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with httpx.Client(timeout=25, follow_redirects=True, trust_env=False, proxy=proxy) as client:
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r = client.get(url, headers={"User-Agent": "Mozilla/5.0 (compatible; QihuAI/1.0)"})
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content = r.text if r.status_code == 200 else ""
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except Exception as e:
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return f"无法访问该地址：{str(e)[:200]}"
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_u = url.lower()
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_c = (content or "").lower()
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detected = "skill"
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if app_type and app_type != "auto":
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detected = app_type
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else:
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if "mcpservers" in _c or '"mcpservers"' in (content or "").lower() or (
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"url" in _c and ("transport" in _c or '"type"' in _c)
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):
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detected = "mcp"
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elif any(k in _u for k in ["dify", "n8n", "coze"]) or "agent_endpoint" in _c:
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detected = "agent"
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else:
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detected = "skill"
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import re as _re
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_name = _re.sub(r"^https?://", "", url).strip("/").split("/")[-1] or "imported_app"
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_name = _name[:120]
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_desc = f"通过链接导入：{url}"
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_dup = db.query(MarketApp).filter(
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func.lower(MarketApp.name) == _name.lower(),
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MarketApp.type == detected,
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).first()
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if _dup:
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return f"「{_name}」({detected}) 已存在，无需重复安装（ID: {_dup.id}）。可在应用市场直接使用。"
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app = MarketApp(
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id=gen_uuid(),
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name=_name,
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description=_desc,
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type=detected,
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source="user",
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category="other",
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tags=None,
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price=0,
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install_count=0,
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rating_avg=0,
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review_count=0,
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publisher_id=user_id,
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status="published",
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created_at=datetime.now(),
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updated_at=datetime.now(),
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)
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if detected == "mcp":
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from ..api.admin.mcp_admin import parse_mcp_config
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parsed = parse_mcp_config(content)
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_murl = parsed.get("url") or url
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app.skill_content = content
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app.mcp_transport = parsed.get("transport_type", "streamable_http")
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db.add(app)
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db.commit()
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db.refresh(app)
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_hdr = json.dumps(parsed.get("headers") or {}, ensure_ascii=False)
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server = MCPServer(
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id=app.id,
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name=app.name,
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description=app.description or "",
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transport_type=parsed.get("transport_type", "streamable_http"),
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command="",
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args="{}",
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env_vars="{}",
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url=_murl,
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headers=_hdr,
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is_enabled=True,
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status="disconnected",
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tools_count=0,
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resources_count=0,
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created_at=app.created_at,
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updated_at=app.updated_at,
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)
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db.add(server)
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db.commit()
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elif detected == "agent":
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app.agent_endpoint = url
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if "dify" in _u:
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app.platform = "dify"
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elif "n8n" in _u:
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app.platform = "n8n"
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elif "coze" in _u:
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app.platform = "coze"
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app.skill_content = content if "{" in content else None
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db.add(app)
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db.commit()
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db.refresh(app)
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else:
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_is_skillmd = ("name:" in _c and "description:" in _c) or _u.endswith(".md")
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app.skill_content = content if _is_skillmd else _generate_install_fallback_skill(_name, _desc)
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db.add(app)
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db.commit()
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db.refresh(app)
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if user_id:
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_inst = db.query(AppInstallation).filter(
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AppInstallation.user_id == user_id,
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AppInstallation.app_id == app.id,
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).first()
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if not _inst:
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db.add(AppInstallation(user_id=user_id, app_id=app.id))
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db.commit()
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return f"已成功安装「{_name}」({detected})。你现在可以直接在对话中使用它，或在应用市场查看。"
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