From 6928cb4201c36b674a4b9d4f9aecd87311f66b25 Mon Sep 17 00:00:00 2001 From: kris Date: Mon, 23 Mar 2026 15:31:36 +0800 Subject: [PATCH] feat: extend oneliner execution workspace --- collector-service/app/oneliner_features.py | 601 ++++++++++++++++++++- web/storyforge-web-v4/assets/app.js | 350 +++++++++++- 2 files changed, 928 insertions(+), 23 deletions(-) diff --git a/collector-service/app/oneliner_features.py b/collector-service/app/oneliner_features.py index 759440c..b3f41d3 100644 --- a/collector-service/app/oneliner_features.py +++ b/collector-service/app/oneliner_features.py @@ -71,6 +71,29 @@ class AdminIncidentReviewRequest(BaseModel): review_notes: str = "" +class PlatformAgentSelfCheckRequest(BaseModel): + project_id: str = "" + sample_limit: int = Field(default=3, ge=1, le=12) + remember_summary: bool = True + + +class PlatformSkillReviewRequest(BaseModel): + project_id: str = "" + accepted: bool = True + score: float = Field(default=0.8, ge=0.0, le=1.0) + status: str = "" + summary: str = "" + review_notes: str = "" + + +class OneLinerActionExecuteRequest(BaseModel): + action_key: str + project_id: str = "" + platform: str = "" + session_id: str = "" + payload: dict[str, Any] = Field(default_factory=dict) + + INTENT_ACTIONS: dict[str, list[dict[str, Any]]] = { "create_project": [{"key": "goto-intake", "label": "去我的项目", "kind": "navigate"}], "create_assistant": [{"key": "open-create-assistant", "label": "创建 Agent", "kind": "ui_action"}], @@ -279,6 +302,28 @@ def register_oneliner_routes(app: Any, legacy: Any) -> None: def _safe_platform(platform_value: str | None, fallback: str = "douyin") -> str: return legacy.ensure_domestic_platform(platform_value or fallback, allow_blank=not fallback) or fallback + def _route_supported(path: str) -> bool: + return any(getattr(route, "path", "") == path for route in app.routes) + + def _platform_route_checks(platform: str) -> list[dict[str, Any]]: + checks = [ + ("accounts", f"/v2/{platform}/accounts"), + ("workspace", f"/v2/{platform}/accounts/{{account_id}}/workspace"), + ("videos", f"/v2/{platform}/accounts/{{account_id}}/videos"), + ("analyze_account", f"/v2/{platform}/accounts/{{account_id}}/analysis"), + ("analyze_top_videos", f"/v2/{platform}/accounts/{{account_id}}/videos/analyze-top"), + ("similar_searches", f"/v2/{platform}/similar-searches"), + ("benchmark_links", f"/v2/{platform}/accounts/{{account_id}}/benchmark-links"), + ] + return [ + { + "key": key, + "path": path, + "ok": _route_supported(path), + } + for key, path in checks + ] + def _fetch_profile_row(account: dict[str, Any], project_id: str = "") -> dict[str, Any] | None: return legacy.db.fetch_one( "SELECT * FROM oneliner_profiles WHERE user_id = ? AND project_id = ?", @@ -388,6 +433,39 @@ def register_oneliner_routes(app: Any, legacy: Any) -> None: """, (account["id"], project_id, platform), )["count"] + recent_memory_row = legacy.db.fetch_one( + """ + SELECT * FROM agent_memories + WHERE user_id = ? AND project_id = ? AND agent_scope = 'platform' AND platform = ? + ORDER BY updated_at DESC + LIMIT 1 + """, + (account["id"], project_id, platform), + ) + recent_skill_row = legacy.db.fetch_one( + """ + SELECT * FROM agent_skills + WHERE user_id = ? AND project_id = ? AND agent_scope = 'platform' AND platform = ? + ORDER BY + CASE WHEN status = 'validated' THEN 0 WHEN status = 'draft' THEN 1 ELSE 2 END, + updated_at DESC + LIMIT 1 + """, + (account["id"], project_id, platform), + ) + readiness_items = [ + bool(row and row.get("status") == "active"), + bool(assistant), + bool(memory_count), + bool(skill_count), + ] + readiness_score = int(sum(1 for item in readiness_items if item) * 25) + if readiness_score >= 100: + readiness_label = "就绪" + elif readiness_score >= 50: + readiness_label = "可用" + else: + readiness_label = "待补全" return { "id": row["id"] if row else "", "user_id": account["id"], @@ -402,6 +480,10 @@ def register_oneliner_routes(app: Any, legacy: Any) -> None: "config": _parse_json((row or {}).get("config_json"), {}), "memory_count": memory_count, "skill_count": skill_count, + "recent_memory": _memory_payload(recent_memory_row) if recent_memory_row else None, + "recent_skill": _skill_payload(recent_skill_row) if recent_skill_row else None, + "readiness_score": readiness_score, + "readiness_label": readiness_label, "assistant": assistant, "created_at": (row or {}).get("created_at", ""), "updated_at": (row or {}).get("updated_at", ""), @@ -497,6 +579,25 @@ def register_oneliner_routes(app: Any, legacy: Any) -> None: "updated_at": row["updated_at"], } + def _platform_source_samples( + account: dict[str, Any], + *, + project_id: str, + platform: str, + limit: int = 3, + ) -> list[dict[str, Any]]: + safe_limit = max(1, min(int(limit or 3), 12)) + rows = legacy.db.fetch_all( + f""" + SELECT * FROM content_sources + WHERE user_id = ? AND project_id = ? AND platform = ? + ORDER BY updated_at DESC + LIMIT {safe_limit} + """, + (account["id"], project_id, platform), + ) + return [legacy.content_source_payload(row) for row in rows] + def _load_owned_session(session_id: str, account: dict[str, Any]) -> dict[str, Any]: row = legacy.db.fetch_one( "SELECT * FROM oneliner_sessions WHERE id = ? AND user_id = ?", @@ -739,6 +840,29 @@ def register_oneliner_routes(app: Any, legacy: Any) -> None: stored = legacy.db.fetch_one("SELECT * FROM agent_memories WHERE id = ?", (memory_id,)) return _memory_payload(stored) if stored else None + def _remember_platform_observation( + account: dict[str, Any], + *, + project_id: str, + platform: str, + memory_key: str, + title: str, + summary: str, + details: dict[str, Any], + confidence: float = 0.82, + ) -> dict[str, Any]: + request = AgentMemoryUpsertRequest( + project_id=project_id, + subject_type="project", + subject_id=project_id, + memory_key=memory_key, + title=title, + summary=summary, + details=details, + confidence=confidence, + ) + return _upsert_memory(account, agent_scope="platform", platform=platform, request=request) + def _session_context_summary(account: dict[str, Any], project_id: str, platform: str) -> dict[str, Any]: project = _resolve_project(account, project_id or None) assistant = None @@ -749,11 +873,43 @@ def register_oneliner_routes(app: Any, legacy: Any) -> None: "SELECT * FROM platform_agent_profiles WHERE user_id = ? AND project_id = ? AND platform = ?", (account["id"], project["id"], platform), ) if platform else None + oneliner_memory_rows = legacy.db.fetch_all( + """ + SELECT * FROM agent_memories + WHERE user_id = ? AND project_id = ? AND agent_scope = 'oneliner' + ORDER BY updated_at DESC + LIMIT 3 + """, + (account["id"], project["id"]), + ) + platform_memory_rows = legacy.db.fetch_all( + """ + SELECT * FROM agent_memories + WHERE user_id = ? AND project_id = ? AND agent_scope = 'platform' AND platform = ? + ORDER BY updated_at DESC + LIMIT 3 + """, + (account["id"], project["id"], platform), + ) if platform else [] + platform_skill_rows = legacy.db.fetch_all( + """ + SELECT * FROM agent_skills + WHERE user_id = ? AND project_id = ? AND agent_scope = 'platform' AND platform = ? + ORDER BY + CASE WHEN status = 'validated' THEN 0 WHEN status = 'draft' THEN 1 ELSE 2 END, + updated_at DESC + LIMIT 3 + """, + (account["id"], project["id"], platform), + ) if platform else [] return { "project": legacy.project_payload(project), "oneliner_profile": _profile_payload(profile_row, account=account) if profile_row else None, "platform_agent": _platform_agent_payload(account, platform_profile, platform=platform, project_id=project["id"]) if platform else None, "assistant": legacy.assistant_payload(assistant) if assistant else None, + "oneliner_memories": [_memory_payload(row) for row in oneliner_memory_rows], + "platform_memories": [_memory_payload(row) for row in platform_memory_rows], + "platform_skills": [_skill_payload(row) for row in platform_skill_rows], } async def _generate_oneliner_reply( @@ -764,6 +920,40 @@ def register_oneliner_routes(app: Any, legacy: Any) -> None: plan: dict[str, Any], ) -> dict[str, Any]: context = _session_context_summary(account, project_id or "", plan.get("platform") or "") + platform_agent = context.get("platform_agent") or {} + primary_action = (plan.get("suggested_actions") or [{}])[0] if plan.get("suggested_actions") else None + evidence = [] + if platform_agent.get("recent_memory"): + evidence.append( + { + "kind": "memory", + "title": platform_agent["recent_memory"].get("title") or platform_agent["recent_memory"].get("memory_key") or "最近记忆", + "summary": platform_agent["recent_memory"].get("summary", ""), + } + ) + if platform_agent.get("recent_skill"): + evidence.append( + { + "kind": "skill", + "title": platform_agent["recent_skill"].get("name") or platform_agent["recent_skill"].get("skill_key") or "最近技能", + "summary": platform_agent["recent_skill"].get("test_spec", {}).get("summary") + or platform_agent["recent_skill"].get("method", {}).get("summary") + or "", + "score": platform_agent["recent_skill"].get("last_score", 0), + } + ) + blocked_reason = "" + if plan.get("intent_key") == "ops_admin" and account.get("role") != "super_admin": + blocked_reason = "当前账号不是平台最高权限用户，所以不会开放运维 Agent。" + elif plan.get("delivery_mode") == "oneliner": + blocked_reason = "当前更适合由 OneLiner 对话承接，等前端产品化后再下沉到固定 UI。" + next_steps = [] + if primary_action: + next_steps.append(f"优先执行「{primary_action.get('label', primary_action.get('key', '下一步'))}」。") + if platform_agent.get("assistant", {}).get("name"): + next_steps.append(f"默认调度 {platform_agent['assistant']['name']} 作为执行 Agent。") + if evidence: + next_steps.append("我会优先参考该平台 Agent 最近沉淀的方法与技能。") summary_lines = [ f"我理解你的目标是：{plan.get('intent_label', '自定义任务')}。", f"建议优先处理的平台：{plan.get('platform_label', '待判断')}。", @@ -775,9 +965,78 @@ def register_oneliner_routes(app: Any, legacy: Any) -> None: summary_lines.append("当前账号不是平台最高权限用户，所以我不会放出运维 Agent 入口。") if context.get("platform_agent"): summary_lines.append(f"当前 {context['platform_agent']['platform_label']} Agent 已绑定：{context['platform_agent'].get('assistant', {}).get('name') or '未绑定执行 Agent'}。") + if platform_agent.get("recent_memory"): + summary_lines.append(f"最近有效经验：{platform_agent['recent_memory'].get('title') or '一条平台记忆'}。") + if platform_agent.get("recent_skill"): + summary_lines.append(f"最近有效技能：{platform_agent['recent_skill'].get('name') or '一条技能'}。") + secondary_actions: list[dict[str, Any]] = [] + if plan.get("platform"): + secondary_actions.append( + { + "key": "run-oneliner-action", + "label": "运行平台自检", + "kind": "api_action", + "executor_key": "platform-self-check", + "platform": plan.get("platform", ""), + } + ) + secondary_actions.append( + { + "key": "open-platform-agent-detail", + "label": f"查看{plan.get('platform_label', '平台')} Agent", + "kind": "ui_action", + "platform": plan.get("platform", ""), + } + ) + if plan.get("intent_key") in {"storage_status", "custom"}: + secondary_actions.append( + { + "key": "run-oneliner-action", + "label": "查看当前存储状态", + "kind": "api_action", + "executor_key": "storage-status", + "platform": plan.get("platform", ""), + } + ) + if plan.get("intent_key") == "live_recorder": + secondary_actions.append( + { + "key": "run-oneliner-action", + "label": "查看录制状态", + "kind": "api_action", + "executor_key": "live-recorder-status", + "platform": plan.get("platform", ""), + } + ) + if account.get("role") == "super_admin": + secondary_actions.append( + { + "key": "run-oneliner-action", + "label": "重新扫描故障", + "kind": "api_action", + "executor_key": "scan-admin-ops", + "platform": "", + } + ) return { "summary_text": "\n".join([line for line in summary_lines if line.strip()]), "context": context, + "execution_card": { + "intent_key": plan.get("intent_key", "custom"), + "intent_label": plan.get("intent_label", "自定义任务"), + "delivery_mode": plan.get("delivery_mode", "oneliner"), + "platform": plan.get("platform", ""), + "platform_label": plan.get("platform_label", "待判断"), + "platform_agent_name": platform_agent.get("name") or "", + "assistant_name": platform_agent.get("assistant", {}).get("name") or context.get("assistant", {}).get("name") or "", + "readiness_label": platform_agent.get("readiness_label") or "", + "readiness_score": platform_agent.get("readiness_score") or 0, + "primary_action": primary_action or {}, + "blocked_reason": blocked_reason, + "evidence": evidence, + "next_steps": next_steps, + "secondary_actions": secondary_actions, + }, "safe_boundary": { "core_code_locked": True, "tenant_isolation": True, @@ -800,6 +1059,12 @@ def register_oneliner_routes(app: Any, legacy: Any) -> None: def _upsert_platform_profile(account: dict[str, Any], platform: str, request: PlatformAgentProfileRequest) -> dict[str, Any]: project = _resolve_project(account, request.project_id or None) assistant = _resolve_assistant(account, request.assistant_id or None, project["id"]) + if not assistant: + fallback_profile = _fetch_profile_row(account, project["id"]) or _ensure_oneliner_profile(account, project["id"]) + if fallback_profile.get("assistant_id"): + assistant = _resolve_assistant(account, fallback_profile.get("assistant_id"), project["id"]) + if not assistant: + assistant = _resolve_assistant(account, None, project["id"]) existing = legacy.db.fetch_one( "SELECT * FROM platform_agent_profiles WHERE user_id = ? AND project_id = ? AND platform = ?", (account["id"], project["id"], platform), @@ -1105,6 +1370,287 @@ def register_oneliner_routes(app: Any, legacy: Any) -> None: "count": len(created), } + def _admin_ops_overview_payload(admin: dict[str, Any]) -> dict[str, Any]: + incidents = [ + _incident_payload(row) + for row in legacy.db.fetch_all( + "SELECT * FROM admin_ops_incidents ORDER BY updated_at DESC LIMIT 50" + ) + ] + open_incidents = [item for item in incidents if item.get("status") in {"open", "watching", ""}] + severity_counts = { + "error": len([item for item in incidents if item.get("severity") == "error"]), + "warn": len([item for item in incidents if item.get("severity") == "warn"]), + "info": len([item for item in incidents if item.get("severity") == "info"]), + } + failed_jobs = [ + legacy.job_payload(row) + for row in legacy.db.fetch_all( + "SELECT * FROM jobs WHERE status = 'failed' ORDER BY updated_at DESC LIMIT 12" + ) + ] + pending_accounts = [ + legacy.normalize_account(row) + for row in legacy.db.fetch_all("SELECT * FROM accounts WHERE approval_status = 'pending' ORDER BY created_at ASC LIMIT 20") + ] + return { + "incidents": incidents, + "incident_count": len(incidents), + "open_incident_count": len(open_incidents), + "severity_counts": severity_counts, + "failed_jobs": failed_jobs, + "failed_job_count": len(failed_jobs), + "pending_accounts": pending_accounts, + "pending_account_count": len(pending_accounts), + "integration_health": legacy.integrations_health(admin), + } + + def _platform_self_check( + account: dict[str, Any], + *, + platform: str, + project_id: str, + sample_limit: int = 3, + remember_summary: bool = True, + ) -> dict[str, Any]: + project = _resolve_project(account, project_id or None) + normalized_platform = _safe_platform(platform) + profile = _platform_agent_payload( + account, + legacy.db.fetch_one( + "SELECT * FROM platform_agent_profiles WHERE user_id = ? AND project_id = ? AND platform = ?", + (account["id"], project["id"], normalized_platform), + ), + platform=normalized_platform, + project_id=project["id"], + ) + route_checks = _platform_route_checks(normalized_platform) + route_ok_count = len([item for item in route_checks if item["ok"]]) + route_ratio = (route_ok_count / len(route_checks)) if route_checks else 0 + source_samples = _platform_source_samples(account, project_id=project["id"], platform=normalized_platform, limit=sample_limit) + signal_checks = [ + ("配置激活", bool(profile.get("status") == "active")), + ("已绑定执行 Agent", bool(profile.get("assistant_id"))), + ("已有平台记忆", bool(profile.get("memory_count"))), + ("已有平台技能", bool(profile.get("skill_count"))), + ("已有平台账号源", bool(source_samples)), + ] + signal_score = sum(1 for _, ok in signal_checks if ok) * 12 + route_score = int(route_ratio * 40) + score = min(100, signal_score + route_score) + if score >= 85: + verdict = "validated" + label = "稳定" + elif score >= 60: + verdict = "usable" + label = "可用" + else: + verdict = "needs_work" + label = "待加强" + suggestions = [] + if not profile.get("assistant_id"): + suggestions.append("先给平台 Agent 绑定一个执行 Agent。") + if not profile.get("memory_count"): + suggestions.append("补一条平台记忆，沉淀最近有效经验。") + if not profile.get("skill_count"): + suggestions.append("补一条可验收的平台技能。") + if not source_samples: + suggestions.append("先导入至少一个该平台账号源，避免空跑。") + if route_ratio < 1: + suggestions.append("补齐当前平台 workbench 路由，避免调度时出现断点。") + payload = { + "platform": normalized_platform, + "platform_label": legacy.platform_label(normalized_platform), + "project_id": project["id"], + "score": score, + "readiness_label": label, + "verdict": verdict, + "route_checks": route_checks, + "signals": [{"label": name, "ok": ok} for name, ok in signal_checks], + "source_count": len(source_samples), + "source_samples": source_samples, + "checked_at": now(), + "suggestions": suggestions, + "profile": profile, + } + if remember_summary: + _remember_platform_observation( + account, + project_id=project["id"], + platform=normalized_platform, + memory_key=f"self_check::{normalized_platform}", + title=f"{legacy.platform_label(normalized_platform)} Agent 自检", + summary=f"平台自检得分 {score}，当前判定为{label}。", + details=payload, + confidence=0.88 if score >= 85 else 0.72, + ) + return payload + + def _review_platform_skill( + account: dict[str, Any], + *, + platform: str, + skill_id: str, + request: PlatformSkillReviewRequest, + ) -> dict[str, Any]: + project = _resolve_project(account, request.project_id or None) + normalized_platform = _safe_platform(platform) + current = legacy.db.fetch_one( + """ + SELECT * FROM agent_skills + WHERE id = ? AND user_id = ? AND project_id = ? AND agent_scope = 'platform' AND platform = ? + """, + (skill_id, account["id"], project["id"], normalized_platform), + ) + if not current: + raise HTTPException(status_code=404, detail="Platform skill not found") + accepted = bool(request.accepted) + next_status = (request.status or "").strip() or ("validated" if accepted else "needs_revision") + timestamp = now() + next_success = int(current.get("success_count") or 0) + (1 if accepted else 0) + next_failure = int(current.get("failure_count") or 0) + (0 if accepted else 1) + result_payload = { + **_parse_json(current.get("last_result_json"), {}), + "accepted": accepted, + "review_notes": request.review_notes.strip(), + "summary": request.summary.strip(), + "reviewed_at": timestamp, + "reviewed_by": account["id"], + } + legacy.db.execute( + """ + UPDATE agent_skills + SET status = ?, last_result_json = ?, success_count = ?, failure_count = ?, last_score = ?, last_validated_at = ?, updated_at = ? + WHERE id = ? + """, + ( + next_status, + _dump(result_payload), + next_success, + next_failure, + request.score, + timestamp, + timestamp, + skill_id, + ), + ) + updated = legacy.db.fetch_one("SELECT * FROM agent_skills WHERE id = ?", (skill_id,)) + feedback_summary = (request.summary or request.review_notes or "").strip() + feedback_memory = None + if feedback_summary: + feedback_memory = _remember_platform_observation( + account, + project_id=project["id"], + platform=normalized_platform, + memory_key=f"skill_feedback::{current.get('skill_key')}", + title=f"{current.get('name') or current.get('skill_key') or '技能'}·{'已验证' if accepted else '待优化'}", + summary=feedback_summary[:280], + details={ + "skill_id": skill_id, + "skill_key": current.get("skill_key", ""), + "accepted": accepted, + "score": request.score, + "review_notes": request.review_notes.strip(), + "status": next_status, + }, + confidence=0.9 if accepted else 0.66, + ) + payload = _skill_payload(updated) + if feedback_memory: + payload["feedback_memory"] = feedback_memory + return payload + + async def _execute_oneliner_action( + account: dict[str, Any], + request: OneLinerActionExecuteRequest, + ) -> dict[str, Any]: + project = _resolve_project(account, request.project_id or None) + normalized_platform = normalize_platform_from_text(request.platform) or _safe_platform(request.platform or "", fallback="") + action_key = (request.action_key or "").strip() + if not action_key: + raise HTTPException(status_code=400, detail="Action key is required") + + async def _run_platform_self_check() -> dict[str, Any]: + if not normalized_platform: + raise HTTPException(status_code=400, detail="Platform is required for self-check") + payload = _platform_self_check( + account, + platform=normalized_platform, + project_id=project["id"], + sample_limit=int((request.payload or {}).get("sample_limit") or 3), + remember_summary=True, + ) + return { + "title": f"{payload['platform_label']} Agent 自检", + "summary": f"平台自检得分 {payload['score']}，当前状态：{payload['readiness_label']}。", + "payload": payload, + } + + async def _run_storage_status() -> dict[str, Any]: + payload = legacy.storage_status(project_id=project["id"], account=account) + tenant_usage = payload.get("tenant_usage", {}) + return { + "title": "当前存储状态", + "summary": ( + f"项目 jobs 占用 {tenant_usage.get('project_jobs', {}).get('human_size', '0B')}，" + f"downloads 占用 {tenant_usage.get('project_downloads', {}).get('human_size', '0B')}。" + ), + "payload": payload, + } + + async def _run_live_recorder_status() -> dict[str, Any]: + payload = legacy.live_recorder_status(project_id=project["id"], account=account) + return { + "title": "直播录制状态", + "summary": f"当前共 {len(payload.get('items', []))} 条录制源，最近文件 {len(payload.get('files', []))} 个。", + "payload": payload, + } + + async def _run_ops_scan() -> dict[str, Any]: + admin = legacy.require_super_admin(account) + payload = _scan_admin_incidents(admin) + return { + "title": "运维 Agent 故障扫描", + "summary": f"本轮共归集 {payload.get('count', 0)} 条事件。", + "payload": payload, + } + + executors = { + "platform-self-check": _run_platform_self_check, + "storage-status": _run_storage_status, + "live-recorder-status": _run_live_recorder_status, + "scan-admin-ops": _run_ops_scan, + } + executor = executors.get(action_key) + if not executor: + raise HTTPException(status_code=400, detail=f"Unsupported OneLiner action: {action_key}") + result = await executor() + if request.session_id: + session = _load_owned_session(request.session_id, account) + _insert_message( + session["id"], + account["id"], + "assistant", + result["summary"], + { + "intent_key": "custom", + "delivery_mode": "oneliner", + "platform": normalized_platform, + "suggested_actions": [], + }, + { + "summary_text": result["summary"], + "execution_result": result, + }, + ) + return { + "action_key": action_key, + "project_id": project["id"], + "platform": normalized_platform, + "executed_at": now(), + **result, + } + @app.get("/v2/oneliner/profile") def get_oneliner_profile( project_id: str | None = Query(default=None), @@ -1265,6 +1811,13 @@ def register_oneliner_routes(app: Any, legacy: Any) -> None: "result": result, } + @app.post("/v2/oneliner/actions/execute") + async def execute_oneliner_action( + request: OneLinerActionExecuteRequest, + account: dict[str, Any] = Depends(legacy.require_approved), + ) -> dict[str, Any]: + return await _execute_oneliner_action(account, request) + @app.get("/v2/platform-agents") def list_platform_agents( project_id: str | None = Query(default=None), @@ -1349,30 +1902,34 @@ def register_oneliner_routes(app: Any, legacy: Any) -> None: normalized_platform = _safe_platform(platform) return _upsert_skill(account, agent_scope="platform", platform=normalized_platform, request=request, skill_id=skill_id) + @app.post("/v2/platform-agents/{platform}/self-check") + def run_platform_agent_self_check( + platform: str, + request: PlatformAgentSelfCheckRequest, + account: dict[str, Any] = Depends(legacy.require_approved), + ) -> dict[str, Any]: + normalized_platform = _safe_platform(platform) + return _platform_self_check( + account, + platform=normalized_platform, + project_id=request.project_id, + sample_limit=request.sample_limit, + remember_summary=request.remember_summary, + ) + + @app.post("/v2/platform-agents/{platform}/skills/{skill_id}/review") + def review_platform_skill( + platform: str, + skill_id: str, + request: PlatformSkillReviewRequest, + account: dict[str, Any] = Depends(legacy.require_approved), + ) -> dict[str, Any]: + normalized_platform = _safe_platform(platform) + return _review_platform_skill(account, platform=normalized_platform, skill_id=skill_id, request=request) + @app.get("/v2/admin/ops/overview") def admin_ops_overview(admin: dict[str, Any] = Depends(legacy.require_super_admin)) -> dict[str, Any]: - incidents = [ - _incident_payload(row) - for row in legacy.db.fetch_all( - "SELECT * FROM admin_ops_incidents ORDER BY updated_at DESC LIMIT 50" - ) - ] - failed_jobs = [ - legacy.job_payload(row) - for row in legacy.db.fetch_all( - "SELECT * FROM jobs WHERE status = 'failed' ORDER BY updated_at DESC LIMIT 12" - ) - ] - pending_accounts = [legacy.normalize_account(row) for row in legacy.db.fetch_all("SELECT * FROM accounts WHERE approval_status = 'pending' ORDER BY created_at ASC LIMIT 20")] - return { - "incidents": incidents, - "incident_count": len(incidents), - "failed_jobs": failed_jobs, - "failed_job_count": len(failed_jobs), - "pending_accounts": pending_accounts, - "pending_account_count": len(pending_accounts), - "integration_health": legacy.integrations_health(admin), - } + return _admin_ops_overview_payload(admin) @app.post("/v2/admin/ops/incidents/scan") def admin_ops_scan(admin: dict[str, Any] = Depends(legacy.require_super_admin)) -> dict[str, Any]: diff --git a/web/storyforge-web-v4/assets/app.js b/web/storyforge-web-v4/assets/app.js index 9807335..d1caf7d 100644 --- a/web/storyforge-web-v4/assets/app.js +++ b/web/storyforge-web-v4/assets/app.js @@ -716,7 +716,9 @@ function renderOneLinerMessagesHtml() { const roleClass = message.role === "assistant" ? "assistant" : "user"; const result = message.result || {}; const plan = message.plan || {}; + const executionCard = result.execution_card || {}; const actions = safeArray(plan.suggested_actions); + const secondaryActions = safeArray(executionCard.secondary_actions); return `
@@ -734,6 +736,47 @@ function renderOneLinerMessagesHtml() { ${actions.map((item) => `${escapeHtml(item.label)}`).join("")}
` : ""} + ${message.role === "assistant" && (executionCard.intent_label || executionCard.platform_label || executionCard.primary_action?.label || safeArray(executionCard.evidence).length) ? ` +
+

${escapeHtml(executionCard.intent_label || "本轮执行建议")}

+

${escapeHtml(executionCard.blocked_reason || `${executionCard.platform_label || "待判断平台"} · ${executionCard.delivery_mode === "ui" ? "优先走前端固定动作" : "优先由 OneLiner 对话承接"}`)}

+
+ ${executionCard.platform_label ? `${escapeHtml(executionCard.platform_label)}` : ""} + ${executionCard.platform_agent_name ? `${escapeHtml(executionCard.platform_agent_name)}` : ""} + ${executionCard.assistant_name ? `${escapeHtml(executionCard.assistant_name)}` : ""} + ${executionCard.readiness_label ? `= 50 ? "blue" : "orange"}">${escapeHtml(executionCard.readiness_label)} ${escapeHtml(formatNumber(executionCard.readiness_score || 0))}` : ""} + ${executionCard.primary_action?.key ? `${escapeHtml(executionCard.primary_action.label || "执行下一步")}` : ""} +
+ ${safeArray(executionCard.evidence).length ? ` +
+ ${safeArray(executionCard.evidence).slice(0, 2).map((item) => ` +
+

${escapeHtml(item.kind === "skill" ? "技能证据" : "记忆证据")} · ${escapeHtml(item.title || "未命名")}

+

${escapeHtml(item.summary || "暂无摘要")}

+
+ `).join("")} +
+ ` : ""} + ${safeArray(executionCard.next_steps).length ? ` +
+ ${safeArray(executionCard.next_steps).slice(0, 3).map((item) => `${escapeHtml(item)}`).join("")} +
+ ` : ""} + ${secondaryActions.length ? ` +
+ ${secondaryActions.map((item) => actionTag( + item.label || item.key || "执行", + item.key || "", + [ + item.executor_key ? `data-executor-key="${escapeHtml(item.executor_key)}"` : "", + item.platform ? `data-platform="${escapeHtml(item.platform)}"` : "", + message.session_id ? `data-session-id="${escapeHtml(message.session_id)}"` : "" + ].filter(Boolean).join(" ") + )).join("")} +
+ ` : ""} +
+ ` : ""}
`; @@ -1073,6 +1116,108 @@ async function submitOneLinerMessage(content) { return payload; } +function renderOneLinerExecutionPayloadHtml(payload) { + if (!payload || typeof payload !== "object") { + return `

没有返回执行结果

当前执行器没有附带额外数据。

`; + } + if (payload.route_checks) { + return ` +
+
平台${escapeHtml(payload.platform_label || payload.platform || "-")}
+
得分${escapeHtml(formatNumber(payload.score || 0))}
+
状态${escapeHtml(payload.readiness_label || payload.verdict || "-")}
+
账号源${escapeHtml(formatNumber(payload.source_count || 0))}
+
+
+
+
路由检查
+
+ ${safeArray(payload.route_checks).map((item) => ` +
+

${escapeHtml(item.key || item.path || "route")}

+

${escapeHtml(item.path || "")}

+
${escapeHtml(item.ok ? "可用" : "缺失")}
+
+ `).join("")} +
+
+
+
建议动作
+
+ ${(safeArray(payload.suggestions).length ? safeArray(payload.suggestions) : ["当前已经达到可运行状态。"]).map((item) => ` +
+

下一步

+

${escapeHtml(item)}

+
+ `).join("")} +
+
+
+ `; + } + if (payload.strategy && payload.tenant_usage) { + return ` +
+
jobs${escapeHtml(payload.tenant_usage?.project_jobs?.human_size || "0B")}
+
downloads${escapeHtml(payload.tenant_usage?.project_downloads?.human_size || "0B")}
+
模型目录${escapeHtml(payload.strategy?.models?.mode || "-")}
+
录像${escapeHtml(payload.strategy?.live_recorder?.mode || "-")}
+
+ `; + } + if (payload.items || payload.files) { + return ` +
+
录制源${escapeHtml(formatNumber(safeArray(payload.items).length))}
+
最近文件${escapeHtml(formatNumber(safeArray(payload.files).length))}
+
+ `; + } + return ` +
+

原始结果

+

${escapeHtml(brief(JSON.stringify(payload, null, 2), 1200))}

+
+ `; +} + +async function executeOneLinerAction(executorKey, options = {}) { + if (!backendSupports("/v2/oneliner/actions/execute")) { + throw new Error("当前后端还没有接入 OneLiner 动作执行器。"); + } + const projectId = getOneLinerProjectId(); + const session = getCurrentOneLinerSession() || await ensureOneLinerSession(); + const payload = await storyforgeFetch("/v2/oneliner/actions/execute", { + method: "POST", + body: { + action_key: executorKey, + project_id: projectId, + platform: options.platform || getPreferredPlatform(), + session_id: session?.id || "", + payload: options.payload || {} + } + }); + await loadAgentControlSurfaces(projectId); + if (appState.selectedOnelinerSessionId) { + await loadOneLinerMessages(appState.selectedOnelinerSessionId); + } + openActionModal({ + title: payload.title || "OneLiner 执行结果", + description: payload.summary || "已完成一次对话内执行。", + hideSubmit: true, + fields: [ + { + type: "html", + label: "执行结果", + html: `
${renderOneLinerExecutionPayloadHtml(payload.payload || {})}
` + } + ] + }); + rememberAction("OneLiner 已执行", payload.summary || "当前动作已在对话内执行。", "green", payload); + renderAll(); + return payload; +} + async function loadPlatformAccount(platform, accountId) { if (!accountId) return; const normalizedPlatform = normalizePlatformValue(platform, getPreferredPlatform()); @@ -1928,11 +2073,33 @@ function renderPlatformAgentPanel() {
${escapeHtml(item.mission || item.notes || "先绑定执行 Agent，再补任务目标和方法论。")}
${escapeHtml(item.status || "draft")} + ${item.readiness_label ? `= 50 ? "blue" : "orange"}">${escapeHtml(item.readiness_label)} ${escapeHtml(formatNumber(item.readiness_score || 0))}` : ""} 记忆 ${escapeHtml(formatNumber(item.memory_count))} 技能 ${escapeHtml(formatNumber(item.skill_count))} ${escapeHtml(item.assistant?.name || "未绑 Agent")}
+ ${item.recent_memory || item.recent_skill ? ` +
+ ${item.recent_memory ? ` +
+

最近记忆 · ${escapeHtml(item.recent_memory.title || item.recent_memory.memory_key || "未命名")}

+

${escapeHtml(brief(item.recent_memory.summary || "暂无摘要", 68))}

+
+ ` : ""} + ${item.recent_skill ? ` +
+

最近技能 · ${escapeHtml(item.recent_skill.name || item.recent_skill.skill_key || "未命名")}

+

${escapeHtml(brief(item.recent_skill.test_spec?.summary || item.recent_skill.method?.summary || "暂无方法摘要", 68))}

+
+ ${escapeHtml(item.recent_skill.status || "draft")} + 得分 ${escapeHtml(formatNumber(item.recent_skill.last_score || 0))} +
+
+ ` : ""} +
+ ` : ""}
+ 查看详情 配置 补记忆 补技能 @@ -1965,6 +2132,8 @@ function renderAdminOpsPanel() {
${escapeHtml(formatNumber(overview.incident_count))} 条事件 + 待处理 ${escapeHtml(formatNumber(overview.open_incident_count || 0))} + 错误 ${escapeHtml(formatNumber(overview.severity_counts?.error || 0))} ${escapeHtml(formatNumber(overview.failed_job_count))} 个失败任务 重新扫描
@@ -1977,7 +2146,11 @@ function renderAdminOpsPanel() {
${escapeHtml(item.severity || "warn")} ${escapeHtml(item.status || "open")} + ${item.source_type ? `${escapeHtml(item.source_type)}` : ""} ${item.tenant_user_id ? `租户 ${escapeHtml(brief(item.tenant_user_id, 12))}` : ""} + ${item.source_type === "job" ? actionTag("看任务详情", "open-job-detail", `data-job-id="${escapeHtml(item.source_id || "")}"`) : ""} + ${item.source_type === "integration" ? actionTag("去自动流程", "goto-automation") : ""} + ${item.tenant_project_id ? actionTag("去生产中心", "goto-production") : ""} 审计处理
@@ -3770,6 +3943,129 @@ function openPlatformAgentSkillAction(platform) { }); } +async function openPlatformAgentDetailAction(platform) { + const project = requireSelectedProject(); + const normalizedPlatform = normalizePlatformValue(platform, getPreferredPlatform()); + const profile = safeArray(appState.platformAgents).find((item) => item.platform === normalizedPlatform) || null; + if (!profile) { + alert("没有找到这个平台 Agent。"); + return; + } + const [memoriesPayload, skillsPayload] = await Promise.all([ + storyforgeFetch(`/v2/platform-agents/${encodeURIComponent(normalizedPlatform)}/memories?project_id=${encodeURIComponent(project.id)}`).catch(() => ({ items: [] })), + storyforgeFetch(`/v2/platform-agents/${encodeURIComponent(normalizedPlatform)}/skills?project_id=${encodeURIComponent(project.id)}`).catch(() => ({ items: [] })) + ]); + const memories = safeArray(memoriesPayload?.items || memoriesPayload).slice(0, 6); + const skills = safeArray(skillsPayload?.items || skillsPayload).slice(0, 6); + openActionModal({ + title: `${platformLabel(normalizedPlatform)} Agent 详情`, + description: "查看当前平台 Agent 最近沉淀的记忆、技能和就绪度。", + hideSubmit: true, + fields: [ + { + type: "html", + label: "详情", + html: ` +
+
+

${escapeHtml(profile.name || `${platformLabel(normalizedPlatform)} Agent`)}

+

${escapeHtml(profile.mission || profile.notes || "暂无任务目标说明")}

+
+ ${escapeHtml(profile.status || "draft")} + ${profile.readiness_label ? `= 50 ? "blue" : "orange"}">${escapeHtml(profile.readiness_label)} ${escapeHtml(formatNumber(profile.readiness_score || 0))}` : ""} + ${escapeHtml(profile.assistant?.name || "未绑执行 Agent")} +
+
+
+
+
最近记忆
+
+ ${memories.map((item) => ` +
+

${escapeHtml(item.title || item.memory_key || "未命名")}

+

${escapeHtml(item.summary || "暂无摘要")}

+
${escapeHtml(item.memory_key || "memory")}${escapeHtml(formatNumber(item.confidence || 0))}
+
+ `).join("") || `

还没有平台记忆

先把这段时间验证有效的方法沉淀进来。

`} +
+
+
+
最近技能
+
+ ${skills.map((item) => ` +
+

${escapeHtml(item.name || item.skill_key || "未命名")}

+

${escapeHtml(item.test_spec?.summary || item.method?.summary || "暂无方法摘要")}

+
+ ${escapeHtml(item.status || "draft")} + 得分 ${escapeHtml(formatNumber(item.last_score || 0))} + 验收通过 + 标记待优化 +
+
+ `).join("") || `

还没有平台技能

等子 Agent 跑出稳定结果后，把方法固化成技能。

`} +
+
+
+
+ 运行平台自检 + 编辑配置 + 继续补记忆 + 继续补技能 + 让 OneLiner 调度 +
+
+ ` + } + ] + }); +} + +function openPlatformSkillReviewAction(platform, skillId, accepted) { + const project = requireSelectedProject(); + const normalizedPlatform = normalizePlatformValue(platform, getPreferredPlatform()); + const profile = safeArray(appState.platformAgents).find((item) => item.platform === normalizedPlatform) || null; + const skill = safeArray(profile?.recent_skill ? [profile.recent_skill] : []) + .concat([]) + .find((item) => item.id === skillId) + || null; + openActionModal({ + title: accepted ? "验收平台技能" : "标记技能待优化", + description: accepted + ? `把这条 ${platformLabel(normalizedPlatform)} 技能标记为当前可复用的方法。` + : `这条 ${platformLabel(normalizedPlatform)} 技能暂时不通过，要求继续优化。`, + submitLabel: accepted ? "确认通过" : "确认待优化", + fields: [ + { name: "summary", label: "结论摘要", placeholder: accepted ? "例如：当前抓取结果和验收数据一致，可固化成技能" : "例如：账号匹配不稳定，需要继续优化抓取方式" }, + { name: "reviewNotes", label: "审计备注", type: "textarea", rows: 4, value: skill?.last_result?.review_notes || "", placeholder: "写清楚为什么通过或退回" }, + { name: "score", label: "得分", type: "number", value: accepted ? 0.9 : 0.45, min: 0, max: 1, step: 0.05 } + ], + onSubmit: async (values) => { + if (!backendSupports("/v2/platform-agents/{platform}/skills/{skill_id}/review")) { + throw new Error("当前后端还没有接入平台技能验收接口。"); + } + const saved = await storyforgeFetch(`/v2/platform-agents/${encodeURIComponent(normalizedPlatform)}/skills/${encodeURIComponent(skillId)}/review`, { + method: "POST", + body: { + project_id: project.id, + accepted, + score: Number(values.score || (accepted ? 0.9 : 0.45)), + summary: values.summary || "", + review_notes: values.reviewNotes || "" + } + }); + rememberAction( + accepted ? "平台技能已通过" : "平台技能待优化", + `技能「${saved.name || saved.skill_key || skillId}」已更新为 ${saved.status || (accepted ? "validated" : "needs_revision")}。`, + accepted ? "green" : "orange", + saved + ); + await loadAgentControlSurfaces(project.id); + renderAll(); + } + }); +} + function openCreateAssistantAction() { const project = requireSelectedProject(); const kbOptions = getKnowledgeBaseOptions(project.id); @@ -4051,7 +4347,31 @@ function openAdminIncidentReviewAction(incidentId) { description: "这里代表管理员侧审计 Agent 的放行/退回动作。", submitLabel: "保存审计结果", fields: [ - { name: "summary", label: "事件摘要", type: "html", html: `
${escapeHtml(incident.title)}

${escapeHtml(incident.summary || "暂无摘要")}

` }, + { + name: "summary", + label: "事件摘要", + type: "html", + html: ` +
+
+

${escapeHtml(incident.title)}

+

${escapeHtml(incident.summary || "暂无摘要")}

+
+ ${escapeHtml(incident.severity || "warn")} + ${escapeHtml(incident.status || "open")} + ${incident.source_type ? `${escapeHtml(incident.source_type)}` : ""} + ${incident.tenant_user_id ? `租户 ${escapeHtml(brief(incident.tenant_user_id, 12))}` : ""} +
+
+ ${incident.source_type === "job" ? actionTag("看任务详情", "open-job-detail", `data-job-id="${escapeHtml(incident.source_id || "")}"`) : ""} + ${incident.source_type === "integration" ? actionTag("去自动流程", "goto-automation") : ""} + ${incident.tenant_project_id ? actionTag("去生产中心", "goto-production") : ""} + 重新扫描 +
+
+
+ ` + }, { name: "status", label: "处理状态", type: "select", value: incident.status || "reviewed", options: [{ value: "reviewed", label: "已审阅" }, { value: "watching", label: "继续观察" }, { value: "resolved", label: "已解决" }, { value: "rejected", label: "驳回修复方案" }] }, { name: "reviewNotes", label: "审计备注", type: "textarea", rows: 5, value: incident.review_notes || "", placeholder: "写清楚为什么放行、退回或继续观察" } ], @@ -4614,6 +4934,24 @@ document.addEventListener("click", async (event) => { openPlatformAgentProfileAction(action.dataset.platform || ""); return; } + if (name === "open-platform-agent-detail") { + await openPlatformAgentDetailAction(action.dataset.platform || ""); + return; + } + if (name === "run-oneliner-action") { + setBusy(true, "OneLiner 正在执行动作..."); + try { + await executeOneLinerAction(action.dataset.executorKey || "", { + platform: action.dataset.platform || "", + payload: {} + }); + } catch (error) { + alert("执行 OneLiner 动作失败: " + error.message); + } finally { + setBusy(false, ""); + } + return; + } if (name === "open-platform-agent-memory") { openPlatformAgentMemoryAction(action.dataset.platform || ""); return; @@ -4622,6 +4960,10 @@ document.addEventListener("click", async (event) => { openPlatformAgentSkillAction(action.dataset.platform || ""); return; } + if (name === "review-platform-skill") { + openPlatformSkillReviewAction(action.dataset.platform || "", action.dataset.skillId || "", action.dataset.accepted !== "false"); + return; + } if (name === "analyze-selected-account") { openAnalyzeSelectedAccountAction(); return; @@ -4762,10 +5104,16 @@ document.addEventListener("click", async (event) => { } return; } + if (name === "submit-oneliner") { + return; + } if (name === "scroll-selected") { document.getElementById("selected-account-anchor")?.scrollIntoView({ behavior: "smooth", block: "start" }); return; } + rememberAction("动作待接入", `前端还没有处理动作「${name}」，当前仍可继续通过 OneLiner 对话承接。`, "orange"); + renderAll(); + return; } });