From 8c13c941c044ef15b1368bebe85d2daabdb7d63e Mon Sep 17 00:00:00 2001 From: OoO Date: Tue, 19 May 2026 21:09:37 +0800 Subject: [PATCH] =?UTF-8?q?=E6=94=B6=E6=96=82=20NemoTron=20=E8=88=8A?= =?UTF-8?q?=E5=9B=9E=E8=A6=86=E8=A1=8C=E5=8B=95?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- config.py | 2 +- docs/AI_INTELLIGENCE_MODULE_SOT.md | 4 +-- services/action_plan_hygiene.py | 51 ++++++++++++++++++++++-------- tests/test_action_plan_hygiene.py | 36 ++++++++++++++++++--- 4 files changed, 73 insertions(+), 20 deletions(-) diff --git a/config.py b/config.py index cef3436..9383960 100644 --- a/config.py +++ b/config.py @@ -320,7 +320,7 @@ YOUTUBE_API_KEY = os.getenv('YOUTUBE_API_KEY', '') # ========================================== # 系統版本與路徑 # ========================================== -SYSTEM_VERSION = "V10.269" +SYSTEM_VERSION = "V10.270" LOG_FILE_PATH = os.path.join(BASE_DIR, 'logs/system.log') public_url = PUBLIC_URL # 用於模板顯示 diff --git a/docs/AI_INTELLIGENCE_MODULE_SOT.md b/docs/AI_INTELLIGENCE_MODULE_SOT.md index 101ddf1..2daca6f 100644 --- a/docs/AI_INTELLIGENCE_MODULE_SOT.md +++ b/docs/AI_INTELLIGENCE_MODULE_SOT.md @@ -2,7 +2,7 @@ > **最後更新**: 2026-05-19 (台北時間) > **狀態**: 🟢 四 AI Agent 自動化閉環已落地；LLM 路由紅線升級為 Ollama-first 三主機級聯，Gemini 僅備援 / 鎖定場景 -> **適用版本**: V10.269 +> **適用版本**: V10.270 --- @@ -107,7 +107,7 @@ SQL漏斗(~300筆) - ElephantAlpha 使用 NVIDIA NIM hosted API；production 預設模型為 `nvidia/llama-3.3-nemotron-super-49b-v1.5`，`ELEPHANT_ALPHA_FALLBACK_MODELS` 需保留至少一個可呼叫備援；403/404、408/409/425/429、5xx、timeout 與 connection error 必須嘗試下一個模型。 - ElephantAlpha L3 HITL 只允許發送有實證、可審核、可行動的升級告警；價格類 trigger 無 Hermes 具體威脅時，只記錄 suppressed escalation telemetry 與 cooldown，不寫 pending `human_review`，不發 Telegram 空告警。 - `resource_optimization` 不再交給 LLM 生成「預期效益 / 已執行」敘事。此 trigger 必須先由程式量測 `action_plans` backlog、P1/P2 數、pending_review、逾時項目與 CPU load；只有 CPU 達門檻、P1/P2 積壓或逾時積壓才發 Telegram「資源壓力告警」。單純 queue 大但 CPU 正常只記錄 telemetry，不派發 Hermes/NemoTron、不宣稱 48 小時效益。 -- `resource_optimization` 會先執行 `ActionPlanHygieneService` 清理過期噪音：只關閉超過 72 小時的 `code_review_fix` / `openclaw_recommendation` 類 advisory action_plans，將狀態改為 `auto_disabled` 或 `rejected` 並寫入 `metadata_json.hygiene_history`；不刪資料、不碰 NemoTron 業務行動。 +- `resource_optimization` 會先執行 `ActionPlanHygieneService` 清理過期噪音：只關閉超過 72 小時的 `code_review_fix` / `openclaw_recommendation` 類 advisory action_plans，以及 NemoTron `direct_response/reply_simple` 舊聊天回覆計畫；將狀態改為 `auto_disabled` 或 `rejected` 並寫入 `metadata_json.hygiene_history`。不刪資料，也不碰 NemoTron human_review / pricing / tool action 類業務行動。 - OpenClaw/Hermes embedding 優先呼叫 Ollama `/api/embed`，只在舊節點不支援時 fallback `/api/embeddings`；timeout 由 `EMBEDDING_TIMEOUT` / `OLLAMA_EMBED_TIMEOUT` 控制。 - PPT 自動產線由 `momo-scheduler` 依節奏執行 `run_ppt_auto_generation_task(schedule_kind)`：每日 20:30 產日報、週一 20:40 產週報/市場情報、每月 1 日 20:50 產月報與管理型簡報、季初 21:00 產季報、半年初 21:10 產半年報、年初 21:20 產年報，再交給 22:00 `ppt_vision_audit` 做視覺審核；每次嘗試會寫入 `ppt_generation_runs`，`/observability/ppt_audit_history` 以精準參數檢查目標版本是否已產生，並可用 `/observability/ppt_audit/generate_missing` 手動補齊缺漏，總開關為 `PPT_AUTO_GENERATION_ENABLED`。PPT vision 需 `PPT_VISION_ENABLED=true` 與容器內 LibreOffice；`/observability/ppt_audit_file/` 會把 PPTX 轉成 PDF 快取供站內線上預覽，原始 PPTX 仍保留下載。 diff --git a/services/action_plan_hygiene.py b/services/action_plan_hygiene.py index 3f09af1..25f6852 100644 --- a/services/action_plan_hygiene.py +++ b/services/action_plan_hygiene.py @@ -24,6 +24,7 @@ CLOSABLE_STATUSES = frozenset({"pending", "auto_pending", "pending_review"}) SOURCE_TARGET_STATUS = { "code_review_fix": "auto_disabled", "code_review_pipeline": "auto_disabled", + "nemotron_direct_response": "auto_disabled", "openclaw_recommendation": "rejected", "openclaw": "rejected", } @@ -51,15 +52,6 @@ def _coerce_datetime(value: Any) -> Optional[datetime]: return None -def _source_for_row(row: Any) -> str: - return str( - _row_get(row, "action_type") - or _row_get(row, "plan_type") - or _row_get(row, "created_by") - or "unknown" - ) - - def _parse_metadata(raw: Any) -> Dict[str, Any]: if isinstance(raw, dict): return dict(raw) @@ -72,6 +64,39 @@ def _parse_metadata(raw: Any) -> Dict[str, Any]: return {"legacy_metadata_raw": str(raw)[:1000]} +def _parse_payload(raw: Any) -> Dict[str, Any]: + if isinstance(raw, dict): + return dict(raw) + if not raw: + return {} + try: + parsed = json.loads(str(raw)) + return parsed if isinstance(parsed, dict) else {} + except Exception: + return {} + + +def _source_for_row(row: Any) -> str: + created_by = str(_row_get(row, "created_by") or "") + if created_by == "nemotron": + payload = _parse_payload(_row_get(row, "payload")) + actions = payload.get("action_plan") if isinstance(payload.get("action_plan"), list) else [] + is_direct_response = payload.get("dispatch_to") == "direct_response" + is_reply_only = bool(actions) and all( + isinstance(action, dict) and action.get("action") == "reply_simple" + for action in actions + ) + if is_direct_response or is_reply_only: + return "nemotron_direct_response" + + return str( + _row_get(row, "action_type") + or _row_get(row, "plan_type") + or created_by + or "unknown" + ) + + def build_action_plan_hygiene_preview( rows: Iterable[Any], *, @@ -140,12 +165,12 @@ class ActionPlanHygieneService: try: rows = session.execute(text(""" SELECT id, status, priority, created_at, action_type, plan_type, - created_by, description, metadata_json + created_by, description, metadata_json, payload FROM action_plans WHERE status IN ('pending', 'auto_pending', 'pending_review') AND ( action_type IN ('code_review_fix', 'openclaw_recommendation') - OR created_by IN ('code_review_pipeline', 'openclaw') + OR created_by IN ('code_review_pipeline', 'openclaw', 'nemotron') ) ORDER BY created_at ASC """)).fetchall() @@ -163,12 +188,12 @@ class ActionPlanHygieneService: try: rows = session.execute(text(""" SELECT id, status, priority, created_at, action_type, plan_type, - created_by, description, metadata_json + created_by, description, metadata_json, payload FROM action_plans WHERE status IN ('pending', 'auto_pending', 'pending_review') AND ( action_type IN ('code_review_fix', 'openclaw_recommendation') - OR created_by IN ('code_review_pipeline', 'openclaw') + OR created_by IN ('code_review_pipeline', 'openclaw', 'nemotron') ) ORDER BY created_at ASC """)).fetchall() diff --git a/tests/test_action_plan_hygiene.py b/tests/test_action_plan_hygiene.py index 59e4330..6abb75d 100644 --- a/tests/test_action_plan_hygiene.py +++ b/tests/test_action_plan_hygiene.py @@ -38,12 +38,40 @@ def test_action_plan_hygiene_preview_closes_only_stale_advisory_sources(): "action_type": "openclaw_recommendation", "description": "fresh advisory", }, + { + "id": 5, + "status": "pending", + "priority": 3, + "created_at": now - timedelta(hours=110), + "created_by": "nemotron", + "payload": { + "dispatch_to": "direct_response", + "action_plan": [{"action": "reply_simple"}], + }, + "description": "old chat response", + }, + { + "id": 6, + "status": "pending", + "priority": 3, + "created_at": now - timedelta(hours=110), + "created_by": "nemotron", + "payload": { + "dispatch_to": "human_review", + "action_plan": [{"action": "flag_for_human_review"}], + }, + "description": "must stay", + }, ] preview = build_action_plan_hygiene_preview(rows, now=now, stale_hours=72) - assert preview["candidate_count"] == 2 - assert preview["by_source"] == {"openclaw_recommendation": 1, "code_review_fix": 1} - assert {item["id"] for item in preview["candidates"]} == {1, 2} + assert preview["candidate_count"] == 3 + assert preview["by_source"] == { + "openclaw_recommendation": 1, + "code_review_fix": 1, + "nemotron_direct_response": 1, + } + assert {item["id"] for item in preview["candidates"]} == {1, 2, 5} target_by_id = {item["id"]: item["to_status"] for item in preview["candidates"]} - assert target_by_id == {1: "rejected", 2: "auto_disabled"} + assert target_by_id == {1: "rejected", 2: "auto_disabled", 5: "auto_disabled"}