feat(server): add workbench API, DSH planner worker and RAG pipeline

server/app/agents/supervisor.py

@@ -0,0 +1,104 @@
+"""全局总监 Agent（画布级）：每段生成后判断是否跑偏，跑偏则带指导重做。
+
+- always：每段生成完必审
+- on_drift：QC 有问题/质检反复（round>1）时才审（默认，省点数）
+- off：不启用
+
+总监不写内容，只输出 JSON：{"on_track": true} 或
+{"on_track": false, "reason": "为什么偏了", "guidance": "怎么拉回来"}。
+guidance 会注入该段下一轮生成提示，最多重做 1 次，防止无限循环烧点数。
+"""
+from __future__ import annotations
+
+import json
+
+from sqlmodel import Session
+
+from ..models import Agent, Campaign, Canvas, Segment
+
+SUPERVISOR_INSTRUCTIONS = (
+    "你是内容生产线的全局总监，负责保证每一段内容不跑偏。"
+    "给你任务目标、验收标准、本段应讲的主题和已生成的正文。"
+    "只判断：1) 正文是否围绕本段主题 2) 是否符合任务目标和验收标准 3) 是否夹带无关内容。"
+    "只输出 JSON：{\"on_track\": true} 或 {\"on_track\": false, \"reason\": \"跑偏原因（一句话）\", "
+    "\"guidance\": \"给写手的具体拉回指导（一两句话，怎么改）\"}"
+)
+
+
+def _canvas_for(campaign: Campaign, session: Session) -> Canvas | None:
+    """任务运行时以画布快照为准；快照存了 supervisor 配置才能启用。"""
+    snap = campaign.canvas_snapshot or {}
+    if not isinstance(snap, dict):
+        return None
+    supervisor_id = snap.get("supervisor_agent_id")
+    mode = str(snap.get("supervisor_mode") or "on_drift")
+    if not supervisor_id or mode == "off":
+        return None
+    # 快照配置即可驱动审核；Canvas 实例仅用于传参，不落库
+    return Canvas(id=0, name="runtime", nodes=[], edges=[],
+                  supervisor_agent_id=int(supervisor_id), supervisor_mode=mode,
+                  organization_id=int(campaign.organization_id or 1))
+
+
+def _segment_text(seg: Segment) -> str:
+    """读取段落正文：优先产物文件，其次锚点卡标题。"""
+    from pathlib import Path
+    if seg.artifact_path and Path(seg.artifact_path).is_file():
+        try:
+            return Path(seg.artifact_path).read_text(encoding="utf-8")
+        except OSError:
+            pass
+    title = str((seg.anchor_card or {}).get("title") or seg.title or "")
+    return title
+
+
+def supervisor_check(session: Session, seg: Segment, campaign: Campaign) -> dict:
+    """总监审核一个刚生成完的段。返回 {"checked": bool, "on_track": bool, "guidance": str, "reason": str}。"""
+    canvas = _canvas_for(campaign, session)
+    if not canvas:
+        return {"checked": False}
+    supervisor = session.get(Agent, int(canvas.supervisor_agent_id or 0))
+    if not supervisor or supervisor.status != "active":
+        return {"checked": False}
+    mode = canvas.supervisor_mode
+    # on_drift 模式：只审可疑段（质检发现问题或已重做过一轮）
+    if mode == "on_drift" and seg.status == "approved" and int(seg.round or 1) <= 1:
+        return {"checked": False}
+
+    from ..llm import chat_json
+    prompt = (
+        f"任务目标：{campaign.objective}\n"
+        f"验收标准：{campaign.success_criteria}\n"
+        f"本段主题：{seg.title}\n"
+        f"已生成正文：\n{_segment_text(seg)[:4000]}"
+    )
+    try:
+        result = chat_json(
+            session,
+            [{"role": "system", "content": SUPERVISOR_INSTRUCTIONS},
+             {"role": "user", "content": prompt}],
+            provider_id=0, model="",
+            campaign_id=int(campaign.id or 0), segment_id=int(seg.id or 0),
+            agent_id=int(supervisor.id or 0), agent_name=f"{supervisor.name}(总监)",
+            user_id=int(campaign.owner_user_id or 0),
+            organization_id=int(campaign.organization_id or 1),
+            max_retries=1,
+        )
+    except Exception:
+        # 总监审核自身失败不阻断主流程
+        return {"checked": False}
+    if result.get("status") != "ok":
+        return {"checked": False}
+    try:
+        verdict = result.get("data") if isinstance(result.get("data"), dict) else json.loads(result.get("text") or "{}")
+    except (json.JSONDecodeError, TypeError):
+        verdict = {}
+    on_track = bool(verdict.get("on_track", True))
+    if on_track:
+        return {"checked": True, "on_track": True}
+    return {"checked": True, "on_track": False,
+            "reason": str(verdict.get("reason") or "内容偏离本段主题或任务目标")[:200],
+            "guidance": str(verdict.get("guidance") or "回到本段主题，紧扣任务目标与验收标准重写")[:300]}
+
+
+__all__ = ["supervisor_check"]