281 lines
10 KiB
Python
281 lines
10 KiB
Python
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#!/usr/bin/env python3
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"""
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从「知你客服12号」复制为「知你客服13号」：
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- **画布**：去除自环边、合并重复的 source→target 边；统一锚点 sourceHandle=right、targetHandle=left；
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按从「开始」出发的分层布局重排节点坐标，减少交叉与「绕圈」观感（不改变节点 id/业务配置）。
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- **提示词**：在 12 号能力（http_request、file_read、file_write、system_info）基础上，增加工具调用纪律
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（避免同轮重复 file_write、勿刷屏 DSML）。
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若已存在同名 Agent「知你客服13号」，则仅更新其 workflow + 描述（不新建）。
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用法:
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cd backend && .\\venv\\Scripts\\python.exe scripts/create_zhini_kefu_13.py
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环境变量: PLATFORM_BASE_URL, PLATFORM_USERNAME, PLATFORM_PASSWORD,
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SOURCE_AGENT_NAME（默认 知你客服12号）, TARGET_NAME（默认 知你客服13号）
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"""
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from __future__ import annotations
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import copy
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import json
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import os
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import sys
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from collections import defaultdict
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from typing import Any, Dict, List, Optional, Tuple
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import requests
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BASE = os.getenv("PLATFORM_BASE_URL", "http://127.0.0.1:8037").rstrip("/")
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USER = os.getenv("PLATFORM_USERNAME", "admin")
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PWD = os.getenv("PLATFORM_PASSWORD", "123456")
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SOURCE_NAME = os.getenv("SOURCE_AGENT_NAME", "知你客服12号")
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TARGET_NAME = os.getenv("TARGET_NAME", "知你客服13号")
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TOOLS_V13 = ["http_request", "file_read", "file_write", "system_info"]
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# 在 12 号提示词基础上追加（create_zhini_kefu_12 正文过长时由脚本从源 Agent 读取再拼接）
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PROMPT_V13_EXTRA = """
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【画布/执行说明（13 号）】
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- 工作流连线已整理为从左到右主线，减少自环与重复边带来的误解；逻辑仍以引擎与节点配置为准。
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【工具调用纪律（13 号）】
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- 同一轮用户请求中，对 **file_write** 无特殊说明时不要重复调用多次；每个明确文件需求通常 **一次写入** 即可。
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- 不要在回复正文中 **重复刷屏** DSML、`<｜DSML｜`、`invoke name=` 等标签行；工具返回后应用自然语言说明，并仍以 **单行 JSON** 收尾。
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- 若上一轮已写入成功，除非用户要求修改或另存，不要再次写入相同路径。
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【单行 JSON 与用户画像（与 12 号一致，勿留空）】
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- 最后一行 JSON 的 user_profile 须与事实一致：用户已告知昵称时须包含 "name"（如「小七」）；**禁止**用空的 user_profile 覆盖会话记忆。
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- 仅靠 file_write 写入本地文件**不能**替代上述 JSON 中的 user_profile；多轮称呼以 JSON + 会话记忆为准。
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"""
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def _sanitize_edges(edges: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
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"""去掉自环、按 (source,target) 去重，统一左右锚点。"""
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seen: set = set()
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out: List[Dict[str, Any]] = []
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for e in edges or []:
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s, t = e.get("source"), e.get("target")
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if not s or not t:
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continue
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if s == t:
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continue
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key = (s, t)
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if key in seen:
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continue
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seen.add(key)
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ne = dict(e)
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ne["sourceHandle"] = "right"
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ne["targetHandle"] = "left"
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if not ne.get("id"):
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ne["id"] = f"edge_{s}_{t}"
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out.append(ne)
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return out
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def _find_start_node_ids(nodes: List[Dict[str, Any]]) -> List[str]:
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ids: List[str] = []
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for n in nodes or []:
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nid = n.get("id") or ""
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nt = (n.get("type") or (n.get("data") or {}).get("type") or "").lower()
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if nt == "start" or nid in ("start", "start-1") or str(nid).startswith("start-"):
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ids.append(nid)
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return ids
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def _compute_ranks(
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nodes: List[Dict[str, Any]], edges: List[Dict[str, Any]]
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) -> Dict[str, int]:
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node_ids = [n["id"] for n in nodes if n.get("id")]
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start_ids = _find_start_node_ids(nodes)
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incoming: Dict[str, int] = {nid: 0 for nid in node_ids}
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for e in edges:
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s, t = e.get("source"), e.get("target")
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if not s or not t or s == t:
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continue
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if t in incoming:
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incoming[t] += 1
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if not start_ids:
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start_ids = [nid for nid in node_ids if incoming.get(nid, 0) == 0] or ([node_ids[0]] if node_ids else [])
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rank: Dict[str, int] = {s: 0 for s in start_ids}
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nmax = max(len(nodes), 8)
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for _ in range(nmax + 5):
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updated = False
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for e in edges:
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s, t = e.get("source"), e.get("target")
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if not s or not t or s == t:
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continue
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if s not in rank:
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continue
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nv = rank[s] + 1
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if t not in rank or rank[t] < nv:
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rank[t] = nv
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updated = True
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if not updated:
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break
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max_r = max(rank.values(), default=0)
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for nid in node_ids:
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if nid not in rank:
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rank[nid] = max_r + 1
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max_r += 1
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return rank
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def _apply_layered_positions(nodes: List[Dict[str, Any]], ranks: Dict[str, int]) -> None:
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layers: Dict[int, List[str]] = defaultdict(list)
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for nid, r in ranks.items():
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layers[r].append(nid)
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for r in layers:
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layers[r].sort()
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x0, y0 = 80.0, 140.0
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x_step = 300.0
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y_step = 110.0
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for r in sorted(layers.keys()):
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ids = layers[r]
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nlen = len(ids)
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y_base = y0 - (nlen - 1) * y_step / 2.0
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for j, nid in enumerate(ids):
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for node in nodes:
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if node.get("id") != nid:
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continue
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pos = node.setdefault("position", {})
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pos["x"] = x0 + r * x_step
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pos["y"] = y_base + j * y_step
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break
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def improve_workflow_layout_and_edges(wf: Dict[str, Any]) -> Tuple[int, int]:
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"""
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返回 (去掉的自环条数, 去掉的重复边条数)。
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"""
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nodes = wf.get("nodes") or []
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raw_edges = wf.get("edges") or []
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loops = sum(
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1
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for e in raw_edges
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if e.get("source") and e.get("target") and e.get("source") == e.get("target")
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)
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clean = _sanitize_edges(raw_edges)
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removed_dup = len(raw_edges) - len(clean) - loops
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wf["edges"] = clean
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ranks = _compute_ranks(nodes, clean)
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_apply_layered_positions(nodes, ranks)
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return loops, max(0, removed_dup)
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def _patch_llm_unified(wf: dict, base_prompt: Optional[str] = None) -> None:
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for n in wf.get("nodes") or []:
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if n.get("id") != "llm-unified":
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continue
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d = n.setdefault("data", {})
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prompt = base_prompt if base_prompt else d.get("prompt") or ""
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if PROMPT_V13_EXTRA.strip() not in prompt:
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prompt = (prompt.rstrip() + "\n" + PROMPT_V13_EXTRA).strip()
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d["prompt"] = prompt
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d["enable_tools"] = True
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d["tools"] = list(TOOLS_V13)
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d["selected_tools"] = list(TOOLS_V13)
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return
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print("警告: 未找到节点 llm-unified", file=sys.stderr)
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def _find_agent_id_by_name(h: Dict[str, str], name: str) -> Optional[str]:
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r = requests.get(f"{BASE}/api/v1/agents", params={"search": name, "limit": 50}, headers=h, timeout=30)
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if r.status_code != 200:
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return None
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for a in r.json() or []:
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if a.get("name") == name:
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return a.get("id")
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return None
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def main() -> int:
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r = requests.post(
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f"{BASE}/api/v1/auth/login",
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data={"username": USER, "password": PWD},
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headers={"Content-Type": "application/x-www-form-urlencoded"},
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timeout=15,
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)
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if r.status_code != 200:
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print("登录失败:", r.status_code, r.text[:500], file=sys.stderr)
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return 1
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token = r.json().get("access_token")
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if not token:
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print("无 access_token", file=sys.stderr)
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return 1
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h = {"Authorization": f"Bearer {token}", "Content-Type": "application/json"}
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src_id = _find_agent_id_by_name(h, SOURCE_NAME)
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if not src_id:
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print(f"未找到源 Agent: {SOURCE_NAME}", file=sys.stderr)
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return 1
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existing_13 = _find_agent_id_by_name(h, TARGET_NAME)
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if existing_13:
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print("已存在", TARGET_NAME, "-> 仅更新工作流", existing_13)
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new_id = existing_13
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g = requests.get(f"{BASE}/api/v1/agents/{new_id}", headers=h, timeout=30)
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if g.status_code != 200:
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print("读取失败:", g.text, file=sys.stderr)
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return 1
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agent = g.json()
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else:
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dup = requests.post(
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f"{BASE}/api/v1/agents/{src_id}/duplicate",
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headers=h,
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json={"name": TARGET_NAME},
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timeout=60,
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)
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if dup.status_code != 201:
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print("复制失败:", dup.status_code, dup.text[:800], file=sys.stderr)
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return 1
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new_id = dup.json()["id"]
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agent = dup.json()
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print("已创建副本:", new_id, TARGET_NAME)
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wf = copy.deepcopy(agent["workflow_config"])
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loops, dup_edges = improve_workflow_layout_and_edges(wf)
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print(f"连线整理: 去掉自环 {loops} 条, 合并重复边 {dup_edges} 条")
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g2 = requests.get(f"{BASE}/api/v1/agents/{src_id}", headers=h, timeout=30)
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base_prompt = None
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if g2.status_code == 200:
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try:
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for n in g2.json().get("workflow_config", {}).get("nodes") or []:
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if n.get("id") == "llm-unified":
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base_prompt = (n.get("data") or {}).get("prompt")
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break
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except Exception:
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pass
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_patch_llm_unified(wf, base_prompt=base_prompt)
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desc = (
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"在知你客服12号基础上：整理工作流连线（去自环/重复边、分层布局、统一左右锚点），"
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"并强化工具调用纪律（避免同轮重复 file_write、勿刷屏 DSML）；"
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"工具仍为 http_request、file_read、file_write、system_info；输出单行 JSON。"
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)
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up = requests.put(
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f"{BASE}/api/v1/agents/{new_id}",
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headers=h,
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json={"description": desc, "workflow_config": wf},
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timeout=120,
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)
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if up.status_code != 200:
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print("更新失败:", up.status_code, up.text[:1200], file=sys.stderr)
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return 1
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print("已写入工具:", ", ".join(TOOLS_V13))
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print("Agent ID:", new_id)
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print(json.dumps({"id": new_id, "name": TARGET_NAME}, ensure_ascii=False))
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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