553 lines
18 KiB
Python
553 lines
18 KiB
Python
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#!/usr/bin/env python3
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"""
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从「知你客服15号」复制为「知你客服16号」—— **B 能力**：画布 **Loop + 循环体内 LLM**。
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- **主线**：Cache 等上游 → `code-build` 注入 `loop_rounds` 数组 → `loop` →（体内）`llm-subtask` → `loop_end`；
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循环结束后 → `code-merge` 将各段 LLM 输出折叠为 `right`/`reply`（并合并 `user_profile`）→ 原 `llm-unified` 之后的节点（如 Cache 写、End）。
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- **弃用节点**：原 `llm-unified` 从主链摘除并保留在画布上（无连线），避免与「多段执行」重复；真正推理在 `zhini16-llm-subtask`。
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- **工具**：与 15 相同；每段内 `max_tool_iterations` 可单独配置（默认 12）。
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- **轮数**：环境变量 `ZHINI16_LOOP_ROUNDS`（默认 3，上限 8）。
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引擎要求：`loop` 的**第一条出边**必须指向循环体起点（脚本会对 `zhini16-loop-main` 的出边排序保证）。
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用法:
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cd backend && .\\venv\\Scripts\\python.exe scripts/create_zhini_kefu_16.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15号）, TARGET_NAME（默认 知你客服16号）
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ZHINI16_LOOP_ROUNDS, ZHINI16_SUBTASK_MAX_TOOL_ITERATIONS
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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15号")
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TARGET_NAME = os.getenv("TARGET_NAME", "知你客服16号")
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LOOP_ROUNDS = max(1, min(int(os.getenv("ZHINI16_LOOP_ROUNDS", "3")), 8))
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SUBTASK_MAX_TOOL_ITER = max(1, min(int(os.getenv("ZHINI16_SUBTASK_MAX_TOOL_ITERATIONS", "12")), 64))
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TOOLS_V16: List[str] = [
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"http_request",
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"file_read",
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"file_write",
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"text_analyze",
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"datetime",
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"math_calculate",
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"system_info",
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"json_process",
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"database_query",
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"adb_log",
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]
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LLM_UNIFIED = "llm-unified"
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N_CODE_BUILD = "zhini16-code-build-rounds"
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N_LOOP = "zhini16-loop-main"
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N_SUB_LLM = "zhini16-llm-subtask"
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N_LOOP_END = "zhini16-loop-end"
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N_CODE_MERGE = "zhini16-code-merge-rounds"
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PROMPT_V16_MARKER = "【知你客服 16 号 · Loop 多段执行】"
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PROMPT_V16_SUBTASK_EXTRA = f"""
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{PROMPT_V16_MARKER}
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【执行方式】当前用户请求会在**同一次 API 调用**内被拆成 **{{{{round_total}}}}** 段顺序执行；你收到的是其中**第 {{{{round_index}}}} 段**（从 0 起计），轮次标量 `round`={{{{round}}}}。每段都调用同一套工具与纪律，但请**聚焦本段可推进的子目标**，避免与前后段完全重复；若本段仅需承接上文，可简短小结并推进下一步。
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【输出】每段末尾仍输出**一行合法 JSON**（含 `intent`、`reply`、`user_profile` 等，与 14/15 一致）。`reply` 写**本段**面向用户的可见说明；最终给用户展示时会与各段 `reply` 合并，请勿在段内假设用户已看到其他段的正文。
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【纪律】继承 15 号：多步工具链、`database_query` 仅 SELECT、勿编造工具返回、勿刷屏 DSML。
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"""
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CODE_MERGE_PYTHON = r"""
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import json as _json
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def _parse_tail_json_obj(s):
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if not isinstance(s, str):
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return None
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t = s.strip()
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if not t:
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return None
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last_nl = t.rfind("\n")
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last_line = t[last_nl + 1 :].strip() if last_nl >= 0 else t
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if not last_line.startswith("{"):
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return None
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try:
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o = _json.loads(last_line)
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return o if isinstance(o, dict) else None
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except Exception:
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return None
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def _reply_from_segment(s):
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if not isinstance(s, str):
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return str(s)
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o = _parse_tail_json_obj(s)
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if o and isinstance(o.get("reply"), str) and o["reply"].strip():
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return o["reply"].strip()
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return s.strip()
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parts = []
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if isinstance(input_data, dict):
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if isinstance(input_data.get("input"), list):
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parts = input_data.get("input")
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elif isinstance(input_data.get("right"), list):
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parts = input_data.get("right")
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elif isinstance(input_data, list):
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parts = input_data
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chunks = []
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merged_profile = {}
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for i, p in enumerate(parts):
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if p is None:
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continue
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chunks.append("【第%d段】\n%s" % (i + 1, _reply_from_segment(p)))
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o = _parse_tail_json_obj(p) if isinstance(p, str) else None
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if o and isinstance(o.get("user_profile"), dict):
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merged_profile.update(o["user_profile"])
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merged_text = "\n\n".join(chunks) if chunks else "（循环未产生有效输出）"
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out = dict(input_data) if isinstance(input_data, dict) else {}
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out.pop("input", None)
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out["reply"] = merged_text
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out["right"] = {"right": merged_text}
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if merged_profile:
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out["user_profile_update"] = merged_profile
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result = out
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""".strip()
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def _code_build_source(rounds: List[int]) -> str:
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return (
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"out = dict(input_data) if isinstance(input_data, dict) else {}\n"
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f"out['loop_rounds'] = {rounds!r}\n"
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"result = out\n"
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)
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def _sanitize_edges(edges: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
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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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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 _sort_loop_out_edges(edges: List[Dict[str, Any]], loop_id: str, body_target: str) -> None:
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loop_es = [e for e in edges if e.get("source") == loop_id]
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non = [e for e in edges if e.get("source") != loop_id]
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body = [e for e in loop_es if e.get("target") == body_target]
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rest = [e for e in loop_es if e.get("target") != body_target]
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edges[:] = non + body + rest
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def _upsert_node(nodes: List[Dict[str, Any]], node: Dict[str, Any]) -> None:
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nid = node.get("id")
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for i, n in enumerate(nodes):
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if n.get("id") == nid:
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nodes[i] = node
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return
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nodes.append(node)
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def _topology_already_applied(nodes: List[Dict[str, Any]]) -> bool:
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return any(n.get("id") == N_LOOP for n in (nodes or []))
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def _apply_loop_b_topology(wf: Dict[str, Any], rounds: List[int]) -> None:
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nodes = wf.setdefault("nodes", [])
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edges = wf.setdefault("edges", [])
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pres: List[str] = []
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posts: List[str] = []
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seen_p: set = set()
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seen_t: set = set()
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for e in edges:
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if e.get("target") == LLM_UNIFIED:
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s = e.get("source")
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if s and s not in seen_p:
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seen_p.add(s)
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pres.append(s)
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if e.get("source") == LLM_UNIFIED:
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t = e.get("target")
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if t and t not in seen_t:
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seen_t.add(t)
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posts.append(t)
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if not pres:
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print("错误: 未找到指向 llm-unified 的边，无法从 15 号主线改造。", file=sys.stderr)
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raise SystemExit(2)
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if not posts:
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print("错误: 未找到从 llm-unified 出发的边。", file=sys.stderr)
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raise SystemExit(2)
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edges[:] = [e for e in edges if e.get("target") != LLM_UNIFIED and e.get("source") != LLM_UNIFIED]
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llm_template: Optional[Dict[str, Any]] = None
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for n in nodes:
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if n.get("id") == LLM_UNIFIED:
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llm_template = copy.deepcopy(n)
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break
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sub_llm: Dict[str, Any] = {
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"id": N_SUB_LLM,
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"type": "llm",
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"position": {"x": 0, "y": 0},
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"data": {
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|
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"label": "16号·循环体内LLM",
|
|||
|
|
"prompt": "你是知你客服多段执行中的子任务模型。\n" + PROMPT_V16_SUBTASK_EXTRA,
|
|||
|
|
"enable_tools": True,
|
|||
|
|
"tools": list(TOOLS_V16),
|
|||
|
|
"selected_tools": list(TOOLS_V16),
|
|||
|
|
"max_tool_iterations": SUBTASK_MAX_TOOL_ITER,
|
|||
|
|
},
|
|||
|
|
}
|
|||
|
|
if llm_template:
|
|||
|
|
td = llm_template.get("data") or {}
|
|||
|
|
sd = sub_llm["data"]
|
|||
|
|
for k in ("provider", "model", "temperature", "max_tokens"):
|
|||
|
|
if k in td and td[k] is not None:
|
|||
|
|
sd[k] = td[k]
|
|||
|
|
base_p = (td.get("prompt") or "").strip()
|
|||
|
|
if base_p and PROMPT_V16_MARKER not in base_p:
|
|||
|
|
sd["prompt"] = base_p + "\n" + PROMPT_V16_SUBTASK_EXTRA.strip()
|
|||
|
|
|
|||
|
|
_upsert_node(
|
|||
|
|
nodes,
|
|||
|
|
{
|
|||
|
|
"id": N_CODE_BUILD,
|
|||
|
|
"type": "code",
|
|||
|
|
"position": {"x": 0, "y": 0},
|
|||
|
|
"data": {
|
|||
|
|
"label": "16号·注入loop_rounds",
|
|||
|
|
"language": "python",
|
|||
|
|
"code": _code_build_source(rounds),
|
|||
|
|
},
|
|||
|
|
},
|
|||
|
|
)
|
|||
|
|
_upsert_node(
|
|||
|
|
nodes,
|
|||
|
|
{
|
|||
|
|
"id": N_LOOP,
|
|||
|
|
"type": "loop",
|
|||
|
|
"position": {"x": 0, "y": 0},
|
|||
|
|
"data": {
|
|||
|
|
"label": "16号·多段循环",
|
|||
|
|
"items_path": "right.loop_rounds",
|
|||
|
|
"item_variable": "round",
|
|||
|
|
"error_handling": "continue",
|
|||
|
|
},
|
|||
|
|
},
|
|||
|
|
)
|
|||
|
|
_upsert_node(nodes, sub_llm)
|
|||
|
|
_upsert_node(
|
|||
|
|
nodes,
|
|||
|
|
{
|
|||
|
|
"id": N_LOOP_END,
|
|||
|
|
"type": "loop_end",
|
|||
|
|
"position": {"x": 0, "y": 0},
|
|||
|
|
"data": {"label": "16号·循环结束"},
|
|||
|
|
},
|
|||
|
|
)
|
|||
|
|
_upsert_node(
|
|||
|
|
nodes,
|
|||
|
|
{
|
|||
|
|
"id": N_CODE_MERGE,
|
|||
|
|
"type": "code",
|
|||
|
|
"position": {"x": 0, "y": 0},
|
|||
|
|
"data": {
|
|||
|
|
"label": "16号·合并各段输出",
|
|||
|
|
"language": "python",
|
|||
|
|
"code": CODE_MERGE_PYTHON,
|
|||
|
|
},
|
|||
|
|
},
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
new_edges: List[Dict[str, Any]] = []
|
|||
|
|
for p in pres:
|
|||
|
|
new_edges.append(
|
|||
|
|
{
|
|||
|
|
"id": f"e_{p}_{N_CODE_BUILD}",
|
|||
|
|
"source": p,
|
|||
|
|
"target": N_CODE_BUILD,
|
|||
|
|
"sourceHandle": "right",
|
|||
|
|
"targetHandle": "left",
|
|||
|
|
}
|
|||
|
|
)
|
|||
|
|
new_edges.append(
|
|||
|
|
{
|
|||
|
|
"id": f"e_{N_CODE_BUILD}_{N_LOOP}",
|
|||
|
|
"source": N_CODE_BUILD,
|
|||
|
|
"target": N_LOOP,
|
|||
|
|
"sourceHandle": "right",
|
|||
|
|
"targetHandle": "left",
|
|||
|
|
}
|
|||
|
|
)
|
|||
|
|
new_edges.append(
|
|||
|
|
{
|
|||
|
|
"id": f"e_{N_LOOP}_{N_SUB_LLM}",
|
|||
|
|
"source": N_LOOP,
|
|||
|
|
"target": N_SUB_LLM,
|
|||
|
|
"sourceHandle": "right",
|
|||
|
|
"targetHandle": "left",
|
|||
|
|
}
|
|||
|
|
)
|
|||
|
|
new_edges.append(
|
|||
|
|
{
|
|||
|
|
"id": f"e_{N_SUB_LLM}_{N_LOOP_END}",
|
|||
|
|
"source": N_SUB_LLM,
|
|||
|
|
"target": N_LOOP_END,
|
|||
|
|
"sourceHandle": "right",
|
|||
|
|
"targetHandle": "left",
|
|||
|
|
}
|
|||
|
|
)
|
|||
|
|
new_edges.append(
|
|||
|
|
{
|
|||
|
|
"id": f"e_{N_LOOP}_{N_CODE_MERGE}",
|
|||
|
|
"source": N_LOOP,
|
|||
|
|
"target": N_CODE_MERGE,
|
|||
|
|
"sourceHandle": "right",
|
|||
|
|
"targetHandle": "left",
|
|||
|
|
}
|
|||
|
|
)
|
|||
|
|
for p in posts:
|
|||
|
|
new_edges.append(
|
|||
|
|
{
|
|||
|
|
"id": f"e_{N_CODE_MERGE}_{p}",
|
|||
|
|
"source": N_CODE_MERGE,
|
|||
|
|
"target": p,
|
|||
|
|
"sourceHandle": "right",
|
|||
|
|
"targetHandle": "left",
|
|||
|
|
}
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
edges.extend(new_edges)
|
|||
|
|
_sort_loop_out_edges(edges, N_LOOP, N_SUB_LLM)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def _patch_zhini16_content_only(wf: Dict[str, Any], rounds: List[int]) -> None:
|
|||
|
|
"""已存在 16 号拓扑时，仅刷新 code 与 sub-llm 参数。"""
|
|||
|
|
for n in wf.get("nodes") or []:
|
|||
|
|
nid = n.get("id")
|
|||
|
|
if nid == N_CODE_BUILD:
|
|||
|
|
n.setdefault("data", {})["code"] = _code_build_source(rounds)
|
|||
|
|
elif nid == N_SUB_LLM:
|
|||
|
|
d = n.setdefault("data", {})
|
|||
|
|
d["tools"] = list(TOOLS_V16)
|
|||
|
|
d["selected_tools"] = list(TOOLS_V16)
|
|||
|
|
d["max_tool_iterations"] = SUBTASK_MAX_TOOL_ITER
|
|||
|
|
elif nid == N_LOOP:
|
|||
|
|
d = n.setdefault("data", {})
|
|||
|
|
d["items_path"] = "right.loop_rounds"
|
|||
|
|
d["item_variable"] = "round"
|
|||
|
|
d["error_handling"] = "continue"
|
|||
|
|
elif nid == N_CODE_MERGE:
|
|||
|
|
n.setdefault("data", {})["code"] = CODE_MERGE_PYTHON
|
|||
|
|
|
|||
|
|
|
|||
|
|
def _find_agent_id_by_name(h: Dict[str, str], name: str) -> Optional[str]:
|
|||
|
|
r = requests.get(f"{BASE}/api/v1/agents", params={"search": name, "limit": 50}, headers=h, timeout=30)
|
|||
|
|
if r.status_code != 200:
|
|||
|
|
return None
|
|||
|
|
for a in r.json() or []:
|
|||
|
|
if a.get("name") == name:
|
|||
|
|
return a.get("id")
|
|||
|
|
return None
|
|||
|
|
|
|||
|
|
|
|||
|
|
def main() -> int:
|
|||
|
|
rounds = list(range(1, LOOP_ROUNDS + 1))
|
|||
|
|
|
|||
|
|
r = requests.post(
|
|||
|
|
f"{BASE}/api/v1/auth/login",
|
|||
|
|
data={"username": USER, "password": PWD},
|
|||
|
|
headers={"Content-Type": "application/x-www-form-urlencoded"},
|
|||
|
|
timeout=15,
|
|||
|
|
)
|
|||
|
|
if r.status_code != 200:
|
|||
|
|
print("登录失败:", r.status_code, r.text[:500], file=sys.stderr)
|
|||
|
|
return 1
|
|||
|
|
token = r.json().get("access_token")
|
|||
|
|
if not token:
|
|||
|
|
print("无 access_token", file=sys.stderr)
|
|||
|
|
return 1
|
|||
|
|
h = {"Authorization": f"Bearer {token}", "Content-Type": "application/json"}
|
|||
|
|
|
|||
|
|
src_id = _find_agent_id_by_name(h, SOURCE_NAME)
|
|||
|
|
if not src_id:
|
|||
|
|
print(f"未找到源 Agent: {SOURCE_NAME}", file=sys.stderr)
|
|||
|
|
return 1
|
|||
|
|
|
|||
|
|
existing = _find_agent_id_by_name(h, TARGET_NAME)
|
|||
|
|
if existing:
|
|||
|
|
print("已存在", TARGET_NAME, "-> 仅更新工作流", existing)
|
|||
|
|
new_id = existing
|
|||
|
|
g = requests.get(f"{BASE}/api/v1/agents/{new_id}", headers=h, timeout=30)
|
|||
|
|
if g.status_code != 200:
|
|||
|
|
print("读取失败:", g.text, file=sys.stderr)
|
|||
|
|
return 1
|
|||
|
|
agent = g.json()
|
|||
|
|
else:
|
|||
|
|
dup = requests.post(
|
|||
|
|
f"{BASE}/api/v1/agents/{src_id}/duplicate",
|
|||
|
|
headers=h,
|
|||
|
|
json={"name": TARGET_NAME},
|
|||
|
|
timeout=60,
|
|||
|
|
)
|
|||
|
|
if dup.status_code != 201:
|
|||
|
|
print("复制失败:", dup.status_code, dup.text[:800], file=sys.stderr)
|
|||
|
|
return 1
|
|||
|
|
new_id = dup.json()["id"]
|
|||
|
|
agent = dup.json()
|
|||
|
|
print("已创建副本:", new_id, TARGET_NAME)
|
|||
|
|
|
|||
|
|
wf = copy.deepcopy(agent["workflow_config"])
|
|||
|
|
|
|||
|
|
if _topology_already_applied(wf.get("nodes") or []):
|
|||
|
|
_patch_zhini16_content_only(wf, rounds)
|
|||
|
|
else:
|
|||
|
|
_apply_loop_b_topology(wf, rounds)
|
|||
|
|
|
|||
|
|
loops, dup_edges = improve_workflow_layout_and_edges(wf)
|
|||
|
|
print(f"连线整理: 去掉自环 {loops} 条, 合并重复边 {dup_edges} 条")
|
|||
|
|
|
|||
|
|
desc = (
|
|||
|
|
"知你客服16号：B能力——Loop+循环体内LLM；"
|
|||
|
|
f"默认 {LOOP_ROUNDS} 段顺序执行，每段节点 zhini16-llm-subtask 工具迭代上限 {SUBTASK_MAX_TOOL_ITER}；"
|
|||
|
|
"原 llm-unified 已从主链摘除；各段 reply 经 zhini16-code-merge-rounds 合并后写入下游 Cache/End。"
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
up = requests.put(
|
|||
|
|
f"{BASE}/api/v1/agents/{new_id}",
|
|||
|
|
headers=h,
|
|||
|
|
json={"description": desc, "workflow_config": wf},
|
|||
|
|
timeout=120,
|
|||
|
|
)
|
|||
|
|
if up.status_code != 200:
|
|||
|
|
print("更新失败:", up.status_code, up.text[:1200], file=sys.stderr)
|
|||
|
|
return 1
|
|||
|
|
print("loop_rounds:", rounds)
|
|||
|
|
print("工具:", ", ".join(TOOLS_V16))
|
|||
|
|
print("Agent ID:", new_id)
|
|||
|
|
print(json.dumps({"id": new_id, "name": TARGET_NAME}, ensure_ascii=False))
|
|||
|
|
return 0
|
|||
|
|
|
|||
|
|
|
|||
|
|
if __name__ == "__main__":
|
|||
|
|
raise SystemExit(main())
|