244 lines
9.0 KiB
Python
244 lines
9.0 KiB
Python
|
#!/usr/bin/env python3
|
|||
|
|
"""
|
|||
|
|
从「知你客服8号」复制为「知你客服9号」，强化「摘要 + 检索」可用性：
|
|||
|
|
|
|||
|
|
1. 上下文 code-build-context：更长近期轮次、注入 conversation_summary、向量结果 + 关键词从历史中捞相关句。
|
|||
|
|
2. 摘要路径 code-build-memory-value：在原有摘要分支上合并进完整 conversation_history（追加而非仅 2 条），并写回 conversation_summary。
|
|||
|
|
3. cache-update-summary：显式 value 为「memory」表达式，避免整包 input_data 写入 Redis。
|
|||
|
|
4. 向量写入：为每条 turn 带 metadata.user_id；引擎侧检索已按 user_id 过滤。
|
|||
|
|
|
|||
|
|
需平台可登录；默认源 8 号 ID 为上次创建结果，可用 ZHINI_8_AGENT_ID 覆盖。
|
|||
|
|
部署后请重启 Celery/API 以加载引擎向量过滤逻辑。
|
|||
|
|
"""
|
|||
|
|
from __future__ import annotations
|
|||
|
|
|
|||
|
|
import json
|
|||
|
|
import os
|
|||
|
|
import sys
|
|||
|
|
|
|||
|
|
import requests
|
|||
|
|
|
|||
|
|
BASE = os.getenv("PLATFORM_BASE_URL", "http://127.0.0.1:8037").rstrip("/")
|
|||
|
|
SOURCE_AGENT_ID = os.getenv("ZHINI_8_AGENT_ID", "d7b64bf6-c8e3-4dc7-befc-03a98d5ff741")
|
|||
|
|
USER = os.getenv("PLATFORM_USERNAME", "admin")
|
|||
|
|
PWD = os.getenv("PLATFORM_PASSWORD", "123456")
|
|||
|
|
|
|||
|
|
NEW_NAME = "知你客服9号"
|
|||
|
|
NEW_DESC = (
|
|||
|
|
"在知你客服8号基础上强化摘要与检索："
|
|||
|
|
"远期要点写入 conversation_summary；"
|
|||
|
|
"当轮上下文含「近期对话 + 摘要 + 向量片段 + 关键词相关历史」；"
|
|||
|
|
"向量库写入带 user_id 元数据，引擎检索按用户隔离。"
|
|||
|
|
"仍依赖 MEMORY_PERSIST_DB_ENABLED 与固定 user_id。"
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
LLM_PROMPT = """你是客服助手。根据「用户当前输入」「已知用户信息」「远期摘要」「相关历史（检索）」和「最近几轮」完成：
|
|||
|
|
1）判断意图；
|
|||
|
|
2）生成一句自然、有帮助的回复；
|
|||
|
|
3）【强制】用户说出或暗示姓名、昵称时，必须在 user_profile.name 保存；合并已有字段勿丢失；
|
|||
|
|
4）用户问「我叫什么」等时，必须依据 user_profile.name 与对话/摘要回答；已有 name 时禁止说「还不知道」；
|
|||
|
|
5）「远期摘要」概括更早话题；「相关历史」可能含向量命中或关键词命中的旧轮次，请结合使用。
|
|||
|
|
|
|||
|
|
只输出一行合法 JSON，不要 markdown。格式示例：
|
|||
|
|
{"intent":"greeting","reply":"你好！","user_profile":{"name":"小明"}}
|
|||
|
|
|
|||
|
|
用户输入：{{user_input}}
|
|||
|
|
已知用户信息：{{memory.user_profile}}
|
|||
|
|
远期摘要：{{memory.conversation_summary}}
|
|||
|
|
相关历史（检索到的）：{{memory.relevant_from_retrieval}}
|
|||
|
|
最近几轮：{{memory.recent_turns}}
|
|||
|
|
|
|||
|
|
要求：reply 简洁自然，200 字以内；user_profile 为对象。"""
|
|||
|
|
|
|||
|
|
CODE_BUILD_CONTEXT = r"""left = input_data.get('left') or {}
|
|||
|
|
right = input_data.get('right') or []
|
|||
|
|
if not isinstance(right, list):
|
|||
|
|
right = []
|
|||
|
|
mem = left.get('memory') or {}
|
|||
|
|
hist = mem.get('conversation_history') or []
|
|||
|
|
if not isinstance(hist, list):
|
|||
|
|
hist = []
|
|||
|
|
summary = mem.get('conversation_summary') or ''
|
|||
|
|
recent_n = 16
|
|||
|
|
recent = hist[-recent_n:] if len(hist) > recent_n else hist
|
|||
|
|
recent_str = '\n'.join(f"{x.get('role', '')}: {x.get('content', '')}" for x in recent)
|
|||
|
|
vec_str = '\n'.join((rec.get('text') or rec.get('content') or '') for rec in right)
|
|||
|
|
query = (left.get('user_input') or left.get('query') or '').strip()
|
|||
|
|
older = hist[:-recent_n] if len(hist) > recent_n else []
|
|||
|
|
|
|||
|
|
|
|||
|
|
def _tok(s):
|
|||
|
|
s = str(s)
|
|||
|
|
ch = {c for c in s if '\u4e00' <= c <= '\u9fff'}
|
|||
|
|
wd = set(s.lower().replace('\n', ' ').split())
|
|||
|
|
return ch | wd
|
|||
|
|
|
|||
|
|
|
|||
|
|
qt = _tok(query) if query else set()
|
|||
|
|
scored = []
|
|||
|
|
for m in older:
|
|||
|
|
c = str(m.get('content', ''))
|
|||
|
|
if not c:
|
|||
|
|
continue
|
|||
|
|
sc = len(qt & _tok(c)) if qt else 0
|
|||
|
|
if sc > 0:
|
|||
|
|
scored.append((sc, str(m.get('role', '')), c[:240]))
|
|||
|
|
scored.sort(key=lambda x: -x[0])
|
|||
|
|
kw_lines = [f"{role}: {text}" for _, role, text in scored[:6]]
|
|||
|
|
kw_str = '\n'.join(kw_lines)
|
|||
|
|
relevant_str = vec_str.strip()
|
|||
|
|
if kw_str:
|
|||
|
|
if relevant_str:
|
|||
|
|
relevant_str = relevant_str + '\n---\n关键词相关历史：\n' + kw_str
|
|||
|
|
else:
|
|||
|
|
relevant_str = '关键词相关历史：\n' + kw_str
|
|||
|
|
result = {
|
|||
|
|
'user_input': left.get('user_input') or left.get('query') or '',
|
|||
|
|
'memory': {
|
|||
|
|
'user_profile': mem.get('user_profile') or {},
|
|||
|
|
'conversation_summary': summary,
|
|||
|
|
'relevant_from_retrieval': relevant_str,
|
|||
|
|
'recent_turns': recent_str,
|
|||
|
|
},
|
|||
|
|
'query': left.get('query') or '',
|
|||
|
|
'user_id': left.get('user_id'),
|
|||
|
|
}
|
|||
|
|
"""
|
|||
|
|
|
|||
|
|
CODE_BUILD_MEMORY_VALUE = r"""left = input_data.get('left') or {}
|
|||
|
|
right_out = input_data.get('right') or {}
|
|||
|
|
summary = ''
|
|||
|
|
if isinstance(right_out, dict):
|
|||
|
|
summary = right_out.get('output') or right_out.get('result') or ''
|
|||
|
|
if not isinstance(summary, str):
|
|||
|
|
summary = str(summary or '')
|
|||
|
|
summary = summary.strip()
|
|||
|
|
mem = left.get('memory') or {}
|
|||
|
|
user_input = left.get('user_input') or left.get('query') or ''
|
|||
|
|
reply = left.get('right') or ''
|
|||
|
|
if isinstance(reply, dict):
|
|||
|
|
reply = reply.get('right') or reply.get('content') or str(reply)
|
|||
|
|
profile_update = left.get('user_profile_update') or {}
|
|||
|
|
if not isinstance(profile_update, dict):
|
|||
|
|
profile_update = {}
|
|||
|
|
user_profile = dict(mem.get('user_profile') or {}, **profile_update)
|
|||
|
|
ts = datetime.now().isoformat()
|
|||
|
|
old_hist = mem.get('conversation_history') or []
|
|||
|
|
if not isinstance(old_hist, list):
|
|||
|
|
old_hist = []
|
|||
|
|
new_hist = old_hist + [
|
|||
|
|
{'role': 'user', 'content': user_input, 'timestamp': ts},
|
|||
|
|
{'role': 'assistant', 'content': str(reply or ''), 'timestamp': ts},
|
|||
|
|
]
|
|||
|
|
max_len = 40
|
|||
|
|
if len(new_hist) > max_len:
|
|||
|
|
new_hist = new_hist[-max_len:]
|
|||
|
|
prev_sum = (mem.get('conversation_summary') or '').strip()
|
|||
|
|
conversation_summary = summary if summary else prev_sum
|
|||
|
|
memory_value = {
|
|||
|
|
'conversation_summary': conversation_summary,
|
|||
|
|
'conversation_history': new_hist,
|
|||
|
|
'user_profile': user_profile,
|
|||
|
|
'context': mem.get('context') or {},
|
|||
|
|
}
|
|||
|
|
result = {
|
|||
|
|
'memory': memory_value,
|
|||
|
|
'user_id': left.get('user_id'),
|
|||
|
|
'query': left.get('query'),
|
|||
|
|
'user_input': user_input,
|
|||
|
|
'right': reply,
|
|||
|
|
'user_profile_update': profile_update,
|
|||
|
|
}
|
|||
|
|
"""
|
|||
|
|
|
|||
|
|
CODE_BUILD_TURN_FOR_VECTOR = r"""reply = input_data.get('right') or ''
|
|||
|
|
if isinstance(reply, dict):
|
|||
|
|
reply = reply.get('right') or reply.get('content') or str(reply)
|
|||
|
|
query = input_data.get('query') or ''
|
|||
|
|
user_id = str(input_data.get('user_id') or 'default')
|
|||
|
|
raw = (user_id + '\n' + str(query) + '\n' + str(reply)).encode('utf-8', errors='ignore')
|
|||
|
|
doc_id = 'turn_' + hashlib.sha256(raw).hexdigest()[:24]
|
|||
|
|
text = '用户：' + str(query) + '\n助手：' + str(reply)
|
|||
|
|
result = {
|
|||
|
|
'text': text,
|
|||
|
|
'user_id': user_id,
|
|||
|
|
'id': doc_id,
|
|||
|
|
'metadata': {'user_id': user_id},
|
|||
|
|
}
|
|||
|
|
"""
|
|||
|
|
|
|||
|
|
|
|||
|
|
def _patch_nodes(wf: dict) -> None:
|
|||
|
|
nodes = wf.get("nodes") or []
|
|||
|
|
for n in nodes:
|
|||
|
|
nid = n.get("id")
|
|||
|
|
if nid == "llm-unified":
|
|||
|
|
n.setdefault("data", {})["prompt"] = LLM_PROMPT
|
|||
|
|
elif nid == "code-build-context":
|
|||
|
|
n.setdefault("data", {})["code"] = CODE_BUILD_CONTEXT
|
|||
|
|
elif nid == "code-build-memory-value":
|
|||
|
|
n.setdefault("data", {})["code"] = CODE_BUILD_MEMORY_VALUE
|
|||
|
|
elif nid == "code-build-turn-for-vector":
|
|||
|
|
n.setdefault("data", {})["code"] = CODE_BUILD_TURN_FOR_VECTOR
|
|||
|
|
elif nid == "cache-update-summary":
|
|||
|
|
d = n.setdefault("data", {})
|
|||
|
|
d["value"] = "memory"
|
|||
|
|
elif nid == "transform-for-vector-upsert":
|
|||
|
|
m = n.setdefault("data", {}).setdefault("mapping", {})
|
|||
|
|
m["metadata"] = "{{left.metadata}}"
|
|||
|
|
|
|||
|
|
|
|||
|
|
def main() -> int:
|
|||
|
|
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"}
|
|||
|
|
|
|||
|
|
dup = requests.post(
|
|||
|
|
f"{BASE}/api/v1/agents/{SOURCE_AGENT_ID}/duplicate",
|
|||
|
|
headers=h,
|
|||
|
|
json={"name": NEW_NAME},
|
|||
|
|
timeout=30,
|
|||
|
|
)
|
|||
|
|
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"]
|
|||
|
|
print("已创建副本:", new_id, NEW_NAME)
|
|||
|
|
|
|||
|
|
g = requests.get(f"{BASE}/api/v1/agents/{new_id}", headers=h, timeout=30)
|
|||
|
|
if g.status_code != 200:
|
|||
|
|
print("读取 Agent 失败:", g.text, file=sys.stderr)
|
|||
|
|
return 1
|
|||
|
|
agent = g.json()
|
|||
|
|
wf = agent["workflow_config"]
|
|||
|
|
_patch_nodes(wf)
|
|||
|
|
|
|||
|
|
up = requests.put(
|
|||
|
|
f"{BASE}/api/v1/agents/{new_id}",
|
|||
|
|
headers=h,
|
|||
|
|
json={"description": NEW_DESC, "workflow_config": wf},
|
|||
|
|
timeout=60,
|
|||
|
|
)
|
|||
|
|
if up.status_code != 200:
|
|||
|
|
print("更新失败:", up.status_code, up.text[:800], file=sys.stderr)
|
|||
|
|
return 1
|
|||
|
|
print("已更新：LLM 提示、code-build-context / memory-value / vector-turn、cache-update-summary.value、upsert.metadata")
|
|||
|
|
print("Agent ID:", new_id)
|
|||
|
|
print(json.dumps({"id": new_id, "name": NEW_NAME}, ensure_ascii=False))
|
|||
|
|
return 0
|
|||
|
|
|
|||
|
|
|
|||
|
|
if __name__ == "__main__":
|
|||
|
|
raise SystemExit(main())
|