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AgentLab/backend/app/engine/schema.py
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from __future__ import annotations
import math
import re
from collections import defaultdict
from enum import StrEnum
from typing import Any, Iterable, Literal
from pydantic import BaseModel, Field, field_validator, model_validator
from app.engine.labels import TYPE_LABEL, field_label, judge_label, option_label, q, type_label # noqa: F401
class NodeType(StrEnum):
"""画布上可用的节点类型。新增类型 = 加一个枚举值 + 一个执行器 + 一个前端渲染。"""
INPUT = "input"
OUTPUT = "output"
LLM = "llm" # 单次模型调用
AGENT = "agent" # 带工具循环的 ReAct agent
SUPERVISOR = "supervisor" # 多 agent 调度
TOOL = "tool" # 直接调用一个工具
CODE = "code" # 沙箱里跑代码
MERGE = "merge" # 合并查询:几次查询的完整结果在库外按键合并(engine/merge_query.py)
BRANCH = "branch" # 条件分支
LOOP = "loop" # 循环 / 迭代
SUBGRAPH = "subgraph" # 嵌套另一个工作流
MEMORY = "memory" # 长期记忆读写
RETRIEVE = "retrieve" # 知识库检索
TRANSFORM = "transform" # 数据整形
HUMAN = "human" # 人工介入
VALIDATE = "validate" # 结构化校验 + 自动重试
METRICS = "metrics" # 口径卡:受控指标集,叙述层唯一合法的数字来源
REPORT = "report" # 报告撰写:模型只写引用标记,数字由系统从口径卡取出来渲染
# 下面两种目前只是占位(执行器原样放行),各自的工作包补上真正的逻辑
DUAL_CHECK = "dual_check" # 双盲复算:另起一路独立算一遍,和原结果比对
CHALLENGE = "challenge" # 反方审稿:专挑报告的毛病,提出反驳意见
# 节点类型在画布上的叫法(TYPE_LABEL / type_label)从 labels.py 导入:报错和门禁文案用它,
# 而不是枚举值——用户在界面上从没见过 supervisor、llm 这些词
class Position(BaseModel):
x: float = 0
y: float = 0
class NodeData(BaseModel):
"""节点上的可编辑内容。config 保持松散 dict,各执行器自己解析成强类型模型,
这样前端加字段不会让整张图反序列化失败。"""
label: str = ""
description: str = ""
config: dict[str, Any] = Field(default_factory=dict)
class GraphNode(BaseModel):
id: str
type: NodeType
position: Position = Field(default_factory=Position)
data: NodeData = Field(default_factory=NodeData)
@field_validator("id")
@classmethod
def _valid_id(cls, v: str) -> str:
if not v or not v.replace("_", "").replace("-", "").isalnum():
raise ValueError(f"节点 ID 只能包含字母、数字、下划线和连字符,当前为「{v}」")
# LangGraph 保留了这两个名字
if v in ("__start__", "__end__"):
raise ValueError(f"「{v}」是保留的节点 ID,请换一个")
return v
@property
def config(self) -> dict[str, Any]:
return self.data.config
@property
def title(self) -> str:
return self.data.label or self.id
class GraphEdge(BaseModel):
id: str = ""
source: str
target: str
# 分支节点用 sourceHandle 区分走哪条路:"true"/"false" 或自定义 case key
sourceHandle: str | None = None
targetHandle: str | None = None
label: str = ""
@model_validator(mode="after")
def _fill_id(self) -> "GraphEdge":
if not self.id:
self.id = f"{self.source}:{self.sourceHandle or ''}->{self.target}"
return self
@property
def branch_key(self) -> str | None:
return self.sourceHandle if self.sourceHandle not in (None, "out", "source") else None
class GraphSpec(BaseModel):
"""一整张可执行的图。前端 React Flow 的画布状态直接序列化成它。"""
nodes: list[GraphNode] = Field(default_factory=list)
edges: list[GraphEdge] = Field(default_factory=list)
viewport: dict[str, Any] = Field(default_factory=dict)
# 图级别的默认值,节点没配 provider/model 时回退到这里
defaults: dict[str, Any] = Field(default_factory=dict)
def node_map(self) -> dict[str, GraphNode]:
return {n.id: n for n in self.nodes}
def outgoing(self, node_id: str) -> list[GraphEdge]:
return [e for e in self.edges if e.source == node_id]
def incoming(self, node_id: str) -> list[GraphEdge]:
return [e for e in self.edges if e.target == node_id]
def entry_nodes(self) -> list[GraphNode]:
"""入口 = input 节点;没有 input 节点时退化为所有无入边的节点。"""
inputs = [n for n in self.nodes if n.type == NodeType.INPUT]
if inputs:
return inputs
return [n for n in self.nodes if not self.incoming(n.id)]
def terminal_nodes(self) -> list[GraphNode]:
outputs = [n for n in self.nodes if n.type == NodeType.OUTPUT]
if outputs:
return outputs
return [n for n in self.nodes if not self.outgoing(n.id)]
# --------------------------------------------------------------------------
# 校验
# --------------------------------------------------------------------------
class ValidationIssue(BaseModel):
#: info 是建议、不是问题(evidence.upgrade_available「可以升级为可追溯结构」):不挡运行、不挡发布,
#: 自查、门禁、修复复核都只数 error
level: Literal["error", "warning", "info"] = "error"
node_id: str | None = None
edge_id: str | None = None
message: str
#: 节点配置里出问题的那个字段:prompt、cases[1].condition、agents[0].system。
#: 检查器靠它把问题落到具体的输入框下面;说不清是哪个字段的(连线、图级)为空
field: str | None = None
#: 机器认的问题编号(governed.agent_approval_never、contract.required_missing…)。发布前自动修复
#: 靠它认出是哪一类问题;文案会改,编号不改。没有编号的问题只能人看着修
code: str | None = None
#: 这条问题对应的修复 id(engine/autofix.py 算出来的)。只在发布检查的结果里填
fix: str | None = None
#: 发布门禁里基于数据目录的 SQL 检查(governance._lint_sql):这条检查本来的级别(error / warning)。level 说的是
#: 拦不拦(已发布档一律 warning),前端要按它说清「错误级问题,已发布只提醒、受管会拦」。别的问题没有这一项,
#: 序列化时也不出现
sql_level: Literal["error", "warning"] | None = Field(default=None, exclude_if=lambda v: v is None)
class ValidationResult(BaseModel):
ok: bool = True
issues: list[ValidationIssue] = Field(default_factory=list)
def add(self, message: str, *, level: str = "error", node_id: str | None = None,
edge_id: str | None = None, field: str | None = None, code: str | None = None,
sql_level: str | None = None) -> None:
self.issues.append(
ValidationIssue(level=level, message=message, node_id=node_id, # type: ignore[arg-type]
edge_id=edge_id, field=field, code=code, sql_level=sql_level) # type: ignore[arg-type]
)
if level == "error":
self.ok = False
def topology_of(spec: GraphSpec) -> tuple[tuple, tuple]:
"""图的骨架:节点的 id 与类型、加上所有的边。**不含任何配置。**
断点续跑要用它。LangGraph 的 checkpoint 是按节点名存的(编译时
`builder.add_node(node.id, …)`),而节点配置是运行时从 spec 现读的
(`NodeContext.cfg`)。所以拿一张只改了配置的图去续,checkpoint 对得上,
前面跑过的节点结果照样能用;一旦增删节点或改连线,checkpoint 里的
通道状态就和新图对不上了——续下去跑出来的是一份似是而非的结果,
比直接报错糟得多。
这正是 resume 那边踩过的坑:不看有没有 checkpoint 就发 Command,
LangGraph 拿空 state 从 START 重跑,最后还落成 succeeded。
"""
return (
tuple(sorted((n.id, str(n.type)) for n in spec.nodes)),
tuple(sorted((e.source, e.target, e.sourceHandle or "") for e in spec.edges)),
)
def back_edges(
node_ids: Iterable[str], edges: Iterable[GraphEdge], *, roots: Iterable[str] = (),
) -> set[tuple[str, str, str]]:
"""DFS 森林里的回边,以 (source, target, sourceHandle) 表示。剔掉它们,剩下的必然无环。
哪条边算"回边"取决于 DFS 从哪里出发。排版不在乎,按节点顺序起算就行;
执行语义在乎——得从入口(roots)起算,否则循环体里的一条普通前向边可能被
误判成回边。两端有一端不在 node_ids 里的悬空边直接忽略。
迭代式而不是递归:一张几百个节点的图不该因为递归深度挂掉。
"""
WHITE, GREY, BLACK = 0, 1, 2
state = dict.fromkeys(node_ids, WHITE)
adj: dict[str, list[GraphEdge]] = defaultdict(list)
for e in edges:
if e.source in state and e.target in state:
adj[e.source].append(e)
back: set[tuple[str, str, str]] = set()
for root in [*roots, *state]:
if state.get(root) != WHITE:
continue
stack: list[tuple[str, int]] = [(root, 0)]
state[root] = GREY
while stack:
node_id, i = stack[-1]
out = adj[node_id]
if i >= len(out):
state[node_id] = BLACK
stack.pop()
continue
stack[-1] = (node_id, i + 1)
edge = out[i]
target = edge.target
if state[target] == GREY:
back.add((edge.source, edge.target, edge.sourceHandle or ""))
elif state[target] == WHITE:
state[target] = GREY
stack.append((target, 0))
return back
def loop_steps(spec: GraphSpec) -> int:
"""图里的循环按各自声明的轮数跑满,最多要走多少步(LangGraph 的 superstep)。
整次运行的步数上限(max_graph_steps)防的是没人把关的环;loop 节点自己带着
max_iterations,那是作者明说的轮数上限。以前两者打架时全局值悄悄赢:「测试 1」
的 while 循环配了 1005 轮、每轮 2 步,跑到 100 轮上下就被 GraphRecursionError
掐断——校验通过,跑到一半才死。runner 把这个数加在全局上限之上。
取上界不求精确:一个节点最多跑 Π(包住它的各层循环的 max_iterations + 1) 次,
逐个加起来。一步至少跑一个节点,所以步数只会比这少。
"""
bodies = loop_bodies(spec)
if not bodies:
return 0
loops = spec.node_map()
runs: dict[str, int] = defaultdict(lambda: 1)
for loop_id, body in bodies.items():
try:
cap = int(loops[loop_id].config.get("max_iterations", 10) or 10)
except (TypeError, ValueError):
cap = 10 # 运行到这个节点时同样会报错,这里不替它报
for n in body | {loop_id}:
runs[n] *= max(cap, 0) + 1
return sum(runs.values())
def loop_bodies(spec: GraphSpec) -> dict[str, set[str]]:
"""每个循环节点的循环体(不含循环节点本身)。
循环体 = 从 body 出口出发、不经过循环节点本身、又能绕回它的那些节点。
没标出口的边路由时按 default 走,body 也会走它。
"""
loops = [n for n in spec.nodes if n.type == NodeType.LOOP]
if not loops:
return {}
succ: dict[str, list[str]] = defaultdict(list)
pred: dict[str, list[str]] = defaultdict(list)
for e in spec.edges:
succ[e.source].append(e.target)
pred[e.target].append(e.source)
def reach(starts: Iterable[str], step: dict[str, list[str]], avoid: str) -> set[str]:
seen: set[str] = set()
stack = [s for s in starts if s != avoid]
while stack:
n = stack.pop()
if n not in seen:
seen.add(n)
stack.extend(x for x in step[n] if x != avoid)
return seen
out: dict[str, set[str]] = {}
for loop in loops:
entries = [e.target for e in spec.outgoing(loop.id) if e.sourceHandle != "done"]
out[loop.id] = reach(entries, succ, loop.id) & reach(pred[loop.id], pred, loop.id)
return out
def innermost_loops(spec: GraphSpec) -> dict[str, str]:
"""节点 -> 直接包住它的那一层循环。嵌套时取循环体最小的那个。"""
bodies = loop_bodies(spec)
out: dict[str, str] = {}
for loop_id, body in sorted(bodies.items(), key=lambda kv: -len(kv[1])):
for n in body:
out[n] = loop_id # 由大到小覆盖,最后留下的是最内层
return out
def expression_fields(node: GraphNode) -> list[tuple[str, str, str]]:
"""这个节点上按表达式求值的字段:(给人看的名字, 原文, 字段路径)。
跟着模式走:foreach 循环的 condition、模板模式整形的 expression 不参与求值,
拿它们报错就是误报。
"""
cfg = node.config
out: list[tuple[str, str, str]] = []
def add(label: str, value: Any, field: str) -> None:
if isinstance(value, str) and value.strip():
out.append((label, value, field))
add("跳过条件", cfg.get("skip_if"), "skip_if")
if node.type == NodeType.BRANCH and cfg.get("mode", "expression") == "expression":
for i, case in enumerate(cfg.get("cases") or []):
case = case or {}
add(f"分支「{case.get('label') or case.get('key') or '?'}」的条件", case.get("condition"),
f"cases[{i}].condition")
elif node.type == NodeType.LOOP and cfg.get("mode", "foreach") == "while":
add("循环条件", cfg.get("condition"), "condition")
elif node.type == NodeType.TRANSFORM and cfg.get("mode", "expression") == "expression":
add("整形表达式", cfg.get("expression"), "expression")
elif node.type == NodeType.METRICS:
for i, d in enumerate(cfg.get("metrics") or []):
d = d or {}
add(f"指标「{d.get('id') or '?'}」的表达式", d.get("expression"), f"metrics[{i}].expression")
return out
# 代码节点可能往 stdout 写东西的迹象。宁可漏判不可误判:这条是 error 级、会挡住运行,
# 所以间接的写法(子进程、exec、附带文件里的 print)都算。整行只有一个 {{ }} 的,
# 那行代码是运行时从上游拿的(⑤号示例整段就是 {{ vars.code }}),看不见,不猜;
# 而 `state = {{ vars.state | json }}` 这种只是填一个值,照查
_MAY_WRITE_STDOUT = re.compile(
r"\b(print|pprint|exec)\s*\(|\bstdout\b|\bos\.(system|write|popen)\b|\bsubprocess\b"
r"|^\s*\{\{.*\}\}\s*$", re.M)
def _check_case_keys(node: GraphNode, cases: list[Any], result: ValidationResult) -> None:
"""分支出口的 id 就是 case 的 key,所以 key 得唯一、非空,而且不能占用兜底出口的名字。
default 只报警告:现存的 ⑥ 模板就写着 key=default、条件为 true,运行语义上等价于
兜底,是自洽的;升成 error 会让它和所有从它复制出来的图直接不能跑。可它在画布上
会和「其他」撞成同一个出口,跑完两条一起点亮——得说出来。
重复和空 key 是真坏了:路由只认 key,重复的那个永远轮不到,空的根本连不出边。
"""
seen: set[str] = set()
for i, case in enumerate(cases, start=1):
case = case or {}
key = str(case.get("key") or "").strip()
name = case.get("label") or key or f"第 {i} 个"
field = f"cases[{i - 1}].key"
if not key:
result.add(f"「条件分支」的分支「{name}」没有标识,无法连线,也不会被选中",
node_id=node.id, field=field)
continue
if key == "default":
result.add(
f"分支「{name}」的标识用了「default」:这是「其他」出口的保留名,两者会合并成"
"同一个出口,运行后无法区分走的是哪一条。请换一个标识,例如 team",
level="warning", node_id=node.id, field=field,
)
elif key in seen:
result.add(f"「条件分支」中有两个分支的标识都是「{key}」:路由只按标识区分,"
"后一个分支不会被选中。请换一个不重复的标识", node_id=node.id, field=field)
seen.add(key)
def _ancestors(spec: GraphSpec, node_id: str) -> set[str]:
"""沿连线往回走能到的所有节点(不含自己)。循环里的节点彼此都算上游。"""
parents: dict[str, list[str]] = defaultdict(list)
for e in spec.edges:
parents[e.target].append(e.source)
seen: set[str] = set()
stack = list(parents[node_id])
while stack:
cur = stack.pop()
if cur not in seen:
seen.add(cur)
stack.extend(parents[cur])
seen.discard(node_id)
return seen
def _check_report_sources(node: GraphNode, spec: GraphSpec, result: ValidationResult) -> None:
"""报告的 metrics_from 只能指向它上游的口径卡。
指错了运行时不会报错:目录里就是没有那张卡的指标,模型要么写不出数、要么被
判成引用不存在——在画图时说破比跑完再猜原因便宜得多。
"""
sources = node.config.get("metrics_from")
if sources in (None, "", []):
return # 不写就取所有上游口径卡
if isinstance(sources, str):
sources = [sources]
code = "report.metrics_from_invalid"
if not isinstance(sources, list) or not all(isinstance(s, str) and s for s in sources):
result.add("「报告撰写」的「指标来自」需要选择口径卡节点", node_id=node.id,
field="metrics_from", code=code)
return
nodes = spec.node_map()
upstream = _ancestors(spec, node.id)
for src in sources:
target = nodes.get(src)
if target is None:
result.add(f"「报告撰写」的「指标来自」选择了「{src}」,但工作流中不存在这个节点",
node_id=node.id, field="metrics_from", code=code)
elif target.type != NodeType.METRICS:
result.add(f"「报告撰写」的「指标来自」选择了「{target.title}」,它是「{type_label(target.type)}」"
"节点,不是口径卡;报告中的指标只能来自口径卡",
node_id=node.id, field="metrics_from", code=code)
elif src not in upstream:
result.add(f"「报告撰写」的「指标来自」选择的口径卡「{target.title}」不在它的上游:撰写报告时"
"该口径卡尚未计算,报告无法引用它的指标。请把口径卡连到报告撰写节点之前",
node_id=node.id, field="metrics_from", code=code)
def _produces_query(node: GraphNode) -> bool:
"""这个节点的产出是一份存成快照的查询结果:调用数据库查询工具的「调用工具」节点,或另一个合并查询。"""
if node.type == NodeType.MERGE:
return True
return node.type == NodeType.TOOL and str(node.config.get("tool") or "").startswith("db_query__")
def _check_merge(node: GraphNode, spec: GraphSpec, result: ValidationResult) -> None:
"""合并查询的输入和合并 SQL。规则和执行时(engine/merge_query.py)同一套,画图时就说破,不等运行到这一步才失败。
输入只认能稳定取到一份查询快照的节点。Agent 查过的库不行:一次循环里可能查好几次,取哪一次说不准,
拿错一次合并出来的数照样像模像样——所以报 error,并说清楚把那条查询单独放进「调用工具」节点。
"""
from app.engine.merge_query import MAX_INPUTS, alias_problem, sql_problem
cfg = node.config
inputs = cfg.get("inputs")
if not isinstance(inputs, dict) or not inputs:
result.add("「合并查询」还没有配置输入:至少选择一个上游的查询节点,并给它起一个别名(合并 SQL 里的表名)",
node_id=node.id, field="inputs", code="merge.inputs_missing")
else:
if len(inputs) > MAX_INPUTS:
result.add(f"「合并查询」最多 {MAX_INPUTS} 个输入,这里有 {len(inputs)} 个。请先在源库里合并一部分",
node_id=node.id, field="inputs", code="merge.inputs_missing")
nodes = spec.node_map()
upstream = _ancestors(spec, node.id)
seen: dict[str, str] = {}
for alias, source in inputs.items():
field = f"inputs.{alias}"
if problem := alias_problem(alias):
result.add(f"「合并查询」的{problem}", node_id=node.id, field=field, code="merge.alias_invalid")
elif alias.lower() in seen:
result.add(f"「合并查询」的别名「{seen[alias.lower()]}」和「{alias}」只差大小写:SQLite 的表名不分大小写,"
"会被当成同一张表。请换一个别名", node_id=node.id, field=field, code="merge.alias_invalid")
else:
seen[alias.lower()] = alias
target = nodes.get(source) if isinstance(source, str) else None
who = f"「合并查询」的输入「{alias}」"
if not isinstance(source, str) or not source:
result.add(f"{who}还没有选择节点", node_id=node.id, field=field, code="merge.input_invalid")
elif target is None:
result.add(f"{who}选择了「{source}」,但工作流中不存在这个节点", node_id=node.id, field=field,
code="merge.input_invalid")
elif target.type == NodeType.AGENT:
result.add(f"{who}选择了「{target.title}」(Agent):Agent 可能查询多次,无法确定合并哪一次的结果。"
"请把要合并的那条查询单独放进「调用工具」节点(选择数据库查询工具),再把它选作输入",
node_id=node.id, field=field, code="merge.input_invalid")
elif target.type == NodeType.TOOL and not _produces_query(target):
result.add(f"{who}选择的「{target.title}」调用的不是数据库查询工具:合并查询只能合并数据库查询的结果",
node_id=node.id, field=field, code="merge.input_invalid")
elif not _produces_query(target):
result.add(f"{who}选择的「{target.title}」是「{type_label(target.type)}」节点,不产出查询结果。"
"输入只能是调用数据库查询工具的「调用工具」节点,或另一个「合并查询」节点",
node_id=node.id, field=field, code="merge.input_invalid")
elif source not in upstream:
result.add(f"{who}选择的「{target.title}」不在合并查询的上游:合并时它还没有运行。请把它连到合并查询之前",
node_id=node.id, field=field, code="merge.input_invalid")
sql = cfg.get("sql")
if not isinstance(sql, str) or not sql.strip():
result.add("「合并查询」还没有填写合并 SQL", node_id=node.id, field="sql", code="merge.sql_invalid")
elif problem := sql_problem(sql):
result.add(problem, node_id=node.id, field="sql", code="merge.sql_invalid")
#: 报告撰写节点的结论句策略(claims)。off:结论句不参与判档(默认,保持以前的行为);
#: require_citation:没挂引用的结论句计入缺口、按出具档位降档。这两档是确定性的(发布前自动修复
#: 给人选的也只有这两档)
REPORT_CLAIMS = ("off", "require_citation")
#: judge:结论句由另一个模型按证据逐句判断(engine/judge.py),子配置写在节点的 judge 里
CLAIMS_JUDGE = "judge"
CLAIMS_VALUES = (*REPORT_CLAIMS, CLAIMS_JUDGE)
#: judge 子配置能写的键。三个上限写 null 表示不限;没写的键运行时取设置里的默认(设置 → judge 一组)
JUDGE_KEYS = ("provider", "model", "max_claims", "max_cost_usd", "timeout_s", "rewrite_once", "on_unsupported")
#: 证据相矛盾时正式运行怎么判档:degrade 降档(默认)/ withhold 不予出具。探索运行只标注
JUDGE_ON_UNSUPPORTED = ("degrade", "withhold")
def claims_problem(value: Any) -> str | None:
"""claims 的取值有什么问题,没问题返回 None。校验和报告撰写节点执行时报的是同一句话。"""
if value in (None, "") or (isinstance(value, str) and value in CLAIMS_VALUES):
return None
allowed = [f"「{option_label('claims', v)}」" for v in CLAIMS_VALUES]
return (f"「{field_label('claims')}」只能选{'、'.join(allowed[:-1])}或{allowed[-1]},当前为「{value}」")
def _positive(value: Any, *, integer: bool = False) -> bool:
if isinstance(value, bool) or not isinstance(value, (int, float)) or not math.isfinite(value) or value <= 0:
return False
return not integer or int(value) == value
def judge_problems(value: Any) -> list[tuple[str, str]]:
"""claims: judge 的子配置有什么问题:[(字段, 人话)],没问题返回 []。校验和节点执行时报的是同一句话。
上限写 null 就是不限(和没写不一样:没写取设置里的默认)。键写错了也报:写成 max_cost 的预算会被
悄悄当成没写、按默认值花钱。
"""
if value in (None, ""):
return []
if not isinstance(value, dict):
return [("judge", f"「{field_label('judge')}」设置格式有误,需要是一个对象"
f'(例如 {{"max_cost_usd": 0.05, "max_claims": 40}}),当前为「{value}」')]
out: list[tuple[str, str]] = []
for key, item in value.items():
field = f"judge.{key}"
if key not in JUDGE_KEYS:
known = "、".join(f"「{judge_label(k)}」" for k in JUDGE_KEYS)
out.append((field, f"「{field_label('judge')}」中无法识别「{key}」,可设置的项为:{known}"))
elif key in ("provider", "model") and item is not None and not isinstance(item, str):
what = "模型接入的名称" if key == "provider" else "模型 ID"
out.append((field, f"「{judge_label(key)}」需要填写{what},留空则使用设置中的「证据裁判」模型,"
f"当前为「{item}」"))
elif key == "max_claims" and item is not None and not _positive(item, integer=True):
out.append((field, f"「{judge_label(key)}」需要填写正整数(每份报告最多裁判的句数),或选择不限,"
f"当前为「{item}」"))
elif key == "max_cost_usd" and item is not None and not _positive(item):
out.append((field, f"「{judge_label(key)}」需要填写大于 0 的金额(每份报告的裁判费用上限),或选择不限,"
f"当前为「{item}」"))
elif key == "timeout_s" and item is not None and not _positive(item):
out.append((field, f"「{judge_label(key)}」需要填写大于 0 的秒数(每份报告的裁判时长上限),或选择不限,"
f"当前为「{item}」"))
elif key == "rewrite_once" and not isinstance(item, bool):
out.append((field, f"「{judge_label(key)}」只能是开启或关闭,当前为「{item}」"))
elif key == "on_unsupported" and item not in JUDGE_ON_UNSUPPORTED:
allowed = "或".join(f"「{option_label(key, v)}」" for v in JUDGE_ON_UNSUPPORTED)
out.append((field, f"「{judge_label(key)}」只能选{allowed},当前为「{item}」"))
return out
def _check_report_claims(node: GraphNode, spec: GraphSpec, result: ValidationResult) -> None:
"""claims 写错了挡住运行:执行时报告节点照样会报这一句,与其跑完取数、算完口径卡才死在写报告
那一步,不如在画图时说破。claims 是 judge 时再查 judge 子配置的形状;裁判模型和写作模型写成
同一个的给警告——等于自己审自己。
和运行时同一个取值规则:节点上没写就取图级 defaults(NodeContext.cfg)。
"""
def effective(key: str) -> Any:
value = node.config.get(key)
return spec.defaults.get(key) if value in (None, "") else value
value = effective("claims")
if problem := claims_problem(value):
result.add(problem, node_id=node.id, field="claims", code="report.claims_invalid")
if value != CLAIMS_JUDGE:
return
judge = effective("judge")
for field, message in judge_problems(judge):
result.add(message, node_id=node.id, field=field, code="report.judge_invalid")
judge_model = judge.get("model") if isinstance(judge, dict) else None
if isinstance(judge_model, str) and judge_model and judge_model == effective("model"):
result.add(f"裁判模型与写作模型相同(「{judge_model}」),难以发现写作模型自身的错误。"
f"请在「{field_label('judge')}」中选择另一个模型", level="warning", node_id=node.id, field="judge.model",
code="report.judge_same_model")
def contract_needs_metrics(contract: dict[str, Any]) -> bool:
"""出具契约要不要写 metrics_from(指标来自哪几张口径卡)。
旧写法按数值回指叙述,没有口径卡就无从回指,一定要写。引用模式(report_from)下,数字回指靠
报告里的引用标记:只引查询单元格(cells)的问数据图根本没有口径卡,不该逼它写;契约里列了
required / expected 指标的,指标总得有个来处,照样要写。运行时 io.py 也是这么判的。
"""
if contract.get("report_from") in (None, ""):
return True
return bool(contract.get("required") or contract.get("expected"))
def _check_report_from(node: GraphNode, report_from: Any, spec: GraphSpec,
result: ValidationResult) -> None:
"""引用模式的契约:report_from 必须是出口上游的报告撰写节点。"""
field, code = "contract.report_from", "contract.report_from_invalid"
if not isinstance(report_from, str):
result.add("出具契约的「报告来自」需要选择一个「报告撰写」节点", node_id=node.id, field=field, code=code)
return
target = spec.node_map().get(report_from)
if target is None:
result.add(f"出具契约的「报告来自」选择了「{report_from}」,但工作流中不存在这个节点",
node_id=node.id, field=field, code=code)
elif target.type != NodeType.REPORT:
result.add(f"出具契约的「报告来自」选择了「{target.title}」,它是「{type_label(target.type)}」节点,"
"不是「报告撰写」节点:出具契约只核对报告撰写节点产出的文档",
node_id=node.id, field=field, code=code)
elif report_from not in _ancestors(spec, node.id):
result.add(f"出具契约的「报告来自」选择的「{target.title}」不在该成果节点的上游:核对时这份报告还没有写出。"
"请把报告撰写节点连到成果节点之前",
node_id=node.id, field=field, code=code)
def validate_graph(spec: GraphSpec) -> ValidationResult:
"""编译前的静态检查。错误会挡住运行,警告只在画布上提示。"""
result = ValidationResult()
nodes = spec.node_map()
if not spec.nodes:
result.add("画布上还没有节点,请先从节点库拖入一个节点")
return result
# 引用完整性
for edge in spec.edges:
if edge.source not in nodes:
result.add(f"连线的起点节点「{edge.source}」不存在", edge_id=edge.id)
if edge.target not in nodes:
result.add(f"连线的终点节点「{edge.target}」不存在", edge_id=edge.id)
if not spec.entry_nodes():
result.add("找不到起始节点:每个节点都有上游连线,工作流中存在环路且没有起点")
# 节点级必填项
for node in spec.nodes:
cfg = node.config
if node.type == NodeType.BRANCH:
cases = cfg.get("cases") or []
if not cases:
result.add("「条件分支」至少需要配置一个分支条件", node_id=node.id, field="cases")
handles = {e.sourceHandle for e in spec.outgoing(node.id)}
_check_case_keys(node, cases, result)
for i, case in enumerate(cases):
key = str((case or {}).get("key") or "").strip()
if key and key != "default" and key not in handles:
result.add(
f"分支「{key}」还没有连线", level="warning", node_id=node.id,
field=f"cases[{i}].key",
)
if "default" not in handles:
result.add(
"建议为「条件分支」的「其他」出口添加连线,处理所有条件都不满足的情况",
level="warning",
node_id=node.id,
field="cases",
)
elif node.type == NodeType.TOOL:
if not cfg.get("tool"):
result.add("「调用工具」节点还没有选择工具", node_id=node.id, field="tool")
elif node.type == NodeType.SUBGRAPH:
if not cfg.get("workflow_id"):
result.add("「子工作流」节点还没有选择要嵌套的工作流", node_id=node.id,
field="workflow_id")
elif node.type == NodeType.VALIDATE:
if not cfg.get("schema"):
result.add("「结构校验」节点需要一个 JSON Schema", node_id=node.id, field="schema")
elif node.type == NodeType.METRICS:
defs = cfg.get("metrics") or []
# 钉住别的工作流里的口径卡时,指标定义运行时从那一版里取,本地不用再写
if not defs and not cfg.get("caliber_from"):
result.add("口径卡还没有定义指标", node_id=node.id, field="metrics")
for i, d in enumerate(defs):
if not d.get("id") or not d.get("expression"):
result.add(f"指标定义缺少 ID 或表达式:{d.get('id') or '(空)'}",
node_id=node.id, field=f"metrics[{i}]")
elif node.type == NodeType.REPORT:
_check_report_sources(node, spec, result)
_check_report_claims(node, spec, result)
elif node.type == NodeType.MERGE:
_check_merge(node, spec, result)
elif node.type == NodeType.OUTPUT:
contract = cfg.get("contract")
if contract and not isinstance(contract, dict):
# 字符串、列表、数字:后面的 .get 会崩,发布、发布检查、发起运行一起 500。
# 报成 error,两档发布和运行前都挡住
result.add("出具契约必须是一个 JSON 对象", node_id=node.id, field="contract",
code="contract.not_object")
elif contract and not contract.get("metrics_from") and contract_needs_metrics(contract):
result.add("出具契约缺少「指标来自」(提供指标的口径卡)",
node_id=node.id, field="contract.metrics_from", code="contract.metrics_from_missing")
if isinstance(contract, dict) and contract.get("report_from") not in (None, ""):
_check_report_from(node, contract["report_from"], spec, result)
elif node.type == NodeType.LOOP:
if not spec.outgoing(node.id):
result.add("「循环」节点没有循环体", node_id=node.id)
if node.type in (NodeType.LLM, NodeType.AGENT, NodeType.SUPERVISOR, NodeType.REPORT):
if not (cfg.get("model") or spec.defaults.get("model")):
result.add(
"没有指定模型,将使用默认模型",
level="warning",
node_id=node.id,
field="model",
)
# 表达式:用运行时同一个 parse_expression 先解析一遍。以前写错了只有跑到那一步
# 才知道——前面的步骤白跑、钱白花,报错还停在半路(开发库里四次运行死在
# "表达式里不允许出现 Set",就是条件里套了 {{ }})
from app.engine.expressions import ExpressionError, parse_expression
for node in spec.nodes:
for label, text, field in expression_fields(node):
try:
_, unwrapped, unknown = parse_expression(text)
except ExpressionError as e:
result.add(f"{label}有误:{e}(原文:{text})", node_id=node.id, field=field)
continue
if unwrapped:
result.add(
f"{label}中的 {{{{ }}}} 是多余的:这里是表达式,不是模板,"
f"已按 {'、'.join(unwrapped)} 理解", level="warning", node_id=node.id,
field=field,
)
if unknown:
result.add(
f"{label}中的 {'、'.join(unknown)} 不是可用的名称,运行时会取到空值"
"(变量需写完整路径,例如 vars.x、input.x、nodes.某节点.text)",
level="warning", node_id=node.id, field=field,
)
cfg = node.config
if node.type == NodeType.LOOP and cfg.get("mode", "foreach") == "while" \
and not str(cfg.get("condition") or "").strip():
result.add("条件循环没有设置「继续条件」,循环体不会执行", level="warning", node_id=node.id,
field="condition")
if node.type == NodeType.TRANSFORM and cfg.get("mode", "expression") == "expression" \
and not str(cfg.get("expression") or "").strip():
result.add("「数据整形」节点还没有填写表达式", node_id=node.id, field="expression")
# assign_to 拿到的是 stdout。脚本最后一行写个裸表达式不会输出(那是 notebook
# 的行为)——变量是空的,下游的循环条件一上来就不成立、成果也是空的,而整次
# 运行照样"成功"。开发库里的「测试 1」就是这样:修好条件之后跑通了,结果为空
if node.type == NodeType.CODE and cfg.get("assign_to") \
and (cfg.get("language") or "python").lower() == "python":
files = cfg.get("files")
source = "\n".join([str(cfg.get("code") or ""),
*(map(str, files.values()) if isinstance(files, dict) else ())])
if not _MAY_WRITE_STDOUT.search(source):
var = cfg["assign_to"]
result.add(
f"代码把输出交给 vars.{var},但代码中没有 print:Python 脚本最后一行的表达式"
f"不会自动输出,vars.{var} 将为空。请用 print 输出结果;如需向下游传递对象,"
"请使用 print(json.dumps(结果))", node_id=node.id, field="code",
)
_check_named_tools(spec, result)
for issue in [*text_parse_issues(spec), *evidence_issues(spec)]:
result.add(issue.message, level=issue.level, node_id=issue.node_id, field=issue.field, code=issue.code)
# 旧结构(报告是模型调用写的、问数据的答案是 agent 的原话…)能一键升级成可追溯的:只给一条建议,
# 画布上的快速修复据此打开升级预览。放在函数里导入:upgrade 反过来要用这里的 GraphSpec
from app.engine.upgrade import HINT_CODE, upgrade_hint
if hint := upgrade_hint(spec):
result.add(hint, level="info", code=HINT_CODE)
# 孤儿节点
for node in spec.nodes:
if node.type in (NodeType.INPUT, NodeType.OUTPUT):
continue
if not spec.incoming(node.id) and not spec.outgoing(node.id):
result.add("节点没有任何连线,不会被执行", level="warning", node_id=node.id)
# 变量问题也进校验结果:模板取不到值只会渲染成空字符串,不报错,
# 所以拼错一个变量名在运行时是完全静默的——只能在这里说破。
# 放在最后导入,避免 variables 反过来 import schema 形成环。
from app.engine.variables import analyze as _analyze_vars
for issue in _analyze_vars(spec).issues:
# info 级是"产出没人用"这类提示,不进校验(它不影响能不能跑)
if issue.level == "info":
continue
result.add(issue.message, level=issue.level, node_id=issue.node_id,
field=issue.field or None)
return result
# --------------------------------------------------------------------------
# 提示词点名的工具,节点得真的绑了它
#
# 一次真实运行:助手改图时把三个查库 agent 的 tools 丢了,提示词里还写着「用
# db_query__… 查」。模型拿不到工具,只能写一句「假设调用工具」,再往下编;校验节点
# 的修复又替它编了个 0。这张图在跑之前就能认出来。Copilot 的自查读的是同一份
# error,搭图时就会交回模型去修。
#
# 这条是 error,会挡住运行,还会作为 Copilot 自查的阻断项交回模型(模型可能反过来
# 把提示词里禁用的工具绑上去),所以宁可漏判不可误判:
# - 认得出的工具名才算点名:内置工具、db_query__ / db_schema__ / mcp: 这几种形状,
# 以及这张图里别的节点绑过的名字;
# - 「不要用 X」「Never call X」「X 的结果」不是在要求用它;
# - calculator 这种本身就是个普通词的工具名,只有写在反引号里、或者紧跟在「用 /
# 调用 / use / call」后面才算点名;「可以用」「如有需要」「if needed」这类非强制的
# 说法也一样。这两种只报 warning。
# --------------------------------------------------------------------------
_DYNAMIC_TOOL = r"db_(?:query|schema)__[A-Za-z0-9_\-]+|mcp:[\w\-]+/[\w\-.]+"
# 工具名紧挨着汉字是常态(「用python_exec核对」),所以边界只排 ASCII 标识符字符
_EDGE_BEFORE, _EDGE_AFTER = r"(?<![A-Za-z0-9_:/\-])", r"(?![A-Za-z0-9_\-])"
_TEMPLATE_SPAN = re.compile(r"\{\{.*?\}\}", re.S)
_NEGATED = re.compile(
r"(?:(?:不要|不用|不必|无需|无须|毋须|不需要|不再|别再|别|禁止|停止|不能|不得|不应|不可|避免|切勿|勿|严禁)"
r"\s*(?:再|去)?(?:使用|调用|用|执行|运行|跑)?"
r"|(?<![A-Za-z])(?:don['’]?t|do\s+not|never|avoid|without|must\s+not|mustn['’]?t|should\s+not"
r"|shouldn['’]?t|cannot|can['’]t|no\s+need\s+to|not|no)\s+(?:(?:use|call|invoke|run|execute|using|calling"
r"|invoking|running|rely\s+on|touch)\s+)?(?:the\s+|any\s+)?)"
r"\s*[「“\"'`]?\s*$", re.I)
_REFERENCED = re.compile(r"^\s*[」”\"'`]?\s*(的|返回|给出|查到|产出|输出|结果"
r"|(?:'s\b)|(?:results?|outputs?|returned|returns)\b)", re.I)
# 普通词形的工具名(calculator)要有明确的「用」字眼紧挨着才算点名
_PLAIN_WORD = re.compile(r"[A-Za-z][a-z]*(?:-[a-z]+)*")
_USE_VERB = re.compile(r"(?:使用|调用|用|(?<![A-Za-z])(?:use|call|invoke|run))\s*$", re.I)
# 非强制的说法:同一句里出现就只算提到,不算要求
_OPTIONAL = re.compile(r"可以|可选|如有需要|如需|若需|必要时|需要时|有需要|酌情"
r"|(?<![A-Za-z])(?:may|might|can|could|optionally|if\s+(?:needed|necessary|required)"
r"|when\s+needed|feel\s+free)(?![A-Za-z])", re.I)
_CLAUSE_END = re.compile(r"[。;;!!??\n]|\.(?:\s|$)")
# 笼统地要求用工具、却没点名
_VAGUE = re.compile(r"(调用|使用|用|借助|通过)\s*(相关|对应|可用|数据库|查询)?\s*工具"
r"|查询?数据库|查库|执行\s*SQL|跑\s*SQL", re.I)
def _bound_tools(cfg: dict[str, Any]) -> set[str]:
return {t for t in cfg.get("tools") or [] if isinstance(t, str)}
def _covers(bound: set[str], tool: str) -> bool:
"""tool 在不在 bound 里。mcp:<server>/*(或只写 mcp:<server>)绑的是这个 server 的全部工具。"""
if tool in bound:
return True
if not tool.startswith("mcp:"):
return False
server = tool[4:].partition("/")[0]
return any(b in (f"mcp:{server}", f"mcp:{server}/", f"mcp:{server}/*") for b in bound)
def _named_tool_pattern(spec: GraphSpec) -> re.Pattern[str]:
from app.tools.registry import all_specs
bound: set[str] = set()
for node in spec.nodes:
cfg = node.config
bound.update(_bound_tools(cfg))
if isinstance(cfg.get("tool"), str):
bound.add(cfg["tool"])
for member in cfg.get("agents") or []:
if isinstance(member, dict):
bound.update(_bound_tools(member))
names = sorted({*all_specs(), *bound}, key=len, reverse=True)
literal = "|".join(re.escape(n) for n in names if n)
body = f"{_DYNAMIC_TOOL}|{literal}" if literal else _DYNAMIC_TOOL
return re.compile(f"{_EDGE_BEFORE}(?:{body}){_EDGE_AFTER}")
# 列举里的分隔:「严禁调用 web_search、web_fetch、http_request 等」「never call a, b or c」
_LIST_TAIL = re.compile(r"(?:[\s、,,/和或及与跟以「」“”\"'`]|(?<![A-Za-z])(?:or|and|nor)(?![A-Za-z]))+$",
re.I)
def _negated(plain: str, start: int, pattern: re.Pattern[str]) -> bool:
"""这个工具名前面是不是一句「不要用」。列举里排在后面的也算:往回跳过前面的工具名和顿号。"""
head = plain[max(0, start - 120):start]
while True:
trimmed = _LIST_TAIL.sub("", head)
last = None
for last in pattern.finditer(trimmed):
pass
if last is not None and last.end() == len(trimmed):
trimmed = trimmed[:last.start()]
if trimmed == head:
break
head = trimmed
return bool(_NEGATED.search(head[-40:] + " "))
def _clause(plain: str, start: int, end: int) -> str:
"""工具名所在的那一句。"""
before = [m.end() for m in _CLAUSE_END.finditer(plain, 0, start)]
after = _CLAUSE_END.search(plain, end)
return plain[before[-1] if before else 0:after.start() if after else len(plain)]
def _asked_tools(text: str, pattern: re.Pattern[str]) -> dict[str, bool]:
"""文本里被要求使用的工具名,按出现顺序。值是「是不是明确要求」:否的只算提到了。"""
# {{ }} 里的是模板引用,不是在点名工具;换成等长空白,位置不变
plain = _TEMPLATE_SPAN.sub(lambda m: " " * len(m.group(0)), text)
found: dict[str, bool] = {}
for m in pattern.finditer(plain):
if _negated(plain, m.start(), pattern) or _REFERENCED.match(plain[m.end():m.end() + 12]):
continue
name = m.group(0)
explicit = not _OPTIONAL.search(_clause(plain, m.start(), m.end()))
if explicit and _PLAIN_WORD.fullmatch(name):
quoted = plain[m.start() - 1:m.start()] == "`" and plain[m.end():m.end() + 1] == "`"
explicit = quoted or bool(_USE_VERB.search(plain[max(0, m.start() - 12):m.start()]))
found[name] = found.get(name, False) or explicit
return found
def _asks_vaguely(text: str) -> bool:
plain = _TEMPLATE_SPAN.sub(" ", text)
return any(not _NEGATED.search(plain[max(0, m.start() - 12):m.start()])
for m in _VAGUE.finditer(plain))
def _check_named_tools(spec: GraphSpec, result: ValidationResult) -> None:
agents = [n for n in spec.nodes if n.type in (NodeType.AGENT, NodeType.SUPERVISOR)]
if not agents:
return
pattern = _named_tool_pattern(spec)
def check(node: GraphNode, texts: list[tuple[str, Any]], tools: Any, who: str = "") -> None:
bound = {t for t in tools or [] if isinstance(t, str)}
vague_at: str | None = None
reported: set[str] = set()
asked: dict[str, tuple[bool, str]] = {}
for field, text in texts:
if not isinstance(text, str) or not text.strip():
continue
for tool, explicit in _asked_tools(text, pattern).items():
# system 和 prompt 里都点了同一个工具,报一次就够:指到先出现的那处,
# 哪一处是明确要求就按要求算
seen = asked.get(tool)
asked[tool] = (explicit or bool(seen and seen[0]), seen[1] if seen else field)
if not bound and vague_at is None and _asks_vaguely(text):
vague_at = field
for tool, (explicit, field) in asked.items():
if _covers(bound, tool):
continue
reported.add(tool)
if explicit:
message = (f"{who}的提示词要求用「{tool}」,但没有给这个成员绑定它" if who
else f"提示词要求用「{tool}」,但节点没有绑定它")
where = "该成员的工具" if who else f"「{field_label('tools')}」"
result.add(f"{message}:运行时模型无法调用该工具,可能会编造结果。"
f"请把它加入{where},或删除提示词中的这项要求",
node_id=node.id, field=field)
else:
result.add(f"{who + '的' if who else ''}提示词提到了「{tool}」,但{'这个成员' if who else '节点'}没有"
"绑定它:如果需要模型调用它,运行时将无法调用。如有需要,请把它加入工具",
level="warning", node_id=node.id, field=field)
# 已经点名报过了,那句笼统的就不再重复
if vague_at is not None and not reported:
result.add(f"{who or '提示词'}要求调用工具,但{'这个成员' if who else '这个节点'}没有绑定任何"
"工具:模型无法调用工具,只能假设调用结果。请绑定要用的工具,或删除这项要求",
level="warning", node_id=node.id, field=vague_at)
for node in agents:
cfg = node.config
if node.type == NodeType.AGENT:
check(node, [("system", cfg.get("system")), ("prompt", cfg.get("prompt"))],
cfg.get("tools"))
continue
members = [m for m in cfg.get("agents") or [] if isinstance(m, dict)]
team_tools: set[str] = set()
for i, member in enumerate(members):
name = member.get("name") or f"agent{i}"
team_tools.update(_bound_tools(member))
check(node, [(f"agents[{i}].system", member.get("system"))], member.get("tools"),
who=f"成员「{name}」")
# 协作目标是给调度者看的:点了名的工具,至少得有一个成员拿得到
goal = cfg.get("goal")
if isinstance(goal, str):
for tool, explicit in _asked_tools(goal, pattern).items():
if _covers(team_tools, tool):
continue
if explicit:
result.add(f"团队目标要求用「{tool}」,但没有任何成员绑定该工具:调度者分派的成员"
"都无法调用它。请为负责的成员添加该工具,或删除目标中的这项要求",
node_id=node.id, field="goal")
else:
result.add(f"团队目标提到了「{tool}」,但没有任何成员绑定该工具:如果需要成员"
"调用它,目前都无法调用。如有需要,请为负责的成员添加",
level="warning", node_id=node.id, field="goal")
# --------------------------------------------------------------------------
# 不按 JSON 解析模型写的文字
#
# 真实踩过的一张图:agent(自由文字)→ transform `{{ nodes.query_logs.text }}`(按 JSON
# 解析)→ 口径卡。模型在 JSON 字符串里夹了没转义的英文引号,整形节点一解析就失败。模型写的
# 文字不是数据:数要交给口径卡,就让 agent 按 output_schema 交结构化字段、开 cite_fields
# 逐个标出处。这里只报 warning(旧工作流照跑);Copilot 自查把它当成要打回的问题。
# --------------------------------------------------------------------------
_MODEL_TEXT_TYPES = (NodeType.AGENT, NodeType.LLM, NodeType.SUPERVISOR)
_TEXT_REF = re.compile(
r"nodes\s*(?:\.\s*(?P<a>[\w-]+)|\[\s*['\"](?P<b>[^'\"]+)['\"]\s*\])"
r"\s*(?:\.\s*text(?![\w-])|\[\s*['\"]text['\"]\s*\])")
_VAR_REF = re.compile(r"vars\s*(?:\.\s*(?P<a>[\w-]+)|\[\s*['\"](?P<b>[^'\"]+)['\"]\s*\])")
def _writes_text(node: GraphNode) -> bool:
"""这个节点的产出是不是模型写的文字(而不是系统序列化的结构化数据)。
llm 配了 output_schema 走原生结构化输出,text 是系统 json.dumps 的;agent 只有同时
开了 cite_fields,assign_to 才拿到核对过的 data——它的 .text 仍然是模型的原话。
"""
if node.type == NodeType.LLM:
return not node.config.get("output_schema")
return node.type in _MODEL_TEXT_TYPES
def _text_sources(text: str, spec: GraphSpec, *, template: bool) -> list[GraphNode]:
"""一段模板(或表达式)读了哪些节点的模型原话。模板里过了 | json 的不算:那是合法的 JSON 字符串。"""
nodes = spec.node_map()
pieces = [m.group(0)[2:-2] for m in _TEMPLATE_SPAN.finditer(text)] if template else [text]
found: dict[str, GraphNode] = {}
for piece in pieces:
head, *filters = [p.strip() for p in piece.split("|")] if template else [piece]
if "json" in filters:
continue
for m in _TEXT_REF.finditer(head):
node = nodes.get(m.group("a") or m.group("b"))
if node is not None and _writes_text(node):
found.setdefault(node.id, node)
for m in _VAR_REF.finditer(head):
var = m.group("a") or m.group("b")
for node in spec.nodes:
if str(node.config.get("assign_to") or "").strip() != var or node.type not in _MODEL_TEXT_TYPES:
continue
structured = (node.type == NodeType.LLM and node.config.get("output_schema")) or (
node.type == NodeType.AGENT and node.config.get("output_schema")
and node.config.get("cite_fields") is True)
if not structured:
found.setdefault(node.id, node)
return list(found.values())
def _descendants(spec: GraphSpec, node_id: str) -> set[str]:
children: dict[str, list[str]] = defaultdict(list)
for e in spec.edges:
children[e.source].append(e.target)
seen: set[str] = set()
stack = list(children[node_id])
while stack:
cur = stack.pop()
if cur not in seen:
seen.add(cur)
stack.extend(children[cur])
seen.discard(node_id)
return seen
def _feeds_caliber(node: GraphNode, spec: GraphSpec) -> bool:
"""下游有口径卡读了这个节点的产出(nodes.<id> 或 vars.<assign_to>)。"""
var = str(node.config.get("assign_to") or "").strip()
reads = [rf"nodes\s*(?:\.\s*{re.escape(node.id)}(?![\w-])|\[\s*['\"]{re.escape(node.id)}['\"]\s*\])"]
if var:
reads.append(rf"vars\s*(?:\.\s*{re.escape(var)}(?![\w-])|\[\s*['\"]{re.escape(var)}['\"]\s*\])")
pattern = re.compile("|".join(reads))
nodes = spec.node_map()
for nid in _descendants(spec, node.id):
card = nodes.get(nid)
if card is not None and card.type == NodeType.METRICS and any(
pattern.search(str((d or {}).get("expression") or "")) for d in card.config.get("metrics") or []):
return True
return False
def _structured_fix(source: GraphNode) -> str:
if source.type == NodeType.AGENT:
var = str(source.config.get("assign_to") or "").strip() or "变量名"
return (f"为「{source.title}」配置「结构化输出 Schema」并开启「按出处核对字段」,口径卡直接读取 "
f"vars.{var}.字段(每个字段都核对到查询结果中的对应单元格)")
if source.type == NodeType.LLM:
return (f"为「{source.title}」配置「结构化输出 Schema」;数字需要进入口径卡时,请改用 Agent 并开启"
"「按出处核对字段」")
return "数字需要进入口径卡时,请改用 Agent,配置「结构化输出 Schema」并开启「按出处核对字段」"
def _json_spans(template: str) -> list[tuple[str, bool]]:
"""模板里每个 {{ }}:(里面的表达式, 它是不是落在 JSON 的引号里)。只数模板自己写的字,跳过 {{ }}。"""
out: list[tuple[str, bool]] = []
inside, last = False, 0
for m in _TEMPLATE_SPAN.finditer(template):
text, i = template[last:m.start()], 0
while i < len(text):
if inside and text[i] == "\\":
i += 2
continue
if text[i] == '"':
inside = not inside
i += 1
out.append((m.group(0)[2:-2].strip(), inside))
last = m.end()
return out
def text_parse_issues(spec: GraphSpec) -> list[ValidationIssue]:
"""整形节点解析 agent / llm 写的文字、产出流向口径卡或按 JSON 解析:一个节点一条 warning。"""
out: list[ValidationIssue] = []
for node in spec.nodes:
if node.type != NodeType.TRANSFORM:
continue
mode = node.config.get("mode", "expression")
field = "expression" if mode == "expression" else "template"
sources = _text_sources(str(node.config.get(field) or ""), spec, template=field == "template")
if not sources:
continue
who = "、".join(f"「{s.title}」({type_label(s.type)})" for s in sources[:3])
spans = [(expr, quoted) for expr, quoted in _json_spans(str(node.config.get(field) or ""))
if _text_sources(f"{{{{ {expr} }}}}", spec, template=True)] if mode == "json" else []
if spans and all(quoted for _, quoted in spans):
# 模型的文字放在模板的引号里:不是在解析它,是在拼字符串,少的是 | json
expr = spans[0][0]
message = (f"模板中的 {{{{ {expr} }}}} 位于 JSON 引号内:{who}写的文字只要包含英文引号或换行,JSON 就会"
f"格式错误,导致整个节点失败。请改写为 {{{{ {expr} | json }}}}(外面不要再加引号)")
elif mode == "json":
message = (f"「数据整形」节点按 JSON 解析{who}写的文字:模型写的 JSON 常含有未转义的英文引号,一旦解析失败,"
f"整个节点就会失败。请改为让它直接输出结构化数据:{_structured_fix(sources[0])}")
elif _feeds_caliber(node, spec):
message = (f"口径卡的数字需要经过这个「数据整形」节点,从{who}写的文字中提取:文字不是结构化数据,提取不可靠,"
f"也无法追溯出处。{_structured_fix(sources[0])}")
else:
continue
out.append(ValidationIssue(level="warning", node_id=node.id, field=field, message=message))
return out
# --------------------------------------------------------------------------
# 证据链相关的配置:agent 的结构化字段、沙箱代码的角色、钉住别处的口径卡
# --------------------------------------------------------------------------
EVIDENCE_ROLES = ("source", "compute")
_REF_HEAD = re.compile(r"^(vars|nodes)\.([\w-]+)")
def _caliber_inputs(card: GraphNode, spec: GraphSpec) -> list[tuple[int, GraphNode]]:
"""口径卡每个指标表达式里读到的节点:(指标下标, 产出它的节点)。"""
from app.engine.expressions import ExpressionError, leaf_refs, parse_expression
nodes = spec.node_map()
out: list[tuple[int, GraphNode]] = []
for i, d in enumerate(card.config.get("metrics") or []):
try:
tree, _, _ = parse_expression(str((d or {}).get("expression") or ""))
except ExpressionError:
continue
for path in leaf_refs(tree):
m = _REF_HEAD.match(path.split("cell(", 1)[-1].lstrip())
if not m:
continue
root, name = m.groups()
if root == "nodes":
producers = [nodes[name]] if name in nodes else []
else:
producers = [n for n in spec.nodes if str(n.config.get("assign_to") or "").strip() == name]
out.extend((i, n) for n in producers)
return out
def evidence_issues(spec: GraphSpec) -> list[ValidationIssue]:
from app.engine.governance import UPGRADE_POLICIES, UPGRADE_POLICY_LABELS
out: list[ValidationIssue] = []
def add(message: str, node: GraphNode, field: str, level: str = "warning", code: str | None = None) -> None:
out.append(ValidationIssue(level=level, node_id=node.id, field=field, message=message, # type: ignore[arg-type]
code=code))
for node in spec.nodes:
cfg = node.config
if node.type == NodeType.AGENT and cfg.get("output_schema") and cfg.get("cite_fields") is not True:
add("「结构化输出 Schema」需要同时开启「按出处核对字段」才会生效(会多一次抽取调用):开启后,Agent 执行"
"结束时按 Schema 抽取字段,每个字段都核对到查询结果中的对应单元格;不开启时,「结果存为变量」得到的"
"仍是自由文本",
node, "output_schema", code="evidence.cite_fields_off")
elif node.type == NodeType.CODE:
role = cfg.get("evidence_role")
if role not in (None, "") and role not in EVIDENCE_ROLES:
add(f"「证据角色」只能是「取数」或「计算」,当前为「{role}」", node,
"evidence_role", level="error")
elif node.type == NodeType.METRICS:
if cfg.get("caliber_from") not in (None, "", {}):
out.extend(_caliber_from_issues(node, UPGRADE_POLICIES, UPGRADE_POLICY_LABELS))
warned: set[str] = set()
for i, producer in _caliber_inputs(node, spec):
role = str(producer.config.get("evidence_role") or "compute")
if producer.type != NodeType.CODE or role == "source" or producer.id in warned:
continue
warned.add(producer.id)
add(f"口径卡的输入来自沙箱代码「{producer.title}」,它的「证据角色」是「计算」:沙箱中计算出的数字"
"无法追溯出处。负责取数的代码节点请将「证据角色」设为「取数」;业务计算请移到口径卡的表达式中",
node, f"metrics[{i}].expression",
code="evidence.caliber_compute_input")
return out
def _caliber_from_issues(node: GraphNode, policies: set[str], labels: dict[str, str]) -> list[ValidationIssue]:
"""钉住别的工作流里一张口径卡:{workflow_id, workflow_version, node_id} 三项都要写对。"""
cfg = node.config
ref = cfg.get("caliber_from")
out: list[ValidationIssue] = []
def add(message: str, field: str, level: str = "error") -> None:
out.append(ValidationIssue(level=level, node_id=node.id, field=field, message=message)) # type: ignore[arg-type]
if not isinstance(ref, dict) or not str(ref.get("workflow_id") or "").strip() \
or not str(ref.get("node_id") or "").strip():
add(f"「{field_label('caliber_from')}」需要选定工作流、版本和其中的口径卡", "caliber_from")
return out
version = ref.get("workflow_version")
if isinstance(version, bool) or not (isinstance(version, int) or (isinstance(version, str) and version.isdigit())) \
or int(version) < 1:
add(f"「{field_label('caliber_from')}」需要选择具体的版本号(1、2…),当前为「{version}」:不固定版本,"
"口径会随上游变化", "caliber_from.workflow_version")
if cfg.get("metrics"):
add(f"已设置「{field_label('caliber_from')}」,将按所引用的口径卡计算,此处填写的「{field_label('metrics')}」"
"不会生效", "metrics", level="warning")
policy = cfg.get("upgrade_policy")
if policy not in (None, "") and policy not in policies:
allowed = [f"「{v}」" for v in labels.values()]
add(f"「{field_label('upgrade_policy')}」只能选{'、'.join(allowed[:-1])}或{allowed[-1]},当前为「{policy}」",
"upgrade_policy")
return out