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dify/api/services/dify_builder/graph_ops.py
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Charles YaoandClaude Opus 5 7e82ab20d9 fix(dify-builder): walk dotted paths in apply_set_node_config
apply_set_node_config wrote node["data"][path] as a flat key, so every
dotted path the repair agent emits (cases.0.conditions.1.value) created a
junk key the workflow engine ignores. The dry run passed, the change set
printed a plausible line, and the graph never changed -- which is why
ESQ1-285 survived nine approvals and ESQ1-290 six.

Paths now resolve through lists and mappings, and an unwalkable path
raises. Raising is half the fix: filter_applicable dry-runs intents
through the real apply_* and feeds rejection reasons back to the repair
agent, so a bad path now produces corrective feedback instead of a
silent no-op.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-09-20 22:09:25 -07:00

423 lines
18 KiB
Python

"""Pure, client-side graph mutation helpers.
Dify's ``sync_draft_workflow`` has no server-side patch primitive: it always
replaces the whole draft graph. The adapter (``dify_port.py``) therefore
reads the current graph, applies mutations like ``apply_set_node_config``
locally, and writes the whole mutated graph back. These helpers do the local
mutation only — no DB, no services, no I/O.
"""
import copy
import hashlib
import json
from typing import Any
from core.dify_builder.models import Graph, MutationIntent
MUTATION_ARG_KEYS: dict[str, tuple[str, ...]] = {
"set_node_config": ("node_id", "path", "value"),
"create_node": ("node_type", "config"),
"delete_node": ("node_id",),
"connect": ("from_node", "to_node"),
"insert_between": ("edge", "node_type", "config"),
}
def validate_intent_args(intent: MutationIntent) -> None:
"""Raise ``ValueError`` if ``intent.args`` is missing a required key for
``intent.op``, or if ``intent.op`` isn't one of ``MUTATION_ARG_KEYS``'s
five recognized verbs. Optional keys (marked ``?`` on ``MutationIntent``)
are not checked here -- each ``apply_*`` function defaults them itself.
"""
required = MUTATION_ARG_KEYS.get(intent.op)
if required is None:
raise ValueError(f"unknown mutation op: {intent.op!r}")
missing = [key for key in required if key not in intent.args]
if missing:
raise ValueError(f"missing required arg(s) {missing} for op {intent.op!r}")
def _resolve_path(container: dict[str, Any], path: str) -> tuple[Any, str | int]:
"""Walk ``path``'s parent segments and return ``(parent, last_key)``.
Segments are dot-separated; an all-digit segment indexes a list, any
other segment is a mapping key. Only the FINAL segment may be absent --
that is the key being written. Every intermediate segment must already
resolve, and a segment that cannot be walked raises ``ValueError``.
Raising is the point. ``filter_applicable`` dry-runs each intent through
this function and turns the exception into a rejection reason the repair
agent sees on its next attempt. Before this existed, a dotted path wrote
one flat junk key that the workflow engine ignored, so every nested
repair silently did nothing (ESQ1-285, ESQ1-290).
"""
segments = path.split(".")
if not path or any(segment == "" for segment in segments):
raise ValueError(f"empty segment in path: {path!r}")
cursor: Any = container
for depth, segment in enumerate(segments[:-1]):
walked = ".".join(segments[: depth + 1])
if segment.isdigit():
if not isinstance(cursor, list):
raise ValueError(f"path {path!r}: {walked} indexes a {type(cursor).__name__}, not a list")
index = int(segment)
if index >= len(cursor):
raise ValueError(f"path {path!r}: index {index} out of range at {walked} (len {len(cursor)})")
cursor = cursor[index]
continue
if not isinstance(cursor, dict):
raise ValueError(f"path {path!r}: {walked} is not a mapping")
if segment not in cursor:
raise ValueError(f"path {path!r}: no key {segment!r} at {walked}")
cursor = cursor[segment]
last = segments[-1]
if last.isdigit():
if not isinstance(cursor, list):
raise ValueError(f"path {path!r}: final segment indexes a {type(cursor).__name__}, not a list")
index = int(last)
if index >= len(cursor):
raise ValueError(f"path {path!r}: index {index} out of range (len {len(cursor)})")
return cursor, index
if not isinstance(cursor, dict):
raise ValueError(f"path {path!r}: final container is a {type(cursor).__name__}, not a mapping")
return cursor, last
def apply_set_node_config(graph: Graph, node_id: str, path: str, value: Any) -> tuple[Graph, list[str]]:
"""Set the value at ``path`` inside ``node["data"]`` for the node whose
``id == node_id``. ``path`` is dot-separated (``"code"``,
``"cases.0.conditions.1.value"``); see ``_resolve_path``.
The placeholder agent emits intents shaped ``{node_id, path, value}``
(e.g. ``path="code"`` to rewrite a Code node's ``data["code"]``); this is
the mutation that consumes them.
Returns a ``(new_graph, changed_node_ids)`` tuple. ``graph`` is
deep-copied first and never mutated. Raises ``ValueError`` if no node in
``graph["nodes"]`` has a matching ``id``.
"""
new_graph = copy.deepcopy(graph)
for node in new_graph.get("nodes", []):
if node.get("id") == node_id:
parent, key = _resolve_path(node.setdefault("data", {}), path)
parent[key] = value
return new_graph, [node_id]
raise ValueError(f"node not found: {node_id}")
def _next_unique_id(base: str, existing_ids: set) -> str:
"""Return ``base`` if unused, else ``base_2``, ``base_3``, ... on
collision with ``existing_ids``. Shared bump sequence for node ids
(``_next_node_id``) and edge ids (``_make_edge``)."""
candidate = base
suffix = 1
while candidate in existing_ids:
suffix += 1
candidate = f"{base}_{suffix}"
return candidate
def _next_node_id(prefix: str, existing_ids: set) -> str:
"""Return a short, human-readable node id not present in ``existing_ids``.
Mirrors ``core.workflow.generator.runner._next_generated_node_id``'s
prefix, then prefix_2, prefix_3, ... collision scheme -- reimplemented
locally so this module stays free of any dependency on the generator
subsystem.
"""
return _next_unique_id(prefix, existing_ids)
def _default_position(graph: Graph) -> dict[str, float]:
"""Place a new node to the right of the rightmost existing node.
Slice 1 uses simple deterministic rightward placement, not the
generator's topology-aware layout (``_layout_top_level_nodes``) --
good enough for one node at a time; a smarter layout is Slice 2/3's
concern if the canvas ever needs it.
"""
nodes = graph.get("nodes", [])
if not nodes:
return {"x": 100.0, "y": 100.0}
max_x = max(float(n.get("position", {}).get("x", 0.0)) for n in nodes)
return {"x": max_x + 260.0, "y": 100.0}
def _build_node(
graph: Graph,
node_type: str,
config: dict[str, Any],
position: dict[str, float] | None,
node_id: str | None,
) -> dict[str, Any]:
"""Construct one ``GraphNodeDict``-shaped node, generating an id/position
when omitted (mirrors the generator's ``_fill_node_defaults``,
``core/workflow/generator/runner.py:2387-2394``). Raises ``ValueError``
if a caller-supplied ``node_id`` already exists in ``graph["nodes"]``.
"""
existing_ids = {n.get("id") for n in graph.get("nodes", [])}
if node_id is not None:
if node_id in existing_ids:
raise ValueError(f"node id already exists: {node_id}")
new_id = node_id
else:
new_id = _next_node_id(node_type, existing_ids)
data = copy.deepcopy(config)
data["type"] = node_type # data.type is the real node type -- never overridden by config
data.setdefault("title", new_id)
data.setdefault("desc", "")
data.setdefault("selected", False)
return {
"id": new_id,
"type": "custom",
"position": position if position is not None else _default_position(graph),
"data": data,
}
def apply_create_node(
graph: Graph,
node_type: str,
config: dict[str, Any],
position: dict[str, float] | None = None,
node_id: str | None = None,
) -> tuple[Graph, list[str]]:
"""Append a new ``GraphNodeDict``-shaped node to the graph.
``node_id`` is optional (not part of spec Sec 9's terse args list) --
when omitted a short id is generated from ``node_type``; when supplied,
a collision with an existing node id raises ``ValueError`` (the Slice 1
duplicate-id validation). Returns ``(new_graph, [new_node_id])``.
"""
new_graph = copy.deepcopy(graph)
node = _build_node(new_graph, node_type, config, position, node_id)
new_graph.setdefault("nodes", []).append(node)
return new_graph, [node["id"]]
def apply_delete_node(graph: Graph, node_id: str) -> tuple[Graph, list[str]]:
"""Remove the node with ``id == node_id`` and every edge touching it.
Raises ``ValueError`` if no node in ``graph["nodes"]`` has a matching
``id`` (mirrors ``apply_set_node_config``'s not-found behavior).
Returns ``(new_graph, [node_id])``.
"""
new_graph = copy.deepcopy(graph)
nodes = new_graph.get("nodes", [])
if not any(n.get("id") == node_id for n in nodes):
raise ValueError(f"node not found: {node_id}")
new_graph["nodes"] = [n for n in nodes if n.get("id") != node_id]
new_graph["edges"] = [
e for e in new_graph.get("edges", []) if e.get("source") != node_id and e.get("target") != node_id
]
return new_graph, [node_id]
def _make_edge(
source: str, target: str, source_handle: str | None, target_handle: str | None, existing_edge_ids: set
) -> dict:
"""Build one ``GraphEdgeDict``-shaped edge dict with a fresh
collision-free id (``source-target``, then ``source-target_2``, ... on
collision with ``existing_edge_ids``). Handles default to
"source"/"target" (mirrors the generator's ``_fill_edge_defaults``)."""
return {
"id": _next_unique_id(f"{source}-{target}", existing_edge_ids),
"source": source,
"target": target,
"type": "custom",
"sourceHandle": source_handle or "source",
"targetHandle": target_handle or "target",
}
def apply_connect(
graph: Graph,
from_node: str,
to_node: str,
source_handle: str | None = None,
target_handle: str | None = None,
) -> tuple[Graph, list[str]]:
"""Add a ``GraphEdgeDict``-shaped edge between two existing nodes.
Raises ``ValueError`` if either ``from_node`` or ``to_node`` is not a
node id present in ``graph["nodes"]`` (the Slice 1 dangling-ref
validation). Handles default to "source"/"target" (mirrors the
generator's ``_fill_edge_defaults``). Returns
``(new_graph, [from_node, to_node])``.
"""
new_graph = copy.deepcopy(graph)
node_ids = {n.get("id") for n in new_graph.get("nodes", [])}
if from_node not in node_ids:
raise ValueError(f"node not found: {from_node}")
if to_node not in node_ids:
raise ValueError(f"node not found: {to_node}")
existing_edge_ids = {e.get("id") for e in new_graph.get("edges", [])}
edge = _make_edge(from_node, to_node, source_handle, target_handle, existing_edge_ids)
new_graph.setdefault("edges", []).append(edge)
return new_graph, [from_node, to_node]
def apply_insert_between(
graph: Graph,
edge: dict[str, str],
node_type: str,
config: dict[str, Any],
position: dict[str, float] | None = None,
node_id: str | None = None,
) -> tuple[Graph, list[str]]:
"""Split an existing edge with a new node: remove the old edge, add
``old_source -> new_node`` and ``new_node -> old_target``.
``edge`` identifies the edge to split by ``{"source": ..., "target": ...}``
(matching Dify's own edge fields, not a caller-known internal edge id).
Raises ``ValueError`` if no edge in ``graph["edges"]`` matches (the
Slice 1 dangling-ref validation). Returns ``(new_graph, [new_node_id])``.
"""
old_source = edge.get("source")
old_target = edge.get("target")
new_graph = copy.deepcopy(graph)
edges = new_graph.get("edges", [])
matched = next((e for e in edges if e.get("source") == old_source and e.get("target") == old_target), None)
if matched is None:
raise ValueError(f"edge not found: {old_source} -> {old_target}")
node = _build_node(new_graph, node_type, config, position, node_id)
new_id = node["id"]
new_graph.setdefault("nodes", []).append(node)
remaining_edges = [e for e in edges if e is not matched]
existing_edge_ids = {e.get("id") for e in remaining_edges}
incoming = _make_edge(old_source, new_id, matched.get("sourceHandle"), "target", existing_edge_ids)
existing_edge_ids.add(incoming["id"])
outgoing = _make_edge(new_id, old_target, "source", matched.get("targetHandle"), existing_edge_ids)
new_graph["edges"] = [*remaining_edges, incoming, outgoing]
return new_graph, [new_id]
def diff_graphs(before: Graph, after: Graph) -> tuple[list[str], str]:
"""Compare two graphs and return ``(changes, scope)``.
``scope`` is ``"structure"`` if any node or edge was added or removed,
else ``"configuration"`` if any surviving node's ``data`` changed, else
``"configuration"`` with an empty ``changes`` list if nothing differs.
``changes`` is human-readable lines (e.g. ``"added node knowledge-1"``,
``"added knowledge-1 → llm-1"``, ``"llm-1: prompt_template updated"``)
-- not bare ids.
"""
before_nodes = {n.get("id"): n for n in before.get("nodes", []) if n.get("id")}
after_nodes = {n.get("id"): n for n in after.get("nodes", []) if n.get("id")}
def _edge_key(e: dict[str, Any]) -> tuple[str, str, str, str]:
return (
str(e.get("source")),
str(e.get("target")),
str(e.get("sourceHandle") or "source"),
str(e.get("targetHandle") or "target"),
)
before_edges = {_edge_key(e) for e in before.get("edges", [])}
after_edges = {_edge_key(e) for e in after.get("edges", [])}
added_nodes = sorted(after_nodes.keys() - before_nodes.keys())
removed_nodes = sorted(before_nodes.keys() - after_nodes.keys())
added_edges = sorted(after_edges - before_edges)
removed_edges = sorted(before_edges - after_edges)
changes: list[str] = []
changes.extend(f"added node {node_id}" for node_id in added_nodes)
changes.extend(f"removed node {node_id}" for node_id in removed_nodes)
changes.extend(f"added {source} → {target}" for source, target, _sh, _th in added_edges)
changes.extend(f"removed {source} → {target}" for source, target, _sh, _th in removed_edges)
for node_id in sorted(before_nodes.keys() & after_nodes.keys()):
before_data = before_nodes[node_id].get("data", {})
after_data = after_nodes[node_id].get("data", {})
changed_keys = sorted(
key for key in set(before_data) | set(after_data) if before_data.get(key) != after_data.get(key)
)
changes.extend(f"{node_id}: {key} updated" for key in changed_keys)
structural = bool(added_nodes or removed_nodes or added_edges or removed_edges)
return changes, "structure" if structural else "configuration"
def structural_fingerprint(graph: Graph) -> str:
"""Stable hash of a graph's STRUCTURE only -- node identity+type and edge
topology -- EXCLUDING node ``data`` config. Two graphs with the same
nodes/edges but different node configs share a fingerprint; adding,
removing, or reconnecting a node changes it. Used by recovery (C-1) to
tell a config-only hand-edit from a structural one. Order-independent
(nodes and edges are sorted before hashing)."""
nodes = sorted((str(n.get("id", "")), str((n.get("data") or {}).get("type", ""))) for n in graph.get("nodes", []))
edges = sorted(
(
str(e.get("source", "")),
str(e.get("target", "")),
str(e.get("sourceHandle", "")),
str(e.get("targetHandle", "")),
)
for e in graph.get("edges", [])
)
canonical = json.dumps({"nodes": nodes, "edges": edges}, sort_keys=True, separators=(",", ":"))
return hashlib.sha256(canonical.encode("utf-8")).hexdigest()
def node_ids(graph: Graph) -> list[str]:
"""The ids of every node in ``graph``, in document order (missing-id
nodes skipped). Used by recovery's target-presence check."""
return [str(n["id"]) for n in graph.get("nodes", []) if n.get("id") is not None]
STRUCTURAL_OPS: frozenset[str] = frozenset({"create_node", "delete_node", "connect", "insert_between"})
APPLY_FNS: dict[str, Any] = {
"set_node_config": apply_set_node_config,
"create_node": apply_create_node,
"delete_node": apply_delete_node,
"connect": apply_connect,
"insert_between": apply_insert_between,
}
def filter_applicable(
graph: Graph,
intents: list[MutationIntent],
allowed_node_types: set[str] | None = None,
) -> tuple[list[MutationIntent], list[tuple[MutationIntent, str]]]:
"""Dry-run each intent through the real validate_intent_args + apply_* on a
working deep copy, in order (so a connect sees a node an earlier create_node
added). Returns (applicable, rejected) where each rejected entry is
(intent, reason).
Catches every failure the live apply_repair would hit -- unknown op, missing
required arg / extra arg key, dangling node/edge ref, duplicate id -- and
additionally rejects a create_node / insert_between whose node_type is not in
allowed_node_types (a check apply_* does not do). Applicable intents advance
the working copy; a rejected intent does not.
"""
working = copy.deepcopy(graph)
applicable: list[MutationIntent] = []
rejected: list[tuple[MutationIntent, str]] = []
for intent in intents:
try:
validate_intent_args(intent)
if allowed_node_types is not None and intent.op in ("create_node", "insert_between"):
node_type = intent.args.get("node_type")
if node_type not in allowed_node_types:
rejected.append((intent, f"node_type not allowed: {node_type!r}"))
continue
working, _changed = APPLY_FNS[intent.op](working, **intent.args)
except Exception as exc:
rejected.append((intent, str(exc)))
continue
applicable.append(intent)
return applicable, rejected