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