mirror of
https://github.com/langgenius/dify.git
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356 lines
13 KiB
Python
356 lines
13 KiB
Python
import json
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import logging
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from collections.abc import Generator, Mapping, Sequence
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from typing import TYPE_CHECKING, Any
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from core.app.entities.app_invoke_entities import InvokeFrom
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from core.repositories.human_input_repository import HumanInputFormRepositoryImpl
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from dify_graph.entities.pause_reason import HumanInputRequired
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from dify_graph.enums import NodeExecutionType, NodeType, WorkflowNodeExecutionStatus
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from dify_graph.node_events import (
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HumanInputFormFilledEvent,
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HumanInputFormTimeoutEvent,
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NodeRunResult,
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PauseRequestedEvent,
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)
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from dify_graph.node_events.base import NodeEventBase
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from dify_graph.node_events.node import StreamCompletedEvent
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from dify_graph.nodes.base.node import Node
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from dify_graph.repositories.human_input_form_repository import (
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FormCreateParams,
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HumanInputFormEntity,
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HumanInputFormRepository,
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)
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from dify_graph.workflow_type_encoder import WorkflowRuntimeTypeConverter
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from extensions.ext_database import db
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from libs.datetime_utils import naive_utc_now
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from .entities import DeliveryChannelConfig, HumanInputNodeData, apply_debug_email_recipient
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from .enums import DeliveryMethodType, HumanInputFormStatus, PlaceholderType
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if TYPE_CHECKING:
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from dify_graph.entities.graph_init_params import GraphInitParams
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from dify_graph.runtime.graph_runtime_state import GraphRuntimeState
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_SELECTED_BRANCH_KEY = "selected_branch"
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logger = logging.getLogger(__name__)
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class HumanInputNode(Node[HumanInputNodeData]):
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node_type = NodeType.HUMAN_INPUT
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execution_type = NodeExecutionType.BRANCH
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_BRANCH_SELECTION_KEYS: tuple[str, ...] = (
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"edge_source_handle",
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"edgeSourceHandle",
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"source_handle",
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_SELECTED_BRANCH_KEY,
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"selectedBranch",
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"branch",
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"branch_id",
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"branchId",
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"handle",
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)
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_node_data: HumanInputNodeData
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_form_repository: HumanInputFormRepository
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_OUTPUT_FIELD_ACTION_ID = "__action_id"
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_OUTPUT_FIELD_RENDERED_CONTENT = "__rendered_content"
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_TIMEOUT_HANDLE = _TIMEOUT_ACTION_ID = "__timeout"
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def __init__(
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self,
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id: str,
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config: Mapping[str, Any],
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graph_init_params: "GraphInitParams",
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graph_runtime_state: "GraphRuntimeState",
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form_repository: HumanInputFormRepository | None = None,
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) -> None:
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super().__init__(
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id=id,
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config=config,
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graph_init_params=graph_init_params,
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graph_runtime_state=graph_runtime_state,
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)
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if form_repository is None:
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form_repository = HumanInputFormRepositoryImpl(
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session_factory=db.engine,
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tenant_id=self.tenant_id,
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)
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self._form_repository = form_repository
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@classmethod
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def version(cls) -> str:
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return "1"
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def _resolve_branch_selection(self) -> str | None:
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"""Determine the branch handle selected by human input if available."""
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variable_pool = self.graph_runtime_state.variable_pool
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for key in self._BRANCH_SELECTION_KEYS:
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handle = self._extract_branch_handle(variable_pool.get((self.id, key)))
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if handle:
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return handle
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default_values = self.node_data.default_value_dict
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for key in self._BRANCH_SELECTION_KEYS:
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handle = self._normalize_branch_value(default_values.get(key))
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if handle:
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return handle
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return None
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@staticmethod
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def _extract_branch_handle(segment: Any) -> str | None:
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if segment is None:
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return None
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candidate = getattr(segment, "to_object", None)
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raw_value = candidate() if callable(candidate) else getattr(segment, "value", None)
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if raw_value is None:
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return None
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return HumanInputNode._normalize_branch_value(raw_value)
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@staticmethod
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def _normalize_branch_value(value: Any) -> str | None:
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if value is None:
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return None
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if isinstance(value, str):
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stripped = value.strip()
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return stripped or None
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if isinstance(value, Mapping):
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for key in ("handle", "edge_source_handle", "edgeSourceHandle", "branch", "id", "value"):
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candidate = value.get(key)
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if isinstance(candidate, str) and candidate:
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return candidate
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return None
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@property
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def _workflow_execution_id(self) -> str:
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workflow_exec_id = self.graph_runtime_state.variable_pool.system_variables.workflow_execution_id
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assert workflow_exec_id is not None
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return workflow_exec_id
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def _form_to_pause_event(self, form_entity: HumanInputFormEntity):
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required_event = self._human_input_required_event(form_entity)
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pause_requested_event = PauseRequestedEvent(reason=required_event)
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return pause_requested_event
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def resolve_default_values(self) -> Mapping[str, Any]:
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variable_pool = self.graph_runtime_state.variable_pool
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resolved_defaults: dict[str, Any] = {}
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for input in self._node_data.inputs:
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if (default_value := input.default) is None:
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continue
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if default_value.type == PlaceholderType.CONSTANT:
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continue
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resolved_value = variable_pool.get(default_value.selector)
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if resolved_value is None:
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# TODO: How should we handle this?
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continue
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resolved_defaults[input.output_variable_name] = (
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WorkflowRuntimeTypeConverter().value_to_json_encodable_recursive(resolved_value.value)
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)
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return resolved_defaults
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def _should_require_console_recipient(self) -> bool:
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if self.invoke_from == InvokeFrom.DEBUGGER:
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return True
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if self.invoke_from == InvokeFrom.EXPLORE:
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return self._node_data.is_webapp_enabled()
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return False
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def _display_in_ui(self) -> bool:
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if self.invoke_from == InvokeFrom.DEBUGGER:
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return True
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return self._node_data.is_webapp_enabled()
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def _effective_delivery_methods(self) -> Sequence[DeliveryChannelConfig]:
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enabled_methods = [method for method in self._node_data.delivery_methods if method.enabled]
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if self.invoke_from in {InvokeFrom.DEBUGGER, InvokeFrom.EXPLORE}:
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enabled_methods = [method for method in enabled_methods if method.type != DeliveryMethodType.WEBAPP]
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return [
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apply_debug_email_recipient(
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method,
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enabled=self.invoke_from == InvokeFrom.DEBUGGER,
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user_id=self.user_id or "",
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)
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for method in enabled_methods
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]
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def _human_input_required_event(self, form_entity: HumanInputFormEntity) -> HumanInputRequired:
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node_data = self._node_data
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resolved_default_values = self.resolve_default_values()
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display_in_ui = self._display_in_ui()
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form_token = form_entity.web_app_token
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if display_in_ui and form_token is None:
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raise AssertionError("Form token should be available for UI execution.")
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return HumanInputRequired(
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form_id=form_entity.id,
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form_content=form_entity.rendered_content,
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inputs=node_data.inputs,
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actions=node_data.user_actions,
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display_in_ui=display_in_ui,
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node_id=self.id,
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node_title=node_data.title,
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form_token=form_token,
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resolved_default_values=resolved_default_values,
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)
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def _run(self) -> Generator[NodeEventBase, None, None]:
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"""
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Execute the human input node.
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This method will:
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1. Generate a unique form ID
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2. Create form content with variable substitution
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3. Create form in database
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4. Send form via configured delivery methods
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5. Suspend workflow execution
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6. Wait for form submission to resume
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"""
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repo = self._form_repository
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form = repo.get_form(self._workflow_execution_id, self.id)
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if form is None:
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display_in_ui = self._display_in_ui()
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params = FormCreateParams(
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app_id=self.app_id,
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workflow_execution_id=self._workflow_execution_id,
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node_id=self.id,
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form_config=self._node_data,
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rendered_content=self.render_form_content_before_submission(),
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delivery_methods=self._effective_delivery_methods(),
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display_in_ui=display_in_ui,
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resolved_default_values=self.resolve_default_values(),
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console_recipient_required=self._should_require_console_recipient(),
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console_creator_account_id=(
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self.user_id if self.invoke_from in {InvokeFrom.DEBUGGER, InvokeFrom.EXPLORE} else None
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),
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backstage_recipient_required=True,
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)
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form_entity = self._form_repository.create_form(params)
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# Create human input required event
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logger.info(
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"Human Input node suspended workflow for form. workflow_run_id=%s, node_id=%s, form_id=%s",
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self.graph_runtime_state.variable_pool.system_variables.workflow_execution_id,
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self.id,
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form_entity.id,
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)
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yield self._form_to_pause_event(form_entity)
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return
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if (
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form.status in {HumanInputFormStatus.TIMEOUT, HumanInputFormStatus.EXPIRED}
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or form.expiration_time <= naive_utc_now()
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):
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yield HumanInputFormTimeoutEvent(
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node_title=self._node_data.title,
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expiration_time=form.expiration_time,
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)
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yield StreamCompletedEvent(
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node_run_result=NodeRunResult(
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status=WorkflowNodeExecutionStatus.SUCCEEDED,
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outputs={self._OUTPUT_FIELD_ACTION_ID: ""},
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edge_source_handle=self._TIMEOUT_HANDLE,
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)
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)
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return
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if not form.submitted:
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yield self._form_to_pause_event(form)
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return
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selected_action_id = form.selected_action_id
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if selected_action_id is None:
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raise AssertionError(f"selected_action_id should not be None when form submitted, form_id={form.id}")
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submitted_data = form.submitted_data or {}
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outputs: dict[str, Any] = dict(submitted_data)
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outputs[self._OUTPUT_FIELD_ACTION_ID] = selected_action_id
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rendered_content = self.render_form_content_with_outputs(
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form.rendered_content,
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outputs,
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self._node_data.outputs_field_names(),
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)
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outputs[self._OUTPUT_FIELD_RENDERED_CONTENT] = rendered_content
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action_text = self._node_data.find_action_text(selected_action_id)
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yield HumanInputFormFilledEvent(
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node_title=self._node_data.title,
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rendered_content=rendered_content,
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action_id=selected_action_id,
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action_text=action_text,
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)
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yield StreamCompletedEvent(
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node_run_result=NodeRunResult(
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status=WorkflowNodeExecutionStatus.SUCCEEDED,
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outputs=outputs,
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edge_source_handle=selected_action_id,
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)
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)
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def render_form_content_before_submission(self) -> str:
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"""
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Process form content by substituting variables.
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This method should:
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1. Parse the form_content markdown
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2. Substitute {{#node_name.var_name#}} with actual values
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3. Keep {{#$output.field_name#}} placeholders for form inputs
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"""
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rendered_form_content = self.graph_runtime_state.variable_pool.convert_template(
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self._node_data.form_content,
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)
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return rendered_form_content.markdown
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@staticmethod
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def render_form_content_with_outputs(
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form_content: str,
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outputs: Mapping[str, Any],
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field_names: Sequence[str],
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) -> str:
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"""
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Replace {{#$output.xxx#}} placeholders with submitted values.
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"""
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rendered_content = form_content
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for field_name in field_names:
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placeholder = "{{#$output." + field_name + "#}}"
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value = outputs.get(field_name)
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if value is None:
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replacement = ""
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elif isinstance(value, (dict, list)):
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replacement = json.dumps(value, ensure_ascii=False)
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else:
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replacement = str(value)
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rendered_content = rendered_content.replace(placeholder, replacement)
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return rendered_content
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@classmethod
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def _extract_variable_selector_to_variable_mapping(
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cls,
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*,
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graph_config: Mapping[str, Any],
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node_id: str,
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node_data: Mapping[str, Any],
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) -> Mapping[str, Sequence[str]]:
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"""
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Extract variable selectors referenced in form content and input default values.
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This method should parse:
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1. Variables referenced in form_content ({{#node_name.var_name#}})
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2. Variables referenced in input default values
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"""
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validated_node_data = HumanInputNodeData.model_validate(node_data)
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return validated_node_data.extract_variable_selector_to_variable_mapping(node_id)
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