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10b738a296
This pull request introduces a feature aimed at improving the debugging experience during workflow editing. With the addition of variable persistence, the system will automatically retain the output variables from previously executed nodes. These persisted variables can then be reused when debugging subsequent nodes, eliminating the need for repetitive manual input. By streamlining this aspect of the workflow, the feature minimizes user errors and significantly reduces debugging effort, offering a smoother and more efficient experience. Key highlights of this change: - Automatic persistence of output variables for executed nodes. - Reuse of persisted variables to simplify input steps for nodes requiring them (e.g., `code`, `template`, `variable_assigner`). - Enhanced debugging experience with reduced friction. Closes #19735.
315 lines
11 KiB
Python
315 lines
11 KiB
Python
import dataclasses
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import json
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from unittest import mock
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from uuid import uuid4
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from constants import HIDDEN_VALUE
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from core.file.enums import FileTransferMethod, FileType
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from core.file.models import File
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from core.variables import FloatVariable, IntegerVariable, SecretVariable, StringVariable
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from core.variables.segments import IntegerSegment, Segment
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from factories.variable_factory import build_segment
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from models.workflow import Workflow, WorkflowDraftVariable, WorkflowNodeExecutionModel, is_system_variable_editable
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def test_environment_variables():
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# tenant_id context variable removed - using current_user.current_tenant_id directly
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# Create a Workflow instance
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workflow = Workflow(
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tenant_id="tenant_id",
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app_id="app_id",
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type="workflow",
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version="draft",
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graph="{}",
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features="{}",
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created_by="account_id",
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environment_variables=[],
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conversation_variables=[],
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)
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# Create some EnvironmentVariable instances
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variable1 = StringVariable.model_validate(
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{"name": "var1", "value": "value1", "id": str(uuid4()), "selector": ["env", "var1"]}
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)
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variable2 = IntegerVariable.model_validate(
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{"name": "var2", "value": 123, "id": str(uuid4()), "selector": ["env", "var2"]}
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)
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variable3 = SecretVariable.model_validate(
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{"name": "var3", "value": "secret", "id": str(uuid4()), "selector": ["env", "var3"]}
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)
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variable4 = FloatVariable.model_validate(
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{"name": "var4", "value": 3.14, "id": str(uuid4()), "selector": ["env", "var4"]}
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)
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# Mock current_user as an EndUser
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mock_user = mock.Mock()
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mock_user.tenant_id = "tenant_id"
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with (
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mock.patch("core.helper.encrypter.encrypt_token", return_value="encrypted_token"),
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mock.patch("core.helper.encrypter.decrypt_token", return_value="secret"),
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mock.patch("models.workflow.current_user", mock_user),
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):
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# Set the environment_variables property of the Workflow instance
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variables = [variable1, variable2, variable3, variable4]
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workflow.environment_variables = variables
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# Get the environment_variables property and assert its value
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assert workflow.environment_variables == variables
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def test_update_environment_variables():
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# tenant_id context variable removed - using current_user.current_tenant_id directly
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# Create a Workflow instance
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workflow = Workflow(
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tenant_id="tenant_id",
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app_id="app_id",
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type="workflow",
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version="draft",
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graph="{}",
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features="{}",
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created_by="account_id",
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environment_variables=[],
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conversation_variables=[],
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)
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# Create some EnvironmentVariable instances
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variable1 = StringVariable.model_validate(
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{"name": "var1", "value": "value1", "id": str(uuid4()), "selector": ["env", "var1"]}
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)
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variable2 = IntegerVariable.model_validate(
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{"name": "var2", "value": 123, "id": str(uuid4()), "selector": ["env", "var2"]}
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)
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variable3 = SecretVariable.model_validate(
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{"name": "var3", "value": "secret", "id": str(uuid4()), "selector": ["env", "var3"]}
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)
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variable4 = FloatVariable.model_validate(
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{"name": "var4", "value": 3.14, "id": str(uuid4()), "selector": ["env", "var4"]}
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)
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# Mock current_user as an EndUser
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mock_user = mock.Mock()
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mock_user.tenant_id = "tenant_id"
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with (
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mock.patch("core.helper.encrypter.encrypt_token", return_value="encrypted_token"),
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mock.patch("core.helper.encrypter.decrypt_token", return_value="secret"),
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mock.patch("models.workflow.current_user", mock_user),
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):
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variables = [variable1, variable2, variable3, variable4]
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# Set the environment_variables property of the Workflow instance
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workflow.environment_variables = variables
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assert workflow.environment_variables == [variable1, variable2, variable3, variable4]
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# Update the name of variable3 and keep the value as it is
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variables[2] = variable3.model_copy(
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update={
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"name": "new name",
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"value": HIDDEN_VALUE,
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}
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)
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workflow.environment_variables = variables
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assert workflow.environment_variables[2].name == "new name"
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assert workflow.environment_variables[2].value == variable3.value
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def test_to_dict():
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# tenant_id context variable removed - using current_user.current_tenant_id directly
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# Create a Workflow instance
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workflow = Workflow(
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tenant_id="tenant_id",
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app_id="app_id",
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type="workflow",
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version="draft",
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graph="{}",
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features="{}",
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created_by="account_id",
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environment_variables=[],
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conversation_variables=[],
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)
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# Create some EnvironmentVariable instances
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# Mock current_user as an EndUser
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mock_user = mock.Mock()
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mock_user.tenant_id = "tenant_id"
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with (
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mock.patch("core.helper.encrypter.encrypt_token", return_value="encrypted_token"),
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mock.patch("core.helper.encrypter.decrypt_token", return_value="secret"),
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mock.patch("models.workflow.current_user", mock_user),
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):
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# Set the environment_variables property of the Workflow instance
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workflow.environment_variables = [
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SecretVariable.model_validate({"name": "secret", "value": "secret", "id": str(uuid4())}),
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StringVariable.model_validate({"name": "text", "value": "text", "id": str(uuid4())}),
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]
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workflow_dict = workflow.to_dict()
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assert workflow_dict["environment_variables"][0]["value"] == ""
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assert workflow_dict["environment_variables"][1]["value"] == "text"
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workflow_dict = workflow.to_dict(include_secret=True)
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assert workflow_dict["environment_variables"][0]["value"] == "secret"
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assert workflow_dict["environment_variables"][1]["value"] == "text"
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class TestWorkflowNodeExecution:
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def test_execution_metadata_dict(self):
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node_exec = WorkflowNodeExecutionModel()
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node_exec.execution_metadata = None
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assert node_exec.execution_metadata_dict == {}
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original = {"a": 1, "b": ["2"]}
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node_exec.execution_metadata = json.dumps(original)
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assert node_exec.execution_metadata_dict == original
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class TestIsSystemVariableEditable:
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def test_is_system_variable(self):
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cases = [
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("query", True),
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("files", True),
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("dialogue_count", False),
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("conversation_id", False),
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("user_id", False),
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("app_id", False),
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("workflow_id", False),
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("workflow_run_id", False),
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]
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for name, editable in cases:
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assert editable == is_system_variable_editable(name)
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assert is_system_variable_editable("invalid_or_new_system_variable") == False
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class TestWorkflowDraftVariableGetValue:
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def test_get_value_by_case(self):
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@dataclasses.dataclass
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class TestCase:
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name: str
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value: Segment
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tenant_id = "test_tenant_id"
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test_file = File(
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tenant_id=tenant_id,
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type=FileType.IMAGE,
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transfer_method=FileTransferMethod.REMOTE_URL,
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remote_url="https://example.com/example.jpg",
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filename="example.jpg",
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extension=".jpg",
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mime_type="image/jpeg",
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size=100,
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)
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cases: list[TestCase] = [
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TestCase(
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name="number/int",
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value=build_segment(1),
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),
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TestCase(
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name="number/float",
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value=build_segment(1.0),
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),
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TestCase(
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name="string",
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value=build_segment("a"),
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),
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TestCase(
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name="object",
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value=build_segment({}),
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),
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TestCase(
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name="file",
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value=build_segment(test_file),
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),
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TestCase(
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name="array[any]",
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value=build_segment([1, "a"]),
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),
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TestCase(
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name="array[string]",
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value=build_segment(["a", "b"]),
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),
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TestCase(
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name="array[number]/int",
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value=build_segment([1, 2]),
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),
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TestCase(
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name="array[number]/float",
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value=build_segment([1.0, 2.0]),
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),
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TestCase(
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name="array[number]/mixed",
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value=build_segment([1, 2.0]),
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),
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TestCase(
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name="array[object]",
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value=build_segment([{}, {"a": 1}]),
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),
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TestCase(
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name="none",
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value=build_segment(None),
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),
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]
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for idx, c in enumerate(cases, 1):
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fail_msg = f"test case {c.name} failed, index={idx}"
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draft_var = WorkflowDraftVariable()
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draft_var.set_value(c.value)
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assert c.value == draft_var.get_value(), fail_msg
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def test_file_variable_preserves_all_fields(self):
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"""Test that File type variables preserve all fields during encoding/decoding."""
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tenant_id = "test_tenant_id"
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# Create a File with specific field values
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test_file = File(
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id="test_file_id",
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tenant_id=tenant_id,
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type=FileType.IMAGE,
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transfer_method=FileTransferMethod.REMOTE_URL,
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remote_url="https://example.com/test.jpg",
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filename="test.jpg",
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extension=".jpg",
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mime_type="image/jpeg",
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size=12345, # Specific size to test preservation
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storage_key="test_storage_key",
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)
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# Create a FileSegment and WorkflowDraftVariable
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file_segment = build_segment(test_file)
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draft_var = WorkflowDraftVariable()
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draft_var.set_value(file_segment)
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# Retrieve the value and verify all fields are preserved
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retrieved_segment = draft_var.get_value()
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retrieved_file = retrieved_segment.value
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# Verify all important fields are preserved
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assert retrieved_file.id == test_file.id
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assert retrieved_file.tenant_id == test_file.tenant_id
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assert retrieved_file.type == test_file.type
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assert retrieved_file.transfer_method == test_file.transfer_method
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assert retrieved_file.remote_url == test_file.remote_url
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assert retrieved_file.filename == test_file.filename
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assert retrieved_file.extension == test_file.extension
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assert retrieved_file.mime_type == test_file.mime_type
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assert retrieved_file.size == test_file.size # This was the main issue being fixed
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# Note: storage_key is not serialized in model_dump() so it won't be preserved
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# Verify the segments have the same type and the important fields match
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assert file_segment.value_type == retrieved_segment.value_type
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def test_get_and_set_value(self):
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draft_var = WorkflowDraftVariable()
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int_var = IntegerSegment(value=1)
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draft_var.set_value(int_var)
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value = draft_var.get_value()
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assert value == int_var
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