mirror of https://github.com/langgenius/dify.git
test(graph_engine): remove outdated tests
Signed-off-by: -LAN- <laipz8200@outlook.com>
This commit is contained in:
-LAN-
parent
55085a9ca2
commit
635eff2e25
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@ -21,7 +21,6 @@ from .test_mock_config import MockConfigBuilder
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from .test_table_runner import TableTestRunner, WorkflowTestCase
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@pytest.mark.skip
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class TestComplexBranchWorkflow:
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"""Test suite for complex branch workflow with parallel execution."""
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@ -30,6 +29,7 @@ class TestComplexBranchWorkflow:
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self.runner = TableTestRunner()
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self.fixture_path = "test_complex_branch"
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@pytest.mark.skip(reason="output in this workflow can be random")
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def test_hello_branch_with_llm(self):
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"""
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Test when query contains 'hello' - should trigger true branch.
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@ -12,7 +12,7 @@ This module provides a robust table-driven testing framework with support for:
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import logging
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import time
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from collections.abc import Callable
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from collections.abc import Callable, Sequence
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from concurrent.futures import ThreadPoolExecutor, as_completed
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from dataclasses import dataclass, field
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from pathlib import Path
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@ -34,7 +34,11 @@ from core.workflow.entities.graph_init_params import GraphInitParams
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from core.workflow.graph import Graph
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from core.workflow.graph_engine import GraphEngine
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from core.workflow.graph_engine.command_channels import InMemoryChannel
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from core.workflow.graph_events import GraphEngineEvent, GraphRunStartedEvent, GraphRunSucceededEvent
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from core.workflow.graph_events import (
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GraphEngineEvent,
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GraphRunStartedEvent,
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GraphRunSucceededEvent,
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)
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from core.workflow.nodes.node_factory import DifyNodeFactory
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from core.workflow.system_variable import SystemVariable
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from models.enums import UserFrom
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@ -57,7 +61,7 @@ class WorkflowTestCase:
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timeout: float = 30.0
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mock_config: Optional[MockConfig] = None
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use_auto_mock: bool = False
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expected_event_sequence: Optional[list[type[GraphEngineEvent]]] = None
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expected_event_sequence: Optional[Sequence[type[GraphEngineEvent]]] = None
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tags: list[str] = field(default_factory=list)
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skip: bool = False
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skip_reason: str = ""
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@ -9,13 +9,6 @@ from core.workflow.nodes.template_transform.template_transform_node import Templ
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from .test_table_runner import TableTestRunner, WorkflowTestCase
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def mock_template_transform_run(self):
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"""Mock the TemplateTransformNode._run() method to return results based on node title."""
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title = self._node_data.title
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return NodeRunResult(status=WorkflowNodeExecutionStatus.SUCCEEDED, inputs={}, outputs={"output": title})
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@pytest.mark.skip
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class TestVariableAggregator:
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"""Test cases for the variable aggregator workflow."""
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@ -37,6 +30,12 @@ class TestVariableAggregator:
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description: str,
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) -> None:
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"""Test all four combinations of switch1 and switch2."""
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def mock_template_transform_run(self):
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"""Mock the TemplateTransformNode._run() method to return results based on node title."""
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title = self._node_data.title
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return NodeRunResult(status=WorkflowNodeExecutionStatus.SUCCEEDED, inputs={}, outputs={"output": title})
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with patch.object(
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TemplateTransformNode,
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"_run",
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@ -1,353 +0,0 @@
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import httpx
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import pytest
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from core.app.entities.app_invoke_entities import InvokeFrom
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from core.file import File, FileTransferMethod, FileType
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from core.variables import ArrayFileVariable, FileVariable
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from core.workflow.entities import GraphInitParams, GraphRuntimeState, VariablePool
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from core.workflow.enums import WorkflowNodeExecutionStatus
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from core.workflow.graph import Graph
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from core.workflow.nodes.answer.entities import AnswerStreamGenerateRoute
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from core.workflow.nodes.end.entities import EndStreamParam
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from core.workflow.nodes.http_request import (
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BodyData,
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HttpRequestNode,
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HttpRequestNodeAuthorization,
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HttpRequestNodeBody,
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HttpRequestNodeData,
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)
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from core.workflow.system_variable import SystemVariable
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from models.enums import UserFrom
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@pytest.mark.skip(
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reason="HTTP request tests use old Graph constructor incompatible with new queue-based engine - "
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"needs rewrite for new architecture"
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)
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def test_http_request_node_binary_file(monkeypatch):
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data = HttpRequestNodeData(
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title="test",
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method="post",
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url="http://example.org/post",
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authorization=HttpRequestNodeAuthorization(type="no-auth"),
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headers="",
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params="",
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body=HttpRequestNodeBody(
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type="binary",
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data=[
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BodyData(
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key="file",
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type="file",
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value="",
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file=["1111", "file"],
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)
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],
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),
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)
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variable_pool = VariablePool(
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system_variables=SystemVariable.empty(),
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user_inputs={},
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)
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variable_pool.add(
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["1111", "file"],
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FileVariable(
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name="file",
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value=File(
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tenant_id="1",
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type=FileType.IMAGE,
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transfer_method=FileTransferMethod.LOCAL_FILE,
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related_id="1111",
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storage_key="",
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),
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),
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)
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node_config = {
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"id": "1",
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"data": data.model_dump(),
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}
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node = HttpRequestNode(
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id="1",
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config=node_config,
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graph_init_params=GraphInitParams(
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tenant_id="1",
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app_id="1",
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workflow_id="1",
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graph_config={},
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user_id="1",
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user_from=UserFrom.ACCOUNT,
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invoke_from=InvokeFrom.SERVICE_API,
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call_depth=0,
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),
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graph=Graph(
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root_node_id="1",
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answer_stream_generate_routes=AnswerStreamGenerateRoute(
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answer_dependencies={},
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answer_generate_route={},
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),
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end_stream_param=EndStreamParam(
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end_dependencies={},
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end_stream_variable_selector_mapping={},
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),
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),
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graph_runtime_state=GraphRuntimeState(
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variable_pool=variable_pool,
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start_at=0,
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),
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)
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# Initialize node data
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node.init_node_data(node_config["data"])
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monkeypatch.setattr(
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"core.workflow.nodes.http_request.executor.file_manager.download",
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lambda *args, **kwargs: b"test",
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)
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monkeypatch.setattr(
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"core.helper.ssrf_proxy.post",
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lambda *args, **kwargs: httpx.Response(200, content=kwargs["content"]),
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)
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result = node._run()
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assert result.status == WorkflowNodeExecutionStatus.SUCCEEDED
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assert result.outputs is not None
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assert result.outputs["body"] == "test"
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@pytest.mark.skip(
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reason="HTTP request tests use old Graph constructor incompatible with new queue-based engine - "
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"needs rewrite for new architecture"
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)
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def test_http_request_node_form_with_file(monkeypatch):
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data = HttpRequestNodeData(
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title="test",
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method="post",
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url="http://example.org/post",
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authorization=HttpRequestNodeAuthorization(type="no-auth"),
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headers="",
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params="",
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body=HttpRequestNodeBody(
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type="form-data",
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data=[
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BodyData(
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key="file",
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type="file",
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file=["1111", "file"],
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),
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BodyData(
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key="name",
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type="text",
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value="test",
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),
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],
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),
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)
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variable_pool = VariablePool(
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system_variables=SystemVariable.empty(),
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user_inputs={},
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)
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variable_pool.add(
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["1111", "file"],
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FileVariable(
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name="file",
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value=File(
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tenant_id="1",
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type=FileType.IMAGE,
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transfer_method=FileTransferMethod.LOCAL_FILE,
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related_id="1111",
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storage_key="",
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),
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),
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)
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node_config = {
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"id": "1",
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"data": data.model_dump(),
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}
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node = HttpRequestNode(
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id="1",
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config=node_config,
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graph_init_params=GraphInitParams(
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tenant_id="1",
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app_id="1",
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workflow_id="1",
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graph_config={},
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user_id="1",
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user_from=UserFrom.ACCOUNT,
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invoke_from=InvokeFrom.SERVICE_API,
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call_depth=0,
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),
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graph=Graph(
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root_node_id="1",
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answer_stream_generate_routes=AnswerStreamGenerateRoute(
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answer_dependencies={},
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answer_generate_route={},
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),
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end_stream_param=EndStreamParam(
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end_dependencies={},
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end_stream_variable_selector_mapping={},
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),
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),
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graph_runtime_state=GraphRuntimeState(
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variable_pool=variable_pool,
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start_at=0,
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),
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)
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# Initialize node data
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node.init_node_data(node_config["data"])
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monkeypatch.setattr(
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"core.workflow.nodes.http_request.executor.file_manager.download",
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lambda *args, **kwargs: b"test",
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)
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def attr_checker(*args, **kwargs):
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assert kwargs["data"] == {"name": "test"}
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assert kwargs["files"] == [("file", (None, b"test", "application/octet-stream"))]
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return httpx.Response(200, content=b"")
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monkeypatch.setattr(
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"core.helper.ssrf_proxy.post",
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attr_checker,
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)
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result = node._run()
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assert result.status == WorkflowNodeExecutionStatus.SUCCEEDED
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assert result.outputs is not None
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assert result.outputs["body"] == ""
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@pytest.mark.skip(
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reason="HTTP request tests use old Graph constructor incompatible with new queue-based engine - "
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"needs rewrite for new architecture"
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)
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def test_http_request_node_form_with_multiple_files(monkeypatch):
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data = HttpRequestNodeData(
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title="test",
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method="post",
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url="http://example.org/upload",
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authorization=HttpRequestNodeAuthorization(type="no-auth"),
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headers="",
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params="",
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body=HttpRequestNodeBody(
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type="form-data",
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data=[
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BodyData(
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key="files",
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type="file",
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file=["1111", "files"],
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),
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BodyData(
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key="name",
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type="text",
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value="test",
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),
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],
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),
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)
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variable_pool = VariablePool(
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system_variables=SystemVariable.empty(),
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user_inputs={},
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)
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files = [
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File(
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tenant_id="1",
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type=FileType.IMAGE,
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transfer_method=FileTransferMethod.LOCAL_FILE,
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related_id="file1",
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filename="image1.jpg",
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mime_type="image/jpeg",
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storage_key="",
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),
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File(
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tenant_id="1",
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type=FileType.DOCUMENT,
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transfer_method=FileTransferMethod.LOCAL_FILE,
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related_id="file2",
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filename="document.pdf",
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mime_type="application/pdf",
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storage_key="",
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),
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]
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variable_pool.add(
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["1111", "files"],
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ArrayFileVariable(
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name="files",
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value=files,
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),
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)
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node_config = {
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"id": "1",
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"data": data.model_dump(),
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}
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node = HttpRequestNode(
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id="1",
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config=node_config,
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graph_init_params=GraphInitParams(
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tenant_id="1",
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app_id="1",
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workflow_id="1",
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graph_config={},
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user_id="1",
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user_from=UserFrom.ACCOUNT,
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invoke_from=InvokeFrom.SERVICE_API,
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call_depth=0,
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),
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graph=Graph(
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root_node_id="1",
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answer_stream_generate_routes=AnswerStreamGenerateRoute(
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answer_dependencies={},
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answer_generate_route={},
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),
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end_stream_param=EndStreamParam(
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end_dependencies={},
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end_stream_variable_selector_mapping={},
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),
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),
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graph_runtime_state=GraphRuntimeState(
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variable_pool=variable_pool,
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start_at=0,
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),
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)
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# Initialize node data
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node.init_node_data(node_config["data"])
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monkeypatch.setattr(
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"core.workflow.nodes.http_request.executor.file_manager.download",
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lambda file: b"test_image_data" if file.mime_type == "image/jpeg" else b"test_pdf_data",
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)
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def attr_checker(*args, **kwargs):
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assert kwargs["data"] == {"name": "test"}
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assert len(kwargs["files"]) == 2
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assert kwargs["files"][0][0] == "files"
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assert kwargs["files"][1][0] == "files"
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file_tuples = [f[1] for f in kwargs["files"]]
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file_contents = [f[1] for f in file_tuples]
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file_types = [f[2] for f in file_tuples]
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assert b"test_image_data" in file_contents
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assert b"test_pdf_data" in file_contents
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assert "image/jpeg" in file_types
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assert "application/pdf" in file_types
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return httpx.Response(200, content=b'{"status":"success"}')
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monkeypatch.setattr(
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"core.helper.ssrf_proxy.post",
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attr_checker,
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)
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result = node._run()
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assert result.status == WorkflowNodeExecutionStatus.SUCCEEDED
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assert result.outputs is not None
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assert result.outputs["body"] == '{"status":"success"}'
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print(result.outputs["body"])
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@ -1,909 +0,0 @@
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import time
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import uuid
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from unittest.mock import patch
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import pytest
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from core.app.entities.app_invoke_entities import InvokeFrom
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from core.variables.segments import ArrayAnySegment, ArrayStringSegment
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from core.workflow.entities import GraphInitParams, GraphRuntimeState, VariablePool
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from core.workflow.enums import WorkflowNodeExecutionStatus
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from core.workflow.graph import Graph
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from core.workflow.node_events import NodeRunResult, StreamCompletedEvent
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from core.workflow.nodes.iteration.entities import ErrorHandleMode
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from core.workflow.nodes.iteration.iteration_node import IterationNode
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from core.workflow.nodes.node_factory import DifyNodeFactory
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from core.workflow.nodes.template_transform.template_transform_node import TemplateTransformNode
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from core.workflow.system_variable import SystemVariable
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from models.enums import UserFrom
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@pytest.mark.skip(
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reason="Iteration nodes are part of Phase 3 container support - not yet implemented in new queue-based engine"
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)
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def test_run():
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graph_config = {
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"edges": [
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{
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"id": "start-source-pe-target",
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"source": "start",
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"target": "pe",
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},
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{
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"id": "iteration-1-source-answer-3-target",
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"source": "iteration-1",
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"target": "answer-3",
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},
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{
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"id": "tt-source-if-else-target",
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"source": "tt",
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"target": "if-else",
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},
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{
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"id": "if-else-true-answer-2-target",
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"source": "if-else",
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"sourceHandle": "true",
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"target": "answer-2",
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},
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{
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"id": "if-else-false-answer-4-target",
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"source": "if-else",
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"sourceHandle": "false",
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"target": "answer-4",
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},
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{
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"id": "pe-source-iteration-1-target",
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"source": "pe",
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"target": "iteration-1",
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},
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],
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"nodes": [
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{"data": {"title": "Start", "type": "start", "variables": []}, "id": "start"},
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{
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"data": {
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"iterator_selector": ["pe", "list_output"],
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"output_selector": ["tt", "output"],
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"output_type": "array[string]",
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"startNodeType": "template-transform",
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"start_node_id": "tt",
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"title": "iteration",
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"type": "iteration",
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},
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"id": "iteration-1",
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},
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{
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"data": {
|
||||
"answer": "{{#tt.output#}}",
|
||||
"iteration_id": "iteration-1",
|
||||
"title": "answer 2",
|
||||
"type": "answer",
|
||||
},
|
||||
"id": "answer-2",
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"iteration_id": "iteration-1",
|
||||
"template": "{{ arg1 }} 123",
|
||||
"title": "template transform",
|
||||
"type": "template-transform",
|
||||
"variables": [{"value_selector": ["sys", "query"], "variable": "arg1"}],
|
||||
},
|
||||
"id": "tt",
|
||||
},
|
||||
{
|
||||
"data": {"answer": "{{#iteration-1.output#}}88888", "title": "answer 3", "type": "answer"},
|
||||
"id": "answer-3",
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"conditions": [
|
||||
{
|
||||
"comparison_operator": "is",
|
||||
"id": "1721916275284",
|
||||
"value": "hi",
|
||||
"variable_selector": ["sys", "query"],
|
||||
}
|
||||
],
|
||||
"iteration_id": "iteration-1",
|
||||
"logical_operator": "and",
|
||||
"title": "if",
|
||||
"type": "if-else",
|
||||
},
|
||||
"id": "if-else",
|
||||
},
|
||||
{
|
||||
"data": {"answer": "no hi", "iteration_id": "iteration-1", "title": "answer 4", "type": "answer"},
|
||||
"id": "answer-4",
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"instruction": "test1",
|
||||
"model": {
|
||||
"completion_params": {"temperature": 0.7},
|
||||
"mode": "chat",
|
||||
"name": "gpt-4o",
|
||||
"provider": "openai",
|
||||
},
|
||||
"parameters": [
|
||||
{"description": "test", "name": "list_output", "required": False, "type": "array[string]"}
|
||||
],
|
||||
"query": ["sys", "query"],
|
||||
"reasoning_mode": "prompt",
|
||||
"title": "pe",
|
||||
"type": "parameter-extractor",
|
||||
},
|
||||
"id": "pe",
|
||||
},
|
||||
],
|
||||
}
|
||||
|
||||
init_params = GraphInitParams(
|
||||
tenant_id="1",
|
||||
app_id="1",
|
||||
workflow_id="1",
|
||||
graph_config=graph_config,
|
||||
user_id="1",
|
||||
user_from=UserFrom.ACCOUNT,
|
||||
invoke_from=InvokeFrom.DEBUGGER,
|
||||
call_depth=0,
|
||||
)
|
||||
|
||||
# construct variable pool
|
||||
pool = VariablePool(
|
||||
system_variables=SystemVariable(
|
||||
user_id="1",
|
||||
files=[],
|
||||
query="dify",
|
||||
conversation_id="abababa",
|
||||
),
|
||||
user_inputs={},
|
||||
environment_variables=[],
|
||||
)
|
||||
pool.add(["pe", "list_output"], ["dify-1", "dify-2"])
|
||||
|
||||
graph_runtime_state = GraphRuntimeState(variable_pool=pool, start_at=time.perf_counter())
|
||||
node_factory = DifyNodeFactory(
|
||||
graph_init_params=init_params,
|
||||
graph_runtime_state=graph_runtime_state,
|
||||
)
|
||||
graph = Graph.init(graph_config=graph_config, node_factory=node_factory)
|
||||
|
||||
node_config = {
|
||||
"data": {
|
||||
"iterator_selector": ["pe", "list_output"],
|
||||
"output_selector": ["tt", "output"],
|
||||
"output_type": "array[string]",
|
||||
"startNodeType": "template-transform",
|
||||
"start_node_id": "tt",
|
||||
"title": "迭代",
|
||||
"type": "iteration",
|
||||
},
|
||||
"id": "iteration-1",
|
||||
}
|
||||
|
||||
iteration_node = IterationNode(
|
||||
id=str(uuid.uuid4()),
|
||||
graph_init_params=init_params,
|
||||
graph_runtime_state=graph_runtime_state,
|
||||
config=node_config,
|
||||
)
|
||||
|
||||
# Initialize node data
|
||||
iteration_node.init_node_data(node_config["data"])
|
||||
|
||||
def tt_generator(self):
|
||||
return NodeRunResult(
|
||||
status=WorkflowNodeExecutionStatus.SUCCEEDED,
|
||||
inputs={"iterator_selector": "dify"},
|
||||
outputs={"output": "dify 123"},
|
||||
)
|
||||
|
||||
with patch.object(TemplateTransformNode, "_run", new=tt_generator):
|
||||
# execute node
|
||||
result = iteration_node._run()
|
||||
|
||||
count = 0
|
||||
for item in result:
|
||||
# print(type(item), item)
|
||||
count += 1
|
||||
if isinstance(item, StreamCompletedEvent):
|
||||
assert item.node_run_result.status == WorkflowNodeExecutionStatus.SUCCEEDED
|
||||
assert item.node_run_result.outputs == {"output": ArrayStringSegment(value=["dify 123", "dify 123"])}
|
||||
|
||||
assert count == 20
|
||||
|
||||
|
||||
@pytest.mark.skip(
|
||||
reason="Iteration nodes are part of Phase 3 container support - not yet implemented in new queue-based engine"
|
||||
)
|
||||
def test_run_parallel():
|
||||
graph_config = {
|
||||
"edges": [
|
||||
{
|
||||
"id": "start-source-pe-target",
|
||||
"source": "start",
|
||||
"target": "pe",
|
||||
},
|
||||
{
|
||||
"id": "iteration-1-source-answer-3-target",
|
||||
"source": "iteration-1",
|
||||
"target": "answer-3",
|
||||
},
|
||||
{
|
||||
"id": "iteration-start-source-tt-target",
|
||||
"source": "iteration-start",
|
||||
"target": "tt",
|
||||
},
|
||||
{
|
||||
"id": "iteration-start-source-tt-2-target",
|
||||
"source": "iteration-start",
|
||||
"target": "tt-2",
|
||||
},
|
||||
{
|
||||
"id": "tt-source-if-else-target",
|
||||
"source": "tt",
|
||||
"target": "if-else",
|
||||
},
|
||||
{
|
||||
"id": "tt-2-source-if-else-target",
|
||||
"source": "tt-2",
|
||||
"target": "if-else",
|
||||
},
|
||||
{
|
||||
"id": "if-else-true-answer-2-target",
|
||||
"source": "if-else",
|
||||
"sourceHandle": "true",
|
||||
"target": "answer-2",
|
||||
},
|
||||
{
|
||||
"id": "if-else-false-answer-4-target",
|
||||
"source": "if-else",
|
||||
"sourceHandle": "false",
|
||||
"target": "answer-4",
|
||||
},
|
||||
{
|
||||
"id": "pe-source-iteration-1-target",
|
||||
"source": "pe",
|
||||
"target": "iteration-1",
|
||||
},
|
||||
],
|
||||
"nodes": [
|
||||
{"data": {"title": "Start", "type": "start", "variables": []}, "id": "start"},
|
||||
{
|
||||
"data": {
|
||||
"iterator_selector": ["pe", "list_output"],
|
||||
"output_selector": ["tt", "output"],
|
||||
"output_type": "array[string]",
|
||||
"startNodeType": "template-transform",
|
||||
"start_node_id": "iteration-start",
|
||||
"title": "iteration",
|
||||
"type": "iteration",
|
||||
},
|
||||
"id": "iteration-1",
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"answer": "{{#tt.output#}}",
|
||||
"iteration_id": "iteration-1",
|
||||
"title": "answer 2",
|
||||
"type": "answer",
|
||||
},
|
||||
"id": "answer-2",
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"iteration_id": "iteration-1",
|
||||
"title": "iteration-start",
|
||||
"type": "iteration-start",
|
||||
},
|
||||
"id": "iteration-start",
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"iteration_id": "iteration-1",
|
||||
"template": "{{ arg1 }} 123",
|
||||
"title": "template transform",
|
||||
"type": "template-transform",
|
||||
"variables": [{"value_selector": ["sys", "query"], "variable": "arg1"}],
|
||||
},
|
||||
"id": "tt",
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"iteration_id": "iteration-1",
|
||||
"template": "{{ arg1 }} 321",
|
||||
"title": "template transform",
|
||||
"type": "template-transform",
|
||||
"variables": [{"value_selector": ["sys", "query"], "variable": "arg1"}],
|
||||
},
|
||||
"id": "tt-2",
|
||||
},
|
||||
{
|
||||
"data": {"answer": "{{#iteration-1.output#}}88888", "title": "answer 3", "type": "answer"},
|
||||
"id": "answer-3",
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"conditions": [
|
||||
{
|
||||
"comparison_operator": "is",
|
||||
"id": "1721916275284",
|
||||
"value": "hi",
|
||||
"variable_selector": ["sys", "query"],
|
||||
}
|
||||
],
|
||||
"iteration_id": "iteration-1",
|
||||
"logical_operator": "and",
|
||||
"title": "if",
|
||||
"type": "if-else",
|
||||
},
|
||||
"id": "if-else",
|
||||
},
|
||||
{
|
||||
"data": {"answer": "no hi", "iteration_id": "iteration-1", "title": "answer 4", "type": "answer"},
|
||||
"id": "answer-4",
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"instruction": "test1",
|
||||
"model": {
|
||||
"completion_params": {"temperature": 0.7},
|
||||
"mode": "chat",
|
||||
"name": "gpt-4o",
|
||||
"provider": "openai",
|
||||
},
|
||||
"parameters": [
|
||||
{"description": "test", "name": "list_output", "required": False, "type": "array[string]"}
|
||||
],
|
||||
"query": ["sys", "query"],
|
||||
"reasoning_mode": "prompt",
|
||||
"title": "pe",
|
||||
"type": "parameter-extractor",
|
||||
},
|
||||
"id": "pe",
|
||||
},
|
||||
],
|
||||
}
|
||||
|
||||
init_params = GraphInitParams(
|
||||
tenant_id="1",
|
||||
app_id="1",
|
||||
workflow_id="1",
|
||||
graph_config=graph_config,
|
||||
user_id="1",
|
||||
user_from=UserFrom.ACCOUNT,
|
||||
invoke_from=InvokeFrom.DEBUGGER,
|
||||
call_depth=0,
|
||||
)
|
||||
|
||||
# construct variable pool
|
||||
pool = VariablePool(
|
||||
system_variables=SystemVariable(
|
||||
user_id="1",
|
||||
files=[],
|
||||
query="dify",
|
||||
conversation_id="abababa",
|
||||
),
|
||||
user_inputs={},
|
||||
environment_variables=[],
|
||||
)
|
||||
|
||||
graph_runtime_state = GraphRuntimeState(variable_pool=pool, start_at=time.perf_counter())
|
||||
node_factory = DifyNodeFactory(
|
||||
graph_init_params=init_params,
|
||||
graph_runtime_state=graph_runtime_state,
|
||||
)
|
||||
graph = Graph.init(graph_config=graph_config, node_factory=node_factory)
|
||||
pool.add(["pe", "list_output"], ["dify-1", "dify-2"])
|
||||
|
||||
node_config = {
|
||||
"data": {
|
||||
"iterator_selector": ["pe", "list_output"],
|
||||
"output_selector": ["tt", "output"],
|
||||
"output_type": "array[string]",
|
||||
"startNodeType": "template-transform",
|
||||
"start_node_id": "iteration-start",
|
||||
"title": "迭代",
|
||||
"type": "iteration",
|
||||
},
|
||||
"id": "iteration-1",
|
||||
}
|
||||
|
||||
iteration_node = IterationNode(
|
||||
id=str(uuid.uuid4()),
|
||||
graph_init_params=init_params,
|
||||
graph_runtime_state=graph_runtime_state,
|
||||
config=node_config,
|
||||
)
|
||||
|
||||
# Initialize node data
|
||||
iteration_node.init_node_data(node_config["data"])
|
||||
|
||||
def tt_generator(self):
|
||||
return NodeRunResult(
|
||||
status=WorkflowNodeExecutionStatus.SUCCEEDED,
|
||||
inputs={"iterator_selector": "dify"},
|
||||
outputs={"output": "dify 123"},
|
||||
)
|
||||
|
||||
with patch.object(TemplateTransformNode, "_run", new=tt_generator):
|
||||
# execute node
|
||||
result = iteration_node._run()
|
||||
|
||||
count = 0
|
||||
for item in result:
|
||||
count += 1
|
||||
if isinstance(item, StreamCompletedEvent):
|
||||
assert item.node_run_result.status == WorkflowNodeExecutionStatus.SUCCEEDED
|
||||
assert item.node_run_result.outputs == {"output": ArrayStringSegment(value=["dify 123", "dify 123"])}
|
||||
|
||||
assert count == 32
|
||||
|
||||
|
||||
@pytest.mark.skip(
|
||||
reason="Iteration nodes are part of Phase 3 container support - not yet implemented in new queue-based engine"
|
||||
)
|
||||
def test_iteration_run_in_parallel_mode():
|
||||
graph_config = {
|
||||
"edges": [
|
||||
{
|
||||
"id": "start-source-pe-target",
|
||||
"source": "start",
|
||||
"target": "pe",
|
||||
},
|
||||
{
|
||||
"id": "iteration-1-source-answer-3-target",
|
||||
"source": "iteration-1",
|
||||
"target": "answer-3",
|
||||
},
|
||||
{
|
||||
"id": "iteration-start-source-tt-target",
|
||||
"source": "iteration-start",
|
||||
"target": "tt",
|
||||
},
|
||||
{
|
||||
"id": "iteration-start-source-tt-2-target",
|
||||
"source": "iteration-start",
|
||||
"target": "tt-2",
|
||||
},
|
||||
{
|
||||
"id": "tt-source-if-else-target",
|
||||
"source": "tt",
|
||||
"target": "if-else",
|
||||
},
|
||||
{
|
||||
"id": "tt-2-source-if-else-target",
|
||||
"source": "tt-2",
|
||||
"target": "if-else",
|
||||
},
|
||||
{
|
||||
"id": "if-else-true-answer-2-target",
|
||||
"source": "if-else",
|
||||
"sourceHandle": "true",
|
||||
"target": "answer-2",
|
||||
},
|
||||
{
|
||||
"id": "if-else-false-answer-4-target",
|
||||
"source": "if-else",
|
||||
"sourceHandle": "false",
|
||||
"target": "answer-4",
|
||||
},
|
||||
{
|
||||
"id": "pe-source-iteration-1-target",
|
||||
"source": "pe",
|
||||
"target": "iteration-1",
|
||||
},
|
||||
],
|
||||
"nodes": [
|
||||
{"data": {"title": "Start", "type": "start", "variables": []}, "id": "start"},
|
||||
{
|
||||
"data": {
|
||||
"iterator_selector": ["pe", "list_output"],
|
||||
"output_selector": ["tt", "output"],
|
||||
"output_type": "array[string]",
|
||||
"startNodeType": "template-transform",
|
||||
"start_node_id": "iteration-start",
|
||||
"title": "iteration",
|
||||
"type": "iteration",
|
||||
},
|
||||
"id": "iteration-1",
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"answer": "{{#tt.output#}}",
|
||||
"iteration_id": "iteration-1",
|
||||
"title": "answer 2",
|
||||
"type": "answer",
|
||||
},
|
||||
"id": "answer-2",
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"iteration_id": "iteration-1",
|
||||
"title": "iteration-start",
|
||||
"type": "iteration-start",
|
||||
},
|
||||
"id": "iteration-start",
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"iteration_id": "iteration-1",
|
||||
"template": "{{ arg1 }} 123",
|
||||
"title": "template transform",
|
||||
"type": "template-transform",
|
||||
"variables": [{"value_selector": ["sys", "query"], "variable": "arg1"}],
|
||||
},
|
||||
"id": "tt",
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"iteration_id": "iteration-1",
|
||||
"template": "{{ arg1 }} 321",
|
||||
"title": "template transform",
|
||||
"type": "template-transform",
|
||||
"variables": [{"value_selector": ["sys", "query"], "variable": "arg1"}],
|
||||
},
|
||||
"id": "tt-2",
|
||||
},
|
||||
{
|
||||
"data": {"answer": "{{#iteration-1.output#}}88888", "title": "answer 3", "type": "answer"},
|
||||
"id": "answer-3",
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"conditions": [
|
||||
{
|
||||
"comparison_operator": "is",
|
||||
"id": "1721916275284",
|
||||
"value": "hi",
|
||||
"variable_selector": ["sys", "query"],
|
||||
}
|
||||
],
|
||||
"iteration_id": "iteration-1",
|
||||
"logical_operator": "and",
|
||||
"title": "if",
|
||||
"type": "if-else",
|
||||
},
|
||||
"id": "if-else",
|
||||
},
|
||||
{
|
||||
"data": {"answer": "no hi", "iteration_id": "iteration-1", "title": "answer 4", "type": "answer"},
|
||||
"id": "answer-4",
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"instruction": "test1",
|
||||
"model": {
|
||||
"completion_params": {"temperature": 0.7},
|
||||
"mode": "chat",
|
||||
"name": "gpt-4o",
|
||||
"provider": "openai",
|
||||
},
|
||||
"parameters": [
|
||||
{"description": "test", "name": "list_output", "required": False, "type": "array[string]"}
|
||||
],
|
||||
"query": ["sys", "query"],
|
||||
"reasoning_mode": "prompt",
|
||||
"title": "pe",
|
||||
"type": "parameter-extractor",
|
||||
},
|
||||
"id": "pe",
|
||||
},
|
||||
],
|
||||
}
|
||||
|
||||
init_params = GraphInitParams(
|
||||
tenant_id="1",
|
||||
app_id="1",
|
||||
workflow_id="1",
|
||||
graph_config=graph_config,
|
||||
user_id="1",
|
||||
user_from=UserFrom.ACCOUNT,
|
||||
invoke_from=InvokeFrom.DEBUGGER,
|
||||
call_depth=0,
|
||||
)
|
||||
|
||||
# construct variable pool
|
||||
pool = VariablePool(
|
||||
system_variables=SystemVariable(
|
||||
user_id="1",
|
||||
files=[],
|
||||
query="dify",
|
||||
conversation_id="abababa",
|
||||
),
|
||||
user_inputs={},
|
||||
environment_variables=[],
|
||||
)
|
||||
|
||||
graph_runtime_state = GraphRuntimeState(variable_pool=pool, start_at=time.perf_counter())
|
||||
node_factory = DifyNodeFactory(
|
||||
graph_init_params=init_params,
|
||||
graph_runtime_state=graph_runtime_state,
|
||||
)
|
||||
graph = Graph.init(graph_config=graph_config, node_factory=node_factory)
|
||||
pool.add(["pe", "list_output"], ["dify-1", "dify-2"])
|
||||
|
||||
parallel_node_config = {
|
||||
"data": {
|
||||
"iterator_selector": ["pe", "list_output"],
|
||||
"output_selector": ["tt", "output"],
|
||||
"output_type": "array[string]",
|
||||
"startNodeType": "template-transform",
|
||||
"start_node_id": "iteration-start",
|
||||
"title": "迭代",
|
||||
"type": "iteration",
|
||||
"is_parallel": True,
|
||||
},
|
||||
"id": "iteration-1",
|
||||
}
|
||||
|
||||
parallel_iteration_node = IterationNode(
|
||||
id=str(uuid.uuid4()),
|
||||
graph_init_params=init_params,
|
||||
graph_runtime_state=graph_runtime_state,
|
||||
config=parallel_node_config,
|
||||
)
|
||||
|
||||
# Initialize node data
|
||||
parallel_iteration_node.init_node_data(parallel_node_config["data"])
|
||||
sequential_node_config = {
|
||||
"data": {
|
||||
"iterator_selector": ["pe", "list_output"],
|
||||
"output_selector": ["tt", "output"],
|
||||
"output_type": "array[string]",
|
||||
"startNodeType": "template-transform",
|
||||
"start_node_id": "iteration-start",
|
||||
"title": "迭代",
|
||||
"type": "iteration",
|
||||
"is_parallel": True,
|
||||
},
|
||||
"id": "iteration-1",
|
||||
}
|
||||
|
||||
sequential_iteration_node = IterationNode(
|
||||
id=str(uuid.uuid4()),
|
||||
graph_init_params=init_params,
|
||||
graph_runtime_state=graph_runtime_state,
|
||||
config=sequential_node_config,
|
||||
)
|
||||
|
||||
# Initialize node data
|
||||
sequential_iteration_node.init_node_data(sequential_node_config["data"])
|
||||
|
||||
def tt_generator(self):
|
||||
return NodeRunResult(
|
||||
status=WorkflowNodeExecutionStatus.SUCCEEDED,
|
||||
inputs={"iterator_selector": "dify"},
|
||||
outputs={"output": "dify 123"},
|
||||
)
|
||||
|
||||
with patch.object(TemplateTransformNode, "_run", new=tt_generator):
|
||||
# execute node
|
||||
parallel_result = parallel_iteration_node._run()
|
||||
sequential_result = sequential_iteration_node._run()
|
||||
assert parallel_iteration_node._node_data.parallel_nums == 10
|
||||
assert parallel_iteration_node._node_data.error_handle_mode == ErrorHandleMode.TERMINATED
|
||||
count = 0
|
||||
parallel_arr = []
|
||||
sequential_arr = []
|
||||
for item in parallel_result:
|
||||
count += 1
|
||||
parallel_arr.append(item)
|
||||
if isinstance(item, StreamCompletedEvent):
|
||||
assert item.node_run_result.status == WorkflowNodeExecutionStatus.SUCCEEDED
|
||||
assert item.node_run_result.outputs == {"output": ArrayStringSegment(value=["dify 123", "dify 123"])}
|
||||
assert count == 32
|
||||
|
||||
for item in sequential_result:
|
||||
sequential_arr.append(item)
|
||||
count += 1
|
||||
if isinstance(item, StreamCompletedEvent):
|
||||
assert item.node_run_result.status == WorkflowNodeExecutionStatus.SUCCEEDED
|
||||
assert item.node_run_result.outputs == {"output": ArrayStringSegment(value=["dify 123", "dify 123"])}
|
||||
assert count == 64
|
||||
|
||||
|
||||
@pytest.mark.skip(
|
||||
reason="Iteration nodes are part of Phase 3 container support - not yet implemented in new queue-based engine"
|
||||
)
|
||||
def test_iteration_run_error_handle():
|
||||
graph_config = {
|
||||
"edges": [
|
||||
{
|
||||
"id": "start-source-pe-target",
|
||||
"source": "start",
|
||||
"target": "pe",
|
||||
},
|
||||
{
|
||||
"id": "iteration-1-source-answer-3-target",
|
||||
"source": "iteration-1",
|
||||
"target": "answer-3",
|
||||
},
|
||||
{
|
||||
"id": "tt-source-if-else-target",
|
||||
"source": "iteration-start",
|
||||
"target": "if-else",
|
||||
},
|
||||
{
|
||||
"id": "if-else-true-answer-2-target",
|
||||
"source": "if-else",
|
||||
"sourceHandle": "true",
|
||||
"target": "tt",
|
||||
},
|
||||
{
|
||||
"id": "if-else-false-answer-4-target",
|
||||
"source": "if-else",
|
||||
"sourceHandle": "false",
|
||||
"target": "tt2",
|
||||
},
|
||||
{
|
||||
"id": "pe-source-iteration-1-target",
|
||||
"source": "pe",
|
||||
"target": "iteration-1",
|
||||
},
|
||||
],
|
||||
"nodes": [
|
||||
{"data": {"title": "Start", "type": "start", "variables": []}, "id": "start"},
|
||||
{
|
||||
"data": {
|
||||
"iterator_selector": ["pe", "list_output"],
|
||||
"output_selector": ["tt2", "output"],
|
||||
"output_type": "array[string]",
|
||||
"start_node_id": "if-else",
|
||||
"title": "iteration",
|
||||
"type": "iteration",
|
||||
},
|
||||
"id": "iteration-1",
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"iteration_id": "iteration-1",
|
||||
"template": "{{ arg1.split(arg2) }}",
|
||||
"title": "template transform",
|
||||
"type": "template-transform",
|
||||
"variables": [
|
||||
{"value_selector": ["iteration-1", "item"], "variable": "arg1"},
|
||||
{"value_selector": ["iteration-1", "index"], "variable": "arg2"},
|
||||
],
|
||||
},
|
||||
"id": "tt",
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"iteration_id": "iteration-1",
|
||||
"template": "{{ arg1 }}",
|
||||
"title": "template transform",
|
||||
"type": "template-transform",
|
||||
"variables": [
|
||||
{"value_selector": ["iteration-1", "item"], "variable": "arg1"},
|
||||
],
|
||||
},
|
||||
"id": "tt2",
|
||||
},
|
||||
{
|
||||
"data": {"answer": "{{#iteration-1.output#}}88888", "title": "answer 3", "type": "answer"},
|
||||
"id": "answer-3",
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"iteration_id": "iteration-1",
|
||||
"title": "iteration-start",
|
||||
"type": "iteration-start",
|
||||
},
|
||||
"id": "iteration-start",
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"conditions": [
|
||||
{
|
||||
"comparison_operator": "is",
|
||||
"id": "1721916275284",
|
||||
"value": "1",
|
||||
"variable_selector": ["iteration-1", "item"],
|
||||
}
|
||||
],
|
||||
"iteration_id": "iteration-1",
|
||||
"logical_operator": "and",
|
||||
"title": "if",
|
||||
"type": "if-else",
|
||||
},
|
||||
"id": "if-else",
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"instruction": "test1",
|
||||
"model": {
|
||||
"completion_params": {"temperature": 0.7},
|
||||
"mode": "chat",
|
||||
"name": "gpt-4o",
|
||||
"provider": "openai",
|
||||
},
|
||||
"parameters": [
|
||||
{"description": "test", "name": "list_output", "required": False, "type": "array[string]"}
|
||||
],
|
||||
"query": ["sys", "query"],
|
||||
"reasoning_mode": "prompt",
|
||||
"title": "pe",
|
||||
"type": "parameter-extractor",
|
||||
},
|
||||
"id": "pe",
|
||||
},
|
||||
],
|
||||
}
|
||||
|
||||
init_params = GraphInitParams(
|
||||
tenant_id="1",
|
||||
app_id="1",
|
||||
workflow_id="1",
|
||||
graph_config=graph_config,
|
||||
user_id="1",
|
||||
user_from=UserFrom.ACCOUNT,
|
||||
invoke_from=InvokeFrom.DEBUGGER,
|
||||
call_depth=0,
|
||||
)
|
||||
|
||||
# construct variable pool
|
||||
pool = VariablePool(
|
||||
system_variables=SystemVariable(
|
||||
user_id="1",
|
||||
files=[],
|
||||
query="dify",
|
||||
conversation_id="abababa",
|
||||
),
|
||||
user_inputs={},
|
||||
environment_variables=[],
|
||||
)
|
||||
|
||||
graph_runtime_state = GraphRuntimeState(variable_pool=pool, start_at=time.perf_counter())
|
||||
node_factory = DifyNodeFactory(
|
||||
graph_init_params=init_params,
|
||||
graph_runtime_state=graph_runtime_state,
|
||||
)
|
||||
graph = Graph.init(graph_config=graph_config, node_factory=node_factory)
|
||||
pool.add(["pe", "list_output"], ["1", "1"])
|
||||
error_node_config = {
|
||||
"data": {
|
||||
"iterator_selector": ["pe", "list_output"],
|
||||
"output_selector": ["tt", "output"],
|
||||
"output_type": "array[string]",
|
||||
"startNodeType": "template-transform",
|
||||
"start_node_id": "iteration-start",
|
||||
"title": "iteration",
|
||||
"type": "iteration",
|
||||
"is_parallel": True,
|
||||
"error_handle_mode": ErrorHandleMode.CONTINUE_ON_ERROR,
|
||||
},
|
||||
"id": "iteration-1",
|
||||
}
|
||||
|
||||
iteration_node = IterationNode(
|
||||
id=str(uuid.uuid4()),
|
||||
graph_init_params=init_params,
|
||||
graph_runtime_state=graph_runtime_state,
|
||||
config=error_node_config,
|
||||
)
|
||||
|
||||
# Initialize node data
|
||||
iteration_node.init_node_data(error_node_config["data"])
|
||||
# execute continue on error node
|
||||
result = iteration_node._run()
|
||||
result_arr = []
|
||||
count = 0
|
||||
for item in result:
|
||||
result_arr.append(item)
|
||||
count += 1
|
||||
if isinstance(item, StreamCompletedEvent):
|
||||
assert item.node_run_result.status == WorkflowNodeExecutionStatus.SUCCEEDED
|
||||
assert item.node_run_result.outputs == {"output": ArrayAnySegment(value=[None, None])}
|
||||
|
||||
assert count == 14
|
||||
# execute remove abnormal output
|
||||
iteration_node._node_data.error_handle_mode = ErrorHandleMode.REMOVE_ABNORMAL_OUTPUT
|
||||
result = iteration_node._run()
|
||||
count = 0
|
||||
for item in result:
|
||||
count += 1
|
||||
if isinstance(item, StreamCompletedEvent):
|
||||
assert item.node_run_result.status == WorkflowNodeExecutionStatus.SUCCEEDED
|
||||
assert item.node_run_result.outputs == {"output": ArrayAnySegment(value=[])}
|
||||
assert count == 14
|
||||
|
|
@ -1,624 +0,0 @@
|
|||
import time
|
||||
from unittest.mock import patch
|
||||
|
||||
import pytest
|
||||
|
||||
from core.app.entities.app_invoke_entities import InvokeFrom
|
||||
from core.workflow.entities import GraphInitParams, GraphRuntimeState, VariablePool
|
||||
from core.workflow.enums import (
|
||||
WorkflowNodeExecutionMetadataKey,
|
||||
WorkflowNodeExecutionStatus,
|
||||
)
|
||||
from core.workflow.graph import Graph
|
||||
from core.workflow.graph_engine import GraphEngine
|
||||
from core.workflow.graph_engine.command_channels import InMemoryChannel
|
||||
from core.workflow.graph_events import (
|
||||
GraphRunPartialSucceededEvent,
|
||||
NodeRunExceptionEvent,
|
||||
NodeRunFailedEvent,
|
||||
NodeRunStreamChunkEvent,
|
||||
)
|
||||
from core.workflow.node_events import NodeRunResult, StreamCompletedEvent
|
||||
from core.workflow.nodes.llm.node import LLMNode
|
||||
from core.workflow.nodes.node_factory import DifyNodeFactory
|
||||
from core.workflow.system_variable import SystemVariable
|
||||
from models.enums import UserFrom
|
||||
|
||||
|
||||
class ContinueOnErrorTestHelper:
|
||||
@staticmethod
|
||||
def get_code_node(
|
||||
code: str, error_strategy: str = "fail-branch", default_value: dict | None = None, retry_config: dict = {}
|
||||
):
|
||||
"""Helper method to create a code node configuration"""
|
||||
node = {
|
||||
"id": "node",
|
||||
"data": {
|
||||
"outputs": {"result": {"type": "number"}},
|
||||
"error_strategy": error_strategy,
|
||||
"title": "code",
|
||||
"variables": [],
|
||||
"code_language": "python3",
|
||||
"code": "\n".join([line[4:] for line in code.split("\n")]),
|
||||
"type": "code",
|
||||
**retry_config,
|
||||
},
|
||||
}
|
||||
if default_value:
|
||||
node["data"]["default_value"] = default_value
|
||||
return node
|
||||
|
||||
@staticmethod
|
||||
def get_http_node(
|
||||
error_strategy: str = "fail-branch",
|
||||
default_value: dict | None = None,
|
||||
authorization_success: bool = False,
|
||||
retry_config: dict = {},
|
||||
):
|
||||
"""Helper method to create a http node configuration"""
|
||||
authorization = (
|
||||
{
|
||||
"type": "api-key",
|
||||
"config": {
|
||||
"type": "basic",
|
||||
"api_key": "ak-xxx",
|
||||
"header": "api-key",
|
||||
},
|
||||
}
|
||||
if authorization_success
|
||||
else {
|
||||
"type": "api-key",
|
||||
# missing config field
|
||||
}
|
||||
)
|
||||
node = {
|
||||
"id": "node",
|
||||
"data": {
|
||||
"title": "http",
|
||||
"desc": "",
|
||||
"method": "get",
|
||||
"url": "http://example.com",
|
||||
"authorization": authorization,
|
||||
"headers": "X-Header:123",
|
||||
"params": "A:b",
|
||||
"body": None,
|
||||
"type": "http-request",
|
||||
"error_strategy": error_strategy,
|
||||
**retry_config,
|
||||
},
|
||||
}
|
||||
if default_value:
|
||||
node["data"]["default_value"] = default_value
|
||||
return node
|
||||
|
||||
@staticmethod
|
||||
def get_error_status_code_http_node(error_strategy: str = "fail-branch", default_value: dict | None = None):
|
||||
"""Helper method to create a http node configuration"""
|
||||
node = {
|
||||
"id": "node",
|
||||
"data": {
|
||||
"type": "http-request",
|
||||
"title": "HTTP Request",
|
||||
"desc": "",
|
||||
"variables": [],
|
||||
"method": "get",
|
||||
"url": "https://api.github.com/issues",
|
||||
"authorization": {"type": "no-auth", "config": None},
|
||||
"headers": "",
|
||||
"params": "",
|
||||
"body": {"type": "none", "data": []},
|
||||
"timeout": {"max_connect_timeout": 0, "max_read_timeout": 0, "max_write_timeout": 0},
|
||||
"error_strategy": error_strategy,
|
||||
},
|
||||
}
|
||||
if default_value:
|
||||
node["data"]["default_value"] = default_value
|
||||
return node
|
||||
|
||||
@staticmethod
|
||||
def get_tool_node(error_strategy: str = "fail-branch", default_value: dict | None = None):
|
||||
"""Helper method to create a tool node configuration"""
|
||||
node = {
|
||||
"id": "node",
|
||||
"data": {
|
||||
"title": "a",
|
||||
"desc": "a",
|
||||
"provider_id": "maths",
|
||||
"provider_type": "builtin",
|
||||
"provider_name": "maths",
|
||||
"tool_name": "eval_expression",
|
||||
"tool_label": "eval_expression",
|
||||
"tool_configurations": {},
|
||||
"tool_parameters": {
|
||||
"expression": {
|
||||
"type": "variable",
|
||||
"value": ["1", "123", "args1"],
|
||||
}
|
||||
},
|
||||
"type": "tool",
|
||||
"error_strategy": error_strategy,
|
||||
},
|
||||
}
|
||||
if default_value:
|
||||
node.node_data.default_value = default_value
|
||||
return node
|
||||
|
||||
@staticmethod
|
||||
def get_llm_node(error_strategy: str = "fail-branch", default_value: dict | None = None):
|
||||
"""Helper method to create a llm node configuration"""
|
||||
node = {
|
||||
"id": "node",
|
||||
"data": {
|
||||
"title": "123",
|
||||
"type": "llm",
|
||||
"model": {"provider": "openai", "name": "gpt-3.5-turbo", "mode": "chat", "completion_params": {}},
|
||||
"prompt_template": [
|
||||
{"role": "system", "text": "you are a helpful assistant.\ntoday's weather is {{#abc.output#}}."},
|
||||
{"role": "user", "text": "{{#sys.query#}}"},
|
||||
],
|
||||
"memory": None,
|
||||
"context": {"enabled": False},
|
||||
"vision": {"enabled": False},
|
||||
"error_strategy": error_strategy,
|
||||
},
|
||||
}
|
||||
if default_value:
|
||||
node["data"]["default_value"] = default_value
|
||||
return node
|
||||
|
||||
@staticmethod
|
||||
def create_test_graph_engine(graph_config: dict, user_inputs: dict | None = None):
|
||||
"""Helper method to create a graph engine instance for testing"""
|
||||
# Create graph initialization parameters
|
||||
init_params = GraphInitParams(
|
||||
tenant_id="1",
|
||||
app_id="1",
|
||||
workflow_id="1",
|
||||
graph_config=graph_config,
|
||||
user_id="1",
|
||||
user_from=UserFrom.ACCOUNT,
|
||||
invoke_from=InvokeFrom.DEBUGGER,
|
||||
call_depth=0,
|
||||
)
|
||||
|
||||
variable_pool = VariablePool(
|
||||
system_variables=SystemVariable(
|
||||
user_id="aaa",
|
||||
files=[],
|
||||
query="clear",
|
||||
conversation_id="abababa",
|
||||
),
|
||||
user_inputs=user_inputs or {"uid": "takato"},
|
||||
)
|
||||
|
||||
graph_runtime_state = GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter())
|
||||
node_factory = DifyNodeFactory(init_params, graph_runtime_state)
|
||||
graph = Graph.init(graph_config=graph_config, node_factory=node_factory)
|
||||
|
||||
return GraphEngine(
|
||||
tenant_id="111",
|
||||
app_id="222",
|
||||
workflow_id="333",
|
||||
graph_config=graph_config,
|
||||
user_id="444",
|
||||
user_from=UserFrom.ACCOUNT,
|
||||
invoke_from=InvokeFrom.WEB_APP,
|
||||
call_depth=0,
|
||||
graph=graph,
|
||||
graph_runtime_state=graph_runtime_state,
|
||||
max_execution_steps=500,
|
||||
max_execution_time=1200,
|
||||
command_channel=InMemoryChannel(),
|
||||
)
|
||||
|
||||
|
||||
DEFAULT_VALUE_EDGE = [
|
||||
{
|
||||
"id": "start-source-node-target",
|
||||
"source": "start",
|
||||
"target": "node",
|
||||
"sourceHandle": "source",
|
||||
},
|
||||
{
|
||||
"id": "node-source-answer-target",
|
||||
"source": "node",
|
||||
"target": "answer",
|
||||
"sourceHandle": "source",
|
||||
},
|
||||
]
|
||||
|
||||
FAIL_BRANCH_EDGES = [
|
||||
{
|
||||
"id": "start-source-node-target",
|
||||
"source": "start",
|
||||
"target": "node",
|
||||
"sourceHandle": "source",
|
||||
},
|
||||
{
|
||||
"id": "node-true-success-target",
|
||||
"source": "node",
|
||||
"target": "success",
|
||||
"sourceHandle": "source",
|
||||
},
|
||||
{
|
||||
"id": "node-false-error-target",
|
||||
"source": "node",
|
||||
"target": "error",
|
||||
"sourceHandle": "fail-branch",
|
||||
},
|
||||
]
|
||||
|
||||
|
||||
@pytest.mark.skip(
|
||||
reason="Continue-on-error functionality is part of Phase 2 enhanced error handling - "
|
||||
"not fully implemented in MVP of queue-based engine"
|
||||
)
|
||||
def test_code_default_value_continue_on_error():
|
||||
error_code = """
|
||||
def main() -> dict:
|
||||
return {
|
||||
"result": 1 / 0,
|
||||
}
|
||||
"""
|
||||
|
||||
graph_config = {
|
||||
"edges": DEFAULT_VALUE_EDGE,
|
||||
"nodes": [
|
||||
{"data": {"title": "start", "type": "start", "variables": []}, "id": "start"},
|
||||
{"data": {"title": "answer", "type": "answer", "answer": "{{#node.result#}}"}, "id": "answer"},
|
||||
ContinueOnErrorTestHelper.get_code_node(
|
||||
error_code, "default-value", [{"key": "result", "type": "number", "value": 132123}]
|
||||
),
|
||||
],
|
||||
}
|
||||
|
||||
graph_engine = ContinueOnErrorTestHelper.create_test_graph_engine(graph_config)
|
||||
events = list(graph_engine.run())
|
||||
assert any(isinstance(e, NodeRunExceptionEvent) for e in events)
|
||||
assert any(isinstance(e, GraphRunPartialSucceededEvent) and e.outputs == {"answer": "132123"} for e in events)
|
||||
assert sum(1 for e in events if isinstance(e, NodeRunStreamChunkEvent)) == 1
|
||||
|
||||
|
||||
@pytest.mark.skip(
|
||||
reason="Continue-on-error functionality is part of Phase 2 enhanced error handling - "
|
||||
"not fully implemented in MVP of queue-based engine"
|
||||
)
|
||||
def test_code_fail_branch_continue_on_error():
|
||||
error_code = """
|
||||
def main() -> dict:
|
||||
return {
|
||||
"result": 1 / 0,
|
||||
}
|
||||
"""
|
||||
|
||||
graph_config = {
|
||||
"edges": FAIL_BRANCH_EDGES,
|
||||
"nodes": [
|
||||
{"data": {"title": "Start", "type": "start", "variables": []}, "id": "start"},
|
||||
{
|
||||
"data": {"title": "success", "type": "answer", "answer": "node node run successfully"},
|
||||
"id": "success",
|
||||
},
|
||||
{
|
||||
"data": {"title": "error", "type": "answer", "answer": "node node run failed"},
|
||||
"id": "error",
|
||||
},
|
||||
ContinueOnErrorTestHelper.get_code_node(error_code),
|
||||
],
|
||||
}
|
||||
|
||||
graph_engine = ContinueOnErrorTestHelper.create_test_graph_engine(graph_config)
|
||||
events = list(graph_engine.run())
|
||||
assert sum(1 for e in events if isinstance(e, NodeRunStreamChunkEvent)) == 1
|
||||
assert any(isinstance(e, NodeRunExceptionEvent) for e in events)
|
||||
assert any(
|
||||
isinstance(e, GraphRunPartialSucceededEvent) and e.outputs == {"answer": "node node run failed"} for e in events
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.skip(
|
||||
reason="Continue-on-error functionality is part of Phase 2 enhanced error handling - "
|
||||
"not fully implemented in MVP of queue-based engine"
|
||||
)
|
||||
def test_http_node_default_value_continue_on_error():
|
||||
"""Test HTTP node with default value error strategy"""
|
||||
graph_config = {
|
||||
"edges": DEFAULT_VALUE_EDGE,
|
||||
"nodes": [
|
||||
{"data": {"title": "start", "type": "start", "variables": []}, "id": "start"},
|
||||
{"data": {"title": "answer", "type": "answer", "answer": "{{#node.response#}}"}, "id": "answer"},
|
||||
ContinueOnErrorTestHelper.get_http_node(
|
||||
"default-value", [{"key": "response", "type": "string", "value": "http node got error response"}]
|
||||
),
|
||||
],
|
||||
}
|
||||
|
||||
graph_engine = ContinueOnErrorTestHelper.create_test_graph_engine(graph_config)
|
||||
events = list(graph_engine.run())
|
||||
|
||||
assert any(isinstance(e, NodeRunExceptionEvent) for e in events)
|
||||
assert any(
|
||||
isinstance(e, GraphRunPartialSucceededEvent) and e.outputs == {"answer": "http node got error response"}
|
||||
for e in events
|
||||
)
|
||||
assert sum(1 for e in events if isinstance(e, NodeRunStreamChunkEvent)) == 1
|
||||
|
||||
|
||||
@pytest.mark.skip(
|
||||
reason="Continue-on-error functionality is part of Phase 2 enhanced error handling - "
|
||||
"not fully implemented in MVP of queue-based engine"
|
||||
)
|
||||
def test_http_node_fail_branch_continue_on_error():
|
||||
"""Test HTTP node with fail-branch error strategy"""
|
||||
graph_config = {
|
||||
"edges": FAIL_BRANCH_EDGES,
|
||||
"nodes": [
|
||||
{"data": {"title": "Start", "type": "start", "variables": []}, "id": "start"},
|
||||
{
|
||||
"data": {"title": "success", "type": "answer", "answer": "HTTP request successful"},
|
||||
"id": "success",
|
||||
},
|
||||
{
|
||||
"data": {"title": "error", "type": "answer", "answer": "HTTP request failed"},
|
||||
"id": "error",
|
||||
},
|
||||
ContinueOnErrorTestHelper.get_http_node(),
|
||||
],
|
||||
}
|
||||
|
||||
graph_engine = ContinueOnErrorTestHelper.create_test_graph_engine(graph_config)
|
||||
events = list(graph_engine.run())
|
||||
|
||||
assert any(isinstance(e, NodeRunExceptionEvent) for e in events)
|
||||
assert any(
|
||||
isinstance(e, GraphRunPartialSucceededEvent) and e.outputs == {"answer": "HTTP request failed"} for e in events
|
||||
)
|
||||
assert sum(1 for e in events if isinstance(e, NodeRunStreamChunkEvent)) == 1
|
||||
|
||||
|
||||
# def test_tool_node_default_value_continue_on_error():
|
||||
# """Test tool node with default value error strategy"""
|
||||
# graph_config = {
|
||||
# "edges": DEFAULT_VALUE_EDGE,
|
||||
# "nodes": [
|
||||
# {"data": {"title": "start", "type": "start", "variables": []}, "id": "start"},
|
||||
# {"data": {"title": "answer", "type": "answer", "answer": "{{#node.result#}}"}, "id": "answer"},
|
||||
# ContinueOnErrorTestHelper.get_tool_node(
|
||||
# "default-value", [{"key": "result", "type": "string", "value": "default tool result"}]
|
||||
# ),
|
||||
# ],
|
||||
# }
|
||||
|
||||
# graph_engine = ContinueOnErrorTestHelper.create_test_graph_engine(graph_config)
|
||||
# events = list(graph_engine.run())
|
||||
|
||||
# assert any(isinstance(e, NodeRunExceptionEvent) for e in events)
|
||||
# assert any(
|
||||
# isinstance(e, GraphRunPartialSucceededEvent) and e.outputs == {"answer": "default tool result"} for e in events # noqa: E501
|
||||
# )
|
||||
# assert sum(1 for e in events if isinstance(e, NodeRunStreamChunkEvent)) == 1
|
||||
|
||||
|
||||
# def test_tool_node_fail_branch_continue_on_error():
|
||||
# """Test HTTP node with fail-branch error strategy"""
|
||||
# graph_config = {
|
||||
# "edges": FAIL_BRANCH_EDGES,
|
||||
# "nodes": [
|
||||
# {"data": {"title": "Start", "type": "start", "variables": []}, "id": "start"},
|
||||
# {
|
||||
# "data": {"title": "success", "type": "answer", "answer": "tool execute successful"},
|
||||
# "id": "success",
|
||||
# },
|
||||
# {
|
||||
# "data": {"title": "error", "type": "answer", "answer": "tool execute failed"},
|
||||
# "id": "error",
|
||||
# },
|
||||
# ContinueOnErrorTestHelper.get_tool_node(),
|
||||
# ],
|
||||
# }
|
||||
|
||||
# graph_engine = ContinueOnErrorTestHelper.create_test_graph_engine(graph_config)
|
||||
# events = list(graph_engine.run())
|
||||
|
||||
# assert any(isinstance(e, NodeRunExceptionEvent) for e in events)
|
||||
# assert any(
|
||||
# isinstance(e, GraphRunPartialSucceededEvent) and e.outputs == {"answer": "tool execute failed"} for e in events # noqa: E501
|
||||
# )
|
||||
# assert sum(1 for e in events if isinstance(e, NodeRunStreamChunkEvent)) == 1
|
||||
|
||||
|
||||
@pytest.mark.skip(
|
||||
reason="Continue-on-error functionality is part of Phase 2 enhanced error handling - "
|
||||
"not fully implemented in MVP of queue-based engine"
|
||||
)
|
||||
def test_llm_node_default_value_continue_on_error():
|
||||
"""Test LLM node with default value error strategy"""
|
||||
graph_config = {
|
||||
"edges": DEFAULT_VALUE_EDGE,
|
||||
"nodes": [
|
||||
{"data": {"title": "start", "type": "start", "variables": []}, "id": "start"},
|
||||
{"data": {"title": "answer", "type": "answer", "answer": "{{#node.answer#}}"}, "id": "answer"},
|
||||
ContinueOnErrorTestHelper.get_llm_node(
|
||||
"default-value", [{"key": "answer", "type": "string", "value": "default LLM response"}]
|
||||
),
|
||||
],
|
||||
}
|
||||
|
||||
graph_engine = ContinueOnErrorTestHelper.create_test_graph_engine(graph_config)
|
||||
events = list(graph_engine.run())
|
||||
|
||||
assert any(isinstance(e, NodeRunExceptionEvent) for e in events)
|
||||
assert any(
|
||||
isinstance(e, GraphRunPartialSucceededEvent) and e.outputs == {"answer": "default LLM response"} for e in events
|
||||
)
|
||||
assert sum(1 for e in events if isinstance(e, NodeRunStreamChunkEvent)) == 1
|
||||
|
||||
|
||||
@pytest.mark.skip(
|
||||
reason="Continue-on-error functionality is part of Phase 2 enhanced error handling - "
|
||||
"not fully implemented in MVP of queue-based engine"
|
||||
)
|
||||
def test_llm_node_fail_branch_continue_on_error():
|
||||
"""Test LLM node with fail-branch error strategy"""
|
||||
graph_config = {
|
||||
"edges": FAIL_BRANCH_EDGES,
|
||||
"nodes": [
|
||||
{"data": {"title": "Start", "type": "start", "variables": []}, "id": "start"},
|
||||
{
|
||||
"data": {"title": "success", "type": "answer", "answer": "LLM request successful"},
|
||||
"id": "success",
|
||||
},
|
||||
{
|
||||
"data": {"title": "error", "type": "answer", "answer": "LLM request failed"},
|
||||
"id": "error",
|
||||
},
|
||||
ContinueOnErrorTestHelper.get_llm_node(),
|
||||
],
|
||||
}
|
||||
|
||||
graph_engine = ContinueOnErrorTestHelper.create_test_graph_engine(graph_config)
|
||||
events = list(graph_engine.run())
|
||||
|
||||
assert any(isinstance(e, NodeRunExceptionEvent) for e in events)
|
||||
assert any(
|
||||
isinstance(e, GraphRunPartialSucceededEvent) and e.outputs == {"answer": "LLM request failed"} for e in events
|
||||
)
|
||||
assert sum(1 for e in events if isinstance(e, NodeRunStreamChunkEvent)) == 1
|
||||
|
||||
|
||||
@pytest.mark.skip(
|
||||
reason="Continue-on-error functionality is part of Phase 2 enhanced error handling - "
|
||||
"not fully implemented in MVP of queue-based engine"
|
||||
)
|
||||
def test_status_code_error_http_node_fail_branch_continue_on_error():
|
||||
"""Test HTTP node with fail-branch error strategy"""
|
||||
graph_config = {
|
||||
"edges": FAIL_BRANCH_EDGES,
|
||||
"nodes": [
|
||||
{"data": {"title": "Start", "type": "start", "variables": []}, "id": "start"},
|
||||
{
|
||||
"data": {"title": "success", "type": "answer", "answer": "http execute successful"},
|
||||
"id": "success",
|
||||
},
|
||||
{
|
||||
"data": {"title": "error", "type": "answer", "answer": "http execute failed"},
|
||||
"id": "error",
|
||||
},
|
||||
ContinueOnErrorTestHelper.get_error_status_code_http_node(),
|
||||
],
|
||||
}
|
||||
|
||||
graph_engine = ContinueOnErrorTestHelper.create_test_graph_engine(graph_config)
|
||||
events = list(graph_engine.run())
|
||||
|
||||
assert any(isinstance(e, NodeRunExceptionEvent) for e in events)
|
||||
assert any(
|
||||
isinstance(e, GraphRunPartialSucceededEvent) and e.outputs == {"answer": "http execute failed"} for e in events
|
||||
)
|
||||
assert sum(1 for e in events if isinstance(e, NodeRunStreamChunkEvent)) == 1
|
||||
|
||||
|
||||
@pytest.mark.skip(
|
||||
reason="Continue-on-error functionality is part of Phase 2 enhanced error handling - "
|
||||
"not fully implemented in MVP of queue-based engine"
|
||||
)
|
||||
def test_variable_pool_error_type_variable():
|
||||
graph_config = {
|
||||
"edges": FAIL_BRANCH_EDGES,
|
||||
"nodes": [
|
||||
{"data": {"title": "Start", "type": "start", "variables": []}, "id": "start"},
|
||||
{
|
||||
"data": {"title": "success", "type": "answer", "answer": "http execute successful"},
|
||||
"id": "success",
|
||||
},
|
||||
{
|
||||
"data": {"title": "error", "type": "answer", "answer": "http execute failed"},
|
||||
"id": "error",
|
||||
},
|
||||
ContinueOnErrorTestHelper.get_error_status_code_http_node(),
|
||||
],
|
||||
}
|
||||
|
||||
graph_engine = ContinueOnErrorTestHelper.create_test_graph_engine(graph_config)
|
||||
list(graph_engine.run())
|
||||
error_message = graph_engine.graph_runtime_state.variable_pool.get(["node", "error_message"])
|
||||
error_type = graph_engine.graph_runtime_state.variable_pool.get(["node", "error_type"])
|
||||
assert error_message != None
|
||||
assert error_type.value == "HTTPResponseCodeError"
|
||||
|
||||
|
||||
@pytest.mark.skip(
|
||||
reason="Continue-on-error functionality is part of Phase 2 enhanced error handling - "
|
||||
"not fully implemented in MVP of queue-based engine"
|
||||
)
|
||||
def test_no_node_in_fail_branch_continue_on_error():
|
||||
"""Test HTTP node with fail-branch error strategy"""
|
||||
graph_config = {
|
||||
"edges": FAIL_BRANCH_EDGES[:-1],
|
||||
"nodes": [
|
||||
{"data": {"title": "Start", "type": "start", "variables": []}, "id": "start"},
|
||||
{"data": {"title": "success", "type": "answer", "answer": "HTTP request successful"}, "id": "success"},
|
||||
ContinueOnErrorTestHelper.get_http_node(),
|
||||
],
|
||||
}
|
||||
|
||||
graph_engine = ContinueOnErrorTestHelper.create_test_graph_engine(graph_config)
|
||||
events = list(graph_engine.run())
|
||||
|
||||
assert any(isinstance(e, NodeRunExceptionEvent) for e in events)
|
||||
assert any(isinstance(e, GraphRunPartialSucceededEvent) and e.outputs == {} for e in events)
|
||||
assert sum(1 for e in events if isinstance(e, NodeRunStreamChunkEvent)) == 0
|
||||
|
||||
|
||||
@pytest.mark.skip(
|
||||
reason="Continue-on-error functionality is part of Phase 2 enhanced error handling - "
|
||||
"not fully implemented in MVP of queue-based engine"
|
||||
)
|
||||
def test_stream_output_with_fail_branch_continue_on_error():
|
||||
"""Test stream output with fail-branch error strategy"""
|
||||
graph_config = {
|
||||
"edges": FAIL_BRANCH_EDGES,
|
||||
"nodes": [
|
||||
{"data": {"title": "Start", "type": "start", "variables": []}, "id": "start"},
|
||||
{
|
||||
"data": {"title": "success", "type": "answer", "answer": "LLM request successful"},
|
||||
"id": "success",
|
||||
},
|
||||
{
|
||||
"data": {"title": "error", "type": "answer", "answer": "{{#node.text#}}"},
|
||||
"id": "error",
|
||||
},
|
||||
ContinueOnErrorTestHelper.get_llm_node(),
|
||||
],
|
||||
}
|
||||
graph_engine = ContinueOnErrorTestHelper.create_test_graph_engine(graph_config)
|
||||
|
||||
def llm_generator(self):
|
||||
contents = ["hi", "bye", "good morning"]
|
||||
|
||||
yield NodeRunStreamChunkEvent(
|
||||
node_id=self.node_id,
|
||||
node_type=self._node_type,
|
||||
selector=[self.node_id, "text"],
|
||||
chunk=contents[0],
|
||||
is_final=False,
|
||||
)
|
||||
|
||||
yield StreamCompletedEvent(
|
||||
node_run_result=NodeRunResult(
|
||||
status=WorkflowNodeExecutionStatus.SUCCEEDED,
|
||||
inputs={},
|
||||
process_data={},
|
||||
outputs={},
|
||||
metadata={
|
||||
WorkflowNodeExecutionMetadataKey.TOTAL_TOKENS: 1,
|
||||
WorkflowNodeExecutionMetadataKey.TOTAL_PRICE: 1,
|
||||
WorkflowNodeExecutionMetadataKey.CURRENCY: "USD",
|
||||
},
|
||||
)
|
||||
)
|
||||
|
||||
with patch.object(LLMNode, "_run", new=llm_generator):
|
||||
events = list(graph_engine.run())
|
||||
assert sum(isinstance(e, NodeRunStreamChunkEvent) for e in events) == 1
|
||||
assert all(not isinstance(e, NodeRunFailedEvent | NodeRunExceptionEvent) for e in events)
|
||||
|
|
@ -1,116 +0,0 @@
|
|||
from collections.abc import Generator
|
||||
|
||||
import pytest
|
||||
|
||||
from core.app.entities.app_invoke_entities import InvokeFrom
|
||||
from core.tools.entities.tool_entities import ToolInvokeMessage, ToolProviderType
|
||||
from core.tools.errors import ToolInvokeError
|
||||
from core.workflow.entities import GraphInitParams, GraphRuntimeState, VariablePool
|
||||
from core.workflow.enums import ErrorStrategy, WorkflowNodeExecutionStatus
|
||||
from core.workflow.graph import Graph
|
||||
from core.workflow.node_events import NodeRunResult, StreamCompletedEvent
|
||||
from core.workflow.nodes.answer.entities import AnswerStreamGenerateRoute
|
||||
from core.workflow.nodes.end.entities import EndStreamParam
|
||||
from core.workflow.nodes.tool import ToolNode
|
||||
from core.workflow.nodes.tool.entities import ToolNodeData
|
||||
from core.workflow.system_variable import SystemVariable
|
||||
from models import UserFrom
|
||||
|
||||
|
||||
def _create_tool_node():
|
||||
data = ToolNodeData(
|
||||
title="Test Tool",
|
||||
tool_parameters={},
|
||||
provider_id="test_tool",
|
||||
provider_type=ToolProviderType.WORKFLOW,
|
||||
provider_name="test tool",
|
||||
tool_name="test tool",
|
||||
tool_label="test tool",
|
||||
tool_configurations={},
|
||||
plugin_unique_identifier=None,
|
||||
desc="Exception handling test tool",
|
||||
error_strategy=ErrorStrategy.FAIL_BRANCH,
|
||||
version="1",
|
||||
)
|
||||
variable_pool = VariablePool(
|
||||
system_variables=SystemVariable.empty(),
|
||||
user_inputs={},
|
||||
)
|
||||
node_config = {
|
||||
"id": "1",
|
||||
"data": data.model_dump(),
|
||||
}
|
||||
node = ToolNode(
|
||||
id="1",
|
||||
config=node_config,
|
||||
graph_init_params=GraphInitParams(
|
||||
tenant_id="1",
|
||||
app_id="1",
|
||||
workflow_id="1",
|
||||
graph_config={},
|
||||
user_id="1",
|
||||
user_from=UserFrom.ACCOUNT,
|
||||
invoke_from=InvokeFrom.SERVICE_API,
|
||||
call_depth=0,
|
||||
),
|
||||
graph=Graph(
|
||||
root_node_id="1",
|
||||
answer_stream_generate_routes=AnswerStreamGenerateRoute(
|
||||
answer_dependencies={},
|
||||
answer_generate_route={},
|
||||
),
|
||||
end_stream_param=EndStreamParam(
|
||||
end_dependencies={},
|
||||
end_stream_variable_selector_mapping={},
|
||||
),
|
||||
),
|
||||
graph_runtime_state=GraphRuntimeState(
|
||||
variable_pool=variable_pool,
|
||||
start_at=0,
|
||||
),
|
||||
)
|
||||
# Initialize node data
|
||||
node.init_node_data(node_config["data"])
|
||||
return node
|
||||
|
||||
|
||||
class MockToolRuntime:
|
||||
def get_merged_runtime_parameters(self):
|
||||
pass
|
||||
|
||||
|
||||
def mock_message_stream() -> Generator[ToolInvokeMessage, None, None]:
|
||||
yield from []
|
||||
raise ToolInvokeError("oops")
|
||||
|
||||
|
||||
@pytest.mark.skip(
|
||||
reason="Tool node test uses old Graph constructor incompatible with new queue-based engine - "
|
||||
"needs rewrite for new architecture"
|
||||
)
|
||||
def test_tool_node_on_tool_invoke_error(monkeypatch: pytest.MonkeyPatch):
|
||||
"""Ensure that ToolNode can handle ToolInvokeError when transforming
|
||||
messages generated by ToolEngine.generic_invoke.
|
||||
"""
|
||||
tool_node = _create_tool_node()
|
||||
|
||||
# Need to patch ToolManager and ToolEngine so that we don't
|
||||
# have to set up a database.
|
||||
monkeypatch.setattr(
|
||||
"core.tools.tool_manager.ToolManager.get_workflow_tool_runtime", lambda *args, **kwargs: MockToolRuntime()
|
||||
)
|
||||
monkeypatch.setattr(
|
||||
"core.tools.tool_engine.ToolEngine.generic_invoke",
|
||||
lambda *args, **kwargs: mock_message_stream(),
|
||||
)
|
||||
|
||||
streams = list(tool_node._run())
|
||||
assert len(streams) == 1
|
||||
stream = streams[0]
|
||||
assert isinstance(stream, StreamCompletedEvent)
|
||||
result = stream.node_run_result
|
||||
assert isinstance(result, NodeRunResult)
|
||||
assert result.status == WorkflowNodeExecutionStatus.FAILED
|
||||
assert "oops" in result.error
|
||||
assert "Failed to invoke tool" in result.error
|
||||
assert result.error_type == "ToolInvokeError"
|
||||
Loading…
Reference in New Issue