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feat: queue-based graph engine

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Signed-off-by: -LAN- <laipz8200@outlook.com>
This commit is contained in:
-LAN-
2025-08-22 03:29:46 +08:00
parent f04844435f
commit 8c35663220
363 changed files with 20911 additions and 8927 deletions
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60
api/tests/integration_tests/workflow/nodes/test_llm.py
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@ -6,17 +6,15 @@ from unittest.mock import MagicMock, patch
from core.app.entities.app_invoke_entities import InvokeFrom
from core.llm_generator.output_parser.structured_output import _parse_structured_output
from core.workflow.entities.variable_pool import VariablePool
from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionStatus
from core.workflow.graph_engine.entities.graph import Graph
from core.workflow.graph_engine.entities.graph_init_params import GraphInitParams
from core.workflow.graph_engine.entities.graph_runtime_state import GraphRuntimeState
from core.workflow.nodes.event import RunCompletedEvent
from core.workflow.entities import GraphInitParams, GraphRuntimeState, VariablePool
from core.workflow.enums import WorkflowNodeExecutionStatus
from core.workflow.graph import Graph
from core.workflow.node_events import 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 extensions.ext_database import db
from models.enums import UserFrom
from models.workflow import WorkflowType
"""FOR MOCK FIXTURES, DO NOT REMOVE"""
@ -30,11 +28,9 @@ def init_llm_node(config: dict) -> LLMNode:
"target": "llm",
},
],
"nodes": [{"data": {"type": "start"}, "id": "start"}, config],
"nodes": [{"data": {"type": "start", "title": "Start"}, "id": "start"}, config],
}
graph = Graph.init(graph_config=graph_config)
# Use proper UUIDs for database compatibility
tenant_id = "9d2074fc-6f86-45a9-b09d-6ecc63b9056b"
app_id = "9d2074fc-6f86-45a9-b09d-6ecc63b9056c"
@ -44,7 +40,6 @@ def init_llm_node(config: dict) -> LLMNode:
init_params = GraphInitParams(
tenant_id=tenant_id,
app_id=app_id,
workflow_type=WorkflowType.WORKFLOW,
workflow_id=workflow_id,
graph_config=graph_config,
user_id=user_id,
@ -69,12 +64,21 @@ def init_llm_node(config: dict) -> LLMNode:
)
variable_pool.add(["abc", "output"], "sunny")
graph_runtime_state = GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter())
# Create node factory
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 = LLMNode(
id=str(uuid.uuid4()),
graph_init_params=init_params,
graph=graph,
graph_runtime_state=GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter()),
config=config,
graph_init_params=init_params,
graph_runtime_state=graph_runtime_state,
)
# Initialize node data
@ -173,15 +177,15 @@ def test_execute_llm():
assert isinstance(result, Generator)
for item in result:
if isinstance(item, RunCompletedEvent):
if item.run_result.status != WorkflowNodeExecutionStatus.SUCCEEDED:
print(f"Error: {item.run_result.error}")
print(f"Error type: {item.run_result.error_type}")
assert item.run_result.status == WorkflowNodeExecutionStatus.SUCCEEDED
assert item.run_result.process_data is not None
assert item.run_result.outputs is not None
assert item.run_result.outputs.get("text") is not None
assert item.run_result.outputs.get("usage", {})["total_tokens"] > 0
if isinstance(item, StreamCompletedEvent):
if item.node_run_result.status != WorkflowNodeExecutionStatus.SUCCEEDED:
print(f"Error: {item.node_run_result.error}")
print(f"Error type: {item.node_run_result.error_type}")
assert item.node_run_result.status == WorkflowNodeExecutionStatus.SUCCEEDED
assert item.node_run_result.process_data is not None
assert item.node_run_result.outputs is not None
assert item.node_run_result.outputs.get("text") is not None
assert item.node_run_result.outputs.get("usage", {})["total_tokens"] > 0
def test_execute_llm_with_jinja2():
@ -284,11 +288,11 @@ def test_execute_llm_with_jinja2():
result = node._run()
for item in result:
if isinstance(item, RunCompletedEvent):
assert item.run_result.status == WorkflowNodeExecutionStatus.SUCCEEDED
assert item.run_result.process_data is not None
assert "sunny" in json.dumps(item.run_result.process_data)
assert "what's the weather today?" in json.dumps(item.run_result.process_data)
if isinstance(item, StreamCompletedEvent):
assert item.node_run_result.status == WorkflowNodeExecutionStatus.SUCCEEDED
assert item.node_run_result.process_data is not None
assert "sunny" in json.dumps(item.node_run_result.process_data)
assert "what's the weather today?" in json.dumps(item.node_run_result.process_data)
def test_extract_json():