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chore(api): Upgrade graphon to v0.5.1 (#37168)

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Co-authored-by: Yunlu Wen <yunlu.wen@dify.ai>
Co-authored-by: L1nSn0w <l1nsn0w@qq.com>
This commit is contained in:
QuantumGhost 2026-06-11 15:37:27 +08:00 committed by GitHub
parent fb39df49c8
commit b4c50eb920
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25 changed files with 450 additions and 90 deletions
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2
api/commands/data_migrate.py
View File

@ -145,7 +145,7 @@ def legacy_model_types(
option_name="--model-types",
)
selected_model_types = (
tuple(ModelType.value_of(model_type) for model_type in normalized_model_types)
tuple(ModelType(model_type) for model_type in normalized_model_types)
if normalized_model_types
else (
ModelType.LLM,

2
api/core/provider_manager.py
View File

@ -816,7 +816,7 @@ class ProviderManager:
return [
{
"model": model_key[0],
"model_type": ModelType.value_of(model_key[1]),
"model_type": ModelType(model_key[1]),
"available_model_credentials": [
CredentialConfiguration(credential_id=cred.id, credential_name=cred.credential_name)
for cred in creds

20
api/core/workflow/workflow_entry.py
View File

@ -30,6 +30,7 @@ from graphon.entities import GraphInitParams
from graphon.entities.graph_config import NodeConfigDictAdapter
from graphon.errors import WorkflowNodeRunFailedError
from graphon.file import File
from graphon.filters import GraphEventFilterContext, ResponseStreamFilter, filter_graph_events
from graphon.graph import Graph
from graphon.graph_engine import GraphEngine, GraphEngineConfig
from graphon.graph_engine.command_channels import CommandChannel, InMemoryChannel
@ -45,6 +46,21 @@ logger = logging.getLogger(__name__)
_file_access_controller = DatabaseFileAccessController()
def iter_dify_graph_engine_events(engine: GraphEngine) -> Generator[GraphEngineEvent, None, None]:
"""
Apply Dify's response streaming compatibility filter to GraphEngine events.
Graphon v0.5.0 emits raw variable stream chunks and requires callers to opt
into the legacy response-ordered stream behavior that Dify exposes to its
workflow runners and tests.
"""
yield from filter_graph_events(
engine.run(),
context=GraphEventFilterContext.from_engine(engine),
filters=[ResponseStreamFilter()],
)
class _WorkflowChildEngineBuilder:
tenant_id: str
@ -223,8 +239,8 @@ class WorkflowEntry:
graph_engine = self.graph_engine
try:
# run workflow
generator = graph_engine.run()
# Preserve Dify's response-stream semantics on top of Graphon 0.5.0.
generator = iter_dify_graph_engine_events(graph_engine)
yield from generator
except GenerateTaskStoppedError:
pass

8
api/models/utils/file_input_compat.py
View File

@ -149,10 +149,10 @@ def build_file_from_mapping_without_lookup(*, file_mapping: Mapping[str, Any]) -
def rebuild_serialized_graph_files_without_lookup(value: Any) -> Any:
"""Recursively rebuild serialized graph file payloads into `File` objects.
`graphon` 0.2.2 no longer accepts legacy serialized file mappings via
`model_validate_json()`. Dify keeps this recovery path at the model boundary
so historical JSON blobs remain readable without reintroducing global graph
patches or test-local coercion.
`graphon` no longer accepts legacy serialized file mappings via
`model_validate_json()`. Dify keeps this recovery path at the model
boundary so historical JSON blobs remain readable without reintroducing
global graph patches or test-local coercion.
"""
match value:
case list():

2
api/pyproject.toml
View File

@ -44,7 +44,7 @@ dependencies = [
"resend>=2.27.0,<3.0.0",
# Emerging: newer and fast-moving, use compatible pins
"fastopenapi[flask]==0.7.0",
"graphon==0.4.0",
"graphon==0.5.1",
"httpx-sse==0.4.3",
"json-repair==0.59.4",
]

12
api/services/model_load_balancing_service.py
View File

@ -66,7 +66,7 @@ class ModelLoadBalancingService:
raise ValueError(f"Provider {provider} does not exist.")
# Enable model load balancing
provider_configuration.enable_model_load_balancing(model=model, model_type=ModelType.value_of(model_type))
provider_configuration.enable_model_load_balancing(model=model, model_type=ModelType(model_type))
def disable_model_load_balancing(self, tenant_id: str, provider: str, model: str, model_type: str):
"""
@ -87,7 +87,7 @@ class ModelLoadBalancingService:
raise ValueError(f"Provider {provider} does not exist.")
# disable model load balancing
provider_configuration.disable_model_load_balancing(model=model, model_type=ModelType.value_of(model_type))
provider_configuration.disable_model_load_balancing(model=model, model_type=ModelType(model_type))
def get_load_balancing_configs(
self, tenant_id: str, provider: str, model: str, model_type: str, config_from: str = ""
@ -109,7 +109,7 @@ class ModelLoadBalancingService:
raise ValueError(f"Provider {provider} does not exist.")
# Convert model type to ModelType
model_type_enum = ModelType.value_of(model_type)
model_type_enum = ModelType(model_type)
# Get provider model setting
provider_model_setting = provider_configuration.get_provider_model_setting(
@ -250,7 +250,7 @@ class ModelLoadBalancingService:
raise ValueError(f"Provider {provider} does not exist.")
# Convert model type to ModelType
model_type_enum = ModelType.value_of(model_type)
model_type_enum = ModelType(model_type)
# Get load balancing configurations
load_balancing_model_config = db.session.scalar(
@ -338,7 +338,7 @@ class ModelLoadBalancingService:
raise ValueError(f"Provider {provider} does not exist.")
# Convert model type to ModelType
model_type_enum = ModelType.value_of(model_type)
model_type_enum = ModelType(model_type)
if not isinstance(configs, list):
raise ValueError("Invalid load balancing configs")
@ -524,7 +524,7 @@ class ModelLoadBalancingService:
raise ValueError(f"Provider {provider} does not exist.")
# Convert model type to ModelType
model_type_enum = ModelType.value_of(model_type)
model_type_enum = ModelType(model_type)
load_balancing_model_config = None
if config_id:

28
api/services/model_provider_service.py
View File

@ -70,7 +70,7 @@ class ModelProviderService:
provider_responses = []
for provider_configuration in provider_configurations.values():
if model_type:
model_type_entity = ModelType.value_of(model_type)
model_type_entity = ModelType(model_type)
if model_type_entity not in provider_configuration.provider.supported_model_types:
continue
@ -273,7 +273,7 @@ class ModelProviderService:
"""
provider_configuration = self._get_provider_configuration(tenant_id, provider)
return provider_configuration.get_custom_model_credential(
model_type=ModelType.value_of(model_type), model=model, credential_id=credential_id
model_type=ModelType(model_type), model=model, credential_id=credential_id
)
def validate_model_credentials(
@ -291,7 +291,7 @@ class ModelProviderService:
"""
provider_configuration = self._get_provider_configuration(tenant_id, provider)
provider_configuration.validate_custom_model_credentials(
model_type=ModelType.value_of(model_type), model=model, credentials=credentials
model_type=ModelType(model_type), model=model, credentials=credentials
)
def create_model_credential(
@ -316,7 +316,7 @@ class ModelProviderService:
"""
provider_configuration = self._get_provider_configuration(tenant_id, provider)
provider_configuration.create_custom_model_credential(
model_type=ModelType.value_of(model_type),
model_type=ModelType(model_type),
model=model,
credentials=credentials,
credential_name=credential_name,
@ -346,7 +346,7 @@ class ModelProviderService:
"""
provider_configuration = self._get_provider_configuration(tenant_id, provider)
provider_configuration.update_custom_model_credential(
model_type=ModelType.value_of(model_type),
model_type=ModelType(model_type),
model=model,
credentials=credentials,
credential_id=credential_id,
@ -366,7 +366,7 @@ class ModelProviderService:
"""
provider_configuration = self._get_provider_configuration(tenant_id, provider)
provider_configuration.delete_custom_model_credential(
model_type=ModelType.value_of(model_type), model=model, credential_id=credential_id
model_type=ModelType(model_type), model=model, credential_id=credential_id
)
def switch_active_custom_model_credential(
@ -384,7 +384,7 @@ class ModelProviderService:
"""
provider_configuration = self._get_provider_configuration(tenant_id, provider)
provider_configuration.switch_custom_model_credential(
model_type=ModelType.value_of(model_type), model=model, credential_id=credential_id
model_type=ModelType(model_type), model=model, credential_id=credential_id
)
def add_model_credential_to_model_list(
@ -402,7 +402,7 @@ class ModelProviderService:
"""
provider_configuration = self._get_provider_configuration(tenant_id, provider)
provider_configuration.add_model_credential_to_model(
model_type=ModelType.value_of(model_type), model=model, credential_id=credential_id
model_type=ModelType(model_type), model=model, credential_id=credential_id
)
def remove_model(self, tenant_id: str, provider: str, model_type: str, model: str):
@ -416,7 +416,7 @@ class ModelProviderService:
:return:
"""
provider_configuration = self._get_provider_configuration(tenant_id, provider)
provider_configuration.delete_custom_model(model_type=ModelType.value_of(model_type), model=model)
provider_configuration.delete_custom_model(model_type=ModelType(model_type), model=model)
def get_models_by_model_type(self, tenant_id: str, model_type: str) -> list[ProviderWithModelsResponse]:
"""
@ -430,7 +430,7 @@ class ModelProviderService:
provider_configurations = self._get_provider_manager(tenant_id).get_configurations(tenant_id)
# Get provider available models
models = provider_configurations.get_models(model_type=ModelType.value_of(model_type), only_active=True)
models = provider_configurations.get_models(model_type=ModelType(model_type), only_active=True)
# Group models by provider
provider_models: dict[str, list[ModelWithProviderEntity]] = {}
@ -509,7 +509,7 @@ class ModelProviderService:
:param model_type: model type
:return:
"""
model_type_enum = ModelType.value_of(model_type)
model_type_enum = ModelType(model_type)
try:
result = self._get_provider_manager(tenant_id).get_default_model(
@ -544,7 +544,7 @@ class ModelProviderService:
:param model: model name
:return:
"""
model_type_enum = ModelType.value_of(model_type)
model_type_enum = ModelType(model_type)
self._get_provider_manager(tenant_id).update_default_model_record(
tenant_id=tenant_id, model_type=model_type_enum, provider=provider, model=model
)
@ -594,7 +594,7 @@ class ModelProviderService:
:return:
"""
provider_configuration = self._get_provider_configuration(tenant_id, provider)
provider_configuration.enable_model(model=model, model_type=ModelType.value_of(model_type))
provider_configuration.enable_model(model=model, model_type=ModelType(model_type))
def disable_model(self, tenant_id: str, provider: str, model: str, model_type: str):
"""
@ -607,4 +607,4 @@ class ModelProviderService:
:return:
"""
provider_configuration = self._get_provider_configuration(tenant_id, provider)
provider_configuration.disable_model(model=model, model_type=ModelType.value_of(model_type))
provider_configuration.disable_model(model=model, model_type=ModelType(model_type))

138
api/tests/fixtures/workflow/response_stream_filter_issue_170_workflow.yml vendored Normal file
View File

@ -0,0 +1,138 @@
app:
description: Response stream ordering fixture matching graphon issue 170.
icon: 🤖
icon_background: '#FFEAD5'
mode: advanced-chat
name: response_stream_filter_issue_170_workflow
use_icon_as_answer_icon: false
dependencies: []
kind: app
version: 0.3.1
workflow:
conversation_variables: []
environment_variables: []
features:
file_upload: {}
opening_statement: ''
retriever_resource:
enabled: true
sensitive_word_avoidance:
enabled: false
speech_to_text:
enabled: false
suggested_questions: []
suggested_questions_after_answer:
enabled: false
text_to_speech:
enabled: false
language: ''
voice: ''
graph:
edges:
- id: start-llm
source: start
sourceHandle: source
target: llm
targetHandle: target
- id: llm-dufu
source: llm
sourceHandle: source
target: dufu
targetHandle: target
- id: dufu-answer
source: dufu
sourceHandle: source
target: answer
targetHandle: target
nodes:
- data:
desc: ''
title: Start
type: start
variables: []
id: start
position:
x: 80
y: 282
sourcePosition: right
targetPosition: left
type: custom
- data:
context:
enabled: false
variable_selector: []
desc: ''
memory:
query_prompt_template: '{{#sys.query#}}'
window:
enabled: false
size: 10
model:
completion_params:
temperature: 0.7
mode: chat
name: gpt-4o-mini
provider: openai
prompt_template:
- role: system
text: Please output a poem by Li Bai
selected: false
title: Li Bai
type: llm
variables: []
vision:
enabled: false
id: llm
position:
x: 380
y: 282
sourcePosition: right
targetPosition: left
type: custom
- data:
context:
enabled: false
variable_selector: []
desc: ''
model:
completion_params:
temperature: 0.7
mode: chat
name: gpt-4o-mini
provider: openai
prompt_template:
- role: system
text: Please output a poem by Du Fu
selected: false
title: Du Fu
type: llm
variables: []
vision:
enabled: false
id: dufu
position:
x: 680
y: 282
sourcePosition: right
targetPosition: left
type: custom
- data:
answer: |-
# Du Fu
{{#dufu.text#}}
# Li Bai
{{#llm.text#}}
desc: ''
title: Answer
type: answer
variables: []
id: answer
position:
x: 980
y: 282
sourcePosition: right
targetPosition: left
type: custom

75
api/tests/integration_tests/workflow/test_response_stream_filter_integration.py Normal file
View File

@ -0,0 +1,75 @@
"""Integration coverage for Dify's ResponseStreamFilter boundary behavior."""
from core.workflow.workflow_entry import iter_dify_graph_engine_events
from graphon.graph_engine import GraphEngine, GraphEngineConfig
from graphon.graph_engine.command_channels import InMemoryChannel
from graphon.graph_events import GraphRunSucceededEvent, NodeRunStreamChunkEvent
from tests.unit_tests.core.workflow.graph_engine.test_mock_config import MockConfigBuilder
from tests.unit_tests.core.workflow.graph_engine.test_table_runner import WorkflowRunner
def _build_issue_170_mock_config():
runner = WorkflowRunner()
mock_config = (
MockConfigBuilder()
.with_node_output(
"llm",
{
"text": "Quiet Night Thought",
"usage": {
"prompt_tokens": 10,
"completion_tokens": 5,
"total_tokens": 15,
},
"finish_reason": "stop",
},
)
.with_node_output(
"dufu",
{
"text": "Spring View",
"usage": {
"prompt_tokens": 10,
"completion_tokens": 5,
"total_tokens": 15,
},
"finish_reason": "stop",
},
)
.build()
)
return runner, mock_config
def test_dify_response_stream_filter_handles_issue_170_shape() -> None:
runner, mock_config = _build_issue_170_mock_config()
fixture_data = runner.load_fixture("response_stream_filter_issue_170_workflow")
graph, graph_runtime_state = runner.create_graph_from_fixture(
fixture_data=fixture_data,
query="1",
use_mock_factory=True,
mock_config=mock_config,
)
expected_answer = "# Du Fu\n\nSpring View\n\n# Li Bai\n\nQuiet Night Thought"
engine = GraphEngine(
workflow_id="test_workflow",
graph=graph,
graph_runtime_state=graph_runtime_state,
command_channel=InMemoryChannel(),
config=GraphEngineConfig(),
)
events = list(iter_dify_graph_engine_events(engine))
stream_chunk_events = [event for event in events if isinstance(event, NodeRunStreamChunkEvent)]
success_events = [event for event in events if isinstance(event, GraphRunSucceededEvent)]
assert success_events
assert stream_chunk_events
actual_answer = "".join(event.chunk for event in stream_chunk_events)
assert actual_answer.strip() == expected_answer
assert stream_chunk_events[-1].is_final is True
assert success_events[-1].outputs["answer"].strip() == expected_answer
assert actual_answer.strip() == success_events[-1].outputs["answer"].strip()

14
api/tests/unit_tests/core/workflow/graph_engine/test_parallel_human_input_join_resume.py
View File

@ -9,7 +9,7 @@ from core.repositories.human_input_repository import (
HumanInputFormEntity,
HumanInputFormRepository,
)
from core.workflow.node_runtime import DifyFileReferenceFactory, DifyHumanInputNodeRuntime
from core.workflow.node_runtime import DifyHumanInputNodeRuntime
from core.workflow.system_variables import build_system_variables
from graphon.entities import WorkflowStartReason
from graphon.file import File, FileTransferMethod, FileType
@ -186,25 +186,29 @@ def _build_graph(runtime_state: GraphRuntimeState, repo: HumanInputFormRepositor
)
human_a_config = {"id": "human_a", "data": human_data.model_dump()}
human_a_runtime = DifyHumanInputNodeRuntime(graph_init_params.run_context)
human_a_runtime._file_reference_factory = _TestFileReferenceFactory() # type: ignore[attr-defined]
human_a = HumanInputNode(
node_id=human_a_config["id"],
data=human_data,
graph_init_params=graph_init_params,
graph_runtime_state=runtime_state,
form_repository=repo,
file_reference_factory=DifyFileReferenceFactory(graph_init_params.run_context),
runtime=DifyHumanInputNodeRuntime(graph_init_params.run_context),
file_reference_factory=_TestFileReferenceFactory(),
runtime=human_a_runtime,
)
human_b_config = {"id": "human_b", "data": human_data.model_dump()}
human_b_runtime = DifyHumanInputNodeRuntime(graph_init_params.run_context)
human_b_runtime._file_reference_factory = _TestFileReferenceFactory() # type: ignore[attr-defined]
human_b = HumanInputNode(
node_id=human_b_config["id"],
data=human_data,
graph_init_params=graph_init_params,
graph_runtime_state=runtime_state,
form_repository=repo,
file_reference_factory=DifyFileReferenceFactory(graph_init_params.run_context),
runtime=DifyHumanInputNodeRuntime(graph_init_params.run_context),
file_reference_factory=_TestFileReferenceFactory(),
runtime=human_b_runtime,
)
end_data = EndNodeData(

3
api/tests/unit_tests/core/workflow/graph_engine/test_table_runner.py
View File

@ -24,6 +24,7 @@ from core.tools.utils.yaml_utils import _load_yaml_file
from core.workflow.node_factory import DifyNodeFactory, get_default_root_node_id
from core.workflow.system_variables import build_bootstrap_variables, build_system_variables
from core.workflow.variable_pool_initializer import add_node_inputs_to_pool, add_variables_to_pool
from core.workflow.workflow_entry import iter_dify_graph_engine_events
from graphon.entities import GraphInitParams
from graphon.graph import Graph
from graphon.graph_engine import GraphEngine, GraphEngineConfig
@ -386,7 +387,7 @@ class TableTestRunner:
# Execute and collect events
events: list[GraphEngineEvent] = []
for event in engine.run():
for event in iter_dify_graph_engine_events(engine):
events.append(event)
# Check execution success

16
api/tests/unit_tests/core/workflow/graph_engine/test_tool_in_chatflow.py
View File

@ -1,3 +1,4 @@
from core.workflow.workflow_entry import iter_dify_graph_engine_events
from graphon.graph_engine import GraphEngine, GraphEngineConfig
from graphon.graph_engine.command_channels import InMemoryChannel
from graphon.graph_events import (
@ -31,20 +32,17 @@ def test_tool_in_chatflow():
config=GraphEngineConfig(),
)
events = list(engine.run())
events = list(iter_dify_graph_engine_events(engine))
# Check for successful completion
success_events = [e for e in events if isinstance(e, GraphRunSucceededEvent)]
assert len(success_events) > 0, "Workflow should complete successfully"
# Check for streaming events
stream_chunk_events = [e for e in events if isinstance(e, NodeRunStreamChunkEvent)]
stream_chunk_count = len(stream_chunk_events)
assert stream_chunk_count == 1, f"Expected 1 streaming events, but got {stream_chunk_count}"
assert stream_chunk_events[0].chunk == "hello, dify!", (
f"Expected chunk to be 'hello, dify!', but got {stream_chunk_events[0].chunk}"
)
assert len(stream_chunk_events) > 0
assert "".join(event.chunk for event in stream_chunk_events) == "hello, dify!"
assert stream_chunk_events[-1].is_final is True
assert success_events[-1].outputs["answer"] == "hello, dify!"
def test_answer_can_render_llm_structured_output_in_chatflow():
@ -88,7 +86,7 @@ def test_answer_can_render_llm_structured_output_in_chatflow():
config=GraphEngineConfig(),
)
events = list(engine.run())
events = list(iter_dify_graph_engine_events(engine))
success_events = [e for e in events if isinstance(e, GraphRunSucceededEvent)]
assert success_events, "Workflow should complete successfully"

5
api/tests/unit_tests/core/workflow/nodes/human_input/test_entities.py
View File

@ -30,7 +30,7 @@ from core.workflow.human_input_adapter import (
WebAppDeliveryMethod,
_WebAppDeliveryConfig,
)
from core.workflow.node_runtime import DifyFileReferenceFactory, DifyHumanInputNodeRuntime
from core.workflow.node_runtime import DifyHumanInputNodeRuntime
from core.workflow.system_variables import build_system_variables
from graphon.entities import GraphInitParams
from graphon.file import File, FileTransferMethod, FileType
@ -171,12 +171,13 @@ def _build_human_input_node(
typed_node_data = (
node_data if isinstance(node_data, HumanInputNodeData) else HumanInputNodeData.model_validate(node_data)
)
runtime._file_reference_factory = _TestFileReferenceFactory() # type: ignore[attr-defined]
return HumanInputNode(
node_id=node_id,
data=typed_node_data,
graph_init_params=graph_init_params,
graph_runtime_state=graph_runtime_state,
file_reference_factory=DifyFileReferenceFactory(graph_init_params.run_context),
file_reference_factory=_TestFileReferenceFactory(),
runtime=runtime,
)

8
api/tests/unit_tests/core/workflow/nodes/human_input/test_human_input_form_filled_event.py
View File

@ -4,7 +4,7 @@ from types import SimpleNamespace
from typing import Any
from core.app.entities.app_invoke_entities import DIFY_RUN_CONTEXT_KEY, InvokeFrom, UserFrom
from core.workflow.node_runtime import DifyFileReferenceFactory, DifyHumanInputNodeRuntime
from core.workflow.node_runtime import DifyHumanInputNodeRuntime
from core.workflow.system_variables import default_system_variables
from graphon.entities import GraphInitParams
from graphon.enums import BuiltinNodeTypes
@ -67,14 +67,16 @@ def _create_human_input_node(
if isinstance(config["data"], HumanInputNodeData)
else HumanInputNodeData.model_validate(config["data"])
)
runtime = DifyHumanInputNodeRuntime(graph_init_params.run_context)
runtime._file_reference_factory = _TestFileReferenceFactory() # type: ignore[attr-defined]
return HumanInputNode(
node_id=config["id"],
data=node_data,
graph_init_params=graph_init_params,
graph_runtime_state=graph_runtime_state,
form_repository=repo,
file_reference_factory=DifyFileReferenceFactory(graph_init_params.run_context),
runtime=DifyHumanInputNodeRuntime(graph_init_params.run_context),
file_reference_factory=_TestFileReferenceFactory(),
runtime=runtime,
)

24
api/tests/unit_tests/core/workflow/nodes/llm/test_node.py
View File

@ -76,6 +76,7 @@ from graphon.nodes.llm.node import (
_render_jinja2_message,
)
from graphon.nodes.llm.protocols import CredentialsProvider, ModelFactory
from graphon.nodes.llm.reasoning import split_reasoning
from graphon.nodes.llm.runtime_protocols import PromptMessageSerializerProtocol
from graphon.runtime import GraphRuntimeState, VariablePool
from graphon.template_rendering import TemplateRenderError
@ -1271,7 +1272,10 @@ class TestLLMNodeSaveMultiModalImageOutput:
assert llm_node._file_outputs == [mock_file]
assert file == mock_file
mock_file_saver.save_binary_string.assert_called_once_with(
data=b"test-data", mime_type="image/png", file_type=FileType.IMAGE
data=b"test-data",
mime_type="image/png",
file_type=FileType.IMAGE,
extension_override=".png",
)
def test_llm_node_save_url_output(self, llm_node_for_multimodal: tuple[LLMNode, LLMFileSaver]):
@ -1305,8 +1309,9 @@ class TestLLMNodeSaveMultiModalImageOutput:
def test_llm_node_image_file_to_markdown(llm_node: LLMNode):
mock_file = mock.MagicMock(spec=File)
mock_file.type = FileType.IMAGE
mock_file.generate_url.return_value = "https://example.com/image.png"
markdown = llm_node._image_file_to_markdown(mock_file)
markdown = llm_node._saved_file_to_markdown(mock_file)
assert markdown == "![](https://example.com/image.png)"
@ -1378,6 +1383,7 @@ class TestSaveMultimodalOutputAndConvertResultToMarkdown:
data=image_raw_data,
mime_type="image/png",
file_type=FileType.IMAGE,
extension_override=".png",
)
assert mock_saved_file in llm_node._file_outputs
@ -1425,7 +1431,7 @@ class TestReasoningFormat:
</think>Dify is an open source AI platform.
"""
clean_text, reasoning_content = LLMNode._split_reasoning(text_with_think, "separated")
clean_text, reasoning_content = split_reasoning(text_with_think, "separated")
assert clean_text == "Dify is an open source AI platform."
assert reasoning_content == "I need to explain what Dify is. It's an open source AI platform."
@ -1438,7 +1444,7 @@ class TestReasoningFormat:
</think>Dify is an open source AI platform.
"""
clean_text, reasoning_content = LLMNode._split_reasoning(text_with_think, "tagged")
clean_text, reasoning_content = split_reasoning(text_with_think, "tagged")
# Original text unchanged
assert clean_text == text_with_think
@ -1450,7 +1456,7 @@ class TestReasoningFormat:
text_without_think = "This is a simple answer without any thinking blocks."
clean_text, reasoning_content = LLMNode._split_reasoning(text_without_think, "separated")
clean_text, reasoning_content = split_reasoning(text_without_think, "separated")
assert clean_text == text_without_think
assert reasoning_content == ""
@ -1471,7 +1477,7 @@ class TestReasoningFormat:
<think>I need to explain what Dify is. It's an open source AI platform.
</think>Dify is an open source AI platform.
"""
clean_text, reasoning_content = LLMNode._split_reasoning(text_with_think, node_data.reasoning_format)
clean_text, reasoning_content = split_reasoning(text_with_think, node_data.reasoning_format)
assert clean_text == text_with_think
assert reasoning_content == ""
@ -1569,10 +1575,10 @@ def test_handle_invoke_result_streaming_collects_text_metrics_and_structured_out
)
assert events[0] == first_chunk
assert events[1] == StreamChunkEvent(selector=["node-1", "text"], chunk="<think>plan</think>", is_final=False)
assert events[2] == StreamChunkEvent(selector=["node-1", "text"], chunk="answer", is_final=False)
completed = events[3]
assert events[1] == StreamChunkEvent(selector=["node-1", "text"], chunk="answer", is_final=False)
completed = events[2]
assert isinstance(completed, ModelInvokeCompletedEvent)
assert completed.text == "answer"
assert completed.reasoning_content == "plan"

46
api/tests/unit_tests/core/workflow/test_workflow_entry_helpers.py
View File

@ -338,6 +338,52 @@ class TestWorkflowEntryRun:
assert list(entry.run()) == []
def test_iter_dify_graph_engine_events_applies_response_stream_filter(self):
graph_engine = MagicMock()
graph_engine.run.return_value = iter([sentinel.raw_event])
with (
patch.object(
workflow_entry.GraphEventFilterContext,
"from_engine",
return_value=sentinel.filter_context,
) as from_engine,
patch.object(
workflow_entry,
"ResponseStreamFilter",
return_value=sentinel.response_stream_filter,
) as response_stream_filter_cls,
patch.object(
workflow_entry,
"filter_graph_events",
return_value=iter([sentinel.filtered_event]),
) as filter_graph_events,
):
events = list(workflow_entry.iter_dify_graph_engine_events(graph_engine))
assert events == [sentinel.filtered_event]
from_engine.assert_called_once_with(graph_engine)
response_stream_filter_cls.assert_called_once_with()
filter_graph_events.assert_called_once_with(
graph_engine.run.return_value,
context=sentinel.filter_context,
filters=[sentinel.response_stream_filter],
)
def test_run_delegates_to_dify_event_iterator(self):
entry = object.__new__(workflow_entry.WorkflowEntry)
entry.graph_engine = sentinel.graph_engine
with patch.object(
workflow_entry,
"iter_dify_graph_engine_events",
return_value=iter([sentinel.filtered_event]),
) as iter_dify_graph_engine_events:
events = list(entry.run())
assert events == [sentinel.filtered_event]
iter_dify_graph_engine_events.assert_called_once_with(sentinel.graph_engine)
def test_run_emits_failed_event_for_unexpected_errors(self):
entry = object.__new__(workflow_entry.WorkflowEntry)
entry.graph_engine = MagicMock()

23
api/tests/unit_tests/services/test_model_load_balancing_service.py
View File

@ -112,6 +112,29 @@ def test_enable_disable_model_load_balancing_should_call_provider_configuration_
)
@pytest.mark.parametrize(
("method_name", "expected_provider_method"),
[
("enable_model_load_balancing", "enable_model_load_balancing"),
("disable_model_load_balancing", "disable_model_load_balancing"),
],
)
def test_enable_disable_model_load_balancing_uses_model_type_constructor_directly(
method_name: str,
expected_provider_method: str,
service: ModelLoadBalancingService,
monkeypatch: pytest.MonkeyPatch,
) -> None:
provider_configuration = _build_provider_configuration(provider_schema=_build_provider_credential_schema())
service.provider_manager.get_configurations.return_value = {"openai": provider_configuration}
getattr(service, method_name)("tenant-1", "openai", "gpt-4o-mini", "text-generation")
getattr(provider_configuration, expected_provider_method).assert_called_once_with(
model="gpt-4o-mini", model_type=ModelType.LLM
)
@pytest.mark.parametrize(
"method_name",
["enable_model_load_balancing", "disable_model_load_balancing"],

64
api/tests/unit_tests/services/test_model_provider_service.py
View File

@ -368,6 +368,70 @@ class TestModelProviderServiceDelegation:
if method_name == "get_model_credential":
assert result == {"api_key": "x"}
@pytest.mark.parametrize(
("method_name", "method_kwargs", "provider_method_name", "expected_kwargs"),
[
(
"get_model_credential",
{
"tenant_id": "tenant-1",
"provider": "openai",
"model_type": "text-generation",
"model": "gpt-4o",
"credential_id": "cred-1",
},
"get_custom_model_credential",
{"model_type": ModelType.LLM, "model": "gpt-4o", "credential_id": "cred-1"},
),
(
"create_model_credential",
{
"tenant_id": "tenant-1",
"provider": "openai",
"model_type": "text-generation",
"model": "gpt-4o",
"credentials": {"api_key": "x"},
"credential_name": "cred-a",
},
"create_custom_model_credential",
{
"model_type": ModelType.LLM,
"model": "gpt-4o",
"credentials": {"api_key": "x"},
"credential_name": "cred-a",
},
),
(
"remove_model",
{
"tenant_id": "tenant-1",
"provider": "openai",
"model_type": "text-generation",
"model": "gpt-4o",
},
"delete_custom_model",
{"model_type": ModelType.LLM, "model": "gpt-4o"},
),
],
)
def test_custom_model_methods_use_model_type_constructor_directly(
self,
method_name: str,
method_kwargs: dict[str, Any],
provider_method_name: str,
expected_kwargs: dict[str, Any],
monkeypatch: pytest.MonkeyPatch,
) -> None:
service = ModelProviderService()
provider_configuration = MagicMock()
get_provider_config_mock = MagicMock(return_value=provider_configuration)
monkeypatch.setattr(service, "_get_provider_configuration", get_provider_config_mock)
getattr(service, method_name)(**method_kwargs)
get_provider_config_mock.assert_called_once_with("tenant-1", "openai")
getattr(provider_configuration, provider_method_name).assert_called_once_with(**expected_kwargs)
class TestModelProviderServiceListingsAndDefaults:
def test_get_models_by_model_type_should_group_active_non_deprecated_models(self) -> None:

10
api/uv.lock generated
View File

@ -1293,7 +1293,7 @@ dependencies = [
[package.metadata]
requires-dist = [
{ name = "fastapi", marker = "extra == 'server'", specifier = "==0.136.0" },
{ name = "graphon", marker = "extra == 'server'", specifier = "==0.2.2" },
{ name = "graphon", marker = "extra == 'server'", specifier = "==0.5.1" },
{ name = "grpclib", extras = ["protobuf"], marker = "extra == 'grpc'", specifier = ">=0.4.9,<0.5.0" },
{ name = "httpx", specifier = "==0.28.1" },
{ name = "jsonschema", marker = "extra == 'server'", specifier = ">=4.23.0,<5.0.0" },
@ -1636,7 +1636,7 @@ requires-dist = [
{ name = "gmpy2", specifier = ">=2.3.0,<3.0.0" },
{ name = "google-api-python-client", specifier = ">=2.196.0,<3.0.0" },
{ name = "google-cloud-aiplatform", specifier = ">=1.151.0,<2.0.0" },
{ name = "graphon", specifier = "==0.4.0" },
{ name = "graphon", specifier = "==0.5.1" },
{ name = "gunicorn", specifier = ">=26.0.0,<27.0.0" },
{ name = "httpx", extras = ["socks"], specifier = "==0.28.1" },
{ name = "httpx-sse", specifier = "==0.4.3" },
@ -2991,7 +2991,7 @@ httpx = [
[[package]]
name = "graphon"
version = "0.4.0"
version = "0.5.1"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "charset-normalizer" },
@ -3012,9 +3012,9 @@ dependencies = [
{ name = "unstructured", extra = ["docx", "epub", "md", "ppt", "pptx"] },
{ name = "webvtt-py" },
]
sdist = { url = "https://files.pythonhosted.org/packages/76/24/eb1e7983404dcac84816b76ea450e1bb97023e55e00c699d609340bc361e/graphon-0.4.0.tar.gz", hash = "sha256:afb0c7a58f89e09cfa585296429b4d08cd0df80b9ac54d550f88e7d76ec48ee0", size = 261812, upload-time = "2026-05-13T11:48:39.198Z" }
sdist = { url = "https://files.pythonhosted.org/packages/a2/fa/432fa802bcb13f7f51dc323ddef92594b15333eafef181d937ffa554116e/graphon-0.5.1.tar.gz", hash = "sha256:ca38cc62ef3fbc2f3072b68235bcb41e32a6369a1753b46418c1d761c57125fe", size = 269741, upload-time = "2026-06-11T03:01:38.197Z" }
wheels = [
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{ url = "https://files.pythonhosted.org/packages/e9/c5/61e8634b89c320af9453083213e8be436071634dbc69cb14b5fe646763e4/graphon-0.5.1-py3-none-any.whl", hash = "sha256:70b49c244a46fb6e338905210cc895bd67584d9ab1412f6ba3cd4ed284010091", size = 381866, upload-time = "2026-06-11T03:01:36.693Z" },
]
[[package]]

2
dify-agent/Makefile
View File

@ -33,7 +33,7 @@ typecheck:
@uv --directory "$(PROJECT_DIR)" run --project . basedpyright --level error src examples tests
test:
@uv --directory "$(PROJECT_DIR)" run --project . python -m pytest tests
@uv --directory "$(PROJECT_DIR)" run --project . --extra server python -m pytest tests
update-examples:
@uv --directory "$(PROJECT_DIR)" run --project . python -m pytest --update-examples tests/docs/test_examples.py

26
dify-agent/pyproject.toml
View File

@ -17,13 +17,10 @@ dify-agent = "dify_agent.agent_stub.cli.main:main"
dify-agent-stub-server = "dify_agent.agent_stub.server.cli:main"
[project.optional-dependencies]
grpc = [
"grpclib[protobuf]>=0.4.9,<0.5.0",
"protobuf>=6.33.5,<7.0.0",
]
grpc = ["grpclib[protobuf]>=0.4.9,<0.5.0", "protobuf>=6.33.5,<7.0.0"]
server = [
"fastapi==0.136.0",
"graphon==0.2.2",
"graphon==0.5.1",
"jsonschema>=4.23.0,<5.0.0",
"jwcrypto>=1.5.6,<2",
"pydantic-ai-slim[anthropic,google,openai]>=1.85.1,<2.0.0",
@ -35,22 +32,14 @@ server = [
[tool.setuptools.packages.find]
where = ["src"]
include = [
"agenton*",
"agenton_collections*",
"dify_agent*",
]
include = ["agenton*", "agenton_collections*", "dify_agent*"]
[tool.pyright]
include = ["src", "examples", "tests"]
venvPath = "."
venv = ".venv"
pythonVersion = "3.12"
extraPaths = [
"src",
"examples/agenton",
"examples/dify_agent",
]
extraPaths = ["src", "examples/agenton", "examples/dify_agent"]
[tool.pytest.ini_options]
testpaths = ["tests"]
@ -59,12 +48,7 @@ python_files = ["test_*.py", "*_test.py"]
[tool.ruff]
line-length = 120
target-version = "py312"
include = [
"src/**/*.py",
"examples/**/*.py",
"tests/**/*.py",
"docs/**/*.py",
]
include = ["src/**/*.py", "examples/**/*.py", "tests/**/*.py", "docs/**/*.py"]
[dependency-groups]
dev = [

1
dify-agent/tests/local/dify_agent/layers/execution_context/__init__.py Normal file
View File

@ -0,0 +1 @@

1
dify-agent/tests/local/dify_agent/layers/shell/__init__.py Normal file
View File

@ -0,0 +1 @@

2
dify-agent/tests/local/test_packaging.py
View File

@ -16,7 +16,7 @@ CLIENT_SHARED_DTO_DEPENDENCIES = {
SERVER_RUNTIME_DEPENDENCIES = {
"fastapi==0.136.0",
"graphon==0.2.2",
"graphon==0.5.1",
"jsonschema>=4.23.0,<5.0.0",
"jwcrypto>=1.5.6,<2",
"pydantic-ai-slim[anthropic,google,openai]>=1.85.1,<2.0.0",

8
dify-agent/uv.lock generated
View File

@ -628,7 +628,7 @@ docs = [
[package.metadata]
requires-dist = [
{ name = "fastapi", marker = "extra == 'server'", specifier = "==0.136.0" },
{ name = "graphon", marker = "extra == 'server'", specifier = "==0.2.2" },
{ name = "graphon", marker = "extra == 'server'", specifier = "==0.5.1" },
{ name = "grpclib", extras = ["protobuf"], marker = "extra == 'grpc'", specifier = ">=0.4.9,<0.5.0" },
{ name = "httpx", specifier = "==0.28.1" },
{ name = "jsonschema", marker = "extra == 'server'", specifier = ">=4.23.0,<5.0.0" },
@ -808,7 +808,7 @@ wheels = [
[[package]]
name = "graphon"
version = "0.2.2"
version = "0.5.1"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "charset-normalizer" },
@ -829,9 +829,9 @@ dependencies = [
{ name = "unstructured", extra = ["docx", "epub", "md", "ppt", "pptx"] },
{ name = "webvtt-py" },
]
sdist = { url = "https://files.pythonhosted.org/packages/08/50/e745a79c5f742f88f6011a1f7c9ba2c2f9cc1beedd982f0b192f1ab8c748/graphon-0.2.2.tar.gz", hash = "sha256:141f0de536171850f1af6f738dc66f0285aadd3c097f1dad2a038636789e0aa5", size = 236360, upload-time = "2026-04-17T08:52:28.047Z" }
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[[package]]