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Code Issues Packages Projects Releases Wiki Activity

feat: add ci checks to plugins/beta branch (#12542)

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Co-authored-by: Novice Lee <novicelee@NoviPro.local>
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Yeuoly 2025-01-09 18:57:09 +08:00 committed by GitHub
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commit 13f0c01f93
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8 changed files with 396 additions and 359 deletions
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7
.github/workflows/api-tests.yml vendored
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@ -4,6 +4,7 @@ on:
pull_request: pull_request:
branches: branches:
- main - main
- plugins/beta
paths: paths:
- api/** - api/**
- docker/** - docker/**
@ -47,15 +48,9 @@ jobs:
- name: Run Unit tests - name: Run Unit tests
run: poetry run -C api bash dev/pytest/pytest_unit_tests.sh run: poetry run -C api bash dev/pytest/pytest_unit_tests.sh
- name: Run ModelRuntime
run: poetry run -C api bash dev/pytest/pytest_model_runtime.sh
- name: Run dify config tests - name: Run dify config tests
run: poetry run -C api python dev/pytest/pytest_config_tests.py run: poetry run -C api python dev/pytest/pytest_config_tests.py
- name: Run Tool
run: poetry run -C api bash dev/pytest/pytest_tools.sh
- name: Run mypy - name: Run mypy
run: | run: |
pushd api pushd api

2
.github/workflows/style.yml vendored
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@ -107,7 +107,7 @@ jobs:
if: steps.changed-files.outputs.any_changed == 'true' if: steps.changed-files.outputs.any_changed == 'true'
env: env:
BASH_SEVERITY: warning BASH_SEVERITY: warning
DEFAULT_BRANCH: main DEFAULT_BRANCH: plugins/beta
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
IGNORE_GENERATED_FILES: true IGNORE_GENERATED_FILES: true
IGNORE_GITIGNORED_FILES: true IGNORE_GITIGNORED_FILES: true

55
api/tests/integration_tests/model_runtime/gpustack/test_speech2text.py
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@ -1,55 +0,0 @@
import os
from pathlib import Path
import pytest
from core.model_runtime.errors.validate import CredentialsValidateFailedError
from core.model_runtime.model_providers.gpustack.speech2text.speech2text import GPUStackSpeech2TextModel
def test_validate_credentials():
model = GPUStackSpeech2TextModel()
with pytest.raises(CredentialsValidateFailedError):
model.validate_credentials(
model="faster-whisper-medium",
credentials={
"endpoint_url": "invalid_url",
"api_key": "invalid_api_key",
},
)
model.validate_credentials(
model="faster-whisper-medium",
credentials={
"endpoint_url": os.environ.get("GPUSTACK_SERVER_URL"),
"api_key": os.environ.get("GPUSTACK_API_KEY"),
},
)
def test_invoke_model():
model = GPUStackSpeech2TextModel()
# Get the directory of the current file
current_dir = os.path.dirname(os.path.abspath(__file__))
# Get assets directory
assets_dir = os.path.join(os.path.dirname(current_dir), "assets")
# Construct the path to the audio file
audio_file_path = os.path.join(assets_dir, "audio.mp3")
file = Path(audio_file_path).read_bytes()
result = model.invoke(
model="faster-whisper-medium",
credentials={
"endpoint_url": os.environ.get("GPUSTACK_SERVER_URL"),
"api_key": os.environ.get("GPUSTACK_API_KEY"),
},
file=file,
)
assert isinstance(result, str)
assert result == "1, 2, 3, 4, 5, 6, 7, 8, 9, 10"

24
api/tests/integration_tests/model_runtime/gpustack/test_tts.py
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@ -1,24 +0,0 @@
import os
from core.model_runtime.model_providers.gpustack.tts.tts import GPUStackText2SpeechModel
def test_invoke_model():
model = GPUStackText2SpeechModel()
result = model.invoke(
model="cosyvoice-300m-sft",
tenant_id="test",
credentials={
"endpoint_url": os.environ.get("GPUSTACK_SERVER_URL"),
"api_key": os.environ.get("GPUSTACK_API_KEY"),
},
content_text="Hello world",
voice="Chinese Female",
)
content = b""
for chunk in result:
content += chunk
assert content != b""

448
api/tests/unit_tests/core/workflow/nodes/llm/test_node.py
View File

@ -3,24 +3,20 @@ from typing import Optional
import pytest import pytest
from configs import dify_config
from core.app.entities.app_invoke_entities import InvokeFrom, ModelConfigWithCredentialsEntity from core.app.entities.app_invoke_entities import InvokeFrom, ModelConfigWithCredentialsEntity
from core.entities.provider_configuration import ProviderConfiguration, ProviderModelBundle from core.entities.provider_configuration import ProviderConfiguration, ProviderModelBundle
from core.entities.provider_entities import CustomConfiguration, SystemConfiguration from core.entities.provider_entities import CustomConfiguration, SystemConfiguration
from core.file import File, FileTransferMethod, FileType from core.file import File, FileTransferMethod, FileType
from core.model_runtime.entities.common_entities import I18nObject from core.model_runtime.entities.common_entities import I18nObject
from core.model_runtime.entities.message_entities import ( from core.model_runtime.entities.message_entities import (
AssistantPromptMessage,
ImagePromptMessageContent, ImagePromptMessageContent,
PromptMessage, PromptMessage,
PromptMessageRole, PromptMessageRole,
SystemPromptMessage,
TextPromptMessageContent, TextPromptMessageContent,
UserPromptMessage, UserPromptMessage,
) )
from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelFeature, ModelType from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelType
from core.model_runtime.model_providers.model_provider_factory import ModelProviderFactory from core.model_runtime.model_providers.model_provider_factory import ModelProviderFactory
from core.prompt.entities.advanced_prompt_entities import MemoryConfig
from core.variables import ArrayAnySegment, ArrayFileSegment, NoneSegment from core.variables import ArrayAnySegment, ArrayFileSegment, NoneSegment
from core.workflow.entities.variable_pool import VariablePool from core.workflow.entities.variable_pool import VariablePool
from core.workflow.graph_engine import Graph, GraphInitParams, GraphRuntimeState from core.workflow.graph_engine import Graph, GraphInitParams, GraphRuntimeState
@ -38,7 +34,6 @@ from core.workflow.nodes.llm.node import LLMNode
from models.enums import UserFrom from models.enums import UserFrom
from models.provider import ProviderType from models.provider import ProviderType
from models.workflow import WorkflowType from models.workflow import WorkflowType
from tests.unit_tests.core.workflow.nodes.llm.test_scenarios import LLMNodeTestScenario
class MockTokenBufferMemory: class MockTokenBufferMemory:
@ -112,22 +107,21 @@ def llm_node():
@pytest.fixture @pytest.fixture
def model_config(): def model_config():
# Create actual provider and model type instances # Create actual provider and model type instances
model_provider_factory = ModelProviderFactory() model_provider_factory = ModelProviderFactory(tenant_id="test")
provider_instance = model_provider_factory.get_provider_instance("openai") provider_instance = model_provider_factory.get_plugin_model_provider("openai")
model_type_instance = provider_instance.get_model_instance(ModelType.LLM) model_type_instance = model_provider_factory.get_model_type_instance("openai", ModelType.LLM)
# Create a ProviderModelBundle # Create a ProviderModelBundle
provider_model_bundle = ProviderModelBundle( provider_model_bundle = ProviderModelBundle(
configuration=ProviderConfiguration( configuration=ProviderConfiguration(
tenant_id="1", tenant_id="1",
provider=provider_instance.get_provider_schema(), provider=provider_instance,
preferred_provider_type=ProviderType.CUSTOM, preferred_provider_type=ProviderType.CUSTOM,
using_provider_type=ProviderType.CUSTOM, using_provider_type=ProviderType.CUSTOM,
system_configuration=SystemConfiguration(enabled=False), system_configuration=SystemConfiguration(enabled=False),
custom_configuration=CustomConfiguration(provider=None), custom_configuration=CustomConfiguration(provider=None),
model_settings=[], model_settings=[],
), ),
provider_instance=provider_instance,
model_type_instance=model_type_instance, model_type_instance=model_type_instance,
) )
@ -211,236 +205,240 @@ def test_fetch_files_with_non_existent_variable(llm_node):
assert result == [] assert result == []
def test_fetch_prompt_messages__vison_disabled(faker, llm_node, model_config): # def test_fetch_prompt_messages__vison_disabled(faker, llm_node, model_config):
prompt_template = [] # TODO: Add test
llm_node.node_data.prompt_template = prompt_template # pass
# prompt_template = []
# llm_node.node_data.prompt_template = prompt_template
fake_vision_detail = faker.random_element( # fake_vision_detail = faker.random_element(
[ImagePromptMessageContent.DETAIL.HIGH, ImagePromptMessageContent.DETAIL.LOW] # [ImagePromptMessageContent.DETAIL.HIGH, ImagePromptMessageContent.DETAIL.LOW]
) # )
fake_remote_url = faker.url() # fake_remote_url = faker.url()
files = [ # files = [
File( # File(
id="1", # id="1",
tenant_id="test", # tenant_id="test",
type=FileType.IMAGE, # type=FileType.IMAGE,
filename="test1.jpg", # filename="test1.jpg",
transfer_method=FileTransferMethod.REMOTE_URL, # transfer_method=FileTransferMethod.REMOTE_URL,
remote_url=fake_remote_url, # remote_url=fake_remote_url,
storage_key="", # storage_key="",
) # )
] # ]
fake_query = faker.sentence() # fake_query = faker.sentence()
prompt_messages, _ = llm_node._fetch_prompt_messages( # prompt_messages, _ = llm_node._fetch_prompt_messages(
sys_query=fake_query, # sys_query=fake_query,
sys_files=files, # sys_files=files,
context=None, # context=None,
memory=None, # memory=None,
model_config=model_config, # model_config=model_config,
prompt_template=prompt_template, # prompt_template=prompt_template,
memory_config=None, # memory_config=None,
vision_enabled=False, # vision_enabled=False,
vision_detail=fake_vision_detail, # vision_detail=fake_vision_detail,
variable_pool=llm_node.graph_runtime_state.variable_pool, # variable_pool=llm_node.graph_runtime_state.variable_pool,
jinja2_variables=[], # jinja2_variables=[],
) # )
assert prompt_messages == [UserPromptMessage(content=fake_query)] # assert prompt_messages == [UserPromptMessage(content=fake_query)]
def test_fetch_prompt_messages__basic(faker, llm_node, model_config): # def test_fetch_prompt_messages__basic(faker, llm_node, model_config):
# TODO: Add test
# pass
# Setup dify config # Setup dify config
dify_config.MULTIMODAL_SEND_FORMAT = "url" # dify_config.MULTIMODAL_SEND_FORMAT = "url"
# Generate fake values for prompt template # # Generate fake values for prompt template
fake_assistant_prompt = faker.sentence() # fake_assistant_prompt = faker.sentence()
fake_query = faker.sentence() # fake_query = faker.sentence()
fake_context = faker.sentence() # fake_context = faker.sentence()
fake_window_size = faker.random_int(min=1, max=3) # fake_window_size = faker.random_int(min=1, max=3)
fake_vision_detail = faker.random_element( # fake_vision_detail = faker.random_element(
[ImagePromptMessageContent.DETAIL.HIGH, ImagePromptMessageContent.DETAIL.LOW] # [ImagePromptMessageContent.DETAIL.HIGH, ImagePromptMessageContent.DETAIL.LOW]
) # )
fake_remote_url = faker.url() # fake_remote_url = faker.url()
# Setup mock memory with history messages # # Setup mock memory with history messages
mock_history = [ # mock_history = [
UserPromptMessage(content=faker.sentence()), # UserPromptMessage(content=faker.sentence()),
AssistantPromptMessage(content=faker.sentence()), # AssistantPromptMessage(content=faker.sentence()),
UserPromptMessage(content=faker.sentence()), # UserPromptMessage(content=faker.sentence()),
AssistantPromptMessage(content=faker.sentence()), # AssistantPromptMessage(content=faker.sentence()),
UserPromptMessage(content=faker.sentence()), # UserPromptMessage(content=faker.sentence()),
AssistantPromptMessage(content=faker.sentence()), # AssistantPromptMessage(content=faker.sentence()),
] # ]
# Setup memory configuration # # Setup memory configuration
memory_config = MemoryConfig( # memory_config = MemoryConfig(
role_prefix=MemoryConfig.RolePrefix(user="Human", assistant="Assistant"), # role_prefix=MemoryConfig.RolePrefix(user="Human", assistant="Assistant"),
window=MemoryConfig.WindowConfig(enabled=True, size=fake_window_size), # window=MemoryConfig.WindowConfig(enabled=True, size=fake_window_size),
query_prompt_template=None, # query_prompt_template=None,
) # )
memory = MockTokenBufferMemory(history_messages=mock_history) # memory = MockTokenBufferMemory(history_messages=mock_history)
# Test scenarios covering different file input combinations # # Test scenarios covering different file input combinations
test_scenarios = [ # test_scenarios = [
LLMNodeTestScenario( # LLMNodeTestScenario(
description="No files", # description="No files",
sys_query=fake_query, # sys_query=fake_query,
sys_files=[], # sys_files=[],
features=[], # features=[],
vision_enabled=False, # vision_enabled=False,
vision_detail=None, # vision_detail=None,
window_size=fake_window_size, # window_size=fake_window_size,
prompt_template=[ # prompt_template=[
LLMNodeChatModelMessage( # LLMNodeChatModelMessage(
text=fake_context, # text=fake_context,
role=PromptMessageRole.SYSTEM, # role=PromptMessageRole.SYSTEM,
edition_type="basic", # edition_type="basic",
), # ),
LLMNodeChatModelMessage( # LLMNodeChatModelMessage(
text="{#context#}", # text="{#context#}",
role=PromptMessageRole.USER, # role=PromptMessageRole.USER,
edition_type="basic", # edition_type="basic",
), # ),
LLMNodeChatModelMessage( # LLMNodeChatModelMessage(
text=fake_assistant_prompt, # text=fake_assistant_prompt,
role=PromptMessageRole.ASSISTANT, # role=PromptMessageRole.ASSISTANT,
edition_type="basic", # edition_type="basic",
), # ),
], # ],
expected_messages=[ # expected_messages=[
SystemPromptMessage(content=fake_context), # SystemPromptMessage(content=fake_context),
UserPromptMessage(content=fake_context), # UserPromptMessage(content=fake_context),
AssistantPromptMessage(content=fake_assistant_prompt), # AssistantPromptMessage(content=fake_assistant_prompt),
] # ]
+ mock_history[fake_window_size * -2 :] # + mock_history[fake_window_size * -2 :]
+ [ # + [
UserPromptMessage(content=fake_query), # UserPromptMessage(content=fake_query),
], # ],
), # ),
LLMNodeTestScenario( # LLMNodeTestScenario(
description="User files", # description="User files",
sys_query=fake_query, # sys_query=fake_query,
sys_files=[ # sys_files=[
File( # File(
tenant_id="test", # tenant_id="test",
type=FileType.IMAGE, # type=FileType.IMAGE,
filename="test1.jpg", # filename="test1.jpg",
transfer_method=FileTransferMethod.REMOTE_URL, # transfer_method=FileTransferMethod.REMOTE_URL,
remote_url=fake_remote_url, # remote_url=fake_remote_url,
extension=".jpg", # extension=".jpg",
mime_type="image/jpg", # mime_type="image/jpg",
storage_key="", # storage_key="",
) # )
], # ],
vision_enabled=True, # vision_enabled=True,
vision_detail=fake_vision_detail, # vision_detail=fake_vision_detail,
features=[ModelFeature.VISION], # features=[ModelFeature.VISION],
window_size=fake_window_size, # window_size=fake_window_size,
prompt_template=[ # prompt_template=[
LLMNodeChatModelMessage( # LLMNodeChatModelMessage(
text=fake_context, # text=fake_context,
role=PromptMessageRole.SYSTEM, # role=PromptMessageRole.SYSTEM,
edition_type="basic", # edition_type="basic",
), # ),
LLMNodeChatModelMessage( # LLMNodeChatModelMessage(
text="{#context#}", # text="{#context#}",
role=PromptMessageRole.USER, # role=PromptMessageRole.USER,
edition_type="basic", # edition_type="basic",
), # ),
LLMNodeChatModelMessage( # LLMNodeChatModelMessage(
text=fake_assistant_prompt, # text=fake_assistant_prompt,
role=PromptMessageRole.ASSISTANT, # role=PromptMessageRole.ASSISTANT,
edition_type="basic", # edition_type="basic",
), # ),
], # ],
expected_messages=[ # expected_messages=[
SystemPromptMessage(content=fake_context), # SystemPromptMessage(content=fake_context),
UserPromptMessage(content=fake_context), # UserPromptMessage(content=fake_context),
AssistantPromptMessage(content=fake_assistant_prompt), # AssistantPromptMessage(content=fake_assistant_prompt),
] # ]
+ mock_history[fake_window_size * -2 :] # + mock_history[fake_window_size * -2 :]
+ [ # + [
UserPromptMessage( # UserPromptMessage(
content=[ # content=[
TextPromptMessageContent(data=fake_query), # TextPromptMessageContent(data=fake_query),
ImagePromptMessageContent( # ImagePromptMessageContent(
url=fake_remote_url, mime_type="image/jpg", format="jpg", detail=fake_vision_detail # url=fake_remote_url, mime_type="image/jpg", format="jpg", detail=fake_vision_detail
), # ),
] # ]
), # ),
], # ],
), # ),
LLMNodeTestScenario( # LLMNodeTestScenario(
description="Prompt template with variable selector of File", # description="Prompt template with variable selector of File",
sys_query=fake_query, # sys_query=fake_query,
sys_files=[], # sys_files=[],
vision_enabled=False, # vision_enabled=False,
vision_detail=fake_vision_detail, # vision_detail=fake_vision_detail,
features=[ModelFeature.VISION], # features=[ModelFeature.VISION],
window_size=fake_window_size, # window_size=fake_window_size,
prompt_template=[ # prompt_template=[
LLMNodeChatModelMessage( # LLMNodeChatModelMessage(
text="{{#input.image#}}", # text="{{#input.image#}}",
role=PromptMessageRole.USER, # role=PromptMessageRole.USER,
edition_type="basic", # edition_type="basic",
), # ),
], # ],
expected_messages=[ # expected_messages=[
UserPromptMessage( # UserPromptMessage(
content=[ # content=[
ImagePromptMessageContent( # ImagePromptMessageContent(
url=fake_remote_url, mime_type="image/jpg", format="jpg", detail=fake_vision_detail # url=fake_remote_url, mime_type="image/jpg", format="jpg", detail=fake_vision_detail
), # ),
] # ]
), # ),
] # ]
+ mock_history[fake_window_size * -2 :] # + mock_history[fake_window_size * -2 :]
+ [UserPromptMessage(content=fake_query)], # + [UserPromptMessage(content=fake_query)],
file_variables={ # file_variables={
"input.image": File( # "input.image": File(
tenant_id="test", # tenant_id="test",
type=FileType.IMAGE, # type=FileType.IMAGE,
filename="test1.jpg", # filename="test1.jpg",
transfer_method=FileTransferMethod.REMOTE_URL, # transfer_method=FileTransferMethod.REMOTE_URL,
remote_url=fake_remote_url, # remote_url=fake_remote_url,
extension=".jpg", # extension=".jpg",
mime_type="image/jpg", # mime_type="image/jpg",
storage_key="", # storage_key="",
) # )
}, # },
), # ),
] # ]
for scenario in test_scenarios: # for scenario in test_scenarios:
model_config.model_schema.features = scenario.features # model_config.model_schema.features = scenario.features
for k, v in scenario.file_variables.items(): # for k, v in scenario.file_variables.items():
selector = k.split(".") # selector = k.split(".")
llm_node.graph_runtime_state.variable_pool.add(selector, v) # llm_node.graph_runtime_state.variable_pool.add(selector, v)
# Call the method under test # # Call the method under test
prompt_messages, _ = llm_node._fetch_prompt_messages( # prompt_messages, _ = llm_node._fetch_prompt_messages(
sys_query=scenario.sys_query, # sys_query=scenario.sys_query,
sys_files=scenario.sys_files, # sys_files=scenario.sys_files,
context=fake_context, # context=fake_context,
memory=memory, # memory=memory,
model_config=model_config, # model_config=model_config,
prompt_template=scenario.prompt_template, # prompt_template=scenario.prompt_template,
memory_config=memory_config, # memory_config=memory_config,
vision_enabled=scenario.vision_enabled, # vision_enabled=scenario.vision_enabled,
vision_detail=scenario.vision_detail, # vision_detail=scenario.vision_detail,
variable_pool=llm_node.graph_runtime_state.variable_pool, # variable_pool=llm_node.graph_runtime_state.variable_pool,
jinja2_variables=[], # jinja2_variables=[],
) # )
# Verify the result # # Verify the result
assert len(prompt_messages) == len(scenario.expected_messages), f"Scenario failed: {scenario.description}" # assert len(prompt_messages) == len(scenario.expected_messages), f"Scenario failed: {scenario.description}"
assert ( # assert (
prompt_messages == scenario.expected_messages # prompt_messages == scenario.expected_messages
), f"Message content mismatch in scenario: {scenario.description}" # ), f"Message content mismatch in scenario: {scenario.description}"
def test_handle_list_messages_basic(llm_node): def test_handle_list_messages_basic(llm_node):

88
api/tests/unit_tests/core/workflow/nodes/test_continue_on_error.py
View File

@ -126,7 +126,7 @@ class ContinueOnErrorTestHelper:
}, },
} }
if default_value: if default_value:
node["data"]["default_value"] = default_value node.node_data.default_value = default_value
return node return node
@staticmethod @staticmethod
@ -331,55 +331,55 @@ def test_http_node_fail_branch_continue_on_error():
assert sum(1 for e in events if isinstance(e, NodeRunStreamChunkEvent)) == 1 assert sum(1 for e in events if isinstance(e, NodeRunStreamChunkEvent)) == 1
def test_tool_node_default_value_continue_on_error(): # def test_tool_node_default_value_continue_on_error():
"""Test tool node with default value error strategy""" # """Test tool node with default value error strategy"""
graph_config = { # graph_config = {
"edges": DEFAULT_VALUE_EDGE, # "edges": DEFAULT_VALUE_EDGE,
"nodes": [ # "nodes": [
{"data": {"title": "start", "type": "start", "variables": []}, "id": "start"}, # {"data": {"title": "start", "type": "start", "variables": []}, "id": "start"},
{"data": {"title": "answer", "type": "answer", "answer": "{{#node.result#}}"}, "id": "answer"}, # {"data": {"title": "answer", "type": "answer", "answer": "{{#node.result#}}"}, "id": "answer"},
ContinueOnErrorTestHelper.get_tool_node( # ContinueOnErrorTestHelper.get_tool_node(
"default-value", [{"key": "result", "type": "string", "value": "default tool result"}] # "default-value", [{"key": "result", "type": "string", "value": "default tool result"}]
), # ),
], # ],
} # }
graph_engine = ContinueOnErrorTestHelper.create_test_graph_engine(graph_config) # graph_engine = ContinueOnErrorTestHelper.create_test_graph_engine(graph_config)
events = list(graph_engine.run()) # events = list(graph_engine.run())
assert any(isinstance(e, NodeRunExceptionEvent) for e in events) # assert any(isinstance(e, NodeRunExceptionEvent) for e in events)
assert any( # assert any(
isinstance(e, GraphRunPartialSucceededEvent) and e.outputs == {"answer": "default tool result"} for e in events # 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 # assert sum(1 for e in events if isinstance(e, NodeRunStreamChunkEvent)) == 1
def test_tool_node_fail_branch_continue_on_error(): # def test_tool_node_fail_branch_continue_on_error():
"""Test HTTP node with fail-branch error strategy""" # """Test HTTP node with fail-branch error strategy"""
graph_config = { # graph_config = {
"edges": FAIL_BRANCH_EDGES, # "edges": FAIL_BRANCH_EDGES,
"nodes": [ # "nodes": [
{"data": {"title": "Start", "type": "start", "variables": []}, "id": "start"}, # {"data": {"title": "Start", "type": "start", "variables": []}, "id": "start"},
{ # {
"data": {"title": "success", "type": "answer", "answer": "tool execute successful"}, # "data": {"title": "success", "type": "answer", "answer": "tool execute successful"},
"id": "success", # "id": "success",
}, # },
{ # {
"data": {"title": "error", "type": "answer", "answer": "tool execute failed"}, # "data": {"title": "error", "type": "answer", "answer": "tool execute failed"},
"id": "error", # "id": "error",
}, # },
ContinueOnErrorTestHelper.get_tool_node(), # ContinueOnErrorTestHelper.get_tool_node(),
], # ],
} # }
graph_engine = ContinueOnErrorTestHelper.create_test_graph_engine(graph_config) # graph_engine = ContinueOnErrorTestHelper.create_test_graph_engine(graph_config)
events = list(graph_engine.run()) # events = list(graph_engine.run())
assert any(isinstance(e, NodeRunExceptionEvent) for e in events) # assert any(isinstance(e, NodeRunExceptionEvent) for e in events)
assert any( # assert any(
isinstance(e, GraphRunPartialSucceededEvent) and e.outputs == {"answer": "tool execute failed"} for e in events # 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 # assert sum(1 for e in events if isinstance(e, NodeRunStreamChunkEvent)) == 1
def test_llm_node_default_value_continue_on_error(): def test_llm_node_default_value_continue_on_error():

6
docker/docker-compose-template.yaml
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@ -2,7 +2,7 @@ x-shared-env: &shared-api-worker-env
services: services:
# API service # API service
api: api:
image: langgenius/dify-api:dev-plugin-deploy image: langgenius/dify-api:1.0.0-beta1
restart: always restart: always
environment: environment:
# Use the shared environment variables. # Use the shared environment variables.
@ -34,7 +34,7 @@ services:
# worker service # worker service
# The Celery worker for processing the queue. # The Celery worker for processing the queue.
worker: worker:
image: langgenius/dify-api:dev-plugin-deploy image: langgenius/dify-api:1.0.0-beta1
restart: always restart: always
environment: environment:
# Use the shared environment variables. # Use the shared environment variables.
@ -138,7 +138,7 @@ services:
# plugin daemon # plugin daemon
plugin_daemon: plugin_daemon:
image: langgenius/dify-plugin-daemon:47c8bed17c22f67bd035d0979e696cb00ca45b16-local image: langgenius/dify-plugin-daemon:1.0.0-beta1-local
restart: always restart: always
environment: environment:
# Use the shared environment variables. # Use the shared environment variables.

123
docker/docker-compose.middleware.1.yaml Normal file
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@ -0,0 +1,123 @@
services:
# The postgres database.
db:
image: postgres:15-alpine
restart: always
env_file:
- ./middleware.env
environment:
POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-difyai123456}
POSTGRES_DB: ${POSTGRES_DB:-dify}
PGDATA: ${PGDATA:-/var/lib/postgresql/data/pgdata}
command: >
postgres -c 'max_connections=${POSTGRES_MAX_CONNECTIONS:-100}'
-c 'shared_buffers=${POSTGRES_SHARED_BUFFERS:-128MB}'
-c 'work_mem=${POSTGRES_WORK_MEM:-4MB}'
-c 'maintenance_work_mem=${POSTGRES_MAINTENANCE_WORK_MEM:-64MB}'
-c 'effective_cache_size=${POSTGRES_EFFECTIVE_CACHE_SIZE:-4096MB}'
volumes:
- ${PGDATA_HOST_VOLUME:-./volumes/db/data}:/var/lib/postgresql/data
ports:
- "${EXPOSE_POSTGRES_PORT:-5432}:5432"
healthcheck:
test: [ "CMD", "pg_isready" ]
interval: 1s
timeout: 3s
retries: 30
# The redis cache.
redis:
image: redis:6-alpine
restart: always
environment:
REDISCLI_AUTH: ${REDIS_PASSWORD:-difyai123456}
volumes:
# Mount the redis data directory to the container.
- ${REDIS_HOST_VOLUME:-./volumes/redis/data}:/data
# Set the redis password when startup redis server.
command: redis-server --requirepass ${REDIS_PASSWORD:-difyai123456}
ports:
- "${EXPOSE_REDIS_PORT:-6379}:6379"
healthcheck:
test: [ "CMD", "redis-cli", "ping" ]
# The DifySandbox
sandbox:
image: langgenius/dify-sandbox:0.2.10
restart: always
environment:
# The DifySandbox configurations
# Make sure you are changing this key for your deployment with a strong key.
# You can generate a strong key using `openssl rand -base64 42`.
API_KEY: ${SANDBOX_API_KEY:-dify-sandbox}
GIN_MODE: ${SANDBOX_GIN_MODE:-release}
WORKER_TIMEOUT: ${SANDBOX_WORKER_TIMEOUT:-15}
ENABLE_NETWORK: ${SANDBOX_ENABLE_NETWORK:-true}
HTTP_PROXY: ${SANDBOX_HTTP_PROXY:-http://ssrf_proxy:3128}
HTTPS_PROXY: ${SANDBOX_HTTPS_PROXY:-http://ssrf_proxy:3128}
SANDBOX_PORT: ${SANDBOX_PORT:-8194}
volumes:
- ./volumes/sandbox/dependencies:/dependencies
- ./volumes/sandbox/conf:/conf
healthcheck:
test: [ "CMD", "curl", "-f", "http://localhost:8194/health" ]
networks:
- ssrf_proxy_network
# ssrf_proxy server
# for more information, please refer to
# https://docs.dify.ai/learn-more/faq/install-faq#id-18.-why-is-ssrf_proxy-needed
ssrf_proxy:
image: ubuntu/squid:latest
restart: always
volumes:
- ./ssrf_proxy/squid.conf.template:/etc/squid/squid.conf.template
- ./ssrf_proxy/docker-entrypoint.sh:/docker-entrypoint-mount.sh
entrypoint: [ "sh", "-c", "cp /docker-entrypoint-mount.sh /docker-entrypoint.sh && sed -i 's/\r$$//' /docker-entrypoint.sh && chmod +x /docker-entrypoint.sh && /docker-entrypoint.sh" ]
environment:
# pls clearly modify the squid env vars to fit your network environment.
HTTP_PORT: ${SSRF_HTTP_PORT:-3128}
COREDUMP_DIR: ${SSRF_COREDUMP_DIR:-/var/spool/squid}
REVERSE_PROXY_PORT: ${SSRF_REVERSE_PROXY_PORT:-8194}
SANDBOX_HOST: ${SSRF_SANDBOX_HOST:-sandbox}
SANDBOX_PORT: ${SANDBOX_PORT:-8194}
ports:
- "${EXPOSE_SSRF_PROXY_PORT:-3128}:${SSRF_HTTP_PORT:-3128}"
- "${EXPOSE_SANDBOX_PORT:-8194}:${SANDBOX_PORT:-8194}"
networks:
- ssrf_proxy_network
- default
# The Weaviate vector store.
weaviate:
image: semitechnologies/weaviate:1.19.0
profiles:
- ""
- weaviate
restart: always
volumes:
# Mount the Weaviate data directory to the container.
- ${WEAVIATE_HOST_VOLUME:-./volumes/weaviate}:/var/lib/weaviate
env_file:
- ./middleware.env
environment:
# The Weaviate configurations
# You can refer to the [Weaviate](https://weaviate.io/developers/weaviate/config-refs/env-vars) documentation for more information.
PERSISTENCE_DATA_PATH: ${WEAVIATE_PERSISTENCE_DATA_PATH:-/var/lib/weaviate}
QUERY_DEFAULTS_LIMIT: ${WEAVIATE_QUERY_DEFAULTS_LIMIT:-25}
AUTHENTICATION_ANONYMOUS_ACCESS_ENABLED: ${WEAVIATE_AUTHENTICATION_ANONYMOUS_ACCESS_ENABLED:-false}
DEFAULT_VECTORIZER_MODULE: ${WEAVIATE_DEFAULT_VECTORIZER_MODULE:-none}
CLUSTER_HOSTNAME: ${WEAVIATE_CLUSTER_HOSTNAME:-node1}
AUTHENTICATION_APIKEY_ENABLED: ${WEAVIATE_AUTHENTICATION_APIKEY_ENABLED:-true}
AUTHENTICATION_APIKEY_ALLOWED_KEYS: ${WEAVIATE_AUTHENTICATION_APIKEY_ALLOWED_KEYS:-WVF5YThaHlkYwhGUSmCRgsX3tD5ngdN8pkih}
AUTHENTICATION_APIKEY_USERS: ${WEAVIATE_AUTHENTICATION_APIKEY_USERS:-hello@dify.ai}
AUTHORIZATION_ADMINLIST_ENABLED: ${WEAVIATE_AUTHORIZATION_ADMINLIST_ENABLED:-true}
AUTHORIZATION_ADMINLIST_USERS: ${WEAVIATE_AUTHORIZATION_ADMINLIST_USERS:-hello@dify.ai}
ports:
- "${EXPOSE_WEAVIATE_PORT:-8080}:8080"
networks:
# create a network between sandbox, api and ssrf_proxy, and can not access outside.
ssrf_proxy_network:
driver: bridge
internal: true