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Introduce Plugins (#13836)

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This commit is contained in:
Yeuoly
2025-02-17 17:05:13 +08:00
committed by GitHub
parent 222df44d21
commit 403e2d58b9
3272 changed files with 66339 additions and 281594 deletions
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50
api/tests/integration_tests/workflow/nodes/__mock/model.py Normal file
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@@ -0,0 +1,50 @@
from unittest.mock import MagicMock
from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEntity
from core.entities.provider_configuration import ProviderConfiguration, ProviderModelBundle
from core.entities.provider_entities import CustomConfiguration, CustomProviderConfiguration, SystemConfiguration
from core.model_manager import ModelInstance
from core.model_runtime.entities.model_entities import ModelType
from core.model_runtime.model_providers.model_provider_factory import ModelProviderFactory
from models.provider import ProviderType
def get_mocked_fetch_model_config(
provider: str,
model: str,
mode: str,
credentials: dict,
):
model_provider_factory = ModelProviderFactory(tenant_id="test_tenant")
model_type_instance = model_provider_factory.get_model_type_instance(provider, ModelType.LLM)
provider_model_bundle = ProviderModelBundle(
configuration=ProviderConfiguration(
tenant_id="1",
provider=model_provider_factory.get_provider_schema(provider),
preferred_provider_type=ProviderType.CUSTOM,
using_provider_type=ProviderType.CUSTOM,
system_configuration=SystemConfiguration(enabled=False),
custom_configuration=CustomConfiguration(provider=CustomProviderConfiguration(credentials=credentials)),
model_settings=[],
),
model_type_instance=model_type_instance,
)
model_instance = ModelInstance(provider_model_bundle=provider_model_bundle, model=model)
model_schema = model_provider_factory.get_model_schema(
provider=provider,
model_type=model_type_instance.model_type,
model=model,
credentials=credentials,
)
assert model_schema is not None
model_config = ModelConfigWithCredentialsEntity(
model=model,
provider=provider,
mode=mode,
credentials=credentials,
parameters={},
model_schema=model_schema,
provider_model_bundle=provider_model_bundle,
)
return MagicMock(return_value=(model_instance, model_config))

95
api/tests/integration_tests/workflow/nodes/test_llm.py
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@@ -7,12 +7,7 @@ from unittest.mock import MagicMock
import pytest
from core.app.entities.app_invoke_entities import InvokeFrom, ModelConfigWithCredentialsEntity
from core.entities.provider_configuration import ProviderConfiguration, ProviderModelBundle
from core.entities.provider_entities import CustomConfiguration, CustomProviderConfiguration, SystemConfiguration
from core.model_manager import ModelInstance
from core.model_runtime.entities.model_entities import ModelType
from core.model_runtime.model_providers import ModelProviderFactory
from core.app.entities.app_invoke_entities import InvokeFrom
from core.workflow.entities.variable_pool import VariablePool
from core.workflow.enums import SystemVariableKey
from core.workflow.graph_engine.entities.graph import Graph
@@ -22,11 +17,11 @@ from core.workflow.nodes.event import RunCompletedEvent
from core.workflow.nodes.llm.node import LLMNode
from extensions.ext_database import db
from models.enums import UserFrom
from models.provider import ProviderType
from models.workflow import WorkflowNodeExecutionStatus, WorkflowType
from tests.integration_tests.workflow.nodes.__mock.model import get_mocked_fetch_model_config
"""FOR MOCK FIXTURES, DO NOT REMOVE"""
from tests.integration_tests.model_runtime.__mock.openai import setup_openai_mock
from tests.integration_tests.model_runtime.__mock.plugin_daemon import setup_model_mock
from tests.integration_tests.workflow.nodes.__mock.code_executor import setup_code_executor_mock
@@ -81,15 +76,19 @@ def init_llm_node(config: dict) -> LLMNode:
return node
@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True)
def test_execute_llm(setup_openai_mock):
def test_execute_llm(setup_model_mock):
node = init_llm_node(
config={
"id": "llm",
"data": {
"title": "123",
"type": "llm",
"model": {"provider": "openai", "name": "gpt-3.5-turbo", "mode": "chat", "completion_params": {}},
"model": {
"provider": "langgenius/openai/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#}}"},
@@ -103,38 +102,15 @@ def test_execute_llm(setup_openai_mock):
credentials = {"openai_api_key": os.environ.get("OPENAI_API_KEY")}
provider_instance = ModelProviderFactory().get_provider_instance("openai")
model_type_instance = provider_instance.get_model_instance(ModelType.LLM)
provider_model_bundle = ProviderModelBundle(
configuration=ProviderConfiguration(
tenant_id="1",
provider=provider_instance.get_provider_schema(),
preferred_provider_type=ProviderType.CUSTOM,
using_provider_type=ProviderType.CUSTOM,
system_configuration=SystemConfiguration(enabled=False),
custom_configuration=CustomConfiguration(provider=CustomProviderConfiguration(credentials=credentials)),
model_settings=[],
),
provider_instance=provider_instance,
model_type_instance=model_type_instance,
)
model_instance = ModelInstance(provider_model_bundle=provider_model_bundle, model="gpt-3.5-turbo")
model_schema = model_type_instance.get_model_schema("gpt-3.5-turbo")
assert model_schema is not None
model_config = ModelConfigWithCredentialsEntity(
model="gpt-3.5-turbo",
provider="openai",
mode="chat",
credentials=credentials,
parameters={},
model_schema=model_schema,
provider_model_bundle=provider_model_bundle,
)
# Mock db.session.close()
db.session.close = MagicMock()
node._fetch_model_config = MagicMock(return_value=(model_instance, model_config))
node._fetch_model_config = get_mocked_fetch_model_config(
provider="langgenius/openai/openai",
model="gpt-3.5-turbo",
mode="chat",
credentials=credentials,
)
# execute node
result = node._run()
@@ -150,8 +126,7 @@ def test_execute_llm(setup_openai_mock):
@pytest.mark.parametrize("setup_code_executor_mock", [["none"]], indirect=True)
@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True)
def test_execute_llm_with_jinja2(setup_code_executor_mock, setup_openai_mock):
def test_execute_llm_with_jinja2(setup_code_executor_mock, setup_model_mock):
"""
Test execute LLM node with jinja2
"""
@@ -191,39 +166,15 @@ def test_execute_llm_with_jinja2(setup_code_executor_mock, setup_openai_mock):
credentials = {"openai_api_key": os.environ.get("OPENAI_API_KEY")}
provider_instance = ModelProviderFactory().get_provider_instance("openai")
model_type_instance = provider_instance.get_model_instance(ModelType.LLM)
provider_model_bundle = ProviderModelBundle(
configuration=ProviderConfiguration(
tenant_id="1",
provider=provider_instance.get_provider_schema(),
preferred_provider_type=ProviderType.CUSTOM,
using_provider_type=ProviderType.CUSTOM,
system_configuration=SystemConfiguration(enabled=False),
custom_configuration=CustomConfiguration(provider=CustomProviderConfiguration(credentials=credentials)),
model_settings=[],
),
provider_instance=provider_instance,
model_type_instance=model_type_instance,
)
model_instance = ModelInstance(provider_model_bundle=provider_model_bundle, model="gpt-3.5-turbo")
model_schema = model_type_instance.get_model_schema("gpt-3.5-turbo")
assert model_schema is not None
model_config = ModelConfigWithCredentialsEntity(
model="gpt-3.5-turbo",
provider="openai",
mode="chat",
credentials=credentials,
parameters={},
model_schema=model_schema,
provider_model_bundle=provider_model_bundle,
)
# Mock db.session.close()
db.session.close = MagicMock()
node._fetch_model_config = MagicMock(return_value=(model_instance, model_config))
node._fetch_model_config = get_mocked_fetch_model_config(
provider="langgenius/openai/openai",
model="gpt-3.5-turbo",
mode="chat",
credentials=credentials,
)
# execute node
result = node._run()

128
api/tests/integration_tests/workflow/nodes/test_parameter_extractor.py
View File

@@ -4,14 +4,7 @@ import uuid
from typing import Optional
from unittest.mock import MagicMock
import pytest
from core.app.entities.app_invoke_entities import InvokeFrom, ModelConfigWithCredentialsEntity
from core.entities.provider_configuration import ProviderConfiguration, ProviderModelBundle
from core.entities.provider_entities import CustomConfiguration, CustomProviderConfiguration, SystemConfiguration
from core.model_manager import ModelInstance
from core.model_runtime.entities.model_entities import ModelType
from core.model_runtime.model_providers.model_provider_factory import ModelProviderFactory
from core.app.entities.app_invoke_entities import InvokeFrom
from core.workflow.entities.variable_pool import VariablePool
from core.workflow.enums import SystemVariableKey
from core.workflow.graph_engine.entities.graph import Graph
@@ -20,49 +13,11 @@ from core.workflow.graph_engine.entities.graph_runtime_state import GraphRuntime
from core.workflow.nodes.parameter_extractor.parameter_extractor_node import ParameterExtractorNode
from extensions.ext_database import db
from models.enums import UserFrom
from models.provider import ProviderType
from tests.integration_tests.workflow.nodes.__mock.model import get_mocked_fetch_model_config
"""FOR MOCK FIXTURES, DO NOT REMOVE"""
from models.workflow import WorkflowNodeExecutionStatus, WorkflowType
from tests.integration_tests.model_runtime.__mock.anthropic import setup_anthropic_mock
from tests.integration_tests.model_runtime.__mock.openai import setup_openai_mock
def get_mocked_fetch_model_config(
provider: str,
model: str,
mode: str,
credentials: dict,
):
provider_instance = ModelProviderFactory().get_provider_instance(provider)
model_type_instance = provider_instance.get_model_instance(ModelType.LLM)
provider_model_bundle = ProviderModelBundle(
configuration=ProviderConfiguration(
tenant_id="1",
provider=provider_instance.get_provider_schema(),
preferred_provider_type=ProviderType.CUSTOM,
using_provider_type=ProviderType.CUSTOM,
system_configuration=SystemConfiguration(enabled=False),
custom_configuration=CustomConfiguration(provider=CustomProviderConfiguration(credentials=credentials)),
model_settings=[],
),
provider_instance=provider_instance,
model_type_instance=model_type_instance,
)
model_instance = ModelInstance(provider_model_bundle=provider_model_bundle, model=model)
model_schema = model_type_instance.get_model_schema(model)
assert model_schema is not None
model_config = ModelConfigWithCredentialsEntity(
model=model,
provider=provider,
mode=mode,
credentials=credentials,
parameters={},
model_schema=model_schema,
provider_model_bundle=provider_model_bundle,
)
return MagicMock(return_value=(model_instance, model_config))
from tests.integration_tests.model_runtime.__mock.plugin_daemon import setup_model_mock
def get_mocked_fetch_memory(memory_text: str):
@@ -129,8 +84,7 @@ def init_parameter_extractor_node(config: dict):
)
@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True)
def test_function_calling_parameter_extractor(setup_openai_mock):
def test_function_calling_parameter_extractor(setup_model_mock):
"""
Test function calling for parameter extractor.
"""
@@ -140,7 +94,12 @@ def test_function_calling_parameter_extractor(setup_openai_mock):
"data": {
"title": "123",
"type": "parameter-extractor",
"model": {"provider": "openai", "name": "gpt-3.5-turbo", "mode": "chat", "completion_params": {}},
"model": {
"provider": "langgenius/openai/openai",
"name": "gpt-3.5-turbo",
"mode": "chat",
"completion_params": {},
},
"query": ["sys", "query"],
"parameters": [{"name": "location", "type": "string", "description": "location", "required": True}],
"instruction": "",
@@ -151,25 +110,13 @@ def test_function_calling_parameter_extractor(setup_openai_mock):
)
node._fetch_model_config = get_mocked_fetch_model_config(
provider="openai",
provider="langgenius/openai/openai",
model="gpt-3.5-turbo",
mode="chat",
credentials={"openai_api_key": os.environ.get("OPENAI_API_KEY")},
)
db.session.close = MagicMock()
# construct variable pool
pool = VariablePool(
system_variables={
SystemVariableKey.QUERY: "what's the weather in SF",
SystemVariableKey.FILES: [],
SystemVariableKey.CONVERSATION_ID: "abababa",
SystemVariableKey.USER_ID: "aaa",
},
user_inputs={},
environment_variables=[],
)
result = node._run()
assert result.status == WorkflowNodeExecutionStatus.SUCCEEDED
@@ -178,8 +125,7 @@ def test_function_calling_parameter_extractor(setup_openai_mock):
assert result.outputs.get("__reason") == None
@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True)
def test_instructions(setup_openai_mock):
def test_instructions(setup_model_mock):
"""
Test chat parameter extractor.
"""
@@ -189,7 +135,12 @@ def test_instructions(setup_openai_mock):
"data": {
"title": "123",
"type": "parameter-extractor",
"model": {"provider": "openai", "name": "gpt-3.5-turbo", "mode": "chat", "completion_params": {}},
"model": {
"provider": "langgenius/openai/openai",
"name": "gpt-3.5-turbo",
"mode": "chat",
"completion_params": {},
},
"query": ["sys", "query"],
"parameters": [{"name": "location", "type": "string", "description": "location", "required": True}],
"reasoning_mode": "function_call",
@@ -200,7 +151,7 @@ def test_instructions(setup_openai_mock):
)
node._fetch_model_config = get_mocked_fetch_model_config(
provider="openai",
provider="langgenius/openai/openai",
model="gpt-3.5-turbo",
mode="chat",
credentials={"openai_api_key": os.environ.get("OPENAI_API_KEY")},
@@ -224,8 +175,7 @@ def test_instructions(setup_openai_mock):
assert "what's the weather in SF" in prompt.get("text")
@pytest.mark.parametrize("setup_anthropic_mock", [["none"]], indirect=True)
def test_chat_parameter_extractor(setup_anthropic_mock):
def test_chat_parameter_extractor(setup_model_mock):
"""
Test chat parameter extractor.
"""
@@ -235,7 +185,12 @@ def test_chat_parameter_extractor(setup_anthropic_mock):
"data": {
"title": "123",
"type": "parameter-extractor",
"model": {"provider": "anthropic", "name": "claude-2", "mode": "chat", "completion_params": {}},
"model": {
"provider": "langgenius/openai/openai",
"name": "gpt-3.5-turbo",
"mode": "chat",
"completion_params": {},
},
"query": ["sys", "query"],
"parameters": [{"name": "location", "type": "string", "description": "location", "required": True}],
"reasoning_mode": "prompt",
@@ -246,10 +201,10 @@ def test_chat_parameter_extractor(setup_anthropic_mock):
)
node._fetch_model_config = get_mocked_fetch_model_config(
provider="anthropic",
model="claude-2",
provider="langgenius/openai/openai",
model="gpt-3.5-turbo",
mode="chat",
credentials={"anthropic_api_key": os.environ.get("ANTHROPIC_API_KEY")},
credentials={"openai_api_key": os.environ.get("OPENAI_API_KEY")},
)
db.session.close = MagicMock()
@@ -271,8 +226,7 @@ def test_chat_parameter_extractor(setup_anthropic_mock):
assert '<structure>\n{"type": "object"' in prompt.get("text")
@pytest.mark.parametrize("setup_openai_mock", [["completion"]], indirect=True)
def test_completion_parameter_extractor(setup_openai_mock):
def test_completion_parameter_extractor(setup_model_mock):
"""
Test completion parameter extractor.
"""
@@ -283,7 +237,7 @@ def test_completion_parameter_extractor(setup_openai_mock):
"title": "123",
"type": "parameter-extractor",
"model": {
"provider": "openai",
"provider": "langgenius/openai/openai",
"name": "gpt-3.5-turbo-instruct",
"mode": "completion",
"completion_params": {},
@@ -298,7 +252,7 @@ def test_completion_parameter_extractor(setup_openai_mock):
)
node._fetch_model_config = get_mocked_fetch_model_config(
provider="openai",
provider="langgenius/openai/openai",
model="gpt-3.5-turbo-instruct",
mode="completion",
credentials={"openai_api_key": os.environ.get("OPENAI_API_KEY")},
@@ -331,7 +285,7 @@ def test_extract_json_response():
"title": "123",
"type": "parameter-extractor",
"model": {
"provider": "openai",
"provider": "langgenius/openai/openai",
"name": "gpt-3.5-turbo-instruct",
"mode": "completion",
"completion_params": {},
@@ -357,8 +311,7 @@ def test_extract_json_response():
assert result["location"] == "kawaii"
@pytest.mark.parametrize("setup_anthropic_mock", [["none"]], indirect=True)
def test_chat_parameter_extractor_with_memory(setup_anthropic_mock):
def test_chat_parameter_extractor_with_memory(setup_model_mock):
"""
Test chat parameter extractor with memory.
"""
@@ -368,7 +321,12 @@ def test_chat_parameter_extractor_with_memory(setup_anthropic_mock):
"data": {
"title": "123",
"type": "parameter-extractor",
"model": {"provider": "anthropic", "name": "claude-2", "mode": "chat", "completion_params": {}},
"model": {
"provider": "langgenius/openai/openai",
"name": "gpt-3.5-turbo",
"mode": "chat",
"completion_params": {},
},
"query": ["sys", "query"],
"parameters": [{"name": "location", "type": "string", "description": "location", "required": True}],
"reasoning_mode": "prompt",
@@ -379,10 +337,10 @@ def test_chat_parameter_extractor_with_memory(setup_anthropic_mock):
)
node._fetch_model_config = get_mocked_fetch_model_config(
provider="anthropic",
model="claude-2",
provider="langgenius/openai/openai",
model="gpt-3.5-turbo",
mode="chat",
credentials={"anthropic_api_key": os.environ.get("ANTHROPIC_API_KEY")},
credentials={"openai_api_key": os.environ.get("OPENAI_API_KEY")},
)
node._fetch_memory = get_mocked_fetch_memory("customized memory")
db.session.close = MagicMock()

60
api/tests/integration_tests/workflow/nodes/test_tool.py
View File

@@ -1,13 +1,15 @@
import time
import uuid
from unittest.mock import MagicMock
from core.app.entities.app_invoke_entities import InvokeFrom
from core.workflow.entities.node_entities import NodeRunResult
from core.tools.utils.configuration import ToolParameterConfigurationManager
from core.workflow.entities.variable_pool import VariablePool
from core.workflow.enums import SystemVariableKey
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.event import RunCompletedEvent
from core.workflow.nodes.tool.tool_node import ToolNode
from models.enums import UserFrom
from models.workflow import WorkflowNodeExecutionStatus, WorkflowType
@@ -63,31 +65,28 @@ def test_tool_variable_invoke():
"data": {
"title": "a",
"desc": "a",
"provider_id": "maths",
"provider_id": "time",
"provider_type": "builtin",
"provider_name": "maths",
"tool_name": "eval_expression",
"tool_label": "eval_expression",
"provider_name": "time",
"tool_name": "current_time",
"tool_label": "current_time",
"tool_configurations": {},
"tool_parameters": {
"expression": {
"type": "variable",
"value": ["1", "123", "args1"],
}
},
"tool_parameters": {},
},
}
)
ToolParameterConfigurationManager.decrypt_tool_parameters = MagicMock(return_value={"format": "%Y-%m-%d %H:%M:%S"})
node.graph_runtime_state.variable_pool.add(["1", "123", "args1"], "1+1")
# execute node
result = node._run()
assert isinstance(result, NodeRunResult)
assert result.status == WorkflowNodeExecutionStatus.SUCCEEDED
assert result.outputs is not None
assert "2" in result.outputs["text"]
assert result.outputs["files"] == []
for item in result:
if isinstance(item, RunCompletedEvent):
assert item.run_result.status == WorkflowNodeExecutionStatus.SUCCEEDED
assert item.run_result.outputs is not None
assert item.run_result.outputs.get("text") is not None
def test_tool_mixed_invoke():
@@ -97,28 +96,25 @@ def test_tool_mixed_invoke():
"data": {
"title": "a",
"desc": "a",
"provider_id": "maths",
"provider_id": "time",
"provider_type": "builtin",
"provider_name": "maths",
"tool_name": "eval_expression",
"tool_label": "eval_expression",
"tool_configurations": {},
"tool_parameters": {
"expression": {
"type": "mixed",
"value": "{{#1.args1#}}",
}
"provider_name": "time",
"tool_name": "current_time",
"tool_label": "current_time",
"tool_configurations": {
"format": "%Y-%m-%d %H:%M:%S",
},
"tool_parameters": {},
},
}
)
node.graph_runtime_state.variable_pool.add(["1", "args1"], "1+1")
ToolParameterConfigurationManager.decrypt_tool_parameters = MagicMock(return_value={"format": "%Y-%m-%d %H:%M:%S"})
# execute node
result = node._run()
assert isinstance(result, NodeRunResult)
assert result.status == WorkflowNodeExecutionStatus.SUCCEEDED
assert result.outputs is not None
assert "2" in result.outputs["text"]
assert result.outputs["files"] == []
for item in result:
if isinstance(item, RunCompletedEvent):
assert item.run_result.status == WorkflowNodeExecutionStatus.SUCCEEDED
assert item.run_result.outputs is not None
assert item.run_result.outputs.get("text") is not None