diff --git a/.github/workflows/style.yml b/.github/workflows/style.yml index c01f408628..302cd36229 100644 --- a/.github/workflows/style.yml +++ b/.github/workflows/style.yml @@ -43,6 +43,10 @@ jobs: if: steps.changed-files.outputs.any_changed == 'true' run: uv sync --project api --dev + - name: Run Import Linter + if: steps.changed-files.outputs.any_changed == 'true' + run: uv run --directory api --dev lint-imports + - name: Run Basedpyright Checks if: steps.changed-files.outputs.any_changed == 'true' run: dev/basedpyright-check diff --git a/api/.importlinter b/api/.importlinter index 4380e8c18e..98fe5f50bb 100644 --- a/api/.importlinter +++ b/api/.importlinter @@ -22,14 +22,15 @@ containers = ignore_imports = core.workflow.nodes.base.node -> core.workflow.graph_events core.workflow.nodes.iteration.iteration_node -> core.workflow.graph_events + core.workflow.nodes.loop.loop_node -> core.workflow.graph_events + + core.workflow.nodes.node_factory -> core.workflow.graph core.workflow.nodes.iteration.iteration_node -> core.workflow.graph_engine core.workflow.nodes.iteration.iteration_node -> core.workflow.graph core.workflow.nodes.iteration.iteration_node -> core.workflow.graph_engine.command_channels - core.workflow.nodes.loop.loop_node -> core.workflow.graph_events core.workflow.nodes.loop.loop_node -> core.workflow.graph_engine core.workflow.nodes.loop.loop_node -> core.workflow.graph core.workflow.nodes.loop.loop_node -> core.workflow.graph_engine.command_channels - core.workflow.nodes.node_factory -> core.workflow.graph [importlinter:contract:rsc] name = RSC @@ -57,9 +58,9 @@ layers = orchestration command_processing event_management - error_handling + error_handler graph_traversal - state_management + graph_state_manager worker_management domain containers = @@ -86,14 +87,6 @@ forbidden_modules = core.workflow.graph_engine.command_processing core.workflow.graph_engine.event_management -[importlinter:contract:error-handling-strategies] -name = Error Handling Strategies -type = independence -modules = - core.workflow.graph_engine.error_handling.abort_strategy - core.workflow.graph_engine.error_handling.retry_strategy - core.workflow.graph_engine.error_handling.fail_branch_strategy - core.workflow.graph_engine.error_handling.default_value_strategy [importlinter:contract:graph-traversal-components] name = Graph Traversal Components diff --git a/api/configs/remote_settings_sources/apollo/utils.py b/api/configs/remote_settings_sources/apollo/utils.py index cff187954d..40731448a0 100644 --- a/api/configs/remote_settings_sources/apollo/utils.py +++ b/api/configs/remote_settings_sources/apollo/utils.py @@ -29,7 +29,7 @@ def no_key_cache_key(namespace: str, key: str) -> str: # Returns whether the obtained value is obtained, and None if it does not -def get_value_from_dict(namespace_cache: dict[str, Any] | None, key: str) -> Any | None: +def get_value_from_dict(namespace_cache: dict[str, Any] | None, key: str) -> Any: if namespace_cache: kv_data = namespace_cache.get(CONFIGURATIONS) if kv_data is None: diff --git a/api/core/app/apps/common/workflow_response_converter.py b/api/core/app/apps/common/workflow_response_converter.py index b1c7ae0df5..7c7a4fd6ac 100644 --- a/api/core/app/apps/common/workflow_response_converter.py +++ b/api/core/app/apps/common/workflow_response_converter.py @@ -355,7 +355,7 @@ class WorkflowResponseConverter: else WorkflowNodeExecutionStatus.FAILED, error=None, elapsed_time=(naive_utc_now() - event.start_at).total_seconds(), - total_tokens=event.metadata.get("total_tokens", 0) if event.metadata else 0, + total_tokens=(lambda x: x if isinstance(x, int) else 0)(event.metadata.get("total_tokens", 0)), execution_metadata=event.metadata, finished_at=int(time.time()), steps=event.steps, @@ -442,7 +442,7 @@ class WorkflowResponseConverter: else WorkflowNodeExecutionStatus.FAILED, error=None, elapsed_time=(naive_utc_now() - event.start_at).total_seconds(), - total_tokens=event.metadata.get("total_tokens", 0) if event.metadata else 0, + total_tokens=(lambda x: x if isinstance(x, int) else 0)(event.metadata.get("total_tokens", 0)), execution_metadata=event.metadata, finished_at=int(time.time()), steps=event.steps, diff --git a/api/core/app/apps/workflow_app_runner.py b/api/core/app/apps/workflow_app_runner.py index 9b104cdace..056e03fa14 100644 --- a/api/core/app/apps/workflow_app_runner.py +++ b/api/core/app/apps/workflow_app_runner.py @@ -384,7 +384,6 @@ class WorkflowBasedAppRunner: predecessor_node_id=event.predecessor_node_id, in_iteration_id=event.in_iteration_id, in_loop_id=event.in_loop_id, - parallel_mode_run_id=event.parallel_mode_run_id, inputs=inputs, process_data=process_data, outputs=outputs, @@ -406,7 +405,6 @@ class WorkflowBasedAppRunner: predecessor_node_id=event.predecessor_node_id, in_iteration_id=event.in_iteration_id, in_loop_id=event.in_loop_id, - parallel_mode_run_id=event.parallel_mode_run_id, agent_strategy=event.agent_strategy, provider_type=event.provider_type, provider_id=event.provider_id, diff --git a/api/core/app/entities/queue_entities.py b/api/core/app/entities/queue_entities.py index 376f52b3b5..76d22d8ac3 100644 --- a/api/core/app/entities/queue_entities.py +++ b/api/core/app/entities/queue_entities.py @@ -1,9 +1,9 @@ from collections.abc import Mapping, Sequence from datetime import datetime from enum import StrEnum, auto -from typing import Any, Optional +from typing import Any -from pydantic import BaseModel +from pydantic import BaseModel, Field from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk from core.rag.entities.citation_metadata import RetrievalSourceMetadata @@ -79,9 +79,9 @@ class QueueIterationStartEvent(AppQueueEvent): start_at: datetime node_run_index: int - inputs: Mapping[str, Any] | None = None + inputs: Mapping[str, object] = Field(default_factory=dict) predecessor_node_id: str | None = None - metadata: Mapping[str, Any] | None = None + metadata: Mapping[str, object] = Field(default_factory=dict) class QueueIterationNextEvent(AppQueueEvent): @@ -97,7 +97,7 @@ class QueueIterationNextEvent(AppQueueEvent): node_type: NodeType node_title: str node_run_index: int - output: Optional[Any] = None # output for the current iteration + output: Any = None # output for the current iteration class QueueIterationCompletedEvent(AppQueueEvent): @@ -114,9 +114,9 @@ class QueueIterationCompletedEvent(AppQueueEvent): start_at: datetime node_run_index: int - inputs: Mapping[str, Any] | None = None - outputs: Mapping[str, Any] | None = None - metadata: Mapping[str, Any] | None = None + inputs: Mapping[str, object] = Field(default_factory=dict) + outputs: Mapping[str, object] = Field(default_factory=dict) + metadata: Mapping[str, object] = Field(default_factory=dict) steps: int = 0 error: str | None = None @@ -143,9 +143,9 @@ class QueueLoopStartEvent(AppQueueEvent): start_at: datetime node_run_index: int - inputs: Mapping[str, Any] | None = None + inputs: Mapping[str, object] = Field(default_factory=dict) predecessor_node_id: str | None = None - metadata: Mapping[str, Any] | None = None + metadata: Mapping[str, object] = Field(default_factory=dict) class QueueLoopNextEvent(AppQueueEvent): @@ -171,7 +171,7 @@ class QueueLoopNextEvent(AppQueueEvent): parallel_mode_run_id: str | None = None """iteration run in parallel mode run id""" node_run_index: int - output: Optional[Any] = None # output for the current loop + output: Any = None # output for the current loop class QueueLoopCompletedEvent(AppQueueEvent): @@ -185,7 +185,7 @@ class QueueLoopCompletedEvent(AppQueueEvent): node_id: str node_type: NodeType node_title: str - parallel_id: Optional[str] = None + parallel_id: str | None = None """parallel id if node is in parallel""" parallel_start_node_id: str | None = None """parallel start node id if node is in parallel""" @@ -196,9 +196,9 @@ class QueueLoopCompletedEvent(AppQueueEvent): start_at: datetime node_run_index: int - inputs: Mapping[str, Any] | None = None - outputs: Mapping[str, Any] | None = None - metadata: Mapping[str, Any] | None = None + inputs: Mapping[str, object] = Field(default_factory=dict) + outputs: Mapping[str, object] = Field(default_factory=dict) + metadata: Mapping[str, object] = Field(default_factory=dict) steps: int = 0 error: str | None = None @@ -299,7 +299,7 @@ class QueueWorkflowSucceededEvent(AppQueueEvent): """ event: QueueEvent = QueueEvent.WORKFLOW_SUCCEEDED - outputs: dict[str, Any] | None = None + outputs: Mapping[str, object] = Field(default_factory=dict) class QueueWorkflowFailedEvent(AppQueueEvent): @@ -319,7 +319,7 @@ class QueueWorkflowPartialSuccessEvent(AppQueueEvent): event: QueueEvent = QueueEvent.WORKFLOW_PARTIAL_SUCCEEDED exceptions_count: int - outputs: dict[str, Any] | None = None + outputs: Mapping[str, object] = Field(default_factory=dict) class QueueNodeStartedEvent(AppQueueEvent): @@ -334,16 +334,16 @@ class QueueNodeStartedEvent(AppQueueEvent): node_title: str node_type: NodeType node_run_index: int = 1 # FIXME(-LAN-): may not used - predecessor_node_id: Optional[str] = None - parallel_id: Optional[str] = None - parallel_start_node_id: Optional[str] = None - parent_parallel_id: Optional[str] = None - parent_parallel_start_node_id: Optional[str] = None - in_iteration_id: Optional[str] = None - in_loop_id: Optional[str] = None + predecessor_node_id: str | None = None + parallel_id: str | None = None + parallel_start_node_id: str | None = None + parent_parallel_id: str | None = None + parent_parallel_start_node_id: str | None = None + in_iteration_id: str | None = None + in_loop_id: str | None = None start_at: datetime - parallel_mode_run_id: Optional[str] = None - agent_strategy: Optional[AgentNodeStrategyInit] = None + parallel_mode_run_id: str | None = None + agent_strategy: AgentNodeStrategyInit | None = None # FIXME(-LAN-): only for ToolNode, need to refactor provider_type: str # should be a core.tools.entities.tool_entities.ToolProviderType @@ -360,7 +360,7 @@ class QueueNodeSucceededEvent(AppQueueEvent): node_execution_id: str node_id: str node_type: NodeType - parallel_id: Optional[str] = None + parallel_id: str | None = None """parallel id if node is in parallel""" parallel_start_node_id: str | None = None """parallel start node id if node is in parallel""" @@ -374,12 +374,12 @@ class QueueNodeSucceededEvent(AppQueueEvent): """loop id if node is in loop""" start_at: datetime - inputs: Mapping[str, Any] | None = None - process_data: Mapping[str, Any] | None = None - outputs: Mapping[str, Any] | None = None + inputs: Mapping[str, object] = Field(default_factory=dict) + process_data: Mapping[str, object] = Field(default_factory=dict) + outputs: Mapping[str, object] = Field(default_factory=dict) execution_metadata: Mapping[WorkflowNodeExecutionMetadataKey, Any] | None = None - error: Optional[str] = None + error: str | None = None class QueueAgentLogEvent(AppQueueEvent): @@ -395,7 +395,7 @@ class QueueAgentLogEvent(AppQueueEvent): error: str | None = None status: str data: Mapping[str, Any] - metadata: Mapping[str, Any] | None = None + metadata: Mapping[str, object] = Field(default_factory=dict) node_id: str @@ -404,9 +404,9 @@ class QueueNodeRetryEvent(QueueNodeStartedEvent): event: QueueEvent = QueueEvent.RETRY - inputs: Mapping[str, Any] | None = None - process_data: Mapping[str, Any] | None = None - outputs: Mapping[str, Any] | None = None + inputs: Mapping[str, object] = Field(default_factory=dict) + process_data: Mapping[str, object] = Field(default_factory=dict) + outputs: Mapping[str, object] = Field(default_factory=dict) execution_metadata: Mapping[WorkflowNodeExecutionMetadataKey, Any] | None = None error: str @@ -423,7 +423,7 @@ class QueueNodeExceptionEvent(AppQueueEvent): node_execution_id: str node_id: str node_type: NodeType - parallel_id: Optional[str] = None + parallel_id: str | None = None """parallel id if node is in parallel""" parallel_start_node_id: str | None = None """parallel start node id if node is in parallel""" @@ -437,9 +437,9 @@ class QueueNodeExceptionEvent(AppQueueEvent): """loop id if node is in loop""" start_at: datetime - inputs: Mapping[str, Any] | None = None - process_data: Mapping[str, Any] | None = None - outputs: Mapping[str, Any] | None = None + inputs: Mapping[str, object] = Field(default_factory=dict) + process_data: Mapping[str, object] = Field(default_factory=dict) + outputs: Mapping[str, object] = Field(default_factory=dict) execution_metadata: Mapping[WorkflowNodeExecutionMetadataKey, Any] | None = None error: str @@ -455,16 +455,16 @@ class QueueNodeFailedEvent(AppQueueEvent): node_execution_id: str node_id: str node_type: NodeType - parallel_id: Optional[str] = None - in_iteration_id: Optional[str] = None + parallel_id: str | None = None + in_iteration_id: str | None = None """iteration id if node is in iteration""" in_loop_id: str | None = None """loop id if node is in loop""" start_at: datetime - inputs: Mapping[str, Any] | None = None - process_data: Mapping[str, Any] | None = None - outputs: Mapping[str, Any] | None = None + inputs: Mapping[str, object] = Field(default_factory=dict) + process_data: Mapping[str, object] = Field(default_factory=dict) + outputs: Mapping[str, object] = Field(default_factory=dict) execution_metadata: Mapping[WorkflowNodeExecutionMetadataKey, Any] | None = None error: str @@ -494,7 +494,7 @@ class QueueErrorEvent(AppQueueEvent): """ event: QueueEvent = QueueEvent.ERROR - error: Any | None = None + error: Any = None class QueuePingEvent(AppQueueEvent): diff --git a/api/core/app/entities/task_entities.py b/api/core/app/entities/task_entities.py index c940a9ab6f..fe8c916d3a 100644 --- a/api/core/app/entities/task_entities.py +++ b/api/core/app/entities/task_entities.py @@ -136,7 +136,7 @@ class MessageEndStreamResponse(StreamResponse): event: StreamEvent = StreamEvent.MESSAGE_END id: str - metadata: dict = Field(default_factory=dict) + metadata: Mapping[str, object] = Field(default_factory=dict) files: Sequence[Mapping[str, Any]] | None = None @@ -173,7 +173,7 @@ class AgentThoughtStreamResponse(StreamResponse): thought: str | None = None observation: str | None = None tool: str | None = None - tool_labels: dict | None = None + tool_labels: Mapping[str, object] = Field(default_factory=dict) tool_input: str | None = None message_files: list[str] | None = None @@ -226,7 +226,7 @@ class WorkflowFinishStreamResponse(StreamResponse): elapsed_time: float total_tokens: int total_steps: int - created_by: dict | None = None + created_by: Mapping[str, object] = Field(default_factory=dict) created_at: int finished_at: int exceptions_count: int | None = 0 @@ -256,7 +256,7 @@ class NodeStartStreamResponse(StreamResponse): inputs: Optional[Mapping[str, Any]] = None inputs_truncated: bool = False created_at: int - extras: dict = Field(default_factory=dict) + extras: dict[str, object] = Field(default_factory=dict) parallel_id: str | None = None parallel_start_node_id: str | None = None parent_parallel_id: str | None = None @@ -513,7 +513,7 @@ class IterationNodeCompletedStreamResponse(StreamResponse): error: str | None = None elapsed_time: float total_tokens: int - execution_metadata: Mapping | None = None + execution_metadata: Mapping[str, object] = Field(default_factory=dict) finished_at: int steps: int @@ -565,11 +565,11 @@ class LoopNodeNextStreamResponse(StreamResponse): title: str index: int created_at: int - pre_loop_output: Any | None = None - extras: dict = Field(default_factory=dict) - parallel_id: Optional[str] = None - parallel_start_node_id: Optional[str] = None - parallel_mode_run_id: Optional[str] = None + pre_loop_output: Any = None + extras: Mapping[str, object] = Field(default_factory=dict) + parallel_id: str | None = None + parallel_start_node_id: str | None = None + parallel_mode_run_id: str | None = None event: StreamEvent = StreamEvent.LOOP_NEXT workflow_run_id: str @@ -600,7 +600,7 @@ class LoopNodeCompletedStreamResponse(StreamResponse): error: str | None = None elapsed_time: float total_tokens: int - execution_metadata: Mapping | None = None + execution_metadata: Mapping[str, object] = Field(default_factory=dict) finished_at: int steps: int parallel_id: str | None = None @@ -710,7 +710,7 @@ class ChatbotAppBlockingResponse(AppBlockingResponse): conversation_id: str message_id: str answer: str - metadata: dict = Field(default_factory=dict) + metadata: Mapping[str, object] = Field(default_factory=dict) created_at: int data: Data @@ -730,7 +730,7 @@ class CompletionAppBlockingResponse(AppBlockingResponse): mode: str message_id: str answer: str - metadata: dict = Field(default_factory=dict) + metadata: Mapping[str, object] = Field(default_factory=dict) created_at: int data: Data @@ -778,7 +778,7 @@ class AgentLogStreamResponse(StreamResponse): error: str | None = None status: str data: Mapping[str, Any] - metadata: Mapping[str, Any] | None = None + metadata: Mapping[str, object] = Field(default_factory=dict) node_id: str event: StreamEvent = StreamEvent.AGENT_LOG diff --git a/api/core/base/tts/app_generator_tts_publisher.py b/api/core/base/tts/app_generator_tts_publisher.py index 1e0fba6215..f83aaa0006 100644 --- a/api/core/base/tts/app_generator_tts_publisher.py +++ b/api/core/base/tts/app_generator_tts_publisher.py @@ -109,7 +109,9 @@ class AppGeneratorTTSPublisher: elif isinstance(message.event, QueueNodeSucceededEvent): if message.event.outputs is None: continue - self.msg_text += message.event.outputs.get("output", "") + output = message.event.outputs.get("output", "") + if isinstance(output, str): + self.msg_text += output self.last_message = message sentence_arr, text_tmp = self._extract_sentence(self.msg_text) if len(sentence_arr) >= min(self.max_sentence, 7): @@ -119,7 +121,7 @@ class AppGeneratorTTSPublisher: _invoice_tts, text_content, self.model_instance, self.tenant_id, self.voice ) future_queue.put(futures_result) - if text_tmp: + if isinstance(text_tmp, str): self.msg_text = text_tmp else: self.msg_text = "" diff --git a/api/core/helper/code_executor/code_node_provider.py b/api/core/helper/code_executor/code_node_provider.py index 701208080c..e93e1e4414 100644 --- a/api/core/helper/code_executor/code_node_provider.py +++ b/api/core/helper/code_executor/code_node_provider.py @@ -1,9 +1,33 @@ -from abc import abstractmethod +from abc import ABC, abstractmethod +from collections.abc import Mapping, Sequence +from typing import TypedDict from pydantic import BaseModel -class CodeNodeProvider(BaseModel): +class VariableConfig(TypedDict): + variable: str + value_selector: Sequence[str | int] + + +class OutputConfig(TypedDict): + type: str + children: None + + +class CodeConfig(TypedDict): + variables: Sequence[VariableConfig] + code_language: str + code: str + outputs: Mapping[str, OutputConfig] + + +class DefaultConfig(TypedDict): + type: str + config: CodeConfig + + +class CodeNodeProvider(BaseModel, ABC): @staticmethod @abstractmethod def get_language() -> str: @@ -22,11 +46,14 @@ class CodeNodeProvider(BaseModel): pass @classmethod - def get_default_config(cls): + def get_default_config(cls) -> DefaultConfig: return { "type": "code", "config": { - "variables": [{"variable": "arg1", "value_selector": []}, {"variable": "arg2", "value_selector": []}], + "variables": [ + {"variable": "arg1", "value_selector": []}, + {"variable": "arg2", "value_selector": []}, + ], "code_language": cls.get_language(), "code": cls.get_default_code(), "outputs": {"result": {"type": "string", "children": None}}, diff --git a/api/core/mcp/types.py b/api/core/mcp/types.py index 7399e8a4b6..c7a046b585 100644 --- a/api/core/mcp/types.py +++ b/api/core/mcp/types.py @@ -160,7 +160,7 @@ class ErrorData(BaseModel): sentence. """ - data: Any | None = None + data: Any = None """ Additional information about the error. The value of this member is defined by the sender (e.g. detailed error information, nested errors etc.). diff --git a/api/core/model_runtime/model_providers/model_provider_factory.py b/api/core/model_runtime/model_providers/model_provider_factory.py index 250b158f99..e070c17abd 100644 --- a/api/core/model_runtime/model_providers/model_provider_factory.py +++ b/api/core/model_runtime/model_providers/model_provider_factory.py @@ -22,13 +22,9 @@ logger = logging.getLogger(__name__) class ModelProviderFactory: - provider_position_map: dict[str, int] - def __init__(self, tenant_id: str): from core.plugin.impl.model import PluginModelClient - self.provider_position_map = {} - self.tenant_id = tenant_id self.plugin_model_manager = PluginModelClient() diff --git a/api/core/ops/ops_trace_manager.py b/api/core/ops/ops_trace_manager.py index 66af061da3..0679b27271 100644 --- a/api/core/ops/ops_trace_manager.py +++ b/api/core/ops/ops_trace_manager.py @@ -408,11 +408,11 @@ class TraceTask: def __init__( self, trace_type: Any, - message_id: Optional[str] = None, + message_id: str | None = None, workflow_execution: Optional["WorkflowExecution"] = None, - conversation_id: Optional[str] = None, - user_id: Optional[str] = None, - timer: Optional[Any] = None, + conversation_id: str | None = None, + user_id: str | None = None, + timer: Any | None = None, **kwargs, ): self.trace_type = trace_type diff --git a/api/core/tools/entities/api_entities.py b/api/core/tools/entities/api_entities.py index ee2b438f5b..00c4ab9dd7 100644 --- a/api/core/tools/entities/api_entities.py +++ b/api/core/tools/entities/api_entities.py @@ -1,5 +1,6 @@ +from collections.abc import Mapping from datetime import datetime -from typing import Any, Literal, Optional +from typing import Any, Literal from pydantic import BaseModel, Field, field_validator @@ -16,10 +17,10 @@ class ToolApiEntity(BaseModel): description: I18nObject parameters: list[ToolParameter] | None = None labels: list[str] = Field(default_factory=list) - output_schema: dict | None = None + output_schema: Mapping[str, object] = Field(default_factory=dict) -ToolProviderTypeApiLiteral = Optional[Literal["builtin", "api", "workflow", "mcp"]] +ToolProviderTypeApiLiteral = Literal["builtin", "api", "workflow", "mcp"] | None class ToolProviderApiEntity(BaseModel): @@ -27,17 +28,17 @@ class ToolProviderApiEntity(BaseModel): author: str name: str # identifier description: I18nObject - icon: str | dict - icon_dark: str | dict | None = Field(default=None, description="The dark icon of the tool") + icon: str | Mapping[str, str] + icon_dark: str | Mapping[str, str] = "" label: I18nObject # label type: ToolProviderType - masked_credentials: dict | None = None - original_credentials: dict | None = None + masked_credentials: Mapping[str, object] = Field(default_factory=dict) + original_credentials: Mapping[str, object] = Field(default_factory=dict) is_team_authorization: bool = False allow_delete: bool = True plugin_id: str | None = Field(default="", description="The plugin id of the tool") plugin_unique_identifier: str | None = Field(default="", description="The unique identifier of the tool") - tools: list[ToolApiEntity] = Field(default_factory=list) + tools: list[ToolApiEntity] = Field(default_factory=list[ToolApiEntity]) labels: list[str] = Field(default_factory=list) # MCP server_url: str | None = Field(default="", description="The server url of the tool") @@ -105,7 +106,7 @@ class ToolProviderCredentialApiEntity(BaseModel): is_default: bool = Field( default=False, description="Whether the credential is the default credential for the provider in the workspace" ) - credentials: dict = Field(description="The credentials of the provider") + credentials: Mapping[str, object] = Field(description="The credentials of the provider", default_factory=dict) class ToolProviderCredentialInfoApiEntity(BaseModel): diff --git a/api/core/tools/entities/tool_entities.py b/api/core/tools/entities/tool_entities.py index 1dc4b3a9ea..a59b54216f 100644 --- a/api/core/tools/entities/tool_entities.py +++ b/api/core/tools/entities/tool_entities.py @@ -187,7 +187,7 @@ class ToolInvokeMessage(BaseModel): error: str | None = Field(default=None, description="The error message") status: LogStatus = Field(..., description="The status of the log") data: Mapping[str, Any] = Field(..., description="Detailed log data") - metadata: Mapping[str, Any] | None = Field(default=None, description="The metadata of the log") + metadata: Mapping[str, Any] = Field(default_factory=dict, description="The metadata of the log") class RetrieverResourceMessage(BaseModel): retriever_resources: list[RetrievalSourceMetadata] = Field(..., description="retriever resources") @@ -363,9 +363,9 @@ class ToolDescription(BaseModel): class ToolEntity(BaseModel): identity: ToolIdentity - parameters: list[ToolParameter] = Field(default_factory=list) + parameters: list[ToolParameter] = Field(default_factory=list[ToolParameter]) description: ToolDescription | None = None - output_schema: dict | None = None + output_schema: Mapping[str, object] = Field(default_factory=dict) has_runtime_parameters: bool = Field(default=False, description="Whether the tool has runtime parameters") # pydantic configs @@ -378,21 +378,23 @@ class ToolEntity(BaseModel): class OAuthSchema(BaseModel): - client_schema: list[ProviderConfig] = Field(default_factory=list, description="The schema of the OAuth client") + client_schema: list[ProviderConfig] = Field( + default_factory=list[ProviderConfig], description="The schema of the OAuth client" + ) credentials_schema: list[ProviderConfig] = Field( - default_factory=list, description="The schema of the OAuth credentials" + default_factory=list[ProviderConfig], description="The schema of the OAuth credentials" ) class ToolProviderEntity(BaseModel): identity: ToolProviderIdentity plugin_id: str | None = None - credentials_schema: list[ProviderConfig] = Field(default_factory=list) + credentials_schema: list[ProviderConfig] = Field(default_factory=list[ProviderConfig]) oauth_schema: OAuthSchema | None = None class ToolProviderEntityWithPlugin(ToolProviderEntity): - tools: list[ToolEntity] = Field(default_factory=list) + tools: list[ToolEntity] = Field(default_factory=list[ToolEntity]) class WorkflowToolParameterConfiguration(BaseModel): diff --git a/api/core/tools/mcp_tool/provider.py b/api/core/tools/mcp_tool/provider.py index 60b393e1ea..5b04f0edbe 100644 --- a/api/core/tools/mcp_tool/provider.py +++ b/api/core/tools/mcp_tool/provider.py @@ -72,7 +72,6 @@ class MCPToolProviderController(ToolProviderController): ), llm=remote_mcp_tool.description or "", ), - output_schema=None, has_runtime_parameters=len(remote_mcp_tool.inputSchema) > 0, ) for remote_mcp_tool in remote_mcp_tools diff --git a/api/core/tools/tool_engine.py b/api/core/tools/tool_engine.py index cb86555783..9fb6062770 100644 --- a/api/core/tools/tool_engine.py +++ b/api/core/tools/tool_engine.py @@ -4,7 +4,7 @@ from collections.abc import Generator, Iterable from copy import deepcopy from datetime import UTC, datetime from mimetypes import guess_type -from typing import Any, Optional, Union, cast +from typing import Any, Union, cast from yarl import URL @@ -152,9 +152,9 @@ class ToolEngine: user_id: str, workflow_tool_callback: DifyWorkflowCallbackHandler, workflow_call_depth: int, - conversation_id: Optional[str] = None, - app_id: Optional[str] = None, - message_id: Optional[str] = None, + conversation_id: str | None = None, + app_id: str | None = None, + message_id: str | None = None, ) -> Generator[ToolInvokeMessage, None, None]: """ Workflow invokes the tool with the given arguments. diff --git a/api/core/tools/tool_manager.py b/api/core/tools/tool_manager.py index 011e7ad242..9e5f5a7c23 100644 --- a/api/core/tools/tool_manager.py +++ b/api/core/tools/tool_manager.py @@ -14,31 +14,17 @@ from sqlalchemy.orm import Session from yarl import URL import contexts -from core.helper.provider_cache import ToolProviderCredentialsCache -from core.plugin.impl.tool import PluginToolManager -from core.tools.__base.tool_provider import ToolProviderController -from core.tools.__base.tool_runtime import ToolRuntime -from core.tools.mcp_tool.provider import MCPToolProviderController -from core.tools.mcp_tool.tool import MCPTool -from core.tools.plugin_tool.provider import PluginToolProviderController -from core.tools.plugin_tool.tool import PluginTool -from core.tools.utils.uuid_utils import is_valid_uuid -from core.tools.workflow_as_tool.provider import WorkflowToolProviderController -from core.workflow.entities.variable_pool import VariablePool -from models.provider_ids import ToolProviderID -from services.enterprise.plugin_manager_service import PluginCredentialType -from services.tools.mcp_tools_manage_service import MCPToolManageService - -if TYPE_CHECKING: - from core.workflow.nodes.tool.entities import ToolEntity - from configs import dify_config from core.agent.entities import AgentToolEntity from core.app.entities.app_invoke_entities import InvokeFrom from core.helper.module_import_helper import load_single_subclass_from_source from core.helper.position_helper import is_filtered +from core.helper.provider_cache import ToolProviderCredentialsCache from core.model_runtime.utils.encoders import jsonable_encoder +from core.plugin.impl.tool import PluginToolManager from core.tools.__base.tool import Tool +from core.tools.__base.tool_provider import ToolProviderController +from core.tools.__base.tool_runtime import ToolRuntime from core.tools.builtin_tool.provider import BuiltinToolProviderController from core.tools.builtin_tool.providers._positions import BuiltinToolProviderSort from core.tools.builtin_tool.tool import BuiltinTool @@ -54,12 +40,21 @@ from core.tools.entities.tool_entities import ( ToolProviderType, ) from core.tools.errors import ToolProviderNotFoundError +from core.tools.mcp_tool.provider import MCPToolProviderController +from core.tools.mcp_tool.tool import MCPTool +from core.tools.plugin_tool.provider import PluginToolProviderController +from core.tools.plugin_tool.tool import PluginTool from core.tools.tool_label_manager import ToolLabelManager from core.tools.utils.configuration import ToolParameterConfigurationManager from core.tools.utils.encryption import create_provider_encrypter, create_tool_provider_encrypter +from core.tools.utils.uuid_utils import is_valid_uuid +from core.tools.workflow_as_tool.provider import WorkflowToolProviderController from core.tools.workflow_as_tool.tool import WorkflowTool from extensions.ext_database import db +from models.provider_ids import ToolProviderID from models.tools import ApiToolProvider, BuiltinToolProvider, MCPToolProvider, WorkflowToolProvider +from services.enterprise.plugin_manager_service import PluginCredentialType +from services.tools.mcp_tools_manage_service import MCPToolManageService from services.tools.tools_transform_service import ToolTransformService if TYPE_CHECKING: @@ -890,7 +885,7 @@ class ToolManager: ) @classmethod - def generate_workflow_tool_icon_url(cls, tenant_id: str, provider_id: str): + def generate_workflow_tool_icon_url(cls, tenant_id: str, provider_id: str) -> Mapping[str, str]: try: workflow_provider: WorkflowToolProvider | None = ( db.session.query(WorkflowToolProvider) @@ -901,13 +896,13 @@ class ToolManager: if workflow_provider is None: raise ToolProviderNotFoundError(f"workflow provider {provider_id} not found") - icon: dict = json.loads(workflow_provider.icon) + icon = json.loads(workflow_provider.icon) return icon except Exception: return {"background": "#252525", "content": "\ud83d\ude01"} @classmethod - def generate_api_tool_icon_url(cls, tenant_id: str, provider_id: str): + def generate_api_tool_icon_url(cls, tenant_id: str, provider_id: str) -> Mapping[str, str]: try: api_provider: ApiToolProvider | None = ( db.session.query(ApiToolProvider) @@ -918,13 +913,13 @@ class ToolManager: if api_provider is None: raise ToolProviderNotFoundError(f"api provider {provider_id} not found") - icon: dict = json.loads(api_provider.icon) + icon = json.loads(api_provider.icon) return icon except Exception: return {"background": "#252525", "content": "\ud83d\ude01"} @classmethod - def generate_mcp_tool_icon_url(cls, tenant_id: str, provider_id: str) -> dict[str, str] | str: + def generate_mcp_tool_icon_url(cls, tenant_id: str, provider_id: str) -> Mapping[str, str] | str: try: mcp_provider: MCPToolProvider | None = ( db.session.query(MCPToolProvider) @@ -945,7 +940,7 @@ class ToolManager: tenant_id: str, provider_type: ToolProviderType, provider_id: str, - ) -> Union[str, dict[str, Any]]: + ) -> str | Mapping[str, str]: """ get the tool icon @@ -970,11 +965,10 @@ class ToolManager: return cls.generate_workflow_tool_icon_url(tenant_id, provider_id) elif provider_type == ToolProviderType.PLUGIN: provider = ToolManager.get_plugin_provider(provider_id, tenant_id) - if isinstance(provider, PluginToolProviderController): - try: - return cls.generate_plugin_tool_icon_url(tenant_id, provider.entity.identity.icon) - except Exception: - return {"background": "#252525", "content": "\ud83d\ude01"} + try: + return cls.generate_plugin_tool_icon_url(tenant_id, provider.entity.identity.icon) + except Exception: + return {"background": "#252525", "content": "\ud83d\ude01"} raise ValueError(f"plugin provider {provider_id} not found") elif provider_type == ToolProviderType.MCP: return cls.generate_mcp_tool_icon_url(tenant_id, provider_id) diff --git a/api/core/workflow/README.md b/api/core/workflow/README.md new file mode 100644 index 0000000000..bef19ba90b --- /dev/null +++ b/api/core/workflow/README.md @@ -0,0 +1,132 @@ +# Workflow + +## Project Overview + +This is the workflow graph engine module of Dify, implementing a queue-based distributed workflow execution system. The engine handles agentic AI workflows with support for parallel execution, node iteration, conditional logic, and external command control. + +## Architecture + +### Core Components + +The graph engine follows a layered architecture with strict dependency rules: + +1. **Graph Engine** (`graph_engine/`) - Orchestrates workflow execution + + - **Manager** - External control interface for stop/pause/resume commands + - **Worker** - Node execution runtime + - **Command Processing** - Handles control commands (abort, pause, resume) + - **Event Management** - Event propagation and layer notifications + - **Graph Traversal** - Edge processing and skip propagation + - **Response Coordinator** - Path tracking and session management + - **Layers** - Pluggable middleware (debug logging, execution limits) + - **Command Channels** - Communication channels (InMemory, Redis) + +1. **Graph** (`graph/`) - Graph structure and runtime state + + - **Graph Template** - Workflow definition + - **Edge** - Node connections with conditions + - **Runtime State Protocol** - State management interface + +1. **Nodes** (`nodes/`) - Node implementations + + - **Base** - Abstract node classes and variable parsing + - **Specific Nodes** - LLM, Agent, Code, HTTP Request, Iteration, Loop, etc. + +1. **Events** (`node_events/`) - Event system + + - **Base** - Event protocols + - **Node Events** - Node lifecycle events + +1. **Entities** (`entities/`) - Domain models + + - **Variable Pool** - Variable storage + - **Graph Init Params** - Initialization configuration + +## Key Design Patterns + +### Command Channel Pattern + +External workflow control via Redis or in-memory channels: + +```python +# Send stop command to running workflow +channel = RedisChannel(redis_client, f"workflow:{task_id}:commands") +channel.send_command(AbortCommand(reason="User requested")) +``` + +### Layer System + +Extensible middleware for cross-cutting concerns: + +```python +engine = GraphEngine(graph) +engine.add_layer(DebugLoggingLayer(level="INFO")) +engine.add_layer(ExecutionLimitsLayer(max_nodes=100)) +``` + +### Event-Driven Architecture + +All node executions emit events for monitoring and integration: + +- `NodeRunStartedEvent` - Node execution begins +- `NodeRunSucceededEvent` - Node completes successfully +- `NodeRunFailedEvent` - Node encounters error +- `GraphRunStartedEvent/GraphRunCompletedEvent` - Workflow lifecycle + +### Variable Pool + +Centralized variable storage with namespace isolation: + +```python +# Variables scoped by node_id +pool.add(["node1", "output"], value) +result = pool.get(["node1", "output"]) +``` + +## Import Architecture Rules + +The codebase enforces strict layering via import-linter: + +1. **Workflow Layers** (top to bottom): + + - graph_engine → graph_events → graph → nodes → node_events → entities + +1. **Graph Engine Internal Layers**: + + - orchestration → command_processing → event_management → graph_traversal → domain + +1. **Domain Isolation**: + + - Domain models cannot import from infrastructure layers + +1. **Command Channel Independence**: + + - InMemory and Redis channels must remain independent + +## Common Tasks + +### Adding a New Node Type + +1. Create node class in `nodes//` +1. Inherit from `BaseNode` or appropriate base class +1. Implement `_run()` method +1. Register in `nodes/node_mapping.py` +1. Add tests in `tests/unit_tests/core/workflow/nodes/` + +### Implementing a Custom Layer + +1. Create class inheriting from `Layer` base +1. Override lifecycle methods: `on_graph_start()`, `on_event()`, `on_graph_end()` +1. Add to engine via `engine.add_layer()` + +### Debugging Workflow Execution + +Enable debug logging layer: + +```python +debug_layer = DebugLoggingLayer( + level="DEBUG", + include_inputs=True, + include_outputs=True +) +``` diff --git a/api/core/workflow/entities/agent.py b/api/core/workflow/entities/agent.py index e1d9f13e31..2b4d6db76f 100644 --- a/api/core/workflow/entities/agent.py +++ b/api/core/workflow/entities/agent.py @@ -1,5 +1,3 @@ -from typing import Optional - from pydantic import BaseModel @@ -7,4 +5,4 @@ class AgentNodeStrategyInit(BaseModel): """Agent node strategy initialization data.""" name: str - icon: Optional[str] = None + icon: str | None = None diff --git a/api/core/workflow/entities/graph_runtime_state.py b/api/core/workflow/entities/graph_runtime_state.py index c06a62d1e7..6362f291ea 100644 --- a/api/core/workflow/entities/graph_runtime_state.py +++ b/api/core/workflow/entities/graph_runtime_state.py @@ -1,5 +1,4 @@ from copy import deepcopy -from typing import Any from pydantic import BaseModel, PrivateAttr @@ -14,17 +13,24 @@ class GraphRuntimeState(BaseModel): _start_at: float = PrivateAttr() _total_tokens: int = PrivateAttr(default=0) _llm_usage: LLMUsage = PrivateAttr(default_factory=LLMUsage.empty_usage) - _outputs: dict[str, Any] = PrivateAttr(default_factory=dict) + _outputs: dict[str, object] = PrivateAttr(default_factory=dict[str, object]) _node_run_steps: int = PrivateAttr(default=0) + _ready_queue_json: str = PrivateAttr() + _graph_execution_json: str = PrivateAttr() + _response_coordinator_json: str = PrivateAttr() def __init__( self, + *, variable_pool: VariablePool, start_at: float, total_tokens: int = 0, llm_usage: LLMUsage | None = None, - outputs: dict[str, Any] | None = None, + outputs: dict[str, object] | None = None, node_run_steps: int = 0, + ready_queue_json: str = "", + graph_execution_json: str = "", + response_coordinator_json: str = "", **kwargs: object, ): """Initialize the GraphRuntimeState with validation.""" @@ -51,6 +57,10 @@ class GraphRuntimeState(BaseModel): raise ValueError("node_run_steps must be non-negative") self._node_run_steps = node_run_steps + self._ready_queue_json = ready_queue_json + self._graph_execution_json = graph_execution_json + self._response_coordinator_json = response_coordinator_json + @property def variable_pool(self) -> VariablePool: """Get the variable pool.""" @@ -90,24 +100,24 @@ class GraphRuntimeState(BaseModel): self._llm_usage = value.model_copy() @property - def outputs(self) -> dict[str, Any]: + def outputs(self) -> dict[str, object]: """Get a copy of the outputs dictionary.""" return deepcopy(self._outputs) @outputs.setter - def outputs(self, value: dict[str, Any]) -> None: + def outputs(self, value: dict[str, object]) -> None: """Set the outputs dictionary.""" self._outputs = deepcopy(value) - def set_output(self, key: str, value: Any) -> None: + def set_output(self, key: str, value: object) -> None: """Set a single output value.""" self._outputs[key] = deepcopy(value) - def get_output(self, key: str, default: Any = None) -> Any: + def get_output(self, key: str, default: object = None) -> object: """Get a single output value.""" return deepcopy(self._outputs.get(key, default)) - def update_outputs(self, updates: dict[str, Any]) -> None: + def update_outputs(self, updates: dict[str, object]) -> None: """Update multiple output values.""" for key, value in updates.items(): self._outputs[key] = deepcopy(value) @@ -133,3 +143,18 @@ class GraphRuntimeState(BaseModel): if tokens < 0: raise ValueError("tokens must be non-negative") self._total_tokens += tokens + + @property + def ready_queue_json(self) -> str: + """Get a copy of the ready queue state.""" + return self._ready_queue_json + + @property + def graph_execution_json(self) -> str: + """Get a copy of the serialized graph execution state.""" + return self._graph_execution_json + + @property + def response_coordinator_json(self) -> str: + """Get a copy of the serialized response coordinator state.""" + return self._response_coordinator_json diff --git a/api/core/workflow/graph/graph.py b/api/core/workflow/graph/graph.py index c81c83fe32..330e14de81 100644 --- a/api/core/workflow/graph/graph.py +++ b/api/core/workflow/graph/graph.py @@ -188,9 +188,9 @@ class Graph: for node_id, node_config in node_configs_map.items(): try: node_instance = node_factory.create_node(node_config) - except ValueError as e: - logger.warning("Failed to create node instance: %s", str(e)) - continue + except Exception: + logger.exception("Failed to create node instance for node_id %s", node_id) + raise nodes[node_id] = node_instance return nodes diff --git a/api/core/workflow/graph_engine/command_channels/redis_channel.py b/api/core/workflow/graph_engine/command_channels/redis_channel.py index ad0aa9402c..056e17bf5d 100644 --- a/api/core/workflow/graph_engine/command_channels/redis_channel.py +++ b/api/core/workflow/graph_engine/command_channels/redis_channel.py @@ -97,8 +97,12 @@ class RedisChannel: Returns: Deserialized command or None if invalid """ + command_type_value = data.get("command_type") + if not isinstance(command_type_value, str): + return None + try: - command_type = CommandType(data.get("command_type")) + command_type = CommandType(command_type_value) if command_type == CommandType.ABORT: return AbortCommand(**data) diff --git a/api/core/workflow/graph_engine/domain/__init__.py b/api/core/workflow/graph_engine/domain/__init__.py index cf6d3e6aa3..9e9afe4c21 100644 --- a/api/core/workflow/graph_engine/domain/__init__.py +++ b/api/core/workflow/graph_engine/domain/__init__.py @@ -5,12 +5,10 @@ This package contains the core domain entities, value objects, and aggregates that represent the business concepts of workflow graph execution. """ -from .execution_context import ExecutionContext from .graph_execution import GraphExecution from .node_execution import NodeExecution __all__ = [ - "ExecutionContext", "GraphExecution", "NodeExecution", ] diff --git a/api/core/workflow/graph_engine/domain/execution_context.py b/api/core/workflow/graph_engine/domain/execution_context.py deleted file mode 100644 index 0b4116f39d..0000000000 --- a/api/core/workflow/graph_engine/domain/execution_context.py +++ /dev/null @@ -1,37 +0,0 @@ -""" -ExecutionContext value object containing immutable execution parameters. -""" - -from dataclasses import dataclass - -from core.app.entities.app_invoke_entities import InvokeFrom -from models.enums import UserFrom - - -@dataclass(frozen=True) -class ExecutionContext: - """ - Immutable value object containing the context for a graph execution. - - This encapsulates all the contextual information needed to execute a workflow, - keeping it separate from the mutable execution state. - """ - - tenant_id: str - app_id: str - workflow_id: str - user_id: str - user_from: UserFrom - invoke_from: InvokeFrom - call_depth: int - max_execution_steps: int - max_execution_time: int - - def __post_init__(self) -> None: - """Validate execution context parameters.""" - if self.call_depth < 0: - raise ValueError("Call depth must be non-negative") - if self.max_execution_steps <= 0: - raise ValueError("Max execution steps must be positive") - if self.max_execution_time <= 0: - raise ValueError("Max execution time must be positive") diff --git a/api/core/workflow/graph_engine/domain/graph_execution.py b/api/core/workflow/graph_engine/domain/graph_execution.py index c375b08fe0..5951af1087 100644 --- a/api/core/workflow/graph_engine/domain/graph_execution.py +++ b/api/core/workflow/graph_engine/domain/graph_execution.py @@ -1,12 +1,94 @@ -""" -GraphExecution aggregate root managing the overall graph execution state. -""" +"""GraphExecution aggregate root managing the overall graph execution state.""" + +from __future__ import annotations from dataclasses import dataclass, field +from importlib import import_module +from typing import Literal + +from pydantic import BaseModel, Field + +from core.workflow.enums import NodeState from .node_execution import NodeExecution +class GraphExecutionErrorState(BaseModel): + """Serializable representation of an execution error.""" + + module: str = Field(description="Module containing the exception class") + qualname: str = Field(description="Qualified name of the exception class") + message: str | None = Field(default=None, description="Exception message string") + + +class NodeExecutionState(BaseModel): + """Serializable representation of a node execution entity.""" + + node_id: str + state: NodeState = Field(default=NodeState.UNKNOWN) + retry_count: int = Field(default=0) + execution_id: str | None = Field(default=None) + error: str | None = Field(default=None) + + +class GraphExecutionState(BaseModel): + """Pydantic model describing serialized GraphExecution state.""" + + type: Literal["GraphExecution"] = Field(default="GraphExecution") + version: str = Field(default="1.0") + workflow_id: str + started: bool = Field(default=False) + completed: bool = Field(default=False) + aborted: bool = Field(default=False) + error: GraphExecutionErrorState | None = Field(default=None) + node_executions: list[NodeExecutionState] = Field(default_factory=list) + + +def _serialize_error(error: Exception | None) -> GraphExecutionErrorState | None: + """Convert an exception into its serializable representation.""" + + if error is None: + return None + + return GraphExecutionErrorState( + module=error.__class__.__module__, + qualname=error.__class__.__qualname__, + message=str(error), + ) + + +def _resolve_exception_class(module_name: str, qualname: str) -> type[Exception]: + """Locate an exception class from its module and qualified name.""" + + module = import_module(module_name) + attr: object = module + for part in qualname.split("."): + attr = getattr(attr, part) + + if isinstance(attr, type) and issubclass(attr, Exception): + return attr + + raise TypeError(f"{qualname} in {module_name} is not an Exception subclass") + + +def _deserialize_error(state: GraphExecutionErrorState | None) -> Exception | None: + """Reconstruct an exception instance from serialized data.""" + + if state is None: + return None + + try: + exception_class = _resolve_exception_class(state.module, state.qualname) + if state.message is None: + return exception_class() + return exception_class(state.message) + except Exception: + # Fallback to RuntimeError when reconstruction fails + if state.message is None: + return RuntimeError(state.qualname) + return RuntimeError(state.message) + + @dataclass class GraphExecution: """ @@ -69,3 +151,57 @@ class GraphExecution: if not self.error: return None return str(self.error) + + def dumps(self) -> str: + """Serialize the aggregate state into a JSON string.""" + + node_states = [ + NodeExecutionState( + node_id=node_id, + state=node_execution.state, + retry_count=node_execution.retry_count, + execution_id=node_execution.execution_id, + error=node_execution.error, + ) + for node_id, node_execution in sorted(self.node_executions.items()) + ] + + state = GraphExecutionState( + workflow_id=self.workflow_id, + started=self.started, + completed=self.completed, + aborted=self.aborted, + error=_serialize_error(self.error), + node_executions=node_states, + ) + + return state.model_dump_json() + + def loads(self, data: str) -> None: + """Restore aggregate state from a serialized JSON string.""" + + state = GraphExecutionState.model_validate_json(data) + + if state.type != "GraphExecution": + raise ValueError(f"Invalid serialized data type: {state.type}") + + if state.version != "1.0": + raise ValueError(f"Unsupported serialized version: {state.version}") + + if self.workflow_id != state.workflow_id: + raise ValueError("Serialized workflow_id does not match aggregate identity") + + self.started = state.started + self.completed = state.completed + self.aborted = state.aborted + self.error = _deserialize_error(state.error) + self.node_executions = { + item.node_id: NodeExecution( + node_id=item.node_id, + state=item.state, + retry_count=item.retry_count, + execution_id=item.execution_id, + error=item.error, + ) + for item in state.node_executions + } diff --git a/api/core/workflow/graph_engine/entities/event.py b/api/core/workflow/graph_engine/entities/event.py deleted file mode 100644 index e69de29bb2..0000000000 diff --git a/api/core/workflow/graph_engine/entities/graph.py b/api/core/workflow/graph_engine/entities/graph.py deleted file mode 100644 index e69de29bb2..0000000000 diff --git a/api/core/workflow/graph_engine/error_handler.py b/api/core/workflow/graph_engine/error_handler.py new file mode 100644 index 0000000000..62e144c12a --- /dev/null +++ b/api/core/workflow/graph_engine/error_handler.py @@ -0,0 +1,211 @@ +""" +Main error handler that coordinates error strategies. +""" + +import logging +import time +from typing import TYPE_CHECKING, final + +from core.workflow.enums import ( + ErrorStrategy as ErrorStrategyEnum, +) +from core.workflow.enums import ( + WorkflowNodeExecutionMetadataKey, + WorkflowNodeExecutionStatus, +) +from core.workflow.graph import Graph +from core.workflow.graph_events import ( + GraphNodeEventBase, + NodeRunExceptionEvent, + NodeRunFailedEvent, + NodeRunRetryEvent, +) +from core.workflow.node_events import NodeRunResult + +if TYPE_CHECKING: + from .domain import GraphExecution + +logger = logging.getLogger(__name__) + + +@final +class ErrorHandler: + """ + Coordinates error handling strategies for node failures. + + This acts as a facade for the various error strategies, + selecting and applying the appropriate strategy based on + node configuration. + """ + + def __init__(self, graph: Graph, graph_execution: "GraphExecution") -> None: + """ + Initialize the error handler. + + Args: + graph: The workflow graph + graph_execution: The graph execution state + """ + self._graph = graph + self._graph_execution = graph_execution + + def handle_node_failure(self, event: NodeRunFailedEvent) -> GraphNodeEventBase | None: + """ + Handle a node failure event. + + Selects and applies the appropriate error strategy based on + the node's configuration. + + Args: + event: The node failure event + + Returns: + Optional new event to process, or None to abort + """ + node = self._graph.nodes[event.node_id] + # Get retry count from NodeExecution + node_execution = self._graph_execution.get_or_create_node_execution(event.node_id) + retry_count = node_execution.retry_count + + # First check if retry is configured and not exhausted + if node.retry and retry_count < node.retry_config.max_retries: + result = self._handle_retry(event, retry_count) + if result: + # Retry count will be incremented when NodeRunRetryEvent is handled + return result + + # Apply configured error strategy + strategy = node.error_strategy + + match strategy: + case None: + return self._handle_abort(event) + case ErrorStrategyEnum.FAIL_BRANCH: + return self._handle_fail_branch(event) + case ErrorStrategyEnum.DEFAULT_VALUE: + return self._handle_default_value(event) + + def _handle_abort(self, event: NodeRunFailedEvent): + """ + Handle error by aborting execution. + + This is the default strategy when no other strategy is specified. + It stops the entire graph execution when a node fails. + + Args: + event: The failure event + + Returns: + None - signals abortion + """ + logger.error("Node %s failed with ABORT strategy: %s", event.node_id, event.error) + # Return None to signal that execution should stop + + def _handle_retry(self, event: NodeRunFailedEvent, retry_count: int): + """ + Handle error by retrying the node. + + This strategy re-attempts node execution up to a configured + maximum number of retries with configurable intervals. + + Args: + event: The failure event + retry_count: Current retry attempt count + + Returns: + NodeRunRetryEvent if retry should occur, None otherwise + """ + node = self._graph.nodes[event.node_id] + + # Check if we've exceeded max retries + if not node.retry or retry_count >= node.retry_config.max_retries: + return None + + # Wait for retry interval + time.sleep(node.retry_config.retry_interval_seconds) + + # Create retry event + return NodeRunRetryEvent( + id=event.id, + node_title=node.title, + node_id=event.node_id, + node_type=event.node_type, + node_run_result=event.node_run_result, + start_at=event.start_at, + error=event.error, + retry_index=retry_count + 1, + ) + + def _handle_fail_branch(self, event: NodeRunFailedEvent): + """ + Handle error by taking the fail branch. + + This strategy converts failures to exceptions and routes execution + through a designated fail-branch edge. + + Args: + event: The failure event + + Returns: + NodeRunExceptionEvent to continue via fail branch + """ + outputs = { + "error_message": event.node_run_result.error, + "error_type": event.node_run_result.error_type, + } + + return NodeRunExceptionEvent( + id=event.id, + node_id=event.node_id, + node_type=event.node_type, + start_at=event.start_at, + node_run_result=NodeRunResult( + status=WorkflowNodeExecutionStatus.EXCEPTION, + inputs=event.node_run_result.inputs, + process_data=event.node_run_result.process_data, + outputs=outputs, + edge_source_handle="fail-branch", + metadata={ + WorkflowNodeExecutionMetadataKey.ERROR_STRATEGY: ErrorStrategyEnum.FAIL_BRANCH, + }, + ), + error=event.error, + ) + + def _handle_default_value(self, event: NodeRunFailedEvent): + """ + Handle error by using default values. + + This strategy allows nodes to fail gracefully by providing + predefined default output values. + + Args: + event: The failure event + + Returns: + NodeRunExceptionEvent with default values + """ + node = self._graph.nodes[event.node_id] + + outputs = { + **node.default_value_dict, + "error_message": event.node_run_result.error, + "error_type": event.node_run_result.error_type, + } + + return NodeRunExceptionEvent( + id=event.id, + node_id=event.node_id, + node_type=event.node_type, + start_at=event.start_at, + node_run_result=NodeRunResult( + status=WorkflowNodeExecutionStatus.EXCEPTION, + inputs=event.node_run_result.inputs, + process_data=event.node_run_result.process_data, + outputs=outputs, + metadata={ + WorkflowNodeExecutionMetadataKey.ERROR_STRATEGY: ErrorStrategyEnum.DEFAULT_VALUE, + }, + ), + error=event.error, + ) diff --git a/api/core/workflow/graph_engine/error_handling/__init__.py b/api/core/workflow/graph_engine/error_handling/__init__.py deleted file mode 100644 index 1316710d0d..0000000000 --- a/api/core/workflow/graph_engine/error_handling/__init__.py +++ /dev/null @@ -1,20 +0,0 @@ -""" -Error handling strategies for graph engine. - -This package implements different error recovery strategies using -the Strategy pattern for clean separation of concerns. -""" - -from .abort_strategy import AbortStrategy -from .default_value_strategy import DefaultValueStrategy -from .error_handler import ErrorHandler -from .fail_branch_strategy import FailBranchStrategy -from .retry_strategy import RetryStrategy - -__all__ = [ - "AbortStrategy", - "DefaultValueStrategy", - "ErrorHandler", - "FailBranchStrategy", - "RetryStrategy", -] diff --git a/api/core/workflow/graph_engine/error_handling/abort_strategy.py b/api/core/workflow/graph_engine/error_handling/abort_strategy.py deleted file mode 100644 index 4593f004f3..0000000000 --- a/api/core/workflow/graph_engine/error_handling/abort_strategy.py +++ /dev/null @@ -1,40 +0,0 @@ -""" -Abort error strategy implementation. -""" - -import logging -from typing import final - -from core.workflow.graph import Graph -from core.workflow.graph_events import GraphNodeEventBase, NodeRunFailedEvent - -logger = logging.getLogger(__name__) - - -@final -class AbortStrategy: - """ - Error strategy that aborts execution on failure. - - This is the default strategy when no other strategy is specified. - It stops the entire graph execution when a node fails. - """ - - def handle_error(self, event: NodeRunFailedEvent, graph: Graph, retry_count: int) -> GraphNodeEventBase | None: - """ - Handle error by aborting execution. - - Args: - event: The failure event - graph: The workflow graph - retry_count: Current retry attempt count (unused) - - Returns: - None - signals abortion - """ - _ = graph - _ = retry_count - logger.error("Node %s failed with ABORT strategy: %s", event.node_id, event.error) - - # Return None to signal that execution should stop - return None diff --git a/api/core/workflow/graph_engine/error_handling/default_value_strategy.py b/api/core/workflow/graph_engine/error_handling/default_value_strategy.py deleted file mode 100644 index 3cdcec88e5..0000000000 --- a/api/core/workflow/graph_engine/error_handling/default_value_strategy.py +++ /dev/null @@ -1,58 +0,0 @@ -""" -Default value error strategy implementation. -""" - -from typing import final - -from core.workflow.enums import ErrorStrategy, WorkflowNodeExecutionMetadataKey, WorkflowNodeExecutionStatus -from core.workflow.graph import Graph -from core.workflow.graph_events import GraphNodeEventBase, NodeRunExceptionEvent, NodeRunFailedEvent -from core.workflow.node_events import NodeRunResult - - -@final -class DefaultValueStrategy: - """ - Error strategy that uses default values on failure. - - This strategy allows nodes to fail gracefully by providing - predefined default output values. - """ - - def handle_error(self, event: NodeRunFailedEvent, graph: Graph, retry_count: int) -> GraphNodeEventBase | None: - """ - Handle error by using default values. - - Args: - event: The failure event - graph: The workflow graph - retry_count: Current retry attempt count (unused) - - Returns: - NodeRunExceptionEvent with default values - """ - _ = retry_count - node = graph.nodes[event.node_id] - - outputs = { - **node.default_value_dict, - "error_message": event.node_run_result.error, - "error_type": event.node_run_result.error_type, - } - - return NodeRunExceptionEvent( - id=event.id, - node_id=event.node_id, - node_type=event.node_type, - start_at=event.start_at, - node_run_result=NodeRunResult( - status=WorkflowNodeExecutionStatus.EXCEPTION, - inputs=event.node_run_result.inputs, - process_data=event.node_run_result.process_data, - outputs=outputs, - metadata={ - WorkflowNodeExecutionMetadataKey.ERROR_STRATEGY: ErrorStrategy.DEFAULT_VALUE, - }, - ), - error=event.error, - ) diff --git a/api/core/workflow/graph_engine/error_handling/error_handler.py b/api/core/workflow/graph_engine/error_handling/error_handler.py deleted file mode 100644 index b51d7e4dad..0000000000 --- a/api/core/workflow/graph_engine/error_handling/error_handler.py +++ /dev/null @@ -1,81 +0,0 @@ -""" -Main error handler that coordinates error strategies. -""" - -from typing import TYPE_CHECKING, final - -from core.workflow.enums import ErrorStrategy as ErrorStrategyEnum -from core.workflow.graph import Graph -from core.workflow.graph_events import GraphNodeEventBase, NodeRunFailedEvent - -from .abort_strategy import AbortStrategy -from .default_value_strategy import DefaultValueStrategy -from .fail_branch_strategy import FailBranchStrategy -from .retry_strategy import RetryStrategy - -if TYPE_CHECKING: - from ..domain import GraphExecution - - -@final -class ErrorHandler: - """ - Coordinates error handling strategies for node failures. - - This acts as a facade for the various error strategies, - selecting and applying the appropriate strategy based on - node configuration. - """ - - def __init__(self, graph: Graph, graph_execution: "GraphExecution") -> None: - """ - Initialize the error handler. - - Args: - graph: The workflow graph - graph_execution: The graph execution state - """ - self._graph = graph - self._graph_execution = graph_execution - - # Initialize strategies - self._abort_strategy = AbortStrategy() - self._retry_strategy = RetryStrategy() - self._fail_branch_strategy = FailBranchStrategy() - self._default_value_strategy = DefaultValueStrategy() - - def handle_node_failure(self, event: NodeRunFailedEvent) -> GraphNodeEventBase | None: - """ - Handle a node failure event. - - Selects and applies the appropriate error strategy based on - the node's configuration. - - Args: - event: The node failure event - - Returns: - Optional new event to process, or None to abort - """ - node = self._graph.nodes[event.node_id] - # Get retry count from NodeExecution - node_execution = self._graph_execution.get_or_create_node_execution(event.node_id) - retry_count = node_execution.retry_count - - # First check if retry is configured and not exhausted - if node.retry and retry_count < node.retry_config.max_retries: - result = self._retry_strategy.handle_error(event, self._graph, retry_count) - if result: - # Retry count will be incremented when NodeRunRetryEvent is handled - return result - - # Apply configured error strategy - strategy = node.error_strategy - - match strategy: - case None: - return self._abort_strategy.handle_error(event, self._graph, retry_count) - case ErrorStrategyEnum.FAIL_BRANCH: - return self._fail_branch_strategy.handle_error(event, self._graph, retry_count) - case ErrorStrategyEnum.DEFAULT_VALUE: - return self._default_value_strategy.handle_error(event, self._graph, retry_count) diff --git a/api/core/workflow/graph_engine/error_handling/fail_branch_strategy.py b/api/core/workflow/graph_engine/error_handling/fail_branch_strategy.py deleted file mode 100644 index 1c156b5be1..0000000000 --- a/api/core/workflow/graph_engine/error_handling/fail_branch_strategy.py +++ /dev/null @@ -1,57 +0,0 @@ -""" -Fail branch error strategy implementation. -""" - -from typing import final - -from core.workflow.enums import ErrorStrategy, WorkflowNodeExecutionMetadataKey, WorkflowNodeExecutionStatus -from core.workflow.graph import Graph -from core.workflow.graph_events import GraphNodeEventBase, NodeRunExceptionEvent, NodeRunFailedEvent -from core.workflow.node_events import NodeRunResult - - -@final -class FailBranchStrategy: - """ - Error strategy that continues execution via a fail branch. - - This strategy converts failures to exceptions and routes execution - through a designated fail-branch edge. - """ - - def handle_error(self, event: NodeRunFailedEvent, graph: Graph, retry_count: int) -> GraphNodeEventBase | None: - """ - Handle error by taking the fail branch. - - Args: - event: The failure event - graph: The workflow graph - retry_count: Current retry attempt count (unused) - - Returns: - NodeRunExceptionEvent to continue via fail branch - """ - _ = graph - _ = retry_count - outputs = { - "error_message": event.node_run_result.error, - "error_type": event.node_run_result.error_type, - } - - return NodeRunExceptionEvent( - id=event.id, - node_id=event.node_id, - node_type=event.node_type, - start_at=event.start_at, - node_run_result=NodeRunResult( - status=WorkflowNodeExecutionStatus.EXCEPTION, - inputs=event.node_run_result.inputs, - process_data=event.node_run_result.process_data, - outputs=outputs, - edge_source_handle="fail-branch", - metadata={ - WorkflowNodeExecutionMetadataKey.ERROR_STRATEGY: ErrorStrategy.FAIL_BRANCH, - }, - ), - error=event.error, - ) diff --git a/api/core/workflow/graph_engine/error_handling/retry_strategy.py b/api/core/workflow/graph_engine/error_handling/retry_strategy.py deleted file mode 100644 index e4010b6bdb..0000000000 --- a/api/core/workflow/graph_engine/error_handling/retry_strategy.py +++ /dev/null @@ -1,52 +0,0 @@ -""" -Retry error strategy implementation. -""" - -import time -from typing import final - -from core.workflow.graph import Graph -from core.workflow.graph_events import GraphNodeEventBase, NodeRunFailedEvent, NodeRunRetryEvent - - -@final -class RetryStrategy: - """ - Error strategy that retries failed nodes. - - This strategy re-attempts node execution up to a configured - maximum number of retries with configurable intervals. - """ - - def handle_error(self, event: NodeRunFailedEvent, graph: Graph, retry_count: int) -> GraphNodeEventBase | None: - """ - Handle error by retrying the node. - - Args: - event: The failure event - graph: The workflow graph - retry_count: Current retry attempt count - - Returns: - NodeRunRetryEvent if retry should occur, None otherwise - """ - node = graph.nodes[event.node_id] - - # Check if we've exceeded max retries - if not node.retry or retry_count >= node.retry_config.max_retries: - return None - - # Wait for retry interval - time.sleep(node.retry_config.retry_interval_seconds) - - # Create retry event - return NodeRunRetryEvent( - id=event.id, - node_title=node.title, - node_id=event.node_id, - node_type=event.node_type, - node_run_result=event.node_run_result, - start_at=event.start_at, - error=event.error, - retry_index=retry_count + 1, - ) diff --git a/api/core/workflow/graph_engine/event_management/event_handlers.py b/api/core/workflow/graph_engine/event_management/event_handlers.py index 3ab69776a4..244f4a4d86 100644 --- a/api/core/workflow/graph_engine/event_management/event_handlers.py +++ b/api/core/workflow/graph_engine/event_management/event_handlers.py @@ -3,6 +3,7 @@ Event handler implementations for different event types. """ import logging +from functools import singledispatchmethod from typing import TYPE_CHECKING, final from core.workflow.entities import GraphRuntimeState @@ -31,9 +32,9 @@ from ..domain.graph_execution import GraphExecution from ..response_coordinator import ResponseStreamCoordinator if TYPE_CHECKING: - from ..error_handling import ErrorHandler + from ..error_handler import ErrorHandler + from ..graph_state_manager import GraphStateManager from ..graph_traversal import EdgeProcessor - from ..state_management import UnifiedStateManager from .event_manager import EventManager logger = logging.getLogger(__name__) @@ -56,7 +57,7 @@ class EventHandler: response_coordinator: ResponseStreamCoordinator, event_collector: "EventManager", edge_processor: "EdgeProcessor", - state_manager: "UnifiedStateManager", + state_manager: "GraphStateManager", error_handler: "ErrorHandler", ) -> None: """ @@ -81,7 +82,7 @@ class EventHandler: self._state_manager = state_manager self._error_handler = error_handler - def handle_event(self, event: GraphNodeEventBase) -> None: + def dispatch(self, event: GraphNodeEventBase) -> None: """ Handle any node event by dispatching to the appropriate handler. @@ -92,42 +93,27 @@ class EventHandler: if event.in_loop_id or event.in_iteration_id: self._event_collector.collect(event) return + return self._dispatch(event) - # Handle specific event types - if isinstance(event, NodeRunStartedEvent): - self._handle_node_started(event) - elif isinstance(event, NodeRunStreamChunkEvent): - self._handle_stream_chunk(event) - elif isinstance(event, NodeRunSucceededEvent): - self._handle_node_succeeded(event) - elif isinstance(event, NodeRunFailedEvent): - self._handle_node_failed(event) - elif isinstance(event, NodeRunExceptionEvent): - self._handle_node_exception(event) - elif isinstance(event, NodeRunRetryEvent): - self._handle_node_retry(event) - elif isinstance( - event, - ( - NodeRunIterationStartedEvent, - NodeRunIterationNextEvent, - NodeRunIterationSucceededEvent, - NodeRunIterationFailedEvent, - NodeRunLoopStartedEvent, - NodeRunLoopNextEvent, - NodeRunLoopSucceededEvent, - NodeRunLoopFailedEvent, - NodeRunAgentLogEvent, - ), - ): - # Iteration and loop events are collected directly - self._event_collector.collect(event) - else: - # Collect unhandled events - self._event_collector.collect(event) - logger.warning("Unhandled event type: %s", type(event).__name__) + @singledispatchmethod + def _dispatch(self, event: GraphNodeEventBase) -> None: + self._event_collector.collect(event) + logger.warning("Unhandled event type: %s", type(event).__name__) - def _handle_node_started(self, event: NodeRunStartedEvent) -> None: + @_dispatch.register(NodeRunIterationStartedEvent) + @_dispatch.register(NodeRunIterationNextEvent) + @_dispatch.register(NodeRunIterationSucceededEvent) + @_dispatch.register(NodeRunIterationFailedEvent) + @_dispatch.register(NodeRunLoopStartedEvent) + @_dispatch.register(NodeRunLoopNextEvent) + @_dispatch.register(NodeRunLoopSucceededEvent) + @_dispatch.register(NodeRunLoopFailedEvent) + @_dispatch.register(NodeRunAgentLogEvent) + def _(self, event: GraphNodeEventBase) -> None: + self._event_collector.collect(event) + + @_dispatch.register + def _(self, event: NodeRunStartedEvent) -> None: """ Handle node started event. @@ -144,7 +130,8 @@ class EventHandler: # Collect the event self._event_collector.collect(event) - def _handle_stream_chunk(self, event: NodeRunStreamChunkEvent) -> None: + @_dispatch.register + def _(self, event: NodeRunStreamChunkEvent) -> None: """ Handle stream chunk event with full processing. @@ -158,7 +145,8 @@ class EventHandler: for stream_event in streaming_events: self._event_collector.collect(stream_event) - def _handle_node_succeeded(self, event: NodeRunSucceededEvent) -> None: + @_dispatch.register + def _(self, event: NodeRunSucceededEvent) -> None: """ Handle node success by coordinating subsystems. @@ -208,7 +196,8 @@ class EventHandler: # Collect the event self._event_collector.collect(event) - def _handle_node_failed(self, event: NodeRunFailedEvent) -> None: + @_dispatch.register + def _(self, event: NodeRunFailedEvent) -> None: """ Handle node failure using error handler. @@ -223,14 +212,15 @@ class EventHandler: if result: # Process the resulting event (retry, exception, etc.) - self.handle_event(result) + self.dispatch(result) else: # Abort execution self._graph_execution.fail(RuntimeError(event.error)) self._event_collector.collect(event) self._state_manager.finish_execution(event.node_id) - def _handle_node_exception(self, event: NodeRunExceptionEvent) -> None: + @_dispatch.register + def _(self, event: NodeRunExceptionEvent) -> None: """ Handle node exception event (fail-branch strategy). @@ -241,7 +231,8 @@ class EventHandler: node_execution = self._graph_execution.get_or_create_node_execution(event.node_id) node_execution.mark_taken() - def _handle_node_retry(self, event: NodeRunRetryEvent) -> None: + @_dispatch.register + def _(self, event: NodeRunRetryEvent) -> None: """ Handle node retry event. diff --git a/api/core/workflow/graph_engine/graph_engine.py b/api/core/workflow/graph_engine/graph_engine.py index 45f3ada7f5..164ae41cca 100644 --- a/api/core/workflow/graph_engine/graph_engine.py +++ b/api/core/workflow/graph_engine/graph_engine.py @@ -8,16 +8,16 @@ Domain-Driven Design principles for improved maintainability and testability. import contextvars import logging import queue -from collections.abc import Generator, Mapping +from collections.abc import Generator from typing import final from flask import Flask, current_app -from core.app.entities.app_invoke_entities import InvokeFrom from core.workflow.entities import GraphRuntimeState from core.workflow.enums import NodeExecutionType from core.workflow.graph import Graph from core.workflow.graph.read_only_state_wrapper import ReadOnlyGraphRuntimeStateWrapper +from core.workflow.graph_engine.ready_queue import InMemoryReadyQueue from core.workflow.graph_events import ( GraphEngineEvent, GraphNodeEventBase, @@ -26,19 +26,19 @@ from core.workflow.graph_events import ( GraphRunStartedEvent, GraphRunSucceededEvent, ) -from models.enums import UserFrom from .command_processing import AbortCommandHandler, CommandProcessor -from .domain import ExecutionContext, GraphExecution +from .domain import GraphExecution from .entities.commands import AbortCommand -from .error_handling import ErrorHandler +from .error_handler import ErrorHandler from .event_management import EventHandler, EventManager +from .graph_state_manager import GraphStateManager from .graph_traversal import EdgeProcessor, SkipPropagator from .layers.base import GraphEngineLayer from .orchestration import Dispatcher, ExecutionCoordinator from .protocols.command_channel import CommandChannel +from .ready_queue import ReadyQueue, ReadyQueueState, create_ready_queue_from_state from .response_coordinator import ResponseStreamCoordinator -from .state_management import UnifiedStateManager from .worker_management import WorkerPool logger = logging.getLogger(__name__) @@ -55,18 +55,9 @@ class GraphEngine: def __init__( self, - tenant_id: str, - app_id: str, workflow_id: str, - user_id: str, - user_from: UserFrom, - invoke_from: InvokeFrom, - call_depth: int, graph: Graph, - graph_config: Mapping[str, object], graph_runtime_state: GraphRuntimeState, - max_execution_steps: int, - max_execution_time: int, command_channel: CommandChannel, min_workers: int | None = None, max_workers: int | None = None, @@ -75,27 +66,14 @@ class GraphEngine: ) -> None: """Initialize the graph engine with all subsystems and dependencies.""" - # === Domain Models === - # Execution context encapsulates workflow execution metadata - self._execution_context = ExecutionContext( - tenant_id=tenant_id, - app_id=app_id, - workflow_id=workflow_id, - user_id=user_id, - user_from=user_from, - invoke_from=invoke_from, - call_depth=call_depth, - max_execution_steps=max_execution_steps, - max_execution_time=max_execution_time, - ) - # Graph execution tracks the overall execution state self._graph_execution = GraphExecution(workflow_id=workflow_id) + if graph_runtime_state.graph_execution_json != "": + self._graph_execution.loads(graph_runtime_state.graph_execution_json) # === Core Dependencies === # Graph structure and configuration self._graph = graph - self._graph_config = graph_config self._graph_runtime_state = graph_runtime_state self._command_channel = command_channel @@ -107,20 +85,28 @@ class GraphEngine: self._scale_down_idle_time = scale_down_idle_time # === Execution Queues === - # Queue for nodes ready to execute - self._ready_queue: queue.Queue[str] = queue.Queue() + # Create ready queue from saved state or initialize new one + self._ready_queue: ReadyQueue + if self._graph_runtime_state.ready_queue_json == "": + self._ready_queue = InMemoryReadyQueue() + else: + ready_queue_state = ReadyQueueState.model_validate_json(self._graph_runtime_state.ready_queue_json) + self._ready_queue = create_ready_queue_from_state(ready_queue_state) + # Queue for events generated during execution self._event_queue: queue.Queue[GraphNodeEventBase] = queue.Queue() # === State Management === # Unified state manager handles all node state transitions and queue operations - self._state_manager = UnifiedStateManager(self._graph, self._ready_queue) + self._state_manager = GraphStateManager(self._graph, self._ready_queue) # === Response Coordination === # Coordinates response streaming from response nodes self._response_coordinator = ResponseStreamCoordinator( variable_pool=self._graph_runtime_state.variable_pool, graph=self._graph ) + if graph_runtime_state.response_coordinator_json != "": + self._response_coordinator.loads(graph_runtime_state.response_coordinator_json) # === Event Management === # Event manager handles both collection and emission of events @@ -216,7 +202,6 @@ class GraphEngine: event_handler=self._event_handler_registry, event_collector=self._event_manager, execution_coordinator=self._execution_coordinator, - max_execution_time=self._execution_context.max_execution_time, event_emitter=self._event_manager, ) diff --git a/api/core/workflow/graph_engine/state_management/unified_state_manager.py b/api/core/workflow/graph_engine/graph_state_manager.py similarity index 90% rename from api/core/workflow/graph_engine/state_management/unified_state_manager.py rename to api/core/workflow/graph_engine/graph_state_manager.py index 258b84c341..22a3a826fc 100644 --- a/api/core/workflow/graph_engine/state_management/unified_state_manager.py +++ b/api/core/workflow/graph_engine/graph_state_manager.py @@ -1,11 +1,7 @@ """ -Unified state manager that combines node, edge, and execution tracking. - -This is a proposed simplification that merges NodeStateManager, EdgeStateManager, -and ExecutionTracker into a single cohesive class. +Graph state manager that combines node, edge, and execution tracking. """ -import queue import threading from collections.abc import Sequence from typing import TypedDict, final @@ -13,6 +9,8 @@ from typing import TypedDict, final from core.workflow.enums import NodeState from core.workflow.graph import Edge, Graph +from .ready_queue import ReadyQueue + class EdgeStateAnalysis(TypedDict): """Analysis result for edge states.""" @@ -23,24 +21,10 @@ class EdgeStateAnalysis(TypedDict): @final -class UnifiedStateManager: - """ - Unified manager for all graph state operations. - - This class combines the responsibilities of: - - NodeStateManager: Node state transitions and ready queue - - EdgeStateManager: Edge state transitions and analysis - - ExecutionTracker: Tracking executing nodes - - Benefits: - - Single lock for all state operations (reduced contention) - - Cohesive state management interface - - Simplified dependency injection - """ - - def __init__(self, graph: Graph, ready_queue: queue.Queue[str]) -> None: +class GraphStateManager: + def __init__(self, graph: Graph, ready_queue: ReadyQueue) -> None: """ - Initialize the unified state manager. + Initialize the state manager. Args: graph: The workflow graph diff --git a/api/core/workflow/graph_engine/graph_traversal/edge_processor.py b/api/core/workflow/graph_engine/graph_traversal/edge_processor.py index c5634ed984..9bd0f86fbf 100644 --- a/api/core/workflow/graph_engine/graph_traversal/edge_processor.py +++ b/api/core/workflow/graph_engine/graph_traversal/edge_processor.py @@ -9,8 +9,8 @@ from core.workflow.enums import NodeExecutionType from core.workflow.graph import Edge, Graph from core.workflow.graph_events import NodeRunStreamChunkEvent +from ..graph_state_manager import GraphStateManager from ..response_coordinator import ResponseStreamCoordinator -from ..state_management import UnifiedStateManager if TYPE_CHECKING: from .skip_propagator import SkipPropagator @@ -29,7 +29,7 @@ class EdgeProcessor: def __init__( self, graph: Graph, - state_manager: UnifiedStateManager, + state_manager: GraphStateManager, response_coordinator: ResponseStreamCoordinator, skip_propagator: "SkipPropagator", ) -> None: diff --git a/api/core/workflow/graph_engine/graph_traversal/skip_propagator.py b/api/core/workflow/graph_engine/graph_traversal/skip_propagator.py index 51ab3c6739..78f8ecdcdf 100644 --- a/api/core/workflow/graph_engine/graph_traversal/skip_propagator.py +++ b/api/core/workflow/graph_engine/graph_traversal/skip_propagator.py @@ -7,7 +7,7 @@ from typing import final from core.workflow.graph import Edge, Graph -from ..state_management import UnifiedStateManager +from ..graph_state_manager import GraphStateManager @final @@ -22,7 +22,7 @@ class SkipPropagator: def __init__( self, graph: Graph, - state_manager: UnifiedStateManager, + state_manager: GraphStateManager, ) -> None: """ Initialize the skip propagator. diff --git a/api/core/workflow/graph_engine/orchestration/dispatcher.py b/api/core/workflow/graph_engine/orchestration/dispatcher.py index 80f744c941..a7229ce4e8 100644 --- a/api/core/workflow/graph_engine/orchestration/dispatcher.py +++ b/api/core/workflow/graph_engine/orchestration/dispatcher.py @@ -34,7 +34,6 @@ class Dispatcher: event_handler: "EventHandler", event_collector: EventManager, execution_coordinator: ExecutionCoordinator, - max_execution_time: int, event_emitter: EventManager | None = None, ) -> None: """ @@ -45,14 +44,12 @@ class Dispatcher: event_handler: Event handler registry for processing events event_collector: Event manager for collecting unhandled events execution_coordinator: Coordinator for execution flow - max_execution_time: Maximum execution time in seconds event_emitter: Optional event manager to signal completion """ self._event_queue = event_queue self._event_handler = event_handler self._event_collector = event_collector self._execution_coordinator = execution_coordinator - self._max_execution_time = max_execution_time self._event_emitter = event_emitter self._thread: threading.Thread | None = None @@ -89,7 +86,7 @@ class Dispatcher: try: event = self._event_queue.get(timeout=0.1) # Route to the event handler - self._event_handler.handle_event(event) + self._event_handler.dispatch(event) self._event_queue.task_done() except queue.Empty: # Check if execution is complete diff --git a/api/core/workflow/graph_engine/orchestration/execution_coordinator.py b/api/core/workflow/graph_engine/orchestration/execution_coordinator.py index 234a3607c3..b35e8bb6d8 100644 --- a/api/core/workflow/graph_engine/orchestration/execution_coordinator.py +++ b/api/core/workflow/graph_engine/orchestration/execution_coordinator.py @@ -7,7 +7,7 @@ from typing import TYPE_CHECKING, final from ..command_processing import CommandProcessor from ..domain import GraphExecution from ..event_management import EventManager -from ..state_management import UnifiedStateManager +from ..graph_state_manager import GraphStateManager from ..worker_management import WorkerPool if TYPE_CHECKING: @@ -26,7 +26,7 @@ class ExecutionCoordinator: def __init__( self, graph_execution: GraphExecution, - state_manager: UnifiedStateManager, + state_manager: GraphStateManager, event_handler: "EventHandler", event_collector: EventManager, command_processor: CommandProcessor, diff --git a/api/core/workflow/graph_engine/protocols/error_strategy.py b/api/core/workflow/graph_engine/protocols/error_strategy.py deleted file mode 100644 index bf8b316423..0000000000 --- a/api/core/workflow/graph_engine/protocols/error_strategy.py +++ /dev/null @@ -1,31 +0,0 @@ -""" -Base error strategy protocol. -""" - -from typing import Protocol - -from core.workflow.graph import Graph -from core.workflow.graph_events import GraphNodeEventBase, NodeRunFailedEvent - - -class ErrorStrategy(Protocol): - """ - Protocol for error handling strategies. - - Each strategy implements a different approach to handling - node execution failures. - """ - - def handle_error(self, event: NodeRunFailedEvent, graph: Graph, retry_count: int) -> GraphNodeEventBase | None: - """ - Handle a node failure event. - - Args: - event: The failure event - graph: The workflow graph - retry_count: Current retry attempt count - - Returns: - Optional new event to process, or None to stop - """ - ... diff --git a/api/core/workflow/graph_engine/ready_queue/__init__.py b/api/core/workflow/graph_engine/ready_queue/__init__.py new file mode 100644 index 0000000000..acba0e961c --- /dev/null +++ b/api/core/workflow/graph_engine/ready_queue/__init__.py @@ -0,0 +1,12 @@ +""" +Ready queue implementations for GraphEngine. + +This package contains the protocol and implementations for managing +the queue of nodes ready for execution. +""" + +from .factory import create_ready_queue_from_state +from .in_memory import InMemoryReadyQueue +from .protocol import ReadyQueue, ReadyQueueState + +__all__ = ["InMemoryReadyQueue", "ReadyQueue", "ReadyQueueState", "create_ready_queue_from_state"] diff --git a/api/core/workflow/graph_engine/ready_queue/factory.py b/api/core/workflow/graph_engine/ready_queue/factory.py new file mode 100644 index 0000000000..1144e1de69 --- /dev/null +++ b/api/core/workflow/graph_engine/ready_queue/factory.py @@ -0,0 +1,35 @@ +""" +Factory for creating ReadyQueue instances from serialized state. +""" + +from typing import TYPE_CHECKING + +from .in_memory import InMemoryReadyQueue +from .protocol import ReadyQueueState + +if TYPE_CHECKING: + from .protocol import ReadyQueue + + +def create_ready_queue_from_state(state: ReadyQueueState) -> "ReadyQueue": + """ + Create a ReadyQueue instance from a serialized state. + + Args: + state: The serialized queue state (Pydantic model, dict, or JSON string), or None for a new empty queue + + Returns: + A ReadyQueue instance initialized with the given state + + Raises: + ValueError: If the queue type is unknown or version is unsupported + """ + if state.type == "InMemoryReadyQueue": + if state.version != "1.0": + raise ValueError(f"Unsupported InMemoryReadyQueue version: {state.version}") + queue = InMemoryReadyQueue() + # Always pass as JSON string to loads() + queue.loads(state.model_dump_json()) + return queue + else: + raise ValueError(f"Unknown ready queue type: {state.type}") diff --git a/api/core/workflow/graph_engine/ready_queue/in_memory.py b/api/core/workflow/graph_engine/ready_queue/in_memory.py new file mode 100644 index 0000000000..f2c265ece0 --- /dev/null +++ b/api/core/workflow/graph_engine/ready_queue/in_memory.py @@ -0,0 +1,140 @@ +""" +In-memory implementation of the ReadyQueue protocol. + +This implementation wraps Python's standard queue.Queue and adds +serialization capabilities for state storage. +""" + +import queue +from typing import final + +from .protocol import ReadyQueue, ReadyQueueState + + +@final +class InMemoryReadyQueue(ReadyQueue): + """ + In-memory ready queue implementation with serialization support. + + This implementation uses Python's queue.Queue internally and provides + methods to serialize and restore the queue state. + """ + + def __init__(self, maxsize: int = 0) -> None: + """ + Initialize the in-memory ready queue. + + Args: + maxsize: Maximum size of the queue (0 for unlimited) + """ + self._queue: queue.Queue[str] = queue.Queue(maxsize=maxsize) + + def put(self, item: str) -> None: + """ + Add a node ID to the ready queue. + + Args: + item: The node ID to add to the queue + """ + self._queue.put(item) + + def get(self, timeout: float | None = None) -> str: + """ + Retrieve and remove a node ID from the queue. + + Args: + timeout: Maximum time to wait for an item (None for blocking) + + Returns: + The node ID retrieved from the queue + + Raises: + queue.Empty: If timeout expires and no item is available + """ + if timeout is None: + return self._queue.get(block=True) + return self._queue.get(timeout=timeout) + + def task_done(self) -> None: + """ + Indicate that a previously retrieved task is complete. + + Used by worker threads to signal task completion for + join() synchronization. + """ + self._queue.task_done() + + def empty(self) -> bool: + """ + Check if the queue is empty. + + Returns: + True if the queue has no items, False otherwise + """ + return self._queue.empty() + + def qsize(self) -> int: + """ + Get the approximate size of the queue. + + Returns: + The approximate number of items in the queue + """ + return self._queue.qsize() + + def dumps(self) -> str: + """ + Serialize the queue state to a JSON string for storage. + + Returns: + A JSON string containing the serialized queue state + """ + # Extract all items from the queue without removing them + items: list[str] = [] + temp_items: list[str] = [] + + # Drain the queue temporarily to get all items + while not self._queue.empty(): + try: + item = self._queue.get_nowait() + temp_items.append(item) + items.append(item) + except queue.Empty: + break + + # Put items back in the same order + for item in temp_items: + self._queue.put(item) + + state = ReadyQueueState( + type="InMemoryReadyQueue", + version="1.0", + items=items, + ) + return state.model_dump_json() + + def loads(self, data: str) -> None: + """ + Restore the queue state from a JSON string. + + Args: + data: The JSON string containing the serialized queue state to restore + """ + state = ReadyQueueState.model_validate_json(data) + + if state.type != "InMemoryReadyQueue": + raise ValueError(f"Invalid serialized data type: {state.type}") + + if state.version != "1.0": + raise ValueError(f"Unsupported version: {state.version}") + + # Clear the current queue + while not self._queue.empty(): + try: + self._queue.get_nowait() + except queue.Empty: + break + + # Restore items + for item in state.items: + self._queue.put(item) diff --git a/api/core/workflow/graph_engine/ready_queue/protocol.py b/api/core/workflow/graph_engine/ready_queue/protocol.py new file mode 100644 index 0000000000..97d3ea6dd2 --- /dev/null +++ b/api/core/workflow/graph_engine/ready_queue/protocol.py @@ -0,0 +1,104 @@ +""" +ReadyQueue protocol for GraphEngine node execution queue. + +This protocol defines the interface for managing the queue of nodes ready +for execution, supporting both in-memory and persistent storage scenarios. +""" + +from collections.abc import Sequence +from typing import Protocol + +from pydantic import BaseModel, Field + + +class ReadyQueueState(BaseModel): + """ + Pydantic model for serialized ready queue state. + + This defines the structure of the data returned by dumps() + and expected by loads() for ready queue serialization. + """ + + type: str = Field(description="Queue implementation type (e.g., 'InMemoryReadyQueue')") + version: str = Field(description="Serialization format version") + items: Sequence[str] = Field(default_factory=list, description="List of node IDs in the queue") + + +class ReadyQueue(Protocol): + """ + Protocol for managing nodes ready for execution in GraphEngine. + + This protocol defines the interface that any ready queue implementation + must provide, enabling both in-memory queues and persistent queues + that can be serialized for state storage. + """ + + def put(self, item: str) -> None: + """ + Add a node ID to the ready queue. + + Args: + item: The node ID to add to the queue + """ + ... + + def get(self, timeout: float | None = None) -> str: + """ + Retrieve and remove a node ID from the queue. + + Args: + timeout: Maximum time to wait for an item (None for blocking) + + Returns: + The node ID retrieved from the queue + + Raises: + queue.Empty: If timeout expires and no item is available + """ + ... + + def task_done(self) -> None: + """ + Indicate that a previously retrieved task is complete. + + Used by worker threads to signal task completion for + join() synchronization. + """ + ... + + def empty(self) -> bool: + """ + Check if the queue is empty. + + Returns: + True if the queue has no items, False otherwise + """ + ... + + def qsize(self) -> int: + """ + Get the approximate size of the queue. + + Returns: + The approximate number of items in the queue + """ + ... + + def dumps(self) -> str: + """ + Serialize the queue state to a JSON string for storage. + + Returns: + A JSON string containing the serialized queue state + that can be persisted and later restored + """ + ... + + def loads(self, data: str) -> None: + """ + Restore the queue state from a JSON string. + + Args: + data: The JSON string containing the serialized queue state to restore + """ + ... diff --git a/api/core/workflow/graph_engine/response_coordinator/coordinator.py b/api/core/workflow/graph_engine/response_coordinator/coordinator.py index b5224cbc22..985992f3f1 100644 --- a/api/core/workflow/graph_engine/response_coordinator/coordinator.py +++ b/api/core/workflow/graph_engine/response_coordinator/coordinator.py @@ -9,9 +9,11 @@ import logging from collections import deque from collections.abc import Sequence from threading import RLock -from typing import TypeAlias, final +from typing import Literal, TypeAlias, final from uuid import uuid4 +from pydantic import BaseModel, Field + from core.workflow.entities.variable_pool import VariablePool from core.workflow.enums import NodeExecutionType, NodeState from core.workflow.graph import Graph @@ -28,6 +30,43 @@ NodeID: TypeAlias = str EdgeID: TypeAlias = str +class ResponseSessionState(BaseModel): + """Serializable representation of a response session.""" + + node_id: str + index: int = Field(default=0, ge=0) + + +class StreamBufferState(BaseModel): + """Serializable representation of buffered stream chunks.""" + + selector: tuple[str, ...] + events: list[NodeRunStreamChunkEvent] = Field(default_factory=list) + + +class StreamPositionState(BaseModel): + """Serializable representation for stream read positions.""" + + selector: tuple[str, ...] + position: int = Field(default=0, ge=0) + + +class ResponseStreamCoordinatorState(BaseModel): + """Serialized snapshot of ResponseStreamCoordinator.""" + + type: Literal["ResponseStreamCoordinator"] = Field(default="ResponseStreamCoordinator") + version: str = Field(default="1.0") + response_nodes: Sequence[str] = Field(default_factory=list) + active_session: ResponseSessionState | None = None + waiting_sessions: Sequence[ResponseSessionState] = Field(default_factory=list) + pending_sessions: Sequence[ResponseSessionState] = Field(default_factory=list) + node_execution_ids: dict[str, str] = Field(default_factory=dict) + paths_map: dict[str, list[list[str]]] = Field(default_factory=dict) + stream_buffers: Sequence[StreamBufferState] = Field(default_factory=list) + stream_positions: Sequence[StreamPositionState] = Field(default_factory=list) + closed_streams: Sequence[tuple[str, ...]] = Field(default_factory=list) + + @final class ResponseStreamCoordinator: """ @@ -69,6 +108,8 @@ class ResponseStreamCoordinator: def register(self, response_node_id: NodeID) -> None: with self._lock: + if response_node_id in self._response_nodes: + return self._response_nodes.add(response_node_id) # Build and save paths map for this response node @@ -558,3 +599,98 @@ class ResponseStreamCoordinator: """ key = tuple(selector) return key in self._closed_streams + + def _serialize_session(self, session: ResponseSession | None) -> ResponseSessionState | None: + """Convert an in-memory session into its serializable form.""" + + if session is None: + return None + return ResponseSessionState(node_id=session.node_id, index=session.index) + + def _session_from_state(self, session_state: ResponseSessionState) -> ResponseSession: + """Rebuild a response session from serialized data.""" + + node = self._graph.nodes.get(session_state.node_id) + if node is None: + raise ValueError(f"Unknown response node '{session_state.node_id}' in serialized state") + + session = ResponseSession.from_node(node) + session.index = session_state.index + return session + + def dumps(self) -> str: + """Serialize coordinator state to JSON.""" + + with self._lock: + state = ResponseStreamCoordinatorState( + response_nodes=sorted(self._response_nodes), + active_session=self._serialize_session(self._active_session), + waiting_sessions=[ + session_state + for session in list(self._waiting_sessions) + if (session_state := self._serialize_session(session)) is not None + ], + pending_sessions=[ + session_state + for _, session in sorted(self._response_sessions.items()) + if (session_state := self._serialize_session(session)) is not None + ], + node_execution_ids=dict(sorted(self._node_execution_ids.items())), + paths_map={ + node_id: [path.edges.copy() for path in paths] + for node_id, paths in sorted(self._paths_maps.items()) + }, + stream_buffers=[ + StreamBufferState( + selector=selector, + events=[event.model_copy(deep=True) for event in events], + ) + for selector, events in sorted(self._stream_buffers.items()) + ], + stream_positions=[ + StreamPositionState(selector=selector, position=position) + for selector, position in sorted(self._stream_positions.items()) + ], + closed_streams=sorted(self._closed_streams), + ) + return state.model_dump_json() + + def loads(self, data: str) -> None: + """Restore coordinator state from JSON.""" + + state = ResponseStreamCoordinatorState.model_validate_json(data) + + if state.type != "ResponseStreamCoordinator": + raise ValueError(f"Invalid serialized data type: {state.type}") + + if state.version != "1.0": + raise ValueError(f"Unsupported serialized version: {state.version}") + + with self._lock: + self._response_nodes = set(state.response_nodes) + self._paths_maps = { + node_id: [Path(edges=list(path_edges)) for path_edges in paths] + for node_id, paths in state.paths_map.items() + } + self._node_execution_ids = dict(state.node_execution_ids) + + self._stream_buffers = { + tuple(buffer.selector): [event.model_copy(deep=True) for event in buffer.events] + for buffer in state.stream_buffers + } + self._stream_positions = { + tuple(position.selector): position.position for position in state.stream_positions + } + for selector in self._stream_buffers: + self._stream_positions.setdefault(selector, 0) + + self._closed_streams = {tuple(selector) for selector in state.closed_streams} + + self._waiting_sessions = deque( + self._session_from_state(session_state) for session_state in state.waiting_sessions + ) + self._response_sessions = { + session_state.node_id: self._session_from_state(session_state) + for session_state in state.pending_sessions + } + self._active_session = self._session_from_state(state.active_session) if state.active_session else None diff --git a/api/core/workflow/graph_engine/response_coordinator/path.py b/api/core/workflow/graph_engine/response_coordinator/path.py index d83dd5e77b..50f2f4eb21 100644 --- a/api/core/workflow/graph_engine/response_coordinator/path.py +++ b/api/core/workflow/graph_engine/response_coordinator/path.py @@ -19,7 +19,7 @@ class Path: Note: This is an internal class not exposed in the public API. """ - edges: list[EdgeID] = field(default_factory=list) + edges: list[EdgeID] = field(default_factory=list[EdgeID]) def contains_edge(self, edge_id: EdgeID) -> bool: """Check if this path contains the given edge.""" diff --git a/api/core/workflow/graph_engine/state_management/__init__.py b/api/core/workflow/graph_engine/state_management/__init__.py deleted file mode 100644 index 9a632a3b9f..0000000000 --- a/api/core/workflow/graph_engine/state_management/__init__.py +++ /dev/null @@ -1,12 +0,0 @@ -""" -State management subsystem for graph engine. - -This package manages node states, edge states, and execution tracking -during workflow graph execution. -""" - -from .unified_state_manager import UnifiedStateManager - -__all__ = [ - "UnifiedStateManager", -] diff --git a/api/core/workflow/graph_engine/worker.py b/api/core/workflow/graph_engine/worker.py index e7462309c9..42c9b936dd 100644 --- a/api/core/workflow/graph_engine/worker.py +++ b/api/core/workflow/graph_engine/worker.py @@ -22,6 +22,8 @@ from core.workflow.graph_events import GraphNodeEventBase, NodeRunFailedEvent from core.workflow.nodes.base.node import Node from libs.flask_utils import preserve_flask_contexts +from .ready_queue import ReadyQueue + @final class Worker(threading.Thread): @@ -35,7 +37,7 @@ class Worker(threading.Thread): def __init__( self, - ready_queue: queue.Queue[str], + ready_queue: ReadyQueue, event_queue: queue.Queue[GraphNodeEventBase], graph: Graph, worker_id: int = 0, @@ -46,7 +48,7 @@ class Worker(threading.Thread): Initialize worker thread. Args: - ready_queue: Queue containing node IDs ready for execution + ready_queue: Ready queue containing node IDs ready for execution event_queue: Queue for pushing execution events graph: Graph containing nodes to execute worker_id: Unique identifier for this worker diff --git a/api/core/workflow/graph_engine/worker_management/worker_pool.py b/api/core/workflow/graph_engine/worker_management/worker_pool.py index 00328fbda1..a9aada9ea5 100644 --- a/api/core/workflow/graph_engine/worker_management/worker_pool.py +++ b/api/core/workflow/graph_engine/worker_management/worker_pool.py @@ -14,6 +14,7 @@ from configs import dify_config from core.workflow.graph import Graph from core.workflow.graph_events import GraphNodeEventBase +from ..ready_queue import ReadyQueue from ..worker import Worker logger = logging.getLogger(__name__) @@ -35,7 +36,7 @@ class WorkerPool: def __init__( self, - ready_queue: queue.Queue[str], + ready_queue: ReadyQueue, event_queue: queue.Queue[GraphNodeEventBase], graph: Graph, flask_app: "Flask | None" = None, @@ -49,7 +50,7 @@ class WorkerPool: Initialize the simple worker pool. Args: - ready_queue: Queue of nodes ready for execution + ready_queue: Ready queue for nodes ready for execution event_queue: Queue for worker events graph: The workflow graph flask_app: Optional Flask app for context preservation diff --git a/api/core/workflow/graph_events/agent.py b/api/core/workflow/graph_events/agent.py index 971a2b918e..759fe3a71c 100644 --- a/api/core/workflow/graph_events/agent.py +++ b/api/core/workflow/graph_events/agent.py @@ -1,5 +1,5 @@ from collections.abc import Mapping -from typing import Any, Optional +from typing import Any from pydantic import Field @@ -14,4 +14,4 @@ class NodeRunAgentLogEvent(GraphAgentNodeEventBase): error: str | None = Field(..., description="error") status: str = Field(..., description="status") data: Mapping[str, Any] = Field(..., description="data") - metadata: Optional[Mapping[str, Any]] = Field(default=None, description="metadata") + metadata: Mapping[str, object] = Field(default_factory=dict) diff --git a/api/core/workflow/graph_events/base.py b/api/core/workflow/graph_events/base.py index 98ffef7924..3714679201 100644 --- a/api/core/workflow/graph_events/base.py +++ b/api/core/workflow/graph_events/base.py @@ -1,5 +1,3 @@ -from typing import Optional - from pydantic import BaseModel, Field from core.workflow.enums import NodeType @@ -19,9 +17,9 @@ class GraphNodeEventBase(GraphEngineEvent): node_id: str node_type: NodeType - in_iteration_id: Optional[str] = None + in_iteration_id: str | None = None """iteration id if node is in iteration""" - in_loop_id: Optional[str] = None + in_loop_id: str | None = None """loop id if node is in loop""" # The version of the node, or "1" if not specified. diff --git a/api/core/workflow/graph_events/graph.py b/api/core/workflow/graph_events/graph.py index 26ae5db336..5d13833faa 100644 --- a/api/core/workflow/graph_events/graph.py +++ b/api/core/workflow/graph_events/graph.py @@ -1,5 +1,3 @@ -from typing import Any, Optional - from pydantic import Field from core.workflow.graph_events import BaseGraphEvent @@ -10,7 +8,7 @@ class GraphRunStartedEvent(BaseGraphEvent): class GraphRunSucceededEvent(BaseGraphEvent): - outputs: Optional[dict[str, Any]] = None + outputs: dict[str, object] = Field(default_factory=dict) class GraphRunFailedEvent(BaseGraphEvent): @@ -20,11 +18,11 @@ class GraphRunFailedEvent(BaseGraphEvent): class GraphRunPartialSucceededEvent(BaseGraphEvent): exceptions_count: int = Field(..., description="exception count") - outputs: Optional[dict[str, Any]] = None + outputs: dict[str, object] = Field(default_factory=dict) class GraphRunAbortedEvent(BaseGraphEvent): """Event emitted when a graph run is aborted by user command.""" - reason: Optional[str] = Field(default=None, description="reason for abort") - outputs: Optional[dict[str, Any]] = Field(default=None, description="partial outputs if any") + reason: str | None = Field(default=None, description="reason for abort") + outputs: dict[str, object] = Field(default_factory=dict, description="partial outputs if any") diff --git a/api/core/workflow/graph_events/iteration.py b/api/core/workflow/graph_events/iteration.py index 908a531d91..28627395fd 100644 --- a/api/core/workflow/graph_events/iteration.py +++ b/api/core/workflow/graph_events/iteration.py @@ -1,6 +1,6 @@ from collections.abc import Mapping from datetime import datetime -from typing import Any, Optional +from typing import Any from pydantic import Field @@ -10,31 +10,31 @@ from .base import GraphNodeEventBase class NodeRunIterationStartedEvent(GraphNodeEventBase): node_title: str start_at: datetime = Field(..., description="start at") - inputs: Optional[Mapping[str, Any]] = None - metadata: Optional[Mapping[str, Any]] = None - predecessor_node_id: Optional[str] = None + inputs: Mapping[str, object] = Field(default_factory=dict) + metadata: Mapping[str, object] = Field(default_factory=dict) + predecessor_node_id: str | None = None class NodeRunIterationNextEvent(GraphNodeEventBase): node_title: str index: int = Field(..., description="index") - pre_iteration_output: Optional[Any] = None + pre_iteration_output: Any = None class NodeRunIterationSucceededEvent(GraphNodeEventBase): node_title: str start_at: datetime = Field(..., description="start at") - inputs: Optional[Mapping[str, Any]] = None - outputs: Optional[Mapping[str, Any]] = None - metadata: Optional[Mapping[str, Any]] = None + inputs: Mapping[str, object] = Field(default_factory=dict) + outputs: Mapping[str, object] = Field(default_factory=dict) + metadata: Mapping[str, object] = Field(default_factory=dict) steps: int = 0 class NodeRunIterationFailedEvent(GraphNodeEventBase): node_title: str start_at: datetime = Field(..., description="start at") - inputs: Optional[Mapping[str, Any]] = None - outputs: Optional[Mapping[str, Any]] = None - metadata: Optional[Mapping[str, Any]] = None + inputs: Mapping[str, object] = Field(default_factory=dict) + outputs: Mapping[str, object] = Field(default_factory=dict) + metadata: Mapping[str, object] = Field(default_factory=dict) steps: int = 0 error: str = Field(..., description="failed reason") diff --git a/api/core/workflow/graph_events/loop.py b/api/core/workflow/graph_events/loop.py index 9982d876ba..7cdc5427e2 100644 --- a/api/core/workflow/graph_events/loop.py +++ b/api/core/workflow/graph_events/loop.py @@ -1,6 +1,6 @@ from collections.abc import Mapping from datetime import datetime -from typing import Any, Optional +from typing import Any from pydantic import Field @@ -10,31 +10,31 @@ from .base import GraphNodeEventBase class NodeRunLoopStartedEvent(GraphNodeEventBase): node_title: str start_at: datetime = Field(..., description="start at") - inputs: Optional[Mapping[str, Any]] = None - metadata: Optional[Mapping[str, Any]] = None - predecessor_node_id: Optional[str] = None + inputs: Mapping[str, object] = Field(default_factory=dict) + metadata: Mapping[str, object] = Field(default_factory=dict) + predecessor_node_id: str | None = None class NodeRunLoopNextEvent(GraphNodeEventBase): node_title: str index: int = Field(..., description="index") - pre_loop_output: Optional[Any] = None + pre_loop_output: Any = None class NodeRunLoopSucceededEvent(GraphNodeEventBase): node_title: str start_at: datetime = Field(..., description="start at") - inputs: Optional[Mapping[str, Any]] = None - outputs: Optional[Mapping[str, Any]] = None - metadata: Optional[Mapping[str, Any]] = None + inputs: Mapping[str, object] = Field(default_factory=dict) + outputs: Mapping[str, object] = Field(default_factory=dict) + metadata: Mapping[str, object] = Field(default_factory=dict) steps: int = 0 class NodeRunLoopFailedEvent(GraphNodeEventBase): node_title: str start_at: datetime = Field(..., description="start at") - inputs: Optional[Mapping[str, Any]] = None - outputs: Optional[Mapping[str, Any]] = None - metadata: Optional[Mapping[str, Any]] = None + inputs: Mapping[str, object] = Field(default_factory=dict) + outputs: Mapping[str, object] = Field(default_factory=dict) + metadata: Mapping[str, object] = Field(default_factory=dict) steps: int = 0 error: str = Field(..., description="failed reason") diff --git a/api/core/workflow/graph_events/node.py b/api/core/workflow/graph_events/node.py index 1f6656535e..1d35a69c4a 100644 --- a/api/core/workflow/graph_events/node.py +++ b/api/core/workflow/graph_events/node.py @@ -1,6 +1,5 @@ from collections.abc import Sequence from datetime import datetime -from typing import Optional from pydantic import Field @@ -12,9 +11,8 @@ from .base import GraphNodeEventBase class NodeRunStartedEvent(GraphNodeEventBase): node_title: str - predecessor_node_id: Optional[str] = None - parallel_mode_run_id: Optional[str] = None - agent_strategy: Optional[AgentNodeStrategyInit] = None + predecessor_node_id: str | None = None + agent_strategy: AgentNodeStrategyInit | None = None start_at: datetime = Field(..., description="node start time") # FIXME(-LAN-): only for ToolNode diff --git a/api/core/workflow/node_events/agent.py b/api/core/workflow/node_events/agent.py index b89e4fe54e..bf295ec774 100644 --- a/api/core/workflow/node_events/agent.py +++ b/api/core/workflow/node_events/agent.py @@ -1,5 +1,5 @@ from collections.abc import Mapping -from typing import Any, Optional +from typing import Any from pydantic import Field @@ -14,5 +14,5 @@ class AgentLogEvent(NodeEventBase): error: str | None = Field(..., description="error") status: str = Field(..., description="status") data: Mapping[str, Any] = Field(..., description="data") - metadata: Optional[Mapping[str, Any]] = Field(default=None, description="metadata") + metadata: Mapping[str, Any] = Field(default_factory=dict, description="metadata") node_id: str = Field(..., description="node id") diff --git a/api/core/workflow/node_events/iteration.py b/api/core/workflow/node_events/iteration.py index 36c74ac9f1..744ddea628 100644 --- a/api/core/workflow/node_events/iteration.py +++ b/api/core/workflow/node_events/iteration.py @@ -1,6 +1,6 @@ from collections.abc import Mapping from datetime import datetime -from typing import Any, Optional +from typing import Any from pydantic import Field @@ -9,28 +9,28 @@ from .base import NodeEventBase class IterationStartedEvent(NodeEventBase): start_at: datetime = Field(..., description="start at") - inputs: Optional[Mapping[str, Any]] = None - metadata: Optional[Mapping[str, Any]] = None - predecessor_node_id: Optional[str] = None + inputs: Mapping[str, object] = Field(default_factory=dict) + metadata: Mapping[str, object] = Field(default_factory=dict) + predecessor_node_id: str | None = None class IterationNextEvent(NodeEventBase): index: int = Field(..., description="index") - pre_iteration_output: Optional[Any] = None + pre_iteration_output: Any = None class IterationSucceededEvent(NodeEventBase): start_at: datetime = Field(..., description="start at") - inputs: Optional[Mapping[str, Any]] = None - outputs: Optional[Mapping[str, Any]] = None - metadata: Optional[Mapping[str, Any]] = None + inputs: Mapping[str, object] = Field(default_factory=dict) + outputs: Mapping[str, object] = Field(default_factory=dict) + metadata: Mapping[str, object] = Field(default_factory=dict) steps: int = 0 class IterationFailedEvent(NodeEventBase): start_at: datetime = Field(..., description="start at") - inputs: Optional[Mapping[str, Any]] = None - outputs: Optional[Mapping[str, Any]] = None - metadata: Optional[Mapping[str, Any]] = None + inputs: Mapping[str, object] = Field(default_factory=dict) + outputs: Mapping[str, object] = Field(default_factory=dict) + metadata: Mapping[str, object] = Field(default_factory=dict) steps: int = 0 error: str = Field(..., description="failed reason") diff --git a/api/core/workflow/node_events/loop.py b/api/core/workflow/node_events/loop.py index 5115fa9d3d..3ae230f9f6 100644 --- a/api/core/workflow/node_events/loop.py +++ b/api/core/workflow/node_events/loop.py @@ -1,6 +1,6 @@ from collections.abc import Mapping from datetime import datetime -from typing import Any, Optional +from typing import Any from pydantic import Field @@ -9,28 +9,28 @@ from .base import NodeEventBase class LoopStartedEvent(NodeEventBase): start_at: datetime = Field(..., description="start at") - inputs: Optional[Mapping[str, Any]] = None - metadata: Optional[Mapping[str, Any]] = None - predecessor_node_id: Optional[str] = None + inputs: Mapping[str, object] = Field(default_factory=dict) + metadata: Mapping[str, object] = Field(default_factory=dict) + predecessor_node_id: str | None = None class LoopNextEvent(NodeEventBase): index: int = Field(..., description="index") - pre_loop_output: Optional[Any] = None + pre_loop_output: Any = None class LoopSucceededEvent(NodeEventBase): start_at: datetime = Field(..., description="start at") - inputs: Optional[Mapping[str, Any]] = None - outputs: Optional[Mapping[str, Any]] = None - metadata: Optional[Mapping[str, Any]] = None + inputs: Mapping[str, object] = Field(default_factory=dict) + outputs: Mapping[str, object] = Field(default_factory=dict) + metadata: Mapping[str, object] = Field(default_factory=dict) steps: int = 0 class LoopFailedEvent(NodeEventBase): start_at: datetime = Field(..., description="start at") - inputs: Optional[Mapping[str, Any]] = None - outputs: Optional[Mapping[str, Any]] = None - metadata: Optional[Mapping[str, Any]] = None + inputs: Mapping[str, object] = Field(default_factory=dict) + outputs: Mapping[str, object] = Field(default_factory=dict) + metadata: Mapping[str, object] = Field(default_factory=dict) steps: int = 0 error: str = Field(..., description="failed reason") diff --git a/api/core/workflow/nodes/agent/agent_node.py b/api/core/workflow/nodes/agent/agent_node.py index 4662cec2e9..ec05805879 100644 --- a/api/core/workflow/nodes/agent/agent_node.py +++ b/api/core/workflow/nodes/agent/agent_node.py @@ -33,7 +33,13 @@ from core.workflow.enums import ( WorkflowNodeExecutionMetadataKey, WorkflowNodeExecutionStatus, ) -from core.workflow.node_events import AgentLogEvent, NodeRunResult, StreamChunkEvent, StreamCompletedEvent +from core.workflow.node_events import ( + AgentLogEvent, + NodeEventBase, + NodeRunResult, + StreamChunkEvent, + StreamCompletedEvent, +) from core.workflow.nodes.agent.entities import AgentNodeData, AgentOldVersionModelFeatures, ParamsAutoGenerated from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig from core.workflow.nodes.base.node import Node @@ -93,7 +99,7 @@ class AgentNode(Node): def version(cls) -> str: return "1" - def _run(self) -> Generator: + def _run(self) -> Generator[NodeEventBase, None, None]: from core.plugin.impl.exc import PluginDaemonClientSideError try: @@ -482,7 +488,7 @@ class AgentNode(Node): node_type: NodeType, node_id: str, node_execution_id: str, - ) -> Generator: + ) -> Generator[NodeEventBase, None, None]: """ Convert ToolInvokeMessages into tuple[plain_text, files] """ diff --git a/api/core/workflow/nodes/base/node.py b/api/core/workflow/nodes/base/node.py index 438d768104..41212abb0e 100644 --- a/api/core/workflow/nodes/base/node.py +++ b/api/core/workflow/nodes/base/node.py @@ -1,12 +1,13 @@ import logging from abc import abstractmethod -from collections.abc import Callable, Generator, Mapping, Sequence -from typing import TYPE_CHECKING, Any, ClassVar, Optional +from collections.abc import Generator, Mapping, Sequence +from functools import singledispatchmethod +from typing import Any, ClassVar from uuid import uuid4 from core.app.entities.app_invoke_entities import InvokeFrom -from core.workflow.entities import AgentNodeStrategyInit -from core.workflow.enums import NodeExecutionType, NodeState, NodeType, WorkflowNodeExecutionStatus +from core.workflow.entities import AgentNodeStrategyInit, GraphInitParams, GraphRuntimeState +from core.workflow.enums import ErrorStrategy, NodeExecutionType, NodeState, NodeType, WorkflowNodeExecutionStatus from core.workflow.graph_events import ( GraphNodeEventBase, NodeRunAgentLogEvent, @@ -45,11 +46,6 @@ from models.enums import UserFrom from .entities import BaseNodeData, RetryConfig -if TYPE_CHECKING: - from core.workflow.entities import GraphInitParams, GraphRuntimeState - from core.workflow.enums import ErrorStrategy, NodeType - from core.workflow.node_events import NodeRunResult - logger = logging.getLogger(__name__) @@ -88,14 +84,14 @@ class Node: def init_node_data(self, data: Mapping[str, Any]) -> None: ... @abstractmethod - def _run(self) -> "NodeRunResult | Generator[GraphNodeEventBase, None, None]": + def _run(self) -> NodeRunResult | Generator[NodeEventBase, None, None]: """ Run node :return: """ raise NotImplementedError - def run(self) -> "Generator[GraphNodeEventBase, None, None]": + def run(self) -> Generator[GraphNodeEventBase, None, None]: # Generate a single node execution ID to use for all events if not self._node_execution_id: self._node_execution_id = str(uuid4()) @@ -151,12 +147,14 @@ class Node: # Handle event stream for event in result: - if isinstance(event, NodeEventBase): - event = self._convert_node_event_to_graph_node_event(event) - - if not event.in_iteration_id and not event.in_loop_id: + # NOTE: this is necessary because iteration and loop nodes yield GraphNodeEventBase + if isinstance(event, NodeEventBase): # pyright: ignore[reportUnnecessaryIsInstance] + yield self._dispatch(event) + elif isinstance(event, GraphNodeEventBase) and not event.in_iteration_id and not event.in_loop_id: # pyright: ignore[reportUnnecessaryIsInstance] event.id = self._node_execution_id - yield event + yield event + else: + yield event except Exception as e: logger.exception("Node %s failed to run", self._node_id) result = NodeRunResult( @@ -249,7 +247,7 @@ class Node: return False @classmethod - def get_default_config(cls, filters: Optional[dict] = None) -> dict: + def get_default_config(cls, filters: Mapping[str, object] | None = None) -> Mapping[str, object]: return {} @classmethod @@ -270,7 +268,7 @@ class Node: # to BaseNodeData properties in a type-safe way @abstractmethod - def _get_error_strategy(self) -> Optional["ErrorStrategy"]: + def _get_error_strategy(self) -> ErrorStrategy | None: """Get the error strategy for this node.""" ... @@ -301,7 +299,7 @@ class Node: # Public interface properties that delegate to abstract methods @property - def error_strategy(self) -> Optional["ErrorStrategy"]: + def error_strategy(self) -> ErrorStrategy | None: """Get the error strategy for this node.""" return self._get_error_strategy() @@ -344,29 +342,15 @@ class Node: start_at=self._start_at, node_run_result=result, ) - raise Exception(f"result status {result.status} not supported") + case _: + raise Exception(f"result status {result.status} not supported") - def _convert_node_event_to_graph_node_event(self, event: NodeEventBase) -> GraphNodeEventBase: - handler_maps: dict[type[NodeEventBase], Callable[[Any], GraphNodeEventBase]] = { - StreamChunkEvent: self._handle_stream_chunk_event, - StreamCompletedEvent: self._handle_stream_completed_event, - AgentLogEvent: self._handle_agent_log_event, - LoopStartedEvent: self._handle_loop_started_event, - LoopNextEvent: self._handle_loop_next_event, - LoopSucceededEvent: self._handle_loop_succeeded_event, - LoopFailedEvent: self._handle_loop_failed_event, - IterationStartedEvent: self._handle_iteration_started_event, - IterationNextEvent: self._handle_iteration_next_event, - IterationSucceededEvent: self._handle_iteration_succeeded_event, - IterationFailedEvent: self._handle_iteration_failed_event, - RunRetrieverResourceEvent: self._handle_run_retriever_resource_event, - } - handler = handler_maps.get(type(event)) - if not handler: - raise NotImplementedError(f"Node {self._node_id} does not support event type {type(event)}") - return handler(event) + @singledispatchmethod + def _dispatch(self, event: NodeEventBase) -> GraphNodeEventBase: + raise NotImplementedError(f"Node {self._node_id} does not support event type {type(event)}") - def _handle_stream_chunk_event(self, event: StreamChunkEvent) -> NodeRunStreamChunkEvent: + @_dispatch.register + def _(self, event: StreamChunkEvent) -> NodeRunStreamChunkEvent: return NodeRunStreamChunkEvent( id=self._node_execution_id, node_id=self._node_id, @@ -376,7 +360,8 @@ class Node: is_final=event.is_final, ) - def _handle_stream_completed_event(self, event: StreamCompletedEvent) -> NodeRunSucceededEvent | NodeRunFailedEvent: + @_dispatch.register + def _(self, event: StreamCompletedEvent) -> NodeRunSucceededEvent | NodeRunFailedEvent: match event.node_run_result.status: case WorkflowNodeExecutionStatus.SUCCEEDED: return NodeRunSucceededEvent( @@ -395,9 +380,13 @@ class Node: node_run_result=event.node_run_result, error=event.node_run_result.error, ) - raise NotImplementedError(f"Node {self._node_id} does not support status {event.node_run_result.status}") + case _: + raise NotImplementedError( + f"Node {self._node_id} does not support status {event.node_run_result.status}" + ) - def _handle_agent_log_event(self, event: AgentLogEvent) -> NodeRunAgentLogEvent: + @_dispatch.register + def _(self, event: AgentLogEvent) -> NodeRunAgentLogEvent: return NodeRunAgentLogEvent( id=self._node_execution_id, node_id=self._node_id, @@ -412,7 +401,8 @@ class Node: metadata=event.metadata, ) - def _handle_loop_started_event(self, event: LoopStartedEvent) -> NodeRunLoopStartedEvent: + @_dispatch.register + def _(self, event: LoopStartedEvent) -> NodeRunLoopStartedEvent: return NodeRunLoopStartedEvent( id=self._node_execution_id, node_id=self._node_id, @@ -424,7 +414,8 @@ class Node: predecessor_node_id=event.predecessor_node_id, ) - def _handle_loop_next_event(self, event: LoopNextEvent) -> NodeRunLoopNextEvent: + @_dispatch.register + def _(self, event: LoopNextEvent) -> NodeRunLoopNextEvent: return NodeRunLoopNextEvent( id=self._node_execution_id, node_id=self._node_id, @@ -434,7 +425,8 @@ class Node: pre_loop_output=event.pre_loop_output, ) - def _handle_loop_succeeded_event(self, event: LoopSucceededEvent) -> NodeRunLoopSucceededEvent: + @_dispatch.register + def _(self, event: LoopSucceededEvent) -> NodeRunLoopSucceededEvent: return NodeRunLoopSucceededEvent( id=self._node_execution_id, node_id=self._node_id, @@ -447,7 +439,8 @@ class Node: steps=event.steps, ) - def _handle_loop_failed_event(self, event: LoopFailedEvent) -> NodeRunLoopFailedEvent: + @_dispatch.register + def _(self, event: LoopFailedEvent) -> NodeRunLoopFailedEvent: return NodeRunLoopFailedEvent( id=self._node_execution_id, node_id=self._node_id, @@ -461,7 +454,8 @@ class Node: error=event.error, ) - def _handle_iteration_started_event(self, event: IterationStartedEvent) -> NodeRunIterationStartedEvent: + @_dispatch.register + def _(self, event: IterationStartedEvent) -> NodeRunIterationStartedEvent: return NodeRunIterationStartedEvent( id=self._node_execution_id, node_id=self._node_id, @@ -473,7 +467,8 @@ class Node: predecessor_node_id=event.predecessor_node_id, ) - def _handle_iteration_next_event(self, event: IterationNextEvent) -> NodeRunIterationNextEvent: + @_dispatch.register + def _(self, event: IterationNextEvent) -> NodeRunIterationNextEvent: return NodeRunIterationNextEvent( id=self._node_execution_id, node_id=self._node_id, @@ -483,7 +478,8 @@ class Node: pre_iteration_output=event.pre_iteration_output, ) - def _handle_iteration_succeeded_event(self, event: IterationSucceededEvent) -> NodeRunIterationSucceededEvent: + @_dispatch.register + def _(self, event: IterationSucceededEvent) -> NodeRunIterationSucceededEvent: return NodeRunIterationSucceededEvent( id=self._node_execution_id, node_id=self._node_id, @@ -496,7 +492,8 @@ class Node: steps=event.steps, ) - def _handle_iteration_failed_event(self, event: IterationFailedEvent) -> NodeRunIterationFailedEvent: + @_dispatch.register + def _(self, event: IterationFailedEvent) -> NodeRunIterationFailedEvent: return NodeRunIterationFailedEvent( id=self._node_execution_id, node_id=self._node_id, @@ -510,7 +507,8 @@ class Node: error=event.error, ) - def _handle_run_retriever_resource_event(self, event: RunRetrieverResourceEvent) -> NodeRunRetrieverResourceEvent: + @_dispatch.register + def _(self, event: RunRetrieverResourceEvent) -> NodeRunRetrieverResourceEvent: return NodeRunRetrieverResourceEvent( id=self._node_execution_id, node_id=self._node_id, diff --git a/api/core/workflow/nodes/code/code_node.py b/api/core/workflow/nodes/code/code_node.py index 4fa97e0478..c87cbf9628 100644 --- a/api/core/workflow/nodes/code/code_node.py +++ b/api/core/workflow/nodes/code/code_node.py @@ -1,6 +1,6 @@ from collections.abc import Mapping, Sequence from decimal import Decimal -from typing import Any +from typing import Any, cast from configs import dify_config from core.helper.code_executor.code_executor import CodeExecutionError, CodeExecutor, CodeLanguage @@ -49,7 +49,7 @@ class CodeNode(Node): return self._node_data @classmethod - def get_default_config(cls, filters: dict | None = None): + def get_default_config(cls, filters: Mapping[str, object] | None = None) -> Mapping[str, object]: """ Get default config of node. :param filters: filter by node config parameters. @@ -57,7 +57,7 @@ class CodeNode(Node): """ code_language = CodeLanguage.PYTHON3 if filters: - code_language = filters.get("code_language", CodeLanguage.PYTHON3) + code_language = cast(CodeLanguage, filters.get("code_language", CodeLanguage.PYTHON3)) providers: list[type[CodeNodeProvider]] = [Python3CodeProvider, JavascriptCodeProvider] code_provider: type[CodeNodeProvider] = next(p for p in providers if p.is_accept_language(code_language)) diff --git a/api/core/workflow/nodes/code/entities.py b/api/core/workflow/nodes/code/entities.py index 8026011196..10a1c897e9 100644 --- a/api/core/workflow/nodes/code/entities.py +++ b/api/core/workflow/nodes/code/entities.py @@ -1,4 +1,4 @@ -from typing import Annotated, Literal +from typing import Annotated, Literal, Self from pydantic import AfterValidator, BaseModel @@ -34,7 +34,7 @@ class CodeNodeData(BaseNodeData): class Output(BaseModel): type: Annotated[SegmentType, AfterValidator(_validate_type)] - children: dict[str, "CodeNodeData.Output"] | None = None + children: dict[str, Self] | None = None class Dependency(BaseModel): name: str diff --git a/api/core/workflow/nodes/http_request/node.py b/api/core/workflow/nodes/http_request/node.py index 6226d8d362..826820a8e3 100644 --- a/api/core/workflow/nodes/http_request/node.py +++ b/api/core/workflow/nodes/http_request/node.py @@ -58,7 +58,7 @@ class HttpRequestNode(Node): return self._node_data @classmethod - def get_default_config(cls, filters: dict[str, Any] | None = None): + def get_default_config(cls, filters: Mapping[str, object] | None = None) -> Mapping[str, object]: return { "type": "http-request", "config": { diff --git a/api/core/workflow/nodes/iteration/entities.py b/api/core/workflow/nodes/iteration/entities.py index 9608edb06e..ed4ab2c11c 100644 --- a/api/core/workflow/nodes/iteration/entities.py +++ b/api/core/workflow/nodes/iteration/entities.py @@ -39,7 +39,7 @@ class IterationState(BaseIterationState): """ outputs: list[Any] = Field(default_factory=list) - current_output: Any | None = None + current_output: Any = None class MetaData(BaseIterationState.MetaData): """ @@ -48,7 +48,7 @@ class IterationState(BaseIterationState): iterator_length: int - def get_last_output(self) -> Any | None: + def get_last_output(self) -> Any: """ Get last output. """ @@ -56,7 +56,7 @@ class IterationState(BaseIterationState): return self.outputs[-1] return None - def get_current_output(self) -> Any | None: + def get_current_output(self) -> Any: """ Get current output. """ diff --git a/api/core/workflow/nodes/iteration/iteration_node.py b/api/core/workflow/nodes/iteration/iteration_node.py index 274e829ea5..5340a5b6ce 100644 --- a/api/core/workflow/nodes/iteration/iteration_node.py +++ b/api/core/workflow/nodes/iteration/iteration_node.py @@ -1,7 +1,10 @@ import logging from collections.abc import Generator, Mapping, Sequence +from concurrent.futures import Future, ThreadPoolExecutor, as_completed from datetime import UTC, datetime -from typing import TYPE_CHECKING, Any, Union, cast +from typing import TYPE_CHECKING, Any, NewType, cast + +from typing_extensions import TypeIs from core.variables import IntegerVariable, NoneSegment from core.variables.segments import ArrayAnySegment, ArraySegment @@ -23,6 +26,7 @@ from core.workflow.node_events import ( IterationNextEvent, IterationStartedEvent, IterationSucceededEvent, + NodeEventBase, NodeRunResult, StreamCompletedEvent, ) @@ -45,6 +49,8 @@ if TYPE_CHECKING: logger = logging.getLogger(__name__) +EmptyArraySegment = NewType("EmptyArraySegment", ArraySegment) + class IterationNode(Node): """ @@ -77,7 +83,7 @@ class IterationNode(Node): return self._node_data @classmethod - def get_default_config(cls, filters: dict | None = None): + def get_default_config(cls, filters: Mapping[str, object] | None = None) -> Mapping[str, object]: return { "type": "iteration", "config": { @@ -91,44 +97,21 @@ class IterationNode(Node): def version(cls) -> str: return "1" - def _run(self) -> Generator: - variable = self.graph_runtime_state.variable_pool.get(self._node_data.iterator_selector) + def _run(self) -> Generator[GraphNodeEventBase | NodeEventBase, None, None]: # type: ignore + variable = self._get_iterator_variable() - if not variable: - raise IteratorVariableNotFoundError(f"iterator variable {self._node_data.iterator_selector} not found") - - if not isinstance(variable, ArraySegment) and not isinstance(variable, NoneSegment): - raise InvalidIteratorValueError(f"invalid iterator value: {variable}, please provide a list.") - - if isinstance(variable, NoneSegment) or len(variable.value) == 0: - # Try our best to preserve the type informat. - if isinstance(variable, ArraySegment): - output = variable.model_copy(update={"value": []}) - else: - output = ArrayAnySegment(value=[]) - yield StreamCompletedEvent( - node_run_result=NodeRunResult( - status=WorkflowNodeExecutionStatus.SUCCEEDED, - # TODO(QuantumGhost): is it possible to compute the type of `output` - # from graph definition? - outputs={"output": output}, - ) - ) + if self._is_empty_iteration(variable): + yield from self._handle_empty_iteration(variable) return - iterator_list_value = variable.to_object() - - if not isinstance(iterator_list_value, list): - raise InvalidIteratorValueError(f"Invalid iterator value: {iterator_list_value}, please provide a list.") - + iterator_list_value = self._validate_and_get_iterator_list(variable) inputs = {"iterator_selector": iterator_list_value} - if not self._node_data.start_node_id: - raise StartNodeIdNotFoundError(f"field start_node_id in iteration {self._node_id} not found") + self._validate_start_node() started_at = naive_utc_now() iter_run_map: dict[str, float] = {} - outputs: list[Any] = [] + outputs: list[object] = [] yield IterationStartedEvent( start_at=started_at, @@ -137,6 +120,86 @@ class IterationNode(Node): ) try: + yield from self._execute_iterations( + iterator_list_value=iterator_list_value, + outputs=outputs, + iter_run_map=iter_run_map, + ) + + yield from self._handle_iteration_success( + started_at=started_at, + inputs=inputs, + outputs=outputs, + iterator_list_value=iterator_list_value, + iter_run_map=iter_run_map, + ) + except IterationNodeError as e: + yield from self._handle_iteration_failure( + started_at=started_at, + inputs=inputs, + outputs=outputs, + iterator_list_value=iterator_list_value, + iter_run_map=iter_run_map, + error=e, + ) + + def _get_iterator_variable(self) -> ArraySegment | NoneSegment: + variable = self.graph_runtime_state.variable_pool.get(self._node_data.iterator_selector) + + if not variable: + raise IteratorVariableNotFoundError(f"iterator variable {self._node_data.iterator_selector} not found") + + if not isinstance(variable, ArraySegment) and not isinstance(variable, NoneSegment): + raise InvalidIteratorValueError(f"invalid iterator value: {variable}, please provide a list.") + + return variable + + def _is_empty_iteration(self, variable: ArraySegment | NoneSegment) -> TypeIs[NoneSegment | EmptyArraySegment]: + return isinstance(variable, NoneSegment) or len(variable.value) == 0 + + def _handle_empty_iteration(self, variable: ArraySegment | NoneSegment) -> Generator[NodeEventBase, None, None]: + # Try our best to preserve the type information. + if isinstance(variable, ArraySegment): + output = variable.model_copy(update={"value": []}) + else: + output = ArrayAnySegment(value=[]) + + yield StreamCompletedEvent( + node_run_result=NodeRunResult( + status=WorkflowNodeExecutionStatus.SUCCEEDED, + # TODO(QuantumGhost): is it possible to compute the type of `output` + # from graph definition? + outputs={"output": output}, + ) + ) + + def _validate_and_get_iterator_list(self, variable: ArraySegment) -> Sequence[object]: + iterator_list_value = variable.to_object() + + if not isinstance(iterator_list_value, list): + raise InvalidIteratorValueError(f"Invalid iterator value: {iterator_list_value}, please provide a list.") + + return cast(list[object], iterator_list_value) + + def _validate_start_node(self) -> None: + if not self._node_data.start_node_id: + raise StartNodeIdNotFoundError(f"field start_node_id in iteration {self._node_id} not found") + + def _execute_iterations( + self, + iterator_list_value: Sequence[object], + outputs: list[object], + iter_run_map: dict[str, float], + ) -> Generator[GraphNodeEventBase | NodeEventBase, None, None]: + if self._node_data.is_parallel: + # Parallel mode execution + yield from self._execute_parallel_iterations( + iterator_list_value=iterator_list_value, + outputs=outputs, + iter_run_map=iter_run_map, + ) + else: + # Sequential mode execution for index, item in enumerate(iterator_list_value): iter_start_at = datetime.now(UTC).replace(tzinfo=None) yield IterationNextEvent(index=index) @@ -154,45 +217,146 @@ class IterationNode(Node): self.graph_runtime_state.total_tokens += graph_engine.graph_runtime_state.total_tokens iter_run_map[str(index)] = (datetime.now(UTC).replace(tzinfo=None) - iter_start_at).total_seconds() - yield IterationSucceededEvent( - start_at=started_at, - inputs=inputs, - outputs={"output": outputs}, - steps=len(iterator_list_value), - metadata={ - WorkflowNodeExecutionMetadataKey.TOTAL_TOKENS: self.graph_runtime_state.total_tokens, - WorkflowNodeExecutionMetadataKey.ITERATION_DURATION_MAP: iter_run_map, - }, - ) + def _execute_parallel_iterations( + self, + iterator_list_value: Sequence[object], + outputs: list[object], + iter_run_map: dict[str, float], + ) -> Generator[GraphNodeEventBase | NodeEventBase, None, None]: + # Initialize outputs list with None values to maintain order + outputs.extend([None] * len(iterator_list_value)) - # Yield final success event - yield StreamCompletedEvent( - node_run_result=NodeRunResult( - status=WorkflowNodeExecutionStatus.SUCCEEDED, - outputs={"output": outputs}, - metadata={ - WorkflowNodeExecutionMetadataKey.TOTAL_TOKENS: self.graph_runtime_state.total_tokens, - }, + # Determine the number of parallel workers + max_workers = min(self._node_data.parallel_nums, len(iterator_list_value)) + + with ThreadPoolExecutor(max_workers=max_workers) as executor: + # Submit all iteration tasks + future_to_index: dict[Future[tuple[datetime, list[GraphNodeEventBase], object | None, int]], int] = {} + for index, item in enumerate(iterator_list_value): + yield IterationNextEvent(index=index) + future = executor.submit( + self._execute_single_iteration_parallel, + index=index, + item=item, ) - ) - except IterationNodeError as e: - yield IterationFailedEvent( - start_at=started_at, - inputs=inputs, + future_to_index[future] = index + + # Process completed iterations as they finish + for future in as_completed(future_to_index): + index = future_to_index[future] + try: + result = future.result() + iter_start_at, events, output_value, tokens_used = result + + # Update outputs at the correct index + outputs[index] = output_value + + # Yield all events from this iteration + yield from events + + # Update tokens and timing + self.graph_runtime_state.total_tokens += tokens_used + iter_run_map[str(index)] = (datetime.now(UTC).replace(tzinfo=None) - iter_start_at).total_seconds() + + except Exception as e: + # Handle errors based on error_handle_mode + match self._node_data.error_handle_mode: + case ErrorHandleMode.TERMINATED: + # Cancel remaining futures and re-raise + for f in future_to_index: + if f != future: + f.cancel() + raise IterationNodeError(str(e)) + case ErrorHandleMode.CONTINUE_ON_ERROR: + outputs[index] = None + case ErrorHandleMode.REMOVE_ABNORMAL_OUTPUT: + outputs[index] = None # Will be filtered later + + # Remove None values if in REMOVE_ABNORMAL_OUTPUT mode + if self._node_data.error_handle_mode == ErrorHandleMode.REMOVE_ABNORMAL_OUTPUT: + outputs[:] = [output for output in outputs if output is not None] + + def _execute_single_iteration_parallel( + self, + index: int, + item: object, + ) -> tuple[datetime, list[GraphNodeEventBase], object | None, int]: + """Execute a single iteration in parallel mode and return results.""" + iter_start_at = datetime.now(UTC).replace(tzinfo=None) + events: list[GraphNodeEventBase] = [] + outputs_temp: list[object] = [] + + graph_engine = self._create_graph_engine(index, item) + + # Collect events instead of yielding them directly + for event in self._run_single_iter( + variable_pool=graph_engine.graph_runtime_state.variable_pool, + outputs=outputs_temp, + graph_engine=graph_engine, + ): + events.append(event) + + # Get the output value from the temporary outputs list + output_value = outputs_temp[0] if outputs_temp else None + + return iter_start_at, events, output_value, graph_engine.graph_runtime_state.total_tokens + + def _handle_iteration_success( + self, + started_at: datetime, + inputs: dict[str, Sequence[object]], + outputs: list[object], + iterator_list_value: Sequence[object], + iter_run_map: dict[str, float], + ) -> Generator[NodeEventBase, None, None]: + yield IterationSucceededEvent( + start_at=started_at, + inputs=inputs, + outputs={"output": outputs}, + steps=len(iterator_list_value), + metadata={ + WorkflowNodeExecutionMetadataKey.TOTAL_TOKENS: self.graph_runtime_state.total_tokens, + WorkflowNodeExecutionMetadataKey.ITERATION_DURATION_MAP: iter_run_map, + }, + ) + + # Yield final success event + yield StreamCompletedEvent( + node_run_result=NodeRunResult( + status=WorkflowNodeExecutionStatus.SUCCEEDED, outputs={"output": outputs}, - steps=len(iterator_list_value), metadata={ WorkflowNodeExecutionMetadataKey.TOTAL_TOKENS: self.graph_runtime_state.total_tokens, - WorkflowNodeExecutionMetadataKey.ITERATION_DURATION_MAP: iter_run_map, }, - error=str(e), ) - yield StreamCompletedEvent( - node_run_result=NodeRunResult( - status=WorkflowNodeExecutionStatus.FAILED, - error=str(e), - ) + ) + + def _handle_iteration_failure( + self, + started_at: datetime, + inputs: dict[str, Sequence[object]], + outputs: list[object], + iterator_list_value: Sequence[object], + iter_run_map: dict[str, float], + error: IterationNodeError, + ) -> Generator[NodeEventBase, None, None]: + yield IterationFailedEvent( + start_at=started_at, + inputs=inputs, + outputs={"output": outputs}, + steps=len(iterator_list_value), + metadata={ + WorkflowNodeExecutionMetadataKey.TOTAL_TOKENS: self.graph_runtime_state.total_tokens, + WorkflowNodeExecutionMetadataKey.ITERATION_DURATION_MAP: iter_run_map, + }, + error=str(error), + ) + yield StreamCompletedEvent( + node_run_result=NodeRunResult( + status=WorkflowNodeExecutionStatus.FAILED, + error=str(error), ) + ) @classmethod def _extract_variable_selector_to_variable_mapping( @@ -305,9 +469,9 @@ class IterationNode(Node): self, *, variable_pool: VariablePool, - outputs: list, + outputs: list[object], graph_engine: "GraphEngine", - ) -> Generator[Union[GraphNodeEventBase, StreamCompletedEvent], None, None]: + ) -> Generator[GraphNodeEventBase, None, None]: rst = graph_engine.run() # get current iteration index index_variable = variable_pool.get([self._node_id, "index"]) @@ -338,7 +502,7 @@ class IterationNode(Node): case ErrorHandleMode.REMOVE_ABNORMAL_OUTPUT: return - def _create_graph_engine(self, index: int, item: Any): + def _create_graph_engine(self, index: int, item: object): # Import dependencies from core.workflow.entities import GraphInitParams, GraphRuntimeState from core.workflow.graph import Graph @@ -387,18 +551,9 @@ class IterationNode(Node): # Create a new GraphEngine for this iteration graph_engine = GraphEngine( - tenant_id=self.tenant_id, - app_id=self.app_id, workflow_id=self.workflow_id, - user_id=self.user_id, - user_from=self.user_from, - invoke_from=self.invoke_from, - call_depth=self.workflow_call_depth, graph=iteration_graph, - graph_config=self.graph_config, graph_runtime_state=graph_runtime_state_copy, - max_execution_steps=10000, # Use default or config value - max_execution_time=600, # Use default or config value command_channel=InMemoryChannel(), # Use InMemoryChannel for sub-graphs ) diff --git a/api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py b/api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py index ee5c4ae289..1afb2e05b9 100644 --- a/api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py +++ b/api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py @@ -4,7 +4,7 @@ import re import time from collections import defaultdict from collections.abc import Mapping, Sequence -from typing import TYPE_CHECKING, Any, Optional, cast +from typing import TYPE_CHECKING, Any, cast from sqlalchemy import Float, and_, func, or_, select, text from sqlalchemy import cast as sqlalchemy_cast @@ -568,7 +568,7 @@ class KnowledgeRetrievalNode(Node): return automatic_metadata_filters def _process_metadata_filter_func( - self, sequence: int, condition: str, metadata_name: str, value: Optional[Any], filters: list[Any] + self, sequence: int, condition: str, metadata_name: str, value: Any, filters: list[Any] ) -> list[Any]: if value is None and condition not in ("empty", "not empty"): return filters diff --git a/api/core/workflow/nodes/llm/node.py b/api/core/workflow/nodes/llm/node.py index f0f27e1e2d..a0f4836e82 100644 --- a/api/core/workflow/nodes/llm/node.py +++ b/api/core/workflow/nodes/llm/node.py @@ -959,7 +959,7 @@ class LLMNode(Node): return variable_mapping @classmethod - def get_default_config(cls, filters: dict | None = None): + def get_default_config(cls, filters: Mapping[str, object] | None = None) -> Mapping[str, object]: return { "type": "llm", "config": { diff --git a/api/core/workflow/nodes/loop/entities.py b/api/core/workflow/nodes/loop/entities.py index 57434fa9f0..4fcad888e4 100644 --- a/api/core/workflow/nodes/loop/entities.py +++ b/api/core/workflow/nodes/loop/entities.py @@ -1,4 +1,4 @@ -from typing import Annotated, Any, Literal, Optional +from typing import Annotated, Any, Literal from pydantic import AfterValidator, BaseModel, Field, field_validator @@ -41,7 +41,7 @@ class LoopNodeData(BaseLoopNodeData): loop_count: int # Maximum number of loops break_conditions: list[Condition] # Conditions to break the loop logical_operator: Literal["and", "or"] - loop_variables: Optional[list[LoopVariableData]] = Field(default_factory=list[LoopVariableData]) + loop_variables: list[LoopVariableData] | None = Field(default_factory=list[LoopVariableData]) outputs: dict[str, Any] = Field(default_factory=dict) @field_validator("outputs", mode="before") @@ -74,7 +74,7 @@ class LoopState(BaseLoopState): """ outputs: list[Any] = Field(default_factory=list) - current_output: Any | None = None + current_output: Any = None class MetaData(BaseLoopState.MetaData): """ @@ -83,7 +83,7 @@ class LoopState(BaseLoopState): loop_length: int - def get_last_output(self) -> Any | None: + def get_last_output(self) -> Any: """ Get last output. """ @@ -91,7 +91,7 @@ class LoopState(BaseLoopState): return self.outputs[-1] return None - def get_current_output(self) -> Any | None: + def get_current_output(self) -> Any: """ Get current output. """ diff --git a/api/core/workflow/nodes/loop/loop_node.py b/api/core/workflow/nodes/loop/loop_node.py index 1b83319ab0..25b0c4f4fe 100644 --- a/api/core/workflow/nodes/loop/loop_node.py +++ b/api/core/workflow/nodes/loop/loop_node.py @@ -4,7 +4,6 @@ from collections.abc import Callable, Generator, Mapping, Sequence from datetime import datetime from typing import TYPE_CHECKING, Any, Literal, cast -from configs import dify_config from core.variables import Segment, SegmentType from core.workflow.enums import ( ErrorStrategy, @@ -444,18 +443,9 @@ class LoopNode(Node): # Create a new GraphEngine for this iteration graph_engine = GraphEngine( - tenant_id=self.tenant_id, - app_id=self.app_id, workflow_id=self.workflow_id, - user_id=self.user_id, - user_from=self.user_from, - invoke_from=self.invoke_from, - call_depth=self.workflow_call_depth, graph=loop_graph, - graph_config=self.graph_config, graph_runtime_state=graph_runtime_state_copy, - max_execution_steps=dify_config.WORKFLOW_MAX_EXECUTION_STEPS, - max_execution_time=dify_config.WORKFLOW_MAX_EXECUTION_TIME, command_channel=InMemoryChannel(), # Use InMemoryChannel for sub-graphs ) diff --git a/api/core/workflow/nodes/parameter_extractor/parameter_extractor_node.py b/api/core/workflow/nodes/parameter_extractor/parameter_extractor_node.py index 832422fcc3..875a0598e0 100644 --- a/api/core/workflow/nodes/parameter_extractor/parameter_extractor_node.py +++ b/api/core/workflow/nodes/parameter_extractor/parameter_extractor_node.py @@ -118,7 +118,7 @@ class ParameterExtractorNode(Node): _model_config: ModelConfigWithCredentialsEntity | None = None @classmethod - def get_default_config(cls, filters: dict | None = None): + def get_default_config(cls, filters: Mapping[str, object] | None = None) -> Mapping[str, object]: return { "model": { "prompt_templates": { diff --git a/api/core/workflow/nodes/question_classifier/question_classifier_node.py b/api/core/workflow/nodes/question_classifier/question_classifier_node.py index 945ce113f1..483cfff574 100644 --- a/api/core/workflow/nodes/question_classifier/question_classifier_node.py +++ b/api/core/workflow/nodes/question_classifier/question_classifier_node.py @@ -271,7 +271,7 @@ class QuestionClassifierNode(Node): return variable_mapping @classmethod - def get_default_config(cls, filters: dict | None = None): + def get_default_config(cls, filters: Mapping[str, object] | None = None) -> Mapping[str, object]: """ Get default config of node. :param filters: filter by node config parameters (not used in this implementation). diff --git a/api/core/workflow/nodes/template_transform/template_transform_node.py b/api/core/workflow/nodes/template_transform/template_transform_node.py index e00c838b1d..cf05ef253a 100644 --- a/api/core/workflow/nodes/template_transform/template_transform_node.py +++ b/api/core/workflow/nodes/template_transform/template_transform_node.py @@ -39,7 +39,7 @@ class TemplateTransformNode(Node): return self._node_data @classmethod - def get_default_config(cls, filters: dict | None = None): + def get_default_config(cls, filters: Mapping[str, object] | None = None) -> Mapping[str, object]: """ Get default config of node. :param filters: filter by node config parameters. diff --git a/api/core/workflow/nodes/tool/tool_node.py b/api/core/workflow/nodes/tool/tool_node.py index 2921b3b911..5f2abcd378 100644 --- a/api/core/workflow/nodes/tool/tool_node.py +++ b/api/core/workflow/nodes/tool/tool_node.py @@ -19,7 +19,7 @@ from core.workflow.enums import ( WorkflowNodeExecutionMetadataKey, WorkflowNodeExecutionStatus, ) -from core.workflow.node_events import NodeRunResult, StreamChunkEvent, StreamCompletedEvent +from core.workflow.node_events import NodeEventBase, NodeRunResult, StreamChunkEvent, StreamCompletedEvent from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig from core.workflow.nodes.base.node import Node from core.workflow.nodes.base.variable_template_parser import VariableTemplateParser @@ -55,7 +55,7 @@ class ToolNode(Node): def version(cls) -> str: return "1" - def _run(self) -> Generator: + def _run(self) -> Generator[NodeEventBase, None, None]: """ Run the tool node """ diff --git a/api/core/workflow/nodes/variable_assigner/v2/entities.py b/api/core/workflow/nodes/variable_assigner/v2/entities.py index bdb8716b8a..2955730289 100644 --- a/api/core/workflow/nodes/variable_assigner/v2/entities.py +++ b/api/core/workflow/nodes/variable_assigner/v2/entities.py @@ -18,7 +18,7 @@ class VariableOperationItem(BaseModel): # 2. For VARIABLE input_type: Initially contains the selector of the source variable. # 3. During the variable updating procedure: The `value` field is reassigned to hold # the resolved actual value that will be applied to the target variable. - value: Any | None = None + value: Any = None class VariableAssignerNodeData(BaseNodeData): diff --git a/api/core/workflow/workflow_entry.py b/api/core/workflow/workflow_entry.py index 83594bff8b..8fba5f91ff 100644 --- a/api/core/workflow/workflow_entry.py +++ b/api/core/workflow/workflow_entry.py @@ -2,7 +2,7 @@ import logging import time import uuid from collections.abc import Generator, Mapping, Sequence -from typing import Any, Optional +from typing import Any from configs import dify_config from core.app.apps.exc import GenerateTaskStoppedError @@ -43,7 +43,7 @@ class WorkflowEntry: call_depth: int, variable_pool: VariablePool, graph_runtime_state: GraphRuntimeState, - command_channel: Optional[CommandChannel] = None, + command_channel: CommandChannel | None = None, ) -> None: """ Init workflow entry @@ -73,18 +73,9 @@ class WorkflowEntry: self.command_channel = command_channel self.graph_engine = GraphEngine( - tenant_id=tenant_id, - app_id=app_id, workflow_id=workflow_id, - user_id=user_id, - user_from=user_from, - invoke_from=invoke_from, - call_depth=call_depth, graph=graph, - graph_config=graph_config, graph_runtime_state=graph_runtime_state, - max_execution_steps=dify_config.WORKFLOW_MAX_EXECUTION_STEPS, - max_execution_time=dify_config.WORKFLOW_MAX_EXECUTION_TIME, command_channel=command_channel, ) diff --git a/api/core/workflow/workflow_type_encoder.py b/api/core/workflow/workflow_type_encoder.py index 2aa6eeaf03..5456043ccd 100644 --- a/api/core/workflow/workflow_type_encoder.py +++ b/api/core/workflow/workflow_type_encoder.py @@ -16,7 +16,9 @@ class WorkflowRuntimeTypeConverter: def to_json_encodable(self, value: Mapping[str, Any] | None) -> Mapping[str, Any] | None: result = self._to_json_encodable_recursive(value) - return result if isinstance(result, Mapping) or result is None else dict(result) + if isinstance(result, Mapping) or result is None: + return result + return {} def _to_json_encodable_recursive(self, value: Any): if value is None: diff --git a/api/models/model.py b/api/models/model.py index 783bef6f88..4342095802 100644 --- a/api/models/model.py +++ b/api/models/model.py @@ -846,7 +846,7 @@ class Conversation(Base): ) @property - def app(self) -> Optional[App]: + def app(self) -> App | None: with Session(db.engine, expire_on_commit=False) as session: return session.query(App).where(App.id == self.app_id).first() @@ -1140,7 +1140,7 @@ class Message(Base): ) @property - def retriever_resources(self) -> Any | list[Any]: + def retriever_resources(self) -> Any: return self.message_metadata_dict.get("retriever_resources") if self.message_metadata else [] @property diff --git a/api/models/tools.py b/api/models/tools.py index dae3d6eb88..7211d7aa3a 100644 --- a/api/models/tools.py +++ b/api/models/tools.py @@ -1,4 +1,5 @@ import json +from collections.abc import Mapping from datetime import datetime from typing import TYPE_CHECKING, Any, cast from urllib.parse import urlparse @@ -314,11 +315,11 @@ class MCPToolProvider(Base): return [MCPTool(**tool) for tool in json.loads(self.tools)] @property - def provider_icon(self) -> dict[str, str] | str: + def provider_icon(self) -> Mapping[str, str] | str: from core.file import helpers as file_helpers try: - return cast(dict[str, str], json.loads(self.icon)) + return json.loads(self.icon) except json.JSONDecodeError: return file_helpers.get_signed_file_url(self.icon) diff --git a/api/pyrightconfig.json b/api/pyrightconfig.json index 7c59c2ca28..61ed3ac3b4 100644 --- a/api/pyrightconfig.json +++ b/api/pyrightconfig.json @@ -12,7 +12,7 @@ "core/ops", "core/tools", "core/model_runtime", - "core/workflow", + "core/workflow/nodes", "core/app/app_config/easy_ui_based_app/dataset" ], "typeCheckingMode": "strict", diff --git a/api/services/tools/tools_transform_service.py b/api/services/tools/tools_transform_service.py index 2325c707ff..bb04728f3a 100644 --- a/api/services/tools/tools_transform_service.py +++ b/api/services/tools/tools_transform_service.py @@ -1,6 +1,7 @@ import json import logging -from typing import Any, Union, cast +from collections.abc import Mapping +from typing import Any, Union from yarl import URL @@ -39,7 +40,9 @@ class ToolTransformService: return str(url_prefix % {"tenant_id": tenant_id, "filename": filename}) @classmethod - def get_tool_provider_icon_url(cls, provider_type: str, provider_name: str, icon: str | dict) -> Union[str, dict]: + def get_tool_provider_icon_url( + cls, provider_type: str, provider_name: str, icon: str | Mapping[str, str] + ) -> str | Mapping[str, str]: """ get tool provider icon url """ @@ -52,7 +55,7 @@ class ToolTransformService: elif provider_type in {ToolProviderType.API.value, ToolProviderType.WORKFLOW.value}: try: if isinstance(icon, str): - return cast(dict, json.loads(icon)) + return json.loads(icon) return icon except Exception: return {"background": "#252525", "content": "\ud83d\ude01"} @@ -119,7 +122,7 @@ class ToolTransformService: name=provider_controller.entity.identity.name, description=provider_controller.entity.identity.description, icon=provider_controller.entity.identity.icon, - icon_dark=provider_controller.entity.identity.icon_dark, + icon_dark=provider_controller.entity.identity.icon_dark or "", label=provider_controller.entity.identity.label, type=ToolProviderType.BUILT_IN, masked_credentials={}, @@ -141,9 +144,10 @@ class ToolTransformService: ) } + masked_creds = {} for name in schema: - if result.masked_credentials: - result.masked_credentials[name] = "" + masked_creds[name] = "" + result.masked_credentials = masked_creds # check if the provider need credentials if not provider_controller.need_credentials: @@ -221,7 +225,7 @@ class ToolTransformService: name=provider_controller.entity.identity.name, description=provider_controller.entity.identity.description, icon=provider_controller.entity.identity.icon, - icon_dark=provider_controller.entity.identity.icon_dark, + icon_dark=provider_controller.entity.identity.icon_dark or "", label=provider_controller.entity.identity.label, type=ToolProviderType.WORKFLOW, masked_credentials={}, @@ -334,7 +338,7 @@ class ToolTransformService: @staticmethod def convert_tool_entity_to_api_entity( - tool: Union[ApiToolBundle, WorkflowTool, Tool], + tool: ApiToolBundle | WorkflowTool | Tool, tenant_id: str, labels: list[str] | None = None, ) -> ToolApiEntity: @@ -388,7 +392,7 @@ class ToolTransformService: parameters=merged_parameters, labels=labels or [], ) - elif isinstance(tool, ApiToolBundle): + else: return ToolApiEntity( author=tool.author, name=tool.operation_id or "", @@ -397,9 +401,6 @@ class ToolTransformService: parameters=tool.parameters, labels=labels or [], ) - else: - # Handle WorkflowTool case - raise ValueError(f"Unsupported tool type: {type(tool)}") @staticmethod def convert_builtin_provider_to_credential_entity( diff --git a/api/services/workflow_service.py b/api/services/workflow_service.py index 9b5a2ea274..2eb54dade3 100644 --- a/api/services/workflow_service.py +++ b/api/services/workflow_service.py @@ -563,12 +563,12 @@ class WorkflowService: # This will prevent validation errors from breaking the workflow return [] - def get_default_block_configs(self) -> list[dict]: + def get_default_block_configs(self) -> Sequence[Mapping[str, object]]: """ Get default block configs """ # return default block config - default_block_configs = [] + default_block_configs: list[Mapping[str, object]] = [] for node_class_mapping in NODE_TYPE_CLASSES_MAPPING.values(): node_class = node_class_mapping[LATEST_VERSION] default_config = node_class.get_default_config() @@ -577,7 +577,9 @@ class WorkflowService: return default_block_configs - def get_default_block_config(self, node_type: str, filters: dict | None = None) -> dict | None: + def get_default_block_config( + self, node_type: str, filters: Mapping[str, object] | None = None + ) -> Mapping[str, object]: """ Get default config of node. :param node_type: node type @@ -588,12 +590,12 @@ class WorkflowService: # return default block config if node_type_enum not in NODE_TYPE_CLASSES_MAPPING: - return None + return {} node_class = NODE_TYPE_CLASSES_MAPPING[node_type_enum][LATEST_VERSION] default_config = node_class.get_default_config(filters=filters) if not default_config: - return None + return {} return default_config @@ -807,11 +809,13 @@ class WorkflowService: WorkflowNodeExecutionStatus.EXCEPTION, ) error = node_run_result.error if not run_succeeded else None - return node, node_run_result, run_succeeded, error - except WorkflowNodeRunFailedError as e: - return e._node, None, False, e._error + node = e.node + run_succeeded = False + node_run_result = None + error = e.error + return node, node_run_result, run_succeeded, error def _apply_error_strategy(self, node: Node, node_run_result: NodeRunResult) -> NodeRunResult: """Apply error strategy when node execution fails.""" diff --git a/api/tests/integration_tests/workflow/nodes/test_code.py b/api/tests/integration_tests/workflow/nodes/test_code.py index a8f3253b35..e2f3a74bf9 100644 --- a/api/tests/integration_tests/workflow/nodes/test_code.py +++ b/api/tests/integration_tests/workflow/nodes/test_code.py @@ -89,6 +89,7 @@ def test_execute_code(setup_code_executor_mock): code_config = { "id": "code", "data": { + "type": "code", "outputs": { "result": { "type": "number", @@ -135,6 +136,7 @@ def test_execute_code_output_validator(setup_code_executor_mock): code_config = { "id": "code", "data": { + "type": "code", "outputs": { "result": { "type": "string", @@ -180,6 +182,7 @@ def test_execute_code_output_validator_depth(): code_config = { "id": "code", "data": { + "type": "code", "outputs": { "string_validator": { "type": "string", @@ -298,6 +301,7 @@ def test_execute_code_output_object_list(): code_config = { "id": "code", "data": { + "type": "code", "outputs": { "object_list": { "type": "array[object]", @@ -358,7 +362,8 @@ def test_execute_code_output_object_list(): node._transform_result(result, node._node_data.outputs) -def test_execute_code_scientific_notation(): +@pytest.mark.parametrize("setup_code_executor_mock", [["none"]], indirect=True) +def test_execute_code_scientific_notation(setup_code_executor_mock): code = """ def main(): return { @@ -370,6 +375,7 @@ def test_execute_code_scientific_notation(): code_config = { "id": "code", "data": { + "type": "code", "outputs": { "result": { "type": "number", diff --git a/api/tests/integration_tests/workflow/nodes/test_http.py b/api/tests/integration_tests/workflow/nodes/test_http.py index 5e900342ce..ea99beacaa 100644 --- a/api/tests/integration_tests/workflow/nodes/test_http.py +++ b/api/tests/integration_tests/workflow/nodes/test_http.py @@ -77,6 +77,7 @@ def test_get(setup_http_mock): config={ "id": "1", "data": { + "type": "http-request", "title": "http", "desc": "", "method": "get", @@ -110,6 +111,7 @@ def test_no_auth(setup_http_mock): config={ "id": "1", "data": { + "type": "http-request", "title": "http", "desc": "", "method": "get", @@ -139,6 +141,7 @@ def test_custom_authorization_header(setup_http_mock): config={ "id": "1", "data": { + "type": "http-request", "title": "http", "desc": "", "method": "get", @@ -231,6 +234,7 @@ def test_bearer_authorization_with_custom_header_ignored(setup_http_mock): config={ "id": "1", "data": { + "type": "http-request", "title": "http", "desc": "", "method": "get", @@ -271,6 +275,7 @@ def test_basic_authorization_with_custom_header_ignored(setup_http_mock): config={ "id": "1", "data": { + "type": "http-request", "title": "http", "desc": "", "method": "get", @@ -310,6 +315,7 @@ def test_custom_authorization_with_empty_api_key(setup_http_mock): config={ "id": "1", "data": { + "type": "http-request", "title": "http", "desc": "", "method": "get", @@ -343,6 +349,7 @@ def test_template(setup_http_mock): config={ "id": "1", "data": { + "type": "http-request", "title": "http", "desc": "", "method": "get", @@ -378,6 +385,7 @@ def test_json(setup_http_mock): config={ "id": "1", "data": { + "type": "http-request", "title": "http", "desc": "", "method": "post", @@ -420,6 +428,7 @@ def test_x_www_form_urlencoded(setup_http_mock): config={ "id": "1", "data": { + "type": "http-request", "title": "http", "desc": "", "method": "post", @@ -467,6 +476,7 @@ def test_form_data(setup_http_mock): config={ "id": "1", "data": { + "type": "http-request", "title": "http", "desc": "", "method": "post", @@ -517,6 +527,7 @@ def test_none_data(setup_http_mock): config={ "id": "1", "data": { + "type": "http-request", "title": "http", "desc": "", "method": "post", @@ -550,6 +561,7 @@ def test_mock_404(setup_http_mock): config={ "id": "1", "data": { + "type": "http-request", "title": "http", "desc": "", "method": "get", @@ -579,6 +591,7 @@ def test_multi_colons_parse(setup_http_mock): config={ "id": "1", "data": { + "type": "http-request", "title": "http", "desc": "", "method": "get", @@ -635,6 +648,7 @@ def test_nested_object_variable_selector(setup_http_mock): { "id": "1", "data": { + "type": "http-request", "title": "http", "desc": "", "method": "get", diff --git a/api/tests/integration_tests/workflow/nodes/test_template_transform.py b/api/tests/integration_tests/workflow/nodes/test_template_transform.py index 02a8460ce6..53252c7f2e 100644 --- a/api/tests/integration_tests/workflow/nodes/test_template_transform.py +++ b/api/tests/integration_tests/workflow/nodes/test_template_transform.py @@ -20,6 +20,7 @@ def test_execute_code(setup_code_executor_mock): config = { "id": "1", "data": { + "type": "template-transform", "title": "123", "variables": [ { diff --git a/api/tests/integration_tests/workflow/nodes/test_tool.py b/api/tests/integration_tests/workflow/nodes/test_tool.py index 780fe0bee6..16d44d1eaf 100644 --- a/api/tests/integration_tests/workflow/nodes/test_tool.py +++ b/api/tests/integration_tests/workflow/nodes/test_tool.py @@ -70,6 +70,7 @@ def test_tool_variable_invoke(): config={ "id": "1", "data": { + "type": "tool", "title": "a", "desc": "a", "provider_id": "time", @@ -101,6 +102,7 @@ def test_tool_mixed_invoke(): config={ "id": "1", "data": { + "type": "tool", "title": "a", "desc": "a", "provider_id": "time", diff --git a/api/tests/test_containers_integration_tests/services/tools/test_tools_transform_service.py b/api/tests/test_containers_integration_tests/services/tools/test_tools_transform_service.py index bf25968100..827f9c010e 100644 --- a/api/tests/test_containers_integration_tests/services/tools/test_tools_transform_service.py +++ b/api/tests/test_containers_integration_tests/services/tools/test_tools_transform_service.py @@ -454,7 +454,7 @@ class TestToolTransformService: name=fake.company(), description=I18nObject(en_US=fake.text(max_nb_chars=100)), icon='{"background": "#FF6B6B", "content": "🔧"}', - icon_dark=None, + icon_dark="", label=I18nObject(en_US=fake.company()), type=ToolProviderType.API, masked_credentials={}, @@ -473,8 +473,8 @@ class TestToolTransformService: assert provider.icon["background"] == "#FF6B6B" assert provider.icon["content"] == "🔧" - # Verify dark icon remains None - assert provider.icon_dark is None + # Verify dark icon remains empty string + assert provider.icon_dark == "" def test_builtin_provider_to_user_provider_success( self, db_session_with_containers, mock_external_service_dependencies @@ -628,7 +628,7 @@ class TestToolTransformService: assert result is not None assert result.is_team_authorization is True assert result.allow_delete is False - assert result.masked_credentials == {} + assert result.masked_credentials == {"api_key": ""} def test_api_provider_to_controller_success(self, db_session_with_containers, mock_external_service_dependencies): """ diff --git a/api/tests/unit_tests/core/tools/workflow_as_tool/test_tool.py b/api/tests/unit_tests/core/tools/workflow_as_tool/test_tool.py index 5348f729f9..17e3ebeea0 100644 --- a/api/tests/unit_tests/core/tools/workflow_as_tool/test_tool.py +++ b/api/tests/unit_tests/core/tools/workflow_as_tool/test_tool.py @@ -17,7 +17,6 @@ def test_workflow_tool_should_raise_tool_invoke_error_when_result_has_error_fiel identity=ToolIdentity(author="test", name="test tool", label=I18nObject(en_US="test tool"), provider="test"), parameters=[], description=None, - output_schema=None, has_runtime_parameters=False, ) runtime = ToolRuntime(tenant_id="test_tool", invoke_from=InvokeFrom.EXPLORE) diff --git a/api/tests/unit_tests/core/workflow/entities/test_graph_runtime_state.py b/api/tests/unit_tests/core/workflow/entities/test_graph_runtime_state.py index 4d8483ce0d..2614424dc7 100644 --- a/api/tests/unit_tests/core/workflow/entities/test_graph_runtime_state.py +++ b/api/tests/unit_tests/core/workflow/entities/test_graph_runtime_state.py @@ -95,17 +95,3 @@ class TestGraphRuntimeState: # Test add_tokens validation with pytest.raises(ValueError): state.add_tokens(-1) - - def test_deep_copy_for_nested_objects(self): - variable_pool = VariablePool() - state = GraphRuntimeState(variable_pool=variable_pool, start_at=time()) - - # Test deep copy for nested dict - nested_data = {"level1": {"level2": {"value": "test"}}} - state.set_output("nested", nested_data) - - retrieved = state.get_output("nested") - retrieved["level1"]["level2"]["value"] = "modified" - - # Original should remain unchanged - assert state.get_output("nested")["level1"]["level2"]["value"] == "test" diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_command_system.py b/api/tests/unit_tests/core/workflow/graph_engine/test_command_system.py index 40b164a0c2..9fec855a93 100644 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_command_system.py +++ b/api/tests/unit_tests/core/workflow/graph_engine/test_command_system.py @@ -3,14 +3,12 @@ import time from unittest.mock import MagicMock -from core.app.entities.app_invoke_entities import InvokeFrom from core.workflow.entities import GraphRuntimeState, VariablePool from core.workflow.graph import Graph from core.workflow.graph_engine import GraphEngine from core.workflow.graph_engine.command_channels import InMemoryChannel from core.workflow.graph_engine.entities.commands import AbortCommand from core.workflow.graph_events import GraphRunAbortedEvent, GraphRunStartedEvent -from models.enums import UserFrom def test_abort_command(): @@ -42,18 +40,9 @@ def test_abort_command(): # Create GraphEngine with same shared runtime state engine = GraphEngine( - tenant_id="test", - app_id="test", workflow_id="test_workflow", - user_id="test", - user_from=UserFrom.ACCOUNT, - invoke_from=InvokeFrom.WEB_APP, - call_depth=0, graph=mock_graph, - graph_config={}, graph_runtime_state=shared_runtime_state, # Use shared instance - max_execution_steps=100, - max_execution_time=10, command_channel=command_channel, ) diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_conditional_streaming_vs_template_workflow.py b/api/tests/unit_tests/core/workflow/graph_engine/test_conditional_streaming_vs_template_workflow.py index 7ea789af51..70a772fc4c 100644 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_conditional_streaming_vs_template_workflow.py +++ b/api/tests/unit_tests/core/workflow/graph_engine/test_conditional_streaming_vs_template_workflow.py @@ -6,7 +6,6 @@ This test validates that: - When blocking != 1: NodeRunStreamChunkEvent present (direct LLM to End output) """ -from core.app.entities.app_invoke_entities import InvokeFrom from core.workflow.enums import NodeType from core.workflow.graph_engine import GraphEngine from core.workflow.graph_engine.command_channels import InMemoryChannel @@ -16,7 +15,6 @@ from core.workflow.graph_events import ( NodeRunStreamChunkEvent, NodeRunSucceededEvent, ) -from models.enums import UserFrom from .test_table_runner import TableTestRunner @@ -40,23 +38,11 @@ def test_streaming_output_with_blocking_equals_one(): use_mock_factory=True, ) - workflow_config = fixture_data.get("workflow", {}) - graph_config = workflow_config.get("graph", {}) - # Create and run the engine engine = GraphEngine( - tenant_id="test_tenant", - app_id="test_app", workflow_id="test_workflow", - user_id="test_user", - user_from=UserFrom.ACCOUNT, - invoke_from=InvokeFrom.DEBUGGER, - call_depth=0, graph=graph, - graph_config=graph_config, graph_runtime_state=graph_runtime_state, - max_execution_steps=500, - max_execution_time=30, command_channel=InMemoryChannel(), ) @@ -147,23 +133,11 @@ def test_streaming_output_with_blocking_not_equals_one(): use_mock_factory=True, ) - workflow_config = fixture_data.get("workflow", {}) - graph_config = workflow_config.get("graph", {}) - # Create and run the engine engine = GraphEngine( - tenant_id="test_tenant", - app_id="test_app", workflow_id="test_workflow", - user_id="test_user", - user_from=UserFrom.ACCOUNT, - invoke_from=InvokeFrom.DEBUGGER, - call_depth=0, graph=graph, - graph_config=graph_config, graph_runtime_state=graph_runtime_state, - max_execution_steps=500, - max_execution_time=30, command_channel=InMemoryChannel(), ) diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_context_preservation.py b/api/tests/unit_tests/core/workflow/graph_engine/test_context_preservation.py index b4bc67c595..c2175f048c 100644 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_context_preservation.py +++ b/api/tests/unit_tests/core/workflow/graph_engine/test_context_preservation.py @@ -9,7 +9,6 @@ import contextvars import queue import threading import time -from typing import Optional from unittest.mock import MagicMock from flask import Flask, g @@ -59,7 +58,7 @@ class TestContextPreservation: context = contextvars.copy_context() # Variable to store value from worker - worker_value: Optional[str] = None + worker_value: str | None = None def worker_task() -> None: nonlocal worker_value @@ -120,7 +119,7 @@ class TestContextPreservation: test_node = MagicMock(spec=Node) # Variable to capture context inside node execution - captured_value: Optional[str] = None + captured_value: str | None = None context_available_in_node = False def mock_run() -> list[GraphNodeEventBase]: diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_graph_engine.py b/api/tests/unit_tests/core/workflow/graph_engine/test_graph_engine.py index 11eecb6d77..6a723999de 100644 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_graph_engine.py +++ b/api/tests/unit_tests/core/workflow/graph_engine/test_graph_engine.py @@ -10,11 +10,9 @@ import time from hypothesis import HealthCheck, given, settings from hypothesis import strategies as st -from core.app.entities.app_invoke_entities import InvokeFrom from core.workflow.graph_engine import GraphEngine from core.workflow.graph_engine.command_channels import InMemoryChannel from core.workflow.graph_events import GraphRunStartedEvent, GraphRunSucceededEvent -from models.enums import UserFrom # Import the test framework from the new module from .test_table_runner import TableTestRunner, WorkflowRunner, WorkflowTestCase @@ -460,18 +458,9 @@ def test_layer_system_basic(): # Create engine with layer engine = GraphEngine( - tenant_id="test_tenant", - app_id="test_app", workflow_id="test_workflow", - user_id="test_user", - user_from=UserFrom.ACCOUNT, - invoke_from=InvokeFrom.WEB_APP, - call_depth=0, graph=graph, - graph_config=fixture_data.get("workflow", {}).get("graph", {}), graph_runtime_state=graph_runtime_state, - max_execution_steps=300, - max_execution_time=60, command_channel=InMemoryChannel(), ) @@ -525,18 +514,9 @@ def test_layer_chaining(): # Create engine engine = GraphEngine( - tenant_id="test_tenant", - app_id="test_app", workflow_id="test_workflow", - user_id="test_user", - user_from=UserFrom.ACCOUNT, - invoke_from=InvokeFrom.WEB_APP, - call_depth=0, graph=graph, - graph_config=fixture_data.get("workflow", {}).get("graph", {}), graph_runtime_state=graph_runtime_state, - max_execution_steps=300, - max_execution_time=60, command_channel=InMemoryChannel(), ) @@ -581,18 +561,9 @@ def test_layer_error_handling(): # Create engine with faulty layer engine = GraphEngine( - tenant_id="test_tenant", - app_id="test_app", workflow_id="test_workflow", - user_id="test_user", - user_from=UserFrom.ACCOUNT, - invoke_from=InvokeFrom.WEB_APP, - call_depth=0, graph=graph, - graph_config=fixture_data.get("workflow", {}).get("graph", {}), graph_runtime_state=graph_runtime_state, - max_execution_steps=300, - max_execution_time=60, command_channel=InMemoryChannel(), ) diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_graph_execution_serialization.py b/api/tests/unit_tests/core/workflow/graph_engine/test_graph_execution_serialization.py new file mode 100644 index 0000000000..6385b0b91f --- /dev/null +++ b/api/tests/unit_tests/core/workflow/graph_engine/test_graph_execution_serialization.py @@ -0,0 +1,194 @@ +"""Unit tests for GraphExecution serialization helpers.""" + +from __future__ import annotations + +import json +from collections import deque +from unittest.mock import MagicMock + +from core.workflow.enums import NodeExecutionType, NodeState, NodeType +from core.workflow.graph_engine.domain import GraphExecution +from core.workflow.graph_engine.response_coordinator import ResponseStreamCoordinator +from core.workflow.graph_engine.response_coordinator.path import Path +from core.workflow.graph_engine.response_coordinator.session import ResponseSession +from core.workflow.graph_events import NodeRunStreamChunkEvent +from core.workflow.nodes.base.template import Template, TextSegment, VariableSegment + + +class CustomGraphExecutionError(Exception): + """Custom exception used to verify error serialization.""" + + +def test_graph_execution_serialization_round_trip() -> None: + """GraphExecution serialization restores full aggregate state.""" + # Arrange + execution = GraphExecution(workflow_id="wf-1") + execution.start() + node_a = execution.get_or_create_node_execution("node-a") + node_a.mark_started(execution_id="exec-1") + node_a.increment_retry() + node_a.mark_failed("boom") + node_b = execution.get_or_create_node_execution("node-b") + node_b.mark_skipped() + execution.fail(CustomGraphExecutionError("serialization failure")) + + # Act + serialized = execution.dumps() + payload = json.loads(serialized) + restored = GraphExecution(workflow_id="wf-1") + restored.loads(serialized) + + # Assert + assert payload["type"] == "GraphExecution" + assert payload["version"] == "1.0" + assert restored.workflow_id == "wf-1" + assert restored.started is True + assert restored.completed is True + assert restored.aborted is False + assert isinstance(restored.error, CustomGraphExecutionError) + assert str(restored.error) == "serialization failure" + assert set(restored.node_executions) == {"node-a", "node-b"} + restored_node_a = restored.node_executions["node-a"] + assert restored_node_a.state is NodeState.TAKEN + assert restored_node_a.retry_count == 1 + assert restored_node_a.execution_id == "exec-1" + assert restored_node_a.error == "boom" + restored_node_b = restored.node_executions["node-b"] + assert restored_node_b.state is NodeState.SKIPPED + assert restored_node_b.retry_count == 0 + assert restored_node_b.execution_id is None + assert restored_node_b.error is None + + +def test_graph_execution_loads_replaces_existing_state() -> None: + """loads replaces existing runtime data with serialized snapshot.""" + # Arrange + source = GraphExecution(workflow_id="wf-2") + source.start() + source_node = source.get_or_create_node_execution("node-source") + source_node.mark_taken() + serialized = source.dumps() + + target = GraphExecution(workflow_id="wf-2") + target.start() + target.abort("pre-existing abort") + temp_node = target.get_or_create_node_execution("node-temp") + temp_node.increment_retry() + temp_node.mark_failed("temp error") + + # Act + target.loads(serialized) + + # Assert + assert target.aborted is False + assert target.error is None + assert target.started is True + assert target.completed is False + assert set(target.node_executions) == {"node-source"} + restored_node = target.node_executions["node-source"] + assert restored_node.state is NodeState.TAKEN + assert restored_node.retry_count == 0 + assert restored_node.execution_id is None + assert restored_node.error is None + + +def test_response_stream_coordinator_serialization_round_trip(monkeypatch) -> None: + """ResponseStreamCoordinator serialization restores coordinator internals.""" + + template_main = Template(segments=[TextSegment(text="Hi "), VariableSegment(selector=["node-source", "text"])]) + template_secondary = Template(segments=[TextSegment(text="secondary")]) + + class DummyNode: + def __init__(self, node_id: str, template: Template, execution_type: NodeExecutionType) -> None: + self.id = node_id + self.node_type = NodeType.ANSWER if execution_type == NodeExecutionType.RESPONSE else NodeType.LLM + self.execution_type = execution_type + self.state = NodeState.UNKNOWN + self.title = node_id + self.template = template + + def blocks_variable_output(self, *_args) -> bool: + return False + + response_node1 = DummyNode("response-1", template_main, NodeExecutionType.RESPONSE) + response_node2 = DummyNode("response-2", template_main, NodeExecutionType.RESPONSE) + response_node3 = DummyNode("response-3", template_main, NodeExecutionType.RESPONSE) + source_node = DummyNode("node-source", template_secondary, NodeExecutionType.EXECUTABLE) + + class DummyGraph: + def __init__(self) -> None: + self.nodes = { + response_node1.id: response_node1, + response_node2.id: response_node2, + response_node3.id: response_node3, + source_node.id: source_node, + } + self.edges: dict[str, object] = {} + self.root_node = response_node1 + + def get_outgoing_edges(self, _node_id: str): # pragma: no cover - not exercised + return [] + + def get_incoming_edges(self, _node_id: str): # pragma: no cover - not exercised + return [] + + graph = DummyGraph() + + def fake_from_node(cls, node: DummyNode) -> ResponseSession: + return ResponseSession(node_id=node.id, template=node.template) + + monkeypatch.setattr(ResponseSession, "from_node", classmethod(fake_from_node)) + + coordinator = ResponseStreamCoordinator(variable_pool=MagicMock(), graph=graph) # type: ignore[arg-type] + coordinator._response_nodes = {"response-1", "response-2", "response-3"} + coordinator._paths_maps = { + "response-1": [Path(edges=["edge-1"])], + "response-2": [Path(edges=[])], + "response-3": [Path(edges=["edge-2", "edge-3"])], + } + + active_session = ResponseSession(node_id="response-1", template=response_node1.template) + active_session.index = 1 + coordinator._active_session = active_session + waiting_session = ResponseSession(node_id="response-2", template=response_node2.template) + coordinator._waiting_sessions = deque([waiting_session]) + pending_session = ResponseSession(node_id="response-3", template=response_node3.template) + pending_session.index = 2 + coordinator._response_sessions = {"response-3": pending_session} + + coordinator._node_execution_ids = {"response-1": "exec-1"} + event = NodeRunStreamChunkEvent( + id="exec-1", + node_id="response-1", + node_type=NodeType.ANSWER, + selector=["node-source", "text"], + chunk="chunk-1", + is_final=False, + ) + coordinator._stream_buffers = {("node-source", "text"): [event]} + coordinator._stream_positions = {("node-source", "text"): 1} + coordinator._closed_streams = {("node-source", "text")} + + serialized = coordinator.dumps() + + restored = ResponseStreamCoordinator(variable_pool=MagicMock(), graph=graph) # type: ignore[arg-type] + monkeypatch.setattr(ResponseSession, "from_node", classmethod(fake_from_node)) + restored.loads(serialized) + + assert restored._response_nodes == {"response-1", "response-2", "response-3"} + assert restored._paths_maps["response-1"][0].edges == ["edge-1"] + assert restored._active_session is not None + assert restored._active_session.node_id == "response-1" + assert restored._active_session.index == 1 + waiting_restored = list(restored._waiting_sessions) + assert len(waiting_restored) == 1 + assert waiting_restored[0].node_id == "response-2" + assert waiting_restored[0].index == 0 + assert set(restored._response_sessions) == {"response-3"} + assert restored._response_sessions["response-3"].index == 2 + assert restored._node_execution_ids == {"response-1": "exec-1"} + assert ("node-source", "text") in restored._stream_buffers + restored_event = restored._stream_buffers[("node-source", "text")][0] + assert restored_event.chunk == "chunk-1" + assert restored._stream_positions[("node-source", "text")] == 1 + assert ("node-source", "text") in restored._closed_streams diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_mock_config.py b/api/tests/unit_tests/core/workflow/graph_engine/test_mock_config.py index 2bd60cc67c..b02f90588b 100644 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_mock_config.py +++ b/api/tests/unit_tests/core/workflow/graph_engine/test_mock_config.py @@ -7,7 +7,7 @@ the behavior of mock nodes during testing. from collections.abc import Callable from dataclasses import dataclass, field -from typing import Any, Optional +from typing import Any from core.workflow.enums import NodeType @@ -18,9 +18,9 @@ class NodeMockConfig: node_id: str outputs: dict[str, Any] = field(default_factory=dict) - error: Optional[str] = None + error: str | None = None delay: float = 0.0 # Simulated execution delay in seconds - custom_handler: Optional[Callable[..., dict[str, Any]]] = None + custom_handler: Callable[..., dict[str, Any]] | None = None @dataclass @@ -51,7 +51,7 @@ class MockConfig: default_template_transform_response: str = "This is mocked template transform output" default_code_response: dict[str, Any] = field(default_factory=lambda: {"result": "mocked code execution result"}) - def get_node_config(self, node_id: str) -> Optional[NodeMockConfig]: + def get_node_config(self, node_id: str) -> NodeMockConfig | None: """Get configuration for a specific node.""" return self.node_configs.get(node_id) diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_mock_nodes.py b/api/tests/unit_tests/core/workflow/graph_engine/test_mock_nodes.py index 3a8142d857..e5ae32bbff 100644 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_mock_nodes.py +++ b/api/tests/unit_tests/core/workflow/graph_engine/test_mock_nodes.py @@ -64,7 +64,7 @@ class MockNodeMixin: return default_outputs - def _should_simulate_error(self) -> Optional[str]: + def _should_simulate_error(self) -> str | None: """Check if this node should simulate an error.""" if not self.mock_config: return None @@ -615,18 +615,9 @@ class MockIterationNode(MockNodeMixin, IterationNode): # Create a new GraphEngine for this iteration graph_engine = GraphEngine( - tenant_id=self.tenant_id, - app_id=self.app_id, workflow_id=self.workflow_id, - user_id=self.user_id, - user_from=self.user_from, - invoke_from=self.invoke_from, - call_depth=self.workflow_call_depth, graph=iteration_graph, - graph_config=self.graph_config, graph_runtime_state=graph_runtime_state_copy, - max_execution_steps=10000, # Use default or config value - max_execution_time=600, # Use default or config value command_channel=InMemoryChannel(), # Use InMemoryChannel for sub-graphs ) @@ -685,18 +676,9 @@ class MockLoopNode(MockNodeMixin, LoopNode): # Create a new GraphEngine for this iteration graph_engine = GraphEngine( - tenant_id=self.tenant_id, - app_id=self.app_id, workflow_id=self.workflow_id, - user_id=self.user_id, - user_from=self.user_from, - invoke_from=self.invoke_from, - call_depth=self.workflow_call_depth, graph=loop_graph, - graph_config=self.graph_config, graph_runtime_state=graph_runtime_state_copy, - max_execution_steps=10000, # Use default or config value - max_execution_time=600, # Use default or config value command_channel=InMemoryChannel(), # Use InMemoryChannel for sub-graphs ) diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_parallel_streaming_workflow.py b/api/tests/unit_tests/core/workflow/graph_engine/test_parallel_streaming_workflow.py index 581f9a07da..d1f1f53b78 100644 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_parallel_streaming_workflow.py +++ b/api/tests/unit_tests/core/workflow/graph_engine/test_parallel_streaming_workflow.py @@ -118,18 +118,9 @@ def test_parallel_streaming_workflow(): # Create the graph engine engine = GraphEngine( - tenant_id="test_tenant", - app_id="test_app", workflow_id="test_workflow", - user_id="test_user", - user_from=UserFrom.ACCOUNT, - invoke_from=InvokeFrom.WEB_APP, - call_depth=0, graph=graph, - graph_config=graph_config, graph_runtime_state=graph_runtime_state, - max_execution_steps=500, - max_execution_time=30, command_channel=InMemoryChannel(), ) diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_table_runner.py b/api/tests/unit_tests/core/workflow/graph_engine/test_table_runner.py index 7677560b05..0f3a142b1a 100644 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_table_runner.py +++ b/api/tests/unit_tests/core/workflow/graph_engine/test_table_runner.py @@ -17,9 +17,8 @@ from concurrent.futures import ThreadPoolExecutor, as_completed from dataclasses import dataclass, field from functools import lru_cache from pathlib import Path -from typing import Any, Optional +from typing import Any -from core.app.entities.app_invoke_entities import InvokeFrom from core.tools.utils.yaml_utils import _load_yaml_file from core.variables import ( ArrayNumberVariable, @@ -42,7 +41,6 @@ from core.workflow.graph_events import ( ) from core.workflow.nodes.node_factory import DifyNodeFactory from core.workflow.system_variable import SystemVariable -from models.enums import UserFrom from .test_mock_config import MockConfig from .test_mock_factory import MockNodeFactory @@ -60,14 +58,14 @@ class WorkflowTestCase: query: str = "" description: str = "" timeout: float = 30.0 - mock_config: Optional[MockConfig] = None + mock_config: MockConfig | None = None use_auto_mock: bool = False - expected_event_sequence: Optional[Sequence[type[GraphEngineEvent]]] = None + expected_event_sequence: Sequence[type[GraphEngineEvent]] | None = None tags: list[str] = field(default_factory=list) skip: bool = False skip_reason: str = "" retry_count: int = 0 - custom_validator: Optional[Callable[[dict[str, Any]], bool]] = None + custom_validator: Callable[[dict[str, Any]], bool] | None = None @dataclass @@ -76,14 +74,14 @@ class WorkflowTestResult: test_case: WorkflowTestCase success: bool - error: Optional[Exception] = None - actual_outputs: Optional[dict[str, Any]] = None + error: Exception | None = None + actual_outputs: dict[str, Any] | None = None execution_time: float = 0.0 - event_sequence_match: Optional[bool] = None - event_mismatch_details: Optional[str] = None + event_sequence_match: bool | None = None + event_mismatch_details: str | None = None events: list[GraphEngineEvent] = field(default_factory=list) retry_attempts: int = 0 - validation_details: Optional[str] = None + validation_details: str | None = None @dataclass @@ -116,7 +114,7 @@ class TestSuiteResult: class WorkflowRunner: """Core workflow execution engine for tests.""" - def __init__(self, fixtures_dir: Optional[Path] = None): + def __init__(self, fixtures_dir: Path | None = None): """Initialize the workflow runner.""" if fixtures_dir is None: # Use the new central fixtures location @@ -147,9 +145,9 @@ class WorkflowRunner: self, fixture_data: dict[str, Any], query: str = "", - inputs: Optional[dict[str, Any]] = None, + inputs: dict[str, Any] | None = None, use_mock_factory: bool = False, - mock_config: Optional[MockConfig] = None, + mock_config: MockConfig | None = None, ) -> tuple[Graph, GraphRuntimeState]: """Create a Graph instance from fixture data.""" workflow_config = fixture_data.get("workflow", {}) @@ -240,7 +238,7 @@ class TableTestRunner: def __init__( self, - fixtures_dir: Optional[Path] = None, + fixtures_dir: Path | None = None, max_workers: int = 4, enable_logging: bool = False, log_level: str = "INFO", @@ -373,23 +371,11 @@ class TableTestRunner: mock_config=test_case.mock_config, ) - workflow_config = fixture_data.get("workflow", {}) - graph_config = workflow_config.get("graph", {}) - # Create and run the engine with configured worker settings engine = GraphEngine( - tenant_id="test_tenant", - app_id="test_app", workflow_id="test_workflow", - user_id="test_user", - user_from=UserFrom.ACCOUNT, - invoke_from=InvokeFrom.DEBUGGER, # Use DEBUGGER to avoid conversation_id requirement - call_depth=0, graph=graph, - graph_config=graph_config, graph_runtime_state=graph_runtime_state, - max_execution_steps=500, - max_execution_time=int(test_case.timeout), command_channel=InMemoryChannel(), min_workers=self.graph_engine_min_workers, max_workers=self.graph_engine_max_workers, @@ -469,8 +455,8 @@ class TableTestRunner: self, expected_outputs: dict[str, Any], actual_outputs: dict[str, Any], - custom_validator: Optional[Callable[[dict[str, Any]], bool]] = None, - ) -> tuple[bool, Optional[str]]: + custom_validator: Callable[[dict[str, Any]], bool] | None = None, + ) -> tuple[bool, str | None]: """ Validate actual outputs against expected outputs. @@ -519,7 +505,7 @@ class TableTestRunner: def _validate_event_sequence( self, expected_sequence: list[type[GraphEngineEvent]], actual_events: list[GraphEngineEvent] - ) -> tuple[bool, Optional[str]]: + ) -> tuple[bool, str | None]: """ Validate that actual events match the expected event sequence. @@ -551,7 +537,7 @@ class TableTestRunner: self, test_cases: list[WorkflowTestCase], parallel: bool = False, - tags_filter: Optional[list[str]] = None, + tags_filter: list[str] | None = None, fail_fast: bool = False, ) -> TestSuiteResult: """ diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_tool_in_chatflow.py b/api/tests/unit_tests/core/workflow/graph_engine/test_tool_in_chatflow.py index a192eadc82..34682ff8f9 100644 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_tool_in_chatflow.py +++ b/api/tests/unit_tests/core/workflow/graph_engine/test_tool_in_chatflow.py @@ -1,11 +1,9 @@ -from core.app.entities.app_invoke_entities import InvokeFrom from core.workflow.graph_engine import GraphEngine from core.workflow.graph_engine.command_channels import InMemoryChannel from core.workflow.graph_events import ( GraphRunSucceededEvent, NodeRunStreamChunkEvent, ) -from models.enums import UserFrom from .test_table_runner import TableTestRunner @@ -23,23 +21,11 @@ def test_tool_in_chatflow(): use_mock_factory=True, ) - workflow_config = fixture_data.get("workflow", {}) - graph_config = workflow_config.get("graph", {}) - # Create and run the engine engine = GraphEngine( - tenant_id="test_tenant", - app_id="test_app", workflow_id="test_workflow", - user_id="test_user", - user_from=UserFrom.ACCOUNT, - invoke_from=InvokeFrom.DEBUGGER, - call_depth=0, graph=graph, - graph_config=graph_config, graph_runtime_state=graph_runtime_state, - max_execution_steps=500, - max_execution_time=30, command_channel=InMemoryChannel(), ) diff --git a/api/uv.lock b/api/uv.lock index 788499f88f..0cc3b1899d 100644 --- a/api/uv.lock +++ b/api/uv.lock @@ -2,18 +2,24 @@ version = 1 revision = 3 requires-python = ">=3.11, <3.13" resolution-markers = [ - "python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and sys_platform == 'linux'", - "python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and sys_platform != 'linux'", - 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b/dev/reformat @@ -5,6 +5,9 @@ set -x SCRIPT_DIR="$(dirname "$(realpath "$0")")" cd "$SCRIPT_DIR/.." +# Import linter +uv run --directory api --dev lint-imports + # run ruff linter uv run --directory api --dev ruff check --fix ./