test: avoid leaking tool parameter decrypt mock

Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>

.github/actions/setup-web/action.yml

@@ -1,33 +1,13 @@
 name: Setup Web Environment
-description: Setup pnpm, Node.js, and install web dependencies.
-
-inputs:
-  node-version:
-    description: Node.js version to use
-    required: false
-    default: "22"
-  install-dependencies:
-    description: Whether to install web dependencies after setting up Node.js
-    required: false
-    default: "true"
 
 runs:
   using: composite
   steps:
-    - name: Install pnpm
-      uses: pnpm/action-setup@41ff72655975bd51cab0327fa583b6e92b6d3061 # v4.2.0
+    - name: Setup Vite+
+      uses: voidzero-dev/setup-vp@b5d848f5a62488f3d3d920f8aa6ac318a60c5f07 # v1
       with:
-        package_json_file: web/package.json
-        run_install: false
-
-    - name: Setup Node.js
-      uses: actions/setup-node@53b83947a5a98c8d113130e565377fae1a50d02f # v6.3.0
-      with:
-        node-version: ${{ inputs.node-version }}
-        cache: pnpm
-        cache-dependency-path: ./web/pnpm-lock.yaml
-
-    - name: Install dependencies
-      if: ${{ inputs.install-dependencies == 'true' }}
-      shell: bash
-      run: pnpm --dir web install --frozen-lockfile
+        node-version-file: "./web/.nvmrc"
+        cache: true
+        run-install: |
+          - cwd: ./web
+            args: ['--frozen-lockfile']

.github/workflows/autofix.yml

@@ -102,13 +102,11 @@ jobs:
       - name: Setup web environment
         if: steps.web-changes.outputs.any_changed == 'true'
         uses: ./.github/actions/setup-web
-        with:
-          node-version: "24"
 
       - name: ESLint autofix
         if: steps.web-changes.outputs.any_changed == 'true'
         run: |
           cd web
-          pnpm eslint --concurrency=2 --prune-suppressions --quiet || true
+          vp exec eslint --concurrency=2 --prune-suppressions --quiet || true
 
       - uses: autofix-ci/action@7a166d7532b277f34e16238930461bf77f9d7ed8 # v1.3.3

.github/workflows/main-ci.yml

@@ -62,6 +62,9 @@ jobs:
     needs: check-changes
     if: needs.check-changes.outputs.web-changed == 'true'
     uses: ./.github/workflows/web-tests.yml
+    with:
+      base_sha: ${{ github.event_name == 'pull_request' && github.event.pull_request.base.sha || github.event.before }}
+      head_sha: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
 
   style-check:
     name: Style Check

.github/workflows/style.yml

@@ -88,7 +88,7 @@ jobs:
         if: steps.changed-files.outputs.any_changed == 'true'
         working-directory: ./web
         run: |
-          pnpm run lint:ci
+          vp run lint:ci
         # pnpm run lint:report
         # continue-on-error: true
 
@@ -102,17 +102,17 @@ jobs:
       - name: Web tsslint
         if: steps.changed-files.outputs.any_changed == 'true'
         working-directory: ./web
-        run: pnpm run lint:tss
+        run: vp run lint:tss
 
       - name: Web type check
         if: steps.changed-files.outputs.any_changed == 'true'
         working-directory: ./web
-        run: pnpm run type-check
+        run: vp run type-check
 
       - name: Web dead code check
         if: steps.changed-files.outputs.any_changed == 'true'
         working-directory: ./web
-        run: pnpm run knip
+        run: vp run knip
 
   superlinter:
     name: SuperLinter

.github/workflows/translate-i18n-claude.yml

@@ -50,8 +50,6 @@ jobs:
 
       - name: Setup web environment
         uses: ./.github/actions/setup-web
-        with:
-          install-dependencies: "false"
 
       - name: Detect changed files and generate diff
         id: detect_changes

.github/workflows/web-tests.yml

@@ -2,6 +2,13 @@ name: Web Tests
 
 on:
   workflow_call:
+    inputs:
+      base_sha:
+        required: false
+        type: string
+      head_sha:
+        required: false
+        type: string
 
 permissions:
   contents: read
@@ -14,6 +21,8 @@ jobs:
   test:
     name: Web Tests (${{ matrix.shardIndex }}/${{ matrix.shardTotal }})
     runs-on: ubuntu-latest
+    env:
+      VITEST_COVERAGE_SCOPE: app-components
     strategy:
       fail-fast: false
       matrix:
@@ -34,7 +43,7 @@ jobs:
         uses: ./.github/actions/setup-web
 
       - name: Run tests
-        run: pnpm vitest run --reporter=blob --shard=${{ matrix.shardIndex }}/${{ matrix.shardTotal }} --coverage
+        run: vp test run --reporter=blob --shard=${{ matrix.shardIndex }}/${{ matrix.shardTotal }} --coverage
 
       - name: Upload blob report
         if: ${{ !cancelled() }}
@@ -50,6 +59,8 @@ jobs:
     if: ${{ !cancelled() }}
     needs: [test]
     runs-on: ubuntu-latest
+    env:
+      VITEST_COVERAGE_SCOPE: app-components
     defaults:
       run:
         shell: bash
@@ -59,6 +70,7 @@ jobs:
       - name: Checkout code
         uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
         with:
+          fetch-depth: 0
           persist-credentials: false
 
       - name: Setup web environment
@@ -72,7 +84,13 @@ jobs:
           merge-multiple: true
 
       - name: Merge reports
-        run: pnpm vitest --merge-reports --coverage --silent=passed-only
+        run: vp test --merge-reports --reporter=json --reporter=agent --coverage
+
+      - name: Check app/components diff coverage
+        env:
+          BASE_SHA: ${{ inputs.base_sha }}
+          HEAD_SHA: ${{ inputs.head_sha }}
+        run: node ./scripts/check-components-diff-coverage.mjs
 
       - name: Coverage Summary
         if: always()
@@ -429,4 +447,4 @@ jobs:
       - name: Web build check
         if: steps.changed-files.outputs.any_changed == 'true'
         working-directory: ./web
-        run: pnpm run build
+        run: vp run build

api/.env.example

@@ -188,7 +188,6 @@ VECTOR_INDEX_NAME_PREFIX=Vector_index
 # Weaviate configuration
 WEAVIATE_ENDPOINT=http://localhost:8080
 WEAVIATE_API_KEY=WVF5YThaHlkYwhGUSmCRgsX3tD5ngdN8pkih
-WEAVIATE_GRPC_ENABLED=false
 WEAVIATE_BATCH_SIZE=100
 WEAVIATE_TOKENIZATION=word
 

api/.importlinter

@@ -43,7 +43,6 @@ forbidden_modules =
     extensions.ext_redis
 allow_indirect_imports = True
 ignore_imports =
-    dify_graph.nodes.agent.agent_node -> extensions.ext_database
     dify_graph.nodes.llm.node -> extensions.ext_database
     dify_graph.model_runtime.model_providers.__base.ai_model -> extensions.ext_redis
     dify_graph.model_runtime.model_providers.model_provider_factory -> extensions.ext_redis
@@ -90,9 +89,6 @@ forbidden_modules =
     core.trigger
     core.variables
 ignore_imports =
-    dify_graph.nodes.agent.agent_node -> core.model_manager
-    dify_graph.nodes.agent.agent_node -> core.provider_manager
-    dify_graph.nodes.agent.agent_node -> core.tools.tool_manager
     dify_graph.nodes.llm.llm_utils -> core.model_manager
     dify_graph.nodes.llm.protocols -> core.model_manager
     dify_graph.nodes.llm.llm_utils -> dify_graph.model_runtime.model_providers.__base.large_language_model
@@ -100,8 +96,6 @@ ignore_imports =
     dify_graph.nodes.tool.tool_node -> core.callback_handler.workflow_tool_callback_handler
     dify_graph.nodes.tool.tool_node -> core.tools.tool_engine
     dify_graph.nodes.tool.tool_node -> core.tools.tool_manager
-    dify_graph.nodes.agent.agent_node -> core.agent.entities
-    dify_graph.nodes.agent.agent_node -> core.agent.plugin_entities
     dify_graph.nodes.knowledge_retrieval.knowledge_retrieval_node -> core.app.app_config.entities
     dify_graph.nodes.parameter_extractor.parameter_extractor_node -> core.prompt.advanced_prompt_transform
     dify_graph.nodes.parameter_extractor.parameter_extractor_node -> core.prompt.simple_prompt_transform
@@ -110,12 +104,10 @@ ignore_imports =
     dify_graph.nodes.parameter_extractor.parameter_extractor_node -> core.model_manager
     dify_graph.nodes.question_classifier.question_classifier_node -> core.model_manager
     dify_graph.nodes.tool.tool_node -> core.tools.utils.message_transformer
-    dify_graph.nodes.agent.agent_node -> models.model
     dify_graph.nodes.llm.node -> core.helper.code_executor
     dify_graph.nodes.llm.node -> core.llm_generator.output_parser.errors
     dify_graph.nodes.llm.node -> core.llm_generator.output_parser.structured_output
     dify_graph.nodes.llm.node -> core.model_manager
-    dify_graph.nodes.agent.entities -> core.prompt.entities.advanced_prompt_entities
     dify_graph.nodes.llm.entities -> core.prompt.entities.advanced_prompt_entities
     dify_graph.nodes.llm.node -> core.prompt.entities.advanced_prompt_entities
     dify_graph.nodes.llm.node -> core.prompt.utils.prompt_message_util
@@ -126,15 +118,11 @@ ignore_imports =
     dify_graph.nodes.question_classifier.question_classifier_node -> core.prompt.utils.prompt_message_util
     dify_graph.nodes.knowledge_index.entities -> core.rag.retrieval.retrieval_methods
     dify_graph.nodes.llm.node -> models.dataset
-    dify_graph.nodes.agent.agent_node -> core.tools.utils.message_transformer
     dify_graph.nodes.llm.file_saver -> core.tools.signature
     dify_graph.nodes.llm.file_saver -> core.tools.tool_file_manager
     dify_graph.nodes.tool.tool_node -> core.tools.errors
-    dify_graph.nodes.agent.agent_node -> extensions.ext_database
     dify_graph.nodes.llm.node -> extensions.ext_database
-    dify_graph.nodes.agent.agent_node -> models
     dify_graph.nodes.llm.node -> models.model
-    dify_graph.nodes.agent.agent_node -> services
     dify_graph.nodes.tool.tool_node -> services
     dify_graph.model_runtime.model_providers.__base.ai_model -> configs
     dify_graph.model_runtime.model_providers.__base.ai_model -> extensions.ext_redis

api/configs/middleware/vdb/weaviate_config.py

@@ -17,11 +17,6 @@ class WeaviateConfig(BaseSettings):
         default=None,
     )
 
-    WEAVIATE_GRPC_ENABLED: bool = Field(
-        description="Whether to enable gRPC for Weaviate connection (True for gRPC, False for HTTP)",
-        default=True,
-    )
-
     WEAVIATE_GRPC_ENDPOINT: str | None = Field(
         description="URL of the Weaviate gRPC server (e.g., 'grpc://localhost:50051' or 'grpcs://weaviate.example.com:443')",
         default=None,

api/controllers/console/workspace/plugin.py

@@ -5,6 +5,7 @@ from typing import Any, Literal
 from flask import request, send_file
 from flask_restx import Resource
 from pydantic import BaseModel, Field
+from werkzeug.datastructures import FileStorage
 from werkzeug.exceptions import Forbidden
 
 from configs import dify_config
@@ -169,6 +170,20 @@ register_enum_models(
 )
 
 
+def _read_upload_content(file: FileStorage, max_size: int) -> bytes:
+    """
+    Read the uploaded file and validate its actual size before delegating to the plugin service.
+
+    FileStorage.content_length is not reliable for multipart test uploads and may be zero even when
+    content exists, so the controllers validate against the loaded bytes instead.
+    """
+    content = file.read()
+    if len(content) > max_size:
+        raise ValueError("File size exceeds the maximum allowed size")
+
+    return content
+
+
 @console_ns.route("/workspaces/current/plugin/debugging-key")
 class PluginDebuggingKeyApi(Resource):
     @setup_required
@@ -284,12 +299,7 @@ class PluginUploadFromPkgApi(Resource):
         _, tenant_id = current_account_with_tenant()
 
         file = request.files["pkg"]
-
-        # check file size
-        if file.content_length > dify_config.PLUGIN_MAX_PACKAGE_SIZE:
-            raise ValueError("File size exceeds the maximum allowed size")
-
-        content = file.read()
+        content = _read_upload_content(file, dify_config.PLUGIN_MAX_PACKAGE_SIZE)
         try:
             response = PluginService.upload_pkg(tenant_id, content)
         except PluginDaemonClientSideError as e:
@@ -328,12 +338,7 @@ class PluginUploadFromBundleApi(Resource):
         _, tenant_id = current_account_with_tenant()
 
         file = request.files["bundle"]
-
-        # check file size
-        if file.content_length > dify_config.PLUGIN_MAX_BUNDLE_SIZE:
-            raise ValueError("File size exceeds the maximum allowed size")
-
-        content = file.read()
+        content = _read_upload_content(file, dify_config.PLUGIN_MAX_BUNDLE_SIZE)
         try:
             response = PluginService.upload_bundle(tenant_id, content)
         except PluginDaemonClientSideError as e:

api/controllers/inner_api/plugin/wraps.py

@@ -114,6 +114,7 @@ def get_user_tenant(view_func: Callable[P, R]):
 
 def plugin_data(view: Callable[P, R] | None = None, *, payload_type: type[BaseModel]):
     def decorator(view_func: Callable[P, R]):
+        @wraps(view_func)
         def decorated_view(*args: P.args, **kwargs: P.kwargs):
             try:
                 data = request.get_json()

api/core/agent/cot_agent_runner.py

@@ -6,6 +6,7 @@ from typing import Any
 
 from core.agent.base_agent_runner import BaseAgentRunner
 from core.agent.entities import AgentScratchpadUnit
+from core.agent.errors import AgentMaxIterationError
 from core.agent.output_parser.cot_output_parser import CotAgentOutputParser
 from core.app.apps.base_app_queue_manager import PublishFrom
 from core.app.entities.queue_entities import QueueAgentThoughtEvent, QueueMessageEndEvent, QueueMessageFileEvent
@@ -22,7 +23,6 @@ from dify_graph.model_runtime.entities.message_entities import (
     ToolPromptMessage,
     UserPromptMessage,
 )
-from dify_graph.nodes.agent.exc import AgentMaxIterationError
 from models.model import Message
 
 logger = logging.getLogger(__name__)

api/core/agent/errors.py

@@ -0,0 +1,9 @@
+class AgentMaxIterationError(Exception):
+    """Raised when an agent runner exceeds the configured max iteration count."""
+
+    def __init__(self, max_iteration: int):
+        self.max_iteration = max_iteration
+        super().__init__(
+            f"Agent exceeded the maximum iteration limit of {max_iteration}. "
+            f"The agent was unable to complete the task within the allowed number of iterations."
+        )

api/core/agent/fc_agent_runner.py

@@ -5,6 +5,7 @@ from copy import deepcopy
 from typing import Any, Union
 
 from core.agent.base_agent_runner import BaseAgentRunner
+from core.agent.errors import AgentMaxIterationError
 from core.app.apps.base_app_queue_manager import PublishFrom
 from core.app.entities.queue_entities import QueueAgentThoughtEvent, QueueMessageEndEvent, QueueMessageFileEvent
 from core.prompt.agent_history_prompt_transform import AgentHistoryPromptTransform
@@ -25,7 +26,6 @@ from dify_graph.model_runtime.entities import (
     UserPromptMessage,
 )
 from dify_graph.model_runtime.entities.message_entities import ImagePromptMessageContent, PromptMessageContentUnionTypes
-from dify_graph.nodes.agent.exc import AgentMaxIterationError
 from models.model import Message
 
 logger = logging.getLogger(__name__)

api/core/app/apps/advanced_chat/generate_response_converter.py

@@ -114,7 +114,7 @@ class AdvancedChatAppGenerateResponseConverter(AppGenerateResponseConverter):
                 metadata = sub_stream_response_dict.get("metadata", {})
                 sub_stream_response_dict["metadata"] = cls._get_simple_metadata(metadata)
                 response_chunk.update(sub_stream_response_dict)
-            if isinstance(sub_stream_response, ErrorStreamResponse):
+            elif isinstance(sub_stream_response, ErrorStreamResponse):
                 data = cls._error_to_stream_response(sub_stream_response.err)
                 response_chunk.update(data)
             elif isinstance(sub_stream_response, NodeStartStreamResponse | NodeFinishStreamResponse):

api/core/app/apps/agent_chat/generate_response_converter.py

@@ -113,7 +113,7 @@ class AgentChatAppGenerateResponseConverter(AppGenerateResponseConverter):
                 metadata = sub_stream_response_dict.get("metadata", {})
                 sub_stream_response_dict["metadata"] = cls._get_simple_metadata(metadata)
                 response_chunk.update(sub_stream_response_dict)
-            if isinstance(sub_stream_response, ErrorStreamResponse):
+            elif isinstance(sub_stream_response, ErrorStreamResponse):
                 data = cls._error_to_stream_response(sub_stream_response.err)
                 response_chunk.update(data)
             else:

api/core/app/apps/chat/generate_response_converter.py

@@ -113,7 +113,7 @@ class ChatAppGenerateResponseConverter(AppGenerateResponseConverter):
                 metadata = sub_stream_response_dict.get("metadata", {})
                 sub_stream_response_dict["metadata"] = cls._get_simple_metadata(metadata)
                 response_chunk.update(sub_stream_response_dict)
-            if isinstance(sub_stream_response, ErrorStreamResponse):
+            elif isinstance(sub_stream_response, ErrorStreamResponse):
                 data = cls._error_to_stream_response(sub_stream_response.err)
                 response_chunk.update(data)
             else:

api/core/app/apps/workflow_app_runner.py

@@ -3,7 +3,10 @@ import time
 from collections.abc import Mapping, Sequence
 from typing import Any, cast
 
+from pydantic import ValidationError
+
 from core.app.apps.base_app_queue_manager import AppQueueManager, PublishFrom
+from core.app.entities.agent_strategy import AgentStrategyInfo
 from core.app.entities.app_invoke_entities import InvokeFrom, UserFrom, build_dify_run_context
 from core.app.entities.queue_entities import (
     AppQueueEvent,
@@ -30,8 +33,10 @@ from core.app.entities.queue_entities import (
     QueueWorkflowSucceededEvent,
 )
 from core.workflow.node_factory import DifyNodeFactory
+from core.workflow.node_resolution import resolve_workflow_node_class
 from core.workflow.workflow_entry import WorkflowEntry
 from dify_graph.entities import GraphInitParams
+from dify_graph.entities.graph_config import NodeConfigDictAdapter
 from dify_graph.entities.pause_reason import HumanInputRequired
 from dify_graph.graph import Graph
 from dify_graph.graph_engine.layers.base import GraphEngineLayer
@@ -62,8 +67,6 @@ from dify_graph.graph_events import (
     NodeRunSucceededEvent,
 )
 from dify_graph.graph_events.graph import GraphRunAbortedEvent
-from dify_graph.nodes import NodeType
-from dify_graph.nodes.node_mapping import NODE_TYPE_CLASSES_MAPPING
 from dify_graph.runtime import GraphRuntimeState, VariablePool
 from dify_graph.system_variable import SystemVariable
 from dify_graph.variable_loader import DUMMY_VARIABLE_LOADER, VariableLoader, load_into_variable_pool
@@ -303,10 +306,12 @@ class WorkflowBasedAppRunner:
         if not target_node_config:
             raise ValueError(f"{node_type_label} node id not found in workflow graph")
 
+        target_node_config = NodeConfigDictAdapter.validate_python(target_node_config)
+
         # Get node class
-        node_type = NodeType(target_node_config.get("data", {}).get("type"))
-        node_version = target_node_config.get("data", {}).get("version", "1")
-        node_cls = NODE_TYPE_CLASSES_MAPPING[node_type][node_version]
+        node_type = target_node_config["data"].type
+        node_version = str(target_node_config["data"].version)
+        node_cls = resolve_workflow_node_class(node_type=node_type, node_version=node_version)
 
         # Use the variable pool from graph_runtime_state instead of creating a new one
         variable_pool = graph_runtime_state.variable_pool
@@ -334,6 +339,18 @@ class WorkflowBasedAppRunner:
 
         return graph, variable_pool
 
+    @staticmethod
+    def _build_agent_strategy_info(event: NodeRunStartedEvent) -> AgentStrategyInfo | None:
+        raw_agent_strategy = event.extras.get("agent_strategy")
+        if raw_agent_strategy is None:
+            return None
+
+        try:
+            return AgentStrategyInfo.model_validate(raw_agent_strategy)
+        except ValidationError:
+            logger.warning("Invalid agent strategy payload for node %s", event.node_id, exc_info=True)
+            return None
+
     def _handle_event(self, workflow_entry: WorkflowEntry, event: GraphEngineEvent):
         """
         Handle event
@@ -419,7 +436,7 @@ class WorkflowBasedAppRunner:
                     start_at=event.start_at,
                     in_iteration_id=event.in_iteration_id,
                     in_loop_id=event.in_loop_id,
-                    agent_strategy=event.agent_strategy,
+                    agent_strategy=self._build_agent_strategy_info(event),
                     provider_type=event.provider_type,
                     provider_id=event.provider_id,
                 )

api/core/app/entities/__init__.py

@@ -0,0 +1,3 @@
+from .agent_strategy import AgentStrategyInfo
+
+__all__ = ["AgentStrategyInfo"]

api/core/app/entities/agent_strategy.py

@@ -0,0 +1,8 @@
+from pydantic import BaseModel, ConfigDict
+
+
+class AgentStrategyInfo(BaseModel):
+    name: str
+    icon: str | None = None
+
+    model_config = ConfigDict(extra="forbid")

api/core/app/entities/queue_entities.py

@@ -5,8 +5,8 @@ from typing import Any
 
 from pydantic import BaseModel, ConfigDict, Field
 
+from core.app.entities.agent_strategy import AgentStrategyInfo
 from core.rag.entities.citation_metadata import RetrievalSourceMetadata
-from dify_graph.entities import AgentNodeStrategyInit
 from dify_graph.entities.pause_reason import PauseReason
 from dify_graph.entities.workflow_start_reason import WorkflowStartReason
 from dify_graph.enums import WorkflowNodeExecutionMetadataKey
@@ -314,7 +314,7 @@ class QueueNodeStartedEvent(AppQueueEvent):
     in_iteration_id: str | None = None
     in_loop_id: str | None = None
     start_at: datetime
-    agent_strategy: AgentNodeStrategyInit | None = None
+    agent_strategy: AgentStrategyInfo | None = None
 
     # FIXME(-LAN-): only for ToolNode, need to refactor
     provider_type: str  # should be a core.tools.entities.tool_entities.ToolProviderType

api/core/app/entities/task_entities.py

@@ -4,8 +4,8 @@ from typing import Any
 
 from pydantic import BaseModel, ConfigDict, Field
 
+from core.app.entities.agent_strategy import AgentStrategyInfo
 from core.rag.entities.citation_metadata import RetrievalSourceMetadata
-from dify_graph.entities import AgentNodeStrategyInit
 from dify_graph.entities.workflow_start_reason import WorkflowStartReason
 from dify_graph.enums import WorkflowExecutionStatus, WorkflowNodeExecutionMetadataKey, WorkflowNodeExecutionStatus
 from dify_graph.model_runtime.entities.llm_entities import LLMResult, LLMUsage
@@ -349,7 +349,7 @@ class NodeStartStreamResponse(StreamResponse):
         extras: dict[str, object] = Field(default_factory=dict)
         iteration_id: str | None = None
         loop_id: str | None = None
-        agent_strategy: AgentNodeStrategyInit | None = None
+        agent_strategy: AgentStrategyInfo | None = None
 
     event: StreamEvent = StreamEvent.NODE_STARTED
     workflow_run_id: str

api/core/llm_generator/llm_generator.py

@@ -193,7 +193,8 @@ class LLMGenerator:
                 error_step = "generate rule config"
             except Exception as e:
                 logger.exception("Failed to generate rule config, model: %s", args.model_config_data.name)
-                rule_config["error"] = str(e)
+                error = str(e)
+                error_step = "generate rule config"
 
             rule_config["error"] = f"Failed to {error_step}. Error: {error}" if error else ""
 
@@ -279,7 +280,8 @@ class LLMGenerator:
 
         except Exception as e:
             logger.exception("Failed to generate rule config, model: %s", args.model_config_data.name)
-            rule_config["error"] = str(e)
+            error = str(e)
+            error_step = "handle unexpected exception"
 
         rule_config["error"] = f"Failed to {error_step}. Error: {error}" if error else ""
 

api/core/plugin/entities/parameters.py

@@ -191,7 +191,7 @@ def cast_parameter_value(typ: StrEnum, value: Any, /):
     except ValueError:
         raise
     except Exception:
-        raise ValueError(f"The tool parameter value {value} is not in correct type of {as_normal_type(typ)}.")
+        raise ValueError(f"The tool parameter value {repr(value)} is not in correct type of {as_normal_type(typ)}.")
 
 
 def init_frontend_parameter(rule: PluginParameter, type: StrEnum, value: Any):

api/core/tools/builtin_tool/provider.py

@@ -113,17 +113,26 @@ class BuiltinToolProviderController(ToolProviderController):
         """
         return self.get_credentials_schema_by_type(CredentialType.API_KEY)
 
-    def get_credentials_schema_by_type(self, credential_type: str) -> list[ProviderConfig]:
+    def get_credentials_schema_by_type(self, credential_type: CredentialType | str) -> list[ProviderConfig]:
         """
         returns the credentials schema of the provider
 
-        :param credential_type: the type of the credential
-        :return: the credentials schema of the provider
+        :param credential_type: the type of the credential, as CredentialType or str; str values
+            are normalized via CredentialType.of and may raise ValueError for invalid values.
+        :return: list[ProviderConfig] for CredentialType.OAUTH2 or CredentialType.API_KEY, an
+            empty list for CredentialType.UNAUTHORIZED or missing schemas.
+
+        Reads from self.entity.oauth_schema and self.entity.credentials_schema.
+        Raises ValueError for invalid credential types.
         """
-        if credential_type == CredentialType.OAUTH2.value:
+        if isinstance(credential_type, str):
+            credential_type = CredentialType.of(credential_type)
+        if credential_type == CredentialType.OAUTH2:
             return self.entity.oauth_schema.credentials_schema.copy() if self.entity.oauth_schema else []
         if credential_type == CredentialType.API_KEY:
             return self.entity.credentials_schema.copy() if self.entity.credentials_schema else []
+        if credential_type == CredentialType.UNAUTHORIZED:
+            return []
         raise ValueError(f"Invalid credential type: {credential_type}")
 
     def get_oauth_client_schema(self) -> list[ProviderConfig]:

api/core/tools/tool_file_manager.py

@@ -137,6 +137,7 @@ class ToolFileManager:
 
             session.add(tool_file)
             session.commit()
+            session.refresh(tool_file)
 
         return tool_file
 

api/core/trigger/debug/event_selectors.py

@@ -19,6 +19,7 @@ from core.trigger.debug.events import (
     build_plugin_pool_key,
     build_webhook_pool_key,
 )
+from dify_graph.entities.graph_config import NodeConfigDict
 from dify_graph.enums import NodeType
 from dify_graph.nodes.trigger_plugin.entities import TriggerEventNodeData
 from dify_graph.nodes.trigger_schedule.entities import ScheduleConfig
@@ -41,10 +42,10 @@ class TriggerDebugEventPoller(ABC):
     app_id: str
     user_id: str
     tenant_id: str
-    node_config: Mapping[str, Any]
+    node_config: NodeConfigDict
     node_id: str
 
-    def __init__(self, tenant_id: str, user_id: str, app_id: str, node_config: Mapping[str, Any], node_id: str):
+    def __init__(self, tenant_id: str, user_id: str, app_id: str, node_config: NodeConfigDict, node_id: str):
         self.tenant_id = tenant_id
         self.user_id = user_id
         self.app_id = app_id
@@ -60,7 +61,7 @@ class PluginTriggerDebugEventPoller(TriggerDebugEventPoller):
     def poll(self) -> TriggerDebugEvent | None:
         from services.trigger.trigger_service import TriggerService
 
-        plugin_trigger_data = TriggerEventNodeData.model_validate(self.node_config.get("data", {}))
+        plugin_trigger_data = TriggerEventNodeData.model_validate(self.node_config["data"], from_attributes=True)
         provider_id = TriggerProviderID(plugin_trigger_data.provider_id)
         pool_key: str = build_plugin_pool_key(
             name=plugin_trigger_data.event_name,

api/core/workflow/node_factory.py

@@ -1,5 +1,5 @@
-from collections.abc import Mapping
-from typing import TYPE_CHECKING, Any, cast, final
+from collections.abc import Callable, Mapping
+from typing import TYPE_CHECKING, Any, TypeAlias, cast, final
 
 from sqlalchemy import select
 from sqlalchemy.orm import Session
@@ -22,7 +22,15 @@ from core.rag.retrieval.dataset_retrieval import DatasetRetrieval
 from core.rag.summary_index.summary_index import SummaryIndex
 from core.repositories.human_input_repository import HumanInputFormRepositoryImpl
 from core.tools.tool_file_manager import ToolFileManager
-from dify_graph.entities.graph_config import NodeConfigDict
+from core.workflow.node_resolution import resolve_workflow_node_class
+from core.workflow.nodes.agent.message_transformer import AgentMessageTransformer
+from core.workflow.nodes.agent.plugin_strategy_adapter import (
+    PluginAgentStrategyPresentationProvider,
+    PluginAgentStrategyResolver,
+)
+from core.workflow.nodes.agent.runtime_support import AgentRuntimeSupport
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.entities.graph_config import NodeConfigDict, NodeConfigDictAdapter
 from dify_graph.entities.graph_init_params import DIFY_RUN_CONTEXT_KEY
 from dify_graph.enums import NodeType, SystemVariableKey
 from dify_graph.file.file_manager import file_manager
@@ -31,26 +39,18 @@ from dify_graph.model_runtime.entities.model_entities import ModelType
 from dify_graph.model_runtime.memory import PromptMessageMemory
 from dify_graph.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from dify_graph.nodes.base.node import Node
-from dify_graph.nodes.code.code_node import CodeNode, WorkflowCodeExecutor
+from dify_graph.nodes.code.code_node import WorkflowCodeExecutor
 from dify_graph.nodes.code.entities import CodeLanguage
 from dify_graph.nodes.code.limits import CodeNodeLimits
-from dify_graph.nodes.datasource import DatasourceNode
-from dify_graph.nodes.document_extractor import DocumentExtractorNode, UnstructuredApiConfig
-from dify_graph.nodes.http_request import HttpRequestNode, build_http_request_config
-from dify_graph.nodes.human_input.human_input_node import HumanInputNode
-from dify_graph.nodes.knowledge_index.knowledge_index_node import KnowledgeIndexNode
-from dify_graph.nodes.knowledge_retrieval.knowledge_retrieval_node import KnowledgeRetrievalNode
-from dify_graph.nodes.llm.entities import ModelConfig
+from dify_graph.nodes.document_extractor import UnstructuredApiConfig
+from dify_graph.nodes.http_request import build_http_request_config
+from dify_graph.nodes.llm.entities import LLMNodeData
 from dify_graph.nodes.llm.exc import LLMModeRequiredError, ModelNotExistError
-from dify_graph.nodes.llm.node import LLMNode
-from dify_graph.nodes.node_mapping import LATEST_VERSION, NODE_TYPE_CLASSES_MAPPING
-from dify_graph.nodes.parameter_extractor.parameter_extractor_node import ParameterExtractorNode
-from dify_graph.nodes.question_classifier.question_classifier_node import QuestionClassifierNode
+from dify_graph.nodes.parameter_extractor.entities import ParameterExtractorNodeData
+from dify_graph.nodes.question_classifier.entities import QuestionClassifierNodeData
 from dify_graph.nodes.template_transform.template_renderer import (
     CodeExecutorJinja2TemplateRenderer,
 )
-from dify_graph.nodes.template_transform.template_transform_node import TemplateTransformNode
-from dify_graph.nodes.tool.tool_node import ToolNode
 from dify_graph.variables.segments import StringSegment
 from extensions.ext_database import db
 from models.model import Conversation
@@ -60,6 +60,9 @@ if TYPE_CHECKING:
     from dify_graph.runtime import GraphRuntimeState
 
 
+LLMCompatibleNodeData: TypeAlias = LLMNodeData | QuestionClassifierNodeData | ParameterExtractorNodeData
+
+
 def fetch_memory(
     *,
     conversation_id: str | None,
@@ -100,10 +103,7 @@ class DefaultWorkflowCodeExecutor:
 @final
 class DifyNodeFactory(NodeFactory):
     """
-    Default implementation of NodeFactory that uses the traditional node mapping.
-
-    This factory creates nodes by looking up their types in NODE_TYPE_CLASSES_MAPPING
-    and instantiating the appropriate node class.
+    Default implementation of NodeFactory that resolves node classes from the live registry.
     """
 
     def __init__(
@@ -146,6 +146,10 @@ class DifyNodeFactory(NodeFactory):
         )
 
         self._llm_credentials_provider, self._llm_model_factory = build_dify_model_access(self._dify_context.tenant_id)
+        self._agent_strategy_resolver = PluginAgentStrategyResolver()
+        self._agent_strategy_presentation_provider = PluginAgentStrategyPresentationProvider()
+        self._agent_runtime_support = AgentRuntimeSupport()
+        self._agent_message_transformer = AgentMessageTransformer()
 
     @staticmethod
     def _resolve_dify_context(run_context: Mapping[str, Any]) -> DifyRunContext:
@@ -157,178 +161,125 @@ class DifyNodeFactory(NodeFactory):
         return DifyRunContext.model_validate(raw_ctx)
 
     @override
-    def create_node(self, node_config: NodeConfigDict) -> Node:
+    def create_node(self, node_config: dict[str, Any] | NodeConfigDict) -> Node:
         """
         Create a Node instance from node configuration data using the traditional mapping.
 
         :param node_config: node configuration dictionary containing type and other data
         :return: initialized Node instance
-        :raises ValueError: if node type is unknown or configuration is invalid
+        :raises ValueError: if node_config fails NodeConfigDict/BaseNodeData validation
+            (including pydantic ValidationError, which subclasses ValueError),
+            if node type is unknown, or if no implementation exists for the resolved version
         """
-        # Get node_id from config
-        node_id = node_config["id"]
-
-        # Get node type from config
-        node_data = node_config["data"]
-        try:
-            node_type = NodeType(node_data["type"])
-        except ValueError:
-            raise ValueError(f"Unknown node type: {node_data['type']}")
-
-        # Get node class
-        node_mapping = NODE_TYPE_CLASSES_MAPPING.get(node_type)
-        if not node_mapping:
-            raise ValueError(f"No class mapping found for node type: {node_type}")
-
-        latest_node_class = node_mapping.get(LATEST_VERSION)
-        node_version = str(node_data.get("version", "1"))
-        matched_node_class = node_mapping.get(node_version)
-        node_class = matched_node_class or latest_node_class
-        if not node_class:
-            raise ValueError(f"No latest version class found for node type: {node_type}")
-
-        # Create node instance
-        if node_type == NodeType.CODE:
-            return CodeNode(
-                id=node_id,
-                config=node_config,
-                graph_init_params=self.graph_init_params,
-                graph_runtime_state=self.graph_runtime_state,
-                code_executor=self._code_executor,
-                code_limits=self._code_limits,
-            )
-
-        if node_type == NodeType.TEMPLATE_TRANSFORM:
-            return TemplateTransformNode(
-                id=node_id,
-                config=node_config,
-                graph_init_params=self.graph_init_params,
-                graph_runtime_state=self.graph_runtime_state,
-                template_renderer=self._template_renderer,
-                max_output_length=self._template_transform_max_output_length,
-            )
-
-        if node_type == NodeType.HTTP_REQUEST:
-            return HttpRequestNode(
-                id=node_id,
-                config=node_config,
-                graph_init_params=self.graph_init_params,
-                graph_runtime_state=self.graph_runtime_state,
-                http_request_config=self._http_request_config,
-                http_client=self._http_request_http_client,
-                tool_file_manager_factory=self._http_request_tool_file_manager_factory,
-                file_manager=self._http_request_file_manager,
-            )
-
-        if node_type == NodeType.HUMAN_INPUT:
-            return HumanInputNode(
-                id=node_id,
-                config=node_config,
-                graph_init_params=self.graph_init_params,
-                graph_runtime_state=self.graph_runtime_state,
-                form_repository=HumanInputFormRepositoryImpl(tenant_id=self._dify_context.tenant_id),
-            )
-
-        if node_type == NodeType.KNOWLEDGE_INDEX:
-            return KnowledgeIndexNode(
-                id=node_id,
-                config=node_config,
-                graph_init_params=self.graph_init_params,
-                graph_runtime_state=self.graph_runtime_state,
-                index_processor=IndexProcessor(),
-                summary_index_service=SummaryIndex(),
-            )
-
-        if node_type == NodeType.LLM:
-            model_instance = self._build_model_instance_for_llm_node(node_data)
-            memory = self._build_memory_for_llm_node(node_data=node_data, model_instance=model_instance)
-            return LLMNode(
-                id=node_id,
-                config=node_config,
-                graph_init_params=self.graph_init_params,
-                graph_runtime_state=self.graph_runtime_state,
-                credentials_provider=self._llm_credentials_provider,
-                model_factory=self._llm_model_factory,
-                model_instance=model_instance,
-                memory=memory,
-                http_client=self._http_request_http_client,
-            )
-
-        if node_type == NodeType.DATASOURCE:
-            return DatasourceNode(
-                id=node_id,
-                config=node_config,
-                graph_init_params=self.graph_init_params,
-                graph_runtime_state=self.graph_runtime_state,
-                datasource_manager=DatasourceManager,
-            )
-
-        if node_type == NodeType.KNOWLEDGE_RETRIEVAL:
-            return KnowledgeRetrievalNode(
-                id=node_id,
-                config=node_config,
-                graph_init_params=self.graph_init_params,
-                graph_runtime_state=self.graph_runtime_state,
-                rag_retrieval=self._rag_retrieval,
-            )
-
-        if node_type == NodeType.DOCUMENT_EXTRACTOR:
-            return DocumentExtractorNode(
-                id=node_id,
-                config=node_config,
-                graph_init_params=self.graph_init_params,
-                graph_runtime_state=self.graph_runtime_state,
-                unstructured_api_config=self._document_extractor_unstructured_api_config,
-                http_client=self._http_request_http_client,
-            )
-
-        if node_type == NodeType.QUESTION_CLASSIFIER:
-            model_instance = self._build_model_instance_for_llm_node(node_data)
-            memory = self._build_memory_for_llm_node(node_data=node_data, model_instance=model_instance)
-            return QuestionClassifierNode(
-                id=node_id,
-                config=node_config,
-                graph_init_params=self.graph_init_params,
-                graph_runtime_state=self.graph_runtime_state,
-                credentials_provider=self._llm_credentials_provider,
-                model_factory=self._llm_model_factory,
-                model_instance=model_instance,
-                memory=memory,
-                http_client=self._http_request_http_client,
-            )
-
-        if node_type == NodeType.PARAMETER_EXTRACTOR:
-            model_instance = self._build_model_instance_for_llm_node(node_data)
-            memory = self._build_memory_for_llm_node(node_data=node_data, model_instance=model_instance)
-            return ParameterExtractorNode(
-                id=node_id,
-                config=node_config,
-                graph_init_params=self.graph_init_params,
-                graph_runtime_state=self.graph_runtime_state,
-                credentials_provider=self._llm_credentials_provider,
-                model_factory=self._llm_model_factory,
-                model_instance=model_instance,
-                memory=memory,
-            )
-
-        if node_type == NodeType.TOOL:
-            return ToolNode(
-                id=node_id,
-                config=node_config,
-                graph_init_params=self.graph_init_params,
-                graph_runtime_state=self.graph_runtime_state,
-                tool_file_manager_factory=self._http_request_tool_file_manager_factory(),
-            )
-
+        typed_node_config = NodeConfigDictAdapter.validate_python(node_config)
+        node_id = typed_node_config["id"]
+        node_data = typed_node_config["data"]
+        node_class = self._resolve_node_class(node_type=node_data.type, node_version=str(node_data.version))
+        node_type = node_data.type
+        node_init_kwargs_factories: Mapping[NodeType, Callable[[], dict[str, object]]] = {
+            NodeType.CODE: lambda: {
+                "code_executor": self._code_executor,
+                "code_limits": self._code_limits,
+            },
+            NodeType.TEMPLATE_TRANSFORM: lambda: {
+                "template_renderer": self._template_renderer,
+                "max_output_length": self._template_transform_max_output_length,
+            },
+            NodeType.HTTP_REQUEST: lambda: {
+                "http_request_config": self._http_request_config,
+                "http_client": self._http_request_http_client,
+                "tool_file_manager_factory": self._http_request_tool_file_manager_factory,
+                "file_manager": self._http_request_file_manager,
+            },
+            NodeType.HUMAN_INPUT: lambda: {
+                "form_repository": HumanInputFormRepositoryImpl(tenant_id=self._dify_context.tenant_id),
+            },
+            NodeType.KNOWLEDGE_INDEX: lambda: {
+                "index_processor": IndexProcessor(),
+                "summary_index_service": SummaryIndex(),
+            },
+            NodeType.LLM: lambda: self._build_llm_compatible_node_init_kwargs(
+                node_class=node_class,
+                node_data=node_data,
+                include_http_client=True,
+            ),
+            NodeType.DATASOURCE: lambda: {
+                "datasource_manager": DatasourceManager,
+            },
+            NodeType.KNOWLEDGE_RETRIEVAL: lambda: {
+                "rag_retrieval": self._rag_retrieval,
+            },
+            NodeType.DOCUMENT_EXTRACTOR: lambda: {
+                "unstructured_api_config": self._document_extractor_unstructured_api_config,
+                "http_client": self._http_request_http_client,
+            },
+            NodeType.QUESTION_CLASSIFIER: lambda: self._build_llm_compatible_node_init_kwargs(
+                node_class=node_class,
+                node_data=node_data,
+                include_http_client=True,
+            ),
+            NodeType.PARAMETER_EXTRACTOR: lambda: self._build_llm_compatible_node_init_kwargs(
+                node_class=node_class,
+                node_data=node_data,
+                include_http_client=False,
+            ),
+            NodeType.TOOL: lambda: {
+                "tool_file_manager_factory": self._http_request_tool_file_manager_factory(),
+            },
+            NodeType.AGENT: lambda: {
+                "strategy_resolver": self._agent_strategy_resolver,
+                "presentation_provider": self._agent_strategy_presentation_provider,
+                "runtime_support": self._agent_runtime_support,
+                "message_transformer": self._agent_message_transformer,
+            },
+        }
+        node_init_kwargs = node_init_kwargs_factories.get(node_type, lambda: {})()
         return node_class(
             id=node_id,
-            config=node_config,
+            config=typed_node_config,
             graph_init_params=self.graph_init_params,
             graph_runtime_state=self.graph_runtime_state,
+            **node_init_kwargs,
         )
 
-    def _build_model_instance_for_llm_node(self, node_data: Mapping[str, Any]) -> ModelInstance:
-        node_data_model = ModelConfig.model_validate(node_data["model"])
+    @staticmethod
+    def _validate_resolved_node_data(node_class: type[Node], node_data: BaseNodeData) -> BaseNodeData:
+        """
+        Re-validate the permissive graph payload with the concrete NodeData model declared by the resolved node class.
+        """
+        return node_class.validate_node_data(node_data)
+
+    @staticmethod
+    def _resolve_node_class(*, node_type: NodeType, node_version: str) -> type[Node]:
+        return resolve_workflow_node_class(node_type=node_type, node_version=node_version)
+
+    def _build_llm_compatible_node_init_kwargs(
+        self,
+        *,
+        node_class: type[Node],
+        node_data: BaseNodeData,
+        include_http_client: bool,
+    ) -> dict[str, object]:
+        validated_node_data = cast(
+            LLMCompatibleNodeData,
+            self._validate_resolved_node_data(node_class=node_class, node_data=node_data),
+        )
+        model_instance = self._build_model_instance_for_llm_node(validated_node_data)
+        node_init_kwargs: dict[str, object] = {
+            "credentials_provider": self._llm_credentials_provider,
+            "model_factory": self._llm_model_factory,
+            "model_instance": model_instance,
+            "memory": self._build_memory_for_llm_node(
+                node_data=validated_node_data,
+                model_instance=model_instance,
+            ),
+        }
+        if include_http_client:
+            node_init_kwargs["http_client"] = self._http_request_http_client
+        return node_init_kwargs
+
+    def _build_model_instance_for_llm_node(self, node_data: LLMCompatibleNodeData) -> ModelInstance:
+        node_data_model = node_data.model
         if not node_data_model.mode:
             raise LLMModeRequiredError("LLM mode is required.")
 
@@ -364,14 +315,12 @@ class DifyNodeFactory(NodeFactory):
     def _build_memory_for_llm_node(
         self,
         *,
-        node_data: Mapping[str, Any],
+        node_data: LLMCompatibleNodeData,
         model_instance: ModelInstance,
     ) -> PromptMessageMemory | None:
-        raw_memory_config = node_data.get("memory")
-        if raw_memory_config is None:
+        if node_data.memory is None:
             return None
 
-        node_memory = MemoryConfig.model_validate(raw_memory_config)
         conversation_id_variable = self.graph_runtime_state.variable_pool.get(
             ["sys", SystemVariableKey.CONVERSATION_ID]
         )
@@ -381,6 +330,6 @@ class DifyNodeFactory(NodeFactory):
         return fetch_memory(
             conversation_id=conversation_id,
             app_id=self._dify_context.app_id,
-            node_data_memory=node_memory,
+            node_data_memory=node_data.memory,
             model_instance=model_instance,
         )

api/core/workflow/node_resolution.py

@@ -0,0 +1,42 @@
+from __future__ import annotations
+
+from collections.abc import Mapping
+from importlib import import_module
+
+from dify_graph.enums import NodeType
+from dify_graph.nodes.base.node import Node
+from dify_graph.nodes.node_mapping import LATEST_VERSION, get_node_type_classes_mapping
+
+_WORKFLOW_NODE_MODULES = ("core.workflow.nodes.agent",)
+_workflow_nodes_registered = False
+
+
+def ensure_workflow_nodes_registered() -> None:
+    """Import workflow-local node modules so they can register with `Node.__init_subclass__`."""
+    global _workflow_nodes_registered
+
+    if _workflow_nodes_registered:
+        return
+
+    for module_name in _WORKFLOW_NODE_MODULES:
+        import_module(module_name)
+
+    _workflow_nodes_registered = True
+
+
+def get_workflow_node_type_classes_mapping() -> Mapping[NodeType, Mapping[str, type[Node]]]:
+    ensure_workflow_nodes_registered()
+    return get_node_type_classes_mapping()
+
+
+def resolve_workflow_node_class(*, node_type: NodeType, node_version: str) -> type[Node]:
+    node_mapping = get_workflow_node_type_classes_mapping().get(node_type)
+    if not node_mapping:
+        raise ValueError(f"No class mapping found for node type: {node_type}")
+
+    latest_node_class = node_mapping.get(LATEST_VERSION)
+    matched_node_class = node_mapping.get(node_version)
+    node_class = matched_node_class or latest_node_class
+    if not node_class:
+        raise ValueError(f"No latest version class found for node type: {node_type}")
+    return node_class

api/core/workflow/nodes/agent/__init__.py

@@ -0,0 +1,4 @@
+from .agent_node import AgentNode
+from .entities import AgentNodeData
+
+__all__ = ["AgentNode", "AgentNodeData"]

api/core/workflow/nodes/agent/agent_node.py

@@ -0,0 +1,188 @@
+from __future__ import annotations
+
+from collections.abc import Generator, Mapping, Sequence
+from typing import TYPE_CHECKING, Any
+
+from dify_graph.entities.graph_config import NodeConfigDict
+from dify_graph.enums import NodeType, SystemVariableKey, WorkflowNodeExecutionStatus
+from dify_graph.node_events import NodeEventBase, NodeRunResult, StreamCompletedEvent
+from dify_graph.nodes.base.node import Node
+from dify_graph.nodes.base.variable_template_parser import VariableTemplateParser
+
+from .entities import AgentNodeData
+from .exceptions import (
+    AgentInvocationError,
+    AgentMessageTransformError,
+)
+from .message_transformer import AgentMessageTransformer
+from .runtime_support import AgentRuntimeSupport
+from .strategy_protocols import AgentStrategyPresentationProvider, AgentStrategyResolver
+
+if TYPE_CHECKING:
+    from dify_graph.entities import GraphInitParams
+    from dify_graph.runtime import GraphRuntimeState
+
+
+class AgentNode(Node[AgentNodeData]):
+    node_type = NodeType.AGENT
+
+    _strategy_resolver: AgentStrategyResolver
+    _presentation_provider: AgentStrategyPresentationProvider
+    _runtime_support: AgentRuntimeSupport
+    _message_transformer: AgentMessageTransformer
+
+    def __init__(
+        self,
+        id: str,
+        config: NodeConfigDict,
+        graph_init_params: GraphInitParams,
+        graph_runtime_state: GraphRuntimeState,
+        *,
+        strategy_resolver: AgentStrategyResolver,
+        presentation_provider: AgentStrategyPresentationProvider,
+        runtime_support: AgentRuntimeSupport,
+        message_transformer: AgentMessageTransformer,
+    ) -> None:
+        super().__init__(
+            id=id,
+            config=config,
+            graph_init_params=graph_init_params,
+            graph_runtime_state=graph_runtime_state,
+        )
+        self._strategy_resolver = strategy_resolver
+        self._presentation_provider = presentation_provider
+        self._runtime_support = runtime_support
+        self._message_transformer = message_transformer
+
+    @classmethod
+    def version(cls) -> str:
+        return "1"
+
+    def populate_start_event(self, event) -> None:
+        dify_ctx = self.require_dify_context()
+        event.extras["agent_strategy"] = {
+            "name": self.node_data.agent_strategy_name,
+            "icon": self._presentation_provider.get_icon(
+                tenant_id=dify_ctx.tenant_id,
+                agent_strategy_provider_name=self.node_data.agent_strategy_provider_name,
+            ),
+        }
+
+    def _run(self) -> Generator[NodeEventBase, None, None]:
+        from core.plugin.impl.exc import PluginDaemonClientSideError
+
+        dify_ctx = self.require_dify_context()
+
+        try:
+            strategy = self._strategy_resolver.resolve(
+                tenant_id=dify_ctx.tenant_id,
+                agent_strategy_provider_name=self.node_data.agent_strategy_provider_name,
+                agent_strategy_name=self.node_data.agent_strategy_name,
+            )
+        except Exception as e:
+            yield StreamCompletedEvent(
+                node_run_result=NodeRunResult(
+                    status=WorkflowNodeExecutionStatus.FAILED,
+                    inputs={},
+                    error=f"Failed to get agent strategy: {str(e)}",
+                ),
+            )
+            return
+
+        agent_parameters = strategy.get_parameters()
+
+        parameters = self._runtime_support.build_parameters(
+            agent_parameters=agent_parameters,
+            variable_pool=self.graph_runtime_state.variable_pool,
+            node_data=self.node_data,
+            strategy=strategy,
+            tenant_id=dify_ctx.tenant_id,
+            app_id=dify_ctx.app_id,
+            invoke_from=dify_ctx.invoke_from,
+        )
+        parameters_for_log = self._runtime_support.build_parameters(
+            agent_parameters=agent_parameters,
+            variable_pool=self.graph_runtime_state.variable_pool,
+            node_data=self.node_data,
+            strategy=strategy,
+            tenant_id=dify_ctx.tenant_id,
+            app_id=dify_ctx.app_id,
+            invoke_from=dify_ctx.invoke_from,
+            for_log=True,
+        )
+        credentials = self._runtime_support.build_credentials(parameters=parameters)
+
+        conversation_id = self.graph_runtime_state.variable_pool.get(["sys", SystemVariableKey.CONVERSATION_ID])
+
+        try:
+            message_stream = strategy.invoke(
+                params=parameters,
+                user_id=dify_ctx.user_id,
+                app_id=dify_ctx.app_id,
+                conversation_id=conversation_id.text if conversation_id else None,
+                credentials=credentials,
+            )
+        except Exception as e:
+            error = AgentInvocationError(f"Failed to invoke agent: {str(e)}", original_error=e)
+            yield StreamCompletedEvent(
+                node_run_result=NodeRunResult(
+                    status=WorkflowNodeExecutionStatus.FAILED,
+                    inputs=parameters_for_log,
+                    error=str(error),
+                )
+            )
+            return
+
+        try:
+            yield from self._message_transformer.transform(
+                messages=message_stream,
+                tool_info={
+                    "icon": self._presentation_provider.get_icon(
+                        tenant_id=dify_ctx.tenant_id,
+                        agent_strategy_provider_name=self.node_data.agent_strategy_provider_name,
+                    ),
+                    "agent_strategy": self.node_data.agent_strategy_name,
+                },
+                parameters_for_log=parameters_for_log,
+                user_id=dify_ctx.user_id,
+                tenant_id=dify_ctx.tenant_id,
+                node_type=self.node_type,
+                node_id=self._node_id,
+                node_execution_id=self.id,
+            )
+        except PluginDaemonClientSideError as e:
+            transform_error = AgentMessageTransformError(
+                f"Failed to transform agent message: {str(e)}", original_error=e
+            )
+            yield StreamCompletedEvent(
+                node_run_result=NodeRunResult(
+                    status=WorkflowNodeExecutionStatus.FAILED,
+                    inputs=parameters_for_log,
+                    error=str(transform_error),
+                )
+            )
+
+    @classmethod
+    def _extract_variable_selector_to_variable_mapping(
+        cls,
+        *,
+        graph_config: Mapping[str, Any],
+        node_id: str,
+        node_data: AgentNodeData,
+    ) -> Mapping[str, Sequence[str]]:
+        _ = graph_config  # Explicitly mark as unused
+        result: dict[str, Any] = {}
+        typed_node_data = node_data
+        for parameter_name in typed_node_data.agent_parameters:
+            input = typed_node_data.agent_parameters[parameter_name]
+            match input.type:
+                case "mixed" | "constant":
+                    selectors = VariableTemplateParser(str(input.value)).extract_variable_selectors()
+                    for selector in selectors:
+                        result[selector.variable] = selector.value_selector
+                case "variable":
+                    result[parameter_name] = input.value
+
+        result = {node_id + "." + key: value for key, value in result.items()}
+
+        return result

api/core/workflow/nodes/agent/entities.py

@@ -5,13 +5,15 @@ from pydantic import BaseModel
 
 from core.prompt.entities.advanced_prompt_entities import MemoryConfig
 from core.tools.entities.tool_entities import ToolSelector
-from dify_graph.nodes.base.entities import BaseNodeData
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.enums import NodeType
 
 
 class AgentNodeData(BaseNodeData):
-    agent_strategy_provider_name: str  # redundancy
+    type: NodeType = NodeType.AGENT
+    agent_strategy_provider_name: str
     agent_strategy_name: str
-    agent_strategy_label: str  # redundancy
+    agent_strategy_label: str
     memory: MemoryConfig | None = None
     # The version of the tool parameter.
     # If this value is None, it indicates this is a previous version

api/core/workflow/nodes/agent/exceptions.py

@@ -119,14 +119,3 @@ class AgentVariableTypeError(AgentNodeError):
         self.expected_type = expected_type
         self.actual_type = actual_type
         super().__init__(message)
-
-
-class AgentMaxIterationError(AgentNodeError):
-    """Exception raised when the agent exceeds the maximum iteration limit."""
-
-    def __init__(self, max_iteration: int):
-        self.max_iteration = max_iteration
-        super().__init__(
-            f"Agent exceeded the maximum iteration limit of {max_iteration}. "
-            f"The agent was unable to complete the task within the allowed number of iterations."
-        )

api/core/workflow/nodes/agent/message_transformer.py

@@ -0,0 +1,292 @@
+from __future__ import annotations
+
+from collections.abc import Generator, Mapping
+from typing import Any, cast
+
+from sqlalchemy import select
+from sqlalchemy.orm import Session
+
+from core.tools.entities.tool_entities import ToolInvokeMessage
+from core.tools.utils.message_transformer import ToolFileMessageTransformer
+from dify_graph.enums import NodeType, WorkflowNodeExecutionMetadataKey, WorkflowNodeExecutionStatus
+from dify_graph.file import File, FileTransferMethod
+from dify_graph.model_runtime.entities.llm_entities import LLMUsage, LLMUsageMetadata
+from dify_graph.model_runtime.utils.encoders import jsonable_encoder
+from dify_graph.node_events import (
+    AgentLogEvent,
+    NodeEventBase,
+    NodeRunResult,
+    StreamChunkEvent,
+    StreamCompletedEvent,
+)
+from dify_graph.variables.segments import ArrayFileSegment
+from extensions.ext_database import db
+from factories import file_factory
+from models import ToolFile
+from services.tools.builtin_tools_manage_service import BuiltinToolManageService
+
+from .exceptions import AgentNodeError, AgentVariableTypeError, ToolFileNotFoundError
+
+
+class AgentMessageTransformer:
+    def transform(
+        self,
+        *,
+        messages: Generator[ToolInvokeMessage, None, None],
+        tool_info: Mapping[str, Any],
+        parameters_for_log: dict[str, Any],
+        user_id: str,
+        tenant_id: str,
+        node_type: NodeType,
+        node_id: str,
+        node_execution_id: str,
+    ) -> Generator[NodeEventBase, None, None]:
+        from core.plugin.impl.plugin import PluginInstaller
+
+        message_stream = ToolFileMessageTransformer.transform_tool_invoke_messages(
+            messages=messages,
+            user_id=user_id,
+            tenant_id=tenant_id,
+            conversation_id=None,
+        )
+
+        text = ""
+        files: list[File] = []
+        json_list: list[dict | list] = []
+
+        agent_logs: list[AgentLogEvent] = []
+        agent_execution_metadata: Mapping[WorkflowNodeExecutionMetadataKey, Any] = {}
+        llm_usage = LLMUsage.empty_usage()
+        variables: dict[str, Any] = {}
+
+        for message in message_stream:
+            if message.type in {
+                ToolInvokeMessage.MessageType.IMAGE_LINK,
+                ToolInvokeMessage.MessageType.BINARY_LINK,
+                ToolInvokeMessage.MessageType.IMAGE,
+            }:
+                assert isinstance(message.message, ToolInvokeMessage.TextMessage)
+
+                url = message.message.text
+                if message.meta:
+                    transfer_method = message.meta.get("transfer_method", FileTransferMethod.TOOL_FILE)
+                else:
+                    transfer_method = FileTransferMethod.TOOL_FILE
+
+                tool_file_id = str(url).split("/")[-1].split(".")[0]
+
+                with Session(db.engine) as session:
+                    stmt = select(ToolFile).where(ToolFile.id == tool_file_id)
+                    tool_file = session.scalar(stmt)
+                    if tool_file is None:
+                        raise ToolFileNotFoundError(tool_file_id)
+
+                mapping = {
+                    "tool_file_id": tool_file_id,
+                    "type": file_factory.get_file_type_by_mime_type(tool_file.mimetype),
+                    "transfer_method": transfer_method,
+                    "url": url,
+                }
+                file = file_factory.build_from_mapping(
+                    mapping=mapping,
+                    tenant_id=tenant_id,
+                )
+                files.append(file)
+            elif message.type == ToolInvokeMessage.MessageType.BLOB:
+                assert isinstance(message.message, ToolInvokeMessage.TextMessage)
+                assert message.meta
+
+                tool_file_id = message.message.text.split("/")[-1].split(".")[0]
+                with Session(db.engine) as session:
+                    stmt = select(ToolFile).where(ToolFile.id == tool_file_id)
+                    tool_file = session.scalar(stmt)
+                    if tool_file is None:
+                        raise ToolFileNotFoundError(tool_file_id)
+
+                mapping = {
+                    "tool_file_id": tool_file_id,
+                    "transfer_method": FileTransferMethod.TOOL_FILE,
+                }
+                files.append(
+                    file_factory.build_from_mapping(
+                        mapping=mapping,
+                        tenant_id=tenant_id,
+                    )
+                )
+            elif message.type == ToolInvokeMessage.MessageType.TEXT:
+                assert isinstance(message.message, ToolInvokeMessage.TextMessage)
+                text += message.message.text
+                yield StreamChunkEvent(
+                    selector=[node_id, "text"],
+                    chunk=message.message.text,
+                    is_final=False,
+                )
+            elif message.type == ToolInvokeMessage.MessageType.JSON:
+                assert isinstance(message.message, ToolInvokeMessage.JsonMessage)
+                if node_type == NodeType.AGENT:
+                    if isinstance(message.message.json_object, dict):
+                        msg_metadata: dict[str, Any] = message.message.json_object.pop("execution_metadata", {})
+                        llm_usage = LLMUsage.from_metadata(cast(LLMUsageMetadata, msg_metadata))
+                        agent_execution_metadata = {
+                            WorkflowNodeExecutionMetadataKey(key): value
+                            for key, value in msg_metadata.items()
+                            if key in WorkflowNodeExecutionMetadataKey.__members__.values()
+                        }
+                    else:
+                        llm_usage = LLMUsage.empty_usage()
+                        agent_execution_metadata = {}
+                if message.message.json_object:
+                    json_list.append(message.message.json_object)
+            elif message.type == ToolInvokeMessage.MessageType.LINK:
+                assert isinstance(message.message, ToolInvokeMessage.TextMessage)
+                stream_text = f"Link: {message.message.text}\n"
+                text += stream_text
+                yield StreamChunkEvent(
+                    selector=[node_id, "text"],
+                    chunk=stream_text,
+                    is_final=False,
+                )
+            elif message.type == ToolInvokeMessage.MessageType.VARIABLE:
+                assert isinstance(message.message, ToolInvokeMessage.VariableMessage)
+                variable_name = message.message.variable_name
+                variable_value = message.message.variable_value
+                if message.message.stream:
+                    if not isinstance(variable_value, str):
+                        raise AgentVariableTypeError(
+                            "When 'stream' is True, 'variable_value' must be a string.",
+                            variable_name=variable_name,
+                            expected_type="str",
+                            actual_type=type(variable_value).__name__,
+                        )
+                    if variable_name not in variables:
+                        variables[variable_name] = ""
+                    variables[variable_name] += variable_value
+
+                    yield StreamChunkEvent(
+                        selector=[node_id, variable_name],
+                        chunk=variable_value,
+                        is_final=False,
+                    )
+                else:
+                    variables[variable_name] = variable_value
+            elif message.type == ToolInvokeMessage.MessageType.FILE:
+                assert message.meta is not None
+                assert isinstance(message.meta, dict)
+                if "file" not in message.meta:
+                    raise AgentNodeError("File message is missing 'file' key in meta")
+
+                if not isinstance(message.meta["file"], File):
+                    raise AgentNodeError(f"Expected File object but got {type(message.meta['file']).__name__}")
+                files.append(message.meta["file"])
+            elif message.type == ToolInvokeMessage.MessageType.LOG:
+                assert isinstance(message.message, ToolInvokeMessage.LogMessage)
+                if message.message.metadata:
+                    icon = tool_info.get("icon", "")
+                    dict_metadata = dict(message.message.metadata)
+                    if dict_metadata.get("provider"):
+                        manager = PluginInstaller()
+                        plugins = manager.list_plugins(tenant_id)
+                        try:
+                            current_plugin = next(
+                                plugin
+                                for plugin in plugins
+                                if f"{plugin.plugin_id}/{plugin.name}" == dict_metadata["provider"]
+                            )
+                            icon = current_plugin.declaration.icon
+                        except StopIteration:
+                            pass
+                        icon_dark = None
+                        try:
+                            builtin_tool = next(
+                                provider
+                                for provider in BuiltinToolManageService.list_builtin_tools(
+                                    user_id,
+                                    tenant_id,
+                                )
+                                if provider.name == dict_metadata["provider"]
+                            )
+                            icon = builtin_tool.icon
+                            icon_dark = builtin_tool.icon_dark
+                        except StopIteration:
+                            pass
+
+                        dict_metadata["icon"] = icon
+                        dict_metadata["icon_dark"] = icon_dark
+                        message.message.metadata = dict_metadata
+                agent_log = AgentLogEvent(
+                    message_id=message.message.id,
+                    node_execution_id=node_execution_id,
+                    parent_id=message.message.parent_id,
+                    error=message.message.error,
+                    status=message.message.status.value,
+                    data=message.message.data,
+                    label=message.message.label,
+                    metadata=message.message.metadata,
+                    node_id=node_id,
+                )
+
+                for log in agent_logs:
+                    if log.message_id == agent_log.message_id:
+                        log.data = agent_log.data
+                        log.status = agent_log.status
+                        log.error = agent_log.error
+                        log.label = agent_log.label
+                        log.metadata = agent_log.metadata
+                        break
+                else:
+                    agent_logs.append(agent_log)
+
+                yield agent_log
+
+        json_output: list[dict[str, Any] | list[Any]] = []
+        if agent_logs:
+            for log in agent_logs:
+                json_output.append(
+                    {
+                        "id": log.message_id,
+                        "parent_id": log.parent_id,
+                        "error": log.error,
+                        "status": log.status,
+                        "data": log.data,
+                        "label": log.label,
+                        "metadata": log.metadata,
+                        "node_id": log.node_id,
+                    }
+                )
+        if json_list:
+            json_output.extend(json_list)
+        else:
+            json_output.append({"data": []})
+
+        yield StreamChunkEvent(
+            selector=[node_id, "text"],
+            chunk="",
+            is_final=True,
+        )
+
+        for var_name in variables:
+            yield StreamChunkEvent(
+                selector=[node_id, var_name],
+                chunk="",
+                is_final=True,
+            )
+
+        yield StreamCompletedEvent(
+            node_run_result=NodeRunResult(
+                status=WorkflowNodeExecutionStatus.SUCCEEDED,
+                outputs={
+                    "text": text,
+                    "usage": jsonable_encoder(llm_usage),
+                    "files": ArrayFileSegment(value=files),
+                    "json": json_output,
+                    **variables,
+                },
+                metadata={
+                    **agent_execution_metadata,
+                    WorkflowNodeExecutionMetadataKey.TOOL_INFO: tool_info,
+                    WorkflowNodeExecutionMetadataKey.AGENT_LOG: agent_logs,
+                },
+                inputs=parameters_for_log,
+                llm_usage=llm_usage,
+            )
+        )

api/core/workflow/nodes/agent/plugin_strategy_adapter.py

@@ -0,0 +1,40 @@
+from __future__ import annotations
+
+from factories.agent_factory import get_plugin_agent_strategy
+
+from .strategy_protocols import AgentStrategyPresentationProvider, AgentStrategyResolver, ResolvedAgentStrategy
+
+
+class PluginAgentStrategyResolver(AgentStrategyResolver):
+    def resolve(
+        self,
+        *,
+        tenant_id: str,
+        agent_strategy_provider_name: str,
+        agent_strategy_name: str,
+    ) -> ResolvedAgentStrategy:
+        return get_plugin_agent_strategy(
+            tenant_id=tenant_id,
+            agent_strategy_provider_name=agent_strategy_provider_name,
+            agent_strategy_name=agent_strategy_name,
+        )
+
+
+class PluginAgentStrategyPresentationProvider(AgentStrategyPresentationProvider):
+    def get_icon(self, *, tenant_id: str, agent_strategy_provider_name: str) -> str | None:
+        from core.plugin.impl.plugin import PluginInstaller
+
+        manager = PluginInstaller()
+        try:
+            plugins = manager.list_plugins(tenant_id)
+        except Exception:
+            return None
+
+        try:
+            current_plugin = next(
+                plugin for plugin in plugins if f"{plugin.plugin_id}/{plugin.name}" == agent_strategy_provider_name
+            )
+        except StopIteration:
+            return None
+
+        return current_plugin.declaration.icon

api/core/workflow/nodes/agent/runtime_support.py

@@ -0,0 +1,276 @@
+from __future__ import annotations
+
+import json
+from collections.abc import Sequence
+from typing import Any, cast
+
+from packaging.version import Version
+from pydantic import ValidationError
+from sqlalchemy import select
+from sqlalchemy.orm import Session
+
+from core.agent.entities import AgentToolEntity
+from core.agent.plugin_entities import AgentStrategyParameter
+from core.memory.token_buffer_memory import TokenBufferMemory
+from core.model_manager import ModelInstance, ModelManager
+from core.plugin.entities.request import InvokeCredentials
+from core.provider_manager import ProviderManager
+from core.tools.entities.tool_entities import ToolIdentity, ToolParameter, ToolProviderType
+from core.tools.tool_manager import ToolManager
+from dify_graph.enums import SystemVariableKey
+from dify_graph.model_runtime.entities.model_entities import AIModelEntity, ModelType
+from dify_graph.runtime import VariablePool
+from dify_graph.variables.segments import StringSegment
+from extensions.ext_database import db
+from models.model import Conversation
+
+from .entities import AgentNodeData, AgentOldVersionModelFeatures, ParamsAutoGenerated
+from .exceptions import AgentInputTypeError, AgentVariableNotFoundError
+from .strategy_protocols import ResolvedAgentStrategy
+
+
+class AgentRuntimeSupport:
+    def build_parameters(
+        self,
+        *,
+        agent_parameters: Sequence[AgentStrategyParameter],
+        variable_pool: VariablePool,
+        node_data: AgentNodeData,
+        strategy: ResolvedAgentStrategy,
+        tenant_id: str,
+        app_id: str,
+        invoke_from: Any,
+        for_log: bool = False,
+    ) -> dict[str, Any]:
+        agent_parameters_dictionary = {parameter.name: parameter for parameter in agent_parameters}
+
+        result: dict[str, Any] = {}
+        for parameter_name in node_data.agent_parameters:
+            parameter = agent_parameters_dictionary.get(parameter_name)
+            if not parameter:
+                result[parameter_name] = None
+                continue
+
+            agent_input = node_data.agent_parameters[parameter_name]
+            match agent_input.type:
+                case "variable":
+                    variable = variable_pool.get(agent_input.value)  # type: ignore[arg-type]
+                    if variable is None:
+                        raise AgentVariableNotFoundError(str(agent_input.value))
+                    parameter_value = variable.value
+                case "mixed" | "constant":
+                    try:
+                        if not isinstance(agent_input.value, str):
+                            parameter_value = json.dumps(agent_input.value, ensure_ascii=False)
+                        else:
+                            parameter_value = str(agent_input.value)
+                    except TypeError:
+                        parameter_value = str(agent_input.value)
+
+                    segment_group = variable_pool.convert_template(parameter_value)
+                    parameter_value = segment_group.log if for_log else segment_group.text
+                    try:
+                        if not isinstance(agent_input.value, str):
+                            parameter_value = json.loads(parameter_value)
+                    except json.JSONDecodeError:
+                        parameter_value = parameter_value
+                case _:
+                    raise AgentInputTypeError(agent_input.type)
+
+            value = parameter_value
+            if parameter.type == "array[tools]":
+                value = cast(list[dict[str, Any]], value)
+                value = [tool for tool in value if tool.get("enabled", False)]
+                value = self._filter_mcp_type_tool(strategy, value)
+                for tool in value:
+                    if "schemas" in tool:
+                        tool.pop("schemas")
+                    parameters = tool.get("parameters", {})
+                    if all(isinstance(v, dict) for _, v in parameters.items()):
+                        params = {}
+                        for key, param in parameters.items():
+                            if param.get("auto", ParamsAutoGenerated.OPEN) in (
+                                ParamsAutoGenerated.CLOSE,
+                                0,
+                            ):
+                                value_param = param.get("value", {})
+                                if value_param and value_param.get("type", "") == "variable":
+                                    variable_selector = value_param.get("value")
+                                    if not variable_selector:
+                                        raise ValueError("Variable selector is missing for a variable-type parameter.")
+
+                                    variable = variable_pool.get(variable_selector)
+                                    if variable is None:
+                                        raise AgentVariableNotFoundError(str(variable_selector))
+
+                                    params[key] = variable.value
+                                else:
+                                    params[key] = value_param.get("value", "") if value_param is not None else None
+                            else:
+                                params[key] = None
+                        parameters = params
+                    tool["settings"] = {k: v.get("value", None) for k, v in tool.get("settings", {}).items()}
+                    tool["parameters"] = parameters
+
+            if not for_log:
+                if parameter.type == "array[tools]":
+                    value = cast(list[dict[str, Any]], value)
+                    tool_value = []
+                    for tool in value:
+                        provider_type = ToolProviderType(tool.get("type", ToolProviderType.BUILT_IN))
+                        setting_params = tool.get("settings", {})
+                        parameters = tool.get("parameters", {})
+                        manual_input_params = [key for key, value in parameters.items() if value is not None]
+
+                        parameters = {**parameters, **setting_params}
+                        entity = AgentToolEntity(
+                            provider_id=tool.get("provider_name", ""),
+                            provider_type=provider_type,
+                            tool_name=tool.get("tool_name", ""),
+                            tool_parameters=parameters,
+                            plugin_unique_identifier=tool.get("plugin_unique_identifier", None),
+                            credential_id=tool.get("credential_id", None),
+                        )
+
+                        extra = tool.get("extra", {})
+
+                        runtime_variable_pool: VariablePool | None = None
+                        if node_data.version != "1" or node_data.tool_node_version is not None:
+                            runtime_variable_pool = variable_pool
+                        tool_runtime = ToolManager.get_agent_tool_runtime(
+                            tenant_id,
+                            app_id,
+                            entity,
+                            invoke_from,
+                            runtime_variable_pool,
+                        )
+                        if tool_runtime.entity.description:
+                            tool_runtime.entity.description.llm = (
+                                extra.get("description", "") or tool_runtime.entity.description.llm
+                            )
+                        for tool_runtime_params in tool_runtime.entity.parameters:
+                            tool_runtime_params.form = (
+                                ToolParameter.ToolParameterForm.FORM
+                                if tool_runtime_params.name in manual_input_params
+                                else tool_runtime_params.form
+                            )
+                        manual_input_value = {}
+                        if tool_runtime.entity.parameters:
+                            manual_input_value = {
+                                key: value for key, value in parameters.items() if key in manual_input_params
+                            }
+                        runtime_parameters = {
+                            **tool_runtime.runtime.runtime_parameters,
+                            **manual_input_value,
+                        }
+                        tool_value.append(
+                            {
+                                **tool_runtime.entity.model_dump(mode="json"),
+                                "runtime_parameters": runtime_parameters,
+                                "credential_id": tool.get("credential_id", None),
+                                "provider_type": provider_type.value,
+                            }
+                        )
+                    value = tool_value
+                if parameter.type == AgentStrategyParameter.AgentStrategyParameterType.MODEL_SELECTOR:
+                    value = cast(dict[str, Any], value)
+                    model_instance, model_schema = self.fetch_model(tenant_id=tenant_id, value=value)
+                    history_prompt_messages = []
+                    if node_data.memory:
+                        memory = self.fetch_memory(
+                            variable_pool=variable_pool,
+                            app_id=app_id,
+                            model_instance=model_instance,
+                        )
+                        if memory:
+                            prompt_messages = memory.get_history_prompt_messages(
+                                message_limit=node_data.memory.window.size or None
+                            )
+                            history_prompt_messages = [
+                                prompt_message.model_dump(mode="json") for prompt_message in prompt_messages
+                            ]
+                    value["history_prompt_messages"] = history_prompt_messages
+                    if model_schema:
+                        model_schema = self._remove_unsupported_model_features_for_old_version(model_schema)
+                        value["entity"] = model_schema.model_dump(mode="json")
+                    else:
+                        value["entity"] = None
+            result[parameter_name] = value
+
+        return result
+
+    def build_credentials(self, *, parameters: dict[str, Any]) -> InvokeCredentials:
+        credentials = InvokeCredentials()
+        credentials.tool_credentials = {}
+        for tool in parameters.get("tools", []):
+            if not tool.get("credential_id"):
+                continue
+            try:
+                identity = ToolIdentity.model_validate(tool.get("identity", {}))
+            except ValidationError:
+                continue
+            credentials.tool_credentials[identity.provider] = tool.get("credential_id", None)
+        return credentials
+
+    def fetch_memory(
+        self,
+        *,
+        variable_pool: VariablePool,
+        app_id: str,
+        model_instance: ModelInstance,
+    ) -> TokenBufferMemory | None:
+        conversation_id_variable = variable_pool.get(["sys", SystemVariableKey.CONVERSATION_ID])
+        if not isinstance(conversation_id_variable, StringSegment):
+            return None
+        conversation_id = conversation_id_variable.value
+
+        with Session(db.engine, expire_on_commit=False) as session:
+            stmt = select(Conversation).where(Conversation.app_id == app_id, Conversation.id == conversation_id)
+            conversation = session.scalar(stmt)
+            if not conversation:
+                return None
+
+        return TokenBufferMemory(conversation=conversation, model_instance=model_instance)
+
+    def fetch_model(self, *, tenant_id: str, value: dict[str, Any]) -> tuple[ModelInstance, AIModelEntity | None]:
+        provider_manager = ProviderManager()
+        provider_model_bundle = provider_manager.get_provider_model_bundle(
+            tenant_id=tenant_id,
+            provider=value.get("provider", ""),
+            model_type=ModelType.LLM,
+        )
+        model_name = value.get("model", "")
+        model_credentials = provider_model_bundle.configuration.get_current_credentials(
+            model_type=ModelType.LLM,
+            model=model_name,
+        )
+        provider_name = provider_model_bundle.configuration.provider.provider
+        model_type_instance = provider_model_bundle.model_type_instance
+        model_instance = ModelManager().get_model_instance(
+            tenant_id=tenant_id,
+            provider=provider_name,
+            model_type=ModelType(value.get("model_type", "")),
+            model=model_name,
+        )
+        model_schema = model_type_instance.get_model_schema(model_name, model_credentials)
+        return model_instance, model_schema
+
+    @staticmethod
+    def _remove_unsupported_model_features_for_old_version(model_schema: AIModelEntity) -> AIModelEntity:
+        if model_schema.features:
+            for feature in model_schema.features[:]:
+                try:
+                    AgentOldVersionModelFeatures(feature.value)
+                except ValueError:
+                    model_schema.features.remove(feature)
+        return model_schema
+
+    @staticmethod
+    def _filter_mcp_type_tool(
+        strategy: ResolvedAgentStrategy,
+        tools: list[dict[str, Any]],
+    ) -> list[dict[str, Any]]:
+        meta_version = strategy.meta_version
+        if meta_version and Version(meta_version) > Version("0.0.1"):
+            return tools
+        return [tool for tool in tools if tool.get("type") != ToolProviderType.MCP]

api/core/workflow/nodes/agent/strategy_protocols.py

@@ -0,0 +1,39 @@
+from __future__ import annotations
+
+from collections.abc import Generator, Sequence
+from typing import Any, Protocol
+
+from core.agent.plugin_entities import AgentStrategyParameter
+from core.plugin.entities.request import InvokeCredentials
+from core.tools.entities.tool_entities import ToolInvokeMessage
+
+
+class ResolvedAgentStrategy(Protocol):
+    meta_version: str | None
+
+    def get_parameters(self) -> Sequence[AgentStrategyParameter]: ...
+
+    def invoke(
+        self,
+        *,
+        params: dict[str, Any],
+        user_id: str,
+        conversation_id: str | None = None,
+        app_id: str | None = None,
+        message_id: str | None = None,
+        credentials: InvokeCredentials | None = None,
+    ) -> Generator[ToolInvokeMessage, None, None]: ...
+
+
+class AgentStrategyResolver(Protocol):
+    def resolve(
+        self,
+        *,
+        tenant_id: str,
+        agent_strategy_provider_name: str,
+        agent_strategy_name: str,
+    ) -> ResolvedAgentStrategy: ...
+
+
+class AgentStrategyPresentationProvider(Protocol):
+    def get_icon(self, *, tenant_id: str, agent_strategy_provider_name: str) -> str | None: ...

api/core/workflow/workflow_entry.py

@@ -9,9 +9,10 @@ from core.app.entities.app_invoke_entities import InvokeFrom, UserFrom, build_di
 from core.app.workflow.layers.llm_quota import LLMQuotaLayer
 from core.app.workflow.layers.observability import ObservabilityLayer
 from core.workflow.node_factory import DifyNodeFactory
+from core.workflow.node_resolution import resolve_workflow_node_class
 from dify_graph.constants import ENVIRONMENT_VARIABLE_NODE_ID
 from dify_graph.entities import GraphInitParams
-from dify_graph.entities.graph_config import NodeConfigData, NodeConfigDict
+from dify_graph.entities.graph_config import NodeConfigDictAdapter
 from dify_graph.errors import WorkflowNodeRunFailedError
 from dify_graph.file.models import File
 from dify_graph.graph import Graph
@@ -23,7 +24,6 @@ from dify_graph.graph_engine.protocols.command_channel import CommandChannel
 from dify_graph.graph_events import GraphEngineEvent, GraphNodeEventBase, GraphRunFailedEvent
 from dify_graph.nodes import NodeType
 from dify_graph.nodes.base.node import Node
-from dify_graph.nodes.node_mapping import NODE_TYPE_CLASSES_MAPPING
 from dify_graph.runtime import ChildGraphNotFoundError, GraphRuntimeState, VariablePool
 from dify_graph.system_variable import SystemVariable
 from dify_graph.variable_loader import DUMMY_VARIABLE_LOADER, VariableLoader, load_into_variable_pool
@@ -212,7 +212,7 @@ class WorkflowEntry:
         node_config_data = node_config["data"]
 
         # Get node type
-        node_type = NodeType(node_config_data["type"])
+        node_type = node_config_data.type
 
         # init graph init params and runtime state
         graph_init_params = GraphInitParams(
@@ -234,8 +234,7 @@ class WorkflowEntry:
             graph_init_params=graph_init_params,
             graph_runtime_state=graph_runtime_state,
         )
-        typed_node_config = cast(dict[str, object], node_config)
-        node = cast(Any, node_factory).create_node(typed_node_config)
+        node = node_factory.create_node(node_config)
         node_cls = type(node)
 
         try:
@@ -344,7 +343,7 @@ class WorkflowEntry:
         if node_type not in {NodeType.PARAMETER_EXTRACTOR, NodeType.QUESTION_CLASSIFIER}:
             raise ValueError(f"Node type {node_type} not supported")
 
-        node_cls = NODE_TYPE_CLASSES_MAPPING[node_type]["1"]
+        node_cls = resolve_workflow_node_class(node_type=node_type, node_version="1")
         if not node_cls:
             raise ValueError(f"Node class not found for node type {node_type}")
 
@@ -371,10 +370,7 @@ class WorkflowEntry:
         graph_runtime_state = GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter())
 
         # init workflow run state
-        node_config: NodeConfigDict = {
-            "id": node_id,
-            "data": cast(NodeConfigData, node_data),
-        }
+        node_config = NodeConfigDictAdapter.validate_python({"id": node_id, "data": node_data})
         node_factory = DifyNodeFactory(
             graph_init_params=graph_init_params,
             graph_runtime_state=graph_runtime_state,

api/dify_graph/entities/__init__.py

@@ -1,11 +1,9 @@
-from .agent import AgentNodeStrategyInit
 from .graph_init_params import GraphInitParams
 from .workflow_execution import WorkflowExecution
 from .workflow_node_execution import WorkflowNodeExecution
 from .workflow_start_reason import WorkflowStartReason
 
 __all__ = [
-    "AgentNodeStrategyInit",
     "GraphInitParams",
     "WorkflowExecution",
     "WorkflowNodeExecution",

api/dify_graph/entities/agent.py

@@ -1,8 +0,0 @@
-from pydantic import BaseModel
-
-
-class AgentNodeStrategyInit(BaseModel):
-    """Agent node strategy initialization data."""
-
-    name: str
-    icon: str | None = None

api/dify_graph/entities/base_node_data.py

@@ -0,0 +1,176 @@
+from __future__ import annotations
+
+import json
+from abc import ABC
+from builtins import type as type_
+from enum import StrEnum
+from typing import Any, Union
+
+from pydantic import BaseModel, ConfigDict, Field, model_validator
+
+from dify_graph.entities.exc import DefaultValueTypeError
+from dify_graph.enums import ErrorStrategy, NodeType
+
+# Project supports Python 3.11+, where `typing.Union[...]` is valid in `isinstance`.
+_NumberType = Union[int, float]
+
+
+class RetryConfig(BaseModel):
+    """node retry config"""
+
+    max_retries: int = 0  # max retry times
+    retry_interval: int = 0  # retry interval in milliseconds
+    retry_enabled: bool = False  # whether retry is enabled
+
+    @property
+    def retry_interval_seconds(self) -> float:
+        return self.retry_interval / 1000
+
+
+class DefaultValueType(StrEnum):
+    STRING = "string"
+    NUMBER = "number"
+    OBJECT = "object"
+    ARRAY_NUMBER = "array[number]"
+    ARRAY_STRING = "array[string]"
+    ARRAY_OBJECT = "array[object]"
+    ARRAY_FILES = "array[file]"
+
+
+class DefaultValue(BaseModel):
+    value: Any = None
+    type: DefaultValueType
+    key: str
+
+    @staticmethod
+    def _parse_json(value: str):
+        """Unified JSON parsing handler"""
+        try:
+            return json.loads(value)
+        except json.JSONDecodeError:
+            raise DefaultValueTypeError(f"Invalid JSON format for value: {value}")
+
+    @staticmethod
+    def _validate_array(value: Any, element_type: type_ | tuple[type_, ...]) -> bool:
+        """Unified array type validation"""
+        return isinstance(value, list) and all(isinstance(x, element_type) for x in value)
+
+    @staticmethod
+    def _convert_number(value: str) -> float:
+        """Unified number conversion handler"""
+        try:
+            return float(value)
+        except ValueError:
+            raise DefaultValueTypeError(f"Cannot convert to number: {value}")
+
+    @model_validator(mode="after")
+    def validate_value_type(self) -> DefaultValue:
+        # Type validation configuration
+        type_validators: dict[DefaultValueType, dict[str, Any]] = {
+            DefaultValueType.STRING: {
+                "type": str,
+                "converter": lambda x: x,
+            },
+            DefaultValueType.NUMBER: {
+                "type": _NumberType,
+                "converter": self._convert_number,
+            },
+            DefaultValueType.OBJECT: {
+                "type": dict,
+                "converter": self._parse_json,
+            },
+            DefaultValueType.ARRAY_NUMBER: {
+                "type": list,
+                "element_type": _NumberType,
+                "converter": self._parse_json,
+            },
+            DefaultValueType.ARRAY_STRING: {
+                "type": list,
+                "element_type": str,
+                "converter": self._parse_json,
+            },
+            DefaultValueType.ARRAY_OBJECT: {
+                "type": list,
+                "element_type": dict,
+                "converter": self._parse_json,
+            },
+        }
+
+        validator: dict[str, Any] = type_validators.get(self.type, {})
+        if not validator:
+            if self.type == DefaultValueType.ARRAY_FILES:
+                # Handle files type
+                return self
+            raise DefaultValueTypeError(f"Unsupported type: {self.type}")
+
+        # Handle string input cases
+        if isinstance(self.value, str) and self.type != DefaultValueType.STRING:
+            self.value = validator["converter"](self.value)
+
+        # Validate base type
+        if not isinstance(self.value, validator["type"]):
+            raise DefaultValueTypeError(f"Value must be {validator['type'].__name__} type for {self.value}")
+
+        # Validate array element types
+        if validator["type"] == list and not self._validate_array(self.value, validator["element_type"]):
+            raise DefaultValueTypeError(f"All elements must be {validator['element_type'].__name__} for {self.value}")
+
+        return self
+
+
+class BaseNodeData(ABC, BaseModel):
+    # Raw graph payloads are first validated through `NodeConfigDictAdapter`, where
+    # `node["data"]` is typed as `BaseNodeData` before the concrete node class is known.
+    # At that boundary, node-specific fields are still "extra" relative to this shared DTO,
+    # and persisted templates/workflows also carry undeclared compatibility keys such as
+    # `selected`, `params`, `paramSchemas`, and `datasource_label`. Keep extras permissive
+    # here until graph parsing becomes discriminated by node type or those legacy payloads
+    # are normalized.
+    model_config = ConfigDict(extra="allow")
+
+    type: NodeType
+    title: str = ""
+    desc: str | None = None
+    version: str = "1"
+    error_strategy: ErrorStrategy | None = None
+    default_value: list[DefaultValue] | None = None
+    retry_config: RetryConfig = Field(default_factory=RetryConfig)
+
+    @property
+    def default_value_dict(self) -> dict[str, Any]:
+        if self.default_value:
+            return {item.key: item.value for item in self.default_value}
+        return {}
+
+    def __getitem__(self, key: str) -> Any:
+        """
+        Dict-style access without calling model_dump() on every lookup.
+        Prefer using model fields and Pydantic's extra storage.
+        """
+        # First, check declared model fields
+        if key in self.__class__.model_fields:
+            return getattr(self, key)
+
+        # Then, check undeclared compatibility fields stored in Pydantic's extra dict.
+        extras = getattr(self, "__pydantic_extra__", None)
+        if extras is None:
+            extras = getattr(self, "model_extra", None)
+        if extras is not None and key in extras:
+            return extras[key]
+
+        raise KeyError(key)
+
+    def get(self, key: str, default: Any = None) -> Any:
+        """
+        Dict-style .get() without calling model_dump() on every lookup.
+        """
+        if key in self.__class__.model_fields:
+            return getattr(self, key)
+
+        extras = getattr(self, "__pydantic_extra__", None)
+        if extras is None:
+            extras = getattr(self, "model_extra", None)
+        if extras is not None and key in extras:
+            return extras.get(key, default)
+
+        return default

api/dify_graph/entities/graph_config.py

@@ -4,21 +4,20 @@ import sys
 
 from pydantic import TypeAdapter, with_config
 
+from dify_graph.entities.base_node_data import BaseNodeData
+
 if sys.version_info >= (3, 12):
     from typing import TypedDict
 else:
     from typing_extensions import TypedDict
 
 
-@with_config(extra="allow")
-class NodeConfigData(TypedDict):
-    type: str
-
-
 @with_config(extra="allow")
 class NodeConfigDict(TypedDict):
     id: str
-    data: NodeConfigData
+    # This is the permissive raw graph boundary. Node factories re-validate `data`
+    # with the concrete `NodeData` subtype after resolving the node implementation.
+    data: BaseNodeData
 
 
 NodeConfigDictAdapter = TypeAdapter(NodeConfigDict)

api/dify_graph/graph/graph.py

@@ -8,7 +8,7 @@ from typing import Protocol, cast, final
 from pydantic import TypeAdapter
 
 from dify_graph.entities.graph_config import NodeConfigDict
-from dify_graph.enums import ErrorStrategy, NodeExecutionType, NodeState, NodeType
+from dify_graph.enums import ErrorStrategy, NodeExecutionType, NodeState
 from dify_graph.nodes.base.node import Node
 from libs.typing import is_str
 
@@ -34,7 +34,8 @@ class NodeFactory(Protocol):
 
         :param node_config: node configuration dictionary containing type and other data
         :return: initialized Node instance
-        :raises ValueError: if node type is unknown or configuration is invalid
+        :raises ValueError: if node type is unknown or no implementation exists for the resolved version
+        :raises ValidationError: if node_config does not satisfy NodeConfigDict/BaseNodeData validation
         """
         ...
 
@@ -115,10 +116,7 @@ class Graph:
         start_node_id = None
         for nid in root_candidates:
             node_data = node_configs_map[nid]["data"]
-            node_type = node_data["type"]
-            if not isinstance(node_type, str):
-                continue
-            if NodeType(node_type).is_start_node:
+            if node_data.type.is_start_node:
                 start_node_id = nid
                 break
 
@@ -203,6 +201,23 @@ class Graph:
 
         return GraphBuilder(graph_cls=cls)
 
+    @staticmethod
+    def _filter_canvas_only_nodes(node_configs: Sequence[Mapping[str, object]]) -> list[dict[str, object]]:
+        """
+        Remove editor-only nodes before `NodeConfigDict` validation.
+
+        Persisted note widgets use a top-level `type == "custom-note"` but leave
+        `data.type` empty because they are never executable graph nodes. Filter
+        them while configs are still raw dicts so Pydantic does not validate
+        their placeholder payloads against `BaseNodeData.type: NodeType`.
+        """
+        filtered_node_configs: list[dict[str, object]] = []
+        for node_config in node_configs:
+            if node_config.get("type", "") == "custom-note":
+                continue
+            filtered_node_configs.append(dict(node_config))
+        return filtered_node_configs
+
     @classmethod
     def _promote_fail_branch_nodes(cls, nodes: dict[str, Node]) -> None:
         """
@@ -302,13 +317,13 @@ class Graph:
         node_configs = graph_config.get("nodes", [])
 
         edge_configs = cast(list[dict[str, object]], edge_configs)
+        node_configs = cast(list[dict[str, object]], node_configs)
+        node_configs = cls._filter_canvas_only_nodes(node_configs)
         node_configs = _ListNodeConfigDict.validate_python(node_configs)
 
         if not node_configs:
             raise ValueError("Graph must have at least one node")
 
-        node_configs = [node_config for node_config in node_configs if node_config.get("type", "") != "custom-note"]
-
         # Parse node configurations
         node_configs_map = cls._parse_node_configs(node_configs)
 

api/dify_graph/graph_events/node.py

@@ -4,7 +4,6 @@ from datetime import datetime
 from pydantic import Field
 
 from core.rag.entities.citation_metadata import RetrievalSourceMetadata
-from dify_graph.entities import AgentNodeStrategyInit
 from dify_graph.entities.pause_reason import PauseReason
 
 from .base import GraphNodeEventBase
@@ -13,8 +12,8 @@ from .base import GraphNodeEventBase
 class NodeRunStartedEvent(GraphNodeEventBase):
     node_title: str
     predecessor_node_id: str | None = None
-    agent_strategy: AgentNodeStrategyInit | None = None
     start_at: datetime = Field(..., description="node start time")
+    extras: dict[str, object] = Field(default_factory=dict)
 
     # FIXME(-LAN-): only for ToolNode
     provider_type: str = ""

api/dify_graph/model_runtime/entities/message_entities.py

@@ -276,7 +276,4 @@ class ToolPromptMessage(PromptMessage):
 
         :return: True if prompt message is empty, False otherwise
         """
-        if not super().is_empty() and not self.tool_call_id:
-            return False
-
-        return True
+        return super().is_empty() and not self.tool_call_id

api/dify_graph/model_runtime/errors/invoke.py

@@ -4,7 +4,8 @@ class InvokeError(ValueError):
     description: str | None = None
 
     def __init__(self, description: str | None = None):
-        self.description = description
+        if description is not None:
+            self.description = description
 
     def __str__(self):
         return self.description or self.__class__.__name__

api/dify_graph/model_runtime/model_providers/model_provider_factory.py

@@ -282,7 +282,8 @@ class ModelProviderFactory:
                 all_model_type_models.append(model_schema)
 
             simple_provider_schema = provider_schema.to_simple_provider()
-            simple_provider_schema.models.extend(all_model_type_models)
+            if model_type:
+                simple_provider_schema.models = all_model_type_models
 
             providers.append(simple_provider_schema)
 

api/dify_graph/nodes/agent/__init__.py

@@ -1,3 +0,0 @@
-from .agent_node import AgentNode
-
-__all__ = ["AgentNode"]

api/dify_graph/nodes/agent/agent_node.py

@@ -1,762 +0,0 @@
-from __future__ import annotations
-
-import json
-from collections.abc import Generator, Mapping, Sequence
-from typing import TYPE_CHECKING, Any, cast
-
-from packaging.version import Version
-from pydantic import ValidationError
-from sqlalchemy import select
-from sqlalchemy.orm import Session
-
-from core.agent.entities import AgentToolEntity
-from core.agent.plugin_entities import AgentStrategyParameter
-from core.memory.token_buffer_memory import TokenBufferMemory
-from core.model_manager import ModelInstance, ModelManager
-from core.provider_manager import ProviderManager
-from core.tools.entities.tool_entities import (
-    ToolIdentity,
-    ToolInvokeMessage,
-    ToolParameter,
-    ToolProviderType,
-)
-from core.tools.tool_manager import ToolManager
-from core.tools.utils.message_transformer import ToolFileMessageTransformer
-from dify_graph.enums import (
-    NodeType,
-    SystemVariableKey,
-    WorkflowNodeExecutionMetadataKey,
-    WorkflowNodeExecutionStatus,
-)
-from dify_graph.file import File, FileTransferMethod
-from dify_graph.model_runtime.entities.llm_entities import LLMUsage, LLMUsageMetadata
-from dify_graph.model_runtime.entities.model_entities import AIModelEntity, ModelType
-from dify_graph.model_runtime.utils.encoders import jsonable_encoder
-from dify_graph.node_events import (
-    AgentLogEvent,
-    NodeEventBase,
-    NodeRunResult,
-    StreamChunkEvent,
-    StreamCompletedEvent,
-)
-from dify_graph.nodes.agent.entities import AgentNodeData, AgentOldVersionModelFeatures, ParamsAutoGenerated
-from dify_graph.nodes.base.node import Node
-from dify_graph.nodes.base.variable_template_parser import VariableTemplateParser
-from dify_graph.runtime import VariablePool
-from dify_graph.variables.segments import ArrayFileSegment, StringSegment
-from extensions.ext_database import db
-from factories import file_factory
-from factories.agent_factory import get_plugin_agent_strategy
-from models import ToolFile
-from models.model import Conversation
-from services.tools.builtin_tools_manage_service import BuiltinToolManageService
-
-from .exc import (
-    AgentInputTypeError,
-    AgentInvocationError,
-    AgentMessageTransformError,
-    AgentNodeError,
-    AgentVariableNotFoundError,
-    AgentVariableTypeError,
-    ToolFileNotFoundError,
-)
-
-if TYPE_CHECKING:
-    from core.agent.strategy.plugin import PluginAgentStrategy
-    from core.plugin.entities.request import InvokeCredentials
-
-
-class AgentNode(Node[AgentNodeData]):
-    """
-    Agent Node
-    """
-
-    node_type = NodeType.AGENT
-
-    @classmethod
-    def version(cls) -> str:
-        return "1"
-
-    def _run(self) -> Generator[NodeEventBase, None, None]:
-        from core.plugin.impl.exc import PluginDaemonClientSideError
-
-        dify_ctx = self.require_dify_context()
-
-        try:
-            strategy = get_plugin_agent_strategy(
-                tenant_id=dify_ctx.tenant_id,
-                agent_strategy_provider_name=self.node_data.agent_strategy_provider_name,
-                agent_strategy_name=self.node_data.agent_strategy_name,
-            )
-        except Exception as e:
-            yield StreamCompletedEvent(
-                node_run_result=NodeRunResult(
-                    status=WorkflowNodeExecutionStatus.FAILED,
-                    inputs={},
-                    error=f"Failed to get agent strategy: {str(e)}",
-                ),
-            )
-            return
-
-        agent_parameters = strategy.get_parameters()
-
-        # get parameters
-        parameters = self._generate_agent_parameters(
-            agent_parameters=agent_parameters,
-            variable_pool=self.graph_runtime_state.variable_pool,
-            node_data=self.node_data,
-            strategy=strategy,
-        )
-        parameters_for_log = self._generate_agent_parameters(
-            agent_parameters=agent_parameters,
-            variable_pool=self.graph_runtime_state.variable_pool,
-            node_data=self.node_data,
-            for_log=True,
-            strategy=strategy,
-        )
-        credentials = self._generate_credentials(parameters=parameters)
-
-        # get conversation id
-        conversation_id = self.graph_runtime_state.variable_pool.get(["sys", SystemVariableKey.CONVERSATION_ID])
-
-        try:
-            message_stream = strategy.invoke(
-                params=parameters,
-                user_id=dify_ctx.user_id,
-                app_id=dify_ctx.app_id,
-                conversation_id=conversation_id.text if conversation_id else None,
-                credentials=credentials,
-            )
-        except Exception as e:
-            error = AgentInvocationError(f"Failed to invoke agent: {str(e)}", original_error=e)
-            yield StreamCompletedEvent(
-                node_run_result=NodeRunResult(
-                    status=WorkflowNodeExecutionStatus.FAILED,
-                    inputs=parameters_for_log,
-                    error=str(error),
-                )
-            )
-            return
-
-        try:
-            yield from self._transform_message(
-                messages=message_stream,
-                tool_info={
-                    "icon": self.agent_strategy_icon,
-                    "agent_strategy": self.node_data.agent_strategy_name,
-                },
-                parameters_for_log=parameters_for_log,
-                user_id=dify_ctx.user_id,
-                tenant_id=dify_ctx.tenant_id,
-                node_type=self.node_type,
-                node_id=self._node_id,
-                node_execution_id=self.id,
-            )
-        except PluginDaemonClientSideError as e:
-            transform_error = AgentMessageTransformError(
-                f"Failed to transform agent message: {str(e)}", original_error=e
-            )
-            yield StreamCompletedEvent(
-                node_run_result=NodeRunResult(
-                    status=WorkflowNodeExecutionStatus.FAILED,
-                    inputs=parameters_for_log,
-                    error=str(transform_error),
-                )
-            )
-
-    def _generate_agent_parameters(
-        self,
-        *,
-        agent_parameters: Sequence[AgentStrategyParameter],
-        variable_pool: VariablePool,
-        node_data: AgentNodeData,
-        for_log: bool = False,
-        strategy: PluginAgentStrategy,
-    ) -> dict[str, Any]:
-        """
-        Generate parameters based on the given tool parameters, variable pool, and node data.
-
-        Args:
-            agent_parameters (Sequence[AgentParameter]): The list of agent parameters.
-            variable_pool (VariablePool): The variable pool containing the variables.
-            node_data (AgentNodeData): The data associated with the agent node.
-
-        Returns:
-            Mapping[str, Any]: A dictionary containing the generated parameters.
-
-        """
-        agent_parameters_dictionary = {parameter.name: parameter for parameter in agent_parameters}
-
-        result: dict[str, Any] = {}
-        for parameter_name in node_data.agent_parameters:
-            parameter = agent_parameters_dictionary.get(parameter_name)
-            if not parameter:
-                result[parameter_name] = None
-                continue
-            agent_input = node_data.agent_parameters[parameter_name]
-            match agent_input.type:
-                case "variable":
-                    variable = variable_pool.get(agent_input.value)  # type: ignore
-                    if variable is None:
-                        raise AgentVariableNotFoundError(str(agent_input.value))
-                    parameter_value = variable.value
-                case "mixed" | "constant":
-                    # variable_pool.convert_template expects a string template,
-                    # but if passing a dict, convert to JSON string first before rendering
-                    try:
-                        if not isinstance(agent_input.value, str):
-                            parameter_value = json.dumps(agent_input.value, ensure_ascii=False)
-                        else:
-                            parameter_value = str(agent_input.value)
-                    except TypeError:
-                        parameter_value = str(agent_input.value)
-                    segment_group = variable_pool.convert_template(parameter_value)
-                    parameter_value = segment_group.log if for_log else segment_group.text
-                    # variable_pool.convert_template returns a string,
-                    # so we need to convert it back to a dictionary
-                    try:
-                        if not isinstance(agent_input.value, str):
-                            parameter_value = json.loads(parameter_value)
-                    except json.JSONDecodeError:
-                        parameter_value = parameter_value
-                case _:
-                    raise AgentInputTypeError(agent_input.type)
-            value = parameter_value
-            if parameter.type == "array[tools]":
-                value = cast(list[dict[str, Any]], value)
-                value = [tool for tool in value if tool.get("enabled", False)]
-                value = self._filter_mcp_type_tool(strategy, value)
-                for tool in value:
-                    if "schemas" in tool:
-                        tool.pop("schemas")
-                    parameters = tool.get("parameters", {})
-                    if all(isinstance(v, dict) for _, v in parameters.items()):
-                        params = {}
-                        for key, param in parameters.items():
-                            if param.get("auto", ParamsAutoGenerated.OPEN) in (
-                                ParamsAutoGenerated.CLOSE,
-                                0,
-                            ):
-                                value_param = param.get("value", {})
-                                if value_param and value_param.get("type", "") == "variable":
-                                    variable_selector = value_param.get("value")
-                                    if not variable_selector:
-                                        raise ValueError("Variable selector is missing for a variable-type parameter.")
-
-                                    variable = variable_pool.get(variable_selector)
-                                    if variable is None:
-                                        raise AgentVariableNotFoundError(str(variable_selector))
-
-                                    params[key] = variable.value
-                                else:
-                                    params[key] = value_param.get("value", "") if value_param is not None else None
-                            else:
-                                params[key] = None
-                        parameters = params
-                    tool["settings"] = {k: v.get("value", None) for k, v in tool.get("settings", {}).items()}
-                    tool["parameters"] = parameters
-
-            if not for_log:
-                if parameter.type == "array[tools]":
-                    value = cast(list[dict[str, Any]], value)
-                    tool_value = []
-                    for tool in value:
-                        provider_type = ToolProviderType(tool.get("type", ToolProviderType.BUILT_IN))
-                        setting_params = tool.get("settings", {})
-                        parameters = tool.get("parameters", {})
-                        manual_input_params = [key for key, value in parameters.items() if value is not None]
-
-                        parameters = {**parameters, **setting_params}
-                        entity = AgentToolEntity(
-                            provider_id=tool.get("provider_name", ""),
-                            provider_type=provider_type,
-                            tool_name=tool.get("tool_name", ""),
-                            tool_parameters=parameters,
-                            plugin_unique_identifier=tool.get("plugin_unique_identifier", None),
-                            credential_id=tool.get("credential_id", None),
-                        )
-
-                        extra = tool.get("extra", {})
-
-                        # This is an issue that caused problems before.
-                        # Logically, we shouldn't use the node_data.version field for judgment
-                        # But for backward compatibility with historical data
-                        # this version field judgment is still preserved here.
-                        runtime_variable_pool: VariablePool | None = None
-                        if node_data.version != "1" or node_data.tool_node_version is not None:
-                            runtime_variable_pool = variable_pool
-                        dify_ctx = self.require_dify_context()
-                        tool_runtime = ToolManager.get_agent_tool_runtime(
-                            dify_ctx.tenant_id,
-                            dify_ctx.app_id,
-                            entity,
-                            dify_ctx.invoke_from,
-                            runtime_variable_pool,
-                        )
-                        if tool_runtime.entity.description:
-                            tool_runtime.entity.description.llm = (
-                                extra.get("description", "") or tool_runtime.entity.description.llm
-                            )
-                        for tool_runtime_params in tool_runtime.entity.parameters:
-                            tool_runtime_params.form = (
-                                ToolParameter.ToolParameterForm.FORM
-                                if tool_runtime_params.name in manual_input_params
-                                else tool_runtime_params.form
-                            )
-                        manual_input_value = {}
-                        if tool_runtime.entity.parameters:
-                            manual_input_value = {
-                                key: value for key, value in parameters.items() if key in manual_input_params
-                            }
-                        runtime_parameters = {
-                            **tool_runtime.runtime.runtime_parameters,
-                            **manual_input_value,
-                        }
-                        tool_value.append(
-                            {
-                                **tool_runtime.entity.model_dump(mode="json"),
-                                "runtime_parameters": runtime_parameters,
-                                "credential_id": tool.get("credential_id", None),
-                                "provider_type": provider_type.value,
-                            }
-                        )
-                    value = tool_value
-                if parameter.type == AgentStrategyParameter.AgentStrategyParameterType.MODEL_SELECTOR:
-                    value = cast(dict[str, Any], value)
-                    model_instance, model_schema = self._fetch_model(value)
-                    # memory config
-                    history_prompt_messages = []
-                    if node_data.memory:
-                        memory = self._fetch_memory(model_instance)
-                        if memory:
-                            prompt_messages = memory.get_history_prompt_messages(
-                                message_limit=node_data.memory.window.size or None
-                            )
-                            history_prompt_messages = [
-                                prompt_message.model_dump(mode="json") for prompt_message in prompt_messages
-                            ]
-                    value["history_prompt_messages"] = history_prompt_messages
-                    if model_schema:
-                        # remove structured output feature to support old version agent plugin
-                        model_schema = self._remove_unsupported_model_features_for_old_version(model_schema)
-                        value["entity"] = model_schema.model_dump(mode="json")
-                    else:
-                        value["entity"] = None
-            result[parameter_name] = value
-
-        return result
-
-    def _generate_credentials(
-        self,
-        parameters: dict[str, Any],
-    ) -> InvokeCredentials:
-        """
-        Generate credentials based on the given agent parameters.
-        """
-        from core.plugin.entities.request import InvokeCredentials
-
-        credentials = InvokeCredentials()
-
-        # generate credentials for tools selector
-        credentials.tool_credentials = {}
-        for tool in parameters.get("tools", []):
-            if tool.get("credential_id"):
-                try:
-                    identity = ToolIdentity.model_validate(tool.get("identity", {}))
-                    credentials.tool_credentials[identity.provider] = tool.get("credential_id", None)
-                except ValidationError:
-                    continue
-        return credentials
-
-    @classmethod
-    def _extract_variable_selector_to_variable_mapping(
-        cls,
-        *,
-        graph_config: Mapping[str, Any],
-        node_id: str,
-        node_data: Mapping[str, Any],
-    ) -> Mapping[str, Sequence[str]]:
-        # Create typed NodeData from dict
-        typed_node_data = AgentNodeData.model_validate(node_data)
-
-        result: dict[str, Any] = {}
-        for parameter_name in typed_node_data.agent_parameters:
-            input = typed_node_data.agent_parameters[parameter_name]
-            match input.type:
-                case "mixed" | "constant":
-                    selectors = VariableTemplateParser(str(input.value)).extract_variable_selectors()
-                    for selector in selectors:
-                        result[selector.variable] = selector.value_selector
-                case "variable":
-                    result[parameter_name] = input.value
-
-        result = {node_id + "." + key: value for key, value in result.items()}
-
-        return result
-
-    @property
-    def agent_strategy_icon(self) -> str | None:
-        """
-        Get agent strategy icon
-        :return:
-        """
-        from core.plugin.impl.plugin import PluginInstaller
-
-        manager = PluginInstaller()
-        dify_ctx = self.require_dify_context()
-        plugins = manager.list_plugins(dify_ctx.tenant_id)
-        try:
-            current_plugin = next(
-                plugin
-                for plugin in plugins
-                if f"{plugin.plugin_id}/{plugin.name}" == self.node_data.agent_strategy_provider_name
-            )
-            icon = current_plugin.declaration.icon
-        except StopIteration:
-            icon = None
-        return icon
-
-    def _fetch_memory(self, model_instance: ModelInstance) -> TokenBufferMemory | None:
-        # get conversation id
-        conversation_id_variable = self.graph_runtime_state.variable_pool.get(
-            ["sys", SystemVariableKey.CONVERSATION_ID]
-        )
-        if not isinstance(conversation_id_variable, StringSegment):
-            return None
-        conversation_id = conversation_id_variable.value
-
-        dify_ctx = self.require_dify_context()
-        with Session(db.engine, expire_on_commit=False) as session:
-            stmt = select(Conversation).where(
-                Conversation.app_id == dify_ctx.app_id, Conversation.id == conversation_id
-            )
-            conversation = session.scalar(stmt)
-
-            if not conversation:
-                return None
-
-        memory = TokenBufferMemory(conversation=conversation, model_instance=model_instance)
-
-        return memory
-
-    def _fetch_model(self, value: dict[str, Any]) -> tuple[ModelInstance, AIModelEntity | None]:
-        dify_ctx = self.require_dify_context()
-        provider_manager = ProviderManager()
-        provider_model_bundle = provider_manager.get_provider_model_bundle(
-            tenant_id=dify_ctx.tenant_id, provider=value.get("provider", ""), model_type=ModelType.LLM
-        )
-        model_name = value.get("model", "")
-        model_credentials = provider_model_bundle.configuration.get_current_credentials(
-            model_type=ModelType.LLM, model=model_name
-        )
-        provider_name = provider_model_bundle.configuration.provider.provider
-        model_type_instance = provider_model_bundle.model_type_instance
-        model_instance = ModelManager().get_model_instance(
-            tenant_id=dify_ctx.tenant_id,
-            provider=provider_name,
-            model_type=ModelType(value.get("model_type", "")),
-            model=model_name,
-        )
-        model_schema = model_type_instance.get_model_schema(model_name, model_credentials)
-        return model_instance, model_schema
-
-    def _remove_unsupported_model_features_for_old_version(self, model_schema: AIModelEntity) -> AIModelEntity:
-        if model_schema.features:
-            for feature in model_schema.features[:]:  # Create a copy to safely modify during iteration
-                try:
-                    AgentOldVersionModelFeatures(feature.value)  # Try to create enum member from value
-                except ValueError:
-                    model_schema.features.remove(feature)
-        return model_schema
-
-    def _filter_mcp_type_tool(self, strategy: PluginAgentStrategy, tools: list[dict[str, Any]]) -> list[dict[str, Any]]:
-        """
-        Filter MCP type tool
-        :param strategy: plugin agent strategy
-        :param tool: tool
-        :return: filtered tool dict
-        """
-        meta_version = strategy.meta_version
-        if meta_version and Version(meta_version) > Version("0.0.1"):
-            return tools
-        else:
-            return [tool for tool in tools if tool.get("type") != ToolProviderType.MCP]
-
-    def _transform_message(
-        self,
-        messages: Generator[ToolInvokeMessage, None, None],
-        tool_info: Mapping[str, Any],
-        parameters_for_log: dict[str, Any],
-        user_id: str,
-        tenant_id: str,
-        node_type: NodeType,
-        node_id: str,
-        node_execution_id: str,
-    ) -> Generator[NodeEventBase, None, None]:
-        """
-        Convert ToolInvokeMessages into tuple[plain_text, files]
-        """
-        # transform message and handle file storage
-        from core.plugin.impl.plugin import PluginInstaller
-
-        message_stream = ToolFileMessageTransformer.transform_tool_invoke_messages(
-            messages=messages,
-            user_id=user_id,
-            tenant_id=tenant_id,
-            conversation_id=None,
-        )
-
-        text = ""
-        files: list[File] = []
-        json_list: list[dict | list] = []
-
-        agent_logs: list[AgentLogEvent] = []
-        agent_execution_metadata: Mapping[WorkflowNodeExecutionMetadataKey, Any] = {}
-        llm_usage = LLMUsage.empty_usage()
-        variables: dict[str, Any] = {}
-
-        for message in message_stream:
-            if message.type in {
-                ToolInvokeMessage.MessageType.IMAGE_LINK,
-                ToolInvokeMessage.MessageType.BINARY_LINK,
-                ToolInvokeMessage.MessageType.IMAGE,
-            }:
-                assert isinstance(message.message, ToolInvokeMessage.TextMessage)
-
-                url = message.message.text
-                if message.meta:
-                    transfer_method = message.meta.get("transfer_method", FileTransferMethod.TOOL_FILE)
-                else:
-                    transfer_method = FileTransferMethod.TOOL_FILE
-
-                tool_file_id = str(url).split("/")[-1].split(".")[0]
-
-                with Session(db.engine) as session:
-                    stmt = select(ToolFile).where(ToolFile.id == tool_file_id)
-                    tool_file = session.scalar(stmt)
-                    if tool_file is None:
-                        raise ToolFileNotFoundError(tool_file_id)
-
-                mapping = {
-                    "tool_file_id": tool_file_id,
-                    "type": file_factory.get_file_type_by_mime_type(tool_file.mimetype),
-                    "transfer_method": transfer_method,
-                    "url": url,
-                }
-                file = file_factory.build_from_mapping(
-                    mapping=mapping,
-                    tenant_id=tenant_id,
-                )
-                files.append(file)
-            elif message.type == ToolInvokeMessage.MessageType.BLOB:
-                # get tool file id
-                assert isinstance(message.message, ToolInvokeMessage.TextMessage)
-                assert message.meta
-
-                tool_file_id = message.message.text.split("/")[-1].split(".")[0]
-                with Session(db.engine) as session:
-                    stmt = select(ToolFile).where(ToolFile.id == tool_file_id)
-                    tool_file = session.scalar(stmt)
-                    if tool_file is None:
-                        raise ToolFileNotFoundError(tool_file_id)
-
-                mapping = {
-                    "tool_file_id": tool_file_id,
-                    "transfer_method": FileTransferMethod.TOOL_FILE,
-                }
-
-                files.append(
-                    file_factory.build_from_mapping(
-                        mapping=mapping,
-                        tenant_id=tenant_id,
-                    )
-                )
-            elif message.type == ToolInvokeMessage.MessageType.TEXT:
-                assert isinstance(message.message, ToolInvokeMessage.TextMessage)
-                text += message.message.text
-                yield StreamChunkEvent(
-                    selector=[node_id, "text"],
-                    chunk=message.message.text,
-                    is_final=False,
-                )
-            elif message.type == ToolInvokeMessage.MessageType.JSON:
-                assert isinstance(message.message, ToolInvokeMessage.JsonMessage)
-                if node_type == NodeType.AGENT:
-                    if isinstance(message.message.json_object, dict):
-                        msg_metadata: dict[str, Any] = message.message.json_object.pop("execution_metadata", {})
-                        llm_usage = LLMUsage.from_metadata(cast(LLMUsageMetadata, msg_metadata))
-                        agent_execution_metadata = {
-                            WorkflowNodeExecutionMetadataKey(key): value
-                            for key, value in msg_metadata.items()
-                            if key in WorkflowNodeExecutionMetadataKey.__members__.values()
-                        }
-                    else:
-                        msg_metadata = {}
-                        llm_usage = LLMUsage.empty_usage()
-                        agent_execution_metadata = {}
-                if message.message.json_object:
-                    json_list.append(message.message.json_object)
-            elif message.type == ToolInvokeMessage.MessageType.LINK:
-                assert isinstance(message.message, ToolInvokeMessage.TextMessage)
-                stream_text = f"Link: {message.message.text}\n"
-                text += stream_text
-                yield StreamChunkEvent(
-                    selector=[node_id, "text"],
-                    chunk=stream_text,
-                    is_final=False,
-                )
-            elif message.type == ToolInvokeMessage.MessageType.VARIABLE:
-                assert isinstance(message.message, ToolInvokeMessage.VariableMessage)
-                variable_name = message.message.variable_name
-                variable_value = message.message.variable_value
-                if message.message.stream:
-                    if not isinstance(variable_value, str):
-                        raise AgentVariableTypeError(
-                            "When 'stream' is True, 'variable_value' must be a string.",
-                            variable_name=variable_name,
-                            expected_type="str",
-                            actual_type=type(variable_value).__name__,
-                        )
-                    if variable_name not in variables:
-                        variables[variable_name] = ""
-                    variables[variable_name] += variable_value
-
-                    yield StreamChunkEvent(
-                        selector=[node_id, variable_name],
-                        chunk=variable_value,
-                        is_final=False,
-                    )
-                else:
-                    variables[variable_name] = variable_value
-            elif message.type == ToolInvokeMessage.MessageType.FILE:
-                assert message.meta is not None
-                assert isinstance(message.meta, dict)
-                # Validate that meta contains a 'file' key
-                if "file" not in message.meta:
-                    raise AgentNodeError("File message is missing 'file' key in meta")
-
-                # Validate that the file is an instance of File
-                if not isinstance(message.meta["file"], File):
-                    raise AgentNodeError(f"Expected File object but got {type(message.meta['file']).__name__}")
-                files.append(message.meta["file"])
-            elif message.type == ToolInvokeMessage.MessageType.LOG:
-                assert isinstance(message.message, ToolInvokeMessage.LogMessage)
-                if message.message.metadata:
-                    icon = tool_info.get("icon", "")
-                    dict_metadata = dict(message.message.metadata)
-                    if dict_metadata.get("provider"):
-                        manager = PluginInstaller()
-                        plugins = manager.list_plugins(tenant_id)
-                        try:
-                            current_plugin = next(
-                                plugin
-                                for plugin in plugins
-                                if f"{plugin.plugin_id}/{plugin.name}" == dict_metadata["provider"]
-                            )
-                            icon = current_plugin.declaration.icon
-                        except StopIteration:
-                            pass
-                        icon_dark = None
-                        try:
-                            builtin_tool = next(
-                                provider
-                                for provider in BuiltinToolManageService.list_builtin_tools(
-                                    user_id,
-                                    tenant_id,
-                                )
-                                if provider.name == dict_metadata["provider"]
-                            )
-                            icon = builtin_tool.icon
-                            icon_dark = builtin_tool.icon_dark
-                        except StopIteration:
-                            pass
-
-                        dict_metadata["icon"] = icon
-                        dict_metadata["icon_dark"] = icon_dark
-                        message.message.metadata = dict_metadata
-                agent_log = AgentLogEvent(
-                    message_id=message.message.id,
-                    node_execution_id=node_execution_id,
-                    parent_id=message.message.parent_id,
-                    error=message.message.error,
-                    status=message.message.status.value,
-                    data=message.message.data,
-                    label=message.message.label,
-                    metadata=message.message.metadata,
-                    node_id=node_id,
-                )
-
-                # check if the agent log is already in the list
-                for log in agent_logs:
-                    if log.message_id == agent_log.message_id:
-                        # update the log
-                        log.data = agent_log.data
-                        log.status = agent_log.status
-                        log.error = agent_log.error
-                        log.label = agent_log.label
-                        log.metadata = agent_log.metadata
-                        break
-                else:
-                    agent_logs.append(agent_log)
-
-                yield agent_log
-
-        # Add agent_logs to outputs['json'] to ensure frontend can access thinking process
-        json_output: list[dict[str, Any] | list[Any]] = []
-
-        # Step 1: append each agent log as its own dict.
-        if agent_logs:
-            for log in agent_logs:
-                json_output.append(
-                    {
-                        "id": log.message_id,
-                        "parent_id": log.parent_id,
-                        "error": log.error,
-                        "status": log.status,
-                        "data": log.data,
-                        "label": log.label,
-                        "metadata": log.metadata,
-                        "node_id": log.node_id,
-                    }
-                )
-        # Step 2: normalize JSON into {"data": [...]}.change json to list[dict]
-        if json_list:
-            json_output.extend(json_list)
-        else:
-            json_output.append({"data": []})
-
-        # Send final chunk events for all streamed outputs
-        # Final chunk for text stream
-        yield StreamChunkEvent(
-            selector=[node_id, "text"],
-            chunk="",
-            is_final=True,
-        )
-
-        # Final chunks for any streamed variables
-        for var_name in variables:
-            yield StreamChunkEvent(
-                selector=[node_id, var_name],
-                chunk="",
-                is_final=True,
-            )
-
-        yield StreamCompletedEvent(
-            node_run_result=NodeRunResult(
-                status=WorkflowNodeExecutionStatus.SUCCEEDED,
-                outputs={
-                    "text": text,
-                    "usage": jsonable_encoder(llm_usage),
-                    "files": ArrayFileSegment(value=files),
-                    "json": json_output,
-                    **variables,
-                },
-                metadata={
-                    **agent_execution_metadata,
-                    WorkflowNodeExecutionMetadataKey.TOOL_INFO: tool_info,
-                    WorkflowNodeExecutionMetadataKey.AGENT_LOG: agent_logs,
-                },
-                inputs=parameters_for_log,
-                llm_usage=llm_usage,
-            )
-        )

api/dify_graph/nodes/answer/answer_node.py

@@ -48,12 +48,10 @@ class AnswerNode(Node[AnswerNodeData]):
         *,
         graph_config: Mapping[str, Any],
         node_id: str,
-        node_data: Mapping[str, Any],
+        node_data: AnswerNodeData,
     ) -> Mapping[str, Sequence[str]]:
-        # Create typed NodeData from dict
-        typed_node_data = AnswerNodeData.model_validate(node_data)
-
-        variable_template_parser = VariableTemplateParser(template=typed_node_data.answer)
+        _ = graph_config  # Explicitly mark as unused
+        variable_template_parser = VariableTemplateParser(template=node_data.answer)
         variable_selectors = variable_template_parser.extract_variable_selectors()
 
         variable_mapping = {}

api/dify_graph/nodes/answer/entities.py

@@ -3,7 +3,8 @@ from enum import StrEnum, auto
 
 from pydantic import BaseModel, Field
 
-from dify_graph.nodes.base import BaseNodeData
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.enums import NodeType
 
 
 class AnswerNodeData(BaseNodeData):
@@ -11,6 +12,7 @@ class AnswerNodeData(BaseNodeData):
     Answer Node Data.
     """
 
+    type: NodeType = NodeType.ANSWER
     answer: str = Field(..., description="answer template string")
 
 

api/dify_graph/nodes/base/__init__.py

@@ -1,4 +1,4 @@
-from .entities import BaseIterationNodeData, BaseIterationState, BaseLoopNodeData, BaseLoopState, BaseNodeData
+from .entities import BaseIterationNodeData, BaseIterationState, BaseLoopNodeData, BaseLoopState
 from .usage_tracking_mixin import LLMUsageTrackingMixin
 
 __all__ = [
@@ -6,6 +6,5 @@ __all__ = [
     "BaseIterationState",
     "BaseLoopNodeData",
     "BaseLoopState",
-    "BaseNodeData",
     "LLMUsageTrackingMixin",
 ]

api/dify_graph/nodes/base/entities.py

@@ -1,31 +1,12 @@
 from __future__ import annotations
 
-import json
-from abc import ABC
-from builtins import type as type_
 from collections.abc import Sequence
 from enum import StrEnum
-from typing import Any, Union
+from typing import Any
 
-from pydantic import BaseModel, field_validator, model_validator
+from pydantic import BaseModel, field_validator
 
-from dify_graph.enums import ErrorStrategy
-
-from .exc import DefaultValueTypeError
-
-_NumberType = Union[int, float]
-
-
-class RetryConfig(BaseModel):
-    """node retry config"""
-
-    max_retries: int = 0  # max retry times
-    retry_interval: int = 0  # retry interval in milliseconds
-    retry_enabled: bool = False  # whether retry is enabled
-
-    @property
-    def retry_interval_seconds(self) -> float:
-        return self.retry_interval / 1000
+from dify_graph.entities.base_node_data import BaseNodeData
 
 
 class VariableSelector(BaseModel):
@@ -76,112 +57,6 @@ class OutputVariableEntity(BaseModel):
         return v
 
 
-class DefaultValueType(StrEnum):
-    STRING = "string"
-    NUMBER = "number"
-    OBJECT = "object"
-    ARRAY_NUMBER = "array[number]"
-    ARRAY_STRING = "array[string]"
-    ARRAY_OBJECT = "array[object]"
-    ARRAY_FILES = "array[file]"
-
-
-class DefaultValue(BaseModel):
-    value: Any = None
-    type: DefaultValueType
-    key: str
-
-    @staticmethod
-    def _parse_json(value: str):
-        """Unified JSON parsing handler"""
-        try:
-            return json.loads(value)
-        except json.JSONDecodeError:
-            raise DefaultValueTypeError(f"Invalid JSON format for value: {value}")
-
-    @staticmethod
-    def _validate_array(value: Any, element_type: type_ | tuple[type_, ...]) -> bool:
-        """Unified array type validation"""
-        return isinstance(value, list) and all(isinstance(x, element_type) for x in value)
-
-    @staticmethod
-    def _convert_number(value: str) -> float:
-        """Unified number conversion handler"""
-        try:
-            return float(value)
-        except ValueError:
-            raise DefaultValueTypeError(f"Cannot convert to number: {value}")
-
-    @model_validator(mode="after")
-    def validate_value_type(self) -> DefaultValue:
-        # Type validation configuration
-        type_validators: dict[DefaultValueType, dict[str, Any]] = {
-            DefaultValueType.STRING: {
-                "type": str,
-                "converter": lambda x: x,
-            },
-            DefaultValueType.NUMBER: {
-                "type": _NumberType,
-                "converter": self._convert_number,
-            },
-            DefaultValueType.OBJECT: {
-                "type": dict,
-                "converter": self._parse_json,
-            },
-            DefaultValueType.ARRAY_NUMBER: {
-                "type": list,
-                "element_type": _NumberType,
-                "converter": self._parse_json,
-            },
-            DefaultValueType.ARRAY_STRING: {
-                "type": list,
-                "element_type": str,
-                "converter": self._parse_json,
-            },
-            DefaultValueType.ARRAY_OBJECT: {
-                "type": list,
-                "element_type": dict,
-                "converter": self._parse_json,
-            },
-        }
-
-        validator: dict[str, Any] = type_validators.get(self.type, {})
-        if not validator:
-            if self.type == DefaultValueType.ARRAY_FILES:
-                # Handle files type
-                return self
-            raise DefaultValueTypeError(f"Unsupported type: {self.type}")
-
-        # Handle string input cases
-        if isinstance(self.value, str) and self.type != DefaultValueType.STRING:
-            self.value = validator["converter"](self.value)
-
-        # Validate base type
-        if not isinstance(self.value, validator["type"]):
-            raise DefaultValueTypeError(f"Value must be {validator['type'].__name__} type for {self.value}")
-
-        # Validate array element types
-        if validator["type"] == list and not self._validate_array(self.value, validator["element_type"]):
-            raise DefaultValueTypeError(f"All elements must be {validator['element_type'].__name__} for {self.value}")
-
-        return self
-
-
-class BaseNodeData(ABC, BaseModel):
-    title: str
-    desc: str | None = None
-    version: str = "1"
-    error_strategy: ErrorStrategy | None = None
-    default_value: list[DefaultValue] | None = None
-    retry_config: RetryConfig = RetryConfig()
-
-    @property
-    def default_value_dict(self) -> dict[str, Any]:
-        if self.default_value:
-            return {item.key: item.value for item in self.default_value}
-        return {}
-
-
 class BaseIterationNodeData(BaseNodeData):
     start_node_id: str | None = None
 

api/dify_graph/nodes/base/node.py

@@ -11,7 +11,9 @@ from types import MappingProxyType
 from typing import Any, ClassVar, Generic, Protocol, TypeVar, cast, get_args, get_origin
 from uuid import uuid4
 
-from dify_graph.entities import AgentNodeStrategyInit, GraphInitParams
+from dify_graph.entities import GraphInitParams
+from dify_graph.entities.base_node_data import BaseNodeData, RetryConfig
+from dify_graph.entities.graph_config import NodeConfigDict
 from dify_graph.entities.graph_init_params import DIFY_RUN_CONTEXT_KEY
 from dify_graph.enums import (
     ErrorStrategy,
@@ -62,8 +64,6 @@ from dify_graph.node_events import (
 from dify_graph.runtime import GraphRuntimeState
 from libs.datetime_utils import naive_utc_now
 
-from .entities import BaseNodeData, RetryConfig
-
 NodeDataT = TypeVar("NodeDataT", bound=BaseNodeData)
 _MISSING_RUN_CONTEXT_VALUE = object()
 
@@ -153,11 +153,11 @@ class Node(Generic[NodeDataT]):
         Later, in __init__:
         ::
 
-            config["data"] ──► _hydrate_node_data() ──► _node_data_type.model_validate()
-                                                                │
-                                                                ▼
-                                                        CodeNodeData instance
-                                                        (stored in self._node_data)
+            config["data"] ──► _node_data_type.model_validate(..., from_attributes=True)
+                                               │
+                                               ▼
+                                       CodeNodeData instance
+                                       (stored in self._node_data)
 
         Example:
             class CodeNode(Node[CodeNodeData]):  # CodeNodeData is auto-extracted
@@ -241,7 +241,7 @@ class Node(Generic[NodeDataT]):
     def __init__(
         self,
         id: str,
-        config: Mapping[str, Any],
+        config: NodeConfigDict,
         graph_init_params: GraphInitParams,
         graph_runtime_state: GraphRuntimeState,
     ) -> None:
@@ -254,22 +254,21 @@ class Node(Generic[NodeDataT]):
         self.graph_runtime_state = graph_runtime_state
         self.state: NodeState = NodeState.UNKNOWN  # node execution state
 
-        node_id = config.get("id")
-        if not node_id:
-            raise ValueError("Node ID is required.")
+        node_id = config["id"]
 
         self._node_id = node_id
         self._node_execution_id: str = ""
         self._start_at = naive_utc_now()
 
-        raw_node_data = config.get("data") or {}
-        if not isinstance(raw_node_data, Mapping):
-            raise ValueError("Node config data must be a mapping.")
-
-        self._node_data: NodeDataT = self._hydrate_node_data(raw_node_data)
+        self._node_data = self.validate_node_data(config["data"])
 
         self.post_init()
 
+    @classmethod
+    def validate_node_data(cls, node_data: BaseNodeData) -> NodeDataT:
+        """Validate shared graph node payloads against the subclass-declared NodeData model."""
+        return cast(NodeDataT, cls._node_data_type.model_validate(node_data, from_attributes=True))
+
     def post_init(self) -> None:
         """Optional hook for subclasses requiring extra initialization."""
         return
@@ -342,9 +341,6 @@ class Node(Generic[NodeDataT]):
             return None
         return str(execution_id)
 
-    def _hydrate_node_data(self, data: Mapping[str, Any]) -> NodeDataT:
-        return cast(NodeDataT, self._node_data_type.model_validate(data))
-
     @abstractmethod
     def _run(self) -> NodeRunResult | Generator[NodeEventBase, None, None]:
         """
@@ -353,6 +349,10 @@ class Node(Generic[NodeDataT]):
         """
         raise NotImplementedError
 
+    def populate_start_event(self, event: NodeRunStartedEvent) -> None:
+        """Allow subclasses to enrich the started event without cross-node imports in the base class."""
+        _ = event
+
     def run(self) -> Generator[GraphNodeEventBase, None, None]:
         execution_id = self.ensure_execution_id()
         self._start_at = naive_utc_now()
@@ -366,41 +366,10 @@ class Node(Generic[NodeDataT]):
             in_iteration_id=None,
             start_at=self._start_at,
         )
-
-        # === FIXME(-LAN-): Needs to refactor.
-        from dify_graph.nodes.tool.tool_node import ToolNode
-
-        if isinstance(self, ToolNode):
-            start_event.provider_id = getattr(self.node_data, "provider_id", "")
-            start_event.provider_type = getattr(self.node_data, "provider_type", "")
-
-        from dify_graph.nodes.datasource.datasource_node import DatasourceNode
-
-        if isinstance(self, DatasourceNode):
-            plugin_id = getattr(self.node_data, "plugin_id", "")
-            provider_name = getattr(self.node_data, "provider_name", "")
-
-            start_event.provider_id = f"{plugin_id}/{provider_name}"
-            start_event.provider_type = getattr(self.node_data, "provider_type", "")
-
-        from dify_graph.nodes.trigger_plugin.trigger_event_node import TriggerEventNode
-
-        if isinstance(self, TriggerEventNode):
-            start_event.provider_id = getattr(self.node_data, "provider_id", "")
-            start_event.provider_type = getattr(self.node_data, "provider_type", "")
-
-        from typing import cast
-
-        from dify_graph.nodes.agent.agent_node import AgentNode
-        from dify_graph.nodes.agent.entities import AgentNodeData
-
-        if isinstance(self, AgentNode):
-            start_event.agent_strategy = AgentNodeStrategyInit(
-                name=cast(AgentNodeData, self.node_data).agent_strategy_name,
-                icon=self.agent_strategy_icon,
-            )
-
-        # ===
+        try:
+            self.populate_start_event(start_event)
+        except Exception:
+            logger.warning("Failed to populate start event for node %s", self._node_id, exc_info=True)
         yield start_event
 
         try:
@@ -442,7 +411,7 @@ class Node(Generic[NodeDataT]):
         cls,
         *,
         graph_config: Mapping[str, Any],
-        config: Mapping[str, Any],
+        config: NodeConfigDict,
     ) -> Mapping[str, Sequence[str]]:
         """Extracts references variable selectors from node configuration.
 
@@ -480,13 +449,12 @@ class Node(Generic[NodeDataT]):
         :param config: node config
         :return:
         """
-        node_id = config.get("id")
-        if not node_id:
-            raise ValueError("Node ID is required when extracting variable selector to variable mapping.")
-
-        # Pass raw dict data instead of creating NodeData instance
+        node_id = config["id"]
+        node_data = cls.validate_node_data(config["data"])
         data = cls._extract_variable_selector_to_variable_mapping(
-            graph_config=graph_config, node_id=node_id, node_data=config.get("data", {})
+            graph_config=graph_config,
+            node_id=node_id,
+            node_data=node_data,
         )
         return data
 
@@ -496,7 +464,7 @@ class Node(Generic[NodeDataT]):
         *,
         graph_config: Mapping[str, Any],
         node_id: str,
-        node_data: Mapping[str, Any],
+        node_data: NodeDataT,
     ) -> Mapping[str, Sequence[str]]:
         return {}
 
@@ -520,10 +488,8 @@ class Node(Generic[NodeDataT]):
     @abstractmethod
     def version(cls) -> str:
         """`node_version` returns the version of current node type."""
-        # NOTE(QuantumGhost): This should be in sync with `NODE_TYPE_CLASSES_MAPPING`.
-        #
-        # If you have introduced a new node type, please add it to `NODE_TYPE_CLASSES_MAPPING`
-        # in `api/dify_graph/nodes/__init__.py`.
+        # NOTE(QuantumGhost): Node versions must remain unique per `NodeType` so
+        # `Node.get_node_type_classes_mapping()` can resolve numeric versions and `latest`.
         raise NotImplementedError("subclasses of BaseNode must implement `version` method.")
 
     @classmethod
@@ -531,7 +497,9 @@ class Node(Generic[NodeDataT]):
         """Return mapping of NodeType -> {version -> Node subclass} using __init_subclass__ registry.
 
         Import all modules under dify_graph.nodes so subclasses register themselves on import.
-        Then we return a readonly view of the registry to avoid accidental mutation.
+        Callers that rely on workflow-local nodes defined outside `dify_graph.nodes` must import
+        those modules before invoking this method so they can register through `__init_subclass__`.
+        We then return a readonly view of the registry to avoid accidental mutation.
         """
         # Import all node modules to ensure they are loaded (thus registered)
         import dify_graph.nodes as _nodes_pkg

api/dify_graph/nodes/code/code_node.py

@@ -3,6 +3,7 @@ from decimal import Decimal
 from textwrap import dedent
 from typing import TYPE_CHECKING, Any, Protocol, cast
 
+from dify_graph.entities.graph_config import NodeConfigDict
 from dify_graph.enums import NodeType, WorkflowNodeExecutionStatus
 from dify_graph.node_events import NodeRunResult
 from dify_graph.nodes.base.node import Node
@@ -77,7 +78,7 @@ class CodeNode(Node[CodeNodeData]):
     def __init__(
         self,
         id: str,
-        config: Mapping[str, Any],
+        config: NodeConfigDict,
         graph_init_params: "GraphInitParams",
         graph_runtime_state: "GraphRuntimeState",
         *,
@@ -466,15 +467,12 @@ class CodeNode(Node[CodeNodeData]):
         *,
         graph_config: Mapping[str, Any],
         node_id: str,
-        node_data: Mapping[str, Any],
+        node_data: CodeNodeData,
     ) -> Mapping[str, Sequence[str]]:
         _ = graph_config  # Explicitly mark as unused
-        # Create typed NodeData from dict
-        typed_node_data = CodeNodeData.model_validate(node_data)
-
         return {
             node_id + "." + variable_selector.variable: variable_selector.value_selector
-            for variable_selector in typed_node_data.variables
+            for variable_selector in node_data.variables
         }
 
     @property

api/dify_graph/nodes/code/entities.py

@@ -3,7 +3,8 @@ from typing import Annotated, Literal
 
 from pydantic import AfterValidator, BaseModel
 
-from dify_graph.nodes.base import BaseNodeData
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.enums import NodeType
 from dify_graph.nodes.base.entities import VariableSelector
 from dify_graph.variables.types import SegmentType
 
@@ -39,6 +40,8 @@ class CodeNodeData(BaseNodeData):
     Code Node Data.
     """
 
+    type: NodeType = NodeType.CODE
+
     class Output(BaseModel):
         type: Annotated[SegmentType, AfterValidator(_validate_type)]
         children: dict[str, "CodeNodeData.Output"] | None = None

api/dify_graph/nodes/datasource/datasource_node.py

@@ -3,6 +3,7 @@ from typing import TYPE_CHECKING, Any
 
 from core.datasource.entities.datasource_entities import DatasourceProviderType
 from core.plugin.impl.exc import PluginDaemonClientSideError
+from dify_graph.entities.graph_config import NodeConfigDict
 from dify_graph.entities.workflow_node_execution import WorkflowNodeExecutionStatus
 from dify_graph.enums import NodeExecutionType, NodeType, SystemVariableKey
 from dify_graph.node_events import NodeRunResult, StreamCompletedEvent
@@ -34,7 +35,7 @@ class DatasourceNode(Node[DatasourceNodeData]):
     def __init__(
         self,
         id: str,
-        config: Mapping[str, Any],
+        config: NodeConfigDict,
         graph_init_params: "GraphInitParams",
         graph_runtime_state: "GraphRuntimeState",
         datasource_manager: DatasourceManagerProtocol,
@@ -47,6 +48,10 @@ class DatasourceNode(Node[DatasourceNodeData]):
         )
         self.datasource_manager = datasource_manager
 
+    def populate_start_event(self, event) -> None:
+        event.provider_id = f"{self.node_data.plugin_id}/{self.node_data.provider_name}"
+        event.provider_type = self.node_data.provider_type
+
     def _run(self) -> Generator:
         """
         Run the datasource node
@@ -181,7 +186,7 @@ class DatasourceNode(Node[DatasourceNodeData]):
         *,
         graph_config: Mapping[str, Any],
         node_id: str,
-        node_data: Mapping[str, Any],
+        node_data: DatasourceNodeData,
     ) -> Mapping[str, Sequence[str]]:
         """
         Extract variable selector to variable mapping
@@ -190,11 +195,10 @@ class DatasourceNode(Node[DatasourceNodeData]):
         :param node_data: node data
         :return:
         """
-        typed_node_data = DatasourceNodeData.model_validate(node_data)
         result = {}
-        if typed_node_data.datasource_parameters:
-            for parameter_name in typed_node_data.datasource_parameters:
-                input = typed_node_data.datasource_parameters[parameter_name]
+        if node_data.datasource_parameters:
+            for parameter_name in node_data.datasource_parameters:
+                input = node_data.datasource_parameters[parameter_name]
                 match input.type:
                     case "mixed":
                         assert isinstance(input.value, str)

api/dify_graph/nodes/datasource/entities.py

@@ -3,7 +3,8 @@ from typing import Any, Literal, Union
 from pydantic import BaseModel, field_validator
 from pydantic_core.core_schema import ValidationInfo
 
-from dify_graph.nodes.base.entities import BaseNodeData
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.enums import NodeType
 
 
 class DatasourceEntity(BaseModel):
@@ -16,6 +17,8 @@ class DatasourceEntity(BaseModel):
 
 
 class DatasourceNodeData(BaseNodeData, DatasourceEntity):
+    type: NodeType = NodeType.DATASOURCE
+
     class DatasourceInput(BaseModel):
         # TODO: check this type
         value: Union[Any, list[str]]

api/dify_graph/nodes/document_extractor/entities.py

@@ -1,10 +1,12 @@
 from collections.abc import Sequence
 from dataclasses import dataclass
 
-from dify_graph.nodes.base import BaseNodeData
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.enums import NodeType
 
 
 class DocumentExtractorNodeData(BaseNodeData):
+    type: NodeType = NodeType.DOCUMENT_EXTRACTOR
     variable_selector: Sequence[str]
 
 

api/dify_graph/nodes/document_extractor/node.py

@@ -21,6 +21,7 @@ from docx.oxml.text.paragraph import CT_P
 from docx.table import Table
 from docx.text.paragraph import Paragraph
 
+from dify_graph.entities.graph_config import NodeConfigDict
 from dify_graph.enums import NodeType, WorkflowNodeExecutionStatus
 from dify_graph.file import File, FileTransferMethod, file_manager
 from dify_graph.node_events import NodeRunResult
@@ -54,7 +55,7 @@ class DocumentExtractorNode(Node[DocumentExtractorNodeData]):
     def __init__(
         self,
         id: str,
-        config: Mapping[str, Any],
+        config: NodeConfigDict,
         graph_init_params: "GraphInitParams",
         graph_runtime_state: "GraphRuntimeState",
         *,
@@ -136,12 +137,10 @@ class DocumentExtractorNode(Node[DocumentExtractorNodeData]):
         *,
         graph_config: Mapping[str, Any],
         node_id: str,
-        node_data: Mapping[str, Any],
+        node_data: DocumentExtractorNodeData,
     ) -> Mapping[str, Sequence[str]]:
-        # Create typed NodeData from dict
-        typed_node_data = DocumentExtractorNodeData.model_validate(node_data)
-
-        return {node_id + ".files": typed_node_data.variable_selector}
+        _ = graph_config  # Explicitly mark as unused
+        return {node_id + ".files": node_data.variable_selector}
 
 
 def _extract_text_by_mime_type(

api/dify_graph/nodes/end/entities.py

@@ -1,6 +1,8 @@
 from pydantic import BaseModel, Field
 
-from dify_graph.nodes.base.entities import BaseNodeData, OutputVariableEntity
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.enums import NodeType
+from dify_graph.nodes.base.entities import OutputVariableEntity
 
 
 class EndNodeData(BaseNodeData):
@@ -8,6 +10,7 @@ class EndNodeData(BaseNodeData):
     END Node Data.
     """
 
+    type: NodeType = NodeType.END
     outputs: list[OutputVariableEntity]
 
 

api/dify_graph/nodes/http_request/entities.py

@@ -8,7 +8,8 @@ import charset_normalizer
 import httpx
 from pydantic import BaseModel, Field, ValidationInfo, field_validator
 
-from dify_graph.nodes.base import BaseNodeData
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.enums import NodeType
 
 HTTP_REQUEST_CONFIG_FILTER_KEY = "http_request_config"
 
@@ -89,6 +90,7 @@ class HttpRequestNodeData(BaseNodeData):
     Code Node Data.
     """
 
+    type: NodeType = NodeType.HTTP_REQUEST
     method: Literal[
         "get",
         "post",

api/dify_graph/nodes/http_request/node.py

@@ -3,6 +3,7 @@ import mimetypes
 from collections.abc import Callable, Mapping, Sequence
 from typing import TYPE_CHECKING, Any
 
+from dify_graph.entities.graph_config import NodeConfigDict
 from dify_graph.enums import NodeType, WorkflowNodeExecutionStatus
 from dify_graph.file import File, FileTransferMethod
 from dify_graph.node_events import NodeRunResult
@@ -37,7 +38,7 @@ class HttpRequestNode(Node[HttpRequestNodeData]):
     def __init__(
         self,
         id: str,
-        config: Mapping[str, Any],
+        config: NodeConfigDict,
         graph_init_params: "GraphInitParams",
         graph_runtime_state: "GraphRuntimeState",
         *,
@@ -163,18 +164,15 @@ class HttpRequestNode(Node[HttpRequestNodeData]):
         *,
         graph_config: Mapping[str, Any],
         node_id: str,
-        node_data: Mapping[str, Any],
+        node_data: HttpRequestNodeData,
     ) -> Mapping[str, Sequence[str]]:
-        # Create typed NodeData from dict
-        typed_node_data = HttpRequestNodeData.model_validate(node_data)
-
         selectors: list[VariableSelector] = []
-        selectors += variable_template_parser.extract_selectors_from_template(typed_node_data.url)
-        selectors += variable_template_parser.extract_selectors_from_template(typed_node_data.headers)
-        selectors += variable_template_parser.extract_selectors_from_template(typed_node_data.params)
-        if typed_node_data.body:
-            body_type = typed_node_data.body.type
-            data = typed_node_data.body.data
+        selectors += variable_template_parser.extract_selectors_from_template(node_data.url)
+        selectors += variable_template_parser.extract_selectors_from_template(node_data.headers)
+        selectors += variable_template_parser.extract_selectors_from_template(node_data.params)
+        if node_data.body:
+            body_type = node_data.body.type
+            data = node_data.body.data
             match body_type:
                 case "none":
                     pass

api/dify_graph/nodes/human_input/entities.py

@@ -10,7 +10,8 @@ from typing import Annotated, Any, ClassVar, Literal, Self
 
 from pydantic import BaseModel, Field, field_validator, model_validator
 
-from dify_graph.nodes.base import BaseNodeData
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.enums import NodeType
 from dify_graph.nodes.base.variable_template_parser import VariableTemplateParser
 from dify_graph.runtime import VariablePool
 from dify_graph.variables.consts import SELECTORS_LENGTH
@@ -71,8 +72,8 @@ class EmailDeliveryConfig(BaseModel):
     body: str
     debug_mode: bool = False
 
-    def with_debug_recipient(self, user_id: str) -> "EmailDeliveryConfig":
-        if not user_id:
+    def with_debug_recipient(self, user_id: str | None) -> "EmailDeliveryConfig":
+        if user_id is None:
             debug_recipients = EmailRecipients(whole_workspace=False, items=[])
             return self.model_copy(update={"recipients": debug_recipients})
         debug_recipients = EmailRecipients(whole_workspace=False, items=[MemberRecipient(user_id=user_id)])
@@ -140,7 +141,7 @@ def apply_debug_email_recipient(
     method: DeliveryChannelConfig,
     *,
     enabled: bool,
-    user_id: str,
+    user_id: str | None,
 ) -> DeliveryChannelConfig:
     if not enabled:
         return method
@@ -148,7 +149,7 @@ def apply_debug_email_recipient(
         return method
     if not method.config.debug_mode:
         return method
-    debug_config = method.config.with_debug_recipient(user_id or "")
+    debug_config = method.config.with_debug_recipient(user_id)
     return method.model_copy(update={"config": debug_config})
 
 
@@ -214,6 +215,7 @@ class UserAction(BaseModel):
 class HumanInputNodeData(BaseNodeData):
     """Human Input node data."""
 
+    type: NodeType = NodeType.HUMAN_INPUT
     delivery_methods: list[DeliveryChannelConfig] = Field(default_factory=list)
     form_content: str = ""
     inputs: list[FormInput] = Field(default_factory=list)

api/dify_graph/nodes/human_input/human_input_node.py

@@ -3,6 +3,7 @@ import logging
 from collections.abc import Generator, Mapping, Sequence
 from typing import TYPE_CHECKING, Any
 
+from dify_graph.entities.graph_config import NodeConfigDict
 from dify_graph.entities.pause_reason import HumanInputRequired
 from dify_graph.enums import NodeExecutionType, NodeType, WorkflowNodeExecutionStatus
 from dify_graph.node_events import (
@@ -63,7 +64,7 @@ class HumanInputNode(Node[HumanInputNodeData]):
     def __init__(
         self,
         id: str,
-        config: Mapping[str, Any],
+        config: NodeConfigDict,
         graph_init_params: "GraphInitParams",
         graph_runtime_state: "GraphRuntimeState",
         form_repository: HumanInputFormRepository,
@@ -348,7 +349,7 @@ class HumanInputNode(Node[HumanInputNodeData]):
         *,
         graph_config: Mapping[str, Any],
         node_id: str,
-        node_data: Mapping[str, Any],
+        node_data: HumanInputNodeData,
     ) -> Mapping[str, Sequence[str]]:
         """
         Extract variable selectors referenced in form content and input default values.
@@ -357,5 +358,4 @@ class HumanInputNode(Node[HumanInputNodeData]):
         1. Variables referenced in form_content ({{#node_name.var_name#}})
         2. Variables referenced in input default values
         """
-        validated_node_data = HumanInputNodeData.model_validate(node_data)
-        return validated_node_data.extract_variable_selector_to_variable_mapping(node_id)
+        return node_data.extract_variable_selector_to_variable_mapping(node_id)

api/dify_graph/nodes/if_else/entities.py

@@ -2,7 +2,8 @@ from typing import Literal
 
 from pydantic import BaseModel, Field
 
-from dify_graph.nodes.base import BaseNodeData
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.enums import NodeType
 from dify_graph.utils.condition.entities import Condition
 
 
@@ -11,6 +12,8 @@ class IfElseNodeData(BaseNodeData):
     If Else Node Data.
     """
 
+    type: NodeType = NodeType.IF_ELSE
+
     class Case(BaseModel):
         """
         Case entity representing a single logical condition group

api/dify_graph/nodes/if_else/if_else_node.py

@@ -97,13 +97,11 @@ class IfElseNode(Node[IfElseNodeData]):
         *,
         graph_config: Mapping[str, Any],
         node_id: str,
-        node_data: Mapping[str, Any],
+        node_data: IfElseNodeData,
     ) -> Mapping[str, Sequence[str]]:
-        # Create typed NodeData from dict
-        typed_node_data = IfElseNodeData.model_validate(node_data)
-
         var_mapping: dict[str, list[str]] = {}
-        for case in typed_node_data.cases or []:
+        _ = graph_config  # Explicitly mark as unused
+        for case in node_data.cases or []:
             for condition in case.conditions:
                 key = f"{node_id}.#{'.'.join(condition.variable_selector)}#"
                 var_mapping[key] = condition.variable_selector

api/dify_graph/nodes/iteration/entities.py

@@ -3,7 +3,9 @@ from typing import Any
 
 from pydantic import Field
 
-from dify_graph.nodes.base import BaseIterationNodeData, BaseIterationState, BaseNodeData
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.enums import NodeType
+from dify_graph.nodes.base import BaseIterationNodeData, BaseIterationState
 
 
 class ErrorHandleMode(StrEnum):
@@ -17,6 +19,7 @@ class IterationNodeData(BaseIterationNodeData):
     Iteration Node Data.
     """
 
+    type: NodeType = NodeType.ITERATION
     parent_loop_id: str | None = None  # redundant field, not used currently
     iterator_selector: list[str]  # variable selector
     output_selector: list[str]  # output selector
@@ -31,7 +34,7 @@ class IterationStartNodeData(BaseNodeData):
     Iteration Start Node Data.
     """
 
-    pass
+    type: NodeType = NodeType.ITERATION_START
 
 
 class IterationState(BaseIterationState):

api/dify_graph/nodes/iteration/iteration_node.py

@@ -7,6 +7,7 @@ from typing import TYPE_CHECKING, Any, NewType, cast
 from typing_extensions import TypeIs
 
 from dify_graph.constants import CONVERSATION_VARIABLE_NODE_ID
+from dify_graph.entities.graph_config import NodeConfigDictAdapter
 from dify_graph.enums import (
     NodeExecutionType,
     NodeType,
@@ -460,21 +461,18 @@ class IterationNode(LLMUsageTrackingMixin, Node[IterationNodeData]):
         *,
         graph_config: Mapping[str, Any],
         node_id: str,
-        node_data: Mapping[str, Any],
+        node_data: IterationNodeData,
     ) -> Mapping[str, Sequence[str]]:
-        # Create typed NodeData from dict
-        typed_node_data = IterationNodeData.model_validate(node_data)
-
         variable_mapping: dict[str, Sequence[str]] = {
-            f"{node_id}.input_selector": typed_node_data.iterator_selector,
+            f"{node_id}.input_selector": node_data.iterator_selector,
         }
         iteration_node_ids = set()
 
         # Find all nodes that belong to this loop
         nodes = graph_config.get("nodes", [])
         for node in nodes:
-            node_data = node.get("data", {})
-            if node_data.get("iteration_id") == node_id:
+            node_config_data = node.get("data", {})
+            if node_config_data.get("iteration_id") == node_id:
                 in_iteration_node_id = node.get("id")
                 if in_iteration_node_id:
                     iteration_node_ids.add(in_iteration_node_id)
@@ -488,16 +486,18 @@ class IterationNode(LLMUsageTrackingMixin, Node[IterationNodeData]):
             # variable selector to variable mapping
             try:
                 # Get node class
-                from dify_graph.nodes.node_mapping import NODE_TYPE_CLASSES_MAPPING
+                from dify_graph.nodes.node_mapping import get_node_type_classes_mapping
 
-                node_type = NodeType(sub_node_config.get("data", {}).get("type"))
-                if node_type not in NODE_TYPE_CLASSES_MAPPING:
+                typed_sub_node_config = NodeConfigDictAdapter.validate_python(sub_node_config)
+                node_type = typed_sub_node_config["data"].type
+                node_mapping = get_node_type_classes_mapping()
+                if node_type not in node_mapping:
                     continue
-                node_version = sub_node_config.get("data", {}).get("version", "1")
-                node_cls = NODE_TYPE_CLASSES_MAPPING[node_type][node_version]
+                node_version = str(typed_sub_node_config["data"].version)
+                node_cls = node_mapping[node_type][node_version]
 
                 sub_node_variable_mapping = node_cls.extract_variable_selector_to_variable_mapping(
-                    graph_config=graph_config, config=sub_node_config
+                    graph_config=graph_config, config=typed_sub_node_config
                 )
                 sub_node_variable_mapping = cast(dict[str, Sequence[str]], sub_node_variable_mapping)
             except NotImplementedError:

api/dify_graph/nodes/knowledge_index/entities.py

@@ -3,7 +3,8 @@ from typing import Literal, Union
 from pydantic import BaseModel
 
 from core.rag.retrieval.retrieval_methods import RetrievalMethod
-from dify_graph.nodes.base import BaseNodeData
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.enums import NodeType
 
 
 class RerankingModelConfig(BaseModel):
@@ -155,7 +156,7 @@ class KnowledgeIndexNodeData(BaseNodeData):
     Knowledge index Node Data.
     """
 
-    type: str = "knowledge-index"
+    type: NodeType = NodeType.KNOWLEDGE_INDEX
     chunk_structure: str
     index_chunk_variable_selector: list[str]
     indexing_technique: str | None = None

api/dify_graph/nodes/knowledge_index/knowledge_index_node.py

@@ -2,6 +2,7 @@ import logging
 from collections.abc import Mapping
 from typing import TYPE_CHECKING, Any
 
+from dify_graph.entities.graph_config import NodeConfigDict
 from dify_graph.entities.workflow_node_execution import WorkflowNodeExecutionStatus
 from dify_graph.enums import NodeExecutionType, NodeType, SystemVariableKey
 from dify_graph.node_events import NodeRunResult
@@ -30,7 +31,7 @@ class KnowledgeIndexNode(Node[KnowledgeIndexNodeData]):
     def __init__(
         self,
         id: str,
-        config: Mapping[str, Any],
+        config: NodeConfigDict,
         graph_init_params: "GraphInitParams",
         graph_runtime_state: "GraphRuntimeState",
         index_processor: IndexProcessorProtocol,

api/dify_graph/nodes/knowledge_retrieval/entities.py

@@ -3,7 +3,8 @@ from typing import Literal
 
 from pydantic import BaseModel, Field
 
-from dify_graph.nodes.base import BaseNodeData
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.enums import NodeType
 from dify_graph.nodes.llm.entities import ModelConfig, VisionConfig
 
 
@@ -113,7 +114,7 @@ class KnowledgeRetrievalNodeData(BaseNodeData):
     Knowledge retrieval Node Data.
     """
 
-    type: str = "knowledge-retrieval"
+    type: NodeType = NodeType.KNOWLEDGE_RETRIEVAL
     query_variable_selector: list[str] | None | str = None
     query_attachment_selector: list[str] | None | str = None
     dataset_ids: list[str]

api/dify_graph/nodes/knowledge_retrieval/knowledge_retrieval_node.py

@@ -4,6 +4,7 @@ from typing import TYPE_CHECKING, Any, Literal
 
 from core.app.app_config.entities import DatasetRetrieveConfigEntity
 from dify_graph.entities import GraphInitParams
+from dify_graph.entities.graph_config import NodeConfigDict
 from dify_graph.enums import (
     NodeType,
     WorkflowNodeExecutionMetadataKey,
@@ -49,7 +50,7 @@ class KnowledgeRetrievalNode(LLMUsageTrackingMixin, Node[KnowledgeRetrievalNodeD
     def __init__(
         self,
         id: str,
-        config: Mapping[str, Any],
+        config: NodeConfigDict,
         graph_init_params: "GraphInitParams",
         graph_runtime_state: "GraphRuntimeState",
         rag_retrieval: RAGRetrievalProtocol,
@@ -301,15 +302,12 @@ class KnowledgeRetrievalNode(LLMUsageTrackingMixin, Node[KnowledgeRetrievalNodeD
         *,
         graph_config: Mapping[str, Any],
         node_id: str,
-        node_data: Mapping[str, Any],
+        node_data: KnowledgeRetrievalNodeData,
     ) -> Mapping[str, Sequence[str]]:
         # graph_config is not used in this node type
-        # Create typed NodeData from dict
-        typed_node_data = KnowledgeRetrievalNodeData.model_validate(node_data)
-
         variable_mapping = {}
-        if typed_node_data.query_variable_selector:
-            variable_mapping[node_id + ".query"] = typed_node_data.query_variable_selector
-        if typed_node_data.query_attachment_selector:
-            variable_mapping[node_id + ".queryAttachment"] = typed_node_data.query_attachment_selector
+        if node_data.query_variable_selector:
+            variable_mapping[node_id + ".query"] = node_data.query_variable_selector
+        if node_data.query_attachment_selector:
+            variable_mapping[node_id + ".queryAttachment"] = node_data.query_attachment_selector
         return variable_mapping

api/dify_graph/nodes/list_operator/entities.py

@@ -3,7 +3,8 @@ from enum import StrEnum
 
 from pydantic import BaseModel, Field
 
-from dify_graph.nodes.base import BaseNodeData
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.enums import NodeType
 
 
 class FilterOperator(StrEnum):
@@ -62,6 +63,7 @@ class ExtractConfig(BaseModel):
 
 
 class ListOperatorNodeData(BaseNodeData):
+    type: NodeType = NodeType.LIST_OPERATOR
     variable: Sequence[str] = Field(default_factory=list)
     filter_by: FilterBy
     order_by: OrderByConfig

api/dify_graph/nodes/llm/entities.py

@@ -4,8 +4,9 @@ from typing import Any, Literal
 from pydantic import BaseModel, Field, field_validator
 
 from core.prompt.entities.advanced_prompt_entities import ChatModelMessage, CompletionModelPromptTemplate, MemoryConfig
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.enums import NodeType
 from dify_graph.model_runtime.entities import ImagePromptMessageContent, LLMMode
-from dify_graph.nodes.base import BaseNodeData
 from dify_graph.nodes.base.entities import VariableSelector
 
 
@@ -59,6 +60,7 @@ class LLMNodeCompletionModelPromptTemplate(CompletionModelPromptTemplate):
 
 
 class LLMNodeData(BaseNodeData):
+    type: NodeType = NodeType.LLM
     model: ModelConfig
     prompt_template: Sequence[LLMNodeChatModelMessage] | LLMNodeCompletionModelPromptTemplate
     prompt_config: PromptConfig = Field(default_factory=PromptConfig)

api/dify_graph/nodes/llm/node.py

@@ -21,6 +21,7 @@ from core.rag.entities.citation_metadata import RetrievalSourceMetadata
 from core.tools.signature import sign_upload_file
 from dify_graph.constants import SYSTEM_VARIABLE_NODE_ID
 from dify_graph.entities import GraphInitParams
+from dify_graph.entities.graph_config import NodeConfigDict
 from dify_graph.enums import (
     NodeType,
     SystemVariableKey,
@@ -121,7 +122,7 @@ class LLMNode(Node[LLMNodeData]):
     def __init__(
         self,
         id: str,
-        config: Mapping[str, Any],
+        config: NodeConfigDict,
         graph_init_params: GraphInitParams,
         graph_runtime_state: GraphRuntimeState,
         *,
@@ -954,14 +955,11 @@ class LLMNode(Node[LLMNodeData]):
         *,
         graph_config: Mapping[str, Any],
         node_id: str,
-        node_data: Mapping[str, Any],
+        node_data: LLMNodeData,
     ) -> Mapping[str, Sequence[str]]:
         # graph_config is not used in this node type
         _ = graph_config  # Explicitly mark as unused
-        # Create typed NodeData from dict
-        typed_node_data = LLMNodeData.model_validate(node_data)
-
-        prompt_template = typed_node_data.prompt_template
+        prompt_template = node_data.prompt_template
         variable_selectors = []
         if isinstance(prompt_template, list):
             for prompt in prompt_template:
@@ -979,7 +977,7 @@ class LLMNode(Node[LLMNodeData]):
         for variable_selector in variable_selectors:
             variable_mapping[variable_selector.variable] = variable_selector.value_selector
 
-        memory = typed_node_data.memory
+        memory = node_data.memory
         if memory and memory.query_prompt_template:
             query_variable_selectors = VariableTemplateParser(
                 template=memory.query_prompt_template
@@ -987,16 +985,16 @@ class LLMNode(Node[LLMNodeData]):
             for variable_selector in query_variable_selectors:
                 variable_mapping[variable_selector.variable] = variable_selector.value_selector
 
-        if typed_node_data.context.enabled:
-            variable_mapping["#context#"] = typed_node_data.context.variable_selector
+        if node_data.context.enabled:
+            variable_mapping["#context#"] = node_data.context.variable_selector
 
-        if typed_node_data.vision.enabled:
-            variable_mapping["#files#"] = typed_node_data.vision.configs.variable_selector
+        if node_data.vision.enabled:
+            variable_mapping["#files#"] = node_data.vision.configs.variable_selector
 
-        if typed_node_data.memory:
+        if node_data.memory:
             variable_mapping["#sys.query#"] = ["sys", SystemVariableKey.QUERY]
 
-        if typed_node_data.prompt_config:
+        if node_data.prompt_config:
             enable_jinja = False
 
             if isinstance(prompt_template, LLMNodeCompletionModelPromptTemplate):
@@ -1009,7 +1007,7 @@ class LLMNode(Node[LLMNodeData]):
                         break
 
             if enable_jinja:
-                for variable_selector in typed_node_data.prompt_config.jinja2_variables or []:
+                for variable_selector in node_data.prompt_config.jinja2_variables or []:
                     variable_mapping[variable_selector.variable] = variable_selector.value_selector
 
         variable_mapping = {node_id + "." + key: value for key, value in variable_mapping.items()}

api/dify_graph/nodes/loop/entities.py

@@ -3,7 +3,9 @@ from typing import Annotated, Any, Literal
 
 from pydantic import AfterValidator, BaseModel, Field, field_validator
 
-from dify_graph.nodes.base import BaseLoopNodeData, BaseLoopState, BaseNodeData
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.enums import NodeType
+from dify_graph.nodes.base import BaseLoopNodeData, BaseLoopState
 from dify_graph.utils.condition.entities import Condition
 from dify_graph.variables.types import SegmentType
 
@@ -39,6 +41,7 @@ class LoopVariableData(BaseModel):
 
 
 class LoopNodeData(BaseLoopNodeData):
+    type: NodeType = NodeType.LOOP
     loop_count: int  # Maximum number of loops
     break_conditions: list[Condition]  # Conditions to break the loop
     logical_operator: Literal["and", "or"]
@@ -58,7 +61,7 @@ class LoopStartNodeData(BaseNodeData):
     Loop Start Node Data.
     """
 
-    pass
+    type: NodeType = NodeType.LOOP_START
 
 
 class LoopEndNodeData(BaseNodeData):
@@ -66,7 +69,7 @@ class LoopEndNodeData(BaseNodeData):
     Loop End Node Data.
     """
 
-    pass
+    type: NodeType = NodeType.LOOP_END
 
 
 class LoopState(BaseLoopState):

api/dify_graph/nodes/loop/loop_node.py

@@ -5,6 +5,7 @@ from collections.abc import Callable, Generator, Mapping, Sequence
 from datetime import datetime
 from typing import TYPE_CHECKING, Any, Literal, cast
 
+from dify_graph.entities.graph_config import NodeConfigDictAdapter
 from dify_graph.enums import (
     NodeExecutionType,
     NodeType,
@@ -298,11 +299,8 @@ class LoopNode(LLMUsageTrackingMixin, Node[LoopNodeData]):
         *,
         graph_config: Mapping[str, Any],
         node_id: str,
-        node_data: Mapping[str, Any],
+        node_data: LoopNodeData,
     ) -> Mapping[str, Sequence[str]]:
-        # Create typed NodeData from dict
-        typed_node_data = LoopNodeData.model_validate(node_data)
-
         variable_mapping = {}
 
         # Extract loop node IDs statically from graph_config
@@ -318,16 +316,18 @@ class LoopNode(LLMUsageTrackingMixin, Node[LoopNodeData]):
             # variable selector to variable mapping
             try:
                 # Get node class
-                from dify_graph.nodes.node_mapping import NODE_TYPE_CLASSES_MAPPING
+                from dify_graph.nodes.node_mapping import get_node_type_classes_mapping
 
-                node_type = NodeType(sub_node_config.get("data", {}).get("type"))
-                if node_type not in NODE_TYPE_CLASSES_MAPPING:
+                typed_sub_node_config = NodeConfigDictAdapter.validate_python(sub_node_config)
+                node_type = typed_sub_node_config["data"].type
+                node_mapping = get_node_type_classes_mapping()
+                if node_type not in node_mapping:
                     continue
-                node_version = sub_node_config.get("data", {}).get("version", "1")
-                node_cls = NODE_TYPE_CLASSES_MAPPING[node_type][node_version]
+                node_version = str(typed_sub_node_config["data"].version)
+                node_cls = node_mapping[node_type][node_version]
 
                 sub_node_variable_mapping = node_cls.extract_variable_selector_to_variable_mapping(
-                    graph_config=graph_config, config=sub_node_config
+                    graph_config=graph_config, config=typed_sub_node_config
                 )
                 sub_node_variable_mapping = cast(dict[str, Sequence[str]], sub_node_variable_mapping)
             except NotImplementedError:
@@ -342,7 +342,7 @@ class LoopNode(LLMUsageTrackingMixin, Node[LoopNodeData]):
 
             variable_mapping.update(sub_node_variable_mapping)
 
-        for loop_variable in typed_node_data.loop_variables or []:
+        for loop_variable in node_data.loop_variables or []:
             if loop_variable.value_type == "variable":
                 assert loop_variable.value is not None, "Loop variable value must be provided for variable type"
                 # add loop variable to variable mapping

api/dify_graph/nodes/node_mapping.py

@@ -5,5 +5,24 @@ from dify_graph.nodes.base.node import Node
 
 LATEST_VERSION = "latest"
 
-# Mapping is built by Node.get_node_type_classes_mapping(), which imports and walks dify_graph.nodes
-NODE_TYPE_CLASSES_MAPPING: Mapping[NodeType, Mapping[str, type[Node]]] = Node.get_node_type_classes_mapping()
+
+def get_node_type_classes_mapping() -> Mapping[NodeType, Mapping[str, type[Node]]]:
+    """Return the live node registry after importing all `dify_graph.nodes` modules."""
+    return Node.get_node_type_classes_mapping()
+
+
+def resolve_node_class(*, node_type: NodeType, node_version: str) -> type[Node]:
+    node_mapping = get_node_type_classes_mapping().get(node_type)
+    if not node_mapping:
+        raise ValueError(f"No class mapping found for node type: {node_type}")
+
+    latest_node_class = node_mapping.get(LATEST_VERSION)
+    matched_node_class = node_mapping.get(node_version)
+    node_class = matched_node_class or latest_node_class
+    if not node_class:
+        raise ValueError(f"No latest version class found for node type: {node_type}")
+    return node_class
+
+
+# Snapshot kept for compatibility with older tests; production paths should use the live helpers.
+NODE_TYPE_CLASSES_MAPPING: Mapping[NodeType, Mapping[str, type[Node]]] = get_node_type_classes_mapping()

api/dify_graph/nodes/parameter_extractor/entities.py

@@ -8,7 +8,8 @@ from pydantic import (
 )
 
 from core.prompt.entities.advanced_prompt_entities import MemoryConfig
-from dify_graph.nodes.base import BaseNodeData
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.enums import NodeType
 from dify_graph.nodes.llm.entities import ModelConfig, VisionConfig
 from dify_graph.variables.types import SegmentType
 
@@ -83,6 +84,7 @@ class ParameterExtractorNodeData(BaseNodeData):
     Parameter Extractor Node Data.
     """
 
+    type: NodeType = NodeType.PARAMETER_EXTRACTOR
     model: ModelConfig
     query: list[str]
     parameters: list[ParameterConfig]

api/dify_graph/nodes/parameter_extractor/parameter_extractor_node.py

@@ -10,6 +10,7 @@ from core.prompt.advanced_prompt_transform import AdvancedPromptTransform
 from core.prompt.entities.advanced_prompt_entities import ChatModelMessage, CompletionModelPromptTemplate
 from core.prompt.simple_prompt_transform import ModelMode
 from core.prompt.utils.prompt_message_util import PromptMessageUtil
+from dify_graph.entities.graph_config import NodeConfigDict
 from dify_graph.enums import (
     NodeType,
     WorkflowNodeExecutionMetadataKey,
@@ -106,7 +107,7 @@ class ParameterExtractorNode(Node[ParameterExtractorNodeData]):
     def __init__(
         self,
         id: str,
-        config: Mapping[str, Any],
+        config: NodeConfigDict,
         graph_init_params: "GraphInitParams",
         graph_runtime_state: "GraphRuntimeState",
         *,
@@ -837,15 +838,13 @@ class ParameterExtractorNode(Node[ParameterExtractorNodeData]):
         *,
         graph_config: Mapping[str, Any],
         node_id: str,
-        node_data: Mapping[str, Any],
+        node_data: ParameterExtractorNodeData,
     ) -> Mapping[str, Sequence[str]]:
-        # Create typed NodeData from dict
-        typed_node_data = ParameterExtractorNodeData.model_validate(node_data)
+        _ = graph_config  # Explicitly mark as unused
+        variable_mapping: dict[str, Sequence[str]] = {"query": node_data.query}
 
-        variable_mapping: dict[str, Sequence[str]] = {"query": typed_node_data.query}
-
-        if typed_node_data.instruction:
-            selectors = variable_template_parser.extract_selectors_from_template(typed_node_data.instruction)
+        if node_data.instruction:
+            selectors = variable_template_parser.extract_selectors_from_template(node_data.instruction)
             for selector in selectors:
                 variable_mapping[selector.variable] = selector.value_selector
 

api/dify_graph/nodes/question_classifier/entities.py

@@ -1,7 +1,8 @@
 from pydantic import BaseModel, Field
 
 from core.prompt.entities.advanced_prompt_entities import MemoryConfig
-from dify_graph.nodes.base import BaseNodeData
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.enums import NodeType
 from dify_graph.nodes.llm import ModelConfig, VisionConfig
 
 
@@ -11,6 +12,7 @@ class ClassConfig(BaseModel):
 
 
 class QuestionClassifierNodeData(BaseNodeData):
+    type: NodeType = NodeType.QUESTION_CLASSIFIER
     query_variable_selector: list[str]
     model: ModelConfig
     classes: list[ClassConfig]

api/dify_graph/nodes/question_classifier/question_classifier_node.py

@@ -7,6 +7,7 @@ from core.model_manager import ModelInstance
 from core.prompt.simple_prompt_transform import ModelMode
 from core.prompt.utils.prompt_message_util import PromptMessageUtil
 from dify_graph.entities import GraphInitParams
+from dify_graph.entities.graph_config import NodeConfigDict
 from dify_graph.enums import (
     NodeExecutionType,
     NodeType,
@@ -62,7 +63,7 @@ class QuestionClassifierNode(Node[QuestionClassifierNodeData]):
     def __init__(
         self,
         id: str,
-        config: Mapping[str, Any],
+        config: NodeConfigDict,
         graph_init_params: "GraphInitParams",
         graph_runtime_state: "GraphRuntimeState",
         *,
@@ -251,16 +252,13 @@ class QuestionClassifierNode(Node[QuestionClassifierNodeData]):
         *,
         graph_config: Mapping[str, Any],
         node_id: str,
-        node_data: Mapping[str, Any],
+        node_data: QuestionClassifierNodeData,
     ) -> Mapping[str, Sequence[str]]:
         # graph_config is not used in this node type
-        # Create typed NodeData from dict
-        typed_node_data = QuestionClassifierNodeData.model_validate(node_data)
-
-        variable_mapping = {"query": typed_node_data.query_variable_selector}
+        variable_mapping = {"query": node_data.query_variable_selector}
         variable_selectors: list[VariableSelector] = []
-        if typed_node_data.instruction:
-            variable_template_parser = VariableTemplateParser(template=typed_node_data.instruction)
+        if node_data.instruction:
+            variable_template_parser = VariableTemplateParser(template=node_data.instruction)
             variable_selectors.extend(variable_template_parser.extract_variable_selectors())
         for variable_selector in variable_selectors:
             variable_mapping[variable_selector.variable] = list(variable_selector.value_selector)

api/dify_graph/nodes/start/entities.py

@@ -2,7 +2,8 @@ from collections.abc import Sequence
 
 from pydantic import Field
 
-from dify_graph.nodes.base import BaseNodeData
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.enums import NodeType
 from dify_graph.variables.input_entities import VariableEntity
 
 
@@ -11,4 +12,5 @@ class StartNodeData(BaseNodeData):
     Start Node Data
     """
 
+    type: NodeType = NodeType.START
     variables: Sequence[VariableEntity] = Field(default_factory=list)

api/dify_graph/nodes/template_transform/entities.py

@@ -1,4 +1,5 @@
-from dify_graph.nodes.base import BaseNodeData
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.enums import NodeType
 from dify_graph.nodes.base.entities import VariableSelector
 
 
@@ -7,5 +8,6 @@ class TemplateTransformNodeData(BaseNodeData):
     Template Transform Node Data.
     """
 
+    type: NodeType = NodeType.TEMPLATE_TRANSFORM
     variables: list[VariableSelector]
     template: str

api/dify_graph/nodes/template_transform/template_transform_node.py

@@ -1,6 +1,7 @@
 from collections.abc import Mapping, Sequence
 from typing import TYPE_CHECKING, Any
 
+from dify_graph.entities.graph_config import NodeConfigDict
 from dify_graph.enums import NodeType, WorkflowNodeExecutionStatus
 from dify_graph.node_events import NodeRunResult
 from dify_graph.nodes.base.node import Node
@@ -25,7 +26,7 @@ class TemplateTransformNode(Node[TemplateTransformNodeData]):
     def __init__(
         self,
         id: str,
-        config: Mapping[str, Any],
+        config: NodeConfigDict,
         graph_init_params: "GraphInitParams",
         graph_runtime_state: "GraphRuntimeState",
         *,
@@ -86,12 +87,9 @@ class TemplateTransformNode(Node[TemplateTransformNodeData]):
 
     @classmethod
     def _extract_variable_selector_to_variable_mapping(
-        cls, *, graph_config: Mapping[str, Any], node_id: str, node_data: Mapping[str, Any]
+        cls, *, graph_config: Mapping[str, Any], node_id: str, node_data: TemplateTransformNodeData
     ) -> Mapping[str, Sequence[str]]:
-        # Create typed NodeData from dict
-        typed_node_data = TemplateTransformNodeData.model_validate(node_data)
-
         return {
             node_id + "." + variable_selector.variable: variable_selector.value_selector
-            for variable_selector in typed_node_data.variables
+            for variable_selector in node_data.variables
         }

api/dify_graph/nodes/tool/entities.py

@@ -4,7 +4,8 @@ from pydantic import BaseModel, field_validator
 from pydantic_core.core_schema import ValidationInfo
 
 from core.tools.entities.tool_entities import ToolProviderType
-from dify_graph.nodes.base.entities import BaseNodeData
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.enums import NodeType
 
 
 class ToolEntity(BaseModel):
@@ -32,6 +33,8 @@ class ToolEntity(BaseModel):
 
 
 class ToolNodeData(BaseNodeData, ToolEntity):
+    type: NodeType = NodeType.TOOL
+
     class ToolInput(BaseModel):
         # TODO: check this type
         value: Union[Any, list[str]]

api/dify_graph/nodes/tool/tool_node.py

@@ -7,6 +7,7 @@ from core.tools.entities.tool_entities import ToolInvokeMessage, ToolParameter
 from core.tools.errors import ToolInvokeError
 from core.tools.tool_engine import ToolEngine
 from core.tools.utils.message_transformer import ToolFileMessageTransformer
+from dify_graph.entities.graph_config import NodeConfigDict
 from dify_graph.enums import (
     NodeType,
     SystemVariableKey,
@@ -46,7 +47,7 @@ class ToolNode(Node[ToolNodeData]):
     def __init__(
         self,
         id: str,
-        config: Mapping[str, Any],
+        config: NodeConfigDict,
         graph_init_params: "GraphInitParams",
         graph_runtime_state: "GraphRuntimeState",
         *,
@@ -64,6 +65,10 @@ class ToolNode(Node[ToolNodeData]):
     def version(cls) -> str:
         return "1"
 
+    def populate_start_event(self, event) -> None:
+        event.provider_id = self.node_data.provider_id
+        event.provider_type = self.node_data.provider_type
+
     def _run(self) -> Generator[NodeEventBase, None, None]:
         """
         Run the tool node
@@ -484,7 +489,7 @@ class ToolNode(Node[ToolNodeData]):
         *,
         graph_config: Mapping[str, Any],
         node_id: str,
-        node_data: Mapping[str, Any],
+        node_data: ToolNodeData,
     ) -> Mapping[str, Sequence[str]]:
         """
         Extract variable selector to variable mapping
@@ -493,9 +498,8 @@ class ToolNode(Node[ToolNodeData]):
         :param node_data: node data
         :return:
         """
-        # Create typed NodeData from dict
-        typed_node_data = ToolNodeData.model_validate(node_data)
-
+        _ = graph_config  # Explicitly mark as unused
+        typed_node_data = node_data
         result = {}
         for parameter_name in typed_node_data.tool_parameters:
             input = typed_node_data.tool_parameters[parameter_name]

api/dify_graph/nodes/trigger_plugin/entities.py

@@ -4,13 +4,16 @@ from typing import Any, Literal, Union
 from pydantic import BaseModel, Field, ValidationInfo, field_validator
 
 from core.trigger.entities.entities import EventParameter
-from dify_graph.nodes.base.entities import BaseNodeData
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.enums import NodeType
 from dify_graph.nodes.trigger_plugin.exc import TriggerEventParameterError
 
 
 class TriggerEventNodeData(BaseNodeData):
     """Plugin trigger node data"""
 
+    type: NodeType = NodeType.TRIGGER_PLUGIN
+
     class TriggerEventInput(BaseModel):
         value: Union[Any, list[str]]
         type: Literal["mixed", "variable", "constant"]
@@ -38,8 +41,6 @@ class TriggerEventNodeData(BaseNodeData):
                 raise ValueError("value must be a string, int, float, bool or dict")
             return type
 
-    title: str
-    desc: str | None = None
     plugin_id: str = Field(..., description="Plugin ID")
     provider_id: str = Field(..., description="Provider ID")
     event_name: str = Field(..., description="Event name")

api/dify_graph/nodes/trigger_plugin/trigger_event_node.py

@@ -32,6 +32,9 @@ class TriggerEventNode(Node[TriggerEventNodeData]):
     def version(cls) -> str:
         return "1"
 
+    def populate_start_event(self, event) -> None:
+        event.provider_id = self.node_data.provider_id
+
     def _run(self) -> NodeRunResult:
         """
         Run the plugin trigger node.

api/dify_graph/nodes/trigger_schedule/entities.py

@@ -2,7 +2,8 @@ from typing import Literal, Union
 
 from pydantic import BaseModel, Field
 
-from dify_graph.nodes.base import BaseNodeData
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.enums import NodeType
 
 
 class TriggerScheduleNodeData(BaseNodeData):
@@ -10,6 +11,7 @@ class TriggerScheduleNodeData(BaseNodeData):
     Trigger Schedule Node Data
     """
 
+    type: NodeType = NodeType.TRIGGER_SCHEDULE
     mode: str = Field(default="visual", description="Schedule mode: visual or cron")
     frequency: str | None = Field(default=None, description="Frequency for visual mode: hourly, daily, weekly, monthly")
     cron_expression: str | None = Field(default=None, description="Cron expression for cron mode")

api/dify_graph/nodes/trigger_schedule/exc.py

@@ -1,4 +1,4 @@
-from dify_graph.nodes.base.exc import BaseNodeError
+from dify_graph.entities.exc import BaseNodeError
 
 
 class ScheduleNodeError(BaseNodeError):

api/dify_graph/nodes/trigger_webhook/entities.py

@@ -1,10 +1,41 @@
 from collections.abc import Sequence
 from enum import StrEnum
-from typing import Literal
 
 from pydantic import BaseModel, Field, field_validator
 
-from dify_graph.nodes.base import BaseNodeData
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.enums import NodeType
+from dify_graph.variables.types import SegmentType
+
+_WEBHOOK_HEADER_ALLOWED_TYPES = frozenset(
+    {
+        SegmentType.STRING,
+    }
+)
+
+_WEBHOOK_QUERY_PARAMETER_ALLOWED_TYPES = frozenset(
+    {
+        SegmentType.STRING,
+        SegmentType.NUMBER,
+        SegmentType.BOOLEAN,
+    }
+)
+
+_WEBHOOK_PARAMETER_ALLOWED_TYPES = _WEBHOOK_HEADER_ALLOWED_TYPES | _WEBHOOK_QUERY_PARAMETER_ALLOWED_TYPES
+
+_WEBHOOK_BODY_ALLOWED_TYPES = frozenset(
+    {
+        SegmentType.STRING,
+        SegmentType.NUMBER,
+        SegmentType.BOOLEAN,
+        SegmentType.OBJECT,
+        SegmentType.ARRAY_STRING,
+        SegmentType.ARRAY_NUMBER,
+        SegmentType.ARRAY_BOOLEAN,
+        SegmentType.ARRAY_OBJECT,
+        SegmentType.FILE,
+    }
+)
 
 
 class Method(StrEnum):
@@ -25,29 +56,34 @@ class ContentType(StrEnum):
 
 
 class WebhookParameter(BaseModel):
-    """Parameter definition for headers, query params, or body."""
+    """Parameter definition for headers or query params."""
 
     name: str
+    type: SegmentType = SegmentType.STRING
     required: bool = False
 
+    @field_validator("type", mode="after")
+    @classmethod
+    def validate_type(cls, v: SegmentType) -> SegmentType:
+        if v not in _WEBHOOK_PARAMETER_ALLOWED_TYPES:
+            raise ValueError(f"Unsupported webhook parameter type: {v}")
+        return v
+
 
 class WebhookBodyParameter(BaseModel):
     """Body parameter with type information."""
 
     name: str
-    type: Literal[
-        "string",
-        "number",
-        "boolean",
-        "object",
-        "array[string]",
-        "array[number]",
-        "array[boolean]",
-        "array[object]",
-        "file",
-    ] = "string"
+    type: SegmentType = SegmentType.STRING
     required: bool = False
 
+    @field_validator("type", mode="after")
+    @classmethod
+    def validate_type(cls, v: SegmentType) -> SegmentType:
+        if v not in _WEBHOOK_BODY_ALLOWED_TYPES:
+            raise ValueError(f"Unsupported webhook body parameter type: {v}")
+        return v
+
 
 class WebhookData(BaseNodeData):
     """
@@ -57,6 +93,7 @@ class WebhookData(BaseNodeData):
     class SyncMode(StrEnum):
         SYNC = "async"  # only support
 
+    type: NodeType = NodeType.TRIGGER_WEBHOOK
     method: Method = Method.GET
     content_type: ContentType = Field(default=ContentType.JSON)
     headers: Sequence[WebhookParameter] = Field(default_factory=list)
@@ -71,6 +108,22 @@ class WebhookData(BaseNodeData):
             return v.lower()
         return v
 
+    @field_validator("headers", mode="after")
+    @classmethod
+    def validate_header_types(cls, v: Sequence[WebhookParameter]) -> Sequence[WebhookParameter]:
+        for param in v:
+            if param.type not in _WEBHOOK_HEADER_ALLOWED_TYPES:
+                raise ValueError(f"Unsupported webhook header parameter type: {param.type}")
+        return v
+
+    @field_validator("params", mode="after")
+    @classmethod
+    def validate_query_parameter_types(cls, v: Sequence[WebhookParameter]) -> Sequence[WebhookParameter]:
+        for param in v:
+            if param.type not in _WEBHOOK_QUERY_PARAMETER_ALLOWED_TYPES:
+                raise ValueError(f"Unsupported webhook query parameter type: {param.type}")
+        return v
+
     status_code: int = 200  # Expected status code for response
     response_body: str = ""  # Template for response body
 

api/dify_graph/nodes/trigger_webhook/exc.py

@@ -1,4 +1,4 @@
-from dify_graph.nodes.base.exc import BaseNodeError
+from dify_graph.entities.exc import BaseNodeError
 
 
 class WebhookNodeError(BaseNodeError):

api/dify_graph/nodes/trigger_webhook/node.py

@@ -152,7 +152,7 @@ class TriggerWebhookNode(Node[WebhookData]):
                     outputs[param_name] = raw_data
                 continue
 
-            if param_type == "file":
+            if param_type == SegmentType.FILE:
                 # Get File object (already processed by webhook controller)
                 files = webhook_data.get("files", {})
                 if files and isinstance(files, dict):

api/dify_graph/nodes/variable_aggregator/entities.py

@@ -1,6 +1,7 @@
 from pydantic import BaseModel
 
-from dify_graph.nodes.base import BaseNodeData
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.enums import NodeType
 from dify_graph.variables.types import SegmentType
 
 
@@ -28,6 +29,7 @@ class VariableAggregatorNodeData(BaseNodeData):
     Variable Aggregator Node Data.
     """
 
+    type: NodeType = NodeType.VARIABLE_AGGREGATOR
     output_type: str
     variables: list[list[str]]
     advanced_settings: AdvancedSettings | None = None

api/dify_graph/nodes/variable_assigner/v1/node.py

@@ -3,6 +3,7 @@ from typing import TYPE_CHECKING, Any
 
 from dify_graph.constants import CONVERSATION_VARIABLE_NODE_ID
 from dify_graph.entities import GraphInitParams
+from dify_graph.entities.graph_config import NodeConfigDict
 from dify_graph.enums import NodeType, WorkflowNodeExecutionStatus
 from dify_graph.node_events import NodeRunResult
 from dify_graph.nodes.base.node import Node
@@ -22,7 +23,7 @@ class VariableAssignerNode(Node[VariableAssignerData]):
     def __init__(
         self,
         id: str,
-        config: Mapping[str, Any],
+        config: NodeConfigDict,
         graph_init_params: "GraphInitParams",
         graph_runtime_state: "GraphRuntimeState",
     ):
@@ -52,21 +53,18 @@ class VariableAssignerNode(Node[VariableAssignerData]):
         *,
         graph_config: Mapping[str, Any],
         node_id: str,
-        node_data: Mapping[str, Any],
+        node_data: VariableAssignerData,
     ) -> Mapping[str, Sequence[str]]:
-        # Create typed NodeData from dict
-        typed_node_data = VariableAssignerData.model_validate(node_data)
-
         mapping = {}
-        assigned_variable_node_id = typed_node_data.assigned_variable_selector[0]
+        assigned_variable_node_id = node_data.assigned_variable_selector[0]
         if assigned_variable_node_id == CONVERSATION_VARIABLE_NODE_ID:
-            selector_key = ".".join(typed_node_data.assigned_variable_selector)
+            selector_key = ".".join(node_data.assigned_variable_selector)
             key = f"{node_id}.#{selector_key}#"
-            mapping[key] = typed_node_data.assigned_variable_selector
+            mapping[key] = node_data.assigned_variable_selector
 
-        selector_key = ".".join(typed_node_data.input_variable_selector)
+        selector_key = ".".join(node_data.input_variable_selector)
         key = f"{node_id}.#{selector_key}#"
-        mapping[key] = typed_node_data.input_variable_selector
+        mapping[key] = node_data.input_variable_selector
         return mapping
 
     def _run(self) -> NodeRunResult:

api/dify_graph/nodes/variable_assigner/v1/node_data.py

@@ -1,7 +1,8 @@
 from collections.abc import Sequence
 from enum import StrEnum
 
-from dify_graph.nodes.base import BaseNodeData
+from dify_graph.entities.base_node_data import BaseNodeData
+from dify_graph.enums import NodeType
 
 
 class WriteMode(StrEnum):
@@ -11,6 +12,7 @@ class WriteMode(StrEnum):
 
 
 class VariableAssignerData(BaseNodeData):
+    type: NodeType = NodeType.VARIABLE_ASSIGNER
     assigned_variable_selector: Sequence[str]
     write_mode: WriteMode
     input_variable_selector: Sequence[str]