r2

api/controllers/console/datasets/rag_pipeline/rag_pipeline_datasets.py

@@ -0,0 +1,170 @@
+from flask_login import current_user  # type: ignore  # type: ignore
+from flask_restful import Resource, marshal, reqparse  # type: ignore
+from werkzeug.exceptions import Forbidden
+
+import services
+from controllers.console import api
+from controllers.console.datasets.error import DatasetNameDuplicateError
+from controllers.console.wraps import (
+    account_initialization_required,
+    cloud_edition_billing_rate_limit_check,
+    setup_required,
+)
+from fields.dataset_fields import dataset_detail_fields
+from libs.login import login_required
+from models.dataset import DatasetPermissionEnum
+from services.dataset_service import DatasetPermissionService, DatasetService
+from services.entities.knowledge_entities.rag_pipeline_entities import RagPipelineDatasetCreateEntity
+
+
+def _validate_name(name):
+    if not name or len(name) < 1 or len(name) > 40:
+        raise ValueError("Name must be between 1 to 40 characters.")
+    return name
+
+
+def _validate_description_length(description):
+    if len(description) > 400:
+        raise ValueError("Description cannot exceed 400 characters.")
+    return description
+
+
+class CreateRagPipelineDatasetApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @cloud_edition_billing_rate_limit_check("knowledge")
+    def post(self):
+        parser = reqparse.RequestParser()
+        parser.add_argument(
+            "name",
+            nullable=False,
+            required=True,
+            help="type is required. Name must be between 1 to 40 characters.",
+            type=_validate_name,
+        )
+        parser.add_argument(
+            "description",
+            type=str,
+            nullable=True,
+            required=False,
+            default="",
+        )
+
+        parser.add_argument(
+            "icon_info",
+            type=dict,
+            nullable=True,
+            required=False,
+            default={},
+        )
+
+        parser.add_argument(
+            "permission",
+            type=str,
+            choices=(DatasetPermissionEnum.ONLY_ME, DatasetPermissionEnum.ALL_TEAM, DatasetPermissionEnum.PARTIAL_TEAM),
+            nullable=True,
+            required=False,
+            default=DatasetPermissionEnum.ONLY_ME,
+        )
+
+        parser.add_argument(
+            "partial_member_list",
+            type=list,
+            nullable=True,
+            required=False,
+            default=[],
+        )
+
+        parser.add_argument(
+            "yaml_content",
+            type=str,
+            nullable=False,
+            required=True,
+            help="yaml_content is required.",
+        )
+
+        args = parser.parse_args()
+
+        # The role of the current user in the ta table must be admin, owner, or editor, or dataset_operator
+        if not current_user.is_dataset_editor:
+            raise Forbidden()
+        rag_pipeline_dataset_create_entity = RagPipelineDatasetCreateEntity(**args)
+        try:
+            import_info = DatasetService.create_rag_pipeline_dataset(
+                tenant_id=current_user.current_tenant_id,
+                rag_pipeline_dataset_create_entity=rag_pipeline_dataset_create_entity,
+            )
+            if rag_pipeline_dataset_create_entity.permission == "partial_members":
+                DatasetPermissionService.update_partial_member_list(
+                    current_user.current_tenant_id,
+                    import_info["dataset_id"],
+                    rag_pipeline_dataset_create_entity.partial_member_list,
+                )
+        except services.errors.dataset.DatasetNameDuplicateError:
+            raise DatasetNameDuplicateError()
+
+        return import_info, 201
+
+
+class CreateEmptyRagPipelineDatasetApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @cloud_edition_billing_rate_limit_check("knowledge")
+    def post(self):
+        # The role of the current user in the ta table must be admin, owner, or editor, or dataset_operator
+        if not current_user.is_dataset_editor:
+            raise Forbidden()
+
+        parser = reqparse.RequestParser()
+        parser.add_argument(
+            "name",
+            nullable=False,
+            required=True,
+            help="type is required. Name must be between 1 to 40 characters.",
+            type=_validate_name,
+        )
+        parser.add_argument(
+            "description",
+            type=str,
+            nullable=True,
+            required=False,
+            default="",
+        )
+
+        parser.add_argument(
+            "icon_info",
+            type=dict,
+            nullable=True,
+            required=False,
+            default={},
+        )
+
+        parser.add_argument(
+            "permission",
+            type=str,
+            choices=(DatasetPermissionEnum.ONLY_ME, DatasetPermissionEnum.ALL_TEAM, DatasetPermissionEnum.PARTIAL_TEAM),
+            nullable=True,
+            required=False,
+            default=DatasetPermissionEnum.ONLY_ME,
+        )
+
+        parser.add_argument(
+            "partial_member_list",
+            type=list,
+            nullable=True,
+            required=False,
+            default=[],
+        )
+
+        args = parser.parse_args()
+        dataset = DatasetService.create_empty_rag_pipeline_dataset(
+            tenant_id=current_user.current_tenant_id,
+            rag_pipeline_dataset_create_entity=args,
+        )
+        return marshal(dataset, dataset_detail_fields), 201
+
+
+api.add_resource(CreateRagPipelineDatasetApi, "/rag/pipeline/dataset")
+api.add_resource(CreateEmptyRagPipelineDatasetApi, "/rag/pipeline/empty-dataset")

api/controllers/console/datasets/rag_pipeline/rag_pipeline_import.py

@@ -0,0 +1,147 @@
+from typing import cast
+
+from flask_login import current_user  # type: ignore
+from flask_restful import Resource, marshal_with, reqparse  # type: ignore
+from sqlalchemy.orm import Session
+from werkzeug.exceptions import Forbidden
+
+from controllers.console import api
+from controllers.console.datasets.wraps import get_rag_pipeline
+from controllers.console.wraps import (
+    account_initialization_required,
+    setup_required,
+)
+from extensions.ext_database import db
+from fields.rag_pipeline_fields import pipeline_import_check_dependencies_fields, pipeline_import_fields
+from libs.login import login_required
+from models import Account
+from models.dataset import Pipeline
+from services.app_dsl_service import ImportStatus
+from services.rag_pipeline.rag_pipeline_dsl_service import RagPipelineDslService
+
+
+class RagPipelineImportApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @marshal_with(pipeline_import_fields)
+    def post(self):
+        # Check user role first
+        if not current_user.is_editor:
+            raise Forbidden()
+
+        parser = reqparse.RequestParser()
+        parser.add_argument("mode", type=str, required=True, location="json")
+        parser.add_argument("yaml_content", type=str, location="json")
+        parser.add_argument("yaml_url", type=str, location="json")
+        parser.add_argument("name", type=str, location="json")
+        parser.add_argument("description", type=str, location="json")
+        parser.add_argument("icon_type", type=str, location="json")
+        parser.add_argument("icon", type=str, location="json")
+        parser.add_argument("icon_background", type=str, location="json")
+        parser.add_argument("pipeline_id", type=str, location="json")
+        args = parser.parse_args()
+
+        # Create service with session
+        with Session(db.engine) as session:
+            import_service = RagPipelineDslService(session)
+            # Import app
+            account = cast(Account, current_user)
+            result = import_service.import_rag_pipeline(
+                account=account,
+                import_mode=args["mode"],
+                yaml_content=args.get("yaml_content"),
+                yaml_url=args.get("yaml_url"),
+                pipeline_id=args.get("pipeline_id"),
+            )
+            session.commit()
+
+        # Return appropriate status code based on result
+        status = result.status
+        if status == ImportStatus.FAILED.value:
+            return result.model_dump(mode="json"), 400
+        elif status == ImportStatus.PENDING.value:
+            return result.model_dump(mode="json"), 202
+        return result.model_dump(mode="json"), 200
+
+
+class RagPipelineImportConfirmApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @marshal_with(pipeline_import_fields)
+    def post(self, import_id):
+        # Check user role first
+        if not current_user.is_editor:
+            raise Forbidden()
+
+        # Create service with session
+        with Session(db.engine) as session:
+            import_service = RagPipelineDslService(session)
+            # Confirm import
+            account = cast(Account, current_user)
+            result = import_service.confirm_import(import_id=import_id, account=account)
+            session.commit()
+
+        # Return appropriate status code based on result
+        if result.status == ImportStatus.FAILED.value:
+            return result.model_dump(mode="json"), 400
+        return result.model_dump(mode="json"), 200
+
+
+class RagPipelineImportCheckDependenciesApi(Resource):
+    @setup_required
+    @login_required
+    @get_rag_pipeline
+    @account_initialization_required
+    @marshal_with(pipeline_import_check_dependencies_fields)
+    def get(self, pipeline: Pipeline):
+        if not current_user.is_editor:
+            raise Forbidden()
+
+        with Session(db.engine) as session:
+            import_service = RagPipelineDslService(session)
+            result = import_service.check_dependencies(pipeline=pipeline)
+
+        return result.model_dump(mode="json"), 200
+
+
+class RagPipelineExportApi(Resource):
+    @setup_required
+    @login_required
+    @get_rag_pipeline
+    @account_initialization_required
+    @marshal_with(pipeline_import_check_dependencies_fields)
+    def get(self, pipeline: Pipeline):
+        if not current_user.is_editor:
+            raise Forbidden()
+
+            # Add include_secret params
+        parser = reqparse.RequestParser()
+        parser.add_argument("include_secret", type=bool, default=False, location="args")
+        args = parser.parse_args()
+
+        with Session(db.engine) as session:
+            export_service = RagPipelineDslService(session)
+            result = export_service.export_rag_pipeline_dsl(pipeline=pipeline, include_secret=args["include_secret"])
+
+        return {"data": result}, 200
+
+
+# Import Rag Pipeline
+api.add_resource(
+    RagPipelineImportApi,
+    "/rag/pipelines/imports",
+)
+api.add_resource(
+    RagPipelineImportConfirmApi,
+    "/rag/pipelines/imports/<string:import_id>/confirm",
+)
+api.add_resource(
+    RagPipelineImportCheckDependenciesApi,
+    "/rag/pipelines/imports/<string:pipeline_id>/check-dependencies",
+)
+api.add_resource(
+    RagPipelineExportApi,
+    "/rag/pipelines/<string:pipeline_id>/exports",
+)

api/controllers/console/datasets/rag_pipeline/rag_pipeline_workflow.py

@@ -4,6 +4,7 @@ from typing import cast
 
 from flask import abort, request
 from flask_restful import Resource, inputs, marshal_with, reqparse  # type: ignore  # type: ignore
+from flask_restful.inputs import int_range  # type: ignore
 from sqlalchemy.orm import Session
 from werkzeug.exceptions import Forbidden, InternalServerError, NotFound
 
@@ -23,12 +24,18 @@ from controllers.console.wraps import (
 from controllers.web.error import InvokeRateLimitError as InvokeRateLimitHttpError
 from core.app.apps.base_app_queue_manager import AppQueueManager
 from core.app.entities.app_invoke_entities import InvokeFrom
+from core.model_runtime.utils.encoders import jsonable_encoder
 from extensions.ext_database import db
 from factories import variable_factory
 from fields.workflow_fields import workflow_fields, workflow_pagination_fields
-from fields.workflow_run_fields import workflow_run_node_execution_fields
+from fields.workflow_run_fields import (
+    workflow_run_detail_fields,
+    workflow_run_node_execution_fields,
+    workflow_run_node_execution_list_fields,
+    workflow_run_pagination_fields,
+)
 from libs import helper
-from libs.helper import TimestampField
+from libs.helper import TimestampField, uuid_value
 from libs.login import current_user, login_required
 from models.account import Account
 from models.dataset import Pipeline
@@ -36,6 +43,7 @@ from services.app_generate_service import AppGenerateService
 from services.errors.app import WorkflowHashNotEqualError
 from services.errors.llm import InvokeRateLimitError
 from services.rag_pipeline.rag_pipeline import RagPipelineService
+from services.tools.builtin_tools_manage_service import BuiltinToolManageService
 from services.workflow_service import DraftWorkflowDeletionError, WorkflowInUseError
 
 logger = logging.getLogger(__name__)
@@ -461,45 +469,6 @@ class DefaultRagPipelineBlockConfigApi(Resource):
         rag_pipeline_service = RagPipelineService()
         return rag_pipeline_service.get_default_block_config(node_type=block_type, filters=filters)
 
-
-class ConvertToRagPipelineApi(Resource):
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @get_rag_pipeline
-    def post(self, pipeline: Pipeline):
-        """
-        Convert basic mode of chatbot app to workflow mode
-        Convert expert mode of chatbot app to workflow mode
-        Convert Completion App to Workflow App
-        """
-        # The role of the current user in the ta table must be admin, owner, or editor
-        if not current_user.is_editor:
-            raise Forbidden()
-
-        if not isinstance(current_user, Account):
-            raise Forbidden()
-
-        if request.data:
-            parser = reqparse.RequestParser()
-            parser.add_argument("name", type=str, required=False, nullable=True, location="json")
-            parser.add_argument("icon_type", type=str, required=False, nullable=True, location="json")
-            parser.add_argument("icon", type=str, required=False, nullable=True, location="json")
-            parser.add_argument("icon_background", type=str, required=False, nullable=True, location="json")
-            args = parser.parse_args()
-        else:
-            args = {}
-
-        # convert to workflow mode
-        rag_pipeline_service = RagPipelineService()
-        new_app_model = rag_pipeline_service.convert_to_workflow(pipeline=pipeline, account=current_user, args=args)
-
-        # return app id
-        return {
-            "new_app_id": new_app_model.id,
-        }
-
-
 class RagPipelineConfigApi(Resource):
     """Resource for rag pipeline configuration."""
 
@@ -674,6 +643,85 @@ class RagPipelineSecondStepApi(Resource):
         )
 
 
+class RagPipelineWorkflowRunListApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_rag_pipeline
+    @marshal_with(workflow_run_pagination_fields)
+    def get(self, pipeline: Pipeline):
+        """
+        Get workflow run list
+        """
+        parser = reqparse.RequestParser()
+        parser.add_argument("last_id", type=uuid_value, location="args")
+        parser.add_argument("limit", type=int_range(1, 100), required=False, default=20, location="args")
+        args = parser.parse_args()
+
+        rag_pipeline_service = RagPipelineService()
+        result = rag_pipeline_service.get_rag_pipeline_paginate_workflow_runs(pipeline=pipeline, args=args)
+
+        return result
+
+
+class RagPipelineWorkflowRunDetailApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_rag_pipeline
+    @marshal_with(workflow_run_detail_fields)
+    def get(self, pipeline: Pipeline, run_id):
+        """
+        Get workflow run detail
+        """
+        run_id = str(run_id)
+
+        rag_pipeline_service = RagPipelineService()
+        workflow_run = rag_pipeline_service.get_rag_pipeline_workflow_run(pipeline=pipeline, run_id=run_id)
+
+        return workflow_run
+
+
+class RagPipelineWorkflowRunNodeExecutionListApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @get_rag_pipeline
+    @marshal_with(workflow_run_node_execution_list_fields)
+    def get(self, pipeline: Pipeline, run_id):
+        """
+        Get workflow run node execution list
+        """
+        run_id = str(run_id)
+
+        rag_pipeline_service = RagPipelineService()
+        node_executions = rag_pipeline_service.get_rag_pipeline_workflow_run_node_executions(
+            pipeline=pipeline,
+            run_id=run_id,
+        )
+
+        return {"data": node_executions}
+
+
+class DatasourceListApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def get(self):
+        user = current_user
+
+        tenant_id = user.current_tenant_id
+
+        return jsonable_encoder(
+            [
+                provider.to_dict()
+                for provider in BuiltinToolManageService.list_rag_pipeline_datasources(
+                    tenant_id,
+                )
+            ]
+        )
+
+
 api.add_resource(
     DraftRagPipelineApi,
     "/rag/pipelines/<uuid:pipeline_id>/workflows/draft",
@@ -694,10 +742,10 @@ api.add_resource(
     RagPipelineDraftNodeRunApi,
     "/rag/pipelines/<uuid:pipeline_id>/workflows/draft/nodes/<string:node_id>/run",
 )
-api.add_resource(
-    RagPipelinePublishedNodeRunApi,
-    "/rag/pipelines/<uuid:pipeline_id>/workflows/published/nodes/<string:node_id>/run",
-)
+# api.add_resource(
+#     RagPipelinePublishedNodeRunApi,
+#     "/rag/pipelines/<uuid:pipeline_id>/workflows/published/nodes/<string:node_id>/run",
+# )
 
 api.add_resource(
     RagPipelineDraftRunIterationNodeApi,
@@ -724,11 +772,24 @@ api.add_resource(
     DefaultRagPipelineBlockConfigApi,
     "/rag/pipelines/<uuid:pipeline_id>/workflows/default-workflow-block-configs/<string:block_type>",
 )
-api.add_resource(
-    ConvertToRagPipelineApi,
-    "/rag/pipelines/<uuid:pipeline_id>/convert-to-workflow",
-)
+
 api.add_resource(
     RagPipelineByIdApi,
     "/rag/pipelines/<uuid:pipeline_id>/workflows/<string:workflow_id>",
 )
+api.add_resource(
+    RagPipelineWorkflowRunListApi,
+    "/rag/pipelines/<uuid:pipeline_id>/workflow-runs",
+)
+api.add_resource(
+    RagPipelineWorkflowRunDetailApi,
+    "/rag/pipelines/<uuid:pipeline_id>/workflow-runs/<uuid:run_id>",
+)
+api.add_resource(
+    RagPipelineWorkflowRunNodeExecutionListApi,
+    "/rag/pipelines/<uuid:pipeline_id>/workflow-runs/<uuid:run_id>/node-executions",
+)
+api.add_resource(
+    DatasourceListApi,
+    "/rag/pipelines/datasources",
+)

api/core/datasource/__base/datasource_plugin.py

@@ -2,13 +2,13 @@ from collections.abc import Generator
 from typing import Any, Optional
 
 from core.datasource.__base.datasource_runtime import DatasourceRuntime
+from core.datasource.datasource_manager import DatasourceManager
 from core.datasource.entities.datasource_entities import (
     DatasourceEntity,
     DatasourceInvokeMessage,
     DatasourceParameter,
     DatasourceProviderType,
 )
-from core.plugin.manager.datasource import PluginDatasourceManager
 from core.plugin.utils.converter import convert_parameters_to_plugin_format
 
 
@@ -44,7 +44,7 @@ class DatasourcePlugin:
         datasource_parameters: dict[str, Any],
         rag_pipeline_id: Optional[str] = None,
     ) -> Generator[DatasourceInvokeMessage, None, None]:
-        manager = PluginDatasourceManager()
+        manager = DatasourceManager()
 
         datasource_parameters = convert_parameters_to_plugin_format(datasource_parameters)
 
@@ -64,7 +64,7 @@ class DatasourcePlugin:
         datasource_parameters: dict[str, Any],
         rag_pipeline_id: Optional[str] = None,
     ) -> Generator[DatasourceInvokeMessage, None, None]:
-        manager = PluginDatasourceManager()
+        manager = DatasourceManager()
 
         datasource_parameters = convert_parameters_to_plugin_format(datasource_parameters)
 

api/core/datasource/__base/datasource_provider.py

@@ -4,12 +4,11 @@ from core.datasource.__base.datasource_plugin import DatasourcePlugin
 from core.datasource.__base.datasource_runtime import DatasourceRuntime
 from core.datasource.entities.datasource_entities import DatasourceProviderEntityWithPlugin, DatasourceProviderType
 from core.entities.provider_entities import ProviderConfig
-from core.plugin.manager.tool import PluginToolManager
-from core.tools.builtin_tool.provider import BuiltinToolProviderController
+from core.plugin.impl.tool import PluginToolManager
 from core.tools.errors import ToolProviderCredentialValidationError
 
 
-class DatasourcePluginProviderController(BuiltinToolProviderController):
+class DatasourcePluginProviderController:
     entity: DatasourceProviderEntityWithPlugin
     tenant_id: str
     plugin_id: str
@@ -32,12 +31,21 @@ class DatasourcePluginProviderController(BuiltinToolProviderController):
         """
         return DatasourceProviderType.RAG_PIPELINE
 
+    @property
+    def need_credentials(self) -> bool:
+        """
+        returns whether the provider needs credentials
+
+        :return: whether the provider needs credentials
+        """
+        return self.entity.credentials_schema is not None and len(self.entity.credentials_schema) != 0
+
     def _validate_credentials(self, user_id: str, credentials: dict[str, Any]) -> None:
         """
         validate the credentials of the provider
         """
         manager = PluginToolManager()
-        if not manager.validate_provider_credentials(
+        if not manager.validate_datasource_credentials(
             tenant_id=self.tenant_id,
             user_id=user_id,
             provider=self.entity.identity.name,
@@ -69,7 +77,7 @@ class DatasourcePluginProviderController(BuiltinToolProviderController):
             plugin_unique_identifier=self.plugin_unique_identifier,
         )
 
-    def get_datasources(self) -> list[DatasourceTool]:  # type: ignore
+    def get_datasources(self) -> list[DatasourcePlugin]:  # type: ignore
         """
         get all datasources
         """

api/core/datasource/entities/api_entities.py

@@ -0,0 +1,73 @@
+from typing import Literal, Optional
+
+from pydantic import BaseModel, Field, field_validator
+
+from core.datasource.entities.datasource_entities import DatasourceParameter
+from core.model_runtime.utils.encoders import jsonable_encoder
+from core.tools.__base.tool import ToolParameter
+from core.tools.entities.common_entities import I18nObject
+from core.tools.entities.tool_entities import ToolProviderType
+
+
+class DatasourceApiEntity(BaseModel):
+    author: str
+    name: str  # identifier
+    label: I18nObject  # label
+    description: I18nObject
+    parameters: Optional[list[ToolParameter]] = None
+    labels: list[str] = Field(default_factory=list)
+    output_schema: Optional[dict] = None
+
+
+ToolProviderTypeApiLiteral = Optional[Literal["builtin", "api", "workflow"]]
+
+
+class DatasourceProviderApiEntity(BaseModel):
+    id: str
+    author: str
+    name: str  # identifier
+    description: I18nObject
+    icon: str | dict
+    label: I18nObject  # label
+    type: ToolProviderType
+    masked_credentials: Optional[dict] = None
+    original_credentials: Optional[dict] = None
+    is_team_authorization: bool = False
+    allow_delete: bool = True
+    plugin_id: Optional[str] = Field(default="", description="The plugin id of the tool")
+    plugin_unique_identifier: Optional[str] = Field(default="", description="The unique identifier of the tool")
+    datasources: list[DatasourceApiEntity] = Field(default_factory=list)
+    labels: list[str] = Field(default_factory=list)
+
+    @field_validator("datasources", mode="before")
+    @classmethod
+    def convert_none_to_empty_list(cls, v):
+        return v if v is not None else []
+
+    def to_dict(self) -> dict:
+        # -------------
+        # overwrite datasource parameter types for temp fix
+        datasources = jsonable_encoder(self.datasources)
+        for datasource in datasources:
+            if datasource.get("parameters"):
+                for parameter in datasource.get("parameters"):
+                    if parameter.get("type") == DatasourceParameter.DatasourceParameterType.SYSTEM_FILES.value:
+                        parameter["type"] = "files"
+        # -------------
+
+        return {
+            "id": self.id,
+            "author": self.author,
+            "name": self.name,
+            "plugin_id": self.plugin_id,
+            "plugin_unique_identifier": self.plugin_unique_identifier,
+            "description": self.description.to_dict(),
+            "icon": self.icon,
+            "label": self.label.to_dict(),
+            "type": self.type.value,
+            "team_credentials": self.masked_credentials,
+            "is_team_authorization": self.is_team_authorization,
+            "allow_delete": self.allow_delete,
+            "datasources": datasources,
+            "labels": self.labels,
+        }

api/core/plugin/entities/plugin_daemon.py

@@ -5,6 +5,7 @@ from typing import Generic, Optional, TypeVar
 from pydantic import BaseModel, ConfigDict, Field
 
 from core.agent.plugin_entities import AgentProviderEntityWithPlugin
+from core.datasource.entities.datasource_entities import DatasourceProviderEntityWithPlugin
 from core.model_runtime.entities.model_entities import AIModelEntity
 from core.model_runtime.entities.provider_entities import ProviderEntity
 from core.plugin.entities.base import BasePluginEntity
@@ -46,6 +47,13 @@ class PluginToolProviderEntity(BaseModel):
     declaration: ToolProviderEntityWithPlugin
 
 
+class PluginDatasourceProviderEntity(BaseModel):
+    provider: str
+    plugin_unique_identifier: str
+    plugin_id: str
+    declaration: DatasourceProviderEntityWithPlugin
+
+
 class PluginAgentProviderEntity(BaseModel):
     provider: str
     plugin_unique_identifier: str

api/core/plugin/impl/tool.py

@@ -4,7 +4,11 @@ from typing import Any, Optional
 from pydantic import BaseModel
 
 from core.plugin.entities.plugin import GenericProviderID, ToolProviderID
-from core.plugin.entities.plugin_daemon import PluginBasicBooleanResponse, PluginToolProviderEntity
+from core.plugin.entities.plugin_daemon import (
+    PluginBasicBooleanResponse,
+    PluginDatasourceProviderEntity,
+    PluginToolProviderEntity,
+)
 from core.plugin.impl.base import BasePluginClient
 from core.tools.entities.tool_entities import ToolInvokeMessage, ToolParameter
 
@@ -41,6 +45,37 @@ class PluginToolManager(BasePluginClient):
 
         return response
 
+    def fetch_datasources(self, tenant_id: str) -> list[PluginDatasourceProviderEntity]:
+        """
+        Fetch datasources for the given tenant.
+        """
+
+        def transformer(json_response: dict[str, Any]) -> dict:
+            for provider in json_response.get("data", []):
+                declaration = provider.get("declaration", {}) or {}
+                provider_name = declaration.get("identity", {}).get("name")
+                for tool in declaration.get("tools", []):
+                    tool["identity"]["provider"] = provider_name
+
+            return json_response
+
+        response = self._request_with_plugin_daemon_response(
+            "GET",
+            f"plugin/{tenant_id}/management/datasources",
+            list[PluginToolProviderEntity],
+            params={"page": 1, "page_size": 256},
+            transformer=transformer,
+        )
+
+        for provider in response:
+            provider.declaration.identity.name = f"{provider.plugin_id}/{provider.declaration.identity.name}"
+
+            # override the provider name for each tool to plugin_id/provider_name
+            for tool in provider.declaration.tools:
+                tool.identity.provider = provider.declaration.identity.name
+
+        return response
+
     def fetch_tool_provider(self, tenant_id: str, provider: str) -> PluginToolProviderEntity:
         """
         Fetch tool provider for the given tenant and plugin.
@@ -197,6 +232,36 @@ class PluginToolManager(BasePluginClient):
 
         return False
 
+    def validate_datasource_credentials(
+        self, tenant_id: str, user_id: str, provider: str, credentials: dict[str, Any]
+    ) -> bool:
+        """
+        validate the credentials of the datasource
+        """
+        tool_provider_id = GenericProviderID(provider)
+
+        response = self._request_with_plugin_daemon_response_stream(
+            "POST",
+            f"plugin/{tenant_id}/dispatch/datasource/validate_credentials",
+            PluginBasicBooleanResponse,
+            data={
+                "user_id": user_id,
+                "data": {
+                    "provider": tool_provider_id.provider_name,
+                    "credentials": credentials,
+                },
+            },
+            headers={
+                "X-Plugin-ID": tool_provider_id.plugin_id,
+                "Content-Type": "application/json",
+            },
+        )
+
+        for resp in response:
+            return resp.result
+
+        return False
+
     def get_runtime_parameters(
         self,
         tenant_id: str,

api/core/tools/tool_manager.py

@@ -9,6 +9,7 @@ from typing import TYPE_CHECKING, Any, Union, cast
 from yarl import URL
 
 import contexts
+from core.datasource.__base.datasource_provider import DatasourcePluginProviderController
 from core.plugin.entities.plugin import ToolProviderID
 from core.plugin.impl.tool import PluginToolManager
 from core.tools.__base.tool_provider import ToolProviderController
@@ -495,6 +496,31 @@ class ToolManager:
         # get plugin providers
         yield from cls.list_plugin_providers(tenant_id)
 
+    @classmethod
+    def list_datasource_providers(cls, tenant_id: str) -> list[DatasourcePluginProviderController]:
+        """
+        list all the datasource providers
+        """
+        manager = PluginToolManager()
+        provider_entities = manager.fetch_datasources(tenant_id)
+        return [
+            DatasourcePluginProviderController(
+                entity=provider.declaration,
+                plugin_id=provider.plugin_id,
+                plugin_unique_identifier=provider.plugin_unique_identifier,
+                tenant_id=tenant_id,
+            )
+            for provider in provider_entities
+        ]
+
+    @classmethod
+    def list_builtin_datasources(cls, tenant_id: str) -> Generator[DatasourcePluginProviderController, None, None]:
+        """
+        list all the builtin datasources
+        """
+        # get builtin datasources
+        yield from cls.list_datasource_providers(tenant_id)
+
     @classmethod
     def _list_hardcoded_providers(cls) -> Generator[BuiltinToolProviderController, None, None]:
         """

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

@@ -10,8 +10,8 @@ class RerankingModelConfig(BaseModel):
     Reranking Model Config.
     """
 
-    provider: str
-    model: str
+    reranking_provider_name: str
+    reranking_model_name: str
 
 
 class VectorSetting(BaseModel):

api/fields/dataset_fields.py

@@ -56,6 +56,8 @@ external_knowledge_info_fields = {
 
 doc_metadata_fields = {"id": fields.String, "name": fields.String, "type": fields.String}
 
+icon_info_fields = {"icon_type": fields.String, "icon": fields.String, "icon_background": fields.String}
+
 dataset_detail_fields = {
     "id": fields.String,
     "name": fields.String,
@@ -81,6 +83,10 @@ dataset_detail_fields = {
     "external_retrieval_model": fields.Nested(external_retrieval_model_fields, allow_null=True),
     "doc_metadata": fields.List(fields.Nested(doc_metadata_fields)),
     "built_in_field_enabled": fields.Boolean,
+    "pipeline_id": fields.String,
+    "runtime_mode": fields.String,
+    "chunk_structure": fields.String,
+    "icon_info": fields.Nested(icon_info_fields),
 }
 
 dataset_query_detail_fields = {

api/fields/rag_pipeline_fields.py

@@ -0,0 +1,163 @@
+from flask_restful import fields  # type: ignore
+
+from fields.workflow_fields import workflow_partial_fields
+from libs.helper import AppIconUrlField, TimestampField
+
+pipeline_detail_kernel_fields = {
+    "id": fields.String,
+    "name": fields.String,
+    "description": fields.String,
+    "icon_type": fields.String,
+    "icon": fields.String,
+    "icon_background": fields.String,
+    "icon_url": AppIconUrlField,
+}
+
+related_app_list = {
+    "data": fields.List(fields.Nested(pipeline_detail_kernel_fields)),
+    "total": fields.Integer,
+}
+
+app_detail_fields = {
+    "id": fields.String,
+    "name": fields.String,
+    "description": fields.String,
+    "mode": fields.String(attribute="mode_compatible_with_agent"),
+    "icon": fields.String,
+    "icon_background": fields.String,
+    "workflow": fields.Nested(workflow_partial_fields, allow_null=True),
+    "tracing": fields.Raw,
+    "created_by": fields.String,
+    "created_at": TimestampField,
+    "updated_by": fields.String,
+    "updated_at": TimestampField,
+}
+
+
+tag_fields = {"id": fields.String, "name": fields.String, "type": fields.String}
+
+app_partial_fields = {
+    "id": fields.String,
+    "name": fields.String,
+    "description": fields.String(attribute="desc_or_prompt"),
+    "icon_type": fields.String,
+    "icon": fields.String,
+    "icon_background": fields.String,
+    "icon_url": AppIconUrlField,
+    "workflow": fields.Nested(workflow_partial_fields, allow_null=True),
+    "created_by": fields.String,
+    "created_at": TimestampField,
+    "updated_by": fields.String,
+    "updated_at": TimestampField,
+    "tags": fields.List(fields.Nested(tag_fields)),
+}
+
+
+app_pagination_fields = {
+    "page": fields.Integer,
+    "limit": fields.Integer(attribute="per_page"),
+    "total": fields.Integer,
+    "has_more": fields.Boolean(attribute="has_next"),
+    "data": fields.List(fields.Nested(app_partial_fields), attribute="items"),
+}
+
+template_fields = {
+    "name": fields.String,
+    "icon": fields.String,
+    "icon_background": fields.String,
+    "description": fields.String,
+    "mode": fields.String,
+}
+
+template_list_fields = {
+    "data": fields.List(fields.Nested(template_fields)),
+}
+
+site_fields = {
+    "access_token": fields.String(attribute="code"),
+    "code": fields.String,
+    "title": fields.String,
+    "icon_type": fields.String,
+    "icon": fields.String,
+    "icon_background": fields.String,
+    "icon_url": AppIconUrlField,
+    "description": fields.String,
+    "default_language": fields.String,
+    "chat_color_theme": fields.String,
+    "chat_color_theme_inverted": fields.Boolean,
+    "customize_domain": fields.String,
+    "copyright": fields.String,
+    "privacy_policy": fields.String,
+    "custom_disclaimer": fields.String,
+    "customize_token_strategy": fields.String,
+    "prompt_public": fields.Boolean,
+    "app_base_url": fields.String,
+    "show_workflow_steps": fields.Boolean,
+    "use_icon_as_answer_icon": fields.Boolean,
+    "created_by": fields.String,
+    "created_at": TimestampField,
+    "updated_by": fields.String,
+    "updated_at": TimestampField,
+}
+
+deleted_tool_fields = {
+    "type": fields.String,
+    "tool_name": fields.String,
+    "provider_id": fields.String,
+}
+
+app_detail_fields_with_site = {
+    "id": fields.String,
+    "name": fields.String,
+    "description": fields.String,
+    "mode": fields.String(attribute="mode_compatible_with_agent"),
+    "icon_type": fields.String,
+    "icon": fields.String,
+    "icon_background": fields.String,
+    "icon_url": AppIconUrlField,
+    "enable_site": fields.Boolean,
+    "enable_api": fields.Boolean,
+    "workflow": fields.Nested(workflow_partial_fields, allow_null=True),
+    "site": fields.Nested(site_fields),
+    "api_base_url": fields.String,
+    "use_icon_as_answer_icon": fields.Boolean,
+    "created_by": fields.String,
+    "created_at": TimestampField,
+    "updated_by": fields.String,
+    "updated_at": TimestampField,
+}
+
+
+app_site_fields = {
+    "app_id": fields.String,
+    "access_token": fields.String(attribute="code"),
+    "code": fields.String,
+    "title": fields.String,
+    "icon": fields.String,
+    "icon_background": fields.String,
+    "description": fields.String,
+    "default_language": fields.String,
+    "customize_domain": fields.String,
+    "copyright": fields.String,
+    "privacy_policy": fields.String,
+    "custom_disclaimer": fields.String,
+    "customize_token_strategy": fields.String,
+    "prompt_public": fields.Boolean,
+    "show_workflow_steps": fields.Boolean,
+    "use_icon_as_answer_icon": fields.Boolean,
+}
+
+leaked_dependency_fields = {"type": fields.String, "value": fields.Raw, "current_identifier": fields.String}
+
+pipeline_import_fields = {
+    "id": fields.String,
+    "status": fields.String,
+    "pipeline_id": fields.String,
+    "current_dsl_version": fields.String,
+    "imported_dsl_version": fields.String,
+    "error": fields.String,
+}
+
+pipeline_import_check_dependencies_fields = {
+    "leaked_dependencies": fields.List(fields.Nested(leaked_dependency_fields)),
+}

api/models/dataset.py

@@ -63,6 +63,10 @@ class Dataset(db.Model):  # type: ignore[name-defined]
     collection_binding_id = db.Column(StringUUID, nullable=True)
     retrieval_model = db.Column(JSONB, nullable=True)
     built_in_field_enabled = db.Column(db.Boolean, nullable=False, server_default=db.text("false"))
+    icon_info = db.Column(JSONB, nullable=True)
+    runtime_mode = db.Column(db.String(255), nullable=True, server_default=db.text("'general'::character varying"))
+    pipeline_id = db.Column(StringUUID, nullable=True)
+    chunk_structure = db.Column(db.String(255), nullable=True)
 
     @property
     def dataset_keyword_table(self):

api/models/tools.py

@@ -51,6 +51,40 @@ class BuiltinToolProvider(Base):
         return cast(dict, json.loads(self.encrypted_credentials))
 
 
+class BuiltinDatasourceProvider(Base):
+    """
+    This table stores the datasource provider information for built-in datasources for each tenant.
+    """
+
+    __tablename__ = "tool_builtin_datasource_providers"
+    __table_args__ = (
+        db.PrimaryKeyConstraint("id", name="tool_builtin_datasource_provider_pkey"),
+        # one tenant can only have one tool provider with the same name
+        db.UniqueConstraint("tenant_id", "provider", name="unique_builtin_datasource_provider"),
+    )
+
+    # id of the tool provider
+    id: Mapped[str] = mapped_column(StringUUID, server_default=db.text("uuid_generate_v4()"))
+    # id of the tenant
+    tenant_id: Mapped[str] = mapped_column(StringUUID, nullable=True)
+    # who created this tool provider
+    user_id: Mapped[str] = mapped_column(StringUUID, nullable=False)
+    # name of the tool provider
+    provider: Mapped[str] = mapped_column(db.String(256), nullable=False)
+    # credential of the tool provider
+    encrypted_credentials: Mapped[str] = mapped_column(db.Text, nullable=True)
+    created_at: Mapped[datetime] = mapped_column(
+        db.DateTime, nullable=False, server_default=db.text("CURRENT_TIMESTAMP(0)")
+    )
+    updated_at: Mapped[datetime] = mapped_column(
+        db.DateTime, nullable=False, server_default=db.text("CURRENT_TIMESTAMP(0)")
+    )
+
+    @property
+    def credentials(self) -> dict:
+        return cast(dict, json.loads(self.encrypted_credentials))
+
+
 class ApiToolProvider(Base):
     """
     The table stores the api providers.

api/services/dataset_service.py

@@ -52,6 +52,7 @@ from services.entities.knowledge_entities.knowledge_entities import (
     RetrievalModel,
     SegmentUpdateArgs,
 )
+from services.entities.knowledge_entities.rag_pipeline_entities import RagPipelineDatasetCreateEntity
 from services.errors.account import InvalidActionError, NoPermissionError
 from services.errors.chunk import ChildChunkDeleteIndexError, ChildChunkIndexingError
 from services.errors.dataset import DatasetNameDuplicateError
@@ -59,6 +60,7 @@ from services.errors.document import DocumentIndexingError
 from services.errors.file import FileNotExistsError
 from services.external_knowledge_service import ExternalDatasetService
 from services.feature_service import FeatureModel, FeatureService
+from services.rag_pipeline.rag_pipeline_dsl_service import ImportMode, RagPipelineDslService, RagPipelineImportInfo
 from services.tag_service import TagService
 from services.vector_service import VectorService
 from tasks.batch_clean_document_task import batch_clean_document_task
@@ -235,6 +237,63 @@ class DatasetService:
         db.session.commit()
         return dataset
 
+    @staticmethod
+    def create_empty_rag_pipeline_dataset(
+        tenant_id: str,
+        rag_pipeline_dataset_create_entity: RagPipelineDatasetCreateEntity,
+    ):
+        # check if dataset name already exists
+        if Dataset.query.filter_by(name=rag_pipeline_dataset_create_entity.name, tenant_id=tenant_id).first():
+            raise DatasetNameDuplicateError(
+                f"Dataset with name {rag_pipeline_dataset_create_entity.name} already exists."
+            )
+
+        dataset = Dataset(
+            name=rag_pipeline_dataset_create_entity.name,
+            description=rag_pipeline_dataset_create_entity.description,
+            permission=rag_pipeline_dataset_create_entity.permission,
+            provider="vendor",
+            runtime_mode="rag_pipeline",
+            icon_info=rag_pipeline_dataset_create_entity.icon_info,
+        )
+        db.session.add(dataset)
+        db.session.commit()
+        return dataset
+
+    @staticmethod
+    def create_rag_pipeline_dataset(
+        tenant_id: str,
+        rag_pipeline_dataset_create_entity: RagPipelineDatasetCreateEntity,
+    ):
+        # check if dataset name already exists
+        if Dataset.query.filter_by(name=rag_pipeline_dataset_create_entity.name, tenant_id=tenant_id).first():
+            raise DatasetNameDuplicateError(
+                f"Dataset with name {rag_pipeline_dataset_create_entity.name} already exists."
+            )
+
+        dataset = Dataset(
+            name=rag_pipeline_dataset_create_entity.name,
+            description=rag_pipeline_dataset_create_entity.description,
+            permission=rag_pipeline_dataset_create_entity.permission,
+            provider="vendor",
+            runtime_mode="rag_pipeline",
+            icon_info=rag_pipeline_dataset_create_entity.icon_info,
+        )
+
+        if rag_pipeline_dataset_create_entity.yaml_content:
+            rag_pipeline_import_info: RagPipelineImportInfo = RagPipelineDslService.import_rag_pipeline(
+                current_user, ImportMode.YAML_CONTENT, rag_pipeline_dataset_create_entity.yaml_content, dataset
+            )
+        return {
+            "id": rag_pipeline_import_info.id,
+            "dataset_id": dataset.id,
+            "pipeline_id": rag_pipeline_import_info.pipeline_id,
+            "status": rag_pipeline_import_info.status,
+            "imported_dsl_version": rag_pipeline_import_info.imported_dsl_version,
+            "current_dsl_version": rag_pipeline_import_info.current_dsl_version,
+            "error": rag_pipeline_import_info.error,
+        }
+
     @staticmethod
     def get_dataset(dataset_id) -> Optional[Dataset]:
         dataset: Optional[Dataset] = Dataset.query.filter_by(id=dataset_id).first()

api/services/entities/knowledge_entities/rag_pipeline_entities.py

@@ -1,4 +1,4 @@
-from typing import Optional
+from typing import Literal, Optional
 
 from pydantic import BaseModel
 
@@ -14,3 +14,100 @@ class PipelineTemplateInfoEntity(BaseModel):
     name: str
     description: str
     icon_info: IconInfo
+
+
+class RagPipelineDatasetCreateEntity(BaseModel):
+    name: str
+    description: str
+    icon_info: IconInfo
+    permission: str
+    partial_member_list: list[str]
+    yaml_content: str
+
+
+class RerankingModelConfig(BaseModel):
+    """
+    Reranking Model Config.
+    """
+
+    reranking_provider_name: str
+    reranking_model_name: str
+
+
+class VectorSetting(BaseModel):
+    """
+    Vector Setting.
+    """
+
+    vector_weight: float
+    embedding_provider_name: str
+    embedding_model_name: str
+
+
+class KeywordSetting(BaseModel):
+    """
+    Keyword Setting.
+    """
+
+    keyword_weight: float
+
+
+class WeightedScoreConfig(BaseModel):
+    """
+    Weighted score Config.
+    """
+
+    vector_setting: VectorSetting
+    keyword_setting: KeywordSetting
+
+
+class EmbeddingSetting(BaseModel):
+    """
+    Embedding Setting.
+    """
+
+    embedding_provider_name: str
+    embedding_model_name: str
+
+
+class EconomySetting(BaseModel):
+    """
+    Economy Setting.
+    """
+
+    keyword_number: int
+
+
+class RetrievalSetting(BaseModel):
+    """
+    Retrieval Setting.
+    """
+
+    search_method: Literal["semantic_search", "keyword_search", "hybrid_search"]
+    top_k: int
+    score_threshold: Optional[float] = 0.5
+    score_threshold_enabled: bool = False
+    reranking_mode: str = "reranking_model"
+    reranking_enable: bool = True
+    reranking_model: Optional[RerankingModelConfig] = None
+    weights: Optional[WeightedScoreConfig] = None
+
+
+class IndexMethod(BaseModel):
+    """
+    Knowledge Index Setting.
+    """
+
+    indexing_technique: Literal["high_quality", "economy"]
+    embedding_setting: EmbeddingSetting
+    economy_setting: EconomySetting
+
+
+class KnowledgeConfiguration(BaseModel):
+    """
+    Knowledge Configuration.
+    """
+
+    chunk_structure: str
+    index_method: IndexMethod
+    retrieval_setting: RetrievalSetting

api/services/rag_pipeline/rag_pipeline.py

@@ -1,28 +1,45 @@
 import json
+import threading
 import time
 from collections.abc import Callable, Generator, Sequence
 from datetime import UTC, datetime
 from typing import Any, Literal, Optional
+from uuid import uuid4
 
 from flask_login import current_user
 from sqlalchemy import select
 from sqlalchemy.orm import Session
 
+import contexts
 from configs import dify_config
+from core.model_runtime.utils.encoders import jsonable_encoder
+from core.repository.repository_factory import RepositoryFactory
+from core.repository.workflow_node_execution_repository import OrderConfig
 from core.variables.variables import Variable
+from core.workflow.entities.node_entities import NodeRunResult
+from core.workflow.errors import WorkflowNodeRunFailedError
 from core.workflow.graph_engine.entities.event import InNodeEvent
 from core.workflow.nodes.base.node import BaseNode
-from core.workflow.nodes.enums import NodeType
+from core.workflow.nodes.enums import ErrorStrategy, NodeType
+from core.workflow.nodes.event.event import RunCompletedEvent
 from core.workflow.nodes.event.types import NodeEvent
 from core.workflow.nodes.node_mapping import LATEST_VERSION, NODE_TYPE_CLASSES_MAPPING
 from core.workflow.workflow_entry import WorkflowEntry
 from extensions.ext_database import db
+from libs.infinite_scroll_pagination import InfiniteScrollPagination
 from models.account import Account
 from models.dataset import Pipeline, PipelineBuiltInTemplate, PipelineCustomizedTemplate  # type: ignore
-from models.workflow import Workflow, WorkflowNodeExecution, WorkflowType
+from models.enums import CreatedByRole, WorkflowRunTriggeredFrom
+from models.workflow import (
+    Workflow,
+    WorkflowNodeExecution,
+    WorkflowNodeExecutionStatus,
+    WorkflowNodeExecutionTriggeredFrom,
+    WorkflowRun,
+    WorkflowType,
+)
 from services.entities.knowledge_entities.rag_pipeline_entities import PipelineTemplateInfoEntity
 from services.errors.app import WorkflowHashNotEqualError
-from services.errors.workflow_service import DraftWorkflowDeletionError
 from services.rag_pipeline.pipeline_template.pipeline_template_factory import PipelineTemplateRetrievalFactory
 
 
@@ -180,7 +197,6 @@ class RagPipelineService:
         *,
         pipeline: Pipeline,
         graph: dict,
-        features: dict,
         unique_hash: Optional[str],
         account: Account,
         environment_variables: Sequence[Variable],
@@ -197,9 +213,6 @@ class RagPipelineService:
         if workflow and workflow.unique_hash != unique_hash:
             raise WorkflowHashNotEqualError()
 
-        # validate features structure
-        self.validate_features_structure(pipeline=pipeline, features=features)
-
         # create draft workflow if not found
         if not workflow:
             workflow = Workflow(
@@ -208,7 +221,6 @@ class RagPipelineService:
                 type=WorkflowType.RAG_PIPELINE.value,
                 version="draft",
                 graph=json.dumps(graph),
-                features=json.dumps(features),
                 created_by=account.id,
                 environment_variables=environment_variables,
                 conversation_variables=conversation_variables,
@@ -218,7 +230,6 @@ class RagPipelineService:
         # update draft workflow if found
         else:
             workflow.graph = json.dumps(graph)
-            workflow.features = json.dumps(features)
             workflow.updated_by = account.id
             workflow.updated_at = datetime.now(UTC).replace(tzinfo=None)
             workflow.environment_variables = environment_variables
@@ -227,8 +238,8 @@ class RagPipelineService:
         # commit db session changes
         db.session.commit()
 
-        # trigger app workflow events
-        app_draft_workflow_was_synced.send(pipeline, synced_draft_workflow=workflow)
+        # trigger  workflow events TODO
+        # app_draft_workflow_was_synced.send(pipeline, synced_draft_workflow=workflow)
 
         # return draft workflow
         return workflow
@@ -269,8 +280,8 @@ class RagPipelineService:
         # commit db session changes
         session.add(workflow)
 
-        # trigger app workflow events
-        app_published_workflow_was_updated.send(pipeline, published_workflow=workflow)
+        # trigger app workflow events TODO
+        # app_published_workflow_was_updated.send(pipeline, published_workflow=workflow)
 
         # return new workflow
         return workflow
@@ -508,46 +519,6 @@ class RagPipelineService:
 
         return workflow_node_execution
 
-    def convert_to_workflow(self, app_model: App, account: Account, args: dict) -> App:
-        """
-        Basic mode of chatbot app(expert mode) to workflow
-        Completion App to Workflow App
-
-        :param app_model: App instance
-        :param account: Account instance
-        :param args: dict
-        :return:
-        """
-        # chatbot convert to workflow mode
-        workflow_converter = WorkflowConverter()
-
-        if app_model.mode not in {AppMode.CHAT.value, AppMode.COMPLETION.value}:
-            raise ValueError(f"Current App mode: {app_model.mode} is not supported convert to workflow.")
-
-        # convert to workflow
-        new_app: App = workflow_converter.convert_to_workflow(
-            app_model=app_model,
-            account=account,
-            name=args.get("name", "Default Name"),
-            icon_type=args.get("icon_type", "emoji"),
-            icon=args.get("icon", "🤖"),
-            icon_background=args.get("icon_background", "#FFEAD5"),
-        )
-
-        return new_app
-
-    def validate_features_structure(self, app_model: App, features: dict) -> dict:
-        if app_model.mode == AppMode.ADVANCED_CHAT.value:
-            return AdvancedChatAppConfigManager.config_validate(
-                tenant_id=app_model.tenant_id, config=features, only_structure_validate=True
-            )
-        elif app_model.mode == AppMode.WORKFLOW.value:
-            return WorkflowAppConfigManager.config_validate(
-                tenant_id=app_model.tenant_id, config=features, only_structure_validate=True
-            )
-        else:
-            raise ValueError(f"Invalid app mode: {app_model.mode}")
-
     def update_workflow(
         self, *, session: Session, workflow_id: str, tenant_id: str, account_id: str, data: dict
     ) -> Optional[Workflow]:
@@ -578,38 +549,6 @@ class RagPipelineService:
 
         return workflow
 
-    def delete_workflow(self, *, session: Session, workflow_id: str, tenant_id: str) -> bool:
-        """
-        Delete a workflow
-
-        :param session: SQLAlchemy database session
-        :param workflow_id: Workflow ID
-        :param tenant_id: Tenant ID
-        :return: True if successful
-        :raises: ValueError if workflow not found
-        :raises: WorkflowInUseError if workflow is in use
-        :raises: DraftWorkflowDeletionError if workflow is a draft version
-        """
-        stmt = select(Workflow).where(Workflow.id == workflow_id, Workflow.tenant_id == tenant_id)
-        workflow = session.scalar(stmt)
-
-        if not workflow:
-            raise ValueError(f"Workflow with ID {workflow_id} not found")
-
-        # Check if workflow is a draft version
-        if workflow.version == "draft":
-            raise DraftWorkflowDeletionError("Cannot delete draft workflow versions")
-
-        # Check if this workflow is currently referenced by an app
-        stmt = select(App).where(App.workflow_id == workflow_id)
-        app = session.scalar(stmt)
-        if app:
-            # Cannot delete a workflow that's currently in use by an app
-            raise WorkflowInUseError(f"Cannot delete workflow that is currently in use by app '{app.name}'")
-
-        session.delete(workflow)
-        return True
-
     def get_second_step_parameters(self, pipeline: Pipeline, datasource_provider: str) -> dict:
         """
         Get second step parameters of rag pipeline
@@ -627,3 +566,101 @@ class RagPipelineService:
         datasource_provider_variables = pipeline_variables.get(datasource_provider, [])
         shared_variables = pipeline_variables.get("shared", [])
         return datasource_provider_variables + shared_variables
+
+    def get_rag_pipeline_paginate_workflow_runs(self, pipeline: Pipeline, args: dict) -> InfiniteScrollPagination:
+        """
+        Get debug workflow run list
+        Only return triggered_from == debugging
+
+        :param app_model: app model
+        :param args: request args
+        """
+        limit = int(args.get("limit", 20))
+
+        base_query = db.session.query(WorkflowRun).filter(
+            WorkflowRun.tenant_id == pipeline.tenant_id,
+            WorkflowRun.app_id == pipeline.id,
+            WorkflowRun.triggered_from == WorkflowRunTriggeredFrom.DEBUGGING.value,
+        )
+
+        if args.get("last_id"):
+            last_workflow_run = base_query.filter(
+                WorkflowRun.id == args.get("last_id"),
+            ).first()
+
+            if not last_workflow_run:
+                raise ValueError("Last workflow run not exists")
+
+            workflow_runs = (
+                base_query.filter(
+                    WorkflowRun.created_at < last_workflow_run.created_at, WorkflowRun.id != last_workflow_run.id
+                )
+                .order_by(WorkflowRun.created_at.desc())
+                .limit(limit)
+                .all()
+            )
+        else:
+            workflow_runs = base_query.order_by(WorkflowRun.created_at.desc()).limit(limit).all()
+
+        has_more = False
+        if len(workflow_runs) == limit:
+            current_page_first_workflow_run = workflow_runs[-1]
+            rest_count = base_query.filter(
+                WorkflowRun.created_at < current_page_first_workflow_run.created_at,
+                WorkflowRun.id != current_page_first_workflow_run.id,
+            ).count()
+
+            if rest_count > 0:
+                has_more = True
+
+        return InfiniteScrollPagination(data=workflow_runs, limit=limit, has_more=has_more)
+
+    def get_rag_pipeline_workflow_run(self, pipeline: Pipeline, run_id: str) -> Optional[WorkflowRun]:
+        """
+        Get workflow run detail
+
+        :param app_model: app model
+        :param run_id: workflow run id
+        """
+        workflow_run = (
+            db.session.query(WorkflowRun)
+            .filter(
+                WorkflowRun.tenant_id == pipeline.tenant_id,
+                WorkflowRun.app_id == pipeline.id,
+                WorkflowRun.id == run_id,
+            )
+            .first()
+        )
+
+        return workflow_run
+
+    def get_rag_pipeline_workflow_run_node_executions(
+        self,
+        pipeline: Pipeline,
+        run_id: str,
+    ) -> list[WorkflowNodeExecution]:
+        """
+        Get workflow run node execution list
+        """
+        workflow_run = self.get_rag_pipeline_workflow_run(pipeline, run_id)
+
+        contexts.plugin_tool_providers.set({})
+        contexts.plugin_tool_providers_lock.set(threading.Lock())
+
+        if not workflow_run:
+            return []
+
+        # Use the repository to get the node executions
+        repository = RepositoryFactory.create_workflow_node_execution_repository(
+            params={
+                "tenant_id": pipeline.tenant_id,
+                "app_id": pipeline.id,
+                "session_factory": db.session.get_bind(),
+            }
+        )
+
+        # Use the repository to get the node executions with ordering
+        order_config = OrderConfig(order_by=["index"], order_direction="desc")
+        node_executions = repository.get_by_workflow_run(workflow_run_id=run_id, order_config=order_config)
+
+        return list(node_executions)

api/services/rag_pipeline/rag_pipeline_dsl_service.py

@@ -0,0 +1,841 @@
+import base64
+import hashlib
+import logging
+import uuid
+from collections.abc import Mapping
+from enum import StrEnum
+from typing import Optional
+from urllib.parse import urlparse
+from uuid import uuid4
+
+import yaml  # type: ignore
+from Crypto.Cipher import AES
+from Crypto.Util.Padding import pad, unpad
+from packaging import version
+from pydantic import BaseModel, Field
+from sqlalchemy import select
+from sqlalchemy.orm import Session
+
+from core.helper import ssrf_proxy
+from core.model_runtime.utils.encoders import jsonable_encoder
+from core.plugin.entities.plugin import PluginDependency
+from core.workflow.nodes.enums import NodeType
+from core.workflow.nodes.knowledge_retrieval.entities import KnowledgeRetrievalNodeData
+from core.workflow.nodes.llm.entities import LLMNodeData
+from core.workflow.nodes.parameter_extractor.entities import ParameterExtractorNodeData
+from core.workflow.nodes.question_classifier.entities import QuestionClassifierNodeData
+from core.workflow.nodes.tool.entities import ToolNodeData
+from extensions.ext_redis import redis_client
+from factories import variable_factory
+from models import Account
+from models.dataset import Dataset, Pipeline
+from models.workflow import Workflow
+from services.dataset_service import DatasetCollectionBindingService
+from services.entities.knowledge_entities.rag_pipeline_entities import KnowledgeConfiguration
+from services.plugin.dependencies_analysis import DependenciesAnalysisService
+from services.rag_pipeline.rag_pipeline import RagPipelineService
+
+logger = logging.getLogger(__name__)
+
+IMPORT_INFO_REDIS_KEY_PREFIX = "app_import_info:"
+CHECK_DEPENDENCIES_REDIS_KEY_PREFIX = "app_check_dependencies:"
+IMPORT_INFO_REDIS_EXPIRY = 10 * 60  # 10 minutes
+DSL_MAX_SIZE = 10 * 1024 * 1024  # 10MB
+CURRENT_DSL_VERSION = "0.1.0"
+
+
+class ImportMode(StrEnum):
+    YAML_CONTENT = "yaml-content"
+    YAML_URL = "yaml-url"
+
+
+class ImportStatus(StrEnum):
+    COMPLETED = "completed"
+    COMPLETED_WITH_WARNINGS = "completed-with-warnings"
+    PENDING = "pending"
+    FAILED = "failed"
+
+
+class RagPipelineImportInfo(BaseModel):
+    id: str
+    status: ImportStatus
+    pipeline_id: Optional[str] = None
+    current_dsl_version: str = CURRENT_DSL_VERSION
+    imported_dsl_version: str = ""
+    error: str = ""
+    dataset_id: Optional[str] = None
+
+
+class CheckDependenciesResult(BaseModel):
+    leaked_dependencies: list[PluginDependency] = Field(default_factory=list)
+
+
+def _check_version_compatibility(imported_version: str) -> ImportStatus:
+    """Determine import status based on version comparison"""
+    try:
+        current_ver = version.parse(CURRENT_DSL_VERSION)
+        imported_ver = version.parse(imported_version)
+    except version.InvalidVersion:
+        return ImportStatus.FAILED
+
+    # If imported version is newer than current, always return PENDING
+    if imported_ver > current_ver:
+        return ImportStatus.PENDING
+
+    # If imported version is older than current's major, return PENDING
+    if imported_ver.major < current_ver.major:
+        return ImportStatus.PENDING
+
+    # If imported version is older than current's minor, return COMPLETED_WITH_WARNINGS
+    if imported_ver.minor < current_ver.minor:
+        return ImportStatus.COMPLETED_WITH_WARNINGS
+
+    # If imported version equals or is older than current's micro, return COMPLETED
+    return ImportStatus.COMPLETED
+
+
+class RagPipelinePendingData(BaseModel):
+    import_mode: str
+    yaml_content: str
+    name: str | None
+    description: str | None
+    icon_type: str | None
+    icon: str | None
+    icon_background: str | None
+    pipeline_id: str | None
+
+
+class CheckDependenciesPendingData(BaseModel):
+    dependencies: list[PluginDependency]
+    pipeline_id: str | None
+
+
+class RagPipelineDslService:
+    def __init__(self, session: Session):
+        self._session = session
+
+    def import_rag_pipeline(
+        self,
+        *,
+        account: Account,
+        import_mode: str,
+        yaml_content: Optional[str] = None,
+        yaml_url: Optional[str] = None,
+        pipeline_id: Optional[str] = None,
+        dataset: Optional[Dataset] = None,
+    ) -> RagPipelineImportInfo:
+        """Import an app from YAML content or URL."""
+        import_id = str(uuid.uuid4())
+
+        # Validate import mode
+        try:
+            mode = ImportMode(import_mode)
+        except ValueError:
+            raise ValueError(f"Invalid import_mode: {import_mode}")
+
+        # Get YAML content
+        content: str = ""
+        if mode == ImportMode.YAML_URL:
+            if not yaml_url:
+                return RagPipelineImportInfo(
+                    id=import_id,
+                    status=ImportStatus.FAILED,
+                    error="yaml_url is required when import_mode is yaml-url",
+                )
+            try:
+                parsed_url = urlparse(yaml_url)
+                if (
+                    parsed_url.scheme == "https"
+                    and parsed_url.netloc == "github.com"
+                    and parsed_url.path.endswith((".yml", ".yaml"))
+                ):
+                    yaml_url = yaml_url.replace("https://github.com", "https://raw.githubusercontent.com")
+                    yaml_url = yaml_url.replace("/blob/", "/")
+                response = ssrf_proxy.get(yaml_url.strip(), follow_redirects=True, timeout=(10, 10))
+                response.raise_for_status()
+                content = response.content.decode()
+
+                if len(content) > DSL_MAX_SIZE:
+                    return RagPipelineImportInfo(
+                        id=import_id,
+                        status=ImportStatus.FAILED,
+                        error="File size exceeds the limit of 10MB",
+                    )
+
+                if not content:
+                    return RagPipelineImportInfo(
+                        id=import_id,
+                        status=ImportStatus.FAILED,
+                        error="Empty content from url",
+                    )
+            except Exception as e:
+                return RagPipelineImportInfo(
+                    id=import_id,
+                    status=ImportStatus.FAILED,
+                    error=f"Error fetching YAML from URL: {str(e)}",
+                )
+        elif mode == ImportMode.YAML_CONTENT:
+            if not yaml_content:
+                return RagPipelineImportInfo(
+                    id=import_id,
+                    status=ImportStatus.FAILED,
+                    error="yaml_content is required when import_mode is yaml-content",
+                )
+            content = yaml_content
+
+        # Process YAML content
+        try:
+            # Parse YAML to validate format
+            data = yaml.safe_load(content)
+            if not isinstance(data, dict):
+                return RagPipelineImportInfo(
+                    id=import_id,
+                    status=ImportStatus.FAILED,
+                    error="Invalid YAML format: content must be a mapping",
+                )
+
+            # Validate and fix DSL version
+            if not data.get("version"):
+                data["version"] = "0.1.0"
+            if not data.get("kind") or data.get("kind") != "rag-pipeline":
+                data["kind"] = "rag-pipeline"
+
+            imported_version = data.get("version", "0.1.0")
+            # check if imported_version is a float-like string
+            if not isinstance(imported_version, str):
+                raise ValueError(f"Invalid version type, expected str, got {type(imported_version)}")
+            status = _check_version_compatibility(imported_version)
+
+            # Extract app data
+            pipeline_data = data.get("pipeline")
+            if not pipeline_data:
+                return RagPipelineImportInfo(
+                    id=import_id,
+                    status=ImportStatus.FAILED,
+                    error="Missing pipeline data in YAML content",
+                )
+
+            # If app_id is provided, check if it exists
+            pipeline = None
+            if pipeline_id:
+                stmt = select(Pipeline).where(
+                    Pipeline.id == pipeline_id,
+                    Pipeline.tenant_id == account.current_tenant_id,
+                )
+                pipeline = self._session.scalar(stmt)
+
+                if not pipeline:
+                    return RagPipelineImportInfo(
+                        id=import_id,
+                        status=ImportStatus.FAILED,
+                        error="Pipeline not found",
+                    )
+
+            # If major version mismatch, store import info in Redis
+            if status == ImportStatus.PENDING:
+                pending_data = RagPipelinePendingData(
+                    import_mode=import_mode,
+                    yaml_content=content,
+                    pipeline_id=pipeline_id,
+                )
+                redis_client.setex(
+                    f"{IMPORT_INFO_REDIS_KEY_PREFIX}{import_id}",
+                    IMPORT_INFO_REDIS_EXPIRY,
+                    pending_data.model_dump_json(),
+                )
+
+                return RagPipelineImportInfo(
+                    id=import_id,
+                    status=status,
+                    pipeline_id=pipeline_id,
+                    imported_dsl_version=imported_version,
+                )
+
+            # Extract dependencies
+            dependencies = data.get("dependencies", [])
+            check_dependencies_pending_data = None
+            if dependencies:
+                check_dependencies_pending_data = [PluginDependency.model_validate(d) for d in dependencies]
+
+            # Create or update app
+            pipeline = self._create_or_update_pipeline(
+                pipeline=pipeline,
+                data=data,
+                account=account,
+                dependencies=check_dependencies_pending_data,
+            )
+            # create dataset
+            name = pipeline.name
+            description = pipeline.description
+            icon_type = data.get("rag_pipeline", {}).get("icon_type")
+            icon = data.get("rag_pipeline", {}).get("icon")
+            icon_background = data.get("rag_pipeline", {}).get("icon_background")
+            icon_url = data.get("rag_pipeline", {}).get("icon_url")
+            workflow = data.get("workflow", {})
+            graph = workflow.get("graph", {})
+            nodes = graph.get("nodes", [])
+            dataset_id = None
+            for node in nodes:
+                if node.get("data", {}).get("type") == "knowledge_index":
+                    knowledge_configuration = node.get("data", {}).get("knowledge_configuration", {})
+                    knowledge_configuration = KnowledgeConfiguration(**knowledge_configuration)
+                    if not dataset:
+                        dataset = Dataset(
+                            tenant_id=account.current_tenant_id,
+                            name=name,
+                            description=description,
+                            icon_info={
+                                "type": icon_type,
+                                "icon": icon,
+                                "background": icon_background,
+                                "url": icon_url,
+                            },
+                            indexing_technique=knowledge_configuration.index_method.indexing_technique,
+                            created_by=account.id,
+                            retrieval_model=knowledge_configuration.retrieval_setting.model_dump(),
+                            runtime_mode="rag_pipeline",
+                            chunk_structure=knowledge_configuration.chunk_structure,
+                        )
+                    else:
+                        dataset.indexing_technique = knowledge_configuration.index_method.indexing_technique
+                        dataset.retrieval_model = knowledge_configuration.retrieval_setting.model_dump()
+                        dataset.runtime_mode = "rag_pipeline"
+                        dataset.chunk_structure = knowledge_configuration.chunk_structure
+                    if knowledge_configuration.index_method.indexing_technique == "high_quality":
+                        dataset_collection_binding = DatasetCollectionBindingService.get_dataset_collection_binding(
+                            knowledge_configuration.index_method.embedding_setting.embedding_provider_name,  # type: ignore
+                            knowledge_configuration.index_method.embedding_setting.embedding_model_name,  # type: ignore
+                        )
+                        dataset_collection_binding_id = dataset_collection_binding.id
+                        dataset.collection_binding_id = dataset_collection_binding_id
+                        dataset.embedding_model = (
+                            knowledge_configuration.index_method.embedding_setting.embedding_model_name
+                        )
+                        dataset.embedding_model_provider = (
+                            knowledge_configuration.index_method.embedding_setting.embedding_provider_name
+                        )
+                    elif knowledge_configuration.index_method.indexing_technique == "economy":
+                        dataset.keyword_number = knowledge_configuration.index_method.economy_setting.keyword_number
+                    dataset.pipeline_id = pipeline.id
+                    self._session.add(dataset)
+                    self._session.commit()
+                    dataset_id = dataset.id
+            if not dataset_id:
+                raise ValueError("DSL is not valid, please check the Knowledge Index node.")
+
+            return RagPipelineImportInfo(
+                id=import_id,
+                status=status,
+                pipeline_id=pipeline.id,
+                dataset_id=dataset_id,
+                imported_dsl_version=imported_version,
+            )
+
+        except yaml.YAMLError as e:
+            return RagPipelineImportInfo(
+                id=import_id,
+                status=ImportStatus.FAILED,
+                error=f"Invalid YAML format: {str(e)}",
+            )
+
+        except Exception as e:
+            logger.exception("Failed to import app")
+            return RagPipelineImportInfo(
+                id=import_id,
+                status=ImportStatus.FAILED,
+                error=str(e),
+            )
+
+    def confirm_import(self, *, import_id: str, account: Account) -> RagPipelineImportInfo:
+        """
+        Confirm an import that requires confirmation
+        """
+        redis_key = f"{IMPORT_INFO_REDIS_KEY_PREFIX}{import_id}"
+        pending_data = redis_client.get(redis_key)
+
+        if not pending_data:
+            return RagPipelineImportInfo(
+                id=import_id,
+                status=ImportStatus.FAILED,
+                error="Import information expired or does not exist",
+            )
+
+        try:
+            if not isinstance(pending_data, str | bytes):
+                return RagPipelineImportInfo(
+                    id=import_id,
+                    status=ImportStatus.FAILED,
+                    error="Invalid import information",
+                )
+            pending_data = RagPipelinePendingData.model_validate_json(pending_data)
+            data = yaml.safe_load(pending_data.yaml_content)
+
+            pipeline = None
+            if pending_data.pipeline_id:
+                stmt = select(Pipeline).where(
+                    Pipeline.id == pending_data.pipeline_id,
+                    Pipeline.tenant_id == account.current_tenant_id,
+                )
+                pipeline = self._session.scalar(stmt)
+
+            # Create or update app
+            pipeline = self._create_or_update_pipeline(
+                pipeline=pipeline,
+                data=data,
+                account=account,
+            )
+
+            # create dataset
+            name = pipeline.name
+            description = pipeline.description
+            icon_type = data.get("rag_pipeline", {}).get("icon_type")
+            icon = data.get("rag_pipeline", {}).get("icon")
+            icon_background = data.get("rag_pipeline", {}).get("icon_background")
+            icon_url = data.get("rag_pipeline", {}).get("icon_url")
+            workflow = data.get("workflow", {})
+            graph = workflow.get("graph", {})
+            nodes = graph.get("nodes", [])
+            dataset_id = None
+            for node in nodes:
+                if node.get("data", {}).get("type") == "knowledge_index":
+                    knowledge_configuration = node.get("data", {}).get("knowledge_configuration", {})
+                    knowledge_configuration = KnowledgeConfiguration(**knowledge_configuration)
+                    if not dataset:
+                        dataset = Dataset(
+                            tenant_id=account.current_tenant_id,
+                            name=name,
+                            description=description,
+                            icon_info={
+                                "type": icon_type,
+                                "icon": icon,
+                                "background": icon_background,
+                                "url": icon_url,
+                            },
+                            indexing_technique=knowledge_configuration.index_method.indexing_technique,
+                            created_by=account.id,
+                            retrieval_model=knowledge_configuration.retrieval_setting.model_dump(),
+                            runtime_mode="rag_pipeline",
+                            chunk_structure=knowledge_configuration.chunk_structure,
+                        )
+                    else:
+                        dataset.indexing_technique = knowledge_configuration.index_method.indexing_technique
+                        dataset.retrieval_model = knowledge_configuration.retrieval_setting.model_dump()
+                        dataset.runtime_mode = "rag_pipeline"
+                        dataset.chunk_structure = knowledge_configuration.chunk_structure
+                    if knowledge_configuration.index_method.indexing_technique == "high_quality":
+                        dataset_collection_binding = DatasetCollectionBindingService.get_dataset_collection_binding(
+                            knowledge_configuration.index_method.embedding_setting.embedding_provider_name,  # type: ignore
+                            knowledge_configuration.index_method.embedding_setting.embedding_model_name,  # type: ignore
+                        )
+                        dataset_collection_binding_id = dataset_collection_binding.id
+                        dataset.collection_binding_id = dataset_collection_binding_id
+                        dataset.embedding_model = (
+                            knowledge_configuration.index_method.embedding_setting.embedding_model_name
+                        )
+                        dataset.embedding_model_provider = (
+                            knowledge_configuration.index_method.embedding_setting.embedding_provider_name
+                        )
+                    elif knowledge_configuration.index_method.indexing_technique == "economy":
+                        dataset.keyword_number = knowledge_configuration.index_method.economy_setting.keyword_number
+                    dataset.pipeline_id = pipeline.id
+                    self._session.add(dataset)
+                    self._session.commit()
+                    dataset_id = dataset.id
+            if not dataset_id:
+                raise ValueError("DSL is not valid, please check the Knowledge Index node.")
+
+            # Delete import info from Redis
+            redis_client.delete(redis_key)
+
+            return RagPipelineImportInfo(
+                id=import_id,
+                status=ImportStatus.COMPLETED,
+                pipeline_id=pipeline.id,
+                dataset_id=dataset_id,
+                current_dsl_version=CURRENT_DSL_VERSION,
+                imported_dsl_version=data.get("version", "0.1.0"),
+            )
+
+        except Exception as e:
+            logger.exception("Error confirming import")
+            return RagPipelineImportInfo(
+                id=import_id,
+                status=ImportStatus.FAILED,
+                error=str(e),
+            )
+
+    def check_dependencies(
+        self,
+        *,
+        pipeline: Pipeline,
+    ) -> CheckDependenciesResult:
+        """Check dependencies"""
+        # Get dependencies from Redis
+        redis_key = f"{CHECK_DEPENDENCIES_REDIS_KEY_PREFIX}{pipeline.id}"
+        dependencies = redis_client.get(redis_key)
+        if not dependencies:
+            return CheckDependenciesResult()
+
+        # Extract dependencies
+        dependencies = CheckDependenciesPendingData.model_validate_json(dependencies)
+
+        # Get leaked dependencies
+        leaked_dependencies = DependenciesAnalysisService.get_leaked_dependencies(
+            tenant_id=pipeline.tenant_id, dependencies=dependencies.dependencies
+        )
+        return CheckDependenciesResult(
+            leaked_dependencies=leaked_dependencies,
+        )
+
+    def _create_or_update_pipeline(
+        self,
+        *,
+        pipeline: Optional[Pipeline],
+        data: dict,
+        account: Account,
+        dependencies: Optional[list[PluginDependency]] = None,
+    ) -> Pipeline:
+        """Create a new app or update an existing one."""
+        pipeline_data = data.get("pipeline", {})
+        pipeline_mode = pipeline_data.get("mode")
+        if not pipeline_mode:
+            raise ValueError("loss pipeline mode")
+        # Set icon type
+        icon_type_value = icon_type or pipeline_data.get("icon_type")
+        if icon_type_value in ["emoji", "link"]:
+            icon_type = icon_type_value
+        else:
+            icon_type = "emoji"
+        icon = icon or str(pipeline_data.get("icon", ""))
+
+        if pipeline:
+            # Update existing pipeline
+            pipeline.name = pipeline_data.get("name", pipeline.name)
+            pipeline.description = pipeline_data.get("description", pipeline.description)
+            pipeline.icon_type = icon_type
+            pipeline.icon = icon
+            pipeline.icon_background = pipeline_data.get("icon_background", pipeline.icon_background)
+            pipeline.updated_by = account.id
+        else:
+            if account.current_tenant_id is None:
+                raise ValueError("Current tenant is not set")
+
+            # Create new app
+            pipeline = Pipeline()
+            pipeline.id = str(uuid4())
+            pipeline.tenant_id = account.current_tenant_id
+            pipeline.mode = pipeline_mode.value
+            pipeline.name = pipeline_data.get("name", "")
+            pipeline.description = pipeline_data.get("description", "")
+            pipeline.icon_type = icon_type
+            pipeline.icon = icon
+            pipeline.icon_background = pipeline_data.get("icon_background", "#FFFFFF")
+            pipeline.enable_site = True
+            pipeline.enable_api = True
+            pipeline.use_icon_as_answer_icon = pipeline_data.get("use_icon_as_answer_icon", False)
+            pipeline.created_by = account.id
+            pipeline.updated_by = account.id
+
+            self._session.add(pipeline)
+            self._session.commit()
+        # save dependencies
+        if dependencies:
+            redis_client.setex(
+                f"{CHECK_DEPENDENCIES_REDIS_KEY_PREFIX}{pipeline.id}",
+                IMPORT_INFO_REDIS_EXPIRY,
+                CheckDependenciesPendingData(pipeline_id=pipeline.id, dependencies=dependencies).model_dump_json(),
+            )
+
+        # Initialize pipeline based on mode
+        workflow_data = data.get("workflow")
+        if not workflow_data or not isinstance(workflow_data, dict):
+            raise ValueError("Missing workflow data for rag pipeline")
+
+        environment_variables_list = workflow_data.get("environment_variables", [])
+        environment_variables = [
+            variable_factory.build_environment_variable_from_mapping(obj) for obj in environment_variables_list
+        ]
+        conversation_variables_list = workflow_data.get("conversation_variables", [])
+        conversation_variables = [
+            variable_factory.build_conversation_variable_from_mapping(obj) for obj in conversation_variables_list
+        ]
+        rag_pipeline_variables_list = workflow_data.get("rag_pipeline_variables", [])
+        rag_pipeline_variables = [
+            variable_factory.build_pipeline_variable_from_mapping(obj) for obj in rag_pipeline_variables_list
+        ]
+
+        rag_pipeline_service = RagPipelineService()
+        current_draft_workflow = rag_pipeline_service.get_draft_workflow(pipeline=pipeline)
+        if current_draft_workflow:
+            unique_hash = current_draft_workflow.unique_hash
+        else:
+            unique_hash = None
+        graph = workflow_data.get("graph", {})
+        for node in graph.get("nodes", []):
+            if node.get("data", {}).get("type", "") == NodeType.KNOWLEDGE_RETRIEVAL.value:
+                dataset_ids = node["data"].get("dataset_ids", [])
+                node["data"]["dataset_ids"] = [
+                    decrypted_id
+                    for dataset_id in dataset_ids
+                    if (
+                        decrypted_id := self.decrypt_dataset_id(
+                            encrypted_data=dataset_id,
+                            tenant_id=pipeline.tenant_id,
+                        )
+                    )
+                ]
+        rag_pipeline_service.sync_draft_workflow(
+            pipeline=pipeline,
+            graph=workflow_data.get("graph", {}),
+            features=workflow_data.get("features", {}),
+            unique_hash=unique_hash,
+            account=account,
+            environment_variables=environment_variables,
+            conversation_variables=conversation_variables,
+        )
+
+        return pipeline
+
+    @classmethod
+    def export_rag_pipeline_dsl(cls, pipeline: Pipeline, include_secret: bool = False) -> str:
+        """
+        Export pipeline
+        :param pipeline: Pipeline instance
+        :param include_secret: Whether include secret variable
+        :return:
+        """
+        export_data = {
+            "version": CURRENT_DSL_VERSION,
+            "kind": "rag_pipeline",
+            "pipeline": {
+                "name": pipeline.name,
+                "mode": pipeline.mode,
+                "icon": "🤖" if pipeline.icon_type == "image" else pipeline.icon,
+                "icon_background": "#FFEAD5" if pipeline.icon_type == "image" else pipeline.icon_background,
+                "description": pipeline.description,
+                "use_icon_as_answer_icon": pipeline.use_icon_as_answer_icon,
+            },
+        }
+
+        cls._append_workflow_export_data(export_data=export_data, pipeline=pipeline, include_secret=include_secret)
+
+        return yaml.dump(export_data, allow_unicode=True)  # type: ignore
+
+    @classmethod
+    def _append_workflow_export_data(cls, *, export_data: dict, pipeline: Pipeline, include_secret: bool) -> None:
+        """
+        Append workflow export data
+        :param export_data: export data
+        :param pipeline: Pipeline instance
+        """
+        rag_pipeline_service = RagPipelineService()
+        workflow = rag_pipeline_service.get_draft_workflow(pipeline=pipeline)
+        if not workflow:
+            raise ValueError("Missing draft workflow configuration, please check.")
+
+        workflow_dict = workflow.to_dict(include_secret=include_secret)
+        for node in workflow_dict.get("graph", {}).get("nodes", []):
+            if node.get("data", {}).get("type", "") == NodeType.KNOWLEDGE_RETRIEVAL.value:
+                dataset_ids = node["data"].get("dataset_ids", [])
+                node["data"]["dataset_ids"] = [
+                    cls.encrypt_dataset_id(dataset_id=dataset_id, tenant_id=pipeline.tenant_id)
+                    for dataset_id in dataset_ids
+                ]
+        export_data["workflow"] = workflow_dict
+        dependencies = cls._extract_dependencies_from_workflow(workflow)
+        export_data["dependencies"] = [
+            jsonable_encoder(d.model_dump())
+            for d in DependenciesAnalysisService.generate_dependencies(
+                tenant_id=pipeline.tenant_id, dependencies=dependencies
+            )
+        ]
+
+    @classmethod
+    def _append_model_config_export_data(cls, export_data: dict, pipeline: Pipeline) -> None:
+        """
+        Append model config export data
+        :param export_data: export data
+        :param pipeline: Pipeline instance
+        """
+        app_model_config = pipeline.app_model_config
+        if not app_model_config:
+            raise ValueError("Missing app configuration, please check.")
+
+        export_data["model_config"] = app_model_config.to_dict()
+        dependencies = cls._extract_dependencies_from_model_config(app_model_config.to_dict())
+        export_data["dependencies"] = [
+            jsonable_encoder(d.model_dump())
+            for d in DependenciesAnalysisService.generate_dependencies(
+                tenant_id=pipeline.tenant_id, dependencies=dependencies
+            )
+        ]
+
+    @classmethod
+    def _extract_dependencies_from_workflow(cls, workflow: Workflow) -> list[str]:
+        """
+        Extract dependencies from workflow
+        :param workflow: Workflow instance
+        :return: dependencies list format like ["langgenius/google"]
+        """
+        graph = workflow.graph_dict
+        dependencies = cls._extract_dependencies_from_workflow_graph(graph)
+        return dependencies
+
+    @classmethod
+    def _extract_dependencies_from_workflow_graph(cls, graph: Mapping) -> list[str]:
+        """
+        Extract dependencies from workflow graph
+        :param graph: Workflow graph
+        :return: dependencies list format like ["langgenius/google"]
+        """
+        dependencies = []
+        for node in graph.get("nodes", []):
+            try:
+                typ = node.get("data", {}).get("type")
+                match typ:
+                    case NodeType.TOOL.value:
+                        tool_entity = ToolNodeData(**node["data"])
+                        dependencies.append(
+                            DependenciesAnalysisService.analyze_tool_dependency(tool_entity.provider_id),
+                        )
+                    case NodeType.LLM.value:
+                        llm_entity = LLMNodeData(**node["data"])
+                        dependencies.append(
+                            DependenciesAnalysisService.analyze_model_provider_dependency(llm_entity.model.provider),
+                        )
+                    case NodeType.QUESTION_CLASSIFIER.value:
+                        question_classifier_entity = QuestionClassifierNodeData(**node["data"])
+                        dependencies.append(
+                            DependenciesAnalysisService.analyze_model_provider_dependency(
+                                question_classifier_entity.model.provider
+                            ),
+                        )
+                    case NodeType.PARAMETER_EXTRACTOR.value:
+                        parameter_extractor_entity = ParameterExtractorNodeData(**node["data"])
+                        dependencies.append(
+                            DependenciesAnalysisService.analyze_model_provider_dependency(
+                                parameter_extractor_entity.model.provider
+                            ),
+                        )
+                    case NodeType.KNOWLEDGE_RETRIEVAL.value:
+                        knowledge_retrieval_entity = KnowledgeRetrievalNodeData(**node["data"])
+                        if knowledge_retrieval_entity.retrieval_mode == "multiple":
+                            if knowledge_retrieval_entity.multiple_retrieval_config:
+                                if (
+                                    knowledge_retrieval_entity.multiple_retrieval_config.reranking_mode
+                                    == "reranking_model"
+                                ):
+                                    if knowledge_retrieval_entity.multiple_retrieval_config.reranking_model:
+                                        dependencies.append(
+                                            DependenciesAnalysisService.analyze_model_provider_dependency(
+                                                knowledge_retrieval_entity.multiple_retrieval_config.reranking_model.provider
+                                            ),
+                                        )
+                                elif (
+                                    knowledge_retrieval_entity.multiple_retrieval_config.reranking_mode
+                                    == "weighted_score"
+                                ):
+                                    if knowledge_retrieval_entity.multiple_retrieval_config.weights:
+                                        vector_setting = (
+                                            knowledge_retrieval_entity.multiple_retrieval_config.weights.vector_setting
+                                        )
+                                        dependencies.append(
+                                            DependenciesAnalysisService.analyze_model_provider_dependency(
+                                                vector_setting.embedding_provider_name
+                                            ),
+                                        )
+                        elif knowledge_retrieval_entity.retrieval_mode == "single":
+                            model_config = knowledge_retrieval_entity.single_retrieval_config
+                            if model_config:
+                                dependencies.append(
+                                    DependenciesAnalysisService.analyze_model_provider_dependency(
+                                        model_config.model.provider
+                                    ),
+                                )
+                    case _:
+                        # TODO: Handle default case or unknown node types
+                        pass
+            except Exception as e:
+                logger.exception("Error extracting node dependency", exc_info=e)
+
+        return dependencies
+
+    @classmethod
+    def _extract_dependencies_from_model_config(cls, model_config: Mapping) -> list[str]:
+        """
+        Extract dependencies from model config
+        :param model_config: model config dict
+        :return: dependencies list format like ["langgenius/google"]
+        """
+        dependencies = []
+
+        try:
+            # completion model
+            model_dict = model_config.get("model", {})
+            if model_dict:
+                dependencies.append(
+                    DependenciesAnalysisService.analyze_model_provider_dependency(model_dict.get("provider", ""))
+                )
+
+            # reranking model
+            dataset_configs = model_config.get("dataset_configs", {})
+            if dataset_configs:
+                for dataset_config in dataset_configs.get("datasets", {}).get("datasets", []):
+                    if dataset_config.get("reranking_model"):
+                        dependencies.append(
+                            DependenciesAnalysisService.analyze_model_provider_dependency(
+                                dataset_config.get("reranking_model", {})
+                                .get("reranking_provider_name", {})
+                                .get("provider")
+                            )
+                        )
+
+            # tools
+            agent_configs = model_config.get("agent_mode", {})
+            if agent_configs:
+                for agent_config in agent_configs.get("tools", []):
+                    dependencies.append(
+                        DependenciesAnalysisService.analyze_tool_dependency(agent_config.get("provider_id"))
+                    )
+
+        except Exception as e:
+            logger.exception("Error extracting model config dependency", exc_info=e)
+
+        return dependencies
+
+    @classmethod
+    def get_leaked_dependencies(cls, tenant_id: str, dsl_dependencies: list[dict]) -> list[PluginDependency]:
+        """
+        Returns the leaked dependencies in current workspace
+        """
+        dependencies = [PluginDependency(**dep) for dep in dsl_dependencies]
+        if not dependencies:
+            return []
+
+        return DependenciesAnalysisService.get_leaked_dependencies(tenant_id=tenant_id, dependencies=dependencies)
+
+    @staticmethod
+    def _generate_aes_key(tenant_id: str) -> bytes:
+        """Generate AES key based on tenant_id"""
+        return hashlib.sha256(tenant_id.encode()).digest()
+
+    @classmethod
+    def encrypt_dataset_id(cls, dataset_id: str, tenant_id: str) -> str:
+        """Encrypt dataset_id using AES-CBC mode"""
+        key = cls._generate_aes_key(tenant_id)
+        iv = key[:16]
+        cipher = AES.new(key, AES.MODE_CBC, iv)
+        ct_bytes = cipher.encrypt(pad(dataset_id.encode(), AES.block_size))
+        return base64.b64encode(ct_bytes).decode()
+
+    @classmethod
+    def decrypt_dataset_id(cls, encrypted_data: str, tenant_id: str) -> str | None:
+        """AES decryption"""
+        try:
+            key = cls._generate_aes_key(tenant_id)
+            iv = key[:16]
+            cipher = AES.new(key, AES.MODE_CBC, iv)
+            pt = unpad(cipher.decrypt(base64.b64decode(encrypted_data)), AES.block_size)
+            return pt.decode()
+        except Exception:
+            return None

api/services/tools/builtin_tools_manage_service.py

@@ -5,6 +5,7 @@ from pathlib import Path
 from sqlalchemy.orm import Session
 
 from configs import dify_config
+from core.datasource.entities.api_entities import DatasourceProviderApiEntity
 from core.helper.position_helper import is_filtered
 from core.model_runtime.utils.encoders import jsonable_encoder
 from core.plugin.entities.plugin import GenericProviderID, ToolProviderID
@@ -16,7 +17,7 @@ from core.tools.tool_label_manager import ToolLabelManager
 from core.tools.tool_manager import ToolManager
 from core.tools.utils.configuration import ProviderConfigEncrypter
 from extensions.ext_database import db
-from models.tools import BuiltinToolProvider
+from models.tools import BuiltinDatasourceProvider, BuiltinToolProvider
 from services.tools.tools_transform_service import ToolTransformService
 
 logger = logging.getLogger(__name__)
@@ -286,6 +287,67 @@ class BuiltinToolManageService:
 
         return BuiltinToolProviderSort.sort(result)
 
+    @staticmethod
+    def list_rag_pipeline_datasources(tenant_id: str) -> list[DatasourceProviderApiEntity]:
+        """
+        list rag pipeline datasources
+        """
+        # get all builtin providers
+        datasource_provider_controllers = ToolManager.list_datasource_providers(tenant_id)
+
+        with db.session.no_autoflush:
+            # get all user added providers
+            db_providers: list[BuiltinDatasourceProvider] = (
+                db.session.query(BuiltinDatasourceProvider)
+                .filter(BuiltinDatasourceProvider.tenant_id == tenant_id)
+                .all()
+                or []
+            )
+
+            # find provider
+            def find_provider(provider):
+                return next(filter(lambda db_provider: db_provider.provider == provider, db_providers), None)
+
+            result: list[DatasourceProviderApiEntity] = []
+
+            for provider_controller in datasource_provider_controllers:
+                try:
+                    # handle include, exclude
+                    if is_filtered(
+                        include_set=dify_config.POSITION_TOOL_INCLUDES_SET,  # type: ignore
+                        exclude_set=dify_config.POSITION_TOOL_EXCLUDES_SET,  # type: ignore
+                        data=provider_controller,
+                        name_func=lambda x: x.identity.name,
+                    ):
+                        continue
+
+                    # convert provider controller to user provider
+                    user_builtin_provider = ToolTransformService.builtin_datasource_provider_to_user_provider(
+                        provider_controller=provider_controller,
+                        db_provider=find_provider(provider_controller.entity.identity.name),
+                        decrypt_credentials=True,
+                    )
+
+                    # add icon
+                    ToolTransformService.repack_provider(tenant_id=tenant_id, provider=user_builtin_provider)
+
+                    datasources = provider_controller.get_datasources()
+                    for datasource in datasources or []:
+                        user_builtin_provider.datasources.append(
+                            ToolTransformService.convert_datasource_entity_to_api_entity(
+                                tenant_id=tenant_id,
+                                datasource=datasource,
+                                credentials=user_builtin_provider.original_credentials,
+                                labels=ToolLabelManager.get_tool_labels(provider_controller),
+                            )
+                        )
+
+                    result.append(user_builtin_provider)
+                except Exception as e:
+                    raise e
+
+        return result
+
     @staticmethod
     def _fetch_builtin_provider(provider_name: str, tenant_id: str) -> BuiltinToolProvider | None:
         try:

api/services/tools/tools_transform_service.py

@@ -5,6 +5,11 @@ from typing import Optional, Union, cast
 from yarl import URL
 
 from configs import dify_config
+from core.datasource.__base.datasource_plugin import DatasourcePlugin
+from core.datasource.__base.datasource_provider import DatasourcePluginProviderController
+from core.datasource.__base.datasource_runtime import DatasourceRuntime
+from core.datasource.entities.api_entities import DatasourceApiEntity, DatasourceProviderApiEntity
+from core.datasource.entities.datasource_entities import DatasourceProviderType
 from core.tools.__base.tool import Tool
 from core.tools.__base.tool_runtime import ToolRuntime
 from core.tools.builtin_tool.provider import BuiltinToolProviderController
@@ -21,7 +26,7 @@ from core.tools.plugin_tool.provider import PluginToolProviderController
 from core.tools.utils.configuration import ProviderConfigEncrypter
 from core.tools.workflow_as_tool.provider import WorkflowToolProviderController
 from core.tools.workflow_as_tool.tool import WorkflowTool
-from models.tools import ApiToolProvider, BuiltinToolProvider, WorkflowToolProvider
+from models.tools import ApiToolProvider, BuiltinDatasourceProvider, BuiltinToolProvider, WorkflowToolProvider
 
 logger = logging.getLogger(__name__)
 
@@ -140,6 +145,64 @@ class ToolTransformService:
 
         return result
 
+    @classmethod
+    def builtin_datasource_provider_to_user_provider(
+        cls,
+        provider_controller: DatasourcePluginProviderController,
+        db_provider: Optional[BuiltinDatasourceProvider],
+        decrypt_credentials: bool = True,
+    ) -> DatasourceProviderApiEntity:
+        """
+        convert provider controller to user provider
+        """
+        result = DatasourceProviderApiEntity(
+            id=provider_controller.entity.identity.name,
+            author=provider_controller.entity.identity.author,
+            name=provider_controller.entity.identity.name,
+            description=provider_controller.entity.identity.description,
+            icon=provider_controller.entity.identity.icon,
+            label=provider_controller.entity.identity.label,
+            type=DatasourceProviderType.RAG_PIPELINE,
+            masked_credentials={},
+            is_team_authorization=False,
+            plugin_id=provider_controller.plugin_id,
+            plugin_unique_identifier=provider_controller.plugin_unique_identifier,
+            datasources=[],
+        )
+
+        # get credentials schema
+        schema = {x.to_basic_provider_config().name: x for x in provider_controller.get_credentials_schema()}
+
+        for name, value in schema.items():
+            if result.masked_credentials:
+                result.masked_credentials[name] = ""
+
+        # check if the provider need credentials
+        if not provider_controller.need_credentials:
+            result.is_team_authorization = True
+            result.allow_delete = False
+        elif db_provider:
+            result.is_team_authorization = True
+
+            if decrypt_credentials:
+                credentials = db_provider.credentials
+
+                # init tool configuration
+                tool_configuration = ProviderConfigEncrypter(
+                    tenant_id=db_provider.tenant_id,
+                    config=[x.to_basic_provider_config() for x in provider_controller.get_credentials_schema()],
+                    provider_type=provider_controller.provider_type.value,
+                    provider_identity=provider_controller.entity.identity.name,
+                )
+                # decrypt the credentials and mask the credentials
+                decrypted_credentials = tool_configuration.decrypt(data=credentials)
+                masked_credentials = tool_configuration.mask_tool_credentials(data=decrypted_credentials)
+
+                result.masked_credentials = masked_credentials
+                result.original_credentials = decrypted_credentials
+
+        return result
+
     @staticmethod
     def api_provider_to_controller(
         db_provider: ApiToolProvider,
@@ -304,3 +367,48 @@ class ToolTransformService:
                 parameters=tool.parameters,
                 labels=labels or [],
             )
+
+    @staticmethod
+    def convert_datasource_entity_to_api_entity(
+        datasource: DatasourcePlugin,
+        tenant_id: str,
+        credentials: dict | None = None,
+        labels: list[str] | None = None,
+    ) -> DatasourceApiEntity:
+        """
+        convert tool to user tool
+        """
+        # fork tool runtime
+        datasource = datasource.fork_datasource_runtime(
+            runtime=DatasourceRuntime(
+                credentials=credentials or {},
+                tenant_id=tenant_id,
+            )
+        )
+
+        # get datasource parameters
+        parameters = datasource.entity.parameters or []
+        # get datasource runtime parameters
+        runtime_parameters = datasource.get_runtime_parameters()
+        # override parameters
+        current_parameters = parameters.copy()
+        for runtime_parameter in runtime_parameters:
+            found = False
+            for index, parameter in enumerate(current_parameters):
+                if parameter.name == runtime_parameter.name and parameter.form == runtime_parameter.form:
+                    current_parameters[index] = runtime_parameter
+                    found = True
+                    break
+
+            if not found and runtime_parameter.form == ToolParameter.ToolParameterForm.FORM:
+                current_parameters.append(runtime_parameter)
+
+        return DatasourceApiEntity(
+            author=datasource.entity.identity.author,
+            name=datasource.entity.identity.name,
+            label=datasource.entity.identity.label,
+            description=datasource.entity.description.human if datasource.entity.description else I18nObject(en_US=""),
+            output_schema=datasource.entity.output_schema,
+            parameters=current_parameters,
+            labels=labels or [],
+        )

api/services/workflow_service.py

@@ -203,7 +203,6 @@ class WorkflowService:
             type=draft_workflow.type,
             version=str(datetime.now(UTC).replace(tzinfo=None)),
             graph=draft_workflow.graph,
-            features=draft_workflow.features,
             created_by=account.id,
             environment_variables=draft_workflow.environment_variables,
             conversation_variables=draft_workflow.conversation_variables,