r2

api/controllers/console/auth/data_source_oauth.py

@@ -8,6 +8,7 @@ from werkzeug.exceptions import Forbidden
 
 from configs import dify_config
 from controllers.console import api
+from core.plugin.impl.datasource import PluginDatasourceManager
 from libs.login import login_required
 from libs.oauth_data_source import NotionOAuth
 
@@ -109,7 +110,30 @@ class OAuthDataSourceSync(Resource):
         return {"result": "success"}, 200
 
 
+class DatasourcePluginOauthApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def get(self, datasource_type, datasource_name):
+        # Check user role first
+        if not current_user.is_editor:
+            raise Forbidden()
+        
+        # get all builtin providers
+        manager = PluginDatasourceManager()
+        # Fix: use correct method name or implement the missing method
+        try:
+            providers = manager.get_providers()  # or whatever the correct method is
+            # Filter by datasource_type and datasource_name if needed
+            oauth_config = {}  # Build appropriate OAuth URL response
+            return oauth_config
+        except AttributeError:
+            # Method doesn't exist, return empty response or implement
+            return {"oauth_url": None, "supported": False}
+
+
 api.add_resource(OAuthDataSource, "/oauth/data-source/<string:provider>")
 api.add_resource(OAuthDataSourceCallback, "/oauth/data-source/callback/<string:provider>")
 api.add_resource(OAuthDataSourceBinding, "/oauth/data-source/binding/<string:provider>")
 api.add_resource(OAuthDataSourceSync, "/oauth/data-source/<string:provider>/<uuid:binding_id>/sync")
+api.add_resource(DatasourcePluginOauthApi, "/oauth/plugin/datasource/<string:datasoruce_type>/<string:datasource_name>")

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

@@ -280,6 +280,8 @@ class PublishedRagPipelineRunApi(Resource):
         parser.add_argument("inputs", type=dict, required=True, nullable=False, location="json")
         parser.add_argument("datasource_type", type=str, required=True, location="json")
         parser.add_argument("datasource_info", type=list, required=True, location="json")
+        parser.add_argument("start_node_id", type=str, required=True, location="json")
+        parser.add_argument("is_preview", type=bool, required=True, location="json", default=False)
         args = parser.parse_args()
 
         try:
@@ -287,7 +289,7 @@ class PublishedRagPipelineRunApi(Resource):
                 pipeline=pipeline,
                 user=current_user,
                 args=args,
-                invoke_from=InvokeFrom.PUBLISHED,
+                invoke_from=InvokeFrom.DEBUGGER if args.get("is_preview") else InvokeFrom.PUBLISHED,
                 streaming=True,
             )
 
@@ -469,6 +471,7 @@ class PublishedRagPipelineApi(Resource):
 
         rag_pipeline_service = RagPipelineService()
         with Session(db.engine) as session:
+            pipeline = session.merge(pipeline)
             workflow = rag_pipeline_service.publish_workflow(
                 session=session,
                 pipeline=pipeline,
@@ -478,6 +481,7 @@ class PublishedRagPipelineApi(Resource):
             )
             pipeline.is_published = True
             pipeline.workflow_id = workflow.id
+            session.add(pipeline)
             workflow_created_at = TimestampField().format(workflow.created_at)
 
             session.commit()
@@ -797,6 +801,10 @@ api.add_resource(
     DraftRagPipelineRunApi,
     "/rag/pipelines/<uuid:pipeline_id>/workflows/draft/run",
 )
+api.add_resource(
+    PublishedRagPipelineRunApi,
+    "/rag/pipelines/<uuid:pipeline_id>/workflows/published/run",
+)
 api.add_resource(
     RagPipelineTaskStopApi,
     "/rag/pipelines/<uuid:pipeline_id>/workflow-runs/tasks/<string:task_id>/stop",

api/core/app/apps/pipeline/pipeline_generator.py

@@ -92,7 +92,7 @@ class PipelineGenerator(BaseAppGenerator):
         streaming: bool = True,
         call_depth: int = 0,
         workflow_thread_pool_id: Optional[str] = None,
-    ) -> Union[Mapping[str, Any], Generator[Mapping | str, None, None], None]:
+    ) -> Union[Mapping[str, Any], Generator[Mapping | str, None, None]]:
         # convert to app config
         pipeline_config = PipelineConfigManager.get_pipeline_config(
             pipeline=pipeline,
@@ -108,23 +108,24 @@ class PipelineGenerator(BaseAppGenerator):
         for datasource_info in datasource_info_list:
             workflow_run_id = str(uuid.uuid4())
             document_id = None
-            dataset = pipeline.dataset
-            if not dataset:
-                raise ValueError("Dataset not found")
+            
+            # Add null check for dataset
+            if not pipeline.dataset:
+                raise ValueError("Pipeline dataset is required")
+            
             if invoke_from == InvokeFrom.PUBLISHED:
-                position = DocumentService.get_documents_position(pipeline.dataset_id)
                 position = DocumentService.get_documents_position(pipeline.dataset_id)
                 document = self._build_document(
                     tenant_id=pipeline.tenant_id,
                     dataset_id=pipeline.dataset_id,
-                    built_in_field_enabled=dataset.built_in_field_enabled,
+                    built_in_field_enabled=pipeline.dataset.built_in_field_enabled,
                     datasource_type=datasource_type,
                     datasource_info=datasource_info,
                     created_from="rag-pipeline",
                     position=position,
                     account=user,
                     batch=batch,
-                    document_form=dataset.chunk_structure,
+                    document_form=pipeline.dataset.chunk_structure,
                 )
                 db.session.add(document)
                 db.session.commit()
@@ -136,7 +137,7 @@ class PipelineGenerator(BaseAppGenerator):
                 pipeline_config=pipeline_config,
                 datasource_type=datasource_type,
                 datasource_info=datasource_info,
-                dataset_id=dataset.id,
+                dataset_id=pipeline.dataset.id,
                 start_node_id=start_node_id,
                 batch=batch,
                 document_id=document_id,
@@ -274,27 +275,24 @@ class PipelineGenerator(BaseAppGenerator):
             raise ValueError("inputs is required")
 
         # convert to app config
-        pipeline_config = PipelineConfigManager.get_pipeline_config(pipeline=pipeline, workflow=workflow)
+        app_config = PipelineConfigManager.get_pipeline_config(pipeline=pipeline, workflow=workflow)
 
-        # init application generate entity
+        # init application generate entity - use RagPipelineGenerateEntity instead
         application_generate_entity = RagPipelineGenerateEntity(
             task_id=str(uuid.uuid4()),
-            app_config=pipeline_config,
-            pipeline_config=pipeline_config,
-            datasource_type=args["datasource_type"],
-            datasource_info=args["datasource_info"],
+            app_config=app_config,
+            pipeline_config=app_config,
+            datasource_type=args.get("datasource_type", ""),
+            datasource_info=args.get("datasource_info", {}),
             dataset_id=pipeline.dataset_id,
-            batch=args["batch"],
-            document_id=args["document_id"],
+            batch=args.get("batch", ""),
+            document_id=args.get("document_id"),
             inputs={},
             files=[],
             user_id=user.id,
             stream=streaming,
             invoke_from=InvokeFrom.DEBUGGER,
-            extras={"auto_generate_conversation_name": False},
-            single_iteration_run=WorkflowAppGenerateEntity.SingleIterationRunEntity(
-                node_id=node_id, inputs=args["inputs"]
-            ),
+            call_depth=0,
             workflow_run_id=str(uuid.uuid4()),
         )
         contexts.tenant_id.set(application_generate_entity.app_config.tenant_id)

api/core/app/apps/pipeline/pipeline_runner.py

@@ -104,6 +104,7 @@ class PipelineRunner(WorkflowBasedAppRunner):
                 SystemVariableKey.DATASET_ID: self.application_generate_entity.dataset_id,
                 SystemVariableKey.DATASOURCE_TYPE: self.application_generate_entity.datasource_type,
                 SystemVariableKey.DATASOURCE_INFO: self.application_generate_entity.datasource_info,
+                SystemVariableKey.INVOKE_FROM: self.application_generate_entity.invoke_from,
             }
 
             variable_pool = VariablePool(

api/core/plugin/impl/datasource.py

@@ -1,12 +1,11 @@
 from collections.abc import Mapping
 from typing import Any
 
-from core.datasource.entities.api_entities import DatasourceProviderApiEntity
 from core.datasource.entities.datasource_entities import (
     GetOnlineDocumentPageContentRequest,
     GetOnlineDocumentPageContentResponse,
     GetOnlineDocumentPagesResponse,
-    GetWebsiteCrawlResponse, DatasourceProviderEntity,
+    GetWebsiteCrawlResponse,
 )
 from core.plugin.entities.plugin import GenericProviderID, ToolProviderID
 from core.plugin.entities.plugin_daemon import (
@@ -228,7 +227,30 @@ class PluginDatasourceManager(BasePluginClient):
             return resp.result
 
         return False
+    
+    def get_provider_oauth_url(self, datasource_type: str, datasource_name: str, provider: str) -> str:
+        """
+        get the oauth url of the provider
+        """
+        tool_provider_id = GenericProviderID(provider)
 
+        response = self._request_with_plugin_daemon_response_stream(
+            "GET",
+            f"plugin/datasource/oauth",
+            PluginBasicBooleanResponse,
+            params={"page": 1, "page_size": 256},
+            headers={
+                "X-Plugin-ID": tool_provider_id.plugin_id,
+                "Content-Type": "application/json",
+            },
+
+        )
+
+        for resp in response:
+            return resp.result
+
+        return False
+    
     def _get_local_file_datasource_provider(self) -> dict[str, Any]:
         return {
             "id": "langgenius/file/file",

api/core/workflow/enums.py

@@ -20,3 +20,4 @@ class SystemVariableKey(StrEnum):
     DATASET_ID = "dataset_id"
     DATASOURCE_TYPE = "datasource_type"
     DATASOURCE_INFO = "datasource_info"
+    INVOKE_FROM = "invoke_from"

api/core/workflow/nodes/datasource/datasource_node.py

@@ -17,7 +17,6 @@ from core.workflow.entities.variable_pool import VariablePool
 from core.workflow.enums import SystemVariableKey
 from core.workflow.nodes.base import BaseNode
 from core.workflow.nodes.enums import NodeType
-from core.workflow.nodes.event import RunCompletedEvent
 from core.workflow.utils.variable_template_parser import VariableTemplateParser
 from models.workflow import WorkflowNodeExecutionStatus
 
@@ -33,7 +32,7 @@ class DatasourceNode(BaseNode[DatasourceNodeData]):
     _node_data_cls = DatasourceNodeData
     _node_type = NodeType.DATASOURCE
 
-    def _run(self) -> Generator:
+    def _run(self) -> NodeRunResult:
         """
         Run the datasource node
         """
@@ -58,21 +57,19 @@ class DatasourceNode(BaseNode[DatasourceNodeData]):
 
             datasource_runtime = DatasourceManager.get_datasource_runtime(
                 provider_id=node_data.provider_id,
-                datasource_name=node_data.datasource_name,
+                datasource_name=node_data.datasource_name or "",
                 tenant_id=self.tenant_id,
                 datasource_type=DatasourceProviderType(datasource_type),
             )
         except DatasourceNodeError as e:
-            yield RunCompletedEvent(
-                run_result=NodeRunResult(
+            return NodeRunResult(
                     status=WorkflowNodeExecutionStatus.FAILED,
                     inputs={},
                     metadata={NodeRunMetadataKey.DATASOURCE_INFO: datasource_info},
                     error=f"Failed to get datasource runtime: {str(e)}",
                     error_type=type(e).__name__,
                 )
-            )
-            return
+            
 
         # get parameters
         datasource_parameters = datasource_runtime.entity.parameters
@@ -99,66 +96,55 @@ class DatasourceNode(BaseNode[DatasourceNodeData]):
                             provider_type=datasource_type,
                         )
                     )
-                    yield RunCompletedEvent(
-                        run_result=NodeRunResult(
-                            status=WorkflowNodeExecutionStatus.SUCCEEDED,
-                            inputs=parameters_for_log,
-                            metadata={NodeRunMetadataKey.DATASOURCE_INFO: datasource_info},
-                            outputs={
-                                "online_document": online_document_result.result.model_dump(),
-                                "datasource_type": datasource_type,
-                            },
-                        )
+                    return NodeRunResult(
+                        status=WorkflowNodeExecutionStatus.SUCCEEDED,
+                        inputs=parameters_for_log,
+                        metadata={NodeRunMetadataKey.DATASOURCE_INFO: datasource_info},
+                        outputs={
+                            "online_document": online_document_result.result.model_dump(),
+                            "datasource_type": datasource_type,
+                        },
                     )
                 case DatasourceProviderType.WEBSITE_CRAWL | DatasourceProviderType.LOCAL_FILE:
-                    yield RunCompletedEvent(
-                        run_result=NodeRunResult(
-                            status=WorkflowNodeExecutionStatus.SUCCEEDED,
-                            inputs=parameters_for_log,
-                            metadata={NodeRunMetadataKey.DATASOURCE_INFO: datasource_info},
-                            outputs={
+                    return NodeRunResult(
+                        status=WorkflowNodeExecutionStatus.SUCCEEDED,
+                        inputs=parameters_for_log,
+                        metadata={NodeRunMetadataKey.DATASOURCE_INFO: datasource_info},
+                        outputs={
                                 "website": datasource_info,
                                 "datasource_type": datasource_type,
-                            },
-                        )
+                        },
                     )
                 case DatasourceProviderType.LOCAL_FILE:
-                    yield RunCompletedEvent(
-                        run_result=NodeRunResult(
-                            status=WorkflowNodeExecutionStatus.SUCCEEDED,
-                            inputs=parameters_for_log,
-                            metadata={NodeRunMetadataKey.DATASOURCE_INFO: datasource_info},
-                            outputs={
+                    return NodeRunResult(
+                        status=WorkflowNodeExecutionStatus.SUCCEEDED,
+                        inputs=parameters_for_log,
+                        metadata={NodeRunMetadataKey.DATASOURCE_INFO: datasource_info},
+                        outputs={
                                 "file": datasource_info,
                                 "datasource_type": datasource_runtime.datasource_provider_type,
                             },
                         )
-                    )
                 case _:
                     raise DatasourceNodeError(
                         f"Unsupported datasource provider: {datasource_runtime.datasource_provider_type}"
                     )
         except PluginDaemonClientSideError as e:
-            yield RunCompletedEvent(
-                run_result=NodeRunResult(
-                    status=WorkflowNodeExecutionStatus.FAILED,
-                    inputs=parameters_for_log,
-                    metadata={NodeRunMetadataKey.DATASOURCE_INFO: datasource_info},
-                    error=f"Failed to transform datasource message: {str(e)}",
-                    error_type=type(e).__name__,
-                )
+            return NodeRunResult(
+                status=WorkflowNodeExecutionStatus.FAILED,
+                inputs=parameters_for_log,
+                metadata={NodeRunMetadataKey.DATASOURCE_INFO: datasource_info},
+                error=f"Failed to transform datasource message: {str(e)}",
+                error_type=type(e).__name__,
             )
         except DatasourceNodeError as e:
-            yield RunCompletedEvent(
-                run_result=NodeRunResult(
-                    status=WorkflowNodeExecutionStatus.FAILED,
-                    inputs=parameters_for_log,
-                    metadata={NodeRunMetadataKey.DATASOURCE_INFO: datasource_info},
-                    error=f"Failed to invoke datasource: {str(e)}",
-                    error_type=type(e).__name__,
-                )
+            return NodeRunResult(
+                status=WorkflowNodeExecutionStatus.FAILED,
+                inputs=parameters_for_log,
+                metadata={NodeRunMetadataKey.DATASOURCE_INFO: datasource_info},
+                error=f"Failed to invoke datasource: {str(e)}",
+                error_type=type(e).__name__,
             )
-            return
 
     def _generate_parameters(
         self,
@@ -225,18 +211,19 @@ class DatasourceNode(BaseNode[DatasourceNodeData]):
         :return:
         """
         result = {}
-        for parameter_name in node_data.datasource_parameters:
-            input = node_data.datasource_parameters[parameter_name]
-            if input.type == "mixed":
-                assert isinstance(input.value, str)
-                selectors = VariableTemplateParser(input.value).extract_variable_selectors()
-                for selector in selectors:
-                    result[selector.variable] = selector.value_selector
-            elif input.type == "variable":
-                result[parameter_name] = input.value
-            elif input.type == "constant":
-                pass
+        if node_data.datasource_parameters:
+            for parameter_name in node_data.datasource_parameters:
+                input = node_data.datasource_parameters[parameter_name]
+                if input.type == "mixed":
+                    assert isinstance(input.value, str)
+                    selectors = VariableTemplateParser(input.value).extract_variable_selectors()
+                    for selector in selectors:
+                        result[selector.variable] = selector.value_selector
+                elif input.type == "variable":
+                    result[parameter_name] = input.value
+                elif input.type == "constant":
+                    pass
 
-        result = {node_id + "." + key: value for key, value in result.items()}
+            result = {node_id + "." + key: value for key, value in result.items()}
 
         return result

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

@@ -1,4 +1,4 @@
-from typing import Any, Literal, Union, Optional
+from typing import Any, Literal, Optional, Union
 
 from pydantic import BaseModel, field_validator
 from pydantic_core.core_schema import ValidationInfo

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

@@ -3,6 +3,7 @@ import logging
 from collections.abc import Mapping
 from typing import Any, cast
 
+from core.app.entities.app_invoke_entities import InvokeFrom
 from core.rag.index_processor.index_processor_factory import IndexProcessorFactory
 from core.rag.retrieval.retrieval_methods import RetrievalMethod
 from core.variables.segments import ObjectSegment
@@ -10,16 +11,15 @@ from core.workflow.entities.node_entities import NodeRunResult
 from core.workflow.entities.variable_pool import VariablePool
 from core.workflow.enums import SystemVariableKey
 from core.workflow.nodes.enums import NodeType
-from core.workflow.nodes.llm.node import LLMNode
 from extensions.ext_database import db
 from models.dataset import Dataset, Document
 from models.workflow import WorkflowNodeExecutionStatus
 
+from ..base import BaseNode
 from .entities import KnowledgeIndexNodeData
 from .exc import (
     KnowledgeIndexNodeError,
 )
-from ..base import BaseNode
 
 logger = logging.getLogger(__name__)
 
@@ -41,6 +41,7 @@ class KnowledgeIndexNode(BaseNode[KnowledgeIndexNodeData]):
         variable_pool = self.graph_runtime_state.variable_pool
         # extract variables
         variable = variable_pool.get(node_data.index_chunk_variable_selector)
+        is_preview = variable_pool.get(["sys", SystemVariableKey.INVOKE_FROM]) == InvokeFrom.DEBUGGER
         if not isinstance(variable, ObjectSegment):
             return NodeRunResult(
                 status=WorkflowNodeExecutionStatus.FAILED,
@@ -55,6 +56,13 @@ class KnowledgeIndexNode(BaseNode[KnowledgeIndexNodeData]):
             )
         # retrieve knowledge
         try:
+            if is_preview:
+                return NodeRunResult(
+                    status=WorkflowNodeExecutionStatus.SUCCEEDED,
+                    inputs=variables,
+                    process_data=None,
+                    outputs={"result": "success"},
+                )
             results = self._invoke_knowledge_index(node_data=node_data, chunks=chunks, variable_pool=variable_pool)
             outputs = {"result": results}
             return NodeRunResult(
@@ -90,15 +98,15 @@ class KnowledgeIndexNode(BaseNode[KnowledgeIndexNodeData]):
         batch = variable_pool.get(["sys", SystemVariableKey.BATCH])
         if not batch:
             raise KnowledgeIndexNodeError("Batch is required.")
-        dataset = Dataset.query.filter_by(id=dataset_id).first()
+        dataset = db.session.query(Dataset).filter_by(id=dataset_id).first()
         if not dataset:
             raise KnowledgeIndexNodeError(f"Dataset {dataset_id} not found.")
 
-        document = Document.query.filter_by(id=document_id).first()
+        document = db.session.query(Document).filter_by(id=document_id).first()
         if not document:
             raise KnowledgeIndexNodeError(f"Document {document_id} not found.")
 
-        index_processor = IndexProcessorFactory(node_data.chunk_structure).init_index_processor()
+        index_processor = IndexProcessorFactory(dataset.chunk_structure).init_index_processor()
         index_processor.index(dataset, document, chunks)
 
         # update document status

api/services/dataset_service.py

@@ -270,7 +270,7 @@ class DatasetService:
             permission=rag_pipeline_dataset_create_entity.permission,
             provider="vendor",
             runtime_mode="rag_pipeline",
-            icon_info=rag_pipeline_dataset_create_entity.icon_info,
+            icon_info=rag_pipeline_dataset_create_entity.icon_info.model_dump(),
             created_by=current_user.id,
             pipeline_id=pipeline.id,
         )
@@ -299,7 +299,7 @@ class DatasetService:
             permission=rag_pipeline_dataset_create_entity.permission,
             provider="vendor",
             runtime_mode="rag-pipeline",
-            icon_info=rag_pipeline_dataset_create_entity.icon_info,
+            icon_info=rag_pipeline_dataset_create_entity.icon_info.model_dump(),
         )
         with Session(db.engine) as session:
             rag_pipeline_dsl_service = RagPipelineDslService(session)

api/services/entities/knowledge_entities/rag_pipeline_entities.py

@@ -21,8 +21,8 @@ class RagPipelineDatasetCreateEntity(BaseModel):
     description: str
     icon_info: IconInfo
     permission: str
-    partial_member_list: list[str]
-    yaml_content: str
+    partial_member_list: Optional[list[str]] = None
+    yaml_content: Optional[str] = None
 
 
 class RerankingModelConfig(BaseModel):