r2

api/controllers/console/__init__.py

@@ -3,7 +3,6 @@ from flask import Blueprint
 from libs.external_api import ExternalApi
 
 from .app.app_import import AppImportApi, AppImportCheckDependenciesApi, AppImportConfirmApi
-from .datasets.rag_pipeline import data_source
 from .explore.audio import ChatAudioApi, ChatTextApi
 from .explore.completion import ChatApi, ChatStopApi, CompletionApi, CompletionStopApi
 from .explore.conversation import (
@@ -84,6 +83,12 @@ from .datasets import (
     metadata,
     website,
 )
+from .datasets.rag_pipeline import (
+    rag_pipeline,
+    rag_pipeline_datasets,
+    rag_pipeline_import,
+    rag_pipeline_workflow,
+)
 
 # Import explore controllers
 from .explore import (

api/core/rag/index_processor/processor/paragraph_index_processor.py

@@ -12,9 +12,8 @@ from core.rag.docstore.dataset_docstore import DatasetDocumentStore
 from core.rag.extractor.entity.extract_setting import ExtractSetting
 from core.rag.extractor.extract_processor import ExtractProcessor
 from core.rag.index_processor.index_processor_base import BaseIndexProcessor
-from core.rag.models.document import Document
+from core.rag.models.document import Document, GeneralStructureChunk
 from core.tools.utils.text_processing_utils import remove_leading_symbols
-from core.workflow.nodes.knowledge_index.entities import GeneralStructureChunk
 from libs import helper
 from models.dataset import Dataset, DatasetProcessRule
 from services.entities.knowledge_entities.knowledge_entities import Rule

api/core/rag/index_processor/processor/parent_child_index_processor.py

@@ -13,8 +13,7 @@ from core.rag.docstore.dataset_docstore import DatasetDocumentStore
 from core.rag.extractor.entity.extract_setting import ExtractSetting
 from core.rag.extractor.extract_processor import ExtractProcessor
 from core.rag.index_processor.index_processor_base import BaseIndexProcessor
-from core.rag.models.document import ChildDocument, Document
-from core.workflow.nodes.knowledge_index.entities import ParentChildStructureChunk
+from core.rag.models.document import ChildDocument, Document, ParentChildStructureChunk
 from extensions.ext_database import db
 from libs import helper
 from models.dataset import ChildChunk, Dataset, DocumentSegment

api/core/rag/models/document.py

@@ -35,6 +35,31 @@ class Document(BaseModel):
     children: Optional[list[ChildDocument]] = None
 
 
+class GeneralStructureChunk(BaseModel):
+    """
+    General Structure Chunk.
+    """
+
+    general_chunk: list[str]
+
+
+class ParentChildChunk(BaseModel):
+    """
+    Parent Child Chunk.
+    """
+
+    parent_content: str
+    child_contents: list[str]
+
+
+class ParentChildStructureChunk(BaseModel):
+    """
+    Parent Child Structure Chunk.
+    """
+
+    parent_child_chunks: list[ParentChildChunk]
+
+
 class BaseDocumentTransformer(ABC):
     """Abstract base class for document transformation systems.
 

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

@@ -1,3 +1,3 @@
-from .knowledge_index_node import KnowledgeRetrievalNode
+from .knowledge_index_node import KnowledgeIndexNode
 
-__all__ = ["KnowledgeRetrievalNode"]
+__all__ = ["KnowledgeIndexNode"]

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

@@ -1,7 +1,7 @@
 import datetime
 import logging
 import time
-from typing import Any, cast
+from typing import Any, cast, Mapping
 
 from flask_login import current_user
 
@@ -106,7 +106,7 @@ class KnowledgeIndexNode(LLMNode):
                 error_type=type(e).__name__,
             )
 
-    def _invoke_knowledge_index(self, node_data: KnowledgeIndexNodeData, chunks: list[Any]) -> Any:
+    def _invoke_knowledge_index(self, node_data: KnowledgeIndexNodeData, chunks: Mapping[str, Any]) -> Any:
         dataset = Dataset.query.filter_by(id=node_data.dataset_id).first()
         if not dataset:
             raise KnowledgeIndexNodeError(f"Dataset {node_data.dataset_id} not found.")

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

@@ -57,8 +57,7 @@ class MultipleRetrievalConfig(BaseModel):
 
 
 class ModelConfig(BaseModel):
-    """
-    Model Config.
+
 
     provider: str
     name: str

api/fields/workflow_fields.py

@@ -62,10 +62,6 @@ workflow_fields = {
     "tool_published": fields.Boolean,
     "environment_variables": fields.List(EnvironmentVariableField()),
     "conversation_variables": fields.List(fields.Nested(conversation_variable_fields)),
-    "pipeline_variables": fields.Dict(
-        keys=fields.String,
-        values=fields.List(fields.Nested(pipeline_variable_fields)),
-    ),
 }
 
 workflow_partial_fields = {

api/services/rag_pipeline/pipeline_template/database/database_retrieval.py

@@ -2,12 +2,12 @@ from typing import Optional
 
 from extensions.ext_database import db
 from models.dataset import Pipeline, PipelineBuiltInTemplate
-from services.app_dsl_service import AppDslService
-from services.recommend_app.recommend_app_base import RecommendAppRetrievalBase
-from services.recommend_app.recommend_app_type import RecommendAppType
+from services.rag_pipeline.pipeline_template.pipeline_template_base import PipelineTemplateRetrievalBase
+from services.rag_pipeline.pipeline_template.pipeline_template_type import PipelineTemplateType
+#from services.rag_pipeline.rag_pipeline_dsl_service import RagPipelineDslService
 
 
-class DatabasePipelineTemplateRetrieval(RecommendAppRetrievalBase):
+class DatabasePipelineTemplateRetrieval(PipelineTemplateRetrievalBase):
     """
     Retrieval pipeline   template from database
     """
@@ -21,7 +21,7 @@ class DatabasePipelineTemplateRetrieval(RecommendAppRetrievalBase):
         return result
 
     def get_type(self) -> str:
-        return RecommendAppType.DATABASE
+        return PipelineTemplateType.DATABASE
 
     @classmethod
     def fetch_pipeline_templates_from_db(cls, language: str) -> dict:
@@ -61,5 +61,5 @@ class DatabasePipelineTemplateRetrieval(RecommendAppRetrievalBase):
             "name": pipeline.name,
             "icon": pipeline.icon,
             "mode": pipeline.mode,
-            "export_data": AppDslService.export_dsl(app_model=pipeline),
+            "export_data": RagPipelineDslService.export_rag_pipeline_dsl(pipeline=pipeline),
         }

api/services/rag_pipeline/rag_pipeline.py

@@ -13,8 +13,7 @@ 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.repositories.sqlalchemy_workflow_node_execution_repository import SQLAlchemyWorkflowNodeExecutionRepository
 from core.variables.variables import Variable
 from core.workflow.entities.node_entities import NodeRunResult
 from core.workflow.errors import WorkflowNodeRunFailedError
@@ -24,6 +23,7 @@ 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.repository.workflow_node_execution_repository import OrderConfig
 from core.workflow.workflow_entry import WorkflowEntry
 from extensions.ext_database import db
 from libs.infinite_scroll_pagination import InfiniteScrollPagination
@@ -650,13 +650,9 @@ class RagPipelineService:
         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 execution
+        repository = SQLAlchemyWorkflowNodeExecutionRepository(
+            session_factory=db.engine, tenant_id=pipeline.tenant_id, app_id=pipeline.id
         )
 
         # Use the repository to get the node executions with ordering

api/services/rag_pipeline/rag_pipeline_dsl_service.py

@@ -25,12 +25,12 @@ 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_database import db
 from extensions.ext_redis import redis_client
 from factories import variable_factory
 from models import Account
-from models.dataset import Dataset, Pipeline
+from models.dataset import Dataset, DatasetCollectionBinding, 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
@@ -306,6 +306,26 @@ class RagPipelineDslService:
                             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 = (
+                            db.session.query(DatasetCollectionBinding)
+                            .filter(
+                                DatasetCollectionBinding.provider_name == knowledge_configuration.index_method.embedding_setting.embedding_provider_name,
+                                DatasetCollectionBinding.model_name == knowledge_configuration.index_method.embedding_setting.embedding_model_name,
+                                DatasetCollectionBinding.type == "dataset",
+                            )
+                            .order_by(DatasetCollectionBinding.created_at)
+                            .first()
+                        )
+
+                        if not dataset_collection_binding:
+                            dataset_collection_binding = DatasetCollectionBinding(
+                                provider_name=knowledge_configuration.index_method.embedding_setting.embedding_provider_name,
+                                model_name=knowledge_configuration.index_method.embedding_setting.embedding_model_name,
+                                collection_name=Dataset.gen_collection_name_by_id(str(uuid.uuid4())),
+                                type="dataset",
+                            )
+                            db.session.add(dataset_collection_binding)
+                            db.session.commit()
                         dataset_collection_binding_id = dataset_collection_binding.id
                         dataset.collection_binding_id = dataset_collection_binding_id
                         dataset.embedding_model = (