mirror of https://github.com/langgenius/dify.git
Merge branch 'feat/r2' into deploy/rag-dev
This commit is contained in:
commit
d3e29ffa74
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@ -301,7 +301,7 @@ class PublishedRagPipelineRunApi(Resource):
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raise InvokeRateLimitHttpError(ex.description)
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class RagPipelineDatasourceNodeRunApi(Resource):
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class RagPipelinePublishedDatasourceNodeRunApi(Resource):
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@setup_required
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@login_required
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@account_initialization_required
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@ -336,10 +336,50 @@ class RagPipelineDatasourceNodeRunApi(Resource):
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user_inputs=inputs,
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account=current_user,
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datasource_type=datasource_type,
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is_published=True
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)
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return result
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class RagPipelineDrafDatasourceNodeRunApi(Resource):
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@setup_required
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@login_required
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@account_initialization_required
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@get_rag_pipeline
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def post(self, pipeline: Pipeline, node_id: str):
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"""
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Run rag pipeline datasource
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"""
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# The role of the current user in the ta table must be admin, owner, or editor
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if not current_user.is_editor:
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raise Forbidden()
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if not isinstance(current_user, Account):
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raise Forbidden()
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parser = reqparse.RequestParser()
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parser.add_argument("inputs", type=dict, required=True, nullable=False, location="json")
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parser.add_argument("datasource_type", type=str, required=True, location="json")
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args = parser.parse_args()
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inputs = args.get("inputs")
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if inputs == None:
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raise ValueError("missing inputs")
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datasource_type = args.get("datasource_type")
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if datasource_type == None:
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raise ValueError("missing datasource_type")
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rag_pipeline_service = RagPipelineService()
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result = rag_pipeline_service.run_datasource_workflow_node(
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pipeline=pipeline,
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node_id=node_id,
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user_inputs=inputs,
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account=current_user,
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datasource_type=datasource_type,
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is_published=False
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)
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return result
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class RagPipelinePublishedNodeRunApi(Resource):
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@setup_required
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@ -851,8 +891,13 @@ api.add_resource(
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"/rag/pipelines/<uuid:pipeline_id>/workflows/draft/nodes/<string:node_id>/run",
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)
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api.add_resource(
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RagPipelineDatasourceNodeRunApi,
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"/rag/pipelines/<uuid:pipeline_id>/workflows/datasource/nodes/<string:node_id>/run",
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RagPipelinePublishedDatasourceNodeRunApi,
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"/rag/pipelines/<uuid:pipeline_id>/workflows/published/datasource/nodes/<string:node_id>/run",
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)
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api.add_resource(
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RagPipelineDrafDatasourceNodeRunApi,
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"/rag/pipelines/<uuid:pipeline_id>/workflows/draft/datasource/nodes/<string:node_id>/run",
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)
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api.add_resource(
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@ -414,27 +414,30 @@ class RagPipelineService:
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return workflow_node_execution
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def run_datasource_workflow_node(
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self, pipeline: Pipeline, node_id: str, user_inputs: dict, account: Account, datasource_type: str
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self, pipeline: Pipeline, node_id: str, user_inputs: dict, account: Account, datasource_type: str, is_published: bool
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) -> dict:
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"""
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Run published workflow datasource
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"""
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if is_published:
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# fetch published workflow by app_model
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published_workflow = self.get_published_workflow(pipeline=pipeline)
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if not published_workflow:
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workflow = self.get_published_workflow(pipeline=pipeline)
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else:
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workflow = self.get_draft_workflow(pipeline=pipeline)
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if not workflow:
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raise ValueError("Workflow not initialized")
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# run draft workflow node
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datasource_node_data = None
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start_at = time.perf_counter()
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datasource_nodes = published_workflow.graph_dict.get("nodes", [])
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datasource_nodes = workflow.graph_dict.get("nodes", [])
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for datasource_node in datasource_nodes:
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if datasource_node.get("id") == node_id:
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datasource_node_data = datasource_node.get("data", {})
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break
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if not datasource_node_data:
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raise ValueError("Datasource node data not found")
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datasource_parameters = datasource_node_data.get("datasource_parameters", {})
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for key, value in datasource_parameters.items():
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if not user_inputs.get(key):
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@ -651,7 +654,7 @@ class RagPipelineService:
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if item.get("belong_to_node_id") == node_id or item.get("belong_to_node_id") == "shared"
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]
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return datasource_provider_variables
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def get_published_first_step_parameters(self, pipeline: Pipeline, node_id: str) -> list[dict]:
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"""
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Get first step parameters of rag pipeline
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@ -683,7 +686,7 @@ class RagPipelineService:
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if not re.match(r"\{\{#([a-zA-Z0-9_]{1,50}(?:\.[a-zA-Z_][a-zA-Z0-9_]{0,29}){1,10})#\}\}", value["value"]):
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user_input_variables.append(variables_map.get(key, {}))
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return user_input_variables
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def get_draft_first_step_parameters(self, pipeline: Pipeline, node_id: str) -> list[dict]:
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"""
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Get first step parameters of rag pipeline
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