From c2473d85dcc5bcb4660d17860d109e98c0c1fabf Mon Sep 17 00:00:00 2001 From: FFXN <31929997+FFXN@users.noreply.github.com> Date: Thu, 29 Jan 2026 13:47:35 +0800 Subject: [PATCH 01/15] feat: Add summary index for knowledge. (#31625) Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com> Co-authored-by: Jyong <76649700+JohnJyong@users.noreply.github.com> Co-authored-by: zxhlyh Co-authored-by: Yansong Zhang <916125788@qq.com> Co-authored-by: hj24 Co-authored-by: CodingOnStar Co-authored-by: CodingOnStar Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com> --- api/.importlinter | 3 + api/controllers/console/datasets/datasets.py | 10 +- .../console/datasets/datasets_document.py | 149 ++ .../console/datasets/datasets_segments.py | 37 +- .../console/datasets/hit_testing.py | 43 +- .../service_api/dataset/dataset.py | 2 + .../service_api/dataset/document.py | 21 + .../base_app_generate_response_converter.py | 1 + api/core/entities/knowledge_entities.py | 1 + api/core/indexing_runner.py | 10 + api/core/llm_generator/prompts.py | 17 + api/core/rag/datasource/retrieval_service.py | 140 +- api/core/rag/embedding/retrieval.py | 1 + api/core/rag/entities/citation_metadata.py | 1 + .../index_processor/index_processor_base.py | 12 + .../processor/paragraph_index_processor.py | 369 ++++- .../processor/parent_child_index_processor.py | 118 ++ .../processor/qa_index_processor.py | 41 +- api/core/rag/retrieval/dataset_retrieval.py | 29 +- .../dataset_retriever_tool.py | 29 +- .../nodes/knowledge_index/entities.py | 2 + .../knowledge_index/knowledge_index_node.py | 328 +++- .../knowledge_retrieval_node.py | 3 + api/core/workflow/nodes/llm/node.py | 3 + api/extensions/ext_celery.py | 2 + api/fields/dataset_fields.py | 9 + api/fields/document_fields.py | 9 + api/fields/hit_testing_fields.py | 1 + api/fields/message_fields.py | 1 + api/fields/segment_fields.py | 1 + ...-788d3099ae3a_add_summary_index_feature.py | 107 ++ api/models/dataset.py | 35 + api/services/dataset_service.py | 272 ++++ .../knowledge_entities/knowledge_entities.py | 2 + .../rag_pipeline_entities.py | 2 + .../rag_pipeline/rag_pipeline_dsl_service.py | 6 + api/services/summary_index_service.py | 1432 +++++++++++++++++ api/tasks/add_document_to_index_task.py | 13 + api/tasks/batch_clean_document_task.py | 4 +- api/tasks/clean_document_task.py | 4 +- api/tasks/clean_notion_document_task.py | 4 +- api/tasks/delete_segment_from_index_task.py | 2 + api/tasks/disable_segment_from_index_task.py | 12 + api/tasks/disable_segments_from_index_task.py | 15 + api/tasks/document_indexing_task.py | 73 + api/tasks/enable_segment_to_index_task.py | 11 + api/tasks/enable_segments_to_index_task.py | 12 + api/tasks/generate_summary_index_task.py | 119 ++ api/tasks/regenerate_summary_index_task.py | 315 ++++ api/tasks/remove_document_from_index_task.py | 15 + .../test_dataset_service_update_dataset.py | 9 + 51 files changed, 3797 insertions(+), 60 deletions(-) create mode 100644 api/migrations/versions/2026_01_27_1815-788d3099ae3a_add_summary_index_feature.py create mode 100644 api/services/summary_index_service.py create mode 100644 api/tasks/generate_summary_index_task.py create mode 100644 api/tasks/regenerate_summary_index_task.py diff --git a/api/.importlinter b/api/.importlinter index 2b4a3a5bd6..ff0577222e 100644 --- a/api/.importlinter +++ b/api/.importlinter @@ -227,6 +227,9 @@ ignore_imports = core.workflow.nodes.knowledge_index.entities -> core.rag.retrieval.retrieval_methods core.workflow.nodes.knowledge_index.knowledge_index_node -> core.rag.retrieval.retrieval_methods core.workflow.nodes.knowledge_index.knowledge_index_node -> models.dataset + core.workflow.nodes.knowledge_index.knowledge_index_node -> services.summary_index_service + core.workflow.nodes.knowledge_index.knowledge_index_node -> tasks.generate_summary_index_task + core.workflow.nodes.knowledge_index.knowledge_index_node -> core.rag.index_processor.processor.paragraph_index_processor core.workflow.nodes.knowledge_retrieval.knowledge_retrieval_node -> core.rag.retrieval.retrieval_methods core.workflow.nodes.llm.node -> models.dataset core.workflow.nodes.agent.agent_node -> core.tools.utils.message_transformer diff --git a/api/controllers/console/datasets/datasets.py b/api/controllers/console/datasets/datasets.py index 8fbbc51e21..30e4ed1119 100644 --- a/api/controllers/console/datasets/datasets.py +++ b/api/controllers/console/datasets/datasets.py @@ -148,6 +148,7 @@ class DatasetUpdatePayload(BaseModel): embedding_model: str | None = None embedding_model_provider: str | None = None retrieval_model: dict[str, Any] | None = None + summary_index_setting: dict[str, Any] | None = None partial_member_list: list[dict[str, str]] | None = None external_retrieval_model: dict[str, Any] | None = None external_knowledge_id: str | None = None @@ -288,7 +289,14 @@ class DatasetListApi(Resource): @enterprise_license_required def get(self): current_user, current_tenant_id = current_account_with_tenant() - query = ConsoleDatasetListQuery.model_validate(request.args.to_dict()) + # Convert query parameters to dict, handling list parameters correctly + query_params: dict[str, str | list[str]] = dict(request.args.to_dict()) + # Handle ids and tag_ids as lists (Flask request.args.getlist returns list even for single value) + if "ids" in request.args: + query_params["ids"] = request.args.getlist("ids") + if "tag_ids" in request.args: + query_params["tag_ids"] = request.args.getlist("tag_ids") + query = ConsoleDatasetListQuery.model_validate(query_params) # provider = request.args.get("provider", default="vendor") if query.ids: datasets, total = DatasetService.get_datasets_by_ids(query.ids, current_tenant_id) diff --git a/api/controllers/console/datasets/datasets_document.py b/api/controllers/console/datasets/datasets_document.py index 57fb9abf29..6e3c0db8a3 100644 --- a/api/controllers/console/datasets/datasets_document.py +++ b/api/controllers/console/datasets/datasets_document.py @@ -45,6 +45,7 @@ from models.dataset import DocumentPipelineExecutionLog from services.dataset_service import DatasetService, DocumentService from services.entities.knowledge_entities.knowledge_entities import KnowledgeConfig, ProcessRule, RetrievalModel from services.file_service import FileService +from tasks.generate_summary_index_task import generate_summary_index_task from ..app.error import ( ProviderModelCurrentlyNotSupportError, @@ -103,6 +104,10 @@ class DocumentRenamePayload(BaseModel): name: str +class GenerateSummaryPayload(BaseModel): + document_list: list[str] + + class DocumentBatchDownloadZipPayload(BaseModel): """Request payload for bulk downloading documents as a zip archive.""" @@ -125,6 +130,7 @@ register_schema_models( RetrievalModel, DocumentRetryPayload, DocumentRenamePayload, + GenerateSummaryPayload, DocumentBatchDownloadZipPayload, ) @@ -312,6 +318,13 @@ class DatasetDocumentListApi(Resource): paginated_documents = db.paginate(select=query, page=page, per_page=limit, max_per_page=100, error_out=False) documents = paginated_documents.items + + DocumentService.enrich_documents_with_summary_index_status( + documents=documents, + dataset=dataset, + tenant_id=current_tenant_id, + ) + if fetch: for document in documents: completed_segments = ( @@ -797,6 +810,7 @@ class DocumentApi(DocumentResource): "display_status": document.display_status, "doc_form": document.doc_form, "doc_language": document.doc_language, + "need_summary": document.need_summary if document.need_summary is not None else False, } else: dataset_process_rules = DatasetService.get_process_rules(dataset_id) @@ -832,6 +846,7 @@ class DocumentApi(DocumentResource): "display_status": document.display_status, "doc_form": document.doc_form, "doc_language": document.doc_language, + "need_summary": document.need_summary if document.need_summary is not None else False, } return response, 200 @@ -1255,3 +1270,137 @@ class DocumentPipelineExecutionLogApi(DocumentResource): "input_data": log.input_data, "datasource_node_id": log.datasource_node_id, }, 200 + + +@console_ns.route("/datasets//documents/generate-summary") +class DocumentGenerateSummaryApi(Resource): + @console_ns.doc("generate_summary_for_documents") + @console_ns.doc(description="Generate summary index for documents") + @console_ns.doc(params={"dataset_id": "Dataset ID"}) + @console_ns.expect(console_ns.models[GenerateSummaryPayload.__name__]) + @console_ns.response(200, "Summary generation started successfully") + @console_ns.response(400, "Invalid request or dataset configuration") + @console_ns.response(403, "Permission denied") + @console_ns.response(404, "Dataset not found") + @setup_required + @login_required + @account_initialization_required + @cloud_edition_billing_rate_limit_check("knowledge") + def post(self, dataset_id): + """ + Generate summary index for specified documents. + + This endpoint checks if the dataset configuration supports summary generation + (indexing_technique must be 'high_quality' and summary_index_setting.enable must be true), + then asynchronously generates summary indexes for the provided documents. + """ + current_user, _ = current_account_with_tenant() + dataset_id = str(dataset_id) + + # Get dataset + dataset = DatasetService.get_dataset(dataset_id) + if not dataset: + raise NotFound("Dataset not found.") + + # Check permissions + if not current_user.is_dataset_editor: + raise Forbidden() + + try: + DatasetService.check_dataset_permission(dataset, current_user) + except services.errors.account.NoPermissionError as e: + raise Forbidden(str(e)) + + # Validate request payload + payload = GenerateSummaryPayload.model_validate(console_ns.payload or {}) + document_list = payload.document_list + + if not document_list: + from werkzeug.exceptions import BadRequest + + raise BadRequest("document_list cannot be empty.") + + # Check if dataset configuration supports summary generation + if dataset.indexing_technique != "high_quality": + raise ValueError( + f"Summary generation is only available for 'high_quality' indexing technique. " + f"Current indexing technique: {dataset.indexing_technique}" + ) + + summary_index_setting = dataset.summary_index_setting + if not summary_index_setting or not summary_index_setting.get("enable"): + raise ValueError("Summary index is not enabled for this dataset. Please enable it in the dataset settings.") + + # Verify all documents exist and belong to the dataset + documents = DocumentService.get_documents_by_ids(dataset_id, document_list) + + if len(documents) != len(document_list): + found_ids = {doc.id for doc in documents} + missing_ids = set(document_list) - found_ids + raise NotFound(f"Some documents not found: {list(missing_ids)}") + + # Dispatch async tasks for each document + for document in documents: + # Skip qa_model documents as they don't generate summaries + if document.doc_form == "qa_model": + logger.info("Skipping summary generation for qa_model document %s", document.id) + continue + + # Dispatch async task + generate_summary_index_task.delay(dataset_id, document.id) + logger.info( + "Dispatched summary generation task for document %s in dataset %s", + document.id, + dataset_id, + ) + + return {"result": "success"}, 200 + + +@console_ns.route("/datasets//documents//summary-status") +class DocumentSummaryStatusApi(DocumentResource): + @console_ns.doc("get_document_summary_status") + @console_ns.doc(description="Get summary index generation status for a document") + @console_ns.doc(params={"dataset_id": "Dataset ID", "document_id": "Document ID"}) + @console_ns.response(200, "Summary status retrieved successfully") + @console_ns.response(404, "Document not found") + @setup_required + @login_required + @account_initialization_required + def get(self, dataset_id, document_id): + """ + Get summary index generation status for a document. + + Returns: + - total_segments: Total number of segments in the document + - summary_status: Dictionary with status counts + - completed: Number of summaries completed + - generating: Number of summaries being generated + - error: Number of summaries with errors + - not_started: Number of segments without summary records + - summaries: List of summary records with status and content preview + """ + current_user, _ = current_account_with_tenant() + dataset_id = str(dataset_id) + document_id = str(document_id) + + # Get dataset + dataset = DatasetService.get_dataset(dataset_id) + if not dataset: + raise NotFound("Dataset not found.") + + # Check permissions + try: + DatasetService.check_dataset_permission(dataset, current_user) + except services.errors.account.NoPermissionError as e: + raise Forbidden(str(e)) + + # Get summary status detail from service + from services.summary_index_service import SummaryIndexService + + result = SummaryIndexService.get_document_summary_status_detail( + document_id=document_id, + dataset_id=dataset_id, + ) + + return result, 200 diff --git a/api/controllers/console/datasets/datasets_segments.py b/api/controllers/console/datasets/datasets_segments.py index 08e1ddd3e0..23a668112d 100644 --- a/api/controllers/console/datasets/datasets_segments.py +++ b/api/controllers/console/datasets/datasets_segments.py @@ -41,6 +41,17 @@ from services.errors.chunk import ChildChunkIndexingError as ChildChunkIndexingS from tasks.batch_create_segment_to_index_task import batch_create_segment_to_index_task +def _get_segment_with_summary(segment, dataset_id): + """Helper function to marshal segment and add summary information.""" + from services.summary_index_service import SummaryIndexService + + segment_dict = dict(marshal(segment, segment_fields)) + # Query summary for this segment (only enabled summaries) + summary = SummaryIndexService.get_segment_summary(segment_id=segment.id, dataset_id=dataset_id) + segment_dict["summary"] = summary.summary_content if summary else None + return segment_dict + + class SegmentListQuery(BaseModel): limit: int = Field(default=20, ge=1, le=100) status: list[str] = Field(default_factory=list) @@ -63,6 +74,7 @@ class SegmentUpdatePayload(BaseModel): keywords: list[str] | None = None regenerate_child_chunks: bool = False attachment_ids: list[str] | None = None + summary: str | None = None # Summary content for summary index class BatchImportPayload(BaseModel): @@ -181,8 +193,25 @@ class DatasetDocumentSegmentListApi(Resource): segments = db.paginate(select=query, page=page, per_page=limit, max_per_page=100, error_out=False) + # Query summaries for all segments in this page (batch query for efficiency) + segment_ids = [segment.id for segment in segments.items] + summaries = {} + if segment_ids: + from services.summary_index_service import SummaryIndexService + + summary_records = SummaryIndexService.get_segments_summaries(segment_ids=segment_ids, dataset_id=dataset_id) + # Only include enabled summaries (already filtered by service) + summaries = {chunk_id: summary.summary_content for chunk_id, summary in summary_records.items()} + + # Add summary to each segment + segments_with_summary = [] + for segment in segments.items: + segment_dict = dict(marshal(segment, segment_fields)) + segment_dict["summary"] = summaries.get(segment.id) + segments_with_summary.append(segment_dict) + response = { - "data": marshal(segments.items, segment_fields), + "data": segments_with_summary, "limit": limit, "total": segments.total, "total_pages": segments.pages, @@ -328,7 +357,7 @@ class DatasetDocumentSegmentAddApi(Resource): payload_dict = payload.model_dump(exclude_none=True) SegmentService.segment_create_args_validate(payload_dict, document) segment = SegmentService.create_segment(payload_dict, document, dataset) - return {"data": marshal(segment, segment_fields), "doc_form": document.doc_form}, 200 + return {"data": _get_segment_with_summary(segment, dataset_id), "doc_form": document.doc_form}, 200 @console_ns.route("/datasets//documents//segments/") @@ -390,10 +419,12 @@ class DatasetDocumentSegmentUpdateApi(Resource): payload = SegmentUpdatePayload.model_validate(console_ns.payload or {}) payload_dict = payload.model_dump(exclude_none=True) SegmentService.segment_create_args_validate(payload_dict, document) + + # Update segment (summary update with change detection is handled in SegmentService.update_segment) segment = SegmentService.update_segment( SegmentUpdateArgs.model_validate(payload.model_dump(exclude_none=True)), segment, document, dataset ) - return {"data": marshal(segment, segment_fields), "doc_form": document.doc_form}, 200 + return {"data": _get_segment_with_summary(segment, dataset_id), "doc_form": document.doc_form}, 200 @setup_required @login_required diff --git a/api/controllers/console/datasets/hit_testing.py b/api/controllers/console/datasets/hit_testing.py index 932cb4fcce..e62be13c2f 100644 --- a/api/controllers/console/datasets/hit_testing.py +++ b/api/controllers/console/datasets/hit_testing.py @@ -1,6 +1,13 @@ -from flask_restx import Resource +from flask_restx import Resource, fields from controllers.common.schema import register_schema_model +from fields.hit_testing_fields import ( + child_chunk_fields, + document_fields, + files_fields, + hit_testing_record_fields, + segment_fields, +) from libs.login import login_required from .. import console_ns @@ -14,13 +21,45 @@ from ..wraps import ( register_schema_model(console_ns, HitTestingPayload) +def _get_or_create_model(model_name: str, field_def): + """Get or create a flask_restx model to avoid dict type issues in Swagger.""" + existing = console_ns.models.get(model_name) + if existing is None: + existing = console_ns.model(model_name, field_def) + return existing + + +# Register models for flask_restx to avoid dict type issues in Swagger +document_model = _get_or_create_model("HitTestingDocument", document_fields) + +segment_fields_copy = segment_fields.copy() +segment_fields_copy["document"] = fields.Nested(document_model) +segment_model = _get_or_create_model("HitTestingSegment", segment_fields_copy) + +child_chunk_model = _get_or_create_model("HitTestingChildChunk", child_chunk_fields) +files_model = _get_or_create_model("HitTestingFile", files_fields) + +hit_testing_record_fields_copy = hit_testing_record_fields.copy() +hit_testing_record_fields_copy["segment"] = fields.Nested(segment_model) +hit_testing_record_fields_copy["child_chunks"] = fields.List(fields.Nested(child_chunk_model)) +hit_testing_record_fields_copy["files"] = fields.List(fields.Nested(files_model)) +hit_testing_record_model = _get_or_create_model("HitTestingRecord", hit_testing_record_fields_copy) + +# Response model for hit testing API +hit_testing_response_fields = { + "query": fields.String, + "records": fields.List(fields.Nested(hit_testing_record_model)), +} +hit_testing_response_model = _get_or_create_model("HitTestingResponse", hit_testing_response_fields) + + @console_ns.route("/datasets//hit-testing") class HitTestingApi(Resource, DatasetsHitTestingBase): @console_ns.doc("test_dataset_retrieval") @console_ns.doc(description="Test dataset knowledge retrieval") @console_ns.doc(params={"dataset_id": "Dataset ID"}) @console_ns.expect(console_ns.models[HitTestingPayload.__name__]) - @console_ns.response(200, "Hit testing completed successfully") + @console_ns.response(200, "Hit testing completed successfully", model=hit_testing_response_model) @console_ns.response(404, "Dataset not found") @console_ns.response(400, "Invalid parameters") @setup_required diff --git a/api/controllers/service_api/dataset/dataset.py b/api/controllers/service_api/dataset/dataset.py index 28864a140a..c11f64585a 100644 --- a/api/controllers/service_api/dataset/dataset.py +++ b/api/controllers/service_api/dataset/dataset.py @@ -46,6 +46,7 @@ class DatasetCreatePayload(BaseModel): retrieval_model: RetrievalModel | None = None embedding_model: str | None = None embedding_model_provider: str | None = None + summary_index_setting: dict | None = None class DatasetUpdatePayload(BaseModel): @@ -217,6 +218,7 @@ class DatasetListApi(DatasetApiResource): embedding_model_provider=payload.embedding_model_provider, embedding_model_name=payload.embedding_model, retrieval_model=payload.retrieval_model, + summary_index_setting=payload.summary_index_setting, ) except services.errors.dataset.DatasetNameDuplicateError: raise DatasetNameDuplicateError() diff --git a/api/controllers/service_api/dataset/document.py b/api/controllers/service_api/dataset/document.py index c85c1cf81e..a01524f1bc 100644 --- a/api/controllers/service_api/dataset/document.py +++ b/api/controllers/service_api/dataset/document.py @@ -45,6 +45,7 @@ from services.entities.knowledge_entities.knowledge_entities import ( Segmentation, ) from services.file_service import FileService +from services.summary_index_service import SummaryIndexService class DocumentTextCreatePayload(BaseModel): @@ -508,6 +509,12 @@ class DocumentListApi(DatasetApiResource): ) documents = paginated_documents.items + DocumentService.enrich_documents_with_summary_index_status( + documents=documents, + dataset=dataset, + tenant_id=tenant_id, + ) + response = { "data": marshal(documents, document_fields), "has_more": len(documents) == query_params.limit, @@ -612,6 +619,16 @@ class DocumentApi(DatasetApiResource): if metadata not in self.METADATA_CHOICES: raise InvalidMetadataError(f"Invalid metadata value: {metadata}") + # Calculate summary_index_status if needed + summary_index_status = None + has_summary_index = dataset.summary_index_setting and dataset.summary_index_setting.get("enable") is True + if has_summary_index and document.need_summary is True: + summary_index_status = SummaryIndexService.get_document_summary_index_status( + document_id=document_id, + dataset_id=dataset_id, + tenant_id=tenant_id, + ) + if metadata == "only": response = {"id": document.id, "doc_type": document.doc_type, "doc_metadata": document.doc_metadata_details} elif metadata == "without": @@ -646,6 +663,8 @@ class DocumentApi(DatasetApiResource): "display_status": document.display_status, "doc_form": document.doc_form, "doc_language": document.doc_language, + "summary_index_status": summary_index_status, + "need_summary": document.need_summary if document.need_summary is not None else False, } else: dataset_process_rules = DatasetService.get_process_rules(dataset_id) @@ -681,6 +700,8 @@ class DocumentApi(DatasetApiResource): "display_status": document.display_status, "doc_form": document.doc_form, "doc_language": document.doc_language, + "summary_index_status": summary_index_status, + "need_summary": document.need_summary if document.need_summary is not None else False, } return response diff --git a/api/core/app/apps/base_app_generate_response_converter.py b/api/core/app/apps/base_app_generate_response_converter.py index 74c6d2eca6..d1e2f16b6f 100644 --- a/api/core/app/apps/base_app_generate_response_converter.py +++ b/api/core/app/apps/base_app_generate_response_converter.py @@ -79,6 +79,7 @@ class AppGenerateResponseConverter(ABC): "document_name": resource["document_name"], "score": resource["score"], "content": resource["content"], + "summary": resource.get("summary"), } ) metadata["retriever_resources"] = updated_resources diff --git a/api/core/entities/knowledge_entities.py b/api/core/entities/knowledge_entities.py index d4093b5245..b1ba3c3e2a 100644 --- a/api/core/entities/knowledge_entities.py +++ b/api/core/entities/knowledge_entities.py @@ -3,6 +3,7 @@ from pydantic import BaseModel, Field, field_validator class PreviewDetail(BaseModel): content: str + summary: str | None = None child_chunks: list[str] | None = None diff --git a/api/core/indexing_runner.py b/api/core/indexing_runner.py index f1b50f360b..e172e88298 100644 --- a/api/core/indexing_runner.py +++ b/api/core/indexing_runner.py @@ -311,14 +311,18 @@ class IndexingRunner: qa_preview_texts: list[QAPreviewDetail] = [] total_segments = 0 + # doc_form represents the segmentation method (general, parent-child, QA) index_type = doc_form index_processor = IndexProcessorFactory(index_type).init_index_processor() + # one extract_setting is one source document for extract_setting in extract_settings: # extract processing_rule = DatasetProcessRule( mode=tmp_processing_rule["mode"], rules=json.dumps(tmp_processing_rule["rules"]) ) + # Extract document content text_docs = index_processor.extract(extract_setting, process_rule_mode=tmp_processing_rule["mode"]) + # Cleaning and segmentation documents = index_processor.transform( text_docs, current_user=None, @@ -361,6 +365,12 @@ class IndexingRunner: if doc_form and doc_form == "qa_model": return IndexingEstimate(total_segments=total_segments * 20, qa_preview=qa_preview_texts, preview=[]) + + # Generate summary preview + summary_index_setting = tmp_processing_rule.get("summary_index_setting") + if summary_index_setting and summary_index_setting.get("enable") and preview_texts: + preview_texts = index_processor.generate_summary_preview(tenant_id, preview_texts, summary_index_setting) + return IndexingEstimate(total_segments=total_segments, preview=preview_texts) def _extract( diff --git a/api/core/llm_generator/prompts.py b/api/core/llm_generator/prompts.py index ec2b7f2d44..d46cf049dd 100644 --- a/api/core/llm_generator/prompts.py +++ b/api/core/llm_generator/prompts.py @@ -434,3 +434,20 @@ INSTRUCTION_GENERATE_TEMPLATE_PROMPT = """The output of this prompt is not as ex You should edit the prompt according to the IDEAL OUTPUT.""" INSTRUCTION_GENERATE_TEMPLATE_CODE = """Please fix the errors in the {{#error_message#}}.""" + +DEFAULT_GENERATOR_SUMMARY_PROMPT = ( + """Summarize the following content. Extract only the key information and main points. """ + """Remove redundant details. + +Requirements: +1. Write a concise summary in plain text +2. Use the same language as the input content +3. Focus on important facts, concepts, and details +4. If images are included, describe their key information +5. Do not use words like "好的", "ok", "I understand", "This text discusses", "The content mentions" +6. Write directly without extra words + +Output only the summary text. Start summarizing now: + +""" +) diff --git a/api/core/rag/datasource/retrieval_service.py b/api/core/rag/datasource/retrieval_service.py index 8ec1ce6242..91c16ce079 100644 --- a/api/core/rag/datasource/retrieval_service.py +++ b/api/core/rag/datasource/retrieval_service.py @@ -24,7 +24,13 @@ from core.rag.rerank.rerank_type import RerankMode from core.rag.retrieval.retrieval_methods import RetrievalMethod from core.tools.signature import sign_upload_file from extensions.ext_database import db -from models.dataset import ChildChunk, Dataset, DocumentSegment, SegmentAttachmentBinding +from models.dataset import ( + ChildChunk, + Dataset, + DocumentSegment, + DocumentSegmentSummary, + SegmentAttachmentBinding, +) from models.dataset import Document as DatasetDocument from models.model import UploadFile from services.external_knowledge_service import ExternalDatasetService @@ -389,15 +395,15 @@ class RetrievalService: .all() } - records = [] - include_segment_ids = set() - segment_child_map = {} - valid_dataset_documents = {} image_doc_ids: list[Any] = [] child_index_node_ids = [] index_node_ids = [] doc_to_document_map = {} + summary_segment_ids = set() # Track segments retrieved via summary + summary_score_map: dict[str, float] = {} # Map original_chunk_id to summary score + + # First pass: collect all document IDs and identify summary documents for document in documents: document_id = document.metadata.get("document_id") if document_id not in dataset_documents: @@ -408,16 +414,39 @@ class RetrievalService: continue valid_dataset_documents[document_id] = dataset_document + doc_id = document.metadata.get("doc_id") or "" + doc_to_document_map[doc_id] = document + + # Check if this is a summary document + is_summary = document.metadata.get("is_summary", False) + if is_summary: + # For summary documents, find the original chunk via original_chunk_id + original_chunk_id = document.metadata.get("original_chunk_id") + if original_chunk_id: + summary_segment_ids.add(original_chunk_id) + # Save summary's score for later use + summary_score = document.metadata.get("score") + if summary_score is not None: + try: + summary_score_float = float(summary_score) + # If the same segment has multiple summary hits, take the highest score + if original_chunk_id not in summary_score_map: + summary_score_map[original_chunk_id] = summary_score_float + else: + summary_score_map[original_chunk_id] = max( + summary_score_map[original_chunk_id], summary_score_float + ) + except (ValueError, TypeError): + # Skip invalid score values + pass + continue # Skip adding to other lists for summary documents + if dataset_document.doc_form == IndexStructureType.PARENT_CHILD_INDEX: - doc_id = document.metadata.get("doc_id") or "" - doc_to_document_map[doc_id] = document if document.metadata.get("doc_type") == DocType.IMAGE: image_doc_ids.append(doc_id) else: child_index_node_ids.append(doc_id) else: - doc_id = document.metadata.get("doc_id") or "" - doc_to_document_map[doc_id] = document if document.metadata.get("doc_type") == DocType.IMAGE: image_doc_ids.append(doc_id) else: @@ -433,6 +462,7 @@ class RetrievalService: attachment_map: dict[str, list[dict[str, Any]]] = {} child_chunk_map: dict[str, list[ChildChunk]] = {} doc_segment_map: dict[str, list[str]] = {} + segment_summary_map: dict[str, str] = {} # Map segment_id to summary content with session_factory.create_session() as session: attachments = cls.get_segment_attachment_infos(image_doc_ids, session) @@ -447,6 +477,7 @@ class RetrievalService: doc_segment_map[attachment["segment_id"]].append(attachment["attachment_id"]) else: doc_segment_map[attachment["segment_id"]] = [attachment["attachment_id"]] + child_chunk_stmt = select(ChildChunk).where(ChildChunk.index_node_id.in_(child_index_node_ids)) child_index_nodes = session.execute(child_chunk_stmt).scalars().all() @@ -470,6 +501,7 @@ class RetrievalService: index_node_segments = session.execute(document_segment_stmt).scalars().all() # type: ignore for index_node_segment in index_node_segments: doc_segment_map[index_node_segment.id] = [index_node_segment.index_node_id] + if segment_ids: document_segment_stmt = select(DocumentSegment).where( DocumentSegment.enabled == True, @@ -481,6 +513,40 @@ class RetrievalService: if index_node_segments: segments.extend(index_node_segments) + # Handle summary documents: query segments by original_chunk_id + if summary_segment_ids: + summary_segment_ids_list = list(summary_segment_ids) + summary_segment_stmt = select(DocumentSegment).where( + DocumentSegment.enabled == True, + DocumentSegment.status == "completed", + DocumentSegment.id.in_(summary_segment_ids_list), + ) + summary_segments = session.execute(summary_segment_stmt).scalars().all() # type: ignore + segments.extend(summary_segments) + # Add summary segment IDs to segment_ids for summary query + for seg in summary_segments: + if seg.id not in segment_ids: + segment_ids.append(seg.id) + + # Batch query summaries for segments retrieved via summary (only enabled summaries) + if summary_segment_ids: + summaries = ( + session.query(DocumentSegmentSummary) + .filter( + DocumentSegmentSummary.chunk_id.in_(list(summary_segment_ids)), + DocumentSegmentSummary.status == "completed", + DocumentSegmentSummary.enabled == True, # Only retrieve enabled summaries + ) + .all() + ) + for summary in summaries: + if summary.summary_content: + segment_summary_map[summary.chunk_id] = summary.summary_content + + include_segment_ids = set() + segment_child_map: dict[str, dict[str, Any]] = {} + records: list[dict[str, Any]] = [] + for segment in segments: child_chunks: list[ChildChunk] = child_chunk_map.get(segment.id, []) attachment_infos: list[dict[str, Any]] = attachment_map.get(segment.id, []) @@ -489,30 +555,44 @@ class RetrievalService: if ds_dataset_document and ds_dataset_document.doc_form == IndexStructureType.PARENT_CHILD_INDEX: if segment.id not in include_segment_ids: include_segment_ids.add(segment.id) + # Check if this segment was retrieved via summary + # Use summary score as base score if available, otherwise 0.0 + max_score = summary_score_map.get(segment.id, 0.0) + if child_chunks or attachment_infos: child_chunk_details = [] - max_score = 0.0 for child_chunk in child_chunks: - document = doc_to_document_map[child_chunk.index_node_id] + child_document: Document | None = doc_to_document_map.get(child_chunk.index_node_id) + if child_document: + child_score = child_document.metadata.get("score", 0.0) + else: + child_score = 0.0 child_chunk_detail = { "id": child_chunk.id, "content": child_chunk.content, "position": child_chunk.position, - "score": document.metadata.get("score", 0.0) if document else 0.0, + "score": child_score, } child_chunk_details.append(child_chunk_detail) - max_score = max(max_score, document.metadata.get("score", 0.0) if document else 0.0) + max_score = max(max_score, child_score) for attachment_info in attachment_infos: - file_document = doc_to_document_map[attachment_info["id"]] - max_score = max( - max_score, file_document.metadata.get("score", 0.0) if file_document else 0.0 - ) + file_document = doc_to_document_map.get(attachment_info["id"]) + if file_document: + max_score = max(max_score, file_document.metadata.get("score", 0.0)) map_detail = { "max_score": max_score, "child_chunks": child_chunk_details, } segment_child_map[segment.id] = map_detail + else: + # No child chunks or attachments, use summary score if available + summary_score = summary_score_map.get(segment.id) + if summary_score is not None: + segment_child_map[segment.id] = { + "max_score": summary_score, + "child_chunks": [], + } record: dict[str, Any] = { "segment": segment, } @@ -520,14 +600,23 @@ class RetrievalService: else: if segment.id not in include_segment_ids: include_segment_ids.add(segment.id) - max_score = 0.0 - segment_document = doc_to_document_map.get(segment.index_node_id) - if segment_document: - max_score = max(max_score, segment_document.metadata.get("score", 0.0)) + + # Check if this segment was retrieved via summary + # Use summary score if available (summary retrieval takes priority) + max_score = summary_score_map.get(segment.id, 0.0) + + # If not retrieved via summary, use original segment's score + if segment.id not in summary_score_map: + segment_document = doc_to_document_map.get(segment.index_node_id) + if segment_document: + max_score = max(max_score, segment_document.metadata.get("score", 0.0)) + + # Also consider attachment scores for attachment_info in attachment_infos: file_doc = doc_to_document_map.get(attachment_info["id"]) if file_doc: max_score = max(max_score, file_doc.metadata.get("score", 0.0)) + record = { "segment": segment, "score": max_score, @@ -576,9 +665,16 @@ class RetrievalService: else None ) + # Extract summary if this segment was retrieved via summary + summary_content = segment_summary_map.get(segment.id) + # Create RetrievalSegments object retrieval_segment = RetrievalSegments( - segment=segment, child_chunks=child_chunks_list, score=score, files=files + segment=segment, + child_chunks=child_chunks_list, + score=score, + files=files, + summary=summary_content, ) result.append(retrieval_segment) diff --git a/api/core/rag/embedding/retrieval.py b/api/core/rag/embedding/retrieval.py index b54a37b49e..f6834ab87b 100644 --- a/api/core/rag/embedding/retrieval.py +++ b/api/core/rag/embedding/retrieval.py @@ -20,3 +20,4 @@ class RetrievalSegments(BaseModel): child_chunks: list[RetrievalChildChunk] | None = None score: float | None = None files: list[dict[str, str | int]] | None = None + summary: str | None = None # Summary content if retrieved via summary index diff --git a/api/core/rag/entities/citation_metadata.py b/api/core/rag/entities/citation_metadata.py index 9f66cd9a03..aec5c353f8 100644 --- a/api/core/rag/entities/citation_metadata.py +++ b/api/core/rag/entities/citation_metadata.py @@ -22,3 +22,4 @@ class RetrievalSourceMetadata(BaseModel): doc_metadata: dict[str, Any] | None = None title: str | None = None files: list[dict[str, Any]] | None = None + summary: str | None = None diff --git a/api/core/rag/index_processor/index_processor_base.py b/api/core/rag/index_processor/index_processor_base.py index e36b54eedd..151a3de7d9 100644 --- a/api/core/rag/index_processor/index_processor_base.py +++ b/api/core/rag/index_processor/index_processor_base.py @@ -13,6 +13,7 @@ from urllib.parse import unquote, urlparse import httpx from configs import dify_config +from core.entities.knowledge_entities import PreviewDetail from core.helper import ssrf_proxy from core.rag.extractor.entity.extract_setting import ExtractSetting from core.rag.index_processor.constant.doc_type import DocType @@ -45,6 +46,17 @@ class BaseIndexProcessor(ABC): def transform(self, documents: list[Document], current_user: Account | None = None, **kwargs) -> list[Document]: raise NotImplementedError + @abstractmethod + def generate_summary_preview( + self, tenant_id: str, preview_texts: list[PreviewDetail], summary_index_setting: dict + ) -> list[PreviewDetail]: + """ + For each segment in preview_texts, generate a summary using LLM and attach it to the segment. + The summary can be stored in a new attribute, e.g., summary. + This method should be implemented by subclasses. + """ + raise NotImplementedError + @abstractmethod def load( self, diff --git a/api/core/rag/index_processor/processor/paragraph_index_processor.py b/api/core/rag/index_processor/processor/paragraph_index_processor.py index cf68cff7dc..ab91e29145 100644 --- a/api/core/rag/index_processor/processor/paragraph_index_processor.py +++ b/api/core/rag/index_processor/processor/paragraph_index_processor.py @@ -1,9 +1,27 @@ """Paragraph index processor.""" +import logging +import re import uuid from collections.abc import Mapping -from typing import Any +from typing import Any, cast +logger = logging.getLogger(__name__) + +from core.entities.knowledge_entities import PreviewDetail +from core.file import File, FileTransferMethod, FileType, file_manager +from core.llm_generator.prompts import DEFAULT_GENERATOR_SUMMARY_PROMPT +from core.model_manager import ModelInstance +from core.model_runtime.entities.llm_entities import LLMResult, LLMUsage +from core.model_runtime.entities.message_entities import ( + ImagePromptMessageContent, + PromptMessage, + PromptMessageContentUnionTypes, + TextPromptMessageContent, + UserPromptMessage, +) +from core.model_runtime.entities.model_entities import ModelFeature, ModelType +from core.provider_manager import ProviderManager from core.rag.cleaner.clean_processor import CleanProcessor from core.rag.datasource.keyword.keyword_factory import Keyword from core.rag.datasource.retrieval_service import RetrievalService @@ -17,12 +35,17 @@ from core.rag.index_processor.index_processor_base import BaseIndexProcessor from core.rag.models.document import AttachmentDocument, Document, MultimodalGeneralStructureChunk from core.rag.retrieval.retrieval_methods import RetrievalMethod from core.tools.utils.text_processing_utils import remove_leading_symbols +from core.workflow.nodes.llm import llm_utils +from extensions.ext_database import db +from factories.file_factory import build_from_mapping from libs import helper +from models import UploadFile from models.account import Account -from models.dataset import Dataset, DatasetProcessRule +from models.dataset import Dataset, DatasetProcessRule, DocumentSegment, SegmentAttachmentBinding from models.dataset import Document as DatasetDocument from services.account_service import AccountService from services.entities.knowledge_entities.knowledge_entities import Rule +from services.summary_index_service import SummaryIndexService class ParagraphIndexProcessor(BaseIndexProcessor): @@ -108,6 +131,29 @@ class ParagraphIndexProcessor(BaseIndexProcessor): keyword.add_texts(documents) def clean(self, dataset: Dataset, node_ids: list[str] | None, with_keywords: bool = True, **kwargs): + # Note: Summary indexes are now disabled (not deleted) when segments are disabled. + # This method is called for actual deletion scenarios (e.g., when segment is deleted). + # For disable operations, disable_summaries_for_segments is called directly in the task. + # Only delete summaries if explicitly requested (e.g., when segment is actually deleted) + delete_summaries = kwargs.get("delete_summaries", False) + if delete_summaries: + if node_ids: + # Find segments by index_node_id + segments = ( + db.session.query(DocumentSegment) + .filter( + DocumentSegment.dataset_id == dataset.id, + DocumentSegment.index_node_id.in_(node_ids), + ) + .all() + ) + segment_ids = [segment.id for segment in segments] + if segment_ids: + SummaryIndexService.delete_summaries_for_segments(dataset, segment_ids) + else: + # Delete all summaries for the dataset + SummaryIndexService.delete_summaries_for_segments(dataset, None) + if dataset.indexing_technique == "high_quality": vector = Vector(dataset) if node_ids: @@ -227,3 +273,322 @@ class ParagraphIndexProcessor(BaseIndexProcessor): } else: raise ValueError("Chunks is not a list") + + def generate_summary_preview( + self, tenant_id: str, preview_texts: list[PreviewDetail], summary_index_setting: dict + ) -> list[PreviewDetail]: + """ + For each segment, concurrently call generate_summary to generate a summary + and write it to the summary attribute of PreviewDetail. + In preview mode (indexing-estimate), if any summary generation fails, the method will raise an exception. + """ + import concurrent.futures + + from flask import current_app + + # Capture Flask app context for worker threads + flask_app = None + try: + flask_app = current_app._get_current_object() # type: ignore + except RuntimeError: + logger.warning("No Flask application context available, summary generation may fail") + + def process(preview: PreviewDetail) -> None: + """Generate summary for a single preview item.""" + if flask_app: + # Ensure Flask app context in worker thread + with flask_app.app_context(): + summary, _ = self.generate_summary(tenant_id, preview.content, summary_index_setting) + preview.summary = summary + else: + # Fallback: try without app context (may fail) + summary, _ = self.generate_summary(tenant_id, preview.content, summary_index_setting) + preview.summary = summary + + # Generate summaries concurrently using ThreadPoolExecutor + # Set a reasonable timeout to prevent hanging (60 seconds per chunk, max 5 minutes total) + timeout_seconds = min(300, 60 * len(preview_texts)) + errors: list[Exception] = [] + + with concurrent.futures.ThreadPoolExecutor(max_workers=min(10, len(preview_texts))) as executor: + futures = [executor.submit(process, preview) for preview in preview_texts] + # Wait for all tasks to complete with timeout + done, not_done = concurrent.futures.wait(futures, timeout=timeout_seconds) + + # Cancel tasks that didn't complete in time + if not_done: + timeout_error_msg = ( + f"Summary generation timeout: {len(not_done)} chunks did not complete within {timeout_seconds}s" + ) + logger.warning("%s. Cancelling remaining tasks...", timeout_error_msg) + # In preview mode, timeout is also an error + errors.append(TimeoutError(timeout_error_msg)) + for future in not_done: + future.cancel() + # Wait a bit for cancellation to take effect + concurrent.futures.wait(not_done, timeout=5) + + # Collect exceptions from completed futures + for future in done: + try: + future.result() # This will raise any exception that occurred + except Exception as e: + logger.exception("Error in summary generation future") + errors.append(e) + + # In preview mode (indexing-estimate), if there are any errors, fail the request + if errors: + error_messages = [str(e) for e in errors] + error_summary = ( + f"Failed to generate summaries for {len(errors)} chunk(s). " + f"Errors: {'; '.join(error_messages[:3])}" # Show first 3 errors + ) + if len(errors) > 3: + error_summary += f" (and {len(errors) - 3} more)" + logger.error("Summary generation failed in preview mode: %s", error_summary) + raise ValueError(error_summary) + + return preview_texts + + @staticmethod + def generate_summary( + tenant_id: str, + text: str, + summary_index_setting: dict | None = None, + segment_id: str | None = None, + ) -> tuple[str, LLMUsage]: + """ + Generate summary for the given text using ModelInstance.invoke_llm and the default or custom summary prompt, + and supports vision models by including images from the segment attachments or text content. + + Args: + tenant_id: Tenant ID + text: Text content to summarize + summary_index_setting: Summary index configuration + segment_id: Optional segment ID to fetch attachments from SegmentAttachmentBinding table + + Returns: + Tuple of (summary_content, llm_usage) where llm_usage is LLMUsage object + """ + if not summary_index_setting or not summary_index_setting.get("enable"): + raise ValueError("summary_index_setting is required and must be enabled to generate summary.") + + model_name = summary_index_setting.get("model_name") + model_provider_name = summary_index_setting.get("model_provider_name") + summary_prompt = summary_index_setting.get("summary_prompt") + + if not model_name or not model_provider_name: + raise ValueError("model_name and model_provider_name are required in summary_index_setting") + + # Import default summary prompt + if not summary_prompt: + summary_prompt = DEFAULT_GENERATOR_SUMMARY_PROMPT + + provider_manager = ProviderManager() + provider_model_bundle = provider_manager.get_provider_model_bundle( + tenant_id, model_provider_name, ModelType.LLM + ) + model_instance = ModelInstance(provider_model_bundle, model_name) + + # Get model schema to check if vision is supported + model_schema = model_instance.model_type_instance.get_model_schema(model_name, model_instance.credentials) + supports_vision = model_schema and model_schema.features and ModelFeature.VISION in model_schema.features + + # Extract images if model supports vision + image_files = [] + if supports_vision: + # First, try to get images from SegmentAttachmentBinding (preferred method) + if segment_id: + image_files = ParagraphIndexProcessor._extract_images_from_segment_attachments(tenant_id, segment_id) + + # If no images from attachments, fall back to extracting from text + if not image_files: + image_files = ParagraphIndexProcessor._extract_images_from_text(tenant_id, text) + + # Build prompt messages + prompt_messages = [] + + if image_files: + # If we have images, create a UserPromptMessage with both text and images + prompt_message_contents: list[PromptMessageContentUnionTypes] = [] + + # Add images first + for file in image_files: + try: + file_content = file_manager.to_prompt_message_content( + file, image_detail_config=ImagePromptMessageContent.DETAIL.LOW + ) + prompt_message_contents.append(file_content) + except Exception as e: + logger.warning("Failed to convert image file to prompt message content: %s", str(e)) + continue + + # Add text content + if prompt_message_contents: # Only add text if we successfully added images + prompt_message_contents.append(TextPromptMessageContent(data=f"{summary_prompt}\n{text}")) + prompt_messages.append(UserPromptMessage(content=prompt_message_contents)) + else: + # If image conversion failed, fall back to text-only + prompt = f"{summary_prompt}\n{text}" + prompt_messages.append(UserPromptMessage(content=prompt)) + else: + # No images, use simple text prompt + prompt = f"{summary_prompt}\n{text}" + prompt_messages.append(UserPromptMessage(content=prompt)) + + result = model_instance.invoke_llm( + prompt_messages=cast(list[PromptMessage], prompt_messages), model_parameters={}, stream=False + ) + + # Type assertion: when stream=False, invoke_llm returns LLMResult, not Generator + if not isinstance(result, LLMResult): + raise ValueError("Expected LLMResult when stream=False") + + summary_content = getattr(result.message, "content", "") + usage = result.usage + + # Deduct quota for summary generation (same as workflow nodes) + try: + llm_utils.deduct_llm_quota(tenant_id=tenant_id, model_instance=model_instance, usage=usage) + except Exception as e: + # Log but don't fail summary generation if quota deduction fails + logger.warning("Failed to deduct quota for summary generation: %s", str(e)) + + return summary_content, usage + + @staticmethod + def _extract_images_from_text(tenant_id: str, text: str) -> list[File]: + """ + Extract images from markdown text and convert them to File objects. + + Args: + tenant_id: Tenant ID + text: Text content that may contain markdown image links + + Returns: + List of File objects representing images found in the text + """ + # Extract markdown images using regex pattern + pattern = r"!\[.*?\]\((.*?)\)" + images = re.findall(pattern, text) + + if not images: + return [] + + upload_file_id_list = [] + + for image in images: + # For data before v0.10.0 + pattern = r"/files/([a-f0-9\-]+)/image-preview(?:\?.*?)?" + match = re.search(pattern, image) + if match: + upload_file_id = match.group(1) + upload_file_id_list.append(upload_file_id) + continue + + # For data after v0.10.0 + pattern = r"/files/([a-f0-9\-]+)/file-preview(?:\?.*?)?" + match = re.search(pattern, image) + if match: + upload_file_id = match.group(1) + upload_file_id_list.append(upload_file_id) + continue + + # For tools directory - direct file formats (e.g., .png, .jpg, etc.) + pattern = r"/files/tools/([a-f0-9\-]+)\.([a-zA-Z0-9]+)(?:\?[^\s\)\"\']*)?" + match = re.search(pattern, image) + if match: + # Tool files are handled differently, skip for now + continue + + if not upload_file_id_list: + return [] + + # Get unique IDs for database query + unique_upload_file_ids = list(set(upload_file_id_list)) + upload_files = ( + db.session.query(UploadFile) + .where(UploadFile.id.in_(unique_upload_file_ids), UploadFile.tenant_id == tenant_id) + .all() + ) + + # Create File objects from UploadFile records + file_objects = [] + for upload_file in upload_files: + # Only process image files + if not upload_file.mime_type or "image" not in upload_file.mime_type: + continue + + mapping = { + "upload_file_id": upload_file.id, + "transfer_method": FileTransferMethod.LOCAL_FILE.value, + "type": FileType.IMAGE.value, + } + + try: + file_obj = build_from_mapping( + mapping=mapping, + tenant_id=tenant_id, + ) + file_objects.append(file_obj) + except Exception as e: + logger.warning("Failed to create File object from UploadFile %s: %s", upload_file.id, str(e)) + continue + + return file_objects + + @staticmethod + def _extract_images_from_segment_attachments(tenant_id: str, segment_id: str) -> list[File]: + """ + Extract images from SegmentAttachmentBinding table (preferred method). + This matches how DatasetRetrieval gets segment attachments. + + Args: + tenant_id: Tenant ID + segment_id: Segment ID to fetch attachments for + + Returns: + List of File objects representing images found in segment attachments + """ + from sqlalchemy import select + + # Query attachments from SegmentAttachmentBinding table + attachments_with_bindings = db.session.execute( + select(SegmentAttachmentBinding, UploadFile) + .join(UploadFile, UploadFile.id == SegmentAttachmentBinding.attachment_id) + .where( + SegmentAttachmentBinding.segment_id == segment_id, + SegmentAttachmentBinding.tenant_id == tenant_id, + ) + ).all() + + if not attachments_with_bindings: + return [] + + file_objects = [] + for _, upload_file in attachments_with_bindings: + # Only process image files + if not upload_file.mime_type or "image" not in upload_file.mime_type: + continue + + try: + # Create File object directly (similar to DatasetRetrieval) + file_obj = File( + id=upload_file.id, + filename=upload_file.name, + extension="." + upload_file.extension, + mime_type=upload_file.mime_type, + tenant_id=tenant_id, + type=FileType.IMAGE, + transfer_method=FileTransferMethod.LOCAL_FILE, + remote_url=upload_file.source_url, + related_id=upload_file.id, + size=upload_file.size, + storage_key=upload_file.key, + ) + file_objects.append(file_obj) + except Exception as e: + logger.warning("Failed to create File object from UploadFile %s: %s", upload_file.id, str(e)) + continue + + return file_objects diff --git a/api/core/rag/index_processor/processor/parent_child_index_processor.py b/api/core/rag/index_processor/processor/parent_child_index_processor.py index 0366f3259f..961df2e50c 100644 --- a/api/core/rag/index_processor/processor/parent_child_index_processor.py +++ b/api/core/rag/index_processor/processor/parent_child_index_processor.py @@ -1,11 +1,14 @@ """Paragraph index processor.""" import json +import logging import uuid from collections.abc import Mapping from typing import Any from configs import dify_config +from core.db.session_factory import session_factory +from core.entities.knowledge_entities import PreviewDetail from core.model_manager import ModelInstance from core.rag.cleaner.clean_processor import CleanProcessor from core.rag.datasource.retrieval_service import RetrievalService @@ -25,6 +28,9 @@ from models.dataset import ChildChunk, Dataset, DatasetProcessRule, DocumentSegm from models.dataset import Document as DatasetDocument from services.account_service import AccountService from services.entities.knowledge_entities.knowledge_entities import ParentMode, Rule +from services.summary_index_service import SummaryIndexService + +logger = logging.getLogger(__name__) class ParentChildIndexProcessor(BaseIndexProcessor): @@ -135,6 +141,30 @@ class ParentChildIndexProcessor(BaseIndexProcessor): def clean(self, dataset: Dataset, node_ids: list[str] | None, with_keywords: bool = True, **kwargs): # node_ids is segment's node_ids + # Note: Summary indexes are now disabled (not deleted) when segments are disabled. + # This method is called for actual deletion scenarios (e.g., when segment is deleted). + # For disable operations, disable_summaries_for_segments is called directly in the task. + # Only delete summaries if explicitly requested (e.g., when segment is actually deleted) + delete_summaries = kwargs.get("delete_summaries", False) + if delete_summaries: + if node_ids: + # Find segments by index_node_id + with session_factory.create_session() as session: + segments = ( + session.query(DocumentSegment) + .filter( + DocumentSegment.dataset_id == dataset.id, + DocumentSegment.index_node_id.in_(node_ids), + ) + .all() + ) + segment_ids = [segment.id for segment in segments] + if segment_ids: + SummaryIndexService.delete_summaries_for_segments(dataset, segment_ids) + else: + # Delete all summaries for the dataset + SummaryIndexService.delete_summaries_for_segments(dataset, None) + if dataset.indexing_technique == "high_quality": delete_child_chunks = kwargs.get("delete_child_chunks") or False precomputed_child_node_ids = kwargs.get("precomputed_child_node_ids") @@ -326,3 +356,91 @@ class ParentChildIndexProcessor(BaseIndexProcessor): "preview": preview, "total_segments": len(parent_childs.parent_child_chunks), } + + def generate_summary_preview( + self, tenant_id: str, preview_texts: list[PreviewDetail], summary_index_setting: dict + ) -> list[PreviewDetail]: + """ + For each parent chunk in preview_texts, concurrently call generate_summary to generate a summary + and write it to the summary attribute of PreviewDetail. + In preview mode (indexing-estimate), if any summary generation fails, the method will raise an exception. + + Note: For parent-child structure, we only generate summaries for parent chunks. + """ + import concurrent.futures + + from flask import current_app + + # Capture Flask app context for worker threads + flask_app = None + try: + flask_app = current_app._get_current_object() # type: ignore + except RuntimeError: + logger.warning("No Flask application context available, summary generation may fail") + + def process(preview: PreviewDetail) -> None: + """Generate summary for a single preview item (parent chunk).""" + from core.rag.index_processor.processor.paragraph_index_processor import ParagraphIndexProcessor + + if flask_app: + # Ensure Flask app context in worker thread + with flask_app.app_context(): + summary, _ = ParagraphIndexProcessor.generate_summary( + tenant_id=tenant_id, + text=preview.content, + summary_index_setting=summary_index_setting, + ) + preview.summary = summary + else: + # Fallback: try without app context (may fail) + summary, _ = ParagraphIndexProcessor.generate_summary( + tenant_id=tenant_id, + text=preview.content, + summary_index_setting=summary_index_setting, + ) + preview.summary = summary + + # Generate summaries concurrently using ThreadPoolExecutor + # Set a reasonable timeout to prevent hanging (60 seconds per chunk, max 5 minutes total) + timeout_seconds = min(300, 60 * len(preview_texts)) + errors: list[Exception] = [] + + with concurrent.futures.ThreadPoolExecutor(max_workers=min(10, len(preview_texts))) as executor: + futures = [executor.submit(process, preview) for preview in preview_texts] + # Wait for all tasks to complete with timeout + done, not_done = concurrent.futures.wait(futures, timeout=timeout_seconds) + + # Cancel tasks that didn't complete in time + if not_done: + timeout_error_msg = ( + f"Summary generation timeout: {len(not_done)} chunks did not complete within {timeout_seconds}s" + ) + logger.warning("%s. Cancelling remaining tasks...", timeout_error_msg) + # In preview mode, timeout is also an error + errors.append(TimeoutError(timeout_error_msg)) + for future in not_done: + future.cancel() + # Wait a bit for cancellation to take effect + concurrent.futures.wait(not_done, timeout=5) + + # Collect exceptions from completed futures + for future in done: + try: + future.result() # This will raise any exception that occurred + except Exception as e: + logger.exception("Error in summary generation future") + errors.append(e) + + # In preview mode (indexing-estimate), if there are any errors, fail the request + if errors: + error_messages = [str(e) for e in errors] + error_summary = ( + f"Failed to generate summaries for {len(errors)} chunk(s). " + f"Errors: {'; '.join(error_messages[:3])}" # Show first 3 errors + ) + if len(errors) > 3: + error_summary += f" (and {len(errors) - 3} more)" + logger.error("Summary generation failed in preview mode: %s", error_summary) + raise ValueError(error_summary) + + return preview_texts diff --git a/api/core/rag/index_processor/processor/qa_index_processor.py b/api/core/rag/index_processor/processor/qa_index_processor.py index 1183d5fbd7..272d2ed351 100644 --- a/api/core/rag/index_processor/processor/qa_index_processor.py +++ b/api/core/rag/index_processor/processor/qa_index_processor.py @@ -11,6 +11,8 @@ import pandas as pd from flask import Flask, current_app from werkzeug.datastructures import FileStorage +from core.db.session_factory import session_factory +from core.entities.knowledge_entities import PreviewDetail from core.llm_generator.llm_generator import LLMGenerator from core.rag.cleaner.clean_processor import CleanProcessor from core.rag.datasource.retrieval_service import RetrievalService @@ -25,9 +27,10 @@ from core.rag.retrieval.retrieval_methods import RetrievalMethod from core.tools.utils.text_processing_utils import remove_leading_symbols from libs import helper from models.account import Account -from models.dataset import Dataset +from models.dataset import Dataset, DocumentSegment from models.dataset import Document as DatasetDocument from services.entities.knowledge_entities.knowledge_entities import Rule +from services.summary_index_service import SummaryIndexService logger = logging.getLogger(__name__) @@ -144,6 +147,31 @@ class QAIndexProcessor(BaseIndexProcessor): vector.create_multimodal(multimodal_documents) def clean(self, dataset: Dataset, node_ids: list[str] | None, with_keywords: bool = True, **kwargs): + # Note: Summary indexes are now disabled (not deleted) when segments are disabled. + # This method is called for actual deletion scenarios (e.g., when segment is deleted). + # For disable operations, disable_summaries_for_segments is called directly in the task. + # Note: qa_model doesn't generate summaries, but we clean them for completeness + # Only delete summaries if explicitly requested (e.g., when segment is actually deleted) + delete_summaries = kwargs.get("delete_summaries", False) + if delete_summaries: + if node_ids: + # Find segments by index_node_id + with session_factory.create_session() as session: + segments = ( + session.query(DocumentSegment) + .filter( + DocumentSegment.dataset_id == dataset.id, + DocumentSegment.index_node_id.in_(node_ids), + ) + .all() + ) + segment_ids = [segment.id for segment in segments] + if segment_ids: + SummaryIndexService.delete_summaries_for_segments(dataset, segment_ids) + else: + # Delete all summaries for the dataset + SummaryIndexService.delete_summaries_for_segments(dataset, None) + vector = Vector(dataset) if node_ids: vector.delete_by_ids(node_ids) @@ -212,6 +240,17 @@ class QAIndexProcessor(BaseIndexProcessor): "total_segments": len(qa_chunks.qa_chunks), } + def generate_summary_preview( + self, tenant_id: str, preview_texts: list[PreviewDetail], summary_index_setting: dict + ) -> list[PreviewDetail]: + """ + QA model doesn't generate summaries, so this method returns preview_texts unchanged. + + Note: QA model uses question-answer pairs, which don't require summary generation. + """ + # QA model doesn't generate summaries, return as-is + return preview_texts + def _format_qa_document(self, flask_app: Flask, tenant_id: str, document_node, all_qa_documents, document_language): format_documents = [] if document_node.page_content is None or not document_node.page_content.strip(): diff --git a/api/core/rag/retrieval/dataset_retrieval.py b/api/core/rag/retrieval/dataset_retrieval.py index f8f85d141a..541c241ae5 100644 --- a/api/core/rag/retrieval/dataset_retrieval.py +++ b/api/core/rag/retrieval/dataset_retrieval.py @@ -236,20 +236,24 @@ class DatasetRetrieval: if records: for record in records: segment = record.segment + # Build content: if summary exists, add it before the segment content if segment.answer: - document_context_list.append( - DocumentContext( - content=f"question:{segment.get_sign_content()} answer:{segment.answer}", - score=record.score, - ) - ) + segment_content = f"question:{segment.get_sign_content()} answer:{segment.answer}" else: - document_context_list.append( - DocumentContext( - content=segment.get_sign_content(), - score=record.score, - ) + segment_content = segment.get_sign_content() + + # If summary exists, prepend it to the content + if record.summary: + final_content = f"{record.summary}\n{segment_content}" + else: + final_content = segment_content + + document_context_list.append( + DocumentContext( + content=final_content, + score=record.score, ) + ) if vision_enabled: attachments_with_bindings = db.session.execute( select(SegmentAttachmentBinding, UploadFile) @@ -316,6 +320,9 @@ class DatasetRetrieval: source.content = f"question:{segment.content} \nanswer:{segment.answer}" else: source.content = segment.content + # Add summary if this segment was retrieved via summary + if hasattr(record, "summary") and record.summary: + source.summary = record.summary retrieval_resource_list.append(source) if hit_callback and retrieval_resource_list: retrieval_resource_list = sorted(retrieval_resource_list, key=lambda x: x.score or 0.0, reverse=True) diff --git a/api/core/tools/utils/dataset_retriever/dataset_retriever_tool.py b/api/core/tools/utils/dataset_retriever/dataset_retriever_tool.py index f96510fb45..057ec41f65 100644 --- a/api/core/tools/utils/dataset_retriever/dataset_retriever_tool.py +++ b/api/core/tools/utils/dataset_retriever/dataset_retriever_tool.py @@ -169,20 +169,24 @@ class DatasetRetrieverTool(DatasetRetrieverBaseTool): if records: for record in records: segment = record.segment + # Build content: if summary exists, add it before the segment content if segment.answer: - document_context_list.append( - DocumentContext( - content=f"question:{segment.get_sign_content()} answer:{segment.answer}", - score=record.score, - ) - ) + segment_content = f"question:{segment.get_sign_content()} answer:{segment.answer}" else: - document_context_list.append( - DocumentContext( - content=segment.get_sign_content(), - score=record.score, - ) + segment_content = segment.get_sign_content() + + # If summary exists, prepend it to the content + if record.summary: + final_content = f"{record.summary}\n{segment_content}" + else: + final_content = segment_content + + document_context_list.append( + DocumentContext( + content=final_content, + score=record.score, ) + ) if self.return_resource: for record in records: @@ -216,6 +220,9 @@ class DatasetRetrieverTool(DatasetRetrieverBaseTool): source.content = f"question:{segment.content} \nanswer:{segment.answer}" else: source.content = segment.content + # Add summary if this segment was retrieved via summary + if hasattr(record, "summary") and record.summary: + source.summary = record.summary retrieval_resource_list.append(source) if self.return_resource and retrieval_resource_list: diff --git a/api/core/workflow/nodes/knowledge_index/entities.py b/api/core/workflow/nodes/knowledge_index/entities.py index 3daca90b9b..bfeb9b5b79 100644 --- a/api/core/workflow/nodes/knowledge_index/entities.py +++ b/api/core/workflow/nodes/knowledge_index/entities.py @@ -158,3 +158,5 @@ class KnowledgeIndexNodeData(BaseNodeData): type: str = "knowledge-index" chunk_structure: str index_chunk_variable_selector: list[str] + indexing_technique: str | None = None + summary_index_setting: dict | None = None diff --git a/api/core/workflow/nodes/knowledge_index/knowledge_index_node.py b/api/core/workflow/nodes/knowledge_index/knowledge_index_node.py index 17ca4bef7b..b88c2d510f 100644 --- a/api/core/workflow/nodes/knowledge_index/knowledge_index_node.py +++ b/api/core/workflow/nodes/knowledge_index/knowledge_index_node.py @@ -1,9 +1,11 @@ +import concurrent.futures import datetime import logging import time from collections.abc import Mapping from typing import Any +from flask import current_app from sqlalchemy import func, select from core.app.entities.app_invoke_entities import InvokeFrom @@ -16,7 +18,9 @@ from core.workflow.nodes.base.node import Node from core.workflow.nodes.base.template import Template from core.workflow.runtime import VariablePool from extensions.ext_database import db -from models.dataset import Dataset, Document, DocumentSegment +from models.dataset import Dataset, Document, DocumentSegment, DocumentSegmentSummary +from services.summary_index_service import SummaryIndexService +from tasks.generate_summary_index_task import generate_summary_index_task from .entities import KnowledgeIndexNodeData from .exc import ( @@ -67,7 +71,20 @@ class KnowledgeIndexNode(Node[KnowledgeIndexNodeData]): # index knowledge try: if is_preview: - outputs = self._get_preview_output(node_data.chunk_structure, chunks) + # Preview mode: generate summaries for chunks directly without saving to database + # Format preview and generate summaries on-the-fly + # Get indexing_technique and summary_index_setting from node_data (workflow graph config) + # or fallback to dataset if not available in node_data + indexing_technique = node_data.indexing_technique or dataset.indexing_technique + summary_index_setting = node_data.summary_index_setting or dataset.summary_index_setting + + outputs = self._get_preview_output_with_summaries( + node_data.chunk_structure, + chunks, + dataset=dataset, + indexing_technique=indexing_technique, + summary_index_setting=summary_index_setting, + ) return NodeRunResult( status=WorkflowNodeExecutionStatus.SUCCEEDED, inputs=variables, @@ -148,6 +165,11 @@ class KnowledgeIndexNode(Node[KnowledgeIndexNodeData]): ) .scalar() ) + # Update need_summary based on dataset's summary_index_setting + if dataset.summary_index_setting and dataset.summary_index_setting.get("enable") is True: + document.need_summary = True + else: + document.need_summary = False db.session.add(document) # update document segment status db.session.query(DocumentSegment).where( @@ -163,6 +185,9 @@ class KnowledgeIndexNode(Node[KnowledgeIndexNodeData]): db.session.commit() + # Generate summary index if enabled + self._handle_summary_index_generation(dataset, document, variable_pool) + return { "dataset_id": ds_id_value, "dataset_name": dataset_name_value, @@ -173,9 +198,304 @@ class KnowledgeIndexNode(Node[KnowledgeIndexNodeData]): "display_status": "completed", } - def _get_preview_output(self, chunk_structure: str, chunks: Any) -> Mapping[str, Any]: + def _handle_summary_index_generation( + self, + dataset: Dataset, + document: Document, + variable_pool: VariablePool, + ) -> None: + """ + Handle summary index generation based on mode (debug/preview or production). + + Args: + dataset: Dataset containing the document + document: Document to generate summaries for + variable_pool: Variable pool to check invoke_from + """ + # Only generate summary index for high_quality indexing technique + if dataset.indexing_technique != "high_quality": + return + + # Check if summary index is enabled + summary_index_setting = dataset.summary_index_setting + if not summary_index_setting or not summary_index_setting.get("enable"): + return + + # Skip qa_model documents + if document.doc_form == "qa_model": + return + + # Determine if in preview/debug mode + invoke_from = variable_pool.get(["sys", SystemVariableKey.INVOKE_FROM]) + is_preview = invoke_from and invoke_from.value == InvokeFrom.DEBUGGER + + if is_preview: + try: + # Query segments that need summary generation + query = db.session.query(DocumentSegment).filter_by( + dataset_id=dataset.id, + document_id=document.id, + status="completed", + enabled=True, + ) + segments = query.all() + + if not segments: + logger.info("No segments found for document %s", document.id) + return + + # Filter segments based on mode + segments_to_process = [] + for segment in segments: + # Skip if summary already exists + existing_summary = ( + db.session.query(DocumentSegmentSummary) + .filter_by(chunk_id=segment.id, dataset_id=dataset.id, status="completed") + .first() + ) + if existing_summary: + continue + + # For parent-child mode, all segments are parent chunks, so process all + segments_to_process.append(segment) + + if not segments_to_process: + logger.info("No segments need summary generation for document %s", document.id) + return + + # Use ThreadPoolExecutor for concurrent generation + flask_app = current_app._get_current_object() # type: ignore + max_workers = min(10, len(segments_to_process)) # Limit to 10 workers + + def process_segment(segment: DocumentSegment) -> None: + """Process a single segment in a thread with Flask app context.""" + with flask_app.app_context(): + try: + SummaryIndexService.generate_and_vectorize_summary(segment, dataset, summary_index_setting) + except Exception: + logger.exception( + "Failed to generate summary for segment %s", + segment.id, + ) + # Continue processing other segments + + with concurrent.futures.ThreadPoolExecutor(max_workers=max_workers) as executor: + futures = [executor.submit(process_segment, segment) for segment in segments_to_process] + # Wait for all tasks to complete + concurrent.futures.wait(futures) + + logger.info( + "Successfully generated summary index for %s segments in document %s", + len(segments_to_process), + document.id, + ) + except Exception: + logger.exception("Failed to generate summary index for document %s", document.id) + # Don't fail the entire indexing process if summary generation fails + else: + # Production mode: asynchronous generation + logger.info( + "Queuing summary index generation task for document %s (production mode)", + document.id, + ) + try: + generate_summary_index_task.delay(dataset.id, document.id, None) + logger.info("Summary index generation task queued for document %s", document.id) + except Exception: + logger.exception( + "Failed to queue summary index generation task for document %s", + document.id, + ) + # Don't fail the entire indexing process if task queuing fails + + def _get_preview_output_with_summaries( + self, + chunk_structure: str, + chunks: Any, + dataset: Dataset, + indexing_technique: str | None = None, + summary_index_setting: dict | None = None, + ) -> Mapping[str, Any]: + """ + Generate preview output with summaries for chunks in preview mode. + This method generates summaries on-the-fly without saving to database. + + Args: + chunk_structure: Chunk structure type + chunks: Chunks to generate preview for + dataset: Dataset object (for tenant_id) + indexing_technique: Indexing technique from node config or dataset + summary_index_setting: Summary index setting from node config or dataset + """ index_processor = IndexProcessorFactory(chunk_structure).init_index_processor() - return index_processor.format_preview(chunks) + preview_output = index_processor.format_preview(chunks) + + # Check if summary index is enabled + if indexing_technique != "high_quality": + return preview_output + + if not summary_index_setting or not summary_index_setting.get("enable"): + return preview_output + + # Generate summaries for chunks + if "preview" in preview_output and isinstance(preview_output["preview"], list): + chunk_count = len(preview_output["preview"]) + logger.info( + "Generating summaries for %s chunks in preview mode (dataset: %s)", + chunk_count, + dataset.id, + ) + # Use ParagraphIndexProcessor's generate_summary method + from core.rag.index_processor.processor.paragraph_index_processor import ParagraphIndexProcessor + + # Get Flask app for application context in worker threads + flask_app = None + try: + flask_app = current_app._get_current_object() # type: ignore + except RuntimeError: + logger.warning("No Flask application context available, summary generation may fail") + + def generate_summary_for_chunk(preview_item: dict) -> None: + """Generate summary for a single chunk.""" + if "content" in preview_item: + # Set Flask application context in worker thread + if flask_app: + with flask_app.app_context(): + summary, _ = ParagraphIndexProcessor.generate_summary( + tenant_id=dataset.tenant_id, + text=preview_item["content"], + summary_index_setting=summary_index_setting, + ) + if summary: + preview_item["summary"] = summary + else: + # Fallback: try without app context (may fail) + summary, _ = ParagraphIndexProcessor.generate_summary( + tenant_id=dataset.tenant_id, + text=preview_item["content"], + summary_index_setting=summary_index_setting, + ) + if summary: + preview_item["summary"] = summary + + # Generate summaries concurrently using ThreadPoolExecutor + # Set a reasonable timeout to prevent hanging (60 seconds per chunk, max 5 minutes total) + timeout_seconds = min(300, 60 * len(preview_output["preview"])) + errors: list[Exception] = [] + + with concurrent.futures.ThreadPoolExecutor(max_workers=min(10, len(preview_output["preview"]))) as executor: + futures = [ + executor.submit(generate_summary_for_chunk, preview_item) + for preview_item in preview_output["preview"] + ] + # Wait for all tasks to complete with timeout + done, not_done = concurrent.futures.wait(futures, timeout=timeout_seconds) + + # Cancel tasks that didn't complete in time + if not_done: + timeout_error_msg = ( + f"Summary generation timeout: {len(not_done)} chunks did not complete within {timeout_seconds}s" + ) + logger.warning("%s. Cancelling remaining tasks...", timeout_error_msg) + # In preview mode, timeout is also an error + errors.append(TimeoutError(timeout_error_msg)) + for future in not_done: + future.cancel() + # Wait a bit for cancellation to take effect + concurrent.futures.wait(not_done, timeout=5) + + # Collect exceptions from completed futures + for future in done: + try: + future.result() # This will raise any exception that occurred + except Exception as e: + logger.exception("Error in summary generation future") + errors.append(e) + + # In preview mode, if there are any errors, fail the request + if errors: + error_messages = [str(e) for e in errors] + error_summary = ( + f"Failed to generate summaries for {len(errors)} chunk(s). " + f"Errors: {'; '.join(error_messages[:3])}" # Show first 3 errors + ) + if len(errors) > 3: + error_summary += f" (and {len(errors) - 3} more)" + logger.error("Summary generation failed in preview mode: %s", error_summary) + raise KnowledgeIndexNodeError(error_summary) + + completed_count = sum(1 for item in preview_output["preview"] if item.get("summary") is not None) + logger.info( + "Completed summary generation for preview chunks: %s/%s succeeded", + completed_count, + len(preview_output["preview"]), + ) + + return preview_output + + def _get_preview_output( + self, + chunk_structure: str, + chunks: Any, + dataset: Dataset | None = None, + variable_pool: VariablePool | None = None, + ) -> Mapping[str, Any]: + index_processor = IndexProcessorFactory(chunk_structure).init_index_processor() + preview_output = index_processor.format_preview(chunks) + + # If dataset is provided, try to enrich preview with summaries + if dataset and variable_pool: + document_id = variable_pool.get(["sys", SystemVariableKey.DOCUMENT_ID]) + if document_id: + document = db.session.query(Document).filter_by(id=document_id.value).first() + if document: + # Query summaries for this document + summaries = ( + db.session.query(DocumentSegmentSummary) + .filter_by( + dataset_id=dataset.id, + document_id=document.id, + status="completed", + enabled=True, + ) + .all() + ) + + if summaries: + # Create a map of segment content to summary for matching + # Use content matching as chunks in preview might not be indexed yet + summary_by_content = {} + for summary in summaries: + segment = ( + db.session.query(DocumentSegment) + .filter_by(id=summary.chunk_id, dataset_id=dataset.id) + .first() + ) + if segment: + # Normalize content for matching (strip whitespace) + normalized_content = segment.content.strip() + summary_by_content[normalized_content] = summary.summary_content + + # Enrich preview with summaries by content matching + if "preview" in preview_output and isinstance(preview_output["preview"], list): + matched_count = 0 + for preview_item in preview_output["preview"]: + if "content" in preview_item: + # Normalize content for matching + normalized_chunk_content = preview_item["content"].strip() + if normalized_chunk_content in summary_by_content: + preview_item["summary"] = summary_by_content[normalized_chunk_content] + matched_count += 1 + + if matched_count > 0: + logger.info( + "Enriched preview with %s existing summaries (dataset: %s, document: %s)", + matched_count, + dataset.id, + document.id, + ) + + return preview_output @classmethod def version(cls) -> str: diff --git a/api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py b/api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py index 8670a71aa3..3c4850ebac 100644 --- a/api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py +++ b/api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py @@ -419,6 +419,9 @@ class KnowledgeRetrievalNode(LLMUsageTrackingMixin, Node[KnowledgeRetrievalNodeD source["content"] = f"question:{segment.get_sign_content()} \nanswer:{segment.answer}" else: source["content"] = segment.get_sign_content() + # Add summary if available + if record.summary: + source["summary"] = record.summary retrieval_resource_list.append(source) if retrieval_resource_list: retrieval_resource_list = sorted( diff --git a/api/core/workflow/nodes/llm/node.py b/api/core/workflow/nodes/llm/node.py index dfb55dcd80..17d82c2118 100644 --- a/api/core/workflow/nodes/llm/node.py +++ b/api/core/workflow/nodes/llm/node.py @@ -685,6 +685,8 @@ class LLMNode(Node[LLMNodeData]): if "content" not in item: raise InvalidContextStructureError(f"Invalid context structure: {item}") + if item.get("summary"): + context_str += item["summary"] + "\n" context_str += item["content"] + "\n" retriever_resource = self._convert_to_original_retriever_resource(item) @@ -746,6 +748,7 @@ class LLMNode(Node[LLMNodeData]): page=metadata.get("page"), doc_metadata=metadata.get("doc_metadata"), files=context_dict.get("files"), + summary=context_dict.get("summary"), ) return source diff --git a/api/extensions/ext_celery.py b/api/extensions/ext_celery.py index 08cf96c1c1..af983f6d87 100644 --- a/api/extensions/ext_celery.py +++ b/api/extensions/ext_celery.py @@ -102,6 +102,8 @@ def init_app(app: DifyApp) -> Celery: imports = [ "tasks.async_workflow_tasks", # trigger workers "tasks.trigger_processing_tasks", # async trigger processing + "tasks.generate_summary_index_task", # summary index generation + "tasks.regenerate_summary_index_task", # summary index regeneration ] day = dify_config.CELERY_BEAT_SCHEDULER_TIME diff --git a/api/fields/dataset_fields.py b/api/fields/dataset_fields.py index 1e5ec7d200..ff6578098b 100644 --- a/api/fields/dataset_fields.py +++ b/api/fields/dataset_fields.py @@ -39,6 +39,14 @@ dataset_retrieval_model_fields = { "score_threshold_enabled": fields.Boolean, "score_threshold": fields.Float, } + +dataset_summary_index_fields = { + "enable": fields.Boolean, + "model_name": fields.String, + "model_provider_name": fields.String, + "summary_prompt": fields.String, +} + external_retrieval_model_fields = { "top_k": fields.Integer, "score_threshold": fields.Float, @@ -83,6 +91,7 @@ dataset_detail_fields = { "embedding_model_provider": fields.String, "embedding_available": fields.Boolean, "retrieval_model_dict": fields.Nested(dataset_retrieval_model_fields), + "summary_index_setting": fields.Nested(dataset_summary_index_fields), "tags": fields.List(fields.Nested(tag_fields)), "doc_form": fields.String, "external_knowledge_info": fields.Nested(external_knowledge_info_fields), diff --git a/api/fields/document_fields.py b/api/fields/document_fields.py index 9be59f7454..35a2a04f3e 100644 --- a/api/fields/document_fields.py +++ b/api/fields/document_fields.py @@ -33,6 +33,11 @@ document_fields = { "hit_count": fields.Integer, "doc_form": fields.String, "doc_metadata": fields.List(fields.Nested(document_metadata_fields), attribute="doc_metadata_details"), + # Summary index generation status: + # "SUMMARIZING" (when task is queued and generating) + "summary_index_status": fields.String, + # Whether this document needs summary index generation + "need_summary": fields.Boolean, } document_with_segments_fields = { @@ -60,6 +65,10 @@ document_with_segments_fields = { "completed_segments": fields.Integer, "total_segments": fields.Integer, "doc_metadata": fields.List(fields.Nested(document_metadata_fields), attribute="doc_metadata_details"), + # Summary index generation status: + # "SUMMARIZING" (when task is queued and generating) + "summary_index_status": fields.String, + "need_summary": fields.Boolean, # Whether this document needs summary index generation } dataset_and_document_fields = { diff --git a/api/fields/hit_testing_fields.py b/api/fields/hit_testing_fields.py index e70f9fa722..0b54992835 100644 --- a/api/fields/hit_testing_fields.py +++ b/api/fields/hit_testing_fields.py @@ -58,4 +58,5 @@ hit_testing_record_fields = { "score": fields.Float, "tsne_position": fields.Raw, "files": fields.List(fields.Nested(files_fields)), + "summary": fields.String, # Summary content if retrieved via summary index } diff --git a/api/fields/message_fields.py b/api/fields/message_fields.py index c81e482f73..e6c3b42f93 100644 --- a/api/fields/message_fields.py +++ b/api/fields/message_fields.py @@ -36,6 +36,7 @@ class RetrieverResource(ResponseModel): segment_position: int | None = None index_node_hash: str | None = None content: str | None = None + summary: str | None = None created_at: int | None = None @field_validator("created_at", mode="before") diff --git a/api/fields/segment_fields.py b/api/fields/segment_fields.py index 56d6b68378..2ce9fb154c 100644 --- a/api/fields/segment_fields.py +++ b/api/fields/segment_fields.py @@ -49,4 +49,5 @@ segment_fields = { "stopped_at": TimestampField, "child_chunks": fields.List(fields.Nested(child_chunk_fields)), "attachments": fields.List(fields.Nested(attachment_fields)), + "summary": fields.String, # Summary content for the segment } diff --git a/api/migrations/versions/2026_01_27_1815-788d3099ae3a_add_summary_index_feature.py b/api/migrations/versions/2026_01_27_1815-788d3099ae3a_add_summary_index_feature.py new file mode 100644 index 0000000000..3c2e0822e1 --- /dev/null +++ b/api/migrations/versions/2026_01_27_1815-788d3099ae3a_add_summary_index_feature.py @@ -0,0 +1,107 @@ +"""add summary index feature + +Revision ID: 788d3099ae3a +Revises: 9d77545f524e +Create Date: 2026-01-27 18:15:45.277928 + +""" +from alembic import op +import models as models +import sqlalchemy as sa + +def _is_pg(conn): + return conn.dialect.name == "postgresql" + +# revision identifiers, used by Alembic. +revision = '788d3099ae3a' +down_revision = '9d77545f524e' +branch_labels = None +depends_on = None + + +def upgrade(): + # ### commands auto generated by Alembic - please adjust! ### + conn = op.get_bind() + if _is_pg(conn): + op.create_table('document_segment_summaries', + sa.Column('id', models.types.StringUUID(), nullable=False), + sa.Column('dataset_id', models.types.StringUUID(), nullable=False), + sa.Column('document_id', models.types.StringUUID(), nullable=False), + sa.Column('chunk_id', models.types.StringUUID(), nullable=False), + sa.Column('summary_content', models.types.LongText(), nullable=True), + sa.Column('summary_index_node_id', sa.String(length=255), nullable=True), + sa.Column('summary_index_node_hash', sa.String(length=255), nullable=True), + sa.Column('tokens', sa.Integer(), nullable=True), + sa.Column('status', sa.String(length=32), server_default=sa.text("'generating'"), nullable=False), + sa.Column('error', models.types.LongText(), nullable=True), + sa.Column('enabled', sa.Boolean(), server_default=sa.text('true'), nullable=False), + sa.Column('disabled_at', sa.DateTime(), nullable=True), + sa.Column('disabled_by', models.types.StringUUID(), nullable=True), + sa.Column('created_at', sa.DateTime(), server_default=sa.text('CURRENT_TIMESTAMP'), nullable=False), + sa.Column('updated_at', sa.DateTime(), server_default=sa.text('CURRENT_TIMESTAMP'), nullable=False), + sa.PrimaryKeyConstraint('id', name='document_segment_summaries_pkey') + ) + with op.batch_alter_table('document_segment_summaries', schema=None) as batch_op: + batch_op.create_index('document_segment_summaries_chunk_id_idx', ['chunk_id'], unique=False) + batch_op.create_index('document_segment_summaries_dataset_id_idx', ['dataset_id'], unique=False) + batch_op.create_index('document_segment_summaries_document_id_idx', ['document_id'], unique=False) + batch_op.create_index('document_segment_summaries_status_idx', ['status'], unique=False) + + with op.batch_alter_table('datasets', schema=None) as batch_op: + batch_op.add_column(sa.Column('summary_index_setting', models.types.AdjustedJSON(), nullable=True)) + + with op.batch_alter_table('documents', schema=None) as batch_op: + batch_op.add_column(sa.Column('need_summary', sa.Boolean(), server_default=sa.text('false'), nullable=True)) + else: + # MySQL: Use compatible syntax + op.create_table( + 'document_segment_summaries', + sa.Column('id', models.types.StringUUID(), nullable=False), + sa.Column('dataset_id', models.types.StringUUID(), nullable=False), + sa.Column('document_id', models.types.StringUUID(), nullable=False), + sa.Column('chunk_id', models.types.StringUUID(), nullable=False), + sa.Column('summary_content', models.types.LongText(), nullable=True), + sa.Column('summary_index_node_id', sa.String(length=255), nullable=True), + sa.Column('summary_index_node_hash', sa.String(length=255), nullable=True), + sa.Column('tokens', sa.Integer(), nullable=True), + sa.Column('status', sa.String(length=32), server_default=sa.text("'generating'"), nullable=False), + sa.Column('error', models.types.LongText(), nullable=True), + sa.Column('enabled', sa.Boolean(), server_default=sa.text('true'), nullable=False), + sa.Column('disabled_at', sa.DateTime(), nullable=True), + sa.Column('disabled_by', models.types.StringUUID(), nullable=True), + sa.Column('created_at', sa.DateTime(), server_default=sa.text('CURRENT_TIMESTAMP'), nullable=False), + sa.Column('updated_at', sa.DateTime(), server_default=sa.text('CURRENT_TIMESTAMP'), nullable=False), + sa.PrimaryKeyConstraint('id', name='document_segment_summaries_pkey'), + ) + with op.batch_alter_table('document_segment_summaries', schema=None) as batch_op: + batch_op.create_index('document_segment_summaries_chunk_id_idx', ['chunk_id'], unique=False) + batch_op.create_index('document_segment_summaries_dataset_id_idx', ['dataset_id'], unique=False) + batch_op.create_index('document_segment_summaries_document_id_idx', ['document_id'], unique=False) + batch_op.create_index('document_segment_summaries_status_idx', ['status'], unique=False) + + with op.batch_alter_table('datasets', schema=None) as batch_op: + batch_op.add_column(sa.Column('summary_index_setting', models.types.AdjustedJSON(), nullable=True)) + + with op.batch_alter_table('documents', schema=None) as batch_op: + batch_op.add_column(sa.Column('need_summary', sa.Boolean(), server_default=sa.text('false'), nullable=True)) + + # ### end Alembic commands ### + + +def downgrade(): + # ### commands auto generated by Alembic - please adjust! ### + + with op.batch_alter_table('documents', schema=None) as batch_op: + batch_op.drop_column('need_summary') + + with op.batch_alter_table('datasets', schema=None) as batch_op: + batch_op.drop_column('summary_index_setting') + + with op.batch_alter_table('document_segment_summaries', schema=None) as batch_op: + batch_op.drop_index('document_segment_summaries_status_idx') + batch_op.drop_index('document_segment_summaries_document_id_idx') + batch_op.drop_index('document_segment_summaries_dataset_id_idx') + batch_op.drop_index('document_segment_summaries_chunk_id_idx') + + op.drop_table('document_segment_summaries') + # ### end Alembic commands ### diff --git a/api/models/dataset.py b/api/models/dataset.py index 62f11b8c72..6ab8f372bf 100644 --- a/api/models/dataset.py +++ b/api/models/dataset.py @@ -72,6 +72,7 @@ class Dataset(Base): keyword_number = mapped_column(sa.Integer, nullable=True, server_default=sa.text("10")) collection_binding_id = mapped_column(StringUUID, nullable=True) retrieval_model = mapped_column(AdjustedJSON, nullable=True) + summary_index_setting = mapped_column(AdjustedJSON, nullable=True) built_in_field_enabled = mapped_column(sa.Boolean, nullable=False, server_default=sa.text("false")) icon_info = mapped_column(AdjustedJSON, nullable=True) runtime_mode = mapped_column(sa.String(255), nullable=True, server_default=sa.text("'general'")) @@ -419,6 +420,7 @@ class Document(Base): doc_metadata = mapped_column(AdjustedJSON, nullable=True) doc_form = mapped_column(String(255), nullable=False, server_default=sa.text("'text_model'")) doc_language = mapped_column(String(255), nullable=True) + need_summary: Mapped[bool | None] = mapped_column(sa.Boolean, nullable=True, server_default=sa.text("false")) DATA_SOURCES = ["upload_file", "notion_import", "website_crawl"] @@ -1575,3 +1577,36 @@ class SegmentAttachmentBinding(Base): segment_id: Mapped[str] = mapped_column(StringUUID, nullable=False) attachment_id: Mapped[str] = mapped_column(StringUUID, nullable=False) created_at: Mapped[datetime] = mapped_column(sa.DateTime, nullable=False, server_default=func.current_timestamp()) + + +class DocumentSegmentSummary(Base): + __tablename__ = "document_segment_summaries" + __table_args__ = ( + sa.PrimaryKeyConstraint("id", name="document_segment_summaries_pkey"), + sa.Index("document_segment_summaries_dataset_id_idx", "dataset_id"), + sa.Index("document_segment_summaries_document_id_idx", "document_id"), + sa.Index("document_segment_summaries_chunk_id_idx", "chunk_id"), + sa.Index("document_segment_summaries_status_idx", "status"), + ) + + id: Mapped[str] = mapped_column(StringUUID, nullable=False, default=lambda: str(uuid4())) + dataset_id: Mapped[str] = mapped_column(StringUUID, nullable=False) + document_id: Mapped[str] = mapped_column(StringUUID, nullable=False) + # corresponds to DocumentSegment.id or parent chunk id + chunk_id: Mapped[str] = mapped_column(StringUUID, nullable=False) + summary_content: Mapped[str] = mapped_column(LongText, nullable=True) + summary_index_node_id: Mapped[str] = mapped_column(String(255), nullable=True) + summary_index_node_hash: Mapped[str] = mapped_column(String(255), nullable=True) + tokens: Mapped[int | None] = mapped_column(sa.Integer, nullable=True) + status: Mapped[str] = mapped_column(String(32), nullable=False, server_default=sa.text("'generating'")) + error: Mapped[str] = mapped_column(LongText, nullable=True) + enabled: Mapped[bool] = mapped_column(sa.Boolean, nullable=False, server_default=sa.text("true")) + disabled_at: Mapped[datetime | None] = mapped_column(DateTime, nullable=True) + disabled_by = mapped_column(StringUUID, nullable=True) + created_at: Mapped[datetime] = mapped_column(DateTime, nullable=False, server_default=func.current_timestamp()) + updated_at: Mapped[datetime] = mapped_column( + DateTime, nullable=False, server_default=func.current_timestamp(), onupdate=func.current_timestamp() + ) + + def __repr__(self): + return f"" diff --git a/api/services/dataset_service.py b/api/services/dataset_service.py index be9a0e9279..0b3fcbe4ae 100644 --- a/api/services/dataset_service.py +++ b/api/services/dataset_service.py @@ -89,6 +89,7 @@ from tasks.disable_segments_from_index_task import disable_segments_from_index_t from tasks.document_indexing_update_task import document_indexing_update_task from tasks.enable_segments_to_index_task import enable_segments_to_index_task from tasks.recover_document_indexing_task import recover_document_indexing_task +from tasks.regenerate_summary_index_task import regenerate_summary_index_task from tasks.remove_document_from_index_task import remove_document_from_index_task from tasks.retry_document_indexing_task import retry_document_indexing_task from tasks.sync_website_document_indexing_task import sync_website_document_indexing_task @@ -211,6 +212,7 @@ class DatasetService: embedding_model_provider: str | None = None, embedding_model_name: str | None = None, retrieval_model: RetrievalModel | None = None, + summary_index_setting: dict | None = None, ): # check if dataset name already exists if db.session.query(Dataset).filter_by(name=name, tenant_id=tenant_id).first(): @@ -253,6 +255,8 @@ class DatasetService: dataset.retrieval_model = retrieval_model.model_dump() if retrieval_model else None dataset.permission = permission or DatasetPermissionEnum.ONLY_ME dataset.provider = provider + if summary_index_setting is not None: + dataset.summary_index_setting = summary_index_setting db.session.add(dataset) db.session.flush() @@ -476,6 +480,11 @@ class DatasetService: if external_retrieval_model: dataset.retrieval_model = external_retrieval_model + # Update summary index setting if provided + summary_index_setting = data.get("summary_index_setting", None) + if summary_index_setting is not None: + dataset.summary_index_setting = summary_index_setting + # Update basic dataset properties dataset.name = data.get("name", dataset.name) dataset.description = data.get("description", dataset.description) @@ -564,6 +573,9 @@ class DatasetService: # update Retrieval model if data.get("retrieval_model"): filtered_data["retrieval_model"] = data["retrieval_model"] + # update summary index setting + if data.get("summary_index_setting"): + filtered_data["summary_index_setting"] = data.get("summary_index_setting") # update icon info if data.get("icon_info"): filtered_data["icon_info"] = data.get("icon_info") @@ -572,12 +584,27 @@ class DatasetService: db.session.query(Dataset).filter_by(id=dataset.id).update(filtered_data) db.session.commit() + # Reload dataset to get updated values + db.session.refresh(dataset) + # update pipeline knowledge base node data DatasetService._update_pipeline_knowledge_base_node_data(dataset, user.id) # Trigger vector index task if indexing technique changed if action: deal_dataset_vector_index_task.delay(dataset.id, action) + # If embedding_model changed, also regenerate summary vectors + if action == "update": + regenerate_summary_index_task.delay( + dataset.id, + regenerate_reason="embedding_model_changed", + regenerate_vectors_only=True, + ) + + # Note: summary_index_setting changes do not trigger automatic regeneration of existing summaries. + # The new setting will only apply to: + # 1. New documents added after the setting change + # 2. Manual summary generation requests return dataset @@ -616,6 +643,7 @@ class DatasetService: knowledge_index_node_data["chunk_structure"] = dataset.chunk_structure knowledge_index_node_data["indexing_technique"] = dataset.indexing_technique # pyright: ignore[reportAttributeAccessIssue] knowledge_index_node_data["keyword_number"] = dataset.keyword_number + knowledge_index_node_data["summary_index_setting"] = dataset.summary_index_setting node["data"] = knowledge_index_node_data updated = True except Exception: @@ -854,6 +882,54 @@ class DatasetService: ) filtered_data["collection_binding_id"] = dataset_collection_binding.id + @staticmethod + def _check_summary_index_setting_model_changed(dataset: Dataset, data: dict[str, Any]) -> bool: + """ + Check if summary_index_setting model (model_name or model_provider_name) has changed. + + Args: + dataset: Current dataset object + data: Update data dictionary + + Returns: + bool: True if summary model changed, False otherwise + """ + # Check if summary_index_setting is being updated + if "summary_index_setting" not in data or data.get("summary_index_setting") is None: + return False + + new_summary_setting = data.get("summary_index_setting") + old_summary_setting = dataset.summary_index_setting + + # If new setting is disabled, no need to regenerate + if not new_summary_setting or not new_summary_setting.get("enable"): + return False + + # If old setting doesn't exist, no need to regenerate (no existing summaries to regenerate) + # Note: This task only regenerates existing summaries, not generates new ones + if not old_summary_setting: + return False + + # Compare model_name and model_provider_name + old_model_name = old_summary_setting.get("model_name") + old_model_provider = old_summary_setting.get("model_provider_name") + new_model_name = new_summary_setting.get("model_name") + new_model_provider = new_summary_setting.get("model_provider_name") + + # Check if model changed + if old_model_name != new_model_name or old_model_provider != new_model_provider: + logger.info( + "Summary index setting model changed for dataset %s: old=%s/%s, new=%s/%s", + dataset.id, + old_model_provider, + old_model_name, + new_model_provider, + new_model_name, + ) + return True + + return False + @staticmethod def update_rag_pipeline_dataset_settings( session: Session, dataset: Dataset, knowledge_configuration: KnowledgeConfiguration, has_published: bool = False @@ -889,6 +965,9 @@ class DatasetService: else: raise ValueError("Invalid index method") dataset.retrieval_model = knowledge_configuration.retrieval_model.model_dump() + # Update summary_index_setting if provided + if knowledge_configuration.summary_index_setting is not None: + dataset.summary_index_setting = knowledge_configuration.summary_index_setting session.add(dataset) else: if dataset.chunk_structure and dataset.chunk_structure != knowledge_configuration.chunk_structure: @@ -994,6 +1073,9 @@ class DatasetService: if dataset.keyword_number != knowledge_configuration.keyword_number: dataset.keyword_number = knowledge_configuration.keyword_number dataset.retrieval_model = knowledge_configuration.retrieval_model.model_dump() + # Update summary_index_setting if provided + if knowledge_configuration.summary_index_setting is not None: + dataset.summary_index_setting = knowledge_configuration.summary_index_setting session.add(dataset) session.commit() if action: @@ -1314,6 +1396,50 @@ class DocumentService: upload_file = DocumentService._get_upload_file_for_upload_file_document(document) return file_helpers.get_signed_file_url(upload_file_id=upload_file.id, as_attachment=True) + @staticmethod + def enrich_documents_with_summary_index_status( + documents: Sequence[Document], + dataset: Dataset, + tenant_id: str, + ) -> None: + """ + Enrich documents with summary_index_status based on dataset summary index settings. + + This method calculates and sets the summary_index_status for each document that needs summary. + Documents that don't need summary or when summary index is disabled will have status set to None. + + Args: + documents: List of Document instances to enrich + dataset: Dataset instance containing summary_index_setting + tenant_id: Tenant ID for summary status lookup + """ + # Check if dataset has summary index enabled + has_summary_index = dataset.summary_index_setting and dataset.summary_index_setting.get("enable") is True + + # Filter documents that need summary calculation + documents_need_summary = [doc for doc in documents if doc.need_summary is True] + document_ids_need_summary = [str(doc.id) for doc in documents_need_summary] + + # Calculate summary_index_status for documents that need summary (only if dataset summary index is enabled) + summary_status_map: dict[str, str | None] = {} + if has_summary_index and document_ids_need_summary: + from services.summary_index_service import SummaryIndexService + + summary_status_map = SummaryIndexService.get_documents_summary_index_status( + document_ids=document_ids_need_summary, + dataset_id=dataset.id, + tenant_id=tenant_id, + ) + + # Add summary_index_status to each document + for document in documents: + if has_summary_index and document.need_summary is True: + # Get status from map, default to None (not queued yet) + document.summary_index_status = summary_status_map.get(str(document.id)) # type: ignore[attr-defined] + else: + # Return null if summary index is not enabled or document doesn't need summary + document.summary_index_status = None # type: ignore[attr-defined] + @staticmethod def prepare_document_batch_download_zip( *, @@ -1964,6 +2090,8 @@ class DocumentService: DuplicateDocumentIndexingTaskProxy( dataset.tenant_id, dataset.id, duplicate_document_ids ).delay() + # Note: Summary index generation is triggered in document_indexing_task after indexing completes + # to ensure segments are available. See tasks/document_indexing_task.py except LockNotOwnedError: pass @@ -2268,6 +2396,11 @@ class DocumentService: name: str, batch: str, ): + # Set need_summary based on dataset's summary_index_setting + need_summary = False + if dataset.summary_index_setting and dataset.summary_index_setting.get("enable") is True: + need_summary = True + document = Document( tenant_id=dataset.tenant_id, dataset_id=dataset.id, @@ -2281,6 +2414,7 @@ class DocumentService: created_by=account.id, doc_form=document_form, doc_language=document_language, + need_summary=need_summary, ) doc_metadata = {} if dataset.built_in_field_enabled: @@ -2505,6 +2639,7 @@ class DocumentService: embedding_model_provider=knowledge_config.embedding_model_provider, collection_binding_id=dataset_collection_binding_id, retrieval_model=retrieval_model.model_dump() if retrieval_model else None, + summary_index_setting=knowledge_config.summary_index_setting, is_multimodal=knowledge_config.is_multimodal, ) @@ -2686,6 +2821,14 @@ class DocumentService: if not isinstance(args["process_rule"]["rules"]["segmentation"]["max_tokens"], int): raise ValueError("Process rule segmentation max_tokens is invalid") + # valid summary index setting + summary_index_setting = args["process_rule"].get("summary_index_setting") + if summary_index_setting and summary_index_setting.get("enable"): + if "model_name" not in summary_index_setting or not summary_index_setting["model_name"]: + raise ValueError("Summary index model name is required") + if "model_provider_name" not in summary_index_setting or not summary_index_setting["model_provider_name"]: + raise ValueError("Summary index model provider name is required") + @staticmethod def batch_update_document_status( dataset: Dataset, document_ids: list[str], action: Literal["enable", "disable", "archive", "un_archive"], user @@ -3154,6 +3297,35 @@ class SegmentService: if args.enabled or keyword_changed: # update segment vector index VectorService.update_segment_vector(args.keywords, segment, dataset) + # update summary index if summary is provided and has changed + if args.summary is not None: + # When user manually provides summary, allow saving even if summary_index_setting doesn't exist + # summary_index_setting is only needed for LLM generation, not for manual summary vectorization + # Vectorization uses dataset.embedding_model, which doesn't require summary_index_setting + if dataset.indexing_technique == "high_quality": + # Query existing summary from database + from models.dataset import DocumentSegmentSummary + + existing_summary = ( + db.session.query(DocumentSegmentSummary) + .where( + DocumentSegmentSummary.chunk_id == segment.id, + DocumentSegmentSummary.dataset_id == dataset.id, + ) + .first() + ) + + # Check if summary has changed + existing_summary_content = existing_summary.summary_content if existing_summary else None + if existing_summary_content != args.summary: + # Summary has changed, update it + from services.summary_index_service import SummaryIndexService + + try: + SummaryIndexService.update_summary_for_segment(segment, dataset, args.summary) + except Exception: + logger.exception("Failed to update summary for segment %s", segment.id) + # Don't fail the entire update if summary update fails else: segment_hash = helper.generate_text_hash(content) tokens = 0 @@ -3228,6 +3400,73 @@ class SegmentService: elif document.doc_form in (IndexStructureType.PARAGRAPH_INDEX, IndexStructureType.QA_INDEX): # update segment vector index VectorService.update_segment_vector(args.keywords, segment, dataset) + # Handle summary index when content changed + if dataset.indexing_technique == "high_quality": + from models.dataset import DocumentSegmentSummary + + existing_summary = ( + db.session.query(DocumentSegmentSummary) + .where( + DocumentSegmentSummary.chunk_id == segment.id, + DocumentSegmentSummary.dataset_id == dataset.id, + ) + .first() + ) + + if args.summary is None: + # User didn't provide summary, auto-regenerate if segment previously had summary + # Auto-regeneration only happens if summary_index_setting exists and enable is True + if ( + existing_summary + and dataset.summary_index_setting + and dataset.summary_index_setting.get("enable") is True + ): + # Segment previously had summary, regenerate it with new content + from services.summary_index_service import SummaryIndexService + + try: + SummaryIndexService.generate_and_vectorize_summary( + segment, dataset, dataset.summary_index_setting + ) + logger.info("Auto-regenerated summary for segment %s after content change", segment.id) + except Exception: + logger.exception("Failed to auto-regenerate summary for segment %s", segment.id) + # Don't fail the entire update if summary regeneration fails + else: + # User provided summary, check if it has changed + # Manual summary updates are allowed even if summary_index_setting doesn't exist + existing_summary_content = existing_summary.summary_content if existing_summary else None + if existing_summary_content != args.summary: + # Summary has changed, use user-provided summary + from services.summary_index_service import SummaryIndexService + + try: + SummaryIndexService.update_summary_for_segment(segment, dataset, args.summary) + logger.info("Updated summary for segment %s with user-provided content", segment.id) + except Exception: + logger.exception("Failed to update summary for segment %s", segment.id) + # Don't fail the entire update if summary update fails + else: + # Summary hasn't changed, regenerate based on new content + # Auto-regeneration only happens if summary_index_setting exists and enable is True + if ( + existing_summary + and dataset.summary_index_setting + and dataset.summary_index_setting.get("enable") is True + ): + from services.summary_index_service import SummaryIndexService + + try: + SummaryIndexService.generate_and_vectorize_summary( + segment, dataset, dataset.summary_index_setting + ) + logger.info( + "Regenerated summary for segment %s after content change (summary unchanged)", + segment.id, + ) + except Exception: + logger.exception("Failed to regenerate summary for segment %s", segment.id) + # Don't fail the entire update if summary regeneration fails # update multimodel vector index VectorService.update_multimodel_vector(segment, args.attachment_ids or [], dataset) except Exception as e: @@ -3616,6 +3855,39 @@ class SegmentService: ) return result if isinstance(result, DocumentSegment) else None + @classmethod + def get_segments_by_document_and_dataset( + cls, + document_id: str, + dataset_id: str, + status: str | None = None, + enabled: bool | None = None, + ) -> Sequence[DocumentSegment]: + """ + Get segments for a document in a dataset with optional filtering. + + Args: + document_id: Document ID + dataset_id: Dataset ID + status: Optional status filter (e.g., "completed") + enabled: Optional enabled filter (True/False) + + Returns: + Sequence of DocumentSegment instances + """ + query = select(DocumentSegment).where( + DocumentSegment.document_id == document_id, + DocumentSegment.dataset_id == dataset_id, + ) + + if status is not None: + query = query.where(DocumentSegment.status == status) + + if enabled is not None: + query = query.where(DocumentSegment.enabled == enabled) + + return db.session.scalars(query).all() + class DatasetCollectionBindingService: @classmethod diff --git a/api/services/entities/knowledge_entities/knowledge_entities.py b/api/services/entities/knowledge_entities/knowledge_entities.py index 7959734e89..8dc5b93501 100644 --- a/api/services/entities/knowledge_entities/knowledge_entities.py +++ b/api/services/entities/knowledge_entities/knowledge_entities.py @@ -119,6 +119,7 @@ class KnowledgeConfig(BaseModel): data_source: DataSource | None = None process_rule: ProcessRule | None = None retrieval_model: RetrievalModel | None = None + summary_index_setting: dict | None = None doc_form: str = "text_model" doc_language: str = "English" embedding_model: str | None = None @@ -141,6 +142,7 @@ class SegmentUpdateArgs(BaseModel): regenerate_child_chunks: bool = False enabled: bool | None = None attachment_ids: list[str] | None = None + summary: str | None = None # Summary content for summary index class ChildChunkUpdateArgs(BaseModel): diff --git a/api/services/entities/knowledge_entities/rag_pipeline_entities.py b/api/services/entities/knowledge_entities/rag_pipeline_entities.py index cbb0efcc2a..041ae4edba 100644 --- a/api/services/entities/knowledge_entities/rag_pipeline_entities.py +++ b/api/services/entities/knowledge_entities/rag_pipeline_entities.py @@ -116,6 +116,8 @@ class KnowledgeConfiguration(BaseModel): embedding_model: str = "" keyword_number: int | None = 10 retrieval_model: RetrievalSetting + # add summary index setting + summary_index_setting: dict | None = None @field_validator("embedding_model_provider", mode="before") @classmethod diff --git a/api/services/rag_pipeline/rag_pipeline_dsl_service.py b/api/services/rag_pipeline/rag_pipeline_dsl_service.py index c1c6e204fb..be1ce834f6 100644 --- a/api/services/rag_pipeline/rag_pipeline_dsl_service.py +++ b/api/services/rag_pipeline/rag_pipeline_dsl_service.py @@ -343,6 +343,9 @@ class RagPipelineDslService: dataset.embedding_model_provider = knowledge_configuration.embedding_model_provider elif knowledge_configuration.indexing_technique == "economy": dataset.keyword_number = knowledge_configuration.keyword_number + # Update summary_index_setting if provided + if knowledge_configuration.summary_index_setting is not None: + dataset.summary_index_setting = knowledge_configuration.summary_index_setting dataset.pipeline_id = pipeline.id self._session.add(dataset) self._session.commit() @@ -477,6 +480,9 @@ class RagPipelineDslService: dataset.embedding_model_provider = knowledge_configuration.embedding_model_provider elif knowledge_configuration.indexing_technique == "economy": dataset.keyword_number = knowledge_configuration.keyword_number + # Update summary_index_setting if provided + if knowledge_configuration.summary_index_setting is not None: + dataset.summary_index_setting = knowledge_configuration.summary_index_setting dataset.pipeline_id = pipeline.id self._session.add(dataset) self._session.commit() diff --git a/api/services/summary_index_service.py b/api/services/summary_index_service.py new file mode 100644 index 0000000000..b8e1f8bc3f --- /dev/null +++ b/api/services/summary_index_service.py @@ -0,0 +1,1432 @@ +"""Summary index service for generating and managing document segment summaries.""" + +import logging +import time +import uuid +from datetime import UTC, datetime +from typing import Any + +from sqlalchemy.orm import Session + +from core.db.session_factory import session_factory +from core.model_manager import ModelManager +from core.model_runtime.entities.llm_entities import LLMUsage +from core.model_runtime.entities.model_entities import ModelType +from core.rag.datasource.vdb.vector_factory import Vector +from core.rag.index_processor.constant.doc_type import DocType +from core.rag.models.document import Document +from libs import helper +from models.dataset import Dataset, DocumentSegment, DocumentSegmentSummary +from models.dataset import Document as DatasetDocument + +logger = logging.getLogger(__name__) + + +class SummaryIndexService: + """Service for generating and managing summary indexes.""" + + @staticmethod + def generate_summary_for_segment( + segment: DocumentSegment, + dataset: Dataset, + summary_index_setting: dict, + ) -> tuple[str, LLMUsage]: + """ + Generate summary for a single segment. + + Args: + segment: DocumentSegment to generate summary for + dataset: Dataset containing the segment + summary_index_setting: Summary index configuration + + Returns: + Tuple of (summary_content, llm_usage) where llm_usage is LLMUsage object + + Raises: + ValueError: If summary_index_setting is invalid or generation fails + """ + # Reuse the existing generate_summary method from ParagraphIndexProcessor + # Use lazy import to avoid circular import + from core.rag.index_processor.processor.paragraph_index_processor import ParagraphIndexProcessor + + summary_content, usage = ParagraphIndexProcessor.generate_summary( + tenant_id=dataset.tenant_id, + text=segment.content, + summary_index_setting=summary_index_setting, + segment_id=segment.id, + ) + + if not summary_content: + raise ValueError("Generated summary is empty") + + return summary_content, usage + + @staticmethod + def create_summary_record( + segment: DocumentSegment, + dataset: Dataset, + summary_content: str, + status: str = "generating", + ) -> DocumentSegmentSummary: + """ + Create or update a DocumentSegmentSummary record. + If a summary record already exists for this segment, it will be updated instead of creating a new one. + + Args: + segment: DocumentSegment to create summary for + dataset: Dataset containing the segment + summary_content: Generated summary content + status: Summary status (default: "generating") + + Returns: + Created or updated DocumentSegmentSummary instance + """ + with session_factory.create_session() as session: + # Check if summary record already exists + existing_summary = ( + session.query(DocumentSegmentSummary).filter_by(chunk_id=segment.id, dataset_id=dataset.id).first() + ) + + if existing_summary: + # Update existing record + existing_summary.summary_content = summary_content + existing_summary.status = status + existing_summary.error = None # type: ignore[assignment] # Clear any previous errors + # Re-enable if it was disabled + if not existing_summary.enabled: + existing_summary.enabled = True + existing_summary.disabled_at = None + existing_summary.disabled_by = None + session.add(existing_summary) + session.flush() + return existing_summary + else: + # Create new record (enabled by default) + summary_record = DocumentSegmentSummary( + dataset_id=dataset.id, + document_id=segment.document_id, + chunk_id=segment.id, + summary_content=summary_content, + status=status, + enabled=True, # Explicitly set enabled to True + ) + session.add(summary_record) + session.flush() + return summary_record + + @staticmethod + def vectorize_summary( + summary_record: DocumentSegmentSummary, + segment: DocumentSegment, + dataset: Dataset, + session: Session | None = None, + ) -> None: + """ + Vectorize summary and store in vector database. + + Args: + summary_record: DocumentSegmentSummary record + segment: Original DocumentSegment + dataset: Dataset containing the segment + session: Optional SQLAlchemy session. If provided, uses this session instead of creating a new one. + If not provided, creates a new session and commits automatically. + """ + if dataset.indexing_technique != "high_quality": + logger.warning( + "Summary vectorization skipped for dataset %s: indexing_technique is not high_quality", + dataset.id, + ) + return + + # Get summary_record_id for later session queries + summary_record_id = summary_record.id + # Save the original session parameter for use in error handling + original_session = session + logger.debug( + "Starting vectorization for segment %s, summary_record_id=%s, using_provided_session=%s", + segment.id, + summary_record_id, + original_session is not None, + ) + + # Reuse existing index_node_id if available (like segment does), otherwise generate new one + old_summary_node_id = summary_record.summary_index_node_id + if old_summary_node_id: + # Reuse existing index_node_id (like segment behavior) + summary_index_node_id = old_summary_node_id + logger.debug("Reusing existing index_node_id %s for segment %s", summary_index_node_id, segment.id) + else: + # Generate new index node ID only for new summaries + summary_index_node_id = str(uuid.uuid4()) + logger.debug("Generated new index_node_id %s for segment %s", summary_index_node_id, segment.id) + + # Always regenerate hash (in case summary content changed) + summary_content = summary_record.summary_content + if not summary_content or not summary_content.strip(): + raise ValueError(f"Summary content is empty for segment {segment.id}, cannot vectorize") + summary_hash = helper.generate_text_hash(summary_content) + + # Delete old vector only if we're reusing the same index_node_id (to overwrite) + # If index_node_id changed, the old vector should have been deleted elsewhere + if old_summary_node_id and old_summary_node_id == summary_index_node_id: + try: + vector = Vector(dataset) + vector.delete_by_ids([old_summary_node_id]) + except Exception as e: + logger.warning( + "Failed to delete old summary vector for segment %s: %s. Continuing with new vectorization.", + segment.id, + str(e), + ) + + # Calculate embedding tokens for summary (for logging and statistics) + embedding_tokens = 0 + try: + model_manager = ModelManager() + embedding_model = model_manager.get_model_instance( + tenant_id=dataset.tenant_id, + provider=dataset.embedding_model_provider, + model_type=ModelType.TEXT_EMBEDDING, + model=dataset.embedding_model, + ) + if embedding_model: + tokens_list = embedding_model.get_text_embedding_num_tokens([summary_content]) + embedding_tokens = tokens_list[0] if tokens_list else 0 + except Exception as e: + logger.warning("Failed to calculate embedding tokens for summary: %s", str(e)) + + # Create document with summary content and metadata + summary_document = Document( + page_content=summary_content, + metadata={ + "doc_id": summary_index_node_id, + "doc_hash": summary_hash, + "dataset_id": dataset.id, + "document_id": segment.document_id, + "original_chunk_id": segment.id, # Key: link to original chunk + "doc_type": DocType.TEXT, + "is_summary": True, # Identifier for summary documents + }, + ) + + # Vectorize and store with retry mechanism for connection errors + max_retries = 3 + retry_delay = 2.0 + + for attempt in range(max_retries): + try: + logger.debug( + "Attempting to vectorize summary for segment %s (attempt %s/%s)", + segment.id, + attempt + 1, + max_retries, + ) + vector = Vector(dataset) + # Use duplicate_check=False to ensure re-vectorization even if old vector still exists + # The old vector should have been deleted above, but if deletion failed, + # we still want to re-vectorize (upsert will overwrite) + vector.add_texts([summary_document], duplicate_check=False) + logger.debug( + "Successfully added summary vector to database for segment %s (attempt %s/%s)", + segment.id, + attempt + 1, + max_retries, + ) + + # Log embedding token usage + if embedding_tokens > 0: + logger.info( + "Summary embedding for segment %s used %s tokens", + segment.id, + embedding_tokens, + ) + + # Success - update summary record with index node info + # Use provided session if available, otherwise create a new one + use_provided_session = session is not None + if not use_provided_session: + logger.debug("Creating new session for vectorization of segment %s", segment.id) + session_context = session_factory.create_session() + session = session_context.__enter__() + else: + logger.debug("Using provided session for vectorization of segment %s", segment.id) + session_context = None # Don't use context manager for provided session + + # At this point, session is guaranteed to be not None + # Type narrowing: session is definitely not None after the if/else above + if session is None: + raise RuntimeError("Session should not be None at this point") + + try: + # Declare summary_record_in_session variable + summary_record_in_session: DocumentSegmentSummary | None + + # If using provided session, merge the summary_record into it + if use_provided_session: + # Merge the summary_record into the provided session + logger.debug( + "Merging summary_record (id=%s) into provided session for segment %s", + summary_record_id, + segment.id, + ) + summary_record_in_session = session.merge(summary_record) + logger.debug( + "Successfully merged summary_record for segment %s, merged_id=%s", + segment.id, + summary_record_in_session.id, + ) + else: + # Query the summary record in the new session + logger.debug( + "Querying summary_record by id=%s for segment %s in new session", + summary_record_id, + segment.id, + ) + summary_record_in_session = ( + session.query(DocumentSegmentSummary).filter_by(id=summary_record_id).first() + ) + + if not summary_record_in_session: + # Record not found - try to find by chunk_id and dataset_id instead + logger.debug( + "Summary record not found by id=%s, trying chunk_id=%s and dataset_id=%s " + "for segment %s", + summary_record_id, + segment.id, + dataset.id, + segment.id, + ) + summary_record_in_session = ( + session.query(DocumentSegmentSummary) + .filter_by(chunk_id=segment.id, dataset_id=dataset.id) + .first() + ) + + if not summary_record_in_session: + # Still not found - create a new one using the parameter data + logger.warning( + "Summary record not found in database for segment %s (id=%s), creating new one. " + "This may indicate a session isolation issue.", + segment.id, + summary_record_id, + ) + summary_record_in_session = DocumentSegmentSummary( + id=summary_record_id, # Use the same ID if available + dataset_id=dataset.id, + document_id=segment.document_id, + chunk_id=segment.id, + summary_content=summary_content, + summary_index_node_id=summary_index_node_id, + summary_index_node_hash=summary_hash, + tokens=embedding_tokens, + status="completed", + enabled=True, + ) + session.add(summary_record_in_session) + logger.info( + "Created new summary record (id=%s) for segment %s after vectorization", + summary_record_id, + segment.id, + ) + else: + # Found by chunk_id - update it + logger.info( + "Found summary record for segment %s by chunk_id " + "(id mismatch: expected %s, found %s). " + "This may indicate the record was created in a different session.", + segment.id, + summary_record_id, + summary_record_in_session.id, + ) + else: + logger.debug( + "Found summary_record (id=%s) for segment %s in new session", + summary_record_id, + segment.id, + ) + + # At this point, summary_record_in_session is guaranteed to be not None + if summary_record_in_session is None: + raise RuntimeError("summary_record_in_session should not be None at this point") + + # Update all fields including summary_content + # Always use the summary_content from the parameter (which is the latest from outer session) + # rather than relying on what's in the database, in case outer session hasn't committed yet + summary_record_in_session.summary_index_node_id = summary_index_node_id + summary_record_in_session.summary_index_node_hash = summary_hash + summary_record_in_session.tokens = embedding_tokens # Save embedding tokens + summary_record_in_session.status = "completed" + # Ensure summary_content is preserved (use the latest from summary_record parameter) + # This is critical: use the parameter value, not the database value + summary_record_in_session.summary_content = summary_content + # Explicitly update updated_at to ensure it's refreshed even if other fields haven't changed + summary_record_in_session.updated_at = datetime.now(UTC).replace(tzinfo=None) + session.add(summary_record_in_session) + + # Only commit if we created the session ourselves + if not use_provided_session: + logger.debug("Committing session for segment %s (self-created session)", segment.id) + session.commit() + logger.debug("Successfully committed session for segment %s", segment.id) + else: + # When using provided session, flush to ensure changes are written to database + # This prevents refresh() from overwriting our changes + logger.debug( + "Flushing session for segment %s (using provided session, caller will commit)", + segment.id, + ) + session.flush() + logger.debug("Successfully flushed session for segment %s", segment.id) + # If using provided session, let the caller handle commit + + logger.info( + "Successfully vectorized summary for segment %s, index_node_id=%s, index_node_hash=%s, " + "tokens=%s, summary_record_id=%s, use_provided_session=%s", + segment.id, + summary_index_node_id, + summary_hash, + embedding_tokens, + summary_record_in_session.id, + use_provided_session, + ) + # Update the original object for consistency + summary_record.summary_index_node_id = summary_index_node_id + summary_record.summary_index_node_hash = summary_hash + summary_record.tokens = embedding_tokens + summary_record.status = "completed" + summary_record.summary_content = summary_content + if summary_record_in_session.updated_at: + summary_record.updated_at = summary_record_in_session.updated_at + finally: + # Only close session if we created it ourselves + if not use_provided_session and session_context: + session_context.__exit__(None, None, None) + # Success, exit function + return + + except (ConnectionError, Exception) as e: + error_str = str(e).lower() + # Check if it's a connection-related error that might be transient + is_connection_error = any( + keyword in error_str + for keyword in [ + "connection", + "disconnected", + "timeout", + "network", + "could not connect", + "server disconnected", + "weaviate", + ] + ) + + if is_connection_error and attempt < max_retries - 1: + # Retry for connection errors + wait_time = retry_delay * (2**attempt) # Exponential backoff + logger.warning( + "Vectorization attempt %s/%s failed for segment %s (connection error): %s. " + "Retrying in %.1f seconds...", + attempt + 1, + max_retries, + segment.id, + str(e), + wait_time, + ) + time.sleep(wait_time) + continue + else: + # Final attempt failed or non-connection error - log and update status + logger.error( + "Failed to vectorize summary for segment %s after %s attempts: %s. " + "summary_record_id=%s, index_node_id=%s, use_provided_session=%s", + segment.id, + attempt + 1, + str(e), + summary_record_id, + summary_index_node_id, + session is not None, + exc_info=True, + ) + # Update error status in session + # Use the original_session saved at function start (the function parameter) + logger.debug( + "Updating error status for segment %s, summary_record_id=%s, has_original_session=%s", + segment.id, + summary_record_id, + original_session is not None, + ) + # Always create a new session for error handling to avoid issues with closed sessions + # Even if original_session was provided, we create a new one for safety + with session_factory.create_session() as error_session: + # Try to find the record by id first + # Note: Using assignment only (no type annotation) to avoid redeclaration error + summary_record_in_session = ( + error_session.query(DocumentSegmentSummary).filter_by(id=summary_record_id).first() + ) + if not summary_record_in_session: + # Try to find by chunk_id and dataset_id + logger.debug( + "Summary record not found by id=%s, trying chunk_id=%s and dataset_id=%s " + "for segment %s", + summary_record_id, + segment.id, + dataset.id, + segment.id, + ) + summary_record_in_session = ( + error_session.query(DocumentSegmentSummary) + .filter_by(chunk_id=segment.id, dataset_id=dataset.id) + .first() + ) + + if summary_record_in_session: + summary_record_in_session.status = "error" + summary_record_in_session.error = f"Vectorization failed: {str(e)}" + summary_record_in_session.updated_at = datetime.now(UTC).replace(tzinfo=None) + error_session.add(summary_record_in_session) + error_session.commit() + logger.info( + "Updated error status in new session for segment %s, record_id=%s", + segment.id, + summary_record_in_session.id, + ) + # Update the original object for consistency + summary_record.status = "error" + summary_record.error = summary_record_in_session.error + summary_record.updated_at = summary_record_in_session.updated_at + else: + logger.warning( + "Could not update error status: summary record not found for segment %s (id=%s). " + "This may indicate a session isolation issue.", + segment.id, + summary_record_id, + ) + raise + + @staticmethod + def batch_create_summary_records( + segments: list[DocumentSegment], + dataset: Dataset, + status: str = "not_started", + ) -> None: + """ + Batch create summary records for segments with specified status. + If a record already exists, update its status. + + Args: + segments: List of DocumentSegment instances + dataset: Dataset containing the segments + status: Initial status for the records (default: "not_started") + """ + segment_ids = [segment.id for segment in segments] + if not segment_ids: + return + + with session_factory.create_session() as session: + # Query existing summary records + existing_summaries = ( + session.query(DocumentSegmentSummary) + .filter( + DocumentSegmentSummary.chunk_id.in_(segment_ids), + DocumentSegmentSummary.dataset_id == dataset.id, + ) + .all() + ) + existing_summary_map = {summary.chunk_id: summary for summary in existing_summaries} + + # Create or update records + for segment in segments: + existing_summary = existing_summary_map.get(segment.id) + if existing_summary: + # Update existing record + existing_summary.status = status + existing_summary.error = None # type: ignore[assignment] # Clear any previous errors + if not existing_summary.enabled: + existing_summary.enabled = True + existing_summary.disabled_at = None + existing_summary.disabled_by = None + session.add(existing_summary) + else: + # Create new record + summary_record = DocumentSegmentSummary( + dataset_id=dataset.id, + document_id=segment.document_id, + chunk_id=segment.id, + summary_content=None, # Will be filled later + status=status, + enabled=True, + ) + session.add(summary_record) + + @staticmethod + def update_summary_record_error( + segment: DocumentSegment, + dataset: Dataset, + error: str, + ) -> None: + """ + Update summary record with error status. + + Args: + segment: DocumentSegment + dataset: Dataset containing the segment + error: Error message + """ + with session_factory.create_session() as session: + summary_record = ( + session.query(DocumentSegmentSummary).filter_by(chunk_id=segment.id, dataset_id=dataset.id).first() + ) + + if summary_record: + summary_record.status = "error" + summary_record.error = error + session.add(summary_record) + session.commit() + else: + logger.warning("Summary record not found for segment %s when updating error", segment.id) + + @staticmethod + def generate_and_vectorize_summary( + segment: DocumentSegment, + dataset: Dataset, + summary_index_setting: dict, + ) -> DocumentSegmentSummary: + """ + Generate summary for a segment and vectorize it. + Assumes summary record already exists (created by batch_create_summary_records). + + Args: + segment: DocumentSegment to generate summary for + dataset: Dataset containing the segment + summary_index_setting: Summary index configuration + + Returns: + Created DocumentSegmentSummary instance + + Raises: + ValueError: If summary generation fails + """ + with session_factory.create_session() as session: + try: + # Get or refresh summary record in this session + summary_record_in_session = ( + session.query(DocumentSegmentSummary).filter_by(chunk_id=segment.id, dataset_id=dataset.id).first() + ) + + if not summary_record_in_session: + # If not found, create one + logger.warning("Summary record not found for segment %s, creating one", segment.id) + summary_record_in_session = DocumentSegmentSummary( + dataset_id=dataset.id, + document_id=segment.document_id, + chunk_id=segment.id, + summary_content="", + status="generating", + enabled=True, + ) + session.add(summary_record_in_session) + session.flush() + + # Update status to "generating" + summary_record_in_session.status = "generating" + summary_record_in_session.error = None # type: ignore[assignment] + session.add(summary_record_in_session) + # Don't flush here - wait until after vectorization succeeds + + # Generate summary (returns summary_content and llm_usage) + summary_content, llm_usage = SummaryIndexService.generate_summary_for_segment( + segment, dataset, summary_index_setting + ) + + # Update summary content + summary_record_in_session.summary_content = summary_content + session.add(summary_record_in_session) + # Flush to ensure summary_content is saved before vectorize_summary queries it + session.flush() + + # Log LLM usage for summary generation + if llm_usage and llm_usage.total_tokens > 0: + logger.info( + "Summary generation for segment %s used %s tokens (prompt: %s, completion: %s)", + segment.id, + llm_usage.total_tokens, + llm_usage.prompt_tokens, + llm_usage.completion_tokens, + ) + + # Vectorize summary (will delete old vector if exists before creating new one) + # Pass the session-managed record to vectorize_summary + # vectorize_summary will update status to "completed" and tokens in its own session + # vectorize_summary will also ensure summary_content is preserved + try: + # Pass the session to vectorize_summary to avoid session isolation issues + SummaryIndexService.vectorize_summary(summary_record_in_session, segment, dataset, session=session) + # Refresh the object from database to get the updated status and tokens from vectorize_summary + session.refresh(summary_record_in_session) + # Commit the session + # (summary_record_in_session should have status="completed" and tokens from refresh) + session.commit() + logger.info("Successfully generated and vectorized summary for segment %s", segment.id) + return summary_record_in_session + except Exception as vectorize_error: + # If vectorization fails, update status to error in current session + logger.exception("Failed to vectorize summary for segment %s", segment.id) + summary_record_in_session.status = "error" + summary_record_in_session.error = f"Vectorization failed: {str(vectorize_error)}" + session.add(summary_record_in_session) + session.commit() + raise + + except Exception as e: + logger.exception("Failed to generate summary for segment %s", segment.id) + # Update summary record with error status + summary_record_in_session = ( + session.query(DocumentSegmentSummary).filter_by(chunk_id=segment.id, dataset_id=dataset.id).first() + ) + if summary_record_in_session: + summary_record_in_session.status = "error" + summary_record_in_session.error = str(e) + session.add(summary_record_in_session) + session.commit() + raise + + @staticmethod + def generate_summaries_for_document( + dataset: Dataset, + document: DatasetDocument, + summary_index_setting: dict, + segment_ids: list[str] | None = None, + only_parent_chunks: bool = False, + ) -> list[DocumentSegmentSummary]: + """ + Generate summaries for all segments in a document including vectorization. + + Args: + dataset: Dataset containing the document + document: DatasetDocument to generate summaries for + summary_index_setting: Summary index configuration + segment_ids: Optional list of specific segment IDs to process + only_parent_chunks: If True, only process parent chunks (for parent-child mode) + + Returns: + List of created DocumentSegmentSummary instances + """ + # Only generate summary index for high_quality indexing technique + if dataset.indexing_technique != "high_quality": + logger.info( + "Skipping summary generation for dataset %s: indexing_technique is %s, not 'high_quality'", + dataset.id, + dataset.indexing_technique, + ) + return [] + + if not summary_index_setting or not summary_index_setting.get("enable"): + logger.info("Summary index is disabled for dataset %s", dataset.id) + return [] + + # Skip qa_model documents + if document.doc_form == "qa_model": + logger.info("Skipping summary generation for qa_model document %s", document.id) + return [] + + logger.info( + "Starting summary generation for document %s in dataset %s, segment_ids: %s, only_parent_chunks: %s", + document.id, + dataset.id, + len(segment_ids) if segment_ids else "all", + only_parent_chunks, + ) + + with session_factory.create_session() as session: + # Query segments (only enabled segments) + query = session.query(DocumentSegment).filter_by( + dataset_id=dataset.id, + document_id=document.id, + status="completed", + enabled=True, # Only generate summaries for enabled segments + ) + + if segment_ids: + query = query.filter(DocumentSegment.id.in_(segment_ids)) + + segments = query.all() + + if not segments: + logger.info("No segments found for document %s", document.id) + return [] + + # Batch create summary records with "not_started" status before processing + # This ensures all records exist upfront, allowing status tracking + SummaryIndexService.batch_create_summary_records( + segments=segments, + dataset=dataset, + status="not_started", + ) + session.commit() # Commit initial records + + summary_records = [] + + for segment in segments: + # For parent-child mode, only process parent chunks + # In parent-child mode, all DocumentSegments are parent chunks, + # so we process all of them. Child chunks are stored in ChildChunk table + # and are not DocumentSegments, so they won't be in the segments list. + # This check is mainly for clarity and future-proofing. + if only_parent_chunks: + # In parent-child mode, all segments in the query are parent chunks + # Child chunks are not DocumentSegments, so they won't appear here + # We can process all segments + pass + + try: + summary_record = SummaryIndexService.generate_and_vectorize_summary( + segment, dataset, summary_index_setting + ) + summary_records.append(summary_record) + except Exception as e: + logger.exception("Failed to generate summary for segment %s", segment.id) + # Update summary record with error status + SummaryIndexService.update_summary_record_error( + segment=segment, + dataset=dataset, + error=str(e), + ) + # Continue with other segments + continue + + logger.info( + "Completed summary generation for document %s: %s summaries generated and vectorized", + document.id, + len(summary_records), + ) + return summary_records + + @staticmethod + def disable_summaries_for_segments( + dataset: Dataset, + segment_ids: list[str] | None = None, + disabled_by: str | None = None, + ) -> None: + """ + Disable summary records and remove vectors from vector database for segments. + Unlike delete, this preserves the summary records but marks them as disabled. + + Args: + dataset: Dataset containing the segments + segment_ids: List of segment IDs to disable summaries for. If None, disable all. + disabled_by: User ID who disabled the summaries + """ + from libs.datetime_utils import naive_utc_now + + with session_factory.create_session() as session: + query = session.query(DocumentSegmentSummary).filter_by( + dataset_id=dataset.id, + enabled=True, # Only disable enabled summaries + ) + + if segment_ids: + query = query.filter(DocumentSegmentSummary.chunk_id.in_(segment_ids)) + + summaries = query.all() + + if not summaries: + return + + logger.info( + "Disabling %s summary records for dataset %s, segment_ids: %s", + len(summaries), + dataset.id, + len(segment_ids) if segment_ids else "all", + ) + + # Remove from vector database (but keep records) + if dataset.indexing_technique == "high_quality": + summary_node_ids = [s.summary_index_node_id for s in summaries if s.summary_index_node_id] + if summary_node_ids: + try: + vector = Vector(dataset) + vector.delete_by_ids(summary_node_ids) + except Exception as e: + logger.warning("Failed to remove summary vectors: %s", str(e)) + + # Disable summary records (don't delete) + now = naive_utc_now() + for summary in summaries: + summary.enabled = False + summary.disabled_at = now + summary.disabled_by = disabled_by + session.add(summary) + + session.commit() + logger.info("Disabled %s summary records for dataset %s", len(summaries), dataset.id) + + @staticmethod + def enable_summaries_for_segments( + dataset: Dataset, + segment_ids: list[str] | None = None, + ) -> None: + """ + Enable summary records and re-add vectors to vector database for segments. + + Note: This method enables summaries based on chunk status, not summary_index_setting.enable. + The summary_index_setting.enable flag only controls automatic generation, + not whether existing summaries can be used. + Summary.enabled should always be kept in sync with chunk.enabled. + + Args: + dataset: Dataset containing the segments + segment_ids: List of segment IDs to enable summaries for. If None, enable all. + """ + # Only enable summary index for high_quality indexing technique + if dataset.indexing_technique != "high_quality": + return + + with session_factory.create_session() as session: + query = session.query(DocumentSegmentSummary).filter_by( + dataset_id=dataset.id, + enabled=False, # Only enable disabled summaries + ) + + if segment_ids: + query = query.filter(DocumentSegmentSummary.chunk_id.in_(segment_ids)) + + summaries = query.all() + + if not summaries: + return + + logger.info( + "Enabling %s summary records for dataset %s, segment_ids: %s", + len(summaries), + dataset.id, + len(segment_ids) if segment_ids else "all", + ) + + # Re-vectorize and re-add to vector database + enabled_count = 0 + for summary in summaries: + # Get the original segment + segment = ( + session.query(DocumentSegment) + .filter_by( + id=summary.chunk_id, + dataset_id=dataset.id, + ) + .first() + ) + + # Summary.enabled stays in sync with chunk.enabled, + # only enable summary if the associated chunk is enabled. + if not segment or not segment.enabled or segment.status != "completed": + continue + + if not summary.summary_content: + continue + + try: + # Re-vectorize summary (this will update status and tokens in its own session) + # Pass the session to vectorize_summary to avoid session isolation issues + SummaryIndexService.vectorize_summary(summary, segment, dataset, session=session) + + # Refresh the object from database to get the updated status and tokens from vectorize_summary + session.refresh(summary) + + # Enable summary record + summary.enabled = True + summary.disabled_at = None + summary.disabled_by = None + session.add(summary) + enabled_count += 1 + except Exception: + logger.exception("Failed to re-vectorize summary %s", summary.id) + # Keep it disabled if vectorization fails + continue + + session.commit() + logger.info("Enabled %s summary records for dataset %s", enabled_count, dataset.id) + + @staticmethod + def delete_summaries_for_segments( + dataset: Dataset, + segment_ids: list[str] | None = None, + ) -> None: + """ + Delete summary records and vectors for segments (used only for actual deletion scenarios). + For disable/enable operations, use disable_summaries_for_segments/enable_summaries_for_segments. + + Args: + dataset: Dataset containing the segments + segment_ids: List of segment IDs to delete summaries for. If None, delete all. + """ + with session_factory.create_session() as session: + query = session.query(DocumentSegmentSummary).filter_by(dataset_id=dataset.id) + + if segment_ids: + query = query.filter(DocumentSegmentSummary.chunk_id.in_(segment_ids)) + + summaries = query.all() + + if not summaries: + return + + # Delete from vector database + if dataset.indexing_technique == "high_quality": + summary_node_ids = [s.summary_index_node_id for s in summaries if s.summary_index_node_id] + if summary_node_ids: + vector = Vector(dataset) + vector.delete_by_ids(summary_node_ids) + + # Delete summary records + for summary in summaries: + session.delete(summary) + + session.commit() + logger.info("Deleted %s summary records for dataset %s", len(summaries), dataset.id) + + @staticmethod + def update_summary_for_segment( + segment: DocumentSegment, + dataset: Dataset, + summary_content: str, + ) -> DocumentSegmentSummary | None: + """ + Update summary for a segment and re-vectorize it. + + Args: + segment: DocumentSegment to update summary for + dataset: Dataset containing the segment + summary_content: New summary content + + Returns: + Updated DocumentSegmentSummary instance, or None if indexing technique is not high_quality + """ + # Only update summary index for high_quality indexing technique + if dataset.indexing_technique != "high_quality": + return None + + # When user manually provides summary, allow saving even if summary_index_setting doesn't exist + # summary_index_setting is only needed for LLM generation, not for manual summary vectorization + # Vectorization uses dataset.embedding_model, which doesn't require summary_index_setting + + # Skip qa_model documents + if segment.document and segment.document.doc_form == "qa_model": + return None + + with session_factory.create_session() as session: + try: + # Check if summary_content is empty (whitespace-only strings are considered empty) + if not summary_content or not summary_content.strip(): + # If summary is empty, only delete existing summary vector and record + summary_record = ( + session.query(DocumentSegmentSummary) + .filter_by(chunk_id=segment.id, dataset_id=dataset.id) + .first() + ) + + if summary_record: + # Delete old vector if exists + old_summary_node_id = summary_record.summary_index_node_id + if old_summary_node_id: + try: + vector = Vector(dataset) + vector.delete_by_ids([old_summary_node_id]) + except Exception as e: + logger.warning( + "Failed to delete old summary vector for segment %s: %s", + segment.id, + str(e), + ) + + # Delete summary record since summary is empty + session.delete(summary_record) + session.commit() + logger.info("Deleted summary for segment %s (empty content provided)", segment.id) + return None + else: + # No existing summary record, nothing to do + logger.info("No summary record found for segment %s, nothing to delete", segment.id) + return None + + # Find existing summary record + summary_record = ( + session.query(DocumentSegmentSummary).filter_by(chunk_id=segment.id, dataset_id=dataset.id).first() + ) + + if summary_record: + # Update existing summary + old_summary_node_id = summary_record.summary_index_node_id + + # Update summary content + summary_record.summary_content = summary_content + summary_record.status = "generating" + summary_record.error = None # type: ignore[assignment] # Clear any previous errors + session.add(summary_record) + # Flush to ensure summary_content is saved before vectorize_summary queries it + session.flush() + + # Delete old vector if exists (before vectorization) + if old_summary_node_id: + try: + vector = Vector(dataset) + vector.delete_by_ids([old_summary_node_id]) + except Exception as e: + logger.warning( + "Failed to delete old summary vector for segment %s: %s", + segment.id, + str(e), + ) + + # Re-vectorize summary (this will update status to "completed" and tokens in its own session) + # vectorize_summary will also ensure summary_content is preserved + # Note: vectorize_summary may take time due to embedding API calls, but we need to complete it + # to ensure the summary is properly indexed + try: + # Pass the session to vectorize_summary to avoid session isolation issues + SummaryIndexService.vectorize_summary(summary_record, segment, dataset, session=session) + # Refresh the object from database to get the updated status and tokens from vectorize_summary + session.refresh(summary_record) + # Now commit the session (summary_record should have status="completed" and tokens from refresh) + session.commit() + logger.info("Successfully updated and re-vectorized summary for segment %s", segment.id) + return summary_record + except Exception as e: + # If vectorization fails, update status to error in current session + # Don't raise the exception - just log it and return the record with error status + # This allows the segment update to complete even if vectorization fails + summary_record.status = "error" + summary_record.error = f"Vectorization failed: {str(e)}" + session.commit() + logger.exception("Failed to vectorize summary for segment %s", segment.id) + # Return the record with error status instead of raising + # The caller can check the status if needed + return summary_record + else: + # Create new summary record if doesn't exist + summary_record = SummaryIndexService.create_summary_record( + segment, dataset, summary_content, status="generating" + ) + # Re-vectorize summary (this will update status to "completed" and tokens in its own session) + # Note: summary_record was created in a different session, + # so we need to merge it into current session + try: + # Merge the record into current session first (since it was created in a different session) + summary_record = session.merge(summary_record) + # Pass the session to vectorize_summary - it will update the merged record + SummaryIndexService.vectorize_summary(summary_record, segment, dataset, session=session) + # Refresh to get updated status and tokens from database + session.refresh(summary_record) + # Commit the session to persist the changes + session.commit() + logger.info("Successfully created and vectorized summary for segment %s", segment.id) + return summary_record + except Exception as e: + # If vectorization fails, update status to error in current session + # Merge the record into current session first + error_record = session.merge(summary_record) + error_record.status = "error" + error_record.error = f"Vectorization failed: {str(e)}" + session.commit() + logger.exception("Failed to vectorize summary for segment %s", segment.id) + # Return the record with error status instead of raising + return error_record + + except Exception as e: + logger.exception("Failed to update summary for segment %s", segment.id) + # Update summary record with error status if it exists + summary_record = ( + session.query(DocumentSegmentSummary).filter_by(chunk_id=segment.id, dataset_id=dataset.id).first() + ) + if summary_record: + summary_record.status = "error" + summary_record.error = str(e) + session.add(summary_record) + session.commit() + raise + + @staticmethod + def get_segment_summary(segment_id: str, dataset_id: str) -> DocumentSegmentSummary | None: + """ + Get summary for a single segment. + + Args: + segment_id: Segment ID (chunk_id) + dataset_id: Dataset ID + + Returns: + DocumentSegmentSummary instance if found, None otherwise + """ + with session_factory.create_session() as session: + return ( + session.query(DocumentSegmentSummary) + .where( + DocumentSegmentSummary.chunk_id == segment_id, + DocumentSegmentSummary.dataset_id == dataset_id, + DocumentSegmentSummary.enabled == True, # Only return enabled summaries + ) + .first() + ) + + @staticmethod + def get_segments_summaries(segment_ids: list[str], dataset_id: str) -> dict[str, DocumentSegmentSummary]: + """ + Get summaries for multiple segments. + + Args: + segment_ids: List of segment IDs (chunk_ids) + dataset_id: Dataset ID + + Returns: + Dictionary mapping segment_id to DocumentSegmentSummary (only enabled summaries) + """ + if not segment_ids: + return {} + + with session_factory.create_session() as session: + summary_records = ( + session.query(DocumentSegmentSummary) + .where( + DocumentSegmentSummary.chunk_id.in_(segment_ids), + DocumentSegmentSummary.dataset_id == dataset_id, + DocumentSegmentSummary.enabled == True, # Only return enabled summaries + ) + .all() + ) + + return {summary.chunk_id: summary for summary in summary_records} + + @staticmethod + def get_document_summaries( + document_id: str, dataset_id: str, segment_ids: list[str] | None = None + ) -> list[DocumentSegmentSummary]: + """ + Get all summary records for a document. + + Args: + document_id: Document ID + dataset_id: Dataset ID + segment_ids: Optional list of segment IDs to filter by + + Returns: + List of DocumentSegmentSummary instances (only enabled summaries) + """ + with session_factory.create_session() as session: + query = session.query(DocumentSegmentSummary).filter( + DocumentSegmentSummary.document_id == document_id, + DocumentSegmentSummary.dataset_id == dataset_id, + DocumentSegmentSummary.enabled == True, # Only return enabled summaries + ) + + if segment_ids: + query = query.filter(DocumentSegmentSummary.chunk_id.in_(segment_ids)) + + return query.all() + + @staticmethod + def get_document_summary_index_status(document_id: str, dataset_id: str, tenant_id: str) -> str | None: + """ + Get summary_index_status for a single document. + + Args: + document_id: Document ID + dataset_id: Dataset ID + tenant_id: Tenant ID + + Returns: + "SUMMARIZING" if there are pending summaries, None otherwise + """ + # Get all segments for this document (excluding qa_model and re_segment) + with session_factory.create_session() as session: + segments = ( + session.query(DocumentSegment.id) + .where( + DocumentSegment.document_id == document_id, + DocumentSegment.status != "re_segment", + DocumentSegment.tenant_id == tenant_id, + ) + .all() + ) + segment_ids = [seg.id for seg in segments] + + if not segment_ids: + return None + + # Get all summary records for these segments + summaries = SummaryIndexService.get_segments_summaries(segment_ids, dataset_id) + summary_status_map = {chunk_id: summary.status for chunk_id, summary in summaries.items()} + + # Check if there are any "not_started" or "generating" status summaries + has_pending_summaries = any( + summary_status_map.get(segment_id) is not None # Ensure summary exists (enabled=True) + and summary_status_map[segment_id] in ("not_started", "generating") + for segment_id in segment_ids + ) + + return "SUMMARIZING" if has_pending_summaries else None + + @staticmethod + def get_documents_summary_index_status( + document_ids: list[str], dataset_id: str, tenant_id: str + ) -> dict[str, str | None]: + """ + Get summary_index_status for multiple documents. + + Args: + document_ids: List of document IDs + dataset_id: Dataset ID + tenant_id: Tenant ID + + Returns: + Dictionary mapping document_id to summary_index_status ("SUMMARIZING" or None) + """ + if not document_ids: + return {} + + # Get all segments for these documents (excluding qa_model and re_segment) + with session_factory.create_session() as session: + segments = ( + session.query(DocumentSegment.id, DocumentSegment.document_id) + .where( + DocumentSegment.document_id.in_(document_ids), + DocumentSegment.status != "re_segment", + DocumentSegment.tenant_id == tenant_id, + ) + .all() + ) + + # Group segments by document_id + document_segments_map: dict[str, list[str]] = {} + for segment in segments: + doc_id = str(segment.document_id) + if doc_id not in document_segments_map: + document_segments_map[doc_id] = [] + document_segments_map[doc_id].append(segment.id) + + # Get all summary records for these segments + all_segment_ids = [seg.id for seg in segments] + summaries = SummaryIndexService.get_segments_summaries(all_segment_ids, dataset_id) + summary_status_map = {chunk_id: summary.status for chunk_id, summary in summaries.items()} + + # Calculate summary_index_status for each document + result: dict[str, str | None] = {} + for doc_id in document_ids: + segment_ids = document_segments_map.get(doc_id, []) + if not segment_ids: + # No segments, status is None (not started) + result[doc_id] = None + continue + + # Check if there are any "not_started" or "generating" status summaries + # Only check enabled=True summaries (already filtered in query) + # If segment has no summary record (summary_status_map.get returns None), + # it means the summary is disabled (enabled=False) or not created yet, ignore it + has_pending_summaries = any( + summary_status_map.get(segment_id) is not None # Ensure summary exists (enabled=True) + and summary_status_map[segment_id] in ("not_started", "generating") + for segment_id in segment_ids + ) + + if has_pending_summaries: + # Task is still running (not started or generating) + result[doc_id] = "SUMMARIZING" + else: + # All enabled=True summaries are "completed" or "error", task finished + # Or no enabled=True summaries exist (all disabled) + result[doc_id] = None + + return result + + @staticmethod + def get_document_summary_status_detail( + document_id: str, + dataset_id: str, + ) -> dict[str, Any]: + """ + Get detailed summary status for a document. + + Args: + document_id: Document ID + dataset_id: Dataset ID + + Returns: + Dictionary containing: + - total_segments: Total number of segments in the document + - summary_status: Dictionary with status counts + - completed: Number of summaries completed + - generating: Number of summaries being generated + - error: Number of summaries with errors + - not_started: Number of segments without summary records + - summaries: List of summary records with status and content preview + """ + from services.dataset_service import SegmentService + + # Get all segments for this document + segments = SegmentService.get_segments_by_document_and_dataset( + document_id=document_id, + dataset_id=dataset_id, + status="completed", + enabled=True, + ) + + total_segments = len(segments) + + # Get all summary records for these segments + segment_ids = [segment.id for segment in segments] + summaries = [] + if segment_ids: + summaries = SummaryIndexService.get_document_summaries( + document_id=document_id, + dataset_id=dataset_id, + segment_ids=segment_ids, + ) + + # Create a mapping of chunk_id to summary + summary_map = {summary.chunk_id: summary for summary in summaries} + + # Count statuses + status_counts = { + "completed": 0, + "generating": 0, + "error": 0, + "not_started": 0, + } + + summary_list = [] + for segment in segments: + summary = summary_map.get(segment.id) + if summary: + status = summary.status + status_counts[status] = status_counts.get(status, 0) + 1 + summary_list.append( + { + "segment_id": segment.id, + "segment_position": segment.position, + "status": summary.status, + "summary_preview": ( + summary.summary_content[:100] + "..." + if summary.summary_content and len(summary.summary_content) > 100 + else summary.summary_content + ), + "error": summary.error, + "created_at": int(summary.created_at.timestamp()) if summary.created_at else None, + "updated_at": int(summary.updated_at.timestamp()) if summary.updated_at else None, + } + ) + else: + status_counts["not_started"] += 1 + summary_list.append( + { + "segment_id": segment.id, + "segment_position": segment.position, + "status": "not_started", + "summary_preview": None, + "error": None, + "created_at": None, + "updated_at": None, + } + ) + + return { + "total_segments": total_segments, + "summary_status": status_counts, + "summaries": summary_list, + } diff --git a/api/tasks/add_document_to_index_task.py b/api/tasks/add_document_to_index_task.py index 62e6497e9d..2d3d00cd50 100644 --- a/api/tasks/add_document_to_index_task.py +++ b/api/tasks/add_document_to_index_task.py @@ -118,6 +118,19 @@ def add_document_to_index_task(dataset_document_id: str): ) session.commit() + # Enable summary indexes for all segments in this document + from services.summary_index_service import SummaryIndexService + + segment_ids_list = [segment.id for segment in segments] + if segment_ids_list: + try: + SummaryIndexService.enable_summaries_for_segments( + dataset=dataset, + segment_ids=segment_ids_list, + ) + except Exception as e: + logger.warning("Failed to enable summaries for document %s: %s", dataset_document.id, str(e)) + end_at = time.perf_counter() logger.info( click.style(f"Document added to index: {dataset_document.id} latency: {end_at - start_at}", fg="green") diff --git a/api/tasks/batch_clean_document_task.py b/api/tasks/batch_clean_document_task.py index 74b939e84d..d388284980 100644 --- a/api/tasks/batch_clean_document_task.py +++ b/api/tasks/batch_clean_document_task.py @@ -50,7 +50,9 @@ def batch_clean_document_task(document_ids: list[str], dataset_id: str, doc_form if segments: index_node_ids = [segment.index_node_id for segment in segments] index_processor = IndexProcessorFactory(doc_form).init_index_processor() - index_processor.clean(dataset, index_node_ids, with_keywords=True, delete_child_chunks=True) + index_processor.clean( + dataset, index_node_ids, with_keywords=True, delete_child_chunks=True, delete_summaries=True + ) for segment in segments: image_upload_file_ids = get_image_upload_file_ids(segment.content) diff --git a/api/tasks/clean_document_task.py b/api/tasks/clean_document_task.py index 86e7cc7160..91ace6be02 100644 --- a/api/tasks/clean_document_task.py +++ b/api/tasks/clean_document_task.py @@ -51,7 +51,9 @@ def clean_document_task(document_id: str, dataset_id: str, doc_form: str, file_i if segments: index_node_ids = [segment.index_node_id for segment in segments] index_processor = IndexProcessorFactory(doc_form).init_index_processor() - index_processor.clean(dataset, index_node_ids, with_keywords=True, delete_child_chunks=True) + index_processor.clean( + dataset, index_node_ids, with_keywords=True, delete_child_chunks=True, delete_summaries=True + ) for segment in segments: image_upload_file_ids = get_image_upload_file_ids(segment.content) diff --git a/api/tasks/clean_notion_document_task.py b/api/tasks/clean_notion_document_task.py index bcca1bf49f..4214f043e0 100644 --- a/api/tasks/clean_notion_document_task.py +++ b/api/tasks/clean_notion_document_task.py @@ -42,7 +42,9 @@ def clean_notion_document_task(document_ids: list[str], dataset_id: str): ).all() index_node_ids = [segment.index_node_id for segment in segments] - index_processor.clean(dataset, index_node_ids, with_keywords=True, delete_child_chunks=True) + index_processor.clean( + dataset, index_node_ids, with_keywords=True, delete_child_chunks=True, delete_summaries=True + ) segment_ids = [segment.id for segment in segments] segment_delete_stmt = delete(DocumentSegment).where(DocumentSegment.id.in_(segment_ids)) session.execute(segment_delete_stmt) diff --git a/api/tasks/delete_segment_from_index_task.py b/api/tasks/delete_segment_from_index_task.py index bfa709502c..764c635d83 100644 --- a/api/tasks/delete_segment_from_index_task.py +++ b/api/tasks/delete_segment_from_index_task.py @@ -47,6 +47,7 @@ def delete_segment_from_index_task( doc_form = dataset_document.doc_form # Proceed with index cleanup using the index_node_ids directly + # For actual deletion, we should delete summaries (not just disable them) index_processor = IndexProcessorFactory(doc_form).init_index_processor() index_processor.clean( dataset, @@ -54,6 +55,7 @@ def delete_segment_from_index_task( with_keywords=True, delete_child_chunks=True, precomputed_child_node_ids=child_node_ids, + delete_summaries=True, # Actually delete summaries when segment is deleted ) if dataset.is_multimodal: # delete segment attachment binding diff --git a/api/tasks/disable_segment_from_index_task.py b/api/tasks/disable_segment_from_index_task.py index 0ce6429a94..bc45171623 100644 --- a/api/tasks/disable_segment_from_index_task.py +++ b/api/tasks/disable_segment_from_index_task.py @@ -60,6 +60,18 @@ def disable_segment_from_index_task(segment_id: str): index_processor = IndexProcessorFactory(index_type).init_index_processor() index_processor.clean(dataset, [segment.index_node_id]) + # Disable summary index for this segment + from services.summary_index_service import SummaryIndexService + + try: + SummaryIndexService.disable_summaries_for_segments( + dataset=dataset, + segment_ids=[segment.id], + disabled_by=segment.disabled_by, + ) + except Exception as e: + logger.warning("Failed to disable summary for segment %s: %s", segment.id, str(e)) + end_at = time.perf_counter() logger.info( click.style( diff --git a/api/tasks/disable_segments_from_index_task.py b/api/tasks/disable_segments_from_index_task.py index 03635902d1..3cc267e821 100644 --- a/api/tasks/disable_segments_from_index_task.py +++ b/api/tasks/disable_segments_from_index_task.py @@ -68,6 +68,21 @@ def disable_segments_from_index_task(segment_ids: list, dataset_id: str, documen index_node_ids.extend(attachment_ids) index_processor.clean(dataset, index_node_ids, with_keywords=True, delete_child_chunks=False) + # Disable summary indexes for these segments + from services.summary_index_service import SummaryIndexService + + segment_ids_list = [segment.id for segment in segments] + try: + # Get disabled_by from first segment (they should all have the same disabled_by) + disabled_by = segments[0].disabled_by if segments else None + SummaryIndexService.disable_summaries_for_segments( + dataset=dataset, + segment_ids=segment_ids_list, + disabled_by=disabled_by, + ) + except Exception as e: + logger.warning("Failed to disable summaries for segments: %s", str(e)) + end_at = time.perf_counter() logger.info(click.style(f"Segments removed from index latency: {end_at - start_at}", fg="green")) except Exception: diff --git a/api/tasks/document_indexing_task.py b/api/tasks/document_indexing_task.py index 3bdff60196..34496e9c6f 100644 --- a/api/tasks/document_indexing_task.py +++ b/api/tasks/document_indexing_task.py @@ -14,6 +14,7 @@ from enums.cloud_plan import CloudPlan from libs.datetime_utils import naive_utc_now from models.dataset import Dataset, Document from services.feature_service import FeatureService +from tasks.generate_summary_index_task import generate_summary_index_task logger = logging.getLogger(__name__) @@ -99,6 +100,78 @@ def _document_indexing(dataset_id: str, document_ids: Sequence[str]): indexing_runner.run(documents) end_at = time.perf_counter() logger.info(click.style(f"Processed dataset: {dataset_id} latency: {end_at - start_at}", fg="green")) + + # Trigger summary index generation for completed documents if enabled + # Only generate for high_quality indexing technique and when summary_index_setting is enabled + # Re-query dataset to get latest summary_index_setting (in case it was updated) + dataset = session.query(Dataset).where(Dataset.id == dataset_id).first() + if not dataset: + logger.warning("Dataset %s not found after indexing", dataset_id) + return + + if dataset.indexing_technique == "high_quality": + summary_index_setting = dataset.summary_index_setting + if summary_index_setting and summary_index_setting.get("enable"): + # expire all session to get latest document's indexing status + session.expire_all() + # Check each document's indexing status and trigger summary generation if completed + for document_id in document_ids: + # Re-query document to get latest status (IndexingRunner may have updated it) + document = ( + session.query(Document) + .where(Document.id == document_id, Document.dataset_id == dataset_id) + .first() + ) + if document: + logger.info( + "Checking document %s for summary generation: status=%s, doc_form=%s, need_summary=%s", + document_id, + document.indexing_status, + document.doc_form, + document.need_summary, + ) + if ( + document.indexing_status == "completed" + and document.doc_form != "qa_model" + and document.need_summary is True + ): + try: + generate_summary_index_task.delay(dataset.id, document_id, None) + logger.info( + "Queued summary index generation task for document %s in dataset %s " + "after indexing completed", + document_id, + dataset.id, + ) + except Exception: + logger.exception( + "Failed to queue summary index generation task for document %s", + document_id, + ) + # Don't fail the entire indexing process if summary task queuing fails + else: + logger.info( + "Skipping summary generation for document %s: " + "status=%s, doc_form=%s, need_summary=%s", + document_id, + document.indexing_status, + document.doc_form, + document.need_summary, + ) + else: + logger.warning("Document %s not found after indexing", document_id) + else: + logger.info( + "Summary index generation skipped for dataset %s: summary_index_setting.enable=%s", + dataset.id, + summary_index_setting.get("enable") if summary_index_setting else None, + ) + else: + logger.info( + "Summary index generation skipped for dataset %s: indexing_technique=%s (not 'high_quality')", + dataset.id, + dataset.indexing_technique, + ) except DocumentIsPausedError as ex: logger.info(click.style(str(ex), fg="yellow")) except Exception: diff --git a/api/tasks/enable_segment_to_index_task.py b/api/tasks/enable_segment_to_index_task.py index 1f9f21aa7e..41ebb0b076 100644 --- a/api/tasks/enable_segment_to_index_task.py +++ b/api/tasks/enable_segment_to_index_task.py @@ -106,6 +106,17 @@ def enable_segment_to_index_task(segment_id: str): # save vector index index_processor.load(dataset, [document], multimodal_documents=multimodel_documents) + # Enable summary index for this segment + from services.summary_index_service import SummaryIndexService + + try: + SummaryIndexService.enable_summaries_for_segments( + dataset=dataset, + segment_ids=[segment.id], + ) + except Exception as e: + logger.warning("Failed to enable summary for segment %s: %s", segment.id, str(e)) + end_at = time.perf_counter() logger.info(click.style(f"Segment enabled to index: {segment.id} latency: {end_at - start_at}", fg="green")) except Exception as e: diff --git a/api/tasks/enable_segments_to_index_task.py b/api/tasks/enable_segments_to_index_task.py index 48d3c8e178..d90eb4c39f 100644 --- a/api/tasks/enable_segments_to_index_task.py +++ b/api/tasks/enable_segments_to_index_task.py @@ -106,6 +106,18 @@ def enable_segments_to_index_task(segment_ids: list, dataset_id: str, document_i # save vector index index_processor.load(dataset, documents, multimodal_documents=multimodal_documents) + # Enable summary indexes for these segments + from services.summary_index_service import SummaryIndexService + + segment_ids_list = [segment.id for segment in segments] + try: + SummaryIndexService.enable_summaries_for_segments( + dataset=dataset, + segment_ids=segment_ids_list, + ) + except Exception as e: + logger.warning("Failed to enable summaries for segments: %s", str(e)) + end_at = time.perf_counter() logger.info(click.style(f"Segments enabled to index latency: {end_at - start_at}", fg="green")) except Exception as e: diff --git a/api/tasks/generate_summary_index_task.py b/api/tasks/generate_summary_index_task.py new file mode 100644 index 0000000000..e4273e16b5 --- /dev/null +++ b/api/tasks/generate_summary_index_task.py @@ -0,0 +1,119 @@ +"""Async task for generating summary indexes.""" + +import logging +import time + +import click +from celery import shared_task + +from core.db.session_factory import session_factory +from models.dataset import Dataset, DocumentSegment +from models.dataset import Document as DatasetDocument +from services.summary_index_service import SummaryIndexService + +logger = logging.getLogger(__name__) + + +@shared_task(queue="dataset") +def generate_summary_index_task(dataset_id: str, document_id: str, segment_ids: list[str] | None = None): + """ + Async generate summary index for document segments. + + Args: + dataset_id: Dataset ID + document_id: Document ID + segment_ids: Optional list of specific segment IDs to process. If None, process all segments. + + Usage: + generate_summary_index_task.delay(dataset_id, document_id) + generate_summary_index_task.delay(dataset_id, document_id, segment_ids) + """ + logger.info( + click.style( + f"Start generating summary index for document {document_id} in dataset {dataset_id}", + fg="green", + ) + ) + start_at = time.perf_counter() + + try: + with session_factory.create_session() as session: + dataset = session.query(Dataset).where(Dataset.id == dataset_id).first() + if not dataset: + logger.error(click.style(f"Dataset not found: {dataset_id}", fg="red")) + return + + document = session.query(DatasetDocument).where(DatasetDocument.id == document_id).first() + if not document: + logger.error(click.style(f"Document not found: {document_id}", fg="red")) + return + + # Check if document needs summary + if not document.need_summary: + logger.info( + click.style( + f"Skipping summary generation for document {document_id}: need_summary is False", + fg="cyan", + ) + ) + return + + # Only generate summary index for high_quality indexing technique + if dataset.indexing_technique != "high_quality": + logger.info( + click.style( + f"Skipping summary generation for dataset {dataset_id}: " + f"indexing_technique is {dataset.indexing_technique}, not 'high_quality'", + fg="cyan", + ) + ) + return + + # Check if summary index is enabled + summary_index_setting = dataset.summary_index_setting + if not summary_index_setting or not summary_index_setting.get("enable"): + logger.info( + click.style( + f"Summary index is disabled for dataset {dataset_id}", + fg="cyan", + ) + ) + return + + # Determine if only parent chunks should be processed + only_parent_chunks = dataset.chunk_structure == "parent_child_index" + + # Generate summaries + summary_records = SummaryIndexService.generate_summaries_for_document( + dataset=dataset, + document=document, + summary_index_setting=summary_index_setting, + segment_ids=segment_ids, + only_parent_chunks=only_parent_chunks, + ) + + end_at = time.perf_counter() + logger.info( + click.style( + f"Summary index generation completed for document {document_id}: " + f"{len(summary_records)} summaries generated, latency: {end_at - start_at}", + fg="green", + ) + ) + + except Exception as e: + logger.exception("Failed to generate summary index for document %s", document_id) + # Update document segments with error status if needed + if segment_ids: + error_message = f"Summary generation failed: {str(e)}" + with session_factory.create_session() as session: + session.query(DocumentSegment).filter( + DocumentSegment.id.in_(segment_ids), + DocumentSegment.dataset_id == dataset_id, + ).update( + { + DocumentSegment.error: error_message, + }, + synchronize_session=False, + ) + session.commit() diff --git a/api/tasks/regenerate_summary_index_task.py b/api/tasks/regenerate_summary_index_task.py new file mode 100644 index 0000000000..cf8988d13e --- /dev/null +++ b/api/tasks/regenerate_summary_index_task.py @@ -0,0 +1,315 @@ +"""Task for regenerating summary indexes when dataset settings change.""" + +import logging +import time +from collections import defaultdict + +import click +from celery import shared_task +from sqlalchemy import or_, select + +from core.db.session_factory import session_factory +from models.dataset import Dataset, DocumentSegment, DocumentSegmentSummary +from models.dataset import Document as DatasetDocument +from services.summary_index_service import SummaryIndexService + +logger = logging.getLogger(__name__) + + +@shared_task(queue="dataset") +def regenerate_summary_index_task( + dataset_id: str, + regenerate_reason: str = "summary_model_changed", + regenerate_vectors_only: bool = False, +): + """ + Regenerate summary indexes for all documents in a dataset. + + This task is triggered when: + 1. summary_index_setting model changes (regenerate_reason="summary_model_changed") + - Regenerates summary content and vectors for all existing summaries + 2. embedding_model changes (regenerate_reason="embedding_model_changed") + - Only regenerates vectors for existing summaries (keeps summary content) + + Args: + dataset_id: Dataset ID + regenerate_reason: Reason for regeneration ("summary_model_changed" or "embedding_model_changed") + regenerate_vectors_only: If True, only regenerate vectors without regenerating summary content + """ + logger.info( + click.style( + f"Start regenerate summary index for dataset {dataset_id}, reason: {regenerate_reason}", + fg="green", + ) + ) + start_at = time.perf_counter() + + try: + with session_factory.create_session() as session: + dataset = session.query(Dataset).filter_by(id=dataset_id).first() + if not dataset: + logger.error(click.style(f"Dataset not found: {dataset_id}", fg="red")) + return + + # Only regenerate summary index for high_quality indexing technique + if dataset.indexing_technique != "high_quality": + logger.info( + click.style( + f"Skipping summary regeneration for dataset {dataset_id}: " + f"indexing_technique is {dataset.indexing_technique}, not 'high_quality'", + fg="cyan", + ) + ) + return + + # Check if summary index is enabled (only for summary_model change) + # For embedding_model change, we still re-vectorize existing summaries even if setting is disabled + summary_index_setting = dataset.summary_index_setting + if not regenerate_vectors_only: + # For summary_model change, require summary_index_setting to be enabled + if not summary_index_setting or not summary_index_setting.get("enable"): + logger.info( + click.style( + f"Summary index is disabled for dataset {dataset_id}", + fg="cyan", + ) + ) + return + + total_segments_processed = 0 + total_segments_failed = 0 + + if regenerate_vectors_only: + # For embedding_model change: directly query all segments with existing summaries + # Don't require document indexing_status == "completed" + # Include summaries with status "completed" or "error" (if they have content) + segments_with_summaries = ( + session.query(DocumentSegment, DocumentSegmentSummary) + .join( + DocumentSegmentSummary, + DocumentSegment.id == DocumentSegmentSummary.chunk_id, + ) + .join( + DatasetDocument, + DocumentSegment.document_id == DatasetDocument.id, + ) + .where( + DocumentSegment.dataset_id == dataset_id, + DocumentSegment.status == "completed", # Segment must be completed + DocumentSegment.enabled == True, + DocumentSegmentSummary.dataset_id == dataset_id, + DocumentSegmentSummary.summary_content.isnot(None), # Must have summary content + # Include completed summaries or error summaries (with content) + or_( + DocumentSegmentSummary.status == "completed", + DocumentSegmentSummary.status == "error", + ), + DatasetDocument.enabled == True, # Document must be enabled + DatasetDocument.archived == False, # Document must not be archived + DatasetDocument.doc_form != "qa_model", # Skip qa_model documents + ) + .order_by(DocumentSegment.document_id.asc(), DocumentSegment.position.asc()) + .all() + ) + + if not segments_with_summaries: + logger.info( + click.style( + f"No segments with summaries found for re-vectorization in dataset {dataset_id}", + fg="cyan", + ) + ) + return + + logger.info( + "Found %s segments with summaries for re-vectorization in dataset %s", + len(segments_with_summaries), + dataset_id, + ) + + # Group by document for logging + segments_by_document = defaultdict(list) + for segment, summary_record in segments_with_summaries: + segments_by_document[segment.document_id].append((segment, summary_record)) + + logger.info( + "Segments grouped into %s documents for re-vectorization", + len(segments_by_document), + ) + + for document_id, segment_summary_pairs in segments_by_document.items(): + logger.info( + "Re-vectorizing summaries for %s segments in document %s", + len(segment_summary_pairs), + document_id, + ) + + for segment, summary_record in segment_summary_pairs: + try: + # Delete old vector + if summary_record.summary_index_node_id: + try: + from core.rag.datasource.vdb.vector_factory import Vector + + vector = Vector(dataset) + vector.delete_by_ids([summary_record.summary_index_node_id]) + except Exception as e: + logger.warning( + "Failed to delete old summary vector for segment %s: %s", + segment.id, + str(e), + ) + + # Re-vectorize with new embedding model + SummaryIndexService.vectorize_summary(summary_record, segment, dataset) + session.commit() + total_segments_processed += 1 + + except Exception as e: + logger.error( + "Failed to re-vectorize summary for segment %s: %s", + segment.id, + str(e), + exc_info=True, + ) + total_segments_failed += 1 + # Update summary record with error status + summary_record.status = "error" + summary_record.error = f"Re-vectorization failed: {str(e)}" + session.add(summary_record) + session.commit() + continue + + else: + # For summary_model change: require document indexing_status == "completed" + # Get all documents with completed indexing status + dataset_documents = session.scalars( + select(DatasetDocument).where( + DatasetDocument.dataset_id == dataset_id, + DatasetDocument.indexing_status == "completed", + DatasetDocument.enabled == True, + DatasetDocument.archived == False, + ) + ).all() + + if not dataset_documents: + logger.info( + click.style( + f"No documents found for summary regeneration in dataset {dataset_id}", + fg="cyan", + ) + ) + return + + logger.info( + "Found %s documents for summary regeneration in dataset %s", + len(dataset_documents), + dataset_id, + ) + + for dataset_document in dataset_documents: + # Skip qa_model documents + if dataset_document.doc_form == "qa_model": + continue + + try: + # Get all segments with existing summaries + segments = ( + session.query(DocumentSegment) + .join( + DocumentSegmentSummary, + DocumentSegment.id == DocumentSegmentSummary.chunk_id, + ) + .where( + DocumentSegment.document_id == dataset_document.id, + DocumentSegment.dataset_id == dataset_id, + DocumentSegment.status == "completed", + DocumentSegment.enabled == True, + DocumentSegmentSummary.dataset_id == dataset_id, + ) + .order_by(DocumentSegment.position.asc()) + .all() + ) + + if not segments: + continue + + logger.info( + "Regenerating summaries for %s segments in document %s", + len(segments), + dataset_document.id, + ) + + for segment in segments: + summary_record = None + try: + # Get existing summary record + summary_record = ( + session.query(DocumentSegmentSummary) + .filter_by( + chunk_id=segment.id, + dataset_id=dataset_id, + ) + .first() + ) + + if not summary_record: + logger.warning("Summary record not found for segment %s, skipping", segment.id) + continue + + # Regenerate both summary content and vectors (for summary_model change) + SummaryIndexService.generate_and_vectorize_summary( + segment, dataset, summary_index_setting + ) + session.commit() + total_segments_processed += 1 + + except Exception as e: + logger.error( + "Failed to regenerate summary for segment %s: %s", + segment.id, + str(e), + exc_info=True, + ) + total_segments_failed += 1 + # Update summary record with error status + if summary_record: + summary_record.status = "error" + summary_record.error = f"Regeneration failed: {str(e)}" + session.add(summary_record) + session.commit() + continue + + except Exception as e: + logger.error( + "Failed to process document %s for summary regeneration: %s", + dataset_document.id, + str(e), + exc_info=True, + ) + continue + + end_at = time.perf_counter() + if regenerate_vectors_only: + logger.info( + click.style( + f"Summary re-vectorization completed for dataset {dataset_id}: " + f"{total_segments_processed} segments processed successfully, " + f"{total_segments_failed} segments failed, " + f"latency: {end_at - start_at:.2f}s", + fg="green", + ) + ) + else: + logger.info( + click.style( + f"Summary index regeneration completed for dataset {dataset_id}: " + f"{total_segments_processed} segments processed successfully, " + f"{total_segments_failed} segments failed, " + f"latency: {end_at - start_at:.2f}s", + fg="green", + ) + ) + + except Exception: + logger.exception("Regenerate summary index failed for dataset %s", dataset_id) diff --git a/api/tasks/remove_document_from_index_task.py b/api/tasks/remove_document_from_index_task.py index c3c255fb17..55259ab527 100644 --- a/api/tasks/remove_document_from_index_task.py +++ b/api/tasks/remove_document_from_index_task.py @@ -46,6 +46,21 @@ def remove_document_from_index_task(document_id: str): index_processor = IndexProcessorFactory(document.doc_form).init_index_processor() segments = session.scalars(select(DocumentSegment).where(DocumentSegment.document_id == document.id)).all() + + # Disable summary indexes for all segments in this document + from services.summary_index_service import SummaryIndexService + + segment_ids_list = [segment.id for segment in segments] + if segment_ids_list: + try: + SummaryIndexService.disable_summaries_for_segments( + dataset=dataset, + segment_ids=segment_ids_list, + disabled_by=document.disabled_by, + ) + except Exception as e: + logger.warning("Failed to disable summaries for document %s: %s", document.id, str(e)) + index_node_ids = [segment.index_node_id for segment in segments] if index_node_ids: try: diff --git a/api/tests/unit_tests/services/test_dataset_service_update_dataset.py b/api/tests/unit_tests/services/test_dataset_service_update_dataset.py index 0aabe2fc30..08818945e3 100644 --- a/api/tests/unit_tests/services/test_dataset_service_update_dataset.py +++ b/api/tests/unit_tests/services/test_dataset_service_update_dataset.py @@ -138,6 +138,7 @@ class TestDatasetServiceUpdateDataset: "services.dataset_service.DatasetCollectionBindingService.get_dataset_collection_binding" ) as mock_get_binding, patch("services.dataset_service.deal_dataset_vector_index_task") as mock_task, + patch("services.dataset_service.regenerate_summary_index_task") as mock_regenerate_task, patch( "services.dataset_service.current_user", create_autospec(Account, instance=True) ) as mock_current_user, @@ -147,6 +148,7 @@ class TestDatasetServiceUpdateDataset: "model_manager": mock_model_manager, "get_binding": mock_get_binding, "task": mock_task, + "regenerate_task": mock_regenerate_task, "current_user": mock_current_user, } @@ -549,6 +551,13 @@ class TestDatasetServiceUpdateDataset: # Verify vector index task was triggered mock_internal_provider_dependencies["task"].delay.assert_called_once_with("dataset-123", "update") + # Verify regenerate summary index task was triggered (when embedding_model changes) + mock_internal_provider_dependencies["regenerate_task"].delay.assert_called_once_with( + "dataset-123", + regenerate_reason="embedding_model_changed", + regenerate_vectors_only=True, + ) + # Verify return value assert result == dataset From dbfc47e8b01919afbb6e83a54fe582483652db51 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E7=9B=90=E7=B2=92=20Yanli?= Date: Thu, 29 Jan 2026 14:01:21 +0800 Subject: [PATCH 02/15] fix: SSRF in WordExtractor URL download (credit to @EaEa0001 ) (#31678) Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com> --- api/core/file/file_manager.py | 4 ++ api/core/helper/ssrf_proxy.py | 30 ++++++++++----- api/core/rag/extractor/word_extractor.py | 9 +++-- .../core/rag/extractor/test_word_extractor.py | 38 +++++++++++++++++++ 4 files changed, 68 insertions(+), 13 deletions(-) diff --git a/api/core/file/file_manager.py b/api/core/file/file_manager.py index 120fb73cdb..c0fefef3d0 100644 --- a/api/core/file/file_manager.py +++ b/api/core/file/file_manager.py @@ -104,6 +104,8 @@ def download(f: File, /): ): return _download_file_content(f.storage_key) elif f.transfer_method == FileTransferMethod.REMOTE_URL: + if f.remote_url is None: + raise ValueError("Missing file remote_url") response = ssrf_proxy.get(f.remote_url, follow_redirects=True) response.raise_for_status() return response.content @@ -134,6 +136,8 @@ def _download_file_content(path: str, /): def _get_encoded_string(f: File, /): match f.transfer_method: case FileTransferMethod.REMOTE_URL: + if f.remote_url is None: + raise ValueError("Missing file remote_url") response = ssrf_proxy.get(f.remote_url, follow_redirects=True) response.raise_for_status() data = response.content diff --git a/api/core/helper/ssrf_proxy.py b/api/core/helper/ssrf_proxy.py index 128c64ff2c..ddccfbaf45 100644 --- a/api/core/helper/ssrf_proxy.py +++ b/api/core/helper/ssrf_proxy.py @@ -4,8 +4,10 @@ Proxy requests to avoid SSRF import logging import time +from typing import Any, TypeAlias import httpx +from pydantic import TypeAdapter, ValidationError from configs import dify_config from core.helper.http_client_pooling import get_pooled_http_client @@ -18,6 +20,9 @@ SSRF_DEFAULT_MAX_RETRIES = dify_config.SSRF_DEFAULT_MAX_RETRIES BACKOFF_FACTOR = 0.5 STATUS_FORCELIST = [429, 500, 502, 503, 504] +Headers: TypeAlias = dict[str, str] +_HEADERS_ADAPTER = TypeAdapter(Headers) + _SSL_VERIFIED_POOL_KEY = "ssrf:verified" _SSL_UNVERIFIED_POOL_KEY = "ssrf:unverified" _SSRF_CLIENT_LIMITS = httpx.Limits( @@ -76,7 +81,7 @@ def _get_ssrf_client(ssl_verify_enabled: bool) -> httpx.Client: ) -def _get_user_provided_host_header(headers: dict | None) -> str | None: +def _get_user_provided_host_header(headers: Headers | None) -> str | None: """ Extract the user-provided Host header from the headers dict. @@ -92,7 +97,7 @@ def _get_user_provided_host_header(headers: dict | None) -> str | None: return None -def _inject_trace_headers(headers: dict | None) -> dict: +def _inject_trace_headers(headers: Headers | None) -> Headers: """ Inject W3C traceparent header for distributed tracing. @@ -125,7 +130,7 @@ def _inject_trace_headers(headers: dict | None) -> dict: return headers -def make_request(method, url, max_retries=SSRF_DEFAULT_MAX_RETRIES, **kwargs): +def make_request(method: str, url: str, max_retries: int = SSRF_DEFAULT_MAX_RETRIES, **kwargs: Any) -> httpx.Response: # Convert requests-style allow_redirects to httpx-style follow_redirects if "allow_redirects" in kwargs: allow_redirects = kwargs.pop("allow_redirects") @@ -142,10 +147,15 @@ def make_request(method, url, max_retries=SSRF_DEFAULT_MAX_RETRIES, **kwargs): # prioritize per-call option, which can be switched on and off inside the HTTP node on the web UI verify_option = kwargs.pop("ssl_verify", dify_config.HTTP_REQUEST_NODE_SSL_VERIFY) + if not isinstance(verify_option, bool): + raise ValueError("ssl_verify must be a boolean") client = _get_ssrf_client(verify_option) # Inject traceparent header for distributed tracing (when OTEL is not enabled) - headers = kwargs.get("headers") or {} + try: + headers: Headers = _HEADERS_ADAPTER.validate_python(kwargs.get("headers") or {}) + except ValidationError as e: + raise ValueError("headers must be a mapping of string keys to string values") from e headers = _inject_trace_headers(headers) kwargs["headers"] = headers @@ -198,25 +208,25 @@ def make_request(method, url, max_retries=SSRF_DEFAULT_MAX_RETRIES, **kwargs): raise MaxRetriesExceededError(f"Reached maximum retries ({max_retries}) for URL {url}") -def get(url, max_retries=SSRF_DEFAULT_MAX_RETRIES, **kwargs): +def get(url: str, max_retries: int = SSRF_DEFAULT_MAX_RETRIES, **kwargs: Any) -> httpx.Response: return make_request("GET", url, max_retries=max_retries, **kwargs) -def post(url, max_retries=SSRF_DEFAULT_MAX_RETRIES, **kwargs): +def post(url: str, max_retries: int = SSRF_DEFAULT_MAX_RETRIES, **kwargs: Any) -> httpx.Response: return make_request("POST", url, max_retries=max_retries, **kwargs) -def put(url, max_retries=SSRF_DEFAULT_MAX_RETRIES, **kwargs): +def put(url: str, max_retries: int = SSRF_DEFAULT_MAX_RETRIES, **kwargs: Any) -> httpx.Response: return make_request("PUT", url, max_retries=max_retries, **kwargs) -def patch(url, max_retries=SSRF_DEFAULT_MAX_RETRIES, **kwargs): +def patch(url: str, max_retries: int = SSRF_DEFAULT_MAX_RETRIES, **kwargs: Any) -> httpx.Response: return make_request("PATCH", url, max_retries=max_retries, **kwargs) -def delete(url, max_retries=SSRF_DEFAULT_MAX_RETRIES, **kwargs): +def delete(url: str, max_retries: int = SSRF_DEFAULT_MAX_RETRIES, **kwargs: Any) -> httpx.Response: return make_request("DELETE", url, max_retries=max_retries, **kwargs) -def head(url, max_retries=SSRF_DEFAULT_MAX_RETRIES, **kwargs): +def head(url: str, max_retries: int = SSRF_DEFAULT_MAX_RETRIES, **kwargs: Any) -> httpx.Response: return make_request("HEAD", url, max_retries=max_retries, **kwargs) diff --git a/api/core/rag/extractor/word_extractor.py b/api/core/rag/extractor/word_extractor.py index 511f5a698d..1ddbfc5864 100644 --- a/api/core/rag/extractor/word_extractor.py +++ b/api/core/rag/extractor/word_extractor.py @@ -1,4 +1,7 @@ -"""Abstract interface for document loader implementations.""" +"""Word (.docx) document extractor used for RAG ingestion. + +Supports local file paths and remote URLs (downloaded via `core.helper.ssrf_proxy`). +""" import logging import mimetypes @@ -8,7 +11,6 @@ import tempfile import uuid from urllib.parse import urlparse -import httpx from docx import Document as DocxDocument from docx.oxml.ns import qn from docx.text.run import Run @@ -44,7 +46,7 @@ class WordExtractor(BaseExtractor): # If the file is a web path, download it to a temporary file, and use that if not os.path.isfile(self.file_path) and self._is_valid_url(self.file_path): - response = httpx.get(self.file_path, timeout=None) + response = ssrf_proxy.get(self.file_path) if response.status_code != 200: response.close() @@ -55,6 +57,7 @@ class WordExtractor(BaseExtractor): self.temp_file = tempfile.NamedTemporaryFile() # noqa SIM115 try: self.temp_file.write(response.content) + self.temp_file.flush() finally: response.close() self.file_path = self.temp_file.name diff --git a/api/tests/unit_tests/core/rag/extractor/test_word_extractor.py b/api/tests/unit_tests/core/rag/extractor/test_word_extractor.py index f9e59a5f05..0792ada194 100644 --- a/api/tests/unit_tests/core/rag/extractor/test_word_extractor.py +++ b/api/tests/unit_tests/core/rag/extractor/test_word_extractor.py @@ -1,7 +1,9 @@ """Primarily used for testing merged cell scenarios""" +import io import os import tempfile +from pathlib import Path from types import SimpleNamespace from docx import Document @@ -56,6 +58,42 @@ def test_parse_row(): assert extractor._parse_row(row, {}, 3) == gt[idx] +def test_init_downloads_via_ssrf_proxy(monkeypatch): + doc = Document() + doc.add_paragraph("hello") + buf = io.BytesIO() + doc.save(buf) + docx_bytes = buf.getvalue() + + calls: list[tuple[str, object]] = [] + + class FakeResponse: + status_code = 200 + content = docx_bytes + + def close(self) -> None: + calls.append(("close", None)) + + def fake_get(url: str, **kwargs): + calls.append(("get", (url, kwargs))) + return FakeResponse() + + monkeypatch.setattr(we, "ssrf_proxy", SimpleNamespace(get=fake_get)) + + extractor = WordExtractor("https://example.com/test.docx", "tenant_id", "user_id") + try: + assert calls + assert calls[0][0] == "get" + url, kwargs = calls[0][1] + assert url == "https://example.com/test.docx" + assert kwargs.get("timeout") is None + assert extractor.web_path == "https://example.com/test.docx" + assert extractor.file_path != extractor.web_path + assert Path(extractor.file_path).read_bytes() == docx_bytes + finally: + extractor.temp_file.close() + + def test_extract_images_from_docx(monkeypatch): external_bytes = b"ext-bytes" internal_bytes = b"int-bytes" From ceb69147931c95ff2df4d31094a3f0dd030cddf2 Mon Sep 17 00:00:00 2001 From: Nie Ronghua Date: Thu, 29 Jan 2026 14:31:15 +0800 Subject: [PATCH 03/15] refactor(model): Refactor plugin model schema cache to be process-global to prevent redundant Daemon API calls (#31689) Signed-off-by: -LAN- Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com> Co-authored-by: -LAN- --- api/configs/feature/__init__.py | 5 ++ api/contexts/__init__.py | 7 -- .../model_providers/__base/ai_model.py | 78 +++++++++++++------ .../model_providers/model_provider_factory.py | 73 ++++++++++++----- 4 files changed, 111 insertions(+), 52 deletions(-) diff --git a/api/configs/feature/__init__.py b/api/configs/feature/__init__.py index 786094f295..4343a056dd 100644 --- a/api/configs/feature/__init__.py +++ b/api/configs/feature/__init__.py @@ -243,6 +243,11 @@ class PluginConfig(BaseSettings): default=15728640 * 12, ) + PLUGIN_MODEL_SCHEMA_CACHE_TTL: PositiveInt = Field( + description="TTL in seconds for caching plugin model schemas in Redis", + default=24 * 60 * 60, + ) + class MarketplaceConfig(BaseSettings): """ diff --git a/api/contexts/__init__.py b/api/contexts/__init__.py index 7c16bc231f..c52dcf8a57 100644 --- a/api/contexts/__init__.py +++ b/api/contexts/__init__.py @@ -6,7 +6,6 @@ from contexts.wrapper import RecyclableContextVar if TYPE_CHECKING: from core.datasource.__base.datasource_provider import DatasourcePluginProviderController - from core.model_runtime.entities.model_entities import AIModelEntity from core.plugin.entities.plugin_daemon import PluginModelProviderEntity from core.tools.plugin_tool.provider import PluginToolProviderController from core.trigger.provider import PluginTriggerProviderController @@ -29,12 +28,6 @@ plugin_model_providers_lock: RecyclableContextVar[Lock] = RecyclableContextVar( ContextVar("plugin_model_providers_lock") ) -plugin_model_schema_lock: RecyclableContextVar[Lock] = RecyclableContextVar(ContextVar("plugin_model_schema_lock")) - -plugin_model_schemas: RecyclableContextVar[dict[str, "AIModelEntity"]] = RecyclableContextVar( - ContextVar("plugin_model_schemas") -) - datasource_plugin_providers: RecyclableContextVar[dict[str, "DatasourcePluginProviderController"]] = ( RecyclableContextVar(ContextVar("datasource_plugin_providers")) ) diff --git a/api/core/model_runtime/model_providers/__base/ai_model.py b/api/core/model_runtime/model_providers/__base/ai_model.py index 45f0335c2e..c3e50eaddd 100644 --- a/api/core/model_runtime/model_providers/__base/ai_model.py +++ b/api/core/model_runtime/model_providers/__base/ai_model.py @@ -1,10 +1,11 @@ import decimal import hashlib -from threading import Lock +import logging -from pydantic import BaseModel, ConfigDict, Field +from pydantic import BaseModel, ConfigDict, Field, ValidationError +from redis import RedisError -import contexts +from configs import dify_config from core.model_runtime.entities.common_entities import I18nObject from core.model_runtime.entities.defaults import PARAMETER_RULE_TEMPLATE from core.model_runtime.entities.model_entities import ( @@ -24,6 +25,9 @@ from core.model_runtime.errors.invoke import ( InvokeServerUnavailableError, ) from core.plugin.entities.plugin_daemon import PluginModelProviderEntity +from extensions.ext_redis import redis_client + +logger = logging.getLogger(__name__) class AIModel(BaseModel): @@ -144,34 +148,60 @@ class AIModel(BaseModel): plugin_model_manager = PluginModelClient() cache_key = f"{self.tenant_id}:{self.plugin_id}:{self.provider_name}:{self.model_type.value}:{model}" - # sort credentials sorted_credentials = sorted(credentials.items()) if credentials else [] cache_key += ":".join([hashlib.md5(f"{k}:{v}".encode()).hexdigest() for k, v in sorted_credentials]) + cached_schema_json = None try: - contexts.plugin_model_schemas.get() - except LookupError: - contexts.plugin_model_schemas.set({}) - contexts.plugin_model_schema_lock.set(Lock()) - - with contexts.plugin_model_schema_lock.get(): - if cache_key in contexts.plugin_model_schemas.get(): - return contexts.plugin_model_schemas.get()[cache_key] - - schema = plugin_model_manager.get_model_schema( - tenant_id=self.tenant_id, - user_id="unknown", - plugin_id=self.plugin_id, - provider=self.provider_name, - model_type=self.model_type.value, - model=model, - credentials=credentials or {}, + cached_schema_json = redis_client.get(cache_key) + except (RedisError, RuntimeError) as exc: + logger.warning( + "Failed to read plugin model schema cache for model %s: %s", + model, + str(exc), + exc_info=True, ) + if cached_schema_json: + try: + return AIModelEntity.model_validate_json(cached_schema_json) + except ValidationError: + logger.warning( + "Failed to validate cached plugin model schema for model %s", + model, + exc_info=True, + ) + try: + redis_client.delete(cache_key) + except (RedisError, RuntimeError) as exc: + logger.warning( + "Failed to delete invalid plugin model schema cache for model %s: %s", + model, + str(exc), + exc_info=True, + ) - if schema: - contexts.plugin_model_schemas.get()[cache_key] = schema + schema = plugin_model_manager.get_model_schema( + tenant_id=self.tenant_id, + user_id="unknown", + plugin_id=self.plugin_id, + provider=self.provider_name, + model_type=self.model_type.value, + model=model, + credentials=credentials or {}, + ) - return schema + if schema: + try: + redis_client.setex(cache_key, dify_config.PLUGIN_MODEL_SCHEMA_CACHE_TTL, schema.model_dump_json()) + except (RedisError, RuntimeError) as exc: + logger.warning( + "Failed to write plugin model schema cache for model %s: %s", + model, + str(exc), + exc_info=True, + ) + + return schema def get_customizable_model_schema_from_credentials(self, model: str, credentials: dict) -> AIModelEntity | None: """ diff --git a/api/core/model_runtime/model_providers/model_provider_factory.py b/api/core/model_runtime/model_providers/model_provider_factory.py index 28f162a928..64538a6779 100644 --- a/api/core/model_runtime/model_providers/model_provider_factory.py +++ b/api/core/model_runtime/model_providers/model_provider_factory.py @@ -5,7 +5,11 @@ import logging from collections.abc import Sequence from threading import Lock +from pydantic import ValidationError +from redis import RedisError + import contexts +from configs import dify_config from core.model_runtime.entities.model_entities import AIModelEntity, ModelType from core.model_runtime.entities.provider_entities import ProviderConfig, ProviderEntity, SimpleProviderEntity from core.model_runtime.model_providers.__base.ai_model import AIModel @@ -18,6 +22,7 @@ from core.model_runtime.model_providers.__base.tts_model import TTSModel from core.model_runtime.schema_validators.model_credential_schema_validator import ModelCredentialSchemaValidator from core.model_runtime.schema_validators.provider_credential_schema_validator import ProviderCredentialSchemaValidator from core.plugin.entities.plugin_daemon import PluginModelProviderEntity +from extensions.ext_redis import redis_client from models.provider_ids import ModelProviderID logger = logging.getLogger(__name__) @@ -175,34 +180,60 @@ class ModelProviderFactory: """ plugin_id, provider_name = self.get_plugin_id_and_provider_name_from_provider(provider) cache_key = f"{self.tenant_id}:{plugin_id}:{provider_name}:{model_type.value}:{model}" - # sort credentials sorted_credentials = sorted(credentials.items()) if credentials else [] cache_key += ":".join([hashlib.md5(f"{k}:{v}".encode()).hexdigest() for k, v in sorted_credentials]) + cached_schema_json = None try: - contexts.plugin_model_schemas.get() - except LookupError: - contexts.plugin_model_schemas.set({}) - contexts.plugin_model_schema_lock.set(Lock()) - - with contexts.plugin_model_schema_lock.get(): - if cache_key in contexts.plugin_model_schemas.get(): - return contexts.plugin_model_schemas.get()[cache_key] - - schema = self.plugin_model_manager.get_model_schema( - tenant_id=self.tenant_id, - user_id="unknown", - plugin_id=plugin_id, - provider=provider_name, - model_type=model_type.value, - model=model, - credentials=credentials or {}, + cached_schema_json = redis_client.get(cache_key) + except (RedisError, RuntimeError) as exc: + logger.warning( + "Failed to read plugin model schema cache for model %s: %s", + model, + str(exc), + exc_info=True, ) + if cached_schema_json: + try: + return AIModelEntity.model_validate_json(cached_schema_json) + except ValidationError: + logger.warning( + "Failed to validate cached plugin model schema for model %s", + model, + exc_info=True, + ) + try: + redis_client.delete(cache_key) + except (RedisError, RuntimeError) as exc: + logger.warning( + "Failed to delete invalid plugin model schema cache for model %s: %s", + model, + str(exc), + exc_info=True, + ) - if schema: - contexts.plugin_model_schemas.get()[cache_key] = schema + schema = self.plugin_model_manager.get_model_schema( + tenant_id=self.tenant_id, + user_id="unknown", + plugin_id=plugin_id, + provider=provider_name, + model_type=model_type.value, + model=model, + credentials=credentials or {}, + ) - return schema + if schema: + try: + redis_client.setex(cache_key, dify_config.PLUGIN_MODEL_SCHEMA_CACHE_TTL, schema.model_dump_json()) + except (RedisError, RuntimeError) as exc: + logger.warning( + "Failed to write plugin model schema cache for model %s: %s", + model, + str(exc), + exc_info=True, + ) + + return schema def get_models( self, From 3bcfb4031ac3a1e97238ab6e5c68a986f73f6a95 Mon Sep 17 00:00:00 2001 From: Asuka Minato Date: Thu, 29 Jan 2026 15:34:14 +0900 Subject: [PATCH 04/15] refactor: ExporleBanner to TypeBase (#31698) --- api/controllers/console/admin.py | 14 ++++++-------- api/models/model.py | 22 ++++++++++++++-------- 2 files changed, 20 insertions(+), 16 deletions(-) diff --git a/api/controllers/console/admin.py b/api/controllers/console/admin.py index e1ee2c24b8..03b602f6e8 100644 --- a/api/controllers/console/admin.py +++ b/api/controllers/console/admin.py @@ -243,15 +243,13 @@ class InsertExploreBannerApi(Resource): def post(self): payload = InsertExploreBannerPayload.model_validate(console_ns.payload) - content = { - "category": payload.category, - "title": payload.title, - "description": payload.description, - "img-src": payload.img_src, - } - banner = ExporleBanner( - content=content, + content={ + "category": payload.category, + "title": payload.title, + "description": payload.description, + "img-src": payload.img_src, + }, link=payload.link, sort=payload.sort, language=payload.language, diff --git a/api/models/model.py b/api/models/model.py index be0cfd58a7..c1c6e04ce9 100644 --- a/api/models/model.py +++ b/api/models/model.py @@ -657,16 +657,22 @@ class AccountTrialAppRecord(Base): return user -class ExporleBanner(Base): +class ExporleBanner(TypeBase): __tablename__ = "exporle_banners" __table_args__ = (sa.PrimaryKeyConstraint("id", name="exporler_banner_pkey"),) - id = mapped_column(StringUUID, server_default=sa.text("uuid_generate_v4()")) - content = mapped_column(sa.JSON, nullable=False) - link = mapped_column(String(255), nullable=False) - sort = mapped_column(sa.Integer, nullable=False) - status = mapped_column(sa.String(255), nullable=False, server_default=sa.text("'enabled'::character varying")) - created_at = mapped_column(sa.DateTime, nullable=False, server_default=func.current_timestamp()) - language = mapped_column(String(255), nullable=False, server_default=sa.text("'en-US'::character varying")) + id: Mapped[str] = mapped_column(StringUUID, server_default=sa.text("uuid_generate_v4()"), init=False) + content: Mapped[dict[str, Any]] = mapped_column(sa.JSON, nullable=False) + link: Mapped[str] = mapped_column(String(255), nullable=False) + sort: Mapped[int] = mapped_column(sa.Integer, nullable=False) + status: Mapped[str] = mapped_column( + sa.String(255), nullable=False, server_default=sa.text("'enabled'::character varying"), default="enabled" + ) + created_at: Mapped[datetime] = mapped_column( + sa.DateTime, nullable=False, server_default=func.current_timestamp(), init=False + ) + language: Mapped[str] = mapped_column( + String(255), nullable=False, server_default=sa.text("'en-US'::character varying"), default="en-US" + ) class OAuthProviderApp(TypeBase): From 0934b89da9401ee3068b7c723b3fc2b24ef38a7d Mon Sep 17 00:00:00 2001 From: -LAN- Date: Thu, 29 Jan 2026 15:06:40 +0800 Subject: [PATCH 05/15] chore(import-linter): add a rule to make model_runtime isolate (#31706) --- api/.importlinter | 52 +++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 52 insertions(+) diff --git a/api/.importlinter b/api/.importlinter index ff0577222e..9dad254560 100644 --- a/api/.importlinter +++ b/api/.importlinter @@ -303,6 +303,58 @@ ignore_imports = core.workflow.nodes.agent.agent_node -> services core.workflow.nodes.tool.tool_node -> services +[importlinter:contract:model-runtime-no-internal-imports] +name = Model Runtime Internal Imports +type = forbidden +source_modules = + core.model_runtime +forbidden_modules = + configs + controllers + extensions + models + services + tasks + core.agent + core.app + core.base + core.callback_handler + core.datasource + core.db + core.entities + core.errors + core.extension + core.external_data_tool + core.file + core.helper + core.hosting_configuration + core.indexing_runner + core.llm_generator + core.logging + core.mcp + core.memory + core.model_manager + core.moderation + core.ops + core.plugin + core.prompt + core.provider_manager + core.rag + core.repositories + core.schemas + core.tools + core.trigger + core.variables + core.workflow +ignore_imports = + core.model_runtime.model_providers.__base.ai_model -> configs + core.model_runtime.model_providers.__base.ai_model -> extensions.ext_redis + core.model_runtime.model_providers.__base.large_language_model -> configs + core.model_runtime.model_providers.__base.text_embedding_model -> core.entities.embedding_type + core.model_runtime.model_providers.model_provider_factory -> configs + core.model_runtime.model_providers.model_provider_factory -> extensions.ext_redis + core.model_runtime.model_providers.model_provider_factory -> models.provider_ids + [importlinter:contract:rsc] name = RSC type = layers From 4f2cd4049856115dab18464b93601c7aa1ea18b1 Mon Sep 17 00:00:00 2001 From: JQSevenMiao <141806521+JQSevenMiao@users.noreply.github.com> Date: Thu, 29 Jan 2026 15:37:37 +0800 Subject: [PATCH 06/15] fix: convert HTTP method to lowercase when parsing cURL commands (#31704) Co-authored-by: jiasiqi --- .../components/workflow/nodes/http/components/curl-panel.tsx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/web/app/components/workflow/nodes/http/components/curl-panel.tsx b/web/app/components/workflow/nodes/http/components/curl-panel.tsx index aa67a2a0ae..6c809c310f 100644 --- a/web/app/components/workflow/nodes/http/components/curl-panel.tsx +++ b/web/app/components/workflow/nodes/http/components/curl-panel.tsx @@ -41,7 +41,7 @@ const parseCurl = (curlCommand: string): { node: HttpNodeType | null, error: str case '--request': if (i + 1 >= args.length) return { node: null, error: 'Missing HTTP method after -X or --request.' } - node.method = (args[++i].replace(/^['"]|['"]$/g, '') as Method) || Method.get + node.method = (args[++i].replace(/^['"]|['"]$/g, '').toLowerCase() as Method) || Method.get hasData = true break case '-H': From 74cfe776744c7aa4ca5c820f0a60cb852a650700 Mon Sep 17 00:00:00 2001 From: Seokrin Taron Sung Date: Thu, 29 Jan 2026 16:51:51 +0900 Subject: [PATCH 07/15] fix(web): remove unwanted border on sticky elements in dark mode (#31699) --- web/app/styles/monaco-sticky-fix.css | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/web/app/styles/monaco-sticky-fix.css b/web/app/styles/monaco-sticky-fix.css index 66bb5921ce..ac928cf246 100644 --- a/web/app/styles/monaco-sticky-fix.css +++ b/web/app/styles/monaco-sticky-fix.css @@ -9,8 +9,7 @@ html[data-theme="dark"] .monaco-editor .sticky-line-content:hover { background-color: var(--color-components-sticky-header-bg-hover) !important; } -/* Fallback: any app sticky header using input-bg variables should use the sticky header bg when sticky */ -html[data-theme="dark"] .sticky, html[data-theme="dark"] .is-sticky { +/* Monaco editor specific sticky scroll styles in dark mode */ +html[data-theme="dark"] .monaco-editor .sticky-line-root { background-color: var(--color-components-sticky-header-bg) !important; - border-bottom: 1px solid var(--color-components-sticky-header-border) !important; } \ No newline at end of file From b9ac7af9c5246f84bf86efd87207ac0e26ae8a9f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E7=9B=90=E7=B2=92=20Yanli?= Date: Thu, 29 Jan 2026 16:02:49 +0800 Subject: [PATCH 08/15] refactor(web): consolidate download helpers (#31664) --- web/app/components/app-sidebar/app-info.tsx | 8 +- .../app-sidebar/dataset-info/dropdown.tsx | 8 +- .../app/annotation/header-opts/index.tsx | 16 ++-- .../configuration/config-var/index.spec.tsx | 6 +- web/app/components/apps/app-card.tsx | 10 +-- .../file-uploader-in-attachment/file-item.tsx | 4 +- .../file-image-item.tsx | 4 +- .../file-uploader-in-chat-input/file-item.tsx | 4 +- .../base/file-uploader/utils.spec.ts | 72 ------------------ .../components/base/file-uploader/utils.ts | 12 --- .../base/image-uploader/image-preview.tsx | 36 +++------ web/app/components/base/qrcode/index.tsx | 10 +-- .../index-failed.spec.tsx | 11 ++- .../list/template-card/index.spec.tsx | 13 ++-- .../list/template-card/index.tsx | 7 +- .../create/website/watercrawl/index.tsx | 20 ++++- .../hooks/use-dataset-card-state.ts | 8 +- .../header/account-dropdown/compliance.tsx | 5 +- .../components/rag-pipeline/hooks/use-DSL.ts | 8 +- .../components/workflow-app/hooks/use-DSL.ts | 8 +- .../market-place-plugin/action.tsx | 4 +- .../workflow/operator/more-actions.tsx | 23 ++---- web/eslint-suppressions.json | 9 +-- web/utils/download.spec.ts | 75 +++++++++++++++++++ web/utils/format.spec.ts | 45 +---------- web/utils/format.ts | 11 --- 26 files changed, 167 insertions(+), 270 deletions(-) create mode 100644 web/utils/download.spec.ts diff --git a/web/app/components/app-sidebar/app-info.tsx b/web/app/components/app-sidebar/app-info.tsx index 255feaccdf..aa31f0201f 100644 --- a/web/app/components/app-sidebar/app-info.tsx +++ b/web/app/components/app-sidebar/app-info.tsx @@ -31,6 +31,7 @@ import { fetchWorkflowDraft } from '@/service/workflow' import { AppModeEnum } from '@/types/app' import { getRedirection } from '@/utils/app-redirection' import { cn } from '@/utils/classnames' +import { downloadBlob } from '@/utils/download' import AppIcon from '../base/app-icon' import AppOperations from './app-operations' @@ -145,13 +146,8 @@ const AppInfo = ({ expand, onlyShowDetail = false, openState = false, onDetailEx appID: appDetail.id, include, }) - const a = document.createElement('a') const file = new Blob([data], { type: 'application/yaml' }) - const url = URL.createObjectURL(file) - a.href = url - a.download = `${appDetail.name}.yml` - a.click() - URL.revokeObjectURL(url) + downloadBlob({ data: file, fileName: `${appDetail.name}.yml` }) } catch { notify({ type: 'error', message: t('exportFailed', { ns: 'app' }) }) diff --git a/web/app/components/app-sidebar/dataset-info/dropdown.tsx b/web/app/components/app-sidebar/dataset-info/dropdown.tsx index 4d7c832e04..96127c4210 100644 --- a/web/app/components/app-sidebar/dataset-info/dropdown.tsx +++ b/web/app/components/app-sidebar/dataset-info/dropdown.tsx @@ -11,6 +11,7 @@ import { datasetDetailQueryKeyPrefix, useInvalidDatasetList } from '@/service/kn import { useInvalid } from '@/service/use-base' import { useExportPipelineDSL } from '@/service/use-pipeline' import { cn } from '@/utils/classnames' +import { downloadBlob } from '@/utils/download' import ActionButton from '../../base/action-button' import Confirm from '../../base/confirm' import { PortalToFollowElem, PortalToFollowElemContent, PortalToFollowElemTrigger } from '../../base/portal-to-follow-elem' @@ -64,13 +65,8 @@ const DropDown = ({ pipelineId: pipeline_id, include, }) - const a = document.createElement('a') const file = new Blob([data], { type: 'application/yaml' }) - const url = URL.createObjectURL(file) - a.href = url - a.download = `${name}.pipeline` - a.click() - URL.revokeObjectURL(url) + downloadBlob({ data: file, fileName: `${name}.pipeline` }) } catch { Toast.notify({ type: 'error', message: t('exportFailed', { ns: 'app' }) }) diff --git a/web/app/components/app/annotation/header-opts/index.tsx b/web/app/components/app/annotation/header-opts/index.tsx index 5add1aed32..4fc1e26007 100644 --- a/web/app/components/app/annotation/header-opts/index.tsx +++ b/web/app/components/app/annotation/header-opts/index.tsx @@ -21,6 +21,7 @@ import { LanguagesSupported } from '@/i18n-config/language' import { clearAllAnnotations, fetchExportAnnotationList } from '@/service/annotation' import { cn } from '@/utils/classnames' +import { downloadBlob } from '@/utils/download' import Button from '../../../base/button' import AddAnnotationModal from '../add-annotation-modal' import BatchAddModal from '../batch-add-annotation-modal' @@ -56,28 +57,23 @@ const HeaderOptions: FC = ({ ) const JSONLOutput = () => { - const a = document.createElement('a') const content = listTransformer(list).join('\n') const file = new Blob([content], { type: 'application/jsonl' }) - const url = URL.createObjectURL(file) - a.href = url - a.download = `annotations-${locale}.jsonl` - a.click() - URL.revokeObjectURL(url) + downloadBlob({ data: file, fileName: `annotations-${locale}.jsonl` }) } - const fetchList = async () => { + const fetchList = React.useCallback(async () => { const { data }: any = await fetchExportAnnotationList(appId) setList(data as AnnotationItemBasic[]) - } + }, [appId]) useEffect(() => { fetchList() - }, []) + }, [fetchList]) useEffect(() => { if (controlUpdateList) fetchList() - }, [controlUpdateList]) + }, [controlUpdateList, fetchList]) const [showBulkImportModal, setShowBulkImportModal] = useState(false) const [showClearConfirm, setShowClearConfirm] = useState(false) diff --git a/web/app/components/app/configuration/config-var/index.spec.tsx b/web/app/components/app/configuration/config-var/index.spec.tsx index b5015ed079..490d7b4410 100644 --- a/web/app/components/app/configuration/config-var/index.spec.tsx +++ b/web/app/components/app/configuration/config-var/index.spec.tsx @@ -2,7 +2,7 @@ import type { ReactNode } from 'react' import type { IConfigVarProps } from './index' import type { ExternalDataTool } from '@/models/common' import type { PromptVariable } from '@/models/debug' -import { act, fireEvent, render, screen } from '@testing-library/react' +import { act, fireEvent, render, screen, waitFor } from '@testing-library/react' import * as React from 'react' import { vi } from 'vitest' import Toast from '@/app/components/base/toast' @@ -240,7 +240,9 @@ describe('ConfigVar', () => { const saveButton = await screen.findByRole('button', { name: 'common.operation.save' }) fireEvent.click(saveButton) - expect(onPromptVariablesChange).toHaveBeenCalledTimes(1) + await waitFor(() => { + expect(onPromptVariablesChange).toHaveBeenCalledTimes(1) + }) }) it('should show error when variable key is duplicated', async () => { diff --git a/web/app/components/apps/app-card.tsx b/web/app/components/apps/app-card.tsx index f1eadb9d05..730a39b68d 100644 --- a/web/app/components/apps/app-card.tsx +++ b/web/app/components/apps/app-card.tsx @@ -33,6 +33,7 @@ import { fetchWorkflowDraft } from '@/service/workflow' import { AppModeEnum } from '@/types/app' import { getRedirection } from '@/utils/app-redirection' import { cn } from '@/utils/classnames' +import { downloadBlob } from '@/utils/download' import { formatTime } from '@/utils/time' import { basePath } from '@/utils/var' @@ -161,13 +162,8 @@ const AppCard = ({ app, onRefresh }: AppCardProps) => { appID: app.id, include, }) - const a = document.createElement('a') const file = new Blob([data], { type: 'application/yaml' }) - const url = URL.createObjectURL(file) - a.href = url - a.download = `${app.name}.yml` - a.click() - URL.revokeObjectURL(url) + downloadBlob({ data: file, fileName: `${app.name}.yml` }) } catch { notify({ type: 'error', message: t('exportFailed', { ns: 'app' }) }) @@ -346,7 +342,7 @@ const AppCard = ({ app, onRefresh }: AppCardProps) => { dateFormat: `${t('segment.dateTimeFormat', { ns: 'datasetDocuments' })}`, }) return `${t('segment.editedAt', { ns: 'datasetDocuments' })} ${timeText}` - }, [app.updated_at, app.created_at]) + }, [app.updated_at, app.created_at, t]) return ( <> diff --git a/web/app/components/base/file-uploader/file-uploader-in-attachment/file-item.tsx b/web/app/components/base/file-uploader/file-uploader-in-attachment/file-item.tsx index 6ef5bcb308..f8015aa7c7 100644 --- a/web/app/components/base/file-uploader/file-uploader-in-attachment/file-item.tsx +++ b/web/app/components/base/file-uploader/file-uploader-in-attachment/file-item.tsx @@ -15,11 +15,11 @@ import ImagePreview from '@/app/components/base/image-uploader/image-preview' import ProgressCircle from '@/app/components/base/progress-bar/progress-circle' import { SupportUploadFileTypes } from '@/app/components/workflow/types' import { cn } from '@/utils/classnames' +import { downloadUrl } from '@/utils/download' import { formatFileSize } from '@/utils/format' import FileImageRender from '../file-image-render' import FileTypeIcon from '../file-type-icon' import { - downloadFile, fileIsUploaded, getFileAppearanceType, getFileExtension, @@ -140,7 +140,7 @@ const FileInAttachmentItem = ({ showDownloadAction && ( { e.stopPropagation() - downloadFile(url || base64Url || '', name) + downloadUrl({ url: url || base64Url || '', fileName: name, target: '_blank' }) }} > diff --git a/web/app/components/base/file-uploader/file-uploader-in-chat-input/file-image-item.tsx b/web/app/components/base/file-uploader/file-uploader-in-chat-input/file-image-item.tsx index 77dc3e35b8..d9118aac4f 100644 --- a/web/app/components/base/file-uploader/file-uploader-in-chat-input/file-image-item.tsx +++ b/web/app/components/base/file-uploader/file-uploader-in-chat-input/file-image-item.tsx @@ -8,9 +8,9 @@ import Button from '@/app/components/base/button' import { ReplayLine } from '@/app/components/base/icons/src/vender/other' import ImagePreview from '@/app/components/base/image-uploader/image-preview' import ProgressCircle from '@/app/components/base/progress-bar/progress-circle' +import { downloadUrl } from '@/utils/download' import FileImageRender from '../file-image-render' import { - downloadFile, fileIsUploaded, } from '../utils' @@ -85,7 +85,7 @@ const FileImageItem = ({ className="absolute bottom-0.5 right-0.5 flex h-6 w-6 items-center justify-center rounded-lg bg-components-actionbar-bg shadow-md" onClick={(e) => { e.stopPropagation() - downloadFile(download_url || '', name) + downloadUrl({ url: download_url || '', fileName: name, target: '_blank' }) }} > diff --git a/web/app/components/base/file-uploader/file-uploader-in-chat-input/file-item.tsx b/web/app/components/base/file-uploader/file-uploader-in-chat-input/file-item.tsx index 828864239a..af32f917b9 100644 --- a/web/app/components/base/file-uploader/file-uploader-in-chat-input/file-item.tsx +++ b/web/app/components/base/file-uploader/file-uploader-in-chat-input/file-item.tsx @@ -12,10 +12,10 @@ import VideoPreview from '@/app/components/base/file-uploader/video-preview' import { ReplayLine } from '@/app/components/base/icons/src/vender/other' import ProgressCircle from '@/app/components/base/progress-bar/progress-circle' import { cn } from '@/utils/classnames' +import { downloadUrl } from '@/utils/download' import { formatFileSize } from '@/utils/format' import FileTypeIcon from '../file-type-icon' import { - downloadFile, fileIsUploaded, getFileAppearanceType, getFileExtension, @@ -100,7 +100,7 @@ const FileItem = ({ className="absolute -right-1 -top-1 hidden group-hover/file-item:flex" onClick={(e) => { e.stopPropagation() - downloadFile(download_url || '', name) + downloadUrl({ url: download_url || '', fileName: name, target: '_blank' }) }} > diff --git a/web/app/components/base/file-uploader/utils.spec.ts b/web/app/components/base/file-uploader/utils.spec.ts index de167a8c25..f69b3c27f5 100644 --- a/web/app/components/base/file-uploader/utils.spec.ts +++ b/web/app/components/base/file-uploader/utils.spec.ts @@ -1,4 +1,3 @@ -import type { MockInstance } from 'vitest' import mime from 'mime' import { SupportUploadFileTypes } from '@/app/components/workflow/types' import { upload } from '@/service/base' @@ -6,7 +5,6 @@ import { TransferMethod } from '@/types/app' import { FILE_EXTS } from '../prompt-editor/constants' import { FileAppearanceTypeEnum } from './types' import { - downloadFile, fileIsUploaded, fileUpload, getFileAppearanceType, @@ -782,74 +780,4 @@ describe('file-uploader utils', () => { } as any)).toBe(true) }) }) - - describe('downloadFile', () => { - let mockAnchor: HTMLAnchorElement - let createElementMock: MockInstance - let appendChildMock: MockInstance - let removeChildMock: MockInstance - - beforeEach(() => { - // Mock createElement and appendChild - mockAnchor = { - href: '', - download: '', - style: { display: '' }, - target: '', - title: '', - click: vi.fn(), - } as unknown as HTMLAnchorElement - - createElementMock = vi.spyOn(document, 'createElement').mockReturnValue(mockAnchor as any) - appendChildMock = vi.spyOn(document.body, 'appendChild').mockImplementation((node: Node) => { - return node - }) - removeChildMock = vi.spyOn(document.body, 'removeChild').mockImplementation((node: Node) => { - return node - }) - }) - - afterEach(() => { - vi.resetAllMocks() - }) - - it('should create and trigger download with correct attributes', () => { - const url = 'https://example.com/test.pdf' - const filename = 'test.pdf' - - downloadFile(url, filename) - - // Verify anchor element was created with correct properties - expect(createElementMock).toHaveBeenCalledWith('a') - expect(mockAnchor.href).toBe(url) - expect(mockAnchor.download).toBe(filename) - expect(mockAnchor.style.display).toBe('none') - expect(mockAnchor.target).toBe('_blank') - expect(mockAnchor.title).toBe(filename) - - // Verify DOM operations - expect(appendChildMock).toHaveBeenCalledWith(mockAnchor) - expect(mockAnchor.click).toHaveBeenCalled() - expect(removeChildMock).toHaveBeenCalledWith(mockAnchor) - }) - - it('should handle empty filename', () => { - const url = 'https://example.com/test.pdf' - const filename = '' - - downloadFile(url, filename) - - expect(mockAnchor.download).toBe('') - expect(mockAnchor.title).toBe('') - }) - - it('should handle empty url', () => { - const url = '' - const filename = 'test.pdf' - - downloadFile(url, filename) - - expect(mockAnchor.href).toBe('') - }) - }) }) diff --git a/web/app/components/base/file-uploader/utils.ts b/web/app/components/base/file-uploader/utils.ts index 5d5754b8fe..23e460db51 100644 --- a/web/app/components/base/file-uploader/utils.ts +++ b/web/app/components/base/file-uploader/utils.ts @@ -249,15 +249,3 @@ export const fileIsUploaded = (file: FileEntity) => { if (file.transferMethod === TransferMethod.remote_url && file.progress === 100) return true } - -export const downloadFile = (url: string, filename: string) => { - const anchor = document.createElement('a') - anchor.href = url - anchor.download = filename - anchor.style.display = 'none' - anchor.target = '_blank' - anchor.title = filename - document.body.appendChild(anchor) - anchor.click() - document.body.removeChild(anchor) -} diff --git a/web/app/components/base/image-uploader/image-preview.tsx b/web/app/components/base/image-uploader/image-preview.tsx index b6a07c60aa..0641af3d79 100644 --- a/web/app/components/base/image-uploader/image-preview.tsx +++ b/web/app/components/base/image-uploader/image-preview.tsx @@ -8,6 +8,7 @@ import { createPortal } from 'react-dom' import { useHotkeys } from 'react-hotkeys-hook' import Toast from '@/app/components/base/toast' import Tooltip from '@/app/components/base/tooltip' +import { downloadUrl } from '@/utils/download' type ImagePreviewProps = { url: string @@ -60,27 +61,14 @@ const ImagePreview: FC = ({ const downloadImage = () => { // Open in a new window, considering the case when the page is inside an iframe - if (url.startsWith('http') || url.startsWith('https')) { - const a = document.createElement('a') - a.href = url - a.target = '_blank' - a.download = title - a.click() - } - else if (url.startsWith('data:image')) { - // Base64 image - const a = document.createElement('a') - a.href = url - a.target = '_blank' - a.download = title - a.click() - } - else { - Toast.notify({ - type: 'error', - message: `Unable to open image: ${url}`, - }) + if (url.startsWith('http') || url.startsWith('https') || url.startsWith('data:image')) { + downloadUrl({ url, fileName: title, target: '_blank' }) + return } + Toast.notify({ + type: 'error', + message: `Unable to open image: ${url}`, + }) } const zoomIn = () => { @@ -135,12 +123,7 @@ const ImagePreview: FC = ({ catch (err) { console.error('Failed to copy image:', err) - const link = document.createElement('a') - link.href = url - link.download = `${title}.png` - document.body.appendChild(link) - link.click() - document.body.removeChild(link) + downloadUrl({ url, fileName: `${title}.png` }) Toast.notify({ type: 'info', @@ -215,6 +198,7 @@ const ImagePreview: FC = ({ tabIndex={-1} > { } + {/* eslint-disable-next-line next/no-img-element */} {title} { }, [isShow]) const downloadQR = () => { - const canvas = document.getElementsByTagName('canvas')[0] - const link = document.createElement('a') - link.download = 'qrcode.png' - link.href = canvas.toDataURL() - link.click() + const canvas = qrCodeRef.current?.querySelector('canvas') + if (!(canvas instanceof HTMLCanvasElement)) + return + downloadUrl({ url: canvas.toDataURL(), fileName: 'qrcode.png' }) } const handlePanelClick = (event: React.MouseEvent) => { diff --git a/web/app/components/datasets/common/document-status-with-action/index-failed.spec.tsx b/web/app/components/datasets/common/document-status-with-action/index-failed.spec.tsx index 43255ce908..27070aaaed 100644 --- a/web/app/components/datasets/common/document-status-with-action/index-failed.spec.tsx +++ b/web/app/components/datasets/common/document-status-with-action/index-failed.spec.tsx @@ -179,8 +179,10 @@ describe('RetryButton (IndexFailed)', () => { }, false), ) - // Delay the response to test loading state - mockRetryErrorDocs.mockImplementation(() => new Promise(resolve => setTimeout(() => resolve({ result: 'success' }), 100))) + let resolveRetry: ((value: { result: 'success' }) => void) | undefined + mockRetryErrorDocs.mockImplementation(() => new Promise((resolve) => { + resolveRetry = resolve + })) render() @@ -193,6 +195,11 @@ describe('RetryButton (IndexFailed)', () => { expect(button).toHaveClass('cursor-not-allowed') expect(button).toHaveClass('text-text-disabled') }) + + resolveRetry?.({ result: 'success' }) + await waitFor(() => { + expect(mockRefetch).toHaveBeenCalled() + }) }) }) diff --git a/web/app/components/datasets/create-from-pipeline/list/template-card/index.spec.tsx b/web/app/components/datasets/create-from-pipeline/list/template-card/index.spec.tsx index 290f7af99b..036370abd3 100644 --- a/web/app/components/datasets/create-from-pipeline/list/template-card/index.spec.tsx +++ b/web/app/components/datasets/create-from-pipeline/list/template-card/index.spec.tsx @@ -23,9 +23,10 @@ vi.mock('@/app/components/base/toast', () => ({ }, })) -// Mock downloadFile utility -vi.mock('@/utils/format', () => ({ - downloadFile: vi.fn(), +// Mock download utilities +vi.mock('@/utils/download', () => ({ + downloadBlob: vi.fn(), + downloadUrl: vi.fn(), })) // Capture Confirm callbacks @@ -502,8 +503,8 @@ describe('TemplateCard', () => { }) }) - it('should call downloadFile on successful export', async () => { - const { downloadFile } = await import('@/utils/format') + it('should call downloadBlob on successful export', async () => { + const { downloadBlob } = await import('@/utils/download') mockExportPipelineDSL.mockImplementation((_id, callbacks) => { callbacks.onSuccess({ data: 'yaml_content' }) return Promise.resolve() @@ -514,7 +515,7 @@ describe('TemplateCard', () => { fireEvent.click(exportButton) await waitFor(() => { - expect(downloadFile).toHaveBeenCalledWith(expect.objectContaining({ + expect(downloadBlob).toHaveBeenCalledWith(expect.objectContaining({ fileName: 'Test Pipeline.pipeline', })) }) diff --git a/web/app/components/datasets/create-from-pipeline/list/template-card/index.tsx b/web/app/components/datasets/create-from-pipeline/list/template-card/index.tsx index 662ca72080..b3395a83d5 100644 --- a/web/app/components/datasets/create-from-pipeline/list/template-card/index.tsx +++ b/web/app/components/datasets/create-from-pipeline/list/template-card/index.tsx @@ -16,7 +16,7 @@ import { useInvalidCustomizedTemplateList, usePipelineTemplateById, } from '@/service/use-pipeline' -import { downloadFile } from '@/utils/format' +import { downloadBlob } from '@/utils/download' import Actions from './actions' import Content from './content' import Details from './details' @@ -108,10 +108,7 @@ const TemplateCard = ({ await exportPipelineDSL(pipeline.id, { onSuccess: (res) => { const blob = new Blob([res.data], { type: 'application/yaml' }) - downloadFile({ - data: blob, - fileName: `${pipeline.name}.pipeline`, - }) + downloadBlob({ data: blob, fileName: `${pipeline.name}.pipeline` }) Toast.notify({ type: 'success', message: t('exportDSL.successTip', { ns: 'datasetPipeline' }), diff --git a/web/app/components/datasets/create/website/watercrawl/index.tsx b/web/app/components/datasets/create/website/watercrawl/index.tsx index 0df2dbe8a1..e68a89ae5a 100644 --- a/web/app/components/datasets/create/website/watercrawl/index.tsx +++ b/web/app/components/datasets/create/website/watercrawl/index.tsx @@ -125,11 +125,25 @@ const WaterCrawl: FC = ({ await sleep(2500) return await waitForCrawlFinished(jobId) } - catch (e: any) { - const errorBody = await e.json() + catch (error: unknown) { + let errorMessage = '' + + const maybeErrorWithJson = error as { json?: () => Promise, message?: unknown } | null + if (maybeErrorWithJson?.json) { + try { + const errorBody = await maybeErrorWithJson.json() as { message?: unknown } | null + if (typeof errorBody?.message === 'string') + errorMessage = errorBody.message + } + catch {} + } + + if (!errorMessage && typeof maybeErrorWithJson?.message === 'string') + errorMessage = maybeErrorWithJson.message + return { isError: true, - errorMessage: errorBody.message, + errorMessage, data: { data: [], }, diff --git a/web/app/components/datasets/list/dataset-card/hooks/use-dataset-card-state.ts b/web/app/components/datasets/list/dataset-card/hooks/use-dataset-card-state.ts index ad68a1df1c..4bd8357f1c 100644 --- a/web/app/components/datasets/list/dataset-card/hooks/use-dataset-card-state.ts +++ b/web/app/components/datasets/list/dataset-card/hooks/use-dataset-card-state.ts @@ -5,6 +5,7 @@ import { useTranslation } from 'react-i18next' import Toast from '@/app/components/base/toast' import { useCheckDatasetUsage, useDeleteDataset } from '@/service/use-dataset-card' import { useExportPipelineDSL } from '@/service/use-pipeline' +import { downloadBlob } from '@/utils/download' type ModalState = { showRenameModal: boolean @@ -65,13 +66,8 @@ export const useDatasetCardState = ({ dataset, onSuccess }: UseDatasetCardStateO pipelineId: pipeline_id, include, }) - const a = document.createElement('a') const file = new Blob([data], { type: 'application/yaml' }) - const url = URL.createObjectURL(file) - a.href = url - a.download = `${name}.pipeline` - a.click() - URL.revokeObjectURL(url) + downloadBlob({ data: file, fileName: `${name}.pipeline` }) } catch { Toast.notify({ type: 'error', message: t('exportFailed', { ns: 'app' }) }) diff --git a/web/app/components/header/account-dropdown/compliance.tsx b/web/app/components/header/account-dropdown/compliance.tsx index 562914dd07..6bc5b5c3f1 100644 --- a/web/app/components/header/account-dropdown/compliance.tsx +++ b/web/app/components/header/account-dropdown/compliance.tsx @@ -10,6 +10,7 @@ import { useModalContext } from '@/context/modal-context' import { useProviderContext } from '@/context/provider-context' import { getDocDownloadUrl } from '@/service/common' import { cn } from '@/utils/classnames' +import { downloadUrl } from '@/utils/download' import Button from '../../base/button' import Gdpr from '../../base/icons/src/public/common/Gdpr' import Iso from '../../base/icons/src/public/common/Iso' @@ -47,9 +48,7 @@ const UpgradeOrDownload: FC = ({ doc_name }) => { mutationFn: async () => { try { const ret = await getDocDownloadUrl(doc_name) - const a = document.createElement('a') - a.href = ret.url - a.click() + downloadUrl({ url: ret.url }) Toast.notify({ type: 'success', message: t('operation.downloadSuccess', { ns: 'common' }), diff --git a/web/app/components/rag-pipeline/hooks/use-DSL.ts b/web/app/components/rag-pipeline/hooks/use-DSL.ts index 1660d555eb..5c0f9def1c 100644 --- a/web/app/components/rag-pipeline/hooks/use-DSL.ts +++ b/web/app/components/rag-pipeline/hooks/use-DSL.ts @@ -11,6 +11,7 @@ import { useWorkflowStore } from '@/app/components/workflow/store' import { useEventEmitterContextContext } from '@/context/event-emitter' import { useExportPipelineDSL } from '@/service/use-pipeline' import { fetchWorkflowDraft } from '@/service/workflow' +import { downloadBlob } from '@/utils/download' import { useNodesSyncDraft } from './use-nodes-sync-draft' export const useDSL = () => { @@ -37,13 +38,8 @@ export const useDSL = () => { pipelineId, include, }) - const a = document.createElement('a') const file = new Blob([data], { type: 'application/yaml' }) - const url = URL.createObjectURL(file) - a.href = url - a.download = `${knowledgeName}.pipeline` - a.click() - URL.revokeObjectURL(url) + downloadBlob({ data: file, fileName: `${knowledgeName}.pipeline` }) } catch { notify({ type: 'error', message: t('exportFailed', { ns: 'app' }) }) diff --git a/web/app/components/workflow-app/hooks/use-DSL.ts b/web/app/components/workflow-app/hooks/use-DSL.ts index 6c01509bc5..939e43b554 100644 --- a/web/app/components/workflow-app/hooks/use-DSL.ts +++ b/web/app/components/workflow-app/hooks/use-DSL.ts @@ -11,6 +11,7 @@ import { import { useEventEmitterContextContext } from '@/context/event-emitter' import { exportAppConfig } from '@/service/apps' import { fetchWorkflowDraft } from '@/service/workflow' +import { downloadBlob } from '@/utils/download' import { useNodesSyncDraft } from './use-nodes-sync-draft' export const useDSL = () => { @@ -37,13 +38,8 @@ export const useDSL = () => { include, workflowID: workflowId, }) - const a = document.createElement('a') const file = new Blob([data], { type: 'application/yaml' }) - const url = URL.createObjectURL(file) - a.href = url - a.download = `${appDetail.name}.yml` - a.click() - URL.revokeObjectURL(url) + downloadBlob({ data: file, fileName: `${appDetail.name}.yml` }) } catch { notify({ type: 'error', message: t('exportFailed', { ns: 'app' }) }) diff --git a/web/app/components/workflow/block-selector/market-place-plugin/action.tsx b/web/app/components/workflow/block-selector/market-place-plugin/action.tsx index b8300d6f2b..abdbae1b4c 100644 --- a/web/app/components/workflow/block-selector/market-place-plugin/action.tsx +++ b/web/app/components/workflow/block-selector/market-place-plugin/action.tsx @@ -15,7 +15,7 @@ import { } from '@/app/components/base/portal-to-follow-elem' import { useDownloadPlugin } from '@/service/use-plugins' import { cn } from '@/utils/classnames' -import { downloadFile } from '@/utils/format' +import { downloadBlob } from '@/utils/download' import { getMarketplaceUrl } from '@/utils/var' type Props = { @@ -67,7 +67,7 @@ const OperationDropdown: FC = ({ if (!needDownload || !blob) return const fileName = `${author}-${name}_${version}.zip` - downloadFile({ data: blob, fileName }) + downloadBlob({ data: blob, fileName }) setNeedDownload(false) queryClient.removeQueries({ queryKey: ['plugins', 'downloadPlugin', downloadInfo], diff --git a/web/app/components/workflow/operator/more-actions.tsx b/web/app/components/workflow/operator/more-actions.tsx index e9fc1ea87d..7e6617e84b 100644 --- a/web/app/components/workflow/operator/more-actions.tsx +++ b/web/app/components/workflow/operator/more-actions.tsx @@ -19,6 +19,7 @@ import { } from '@/app/components/base/portal-to-follow-elem' import { useStore } from '@/app/components/workflow/store' import { cn } from '@/utils/classnames' +import { downloadUrl } from '@/utils/download' import { useNodesReadOnly } from '../hooks' import TipPopup from './tip-popup' @@ -146,26 +147,14 @@ const MoreActions: FC = () => { } } + const fileName = `${filename}.${type}` + if (currentWorkflow) { setPreviewUrl(dataUrl) - setPreviewTitle(`${filename}.${type}`) + setPreviewTitle(fileName) + } - const link = document.createElement('a') - link.href = dataUrl - link.download = `${filename}.${type}` - document.body.appendChild(link) - link.click() - document.body.removeChild(link) - } - else { - // For current view, just download - const link = document.createElement('a') - link.href = dataUrl - link.download = `${filename}.${type}` - document.body.appendChild(link) - link.click() - document.body.removeChild(link) - } + downloadUrl({ url: dataUrl, fileName }) } catch (error) { console.error('Export image failed:', error) diff --git a/web/eslint-suppressions.json b/web/eslint-suppressions.json index abee200f66..6193a8ad4e 100644 --- a/web/eslint-suppressions.json +++ b/web/eslint-suppressions.json @@ -994,7 +994,7 @@ "count": 1 }, "ts/no-explicit-any": { - "count": 3 + "count": 2 } }, "app/components/base/file-uploader/utils.ts": { @@ -1661,7 +1661,7 @@ "count": 1 }, "ts/no-explicit-any": { - "count": 5 + "count": 4 } }, "app/components/datasets/create/website/watercrawl/options.tsx": { @@ -4376,11 +4376,6 @@ "count": 1 } }, - "utils/format.spec.ts": { - "ts/no-explicit-any": { - "count": 1 - } - }, "utils/get-icon.spec.ts": { "ts/no-explicit-any": { "count": 2 diff --git a/web/utils/download.spec.ts b/web/utils/download.spec.ts new file mode 100644 index 0000000000..ff41ddfff7 --- /dev/null +++ b/web/utils/download.spec.ts @@ -0,0 +1,75 @@ +import { downloadBlob, downloadUrl } from './download' + +describe('downloadUrl', () => { + let mockAnchor: HTMLAnchorElement + + beforeEach(() => { + mockAnchor = { + href: '', + download: '', + rel: '', + target: '', + style: { display: '' }, + click: vi.fn(), + remove: vi.fn(), + } as unknown as HTMLAnchorElement + + vi.spyOn(document, 'createElement').mockReturnValue(mockAnchor) + vi.spyOn(document.body, 'appendChild').mockImplementation((node: Node) => node) + }) + + afterEach(() => { + vi.restoreAllMocks() + }) + + it('should create a link and trigger a download correctly', () => { + downloadUrl({ url: 'https://example.com/file.txt', fileName: 'file.txt', target: '_blank' }) + + expect(mockAnchor.href).toBe('https://example.com/file.txt') + expect(mockAnchor.download).toBe('file.txt') + expect(mockAnchor.rel).toBe('noopener noreferrer') + expect(mockAnchor.target).toBe('_blank') + expect(mockAnchor.style.display).toBe('none') + expect(mockAnchor.click).toHaveBeenCalled() + expect(mockAnchor.remove).toHaveBeenCalled() + }) + + it('should skip when url is empty', () => { + downloadUrl({ url: '' }) + expect(document.createElement).not.toHaveBeenCalled() + }) +}) + +describe('downloadBlob', () => { + it('should create a blob url, trigger download, and revoke url', () => { + const blob = new Blob(['test'], { type: 'text/plain' }) + const mockUrl = 'blob:mock-url' + const createObjectURLMock = vi.spyOn(window.URL, 'createObjectURL').mockReturnValue(mockUrl) + const revokeObjectURLMock = vi.spyOn(window.URL, 'revokeObjectURL').mockImplementation(() => {}) + + const mockAnchor = { + href: '', + download: '', + rel: '', + target: '', + style: { display: '' }, + click: vi.fn(), + remove: vi.fn(), + } as unknown as HTMLAnchorElement + + vi.spyOn(document, 'createElement').mockReturnValue(mockAnchor) + vi.spyOn(document.body, 'appendChild').mockImplementation((node: Node) => node) + + downloadBlob({ data: blob, fileName: 'file.txt' }) + + expect(createObjectURLMock).toHaveBeenCalledWith(blob) + expect(mockAnchor.href).toBe(mockUrl) + expect(mockAnchor.download).toBe('file.txt') + expect(mockAnchor.rel).toBe('noopener noreferrer') + expect(mockAnchor.click).toHaveBeenCalled() + expect(mockAnchor.remove).toHaveBeenCalled() + expect(revokeObjectURLMock).toHaveBeenCalledWith(mockUrl) + + vi.restoreAllMocks() + }) +}) diff --git a/web/utils/format.spec.ts b/web/utils/format.spec.ts index 3a1709dbdc..2796854e34 100644 --- a/web/utils/format.spec.ts +++ b/web/utils/format.spec.ts @@ -1,4 +1,4 @@ -import { downloadFile, formatFileSize, formatNumber, formatNumberAbbreviated, formatTime } from './format' +import { formatFileSize, formatNumber, formatNumberAbbreviated, formatTime } from './format' describe('formatNumber', () => { it('should correctly format integers', () => { @@ -82,49 +82,6 @@ describe('formatTime', () => { expect(formatTime(7200)).toBe('2.00 h') }) }) -describe('downloadFile', () => { - it('should create a link and trigger a download correctly', () => { - // Mock data - const blob = new Blob(['test content'], { type: 'text/plain' }) - const fileName = 'test-file.txt' - const mockUrl = 'blob:mockUrl' - - // Mock URL.createObjectURL - const createObjectURLMock = vi.fn().mockReturnValue(mockUrl) - const revokeObjectURLMock = vi.fn() - Object.defineProperty(window.URL, 'createObjectURL', { value: createObjectURLMock }) - Object.defineProperty(window.URL, 'revokeObjectURL', { value: revokeObjectURLMock }) - - // Mock createElement and appendChild - const mockLink = { - href: '', - download: '', - click: vi.fn(), - remove: vi.fn(), - } - const createElementMock = vi.spyOn(document, 'createElement').mockReturnValue(mockLink as any) - const appendChildMock = vi.spyOn(document.body, 'appendChild').mockImplementation((node: Node) => { - return node - }) - - // Call the function - downloadFile({ data: blob, fileName }) - - // Assertions - expect(createObjectURLMock).toHaveBeenCalledWith(blob) - expect(createElementMock).toHaveBeenCalledWith('a') - expect(mockLink.href).toBe(mockUrl) - expect(mockLink.download).toBe(fileName) - expect(appendChildMock).toHaveBeenCalledWith(mockLink) - expect(mockLink.click).toHaveBeenCalled() - expect(mockLink.remove).toHaveBeenCalled() - expect(revokeObjectURLMock).toHaveBeenCalledWith(mockUrl) - - // Clean up mocks - vi.restoreAllMocks() - }) -}) - describe('formatNumberAbbreviated', () => { it('should return number as string when less than 1000', () => { expect(formatNumberAbbreviated(0)).toBe('0') diff --git a/web/utils/format.ts b/web/utils/format.ts index ce813d3999..d6968e0ef1 100644 --- a/web/utils/format.ts +++ b/web/utils/format.ts @@ -100,17 +100,6 @@ export const formatTime = (seconds: number) => { return `${seconds.toFixed(2)} ${units[index]}` } -export const downloadFile = ({ data, fileName }: { data: Blob, fileName: string }) => { - const url = window.URL.createObjectURL(data) - const a = document.createElement('a') - a.href = url - a.download = fileName - document.body.appendChild(a) - a.click() - a.remove() - window.URL.revokeObjectURL(url) -} - /** * Formats a number into a readable string using "k", "M", or "B" suffix. * @example From 2626e773d90c5dd71b705014187fdcd0e592325b Mon Sep 17 00:00:00 2001 From: -LAN- Date: Thu, 29 Jan 2026 16:41:09 +0800 Subject: [PATCH 09/15] chore: Set plugin schema cache TTL to 1h (#31708) --- api/.env.example | 2 +- api/configs/feature/__init__.py | 2 +- docker/.env.example | 1 + docker/docker-compose.yaml | 1 + 4 files changed, 4 insertions(+), 2 deletions(-) diff --git a/api/.env.example b/api/.env.example index c3b1474549..8bd2c706c1 100644 --- a/api/.env.example +++ b/api/.env.example @@ -617,6 +617,7 @@ PLUGIN_DAEMON_URL=http://127.0.0.1:5002 PLUGIN_REMOTE_INSTALL_PORT=5003 PLUGIN_REMOTE_INSTALL_HOST=localhost PLUGIN_MAX_PACKAGE_SIZE=15728640 +PLUGIN_MODEL_SCHEMA_CACHE_TTL=3600 INNER_API_KEY_FOR_PLUGIN=QaHbTe77CtuXmsfyhR7+vRjI/+XbV1AaFy691iy+kGDv2Jvy0/eAh8Y1 # Marketplace configuration @@ -716,4 +717,3 @@ SANDBOX_EXPIRED_RECORDS_CLEAN_GRACEFUL_PERIOD=21 SANDBOX_EXPIRED_RECORDS_CLEAN_BATCH_SIZE=1000 SANDBOX_EXPIRED_RECORDS_RETENTION_DAYS=30 SANDBOX_EXPIRED_RECORDS_CLEAN_TASK_LOCK_TTL=90000 - diff --git a/api/configs/feature/__init__.py b/api/configs/feature/__init__.py index 4343a056dd..d97e9a0440 100644 --- a/api/configs/feature/__init__.py +++ b/api/configs/feature/__init__.py @@ -245,7 +245,7 @@ class PluginConfig(BaseSettings): PLUGIN_MODEL_SCHEMA_CACHE_TTL: PositiveInt = Field( description="TTL in seconds for caching plugin model schemas in Redis", - default=24 * 60 * 60, + default=60 * 60, ) diff --git a/docker/.env.example b/docker/.env.example index b6c04fdb77..41a0205bf5 100644 --- a/docker/.env.example +++ b/docker/.env.example @@ -1375,6 +1375,7 @@ PLUGIN_DAEMON_PORT=5002 PLUGIN_DAEMON_KEY=lYkiYYT6owG+71oLerGzA7GXCgOT++6ovaezWAjpCjf+Sjc3ZtU+qUEi PLUGIN_DAEMON_URL=http://plugin_daemon:5002 PLUGIN_MAX_PACKAGE_SIZE=52428800 +PLUGIN_MODEL_SCHEMA_CACHE_TTL=3600 PLUGIN_PPROF_ENABLED=false PLUGIN_DEBUGGING_HOST=0.0.0.0 diff --git a/docker/docker-compose.yaml b/docker/docker-compose.yaml index 902ca3103c..2e97891a60 100644 --- a/docker/docker-compose.yaml +++ b/docker/docker-compose.yaml @@ -589,6 +589,7 @@ x-shared-env: &shared-api-worker-env PLUGIN_DAEMON_KEY: ${PLUGIN_DAEMON_KEY:-lYkiYYT6owG+71oLerGzA7GXCgOT++6ovaezWAjpCjf+Sjc3ZtU+qUEi} PLUGIN_DAEMON_URL: ${PLUGIN_DAEMON_URL:-http://plugin_daemon:5002} PLUGIN_MAX_PACKAGE_SIZE: ${PLUGIN_MAX_PACKAGE_SIZE:-52428800} + PLUGIN_MODEL_SCHEMA_CACHE_TTL: ${PLUGIN_MODEL_SCHEMA_CACHE_TTL:-3600} PLUGIN_PPROF_ENABLED: ${PLUGIN_PPROF_ENABLED:-false} PLUGIN_DEBUGGING_HOST: ${PLUGIN_DEBUGGING_HOST:-0.0.0.0} PLUGIN_DEBUGGING_PORT: ${PLUGIN_DEBUGGING_PORT:-5003} From 62f46fc55c434862c1418d0f86e378a1d6adf344 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E7=9B=90=E7=B2=92=20Yanli?= Date: Thu, 29 Jan 2026 16:45:07 +0800 Subject: [PATCH 10/15] chore(ty): Bootstrap ty type checking for api (#31681) --- .github/workflows/style.yml | 8 ++------ Makefile | 10 ++++++---- api/ty.toml | 24 +++++++++++++++++++++++- 3 files changed, 31 insertions(+), 11 deletions(-) diff --git a/.github/workflows/style.yml b/.github/workflows/style.yml index fdc05d1d65..cbd6edf94b 100644 --- a/.github/workflows/style.yml +++ b/.github/workflows/style.yml @@ -47,13 +47,9 @@ jobs: if: steps.changed-files.outputs.any_changed == 'true' run: uv run --directory api --dev lint-imports - - name: Run Basedpyright Checks + - name: Run Type Checks if: steps.changed-files.outputs.any_changed == 'true' - run: dev/basedpyright-check - - - name: Run Mypy Type Checks - if: steps.changed-files.outputs.any_changed == 'true' - run: uv --directory api run mypy --exclude-gitignore --exclude 'tests/' --exclude 'migrations/' --check-untyped-defs --disable-error-code=import-untyped . + run: make type-check - name: Dotenv check if: steps.changed-files.outputs.any_changed == 'true' diff --git a/Makefile b/Makefile index e92a7b1314..20cede9a5e 100644 --- a/Makefile +++ b/Makefile @@ -68,9 +68,11 @@ lint: @echo "✅ Linting complete" type-check: - @echo "📝 Running type check with basedpyright..." - @uv run --directory api --dev basedpyright - @echo "✅ Type check complete" + @echo "📝 Running type checks (basedpyright + mypy + ty)..." + @./dev/basedpyright-check $(PATH_TO_CHECK) + @uv --directory api run mypy --exclude-gitignore --exclude 'tests/' --exclude 'migrations/' --check-untyped-defs --disable-error-code=import-untyped . + @cd api && uv run ty check + @echo "✅ Type checks complete" test: @echo "🧪 Running backend unit tests..." @@ -130,7 +132,7 @@ help: @echo " make format - Format code with ruff" @echo " make check - Check code with ruff" @echo " make lint - Format, fix, and lint code (ruff, imports, dotenv)" - @echo " make type-check - Run type checking with basedpyright" + @echo " make type-check - Run type checks (basedpyright, mypy, ty)" @echo " make test - Run backend unit tests (or TARGET_TESTS=./api/tests/)" @echo "" @echo "Docker Build Targets:" diff --git a/api/ty.toml b/api/ty.toml index bb4ff5bbcf..640ed6cdee 100644 --- a/api/ty.toml +++ b/api/ty.toml @@ -1,11 +1,33 @@ [src] exclude = [ - # TODO: enable when violations fixed + # deps groups (A1/A2/B/C/D/E) + # A1: foundational runtime typing / provider plumbing + "core/mcp/session", + "core/model_runtime/model_providers", + "core/workflow/nodes/protocols.py", + "libs/gmpy2_pkcs10aep_cipher.py", + # A2: workflow engine/nodes + "core/workflow", + "core/app/workflow", + "core/helper/code_executor", + # B: app runner + prompt + "core/prompt", + "core/app/apps/base_app_runner.py", "core/app/apps/workflow_app_runner.py", + # C: services/controllers/fields/libs + "services", "controllers/console/app", "controllers/console/explore", "controllers/console/datasets", "controllers/console/workspace", + "controllers/service_api/wraps.py", + "fields/conversation_fields.py", + "libs/external_api.py", + # D: observability + integrations + "core/ops", + "extensions", + # E: vector DB integrations + "core/rag/datasource/vdb", # non-producition or generated code "migrations", "tests", From 7d1ad7e03ad008c810dfa6851729d0d9b0046ca8 Mon Sep 17 00:00:00 2001 From: CrabSAMA <40541269+CrabSAMA@users.noreply.github.com> Date: Thu, 29 Jan 2026 17:57:46 +0800 Subject: [PATCH 11/15] refactor: unified shortcut keys display using component (#31713) --- .../components/app-sidebar/toggle-button.tsx | 15 ++------------- web/app/components/app/app-publisher/index.tsx | 11 +++-------- .../components/app/create-app-modal/index.tsx | 8 +++----- .../app/create-from-dsl-modal/index.tsx | 8 +++----- .../detail/completed/common/action-buttons.tsx | 10 ++++------ .../explore/create-app-modal/index.tsx | 8 +++----- web/app/components/goto-anything/index.tsx | 12 +++--------- .../rag-pipeline-header/publisher/popup.tsx | 11 +++-------- .../components/rag-pipeline-header/run-mode.tsx | 11 ++--------- .../workflow-onboarding-modal/index.tsx | 5 ++--- web/app/components/workflow/header/run-mode.tsx | 11 ++--------- .../workflow/header/version-history-button.tsx | 14 +++----------- .../edit-card/advanced-actions.tsx | 17 +++-------------- web/app/components/workflow/shortcuts-name.tsx | 6 +++++- 14 files changed, 41 insertions(+), 106 deletions(-) diff --git a/web/app/components/app-sidebar/toggle-button.tsx b/web/app/components/app-sidebar/toggle-button.tsx index a6bdee4f78..cbfbeee452 100644 --- a/web/app/components/app-sidebar/toggle-button.tsx +++ b/web/app/components/app-sidebar/toggle-button.tsx @@ -4,7 +4,7 @@ import { useTranslation } from 'react-i18next' import { cn } from '@/utils/classnames' import Button from '../base/button' import Tooltip from '../base/tooltip' -import { getKeyboardKeyNameBySystem } from '../workflow/utils' +import ShortcutsName from '../workflow/shortcuts-name' type TooltipContentProps = { expand: boolean @@ -20,18 +20,7 @@ const TooltipContent = ({ return (
{expand ? t('sidebar.collapseSidebar', { ns: 'layout' }) : t('sidebar.expandSidebar', { ns: 'layout' })} -
- { - TOGGLE_SHORTCUT.map(key => ( - - {getKeyboardKeyNameBySystem(key)} - - )) - } -
+
) } diff --git a/web/app/components/app/app-publisher/index.tsx b/web/app/components/app/app-publisher/index.tsx index 0a026a680b..0fc364cb7e 100644 --- a/web/app/components/app/app-publisher/index.tsx +++ b/web/app/components/app/app-publisher/index.tsx @@ -49,7 +49,8 @@ import Divider from '../../base/divider' import Loading from '../../base/loading' import Toast from '../../base/toast' import Tooltip from '../../base/tooltip' -import { getKeyboardKeyCodeBySystem, getKeyboardKeyNameBySystem } from '../../workflow/utils' +import ShortcutsName from '../../workflow/shortcuts-name' +import { getKeyboardKeyCodeBySystem } from '../../workflow/utils' import AccessControl from '../app-access-control' import PublishWithMultipleModel from './publish-with-multiple-model' import SuggestedAction from './suggested-action' @@ -345,13 +346,7 @@ const AppPublisher = ({ : (
{t('common.publishUpdate', { ns: 'workflow' })} -
- {PUBLISH_SHORTCUT.map(key => ( - - {getKeyboardKeyNameBySystem(key)} - - ))} -
+
) } diff --git a/web/app/components/app/create-app-modal/index.tsx b/web/app/components/app/create-app-modal/index.tsx index e2b50cf030..66c7bce80c 100644 --- a/web/app/components/app/create-app-modal/index.tsx +++ b/web/app/components/app/create-app-modal/index.tsx @@ -1,7 +1,7 @@ 'use client' import type { AppIconSelection } from '../../base/app-icon-picker' -import { RiArrowRightLine, RiArrowRightSLine, RiCommandLine, RiCornerDownLeftLine, RiExchange2Fill } from '@remixicon/react' +import { RiArrowRightLine, RiArrowRightSLine, RiExchange2Fill } from '@remixicon/react' import { useDebounceFn, useKeyPress } from 'ahooks' import Image from 'next/image' @@ -29,6 +29,7 @@ import { getRedirection } from '@/utils/app-redirection' import { cn } from '@/utils/classnames' import { basePath } from '@/utils/var' import AppIconPicker from '../../base/app-icon-picker' +import ShortcutsName from '../../workflow/shortcuts-name' type CreateAppProps = { onSuccess: () => void @@ -269,10 +270,7 @@ function CreateApp({ onClose, onSuccess, onCreateFromTemplate, defaultAppMode }: diff --git a/web/app/components/app/create-from-dsl-modal/index.tsx b/web/app/components/app/create-from-dsl-modal/index.tsx index 838e9cc03f..04d8b1e754 100644 --- a/web/app/components/app/create-from-dsl-modal/index.tsx +++ b/web/app/components/app/create-from-dsl-modal/index.tsx @@ -1,7 +1,7 @@ 'use client' import type { MouseEventHandler } from 'react' -import { RiCloseLine, RiCommandLine, RiCornerDownLeftLine } from '@remixicon/react' +import { RiCloseLine } from '@remixicon/react' import { useDebounceFn, useKeyPress } from 'ahooks' import { noop } from 'es-toolkit/function' import { useRouter } from 'next/navigation' @@ -28,6 +28,7 @@ import { } from '@/service/apps' import { getRedirection } from '@/utils/app-redirection' import { cn } from '@/utils/classnames' +import ShortcutsName from '../../workflow/shortcuts-name' import Uploader from './uploader' type CreateFromDSLModalProps = { @@ -298,10 +299,7 @@ const CreateFromDSLModal = ({ show, onSuccess, onClose, activeTab = CreateFromDS className="gap-1" > {t('newApp.Create', { ns: 'app' })} -
- - -
+ diff --git a/web/app/components/datasets/documents/detail/completed/common/action-buttons.tsx b/web/app/components/datasets/documents/detail/completed/common/action-buttons.tsx index efb9848494..a0cbfea147 100644 --- a/web/app/components/datasets/documents/detail/completed/common/action-buttons.tsx +++ b/web/app/components/datasets/documents/detail/completed/common/action-buttons.tsx @@ -4,7 +4,8 @@ import * as React from 'react' import { useMemo } from 'react' import { useTranslation } from 'react-i18next' import Button from '@/app/components/base/button' -import { getKeyboardKeyCodeBySystem, getKeyboardKeyNameBySystem } from '@/app/components/workflow/utils' +import ShortcutsName from '@/app/components/workflow/shortcuts-name' +import { getKeyboardKeyCodeBySystem } from '@/app/components/workflow/utils' import { ChunkingMode } from '@/models/datasets' import { useDocumentContext } from '../../context' @@ -54,7 +55,7 @@ const ActionButtons: FC = ({ >
{t('operation.cancel', { ns: 'common' })} - ESC +
{(isParentChildParagraphMode && actionType === 'edit' && !isChildChunk && showRegenerationButton) @@ -76,10 +77,7 @@ const ActionButtons: FC = ({ >
{t('operation.save', { ns: 'common' })} -
- {getKeyboardKeyNameBySystem('ctrl')} - S -
+
diff --git a/web/app/components/explore/create-app-modal/index.tsx b/web/app/components/explore/create-app-modal/index.tsx index 9bffcc6c69..cfe59fb7f3 100644 --- a/web/app/components/explore/create-app-modal/index.tsx +++ b/web/app/components/explore/create-app-modal/index.tsx @@ -1,6 +1,6 @@ 'use client' import type { AppIconType } from '@/types/app' -import { RiCloseLine, RiCommandLine, RiCornerDownLeftLine } from '@remixicon/react' +import { RiCloseLine } from '@remixicon/react' import { useDebounceFn, useKeyPress } from 'ahooks' import { noop } from 'es-toolkit/function' import * as React from 'react' @@ -17,6 +17,7 @@ import AppsFull from '@/app/components/billing/apps-full-in-dialog' import { useProviderContext } from '@/context/provider-context' import { AppModeEnum } from '@/types/app' import AppIconPicker from '../../base/app-icon-picker' +import ShortcutsName from '../../workflow/shortcuts-name' export type CreateAppModalProps = { show: boolean @@ -198,10 +199,7 @@ const CreateAppModal = ({ onClick={handleSubmit} > {!isEditModal ? t('operation.create', { ns: 'common' }) : t('operation.save', { ns: 'common' })} -
- - -
+ diff --git a/web/app/components/goto-anything/index.tsx b/web/app/components/goto-anything/index.tsx index d34176e4c7..733e1d3162 100644 --- a/web/app/components/goto-anything/index.tsx +++ b/web/app/components/goto-anything/index.tsx @@ -12,7 +12,8 @@ import { useCallback, useEffect, useMemo, useRef, useState } from 'react' import { useTranslation } from 'react-i18next' import Input from '@/app/components/base/input' import Modal from '@/app/components/base/modal' -import { getKeyboardKeyCodeBySystem, isEventTargetInputArea, isMac } from '@/app/components/workflow/utils/common' +import ShortcutsName from '@/app/components/workflow/shortcuts-name' +import { getKeyboardKeyCodeBySystem, isEventTargetInputArea } from '@/app/components/workflow/utils/common' import { selectWorkflowNode } from '@/app/components/workflow/utils/node-navigation' import { useGetLanguage } from '@/context/i18n' import InstallFromMarketplace from '../plugins/install-plugin/install-from-marketplace' @@ -356,14 +357,7 @@ const GotoAnything: FC = ({ )} -
- - {isMac() ? '⌘' : 'Ctrl'} - - - K - -
+ diff --git a/web/app/components/rag-pipeline/components/rag-pipeline-header/publisher/popup.tsx b/web/app/components/rag-pipeline/components/rag-pipeline-header/publisher/popup.tsx index 0cdc9a0327..c66b293d8a 100644 --- a/web/app/components/rag-pipeline/components/rag-pipeline-header/publisher/popup.tsx +++ b/web/app/components/rag-pipeline/components/rag-pipeline-header/publisher/popup.tsx @@ -28,11 +28,12 @@ import { useToastContext } from '@/app/components/base/toast' import { useChecklistBeforePublish, } from '@/app/components/workflow/hooks' +import ShortcutsName from '@/app/components/workflow/shortcuts-name' import { useStore, useWorkflowStore, } from '@/app/components/workflow/store' -import { getKeyboardKeyCodeBySystem, getKeyboardKeyNameBySystem } from '@/app/components/workflow/utils' +import { getKeyboardKeyCodeBySystem } from '@/app/components/workflow/utils' import { useDatasetDetailContextWithSelector } from '@/context/dataset-detail' import { useDocLink } from '@/context/i18n' import { useModalContextSelector } from '@/context/modal-context' @@ -261,13 +262,7 @@ const Popup = () => { : (
{t('common.publishUpdate', { ns: 'workflow' })} -
- {PUBLISH_SHORTCUT.map(key => ( - - {getKeyboardKeyNameBySystem(key)} - - ))} -
+
) } diff --git a/web/app/components/rag-pipeline/components/rag-pipeline-header/run-mode.tsx b/web/app/components/rag-pipeline/components/rag-pipeline-header/run-mode.tsx index 00c531004f..81389e51b4 100644 --- a/web/app/components/rag-pipeline/components/rag-pipeline-header/run-mode.tsx +++ b/web/app/components/rag-pipeline/components/rag-pipeline-header/run-mode.tsx @@ -4,9 +4,9 @@ import { useCallback } from 'react' import { useTranslation } from 'react-i18next' import { StopCircle } from '@/app/components/base/icons/src/vender/line/mediaAndDevices' import { useWorkflowRun, useWorkflowStartRun } from '@/app/components/workflow/hooks' +import ShortcutsName from '@/app/components/workflow/shortcuts-name' import { useStore, useWorkflowStore } from '@/app/components/workflow/store' import { WorkflowRunningStatus } from '@/app/components/workflow/types' -import { getKeyboardKeyNameBySystem } from '@/app/components/workflow/utils' import { EVENT_WORKFLOW_STOP } from '@/app/components/workflow/variable-inspect/types' import { useEventEmitterContextContext } from '@/context/event-emitter' import { cn } from '@/utils/classnames' @@ -78,14 +78,7 @@ const RunMode = ({ )} { !isDisabled && ( -
-
- {getKeyboardKeyNameBySystem('alt')} -
-
- R -
-
+ ) } diff --git a/web/app/components/workflow-app/components/workflow-onboarding-modal/index.tsx b/web/app/components/workflow-app/components/workflow-onboarding-modal/index.tsx index c483abfb0b..16bae51246 100644 --- a/web/app/components/workflow-app/components/workflow-onboarding-modal/index.tsx +++ b/web/app/components/workflow-app/components/workflow-onboarding-modal/index.tsx @@ -7,6 +7,7 @@ import { } from 'react' import { useTranslation } from 'react-i18next' import Modal from '@/app/components/base/modal' +import ShortcutsName from '@/app/components/workflow/shortcuts-name' import { BlockEnum } from '@/app/components/workflow/types' import StartNodeSelectionPanel from './start-node-selection-panel' @@ -75,9 +76,7 @@ const WorkflowOnboardingModal: FC = ({ {isShow && (
{t('onboarding.escTip.press', { ns: 'workflow' })} - - {t('onboarding.escTip.key', { ns: 'workflow' })} - + {t('onboarding.escTip.toDismiss', { ns: 'workflow' })}
)} diff --git a/web/app/components/workflow/header/run-mode.tsx b/web/app/components/workflow/header/run-mode.tsx index 1a101bc6d2..74bc5bc80a 100644 --- a/web/app/components/workflow/header/run-mode.tsx +++ b/web/app/components/workflow/header/run-mode.tsx @@ -7,9 +7,9 @@ import { trackEvent } from '@/app/components/base/amplitude' import { StopCircle } from '@/app/components/base/icons/src/vender/line/mediaAndDevices' import { useToastContext } from '@/app/components/base/toast' import { useWorkflowRun, useWorkflowRunValidation, useWorkflowStartRun } from '@/app/components/workflow/hooks' +import ShortcutsName from '@/app/components/workflow/shortcuts-name' import { useStore } from '@/app/components/workflow/store' import { WorkflowRunningStatus } from '@/app/components/workflow/types' -import { getKeyboardKeyNameBySystem } from '@/app/components/workflow/utils' import { EVENT_WORKFLOW_STOP } from '@/app/components/workflow/variable-inspect/types' import { useEventEmitterContextContext } from '@/context/event-emitter' import { cn } from '@/utils/classnames' @@ -143,14 +143,7 @@ const RunMode = ({ > {text ?? t('common.run', { ns: 'workflow' })} -
-
- {getKeyboardKeyNameBySystem('alt')} -
-
- R -
-
+ ) diff --git a/web/app/components/workflow/header/version-history-button.tsx b/web/app/components/workflow/header/version-history-button.tsx index 32e72dc184..b98dfeea76 100644 --- a/web/app/components/workflow/header/version-history-button.tsx +++ b/web/app/components/workflow/header/version-history-button.tsx @@ -8,7 +8,8 @@ import useTheme from '@/hooks/use-theme' import { cn } from '@/utils/classnames' import Button from '../../base/button' import Tooltip from '../../base/tooltip' -import { getKeyboardKeyCodeBySystem, getKeyboardKeyNameBySystem } from '../utils' +import ShortcutsName from '../shortcuts-name' +import { getKeyboardKeyCodeBySystem } from '../utils' type VersionHistoryButtonProps = { onClick: () => Promise | unknown @@ -23,16 +24,7 @@ const PopupContent = React.memo(() => {
{t('common.versionHistory', { ns: 'workflow' })}
-
- {VERSION_HISTORY_SHORTCUT.map(key => ( - - {getKeyboardKeyNameBySystem(key)} - - ))} -
+ ) }) diff --git a/web/app/components/workflow/nodes/llm/components/json-schema-config-modal/visual-editor/edit-card/advanced-actions.tsx b/web/app/components/workflow/nodes/llm/components/json-schema-config-modal/visual-editor/edit-card/advanced-actions.tsx index 536277b9e2..8aad824008 100644 --- a/web/app/components/workflow/nodes/llm/components/json-schema-config-modal/visual-editor/edit-card/advanced-actions.tsx +++ b/web/app/components/workflow/nodes/llm/components/json-schema-config-modal/visual-editor/edit-card/advanced-actions.tsx @@ -3,7 +3,8 @@ import { useKeyPress } from 'ahooks' import * as React from 'react' import { useTranslation } from 'react-i18next' import Button from '@/app/components/base/button' -import { getKeyboardKeyCodeBySystem, getKeyboardKeyNameBySystem } from '@/app/components/workflow/utils' +import ShortcutsName from '@/app/components/workflow/shortcuts-name' +import { getKeyboardKeyCodeBySystem } from '@/app/components/workflow/utils' type AdvancedActionsProps = { isConfirmDisabled: boolean @@ -11,15 +12,6 @@ type AdvancedActionsProps = { onConfirm: () => void } -const Key = (props: { keyName: string }) => { - const { keyName } = props - return ( - - {keyName} - - ) -} - const AdvancedActions: FC = ({ isConfirmDisabled, onCancel, @@ -48,10 +40,7 @@ const AdvancedActions: FC = ({ onClick={onConfirm} > {t('operation.confirm', { ns: 'common' })} -
- - -
+ ) diff --git a/web/app/components/workflow/shortcuts-name.tsx b/web/app/components/workflow/shortcuts-name.tsx index d0ce007f61..3d21cff316 100644 --- a/web/app/components/workflow/shortcuts-name.tsx +++ b/web/app/components/workflow/shortcuts-name.tsx @@ -6,11 +6,13 @@ type ShortcutsNameProps = { keys: string[] className?: string textColor?: 'default' | 'secondary' + bgColor?: 'gray' | 'white' } const ShortcutsName = ({ keys, className, textColor = 'default', + bgColor = 'gray', }: ShortcutsNameProps) => { return (
From 25ac69afc5ac9324079be5f0d02b2a2b03dcc784 Mon Sep 17 00:00:00 2001 From: Stephen Zhou <38493346+hyoban@users.noreply.github.com> Date: Thu, 29 Jan 2026 17:58:10 +0800 Subject: [PATCH 12/15] docs: relocate frontend docs for agents and human (#31714) Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --- .agents/skills/component-refactoring/SKILL.md | 2 +- .agents/skills/frontend-testing/SKILL.md | 4 +- .../frontend-testing/references/workflow.md | 2 +- AGENTS.md | 33 +----------- CONTRIBUTING.md | 2 +- web/AGENTS.md | 6 ++- web/README.md | 2 + web/docs/lint.md | 51 +++++++++++++++++++ web/{testing/testing.md => docs/test.md} | 4 +- web/eslint-suppressions.json | 5 -- web/scripts/analyze-component.js | 4 +- 11 files changed, 69 insertions(+), 46 deletions(-) create mode 100644 web/docs/lint.md rename web/{testing/testing.md => docs/test.md} (99%) diff --git a/.agents/skills/component-refactoring/SKILL.md b/.agents/skills/component-refactoring/SKILL.md index 7006c382c8..140e0ef434 100644 --- a/.agents/skills/component-refactoring/SKILL.md +++ b/.agents/skills/component-refactoring/SKILL.md @@ -480,4 +480,4 @@ const useButtonState = () => { ### Related Skills - `frontend-testing` - For testing refactored components -- `web/testing/testing.md` - Testing specification +- `web/docs/test.md` - Testing specification diff --git a/.agents/skills/frontend-testing/SKILL.md b/.agents/skills/frontend-testing/SKILL.md index 0716c81ef7..280fcb6341 100644 --- a/.agents/skills/frontend-testing/SKILL.md +++ b/.agents/skills/frontend-testing/SKILL.md @@ -7,7 +7,7 @@ description: Generate Vitest + React Testing Library tests for Dify frontend com This skill enables Claude to generate high-quality, comprehensive frontend tests for the Dify project following established conventions and best practices. -> **⚠️ Authoritative Source**: This skill is derived from `web/testing/testing.md`. Use Vitest mock/timer APIs (`vi.*`). +> **⚠️ Authoritative Source**: This skill is derived from `web/docs/test.md`. Use Vitest mock/timer APIs (`vi.*`). ## When to Apply This Skill @@ -309,7 +309,7 @@ For more detailed information, refer to: ### Primary Specification (MUST follow) -- **`web/testing/testing.md`** - The canonical testing specification. This skill is derived from this document. +- **`web/docs/test.md`** - The canonical testing specification. This skill is derived from this document. ### Reference Examples in Codebase diff --git a/.agents/skills/frontend-testing/references/workflow.md b/.agents/skills/frontend-testing/references/workflow.md index 009c3e013b..bc4ed8285a 100644 --- a/.agents/skills/frontend-testing/references/workflow.md +++ b/.agents/skills/frontend-testing/references/workflow.md @@ -4,7 +4,7 @@ This guide defines the workflow for generating tests, especially for complex com ## Scope Clarification -This guide addresses **multi-file workflow** (how to process multiple test files). For coverage requirements within a single test file, see `web/testing/testing.md` § Coverage Goals. +This guide addresses **multi-file workflow** (how to process multiple test files). For coverage requirements within a single test file, see `web/docs/test.md` § Coverage Goals. | Scope | Rule | |-------|------| diff --git a/AGENTS.md b/AGENTS.md index 7d96ac3a6d..51fa6e4527 100644 --- a/AGENTS.md +++ b/AGENTS.md @@ -7,7 +7,7 @@ Dify is an open-source platform for developing LLM applications with an intuitiv The codebase is split into: - **Backend API** (`/api`): Python Flask application organized with Domain-Driven Design -- **Frontend Web** (`/web`): Next.js 15 application using TypeScript and React 19 +- **Frontend Web** (`/web`): Next.js application using TypeScript and React - **Docker deployment** (`/docker`): Containerized deployment configurations ## Backend Workflow @@ -18,36 +18,7 @@ The codebase is split into: ## Frontend Workflow -```bash -cd web -pnpm lint:fix -pnpm type-check:tsgo -pnpm test -``` - -### Frontend Linting - -ESLint is used for frontend code quality. Available commands: - -```bash -# Lint all files (report only) -pnpm lint - -# Lint and auto-fix issues -pnpm lint:fix - -# Lint specific files or directories -pnpm lint:fix app/components/base/button/ -pnpm lint:fix app/components/base/button/index.tsx - -# Lint quietly (errors only, no warnings) -pnpm lint:quiet - -# Check code complexity -pnpm lint:complexity -``` - -**Important**: Always run `pnpm lint:fix` before committing. The pre-commit hook runs `lint-staged` which only lints staged files. +- Read `web/AGENTS.md` for details ## Testing & Quality Practices diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 20a7d6c6f6..d7f007af67 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -77,7 +77,7 @@ How we prioritize: For setting up the frontend service, please refer to our comprehensive [guide](https://github.com/langgenius/dify/blob/main/web/README.md) in the `web/README.md` file. This document provides detailed instructions to help you set up the frontend environment properly. -**Testing**: All React components must have comprehensive test coverage. See [web/testing/testing.md](https://github.com/langgenius/dify/blob/main/web/testing/testing.md) for the canonical frontend testing guidelines and follow every requirement described there. +**Testing**: All React components must have comprehensive test coverage. See [web/docs/test.md](https://github.com/langgenius/dify/blob/main/web/docs/test.md) for the canonical frontend testing guidelines and follow every requirement described there. #### Backend diff --git a/web/AGENTS.md b/web/AGENTS.md index 7362cd51db..5dd41b8a3c 100644 --- a/web/AGENTS.md +++ b/web/AGENTS.md @@ -1,5 +1,9 @@ +## Frontend Workflow + +- Refer to the `./docs/test.md` and `./docs/lint.md` for detailed frontend workflow instructions. + ## Automated Test Generation -- Use `web/testing/testing.md` as the canonical instruction set for generating frontend automated tests. +- Use `./docs/test.md` as the canonical instruction set for generating frontend automated tests. - When proposing or saving tests, re-read that document and follow every requirement. - All frontend tests MUST also comply with the `frontend-testing` skill. Treat the skill as a mandatory constraint, not optional guidance. diff --git a/web/README.md b/web/README.md index 9c731a081a..64039709dc 100644 --- a/web/README.md +++ b/web/README.md @@ -107,6 +107,8 @@ Open [http://localhost:6006](http://localhost:6006) with your browser to see the If your IDE is VSCode, rename `web/.vscode/settings.example.json` to `web/.vscode/settings.json` for lint code setting. +Then follow the [Lint Documentation](./docs/lint.md) to lint the code. + ## Test We use [Vitest](https://vitest.dev/) and [React Testing Library](https://testing-library.com/docs/react-testing-library/intro/) for Unit Testing. diff --git a/web/docs/lint.md b/web/docs/lint.md new file mode 100644 index 0000000000..051f9e6ecd --- /dev/null +++ b/web/docs/lint.md @@ -0,0 +1,51 @@ +# Lint Guide + +We use ESLint and Typescript to maintain code quality and consistency across the project. + +## ESLint + +### Common Flags + +**File/folder targeting**: Append paths to lint specific files or directories. + +```sh +pnpm eslint [options] file.js [file.js] [dir] +``` + +**`--cache`**: Caches lint results for faster subsequent runs. Keep this enabled by default; only disable when you encounter unexpected lint results. + +**`--concurrency`**: Enables multi-threaded linting. Use `--concurrency=auto` or experiment with specific numbers to find the optimal setting for your machine. Keep this enabled when linting multiple files. + +- [ESLint multi-thread linting blog post](https://eslint.org/blog/2025/08/multithread-linting/) + +**`--fix`**: Automatically fixes auto-fixable rule violations. Always review the diff before committing to ensure no unintended changes. + +**`--quiet`**: Suppresses warnings and only shows errors. Useful when you want to reduce noise from existing issues. + +**`--suppress-all`**: Temporarily suppresses error-level violations and records them, allowing CI to pass. Treat this as an escape hatch—fix these errors when time permits. + +**`--prune-suppressions`**: Removes outdated suppressions after you've fixed the underlying errors. + +- [ESLint bulk suppressions blog post](https://eslint.org/blog/2025/04/introducing-bulk-suppressions/) + +### Type-Aware Linting + +Some ESLint rules require type information, such as [no-leaked-conditional-rendering](https://www.eslint-react.xyz/docs/rules/no-leaked-conditional-rendering). However, [typed linting via typescript-eslint](https://typescript-eslint.io/getting-started/typed-linting) is too slow for practical use, so we use [TSSLint](https://github.com/johnsoncodehk/tsslint) instead. + +```sh +pnpm lint:tss +``` + +This command lints the entire project and is intended for final verification before committing or pushing changes. + +## Type Check + +You should be able to see suggestions from TypeScript in your editor for all open files. + +However, it can be useful to run the TypeScript 7 command-line (tsgo) to type check all files: + +```sh +pnpm type-check:tsgo +``` + +Prefer using `tsgo` for type checking as it is significantly faster than the standard TypeScript compiler. Only fall back to `pnpm type-check` (which uses `tsc`) if you encounter unexpected results. diff --git a/web/testing/testing.md b/web/docs/test.md similarity index 99% rename from web/testing/testing.md rename to web/docs/test.md index 47341e445e..cac0e0e351 100644 --- a/web/testing/testing.md +++ b/web/docs/test.md @@ -360,11 +360,11 @@ describe('ComponentName', () => { let mockPortalOpenState = false vi.mock('@/app/components/base/portal-to-follow-elem', () => ({ - PortalToFollowElem: ({ children, open, ...props }: any) => { + PortalToFollowElem: ({ children, open, ...props }) => { mockPortalOpenState = open || false // Update shared state return
{children}
}, - PortalToFollowElemContent: ({ children }: any) => { + PortalToFollowElemContent: ({ children }) => { // ✅ Matches actual: returns null when open is false if (!mockPortalOpenState) return null diff --git a/web/eslint-suppressions.json b/web/eslint-suppressions.json index 6193a8ad4e..63f10d238c 100644 --- a/web/eslint-suppressions.json +++ b/web/eslint-suppressions.json @@ -4318,11 +4318,6 @@ "count": 10 } }, - "testing/testing.md": { - "ts/no-explicit-any": { - "count": 2 - } - }, "types/app.ts": { "ts/no-explicit-any": { "count": 1 diff --git a/web/scripts/analyze-component.js b/web/scripts/analyze-component.js index b09301503c..2fdff2f3d0 100755 --- a/web/scripts/analyze-component.js +++ b/web/scripts/analyze-component.js @@ -337,7 +337,7 @@ Test file under review: ${testPath} Checklist (ensure every item is addressed in your review): -- Confirm the tests satisfy all requirements listed above and in web/testing/TESTING.md. +- Confirm the tests satisfy all requirements listed above and in web/docs/test.md. - Verify Arrange → Act → Assert structure, mocks, and cleanup follow project conventions. - Ensure all detected component features (state, effects, routing, API, events, etc.) are exercised, including edge cases and error paths. - Check coverage of prop variations, null/undefined inputs, and high-priority workflows implied by usage score. @@ -382,7 +382,7 @@ Examples: # Review existing test pnpm analyze-component app/components/base/button/index.tsx --review -For complete testing guidelines, see: web/testing/testing.md +For complete testing guidelines, see: web/docs/test.md `) } From 8aeef36e2d16c9b9ba41088aee937d0348b5cbec Mon Sep 17 00:00:00 2001 From: yihong Date: Thu, 29 Jan 2026 18:17:40 +0800 Subject: [PATCH 13/15] feat: use xdist to make make test faster (#30824) Signed-off-by: yihong0618 --- .github/workflows/api-tests.yml | 1 + Makefile | 2 +- api/pyproject.toml | 1 + api/tests/unit_tests/conftest.py | 17 +++++++++++++ .../console/app/test_app_response_models.py | 7 ++++++ api/uv.lock | 24 +++++++++++++++++++ dev/pytest/pytest_unit_tests.sh | 10 ++++++-- 7 files changed, 59 insertions(+), 3 deletions(-) diff --git a/.github/workflows/api-tests.yml b/.github/workflows/api-tests.yml index 190e00d9fe..52e3272f99 100644 --- a/.github/workflows/api-tests.yml +++ b/.github/workflows/api-tests.yml @@ -72,6 +72,7 @@ jobs: OPENDAL_FS_ROOT: /tmp/dify-storage run: | uv run --project api pytest \ + -n auto \ --timeout "${PYTEST_TIMEOUT:-180}" \ api/tests/integration_tests/workflow \ api/tests/integration_tests/tools \ diff --git a/Makefile b/Makefile index 20cede9a5e..984e8676ee 100644 --- a/Makefile +++ b/Makefile @@ -80,7 +80,7 @@ test: echo "Target: $(TARGET_TESTS)"; \ uv run --project api --dev pytest $(TARGET_TESTS); \ else \ - uv run --project api --dev dev/pytest/pytest_unit_tests.sh; \ + PYTEST_XDIST_ARGS="-n auto" uv run --project api --dev dev/pytest/pytest_unit_tests.sh; \ fi @echo "✅ Tests complete" diff --git a/api/pyproject.toml b/api/pyproject.toml index 575c1434c5..af2dba6fac 100644 --- a/api/pyproject.toml +++ b/api/pyproject.toml @@ -175,6 +175,7 @@ dev = [ # "locust>=2.40.4", # Temporarily removed due to compatibility issues. Uncomment when resolved. "sseclient-py>=1.8.0", "pytest-timeout>=2.4.0", + "pytest-xdist>=3.8.0", ] ############################################################ diff --git a/api/tests/unit_tests/conftest.py b/api/tests/unit_tests/conftest.py index c5e1576186..e3c1a617f7 100644 --- a/api/tests/unit_tests/conftest.py +++ b/api/tests/unit_tests/conftest.py @@ -3,6 +3,7 @@ from unittest.mock import MagicMock, patch import pytest from flask import Flask +from sqlalchemy import create_engine # Getting the absolute path of the current file's directory ABS_PATH = os.path.dirname(os.path.abspath(__file__)) @@ -36,6 +37,7 @@ import sys sys.path.insert(0, PROJECT_DIR) +from core.db.session_factory import configure_session_factory, session_factory from extensions import ext_redis @@ -102,3 +104,18 @@ def reset_secret_key(): yield finally: dify_config.SECRET_KEY = original + + +@pytest.fixture(scope="session") +def _unit_test_engine(): + engine = create_engine("sqlite:///:memory:") + yield engine + engine.dispose() + + +@pytest.fixture(autouse=True) +def _configure_session_factory(_unit_test_engine): + try: + session_factory.get_session_maker() + except RuntimeError: + configure_session_factory(_unit_test_engine, expire_on_commit=False) diff --git a/api/tests/unit_tests/controllers/console/app/test_app_response_models.py b/api/tests/unit_tests/controllers/console/app/test_app_response_models.py index 40eb59a8f4..c557605916 100644 --- a/api/tests/unit_tests/controllers/console/app/test_app_response_models.py +++ b/api/tests/unit_tests/controllers/console/app/test_app_response_models.py @@ -31,6 +31,13 @@ def _load_app_module(): def schema_model(self, name, schema): self.models[name] = schema + return schema + + def model(self, name, model_dict=None, **kwargs): + """Register a model with the namespace (flask-restx compatibility).""" + if model_dict is not None: + self.models[name] = model_dict + return model_dict def _decorator(self, obj): return obj diff --git a/api/uv.lock b/api/uv.lock index 7808c16a8c..a3ad292168 100644 --- a/api/uv.lock +++ b/api/uv.lock @@ -1479,6 +1479,7 @@ dev = [ { name = "pytest-env" }, { name = "pytest-mock" }, { name = "pytest-timeout" }, + { name = "pytest-xdist" }, { name = "ruff" }, { name = "scipy-stubs" }, { name = "sseclient-py" }, @@ -1678,6 +1679,7 @@ dev = [ { name = "pytest-env", specifier = "~=1.1.3" }, { name = "pytest-mock", specifier = "~=3.14.0" }, { name = "pytest-timeout", specifier = ">=2.4.0" }, + { name = "pytest-xdist", specifier = ">=3.8.0" }, { name = "ruff", specifier = "~=0.14.0" }, { name = "scipy-stubs", specifier = ">=1.15.3.0" }, { name = "sseclient-py", specifier = ">=1.8.0" }, @@ -1896,6 +1898,15 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/19/d8/2a1c638d9e0aa7e269269a1a1bf423ddd94267f1a01bbe3ad03432b67dd4/eval_type_backport-0.3.0-py3-none-any.whl", hash = "sha256:975a10a0fe333c8b6260d7fdb637698c9a16c3a9e3b6eb943fee6a6f67a37fe8", size = 6061, upload-time = "2025-11-13T20:56:49.499Z" }, ] +[[package]] +name = "execnet" +version = "2.1.2" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/bf/89/780e11f9588d9e7128a3f87788354c7946a9cbb1401ad38a48c4db9a4f07/execnet-2.1.2.tar.gz", hash = "sha256:63d83bfdd9a23e35b9c6a3261412324f964c2ec8dcd8d3c6916ee9373e0befcd", size = 166622, upload-time = "2025-11-12T09:56:37.75Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/ab/84/02fc1827e8cdded4aa65baef11296a9bbe595c474f0d6d758af082d849fd/execnet-2.1.2-py3-none-any.whl", hash = "sha256:67fba928dd5a544b783f6056f449e5e3931a5c378b128bc18501f7ea79e296ec", size = 40708, upload-time = "2025-11-12T09:56:36.333Z" }, +] + [[package]] name = "faker" version = "38.2.0" @@ -5141,6 +5152,19 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/fa/b6/3127540ecdf1464a00e5a01ee60a1b09175f6913f0644ac748494d9c4b21/pytest_timeout-2.4.0-py3-none-any.whl", hash = "sha256:c42667e5cdadb151aeb5b26d114aff6bdf5a907f176a007a30b940d3d865b5c2", size = 14382, upload-time = "2025-05-05T19:44:33.502Z" }, ] +[[package]] +name = "pytest-xdist" +version = "3.8.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "execnet" }, + { name = "pytest" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/78/b4/439b179d1ff526791eb921115fca8e44e596a13efeda518b9d845a619450/pytest_xdist-3.8.0.tar.gz", hash = "sha256:7e578125ec9bc6050861aa93f2d59f1d8d085595d6551c2c90b6f4fad8d3a9f1", size = 88069, upload-time = "2025-07-01T13:30:59.346Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/ca/31/d4e37e9e550c2b92a9cbc2e4d0b7420a27224968580b5a447f420847c975/pytest_xdist-3.8.0-py3-none-any.whl", hash = "sha256:202ca578cfeb7370784a8c33d6d05bc6e13b4f25b5053c30a152269fd10f0b88", size = 46396, upload-time = "2025-07-01T13:30:56.632Z" }, +] + [[package]] name = "python-calamine" version = "0.5.4" diff --git a/dev/pytest/pytest_unit_tests.sh b/dev/pytest/pytest_unit_tests.sh index 496cb40952..7c39a48bf4 100755 --- a/dev/pytest/pytest_unit_tests.sh +++ b/dev/pytest/pytest_unit_tests.sh @@ -5,6 +5,12 @@ SCRIPT_DIR="$(dirname "$(realpath "$0")")" cd "$SCRIPT_DIR/../.." PYTEST_TIMEOUT="${PYTEST_TIMEOUT:-20}" +PYTEST_XDIST_ARGS="${PYTEST_XDIST_ARGS:--n auto}" -# libs -pytest --timeout "${PYTEST_TIMEOUT}" api/tests/unit_tests +# Run most tests in parallel (excluding controllers which have import conflicts with xdist) +# Controller tests have module-level side effects (Flask route registration) that cause +# race conditions when imported concurrently by multiple pytest-xdist workers. +pytest --timeout "${PYTEST_TIMEOUT}" ${PYTEST_XDIST_ARGS} api/tests/unit_tests --ignore=api/tests/unit_tests/controllers + +# Run controller tests sequentially to avoid import race conditions +pytest --timeout "${PYTEST_TIMEOUT}" api/tests/unit_tests/controllers From c27df884170b318b05ddd19b5c55a959f2649c53 Mon Sep 17 00:00:00 2001 From: Joel Date: Thu, 29 Jan 2026 19:40:47 +0800 Subject: [PATCH 14/15] feat: try app support review (#31716) --- web/app/components/apps/index.tsx | 1 + web/app/components/explore/app-card/index.tsx | 12 +++++------- web/app/components/explore/app-list/index.tsx | 1 + web/app/components/explore/try-app/index.tsx | 16 +++++++++++++++- web/app/components/explore/try-app/tab.tsx | 4 +++- web/i18n/en-US/explore.json | 2 +- 6 files changed, 26 insertions(+), 10 deletions(-) diff --git a/web/app/components/apps/index.tsx b/web/app/components/apps/index.tsx index 255bfbf9c5..3be8492489 100644 --- a/web/app/components/apps/index.tsx +++ b/web/app/components/apps/index.tsx @@ -105,6 +105,7 @@ const Apps = () => { {isShowTryAppPanel && ( {isExplore && (canCreate || isTrialApp) && (