dify

dify/api/tasks/clean_dataset_task.py

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+import logging
+import time
+
+import click
+from celery import shared_task
+from sqlalchemy import select
+
+from core.rag.index_processor.index_processor_factory import IndexProcessorFactory
+from core.tools.utils.web_reader_tool import get_image_upload_file_ids
+from extensions.ext_database import db
+from extensions.ext_storage import storage
+from models.dataset import (
+    AppDatasetJoin,
+    Dataset,
+    DatasetMetadata,
+    DatasetMetadataBinding,
+    DatasetProcessRule,
+    DatasetQuery,
+    Document,
+    DocumentSegment,
+)
+from models.model import UploadFile
+
+logger = logging.getLogger(__name__)
+
+
+# Add import statement for ValueError
+@shared_task(queue="dataset")
+def clean_dataset_task(
+    dataset_id: str,
+    tenant_id: str,
+    indexing_technique: str,
+    index_struct: str,
+    collection_binding_id: str,
+    doc_form: str,
+):
+    """
+    Clean dataset when dataset deleted.
+    :param dataset_id: dataset id
+    :param tenant_id: tenant id
+    :param indexing_technique: indexing technique
+    :param index_struct: index struct dict
+    :param collection_binding_id: collection binding id
+    :param doc_form: dataset form
+
+    Usage: clean_dataset_task.delay(dataset_id, tenant_id, indexing_technique, index_struct)
+    """
+    logger.info(click.style(f"Start clean dataset when dataset deleted: {dataset_id}", fg="green"))
+    start_at = time.perf_counter()
+
+    try:
+        dataset = Dataset(
+            id=dataset_id,
+            tenant_id=tenant_id,
+            indexing_technique=indexing_technique,
+            index_struct=index_struct,
+            collection_binding_id=collection_binding_id,
+        )
+        documents = db.session.scalars(select(Document).where(Document.dataset_id == dataset_id)).all()
+        segments = db.session.scalars(select(DocumentSegment).where(DocumentSegment.dataset_id == dataset_id)).all()
+
+        # Enhanced validation: Check if doc_form is None, empty string, or contains only whitespace
+        # This ensures all invalid doc_form values are properly handled
+        if doc_form is None or (isinstance(doc_form, str) and not doc_form.strip()):
+            # Use default paragraph index type for empty/invalid datasets to enable vector database cleanup
+            from core.rag.index_processor.constant.index_type import IndexType
+
+            doc_form = IndexType.PARAGRAPH_INDEX
+            logger.info(
+                click.style(f"Invalid doc_form detected, using default index type for cleanup: {doc_form}", fg="yellow")
+            )
+
+        # Add exception handling around IndexProcessorFactory.clean() to prevent single point of failure
+        # This ensures Document/Segment deletion can continue even if vector database cleanup fails
+        try:
+            index_processor = IndexProcessorFactory(doc_form).init_index_processor()
+            index_processor.clean(dataset, None, with_keywords=True, delete_child_chunks=True)
+            logger.info(click.style(f"Successfully cleaned vector database for dataset: {dataset_id}", fg="green"))
+        except Exception:
+            logger.exception(click.style(f"Failed to clean vector database for dataset {dataset_id}", fg="red"))
+            # Continue with document and segment deletion even if vector cleanup fails
+            logger.info(
+                click.style(f"Continuing with document and segment deletion for dataset: {dataset_id}", fg="yellow")
+            )
+
+        if documents is None or len(documents) == 0:
+            logger.info(click.style(f"No documents found for dataset: {dataset_id}", fg="green"))
+        else:
+            logger.info(click.style(f"Cleaning documents for dataset: {dataset_id}", fg="green"))
+
+            for document in documents:
+                db.session.delete(document)
+
+            for segment in segments:
+                image_upload_file_ids = get_image_upload_file_ids(segment.content)
+                for upload_file_id in image_upload_file_ids:
+                    image_file = db.session.query(UploadFile).where(UploadFile.id == upload_file_id).first()
+                    if image_file is None:
+                        continue
+                    try:
+                        storage.delete(image_file.key)
+                    except Exception:
+                        logger.exception(
+                            "Delete image_files failed when storage deleted, \
+                                          image_upload_file_is: %s",
+                            upload_file_id,
+                        )
+                    db.session.delete(image_file)
+                db.session.delete(segment)
+
+        db.session.query(DatasetProcessRule).where(DatasetProcessRule.dataset_id == dataset_id).delete()
+        db.session.query(DatasetQuery).where(DatasetQuery.dataset_id == dataset_id).delete()
+        db.session.query(AppDatasetJoin).where(AppDatasetJoin.dataset_id == dataset_id).delete()
+        # delete dataset metadata
+        db.session.query(DatasetMetadata).where(DatasetMetadata.dataset_id == dataset_id).delete()
+        db.session.query(DatasetMetadataBinding).where(DatasetMetadataBinding.dataset_id == dataset_id).delete()
+        # delete files
+        if documents:
+            for document in documents:
+                try:
+                    if document.data_source_type == "upload_file":
+                        if document.data_source_info:
+                            data_source_info = document.data_source_info_dict
+                            if data_source_info and "upload_file_id" in data_source_info:
+                                file_id = data_source_info["upload_file_id"]
+                                file = (
+                                    db.session.query(UploadFile)
+                                    .where(UploadFile.tenant_id == document.tenant_id, UploadFile.id == file_id)
+                                    .first()
+                                )
+                                if not file:
+                                    continue
+                                storage.delete(file.key)
+                                db.session.delete(file)
+                except Exception:
+                    continue
+
+        db.session.commit()
+        end_at = time.perf_counter()
+        logger.info(
+            click.style(f"Cleaned dataset when dataset deleted: {dataset_id} latency: {end_at - start_at}", fg="green")
+        )
+    except Exception:
+        # Add rollback to prevent dirty session state in case of exceptions
+        # This ensures the database session is properly cleaned up
+        try:
+            db.session.rollback()
+            logger.info(click.style(f"Rolled back database session for dataset: {dataset_id}", fg="yellow"))
+        except Exception:
+            logger.exception("Failed to rollback database session")
+
+        logger.exception("Cleaned dataset when dataset deleted failed")
+    finally:
+        db.session.close()