langgenius/dify · error · NotFound

not_found

not_found

Error message

Some documents not found: {list(missing_ids)}

What it means

NotFound raised at datasets_document.py:1710 when DocumentService.get_documents_by_ids returns fewer rows than the number of IDs submitted in document_list. The difference set (requested minus found) is computed and reported as missing_ids. This guards against generating summaries for documents that do not exist or do not belong to the dataset.

Source

Thrown at api/controllers/console/datasets/datasets_document.py:1710

        if dataset.indexing_technique != IndexTechniqueType.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(
            DatasetRefService.create_dataset_ref(dataset), document_list, session
        )

        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)}")

        # Update need_summary to True for documents that don't have it set
        # This handles the case where documents were created when summary_index_setting was disabled
        documents_to_update = [doc for doc in documents if not doc.need_summary and doc.doc_form != "qa_model"]

        if documents_to_update:
            document_ids_to_update = [str(doc.id) for doc in documents_to_update]
            DocumentService.update_documents_need_summary(
                dataset_id=dataset_id_str,
                document_ids=document_ids_to_update,
                session=session,
                need_summary=True,
            )

        # 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":

View on GitHub (pinned to ef8544b173)

Solutions

1. Intersect the requested document_list with the current document set returned by GET /datasets/{id}/documents before submitting.
2. Parse missing_ids from the 404 response and re-issue only the still-valid IDs.
3. Confirm each ID is a UUID that belongs to the same dataset_id used in the path.

Example fix

# before
client.post(f'/datasets/{dataset_id}/generate-summary', json={'document_list': requested_ids})

# after
valid = {d['id'] for page in itertools.count(1) for d in client.get(f'/datasets/{dataset_id}/documents', params={'page': page}).json()['data']}
client.post(f'/datasets/{dataset_id}/generate-summary', json={'document_list': [i for i in requested_ids if i in valid]})

existing = {d['id'] for d in client.get(f'/console/api/datasets/{dataset_id}/documents').json()['data']}
safe = [i for i in document_list if i in existing]
assert len(safe) == len(document_list), f'missing: {set(document_list) - existing}'
client.post(f'/datasets/{dataset_id}/generate-summary', json={'document_list': safe})

def all_belong(ids: list[str], known: set[str]) -> bool:
    return set(ids).issubset(known)

try:
    client.post(...)
except HTTPError as e:
    if e.response.status_code == 404:
        missing = e.response.json().get('missing_ids')
        document_list = [i for i in document_list if i not in set(missing)]

When it happens

Trigger: POST generate-summary with a document_list containing IDs that are deleted, belong to a different dataset, or are malformed. The ref-based lookup (DatasetRefService.create_dataset_ref) scopes the query to the dataset, so cross-dataset IDs count as missing.

Common situations: Stale document IDs cached on the client after a document was deleted; copy-paste error mixing IDs from two datasets; race where a document is purged between the UI listing documents and the summary request; UUID typos.

Related errors

• invalid_param
• not_found
• Data source binding not found.
• Credential not found.
• Dataset not found.

AI-assisted analysis of langgenius/dify@ef8544b173 (2026-08-12). Data as JSON: /api/errors/0586497e7ed9a199. Report an issue: GitHub.