{"record":{"id":"fb5e1fd6f4df0449","repo":"HKUDS/DeepTutor","slug":"graphrag-indexing-failed-detail","errorCode":null,"errorMessage":"GraphRAG indexing failed: {detail}","messagePattern":"GraphRAG indexing failed: (.+?)","errorType":"exception","errorClass":"RuntimeError","httpStatus":null,"severity":"critical","filePath":"deeptutor/services/rag/pipelines/graphrag/engine.py","lineNumber":350,"sourceCode":"        config=config,\n        method=IndexingMethod.Standard,\n        is_update_run=is_update,\n    )\n    errors = [r for r in results if getattr(r, \"error\", None) is not None]\n    if errors:\n        for result in errors:\n            error = getattr(result, \"error\", None)\n            if isinstance(error, BaseException):\n                workflow = str(getattr(result, \"workflow\", \"\") or \"\").lower()\n                classified = (\n                    classify_embedding_error(error)\n                    if \"embed\" in workflow\n                    else classify_model_error(error)\n                )\n                if classified is not None:\n                    raise classified from error\n        detail = \"; \".join(f\"{r.workflow}: {r.error}\" for r in errors[:3])\n        raise RuntimeError(f\"GraphRAG indexing failed: {detail}\")\n\n\nasync def _resolve_outputs(config, names: list[str], optional: list[str]) -> dict[str, Any]:\n    \"\"\"Load the requested output parquet tables as DataFrames (mirrors the CLI).\"\"\"\n    from graphrag.data_model.data_reader import DataReader\n    from graphrag_storage import create_storage\n    from graphrag_storage.tables.table_provider_factory import create_table_provider\n\n    storage_obj = create_storage(config.output_storage)\n    table_provider = create_table_provider(config.table_provider, storage=storage_obj)\n    reader = DataReader(table_provider)\n\n    frames: dict[str, Any] = {}\n    for name in names:\n        frames[name] = await getattr(reader, name)()\n    for name in optional:\n        frames[name] = await getattr(reader, name)() if await table_provider.has(name) else None\n    return frames","sourceCodeStart":332,"sourceCodeEnd":368,"githubUrl":"https://github.com/HKUDS/DeepTutor/blob/3e82f130422a813cdd73c10b21a44e9325f5821a/deeptutor/services/rag/pipelines/graphrag/engine.py#L332-L368","documentation":"Generic RuntimeError from _build_impl: the GraphRAG indexing run itself failed; the message aggregates up to the first three workflow errors as 'workflow: error' detail strings after unclassifiable errors (model errors that classify_model_error / embedding classification couldn't map).","triggerScenarios":"Running build() for a GraphRAG KB where one or more GraphRAG workflows (e.g. extract_graph, embed_text) errored during the indexing pipeline, with causes outside the recognized error taxonomy.","commonSituations":"Mid-index API rate limits/outages, malformed source documents crashing a workflow, GraphRAG library version mismatches, disk/full parquet write failures in the output dir.","solutions":["Read the joined detail to see which workflow and underlying error failed, then address it directly.","Retry the build after fixing rate limits/network/storage issues; indexing resumes over outputs.","Check graphrag logs/output dir for full per-workflow errors beyond the first three.","Align the installed graphrag package version with what DeepTutor's adapter expects."],"exampleFix":null,"handlingStrategy":"try-catch","validationCode":null,"typeGuard":null,"tryCatchPattern":"try:\n    await build(root_dir)\nexcept RuntimeError as e:\n    detail = str(e)\n    if not detail.startswith(\"GraphRAG indexing failed:\"):\n        raise\n    persist_partial_failure(detail); notify_user(detail)","preventionTips":["Run both preflights before build.","Keep graphrag package version pinned to what the adapter supports.","Monitor rate limits during long indexing runs."],"tags":["graphrag","indexing","pipeline-failure"],"backgroundTag":"rag-indexing-failed","analyzedSha":"3e82f130422a813cdd73c10b21a44e9325f5821a","analyzedAt":"2026-08-27T06:57:25.364Z","schemaVersion":2},"datasetVersion":"2026-08-27T08:17:20.692Z"}