{"record":{"id":"6679a9ba73fc0969","repo":"microsoft/graphrag","slug":"no-community-reports-available-please-provide-a-l","errorCode":null,"errorMessage":"No community reports available. Please provide a list of reports.","messagePattern":"No community reports available\\. Please provide a list of reports\\.","errorType":"validation","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"packages/graphrag/graphrag/query/structured_search/drift_search/drift_context.py","lineNumber":193,"sourceCode":"        ----\n        query : str\n            Search query string.\n\n        Returns\n        -------\n        pd.DataFrame: Top-k most similar documents.\n        dict[str, int]: Number of LLM calls, and prompts and output tokens.\n\n        Raises\n        ------\n        ValueError: If no community reports are available, or embeddings\n        are incompatible.\n        \"\"\"\n        if self.reports is None:\n            missing_reports_error = (\n                \"No community reports available. Please provide a list of reports.\"\n            )\n            raise ValueError(missing_reports_error)\n\n        query_processor = PrimerQueryProcessor(\n            chat_model=self.model,\n            text_embedder=self.text_embedder,\n            tokenizer=self.tokenizer,\n            reports=self.reports,\n        )\n\n        query_embedding, token_ct = await query_processor(query)\n\n        report_df = self.convert_reports_to_df(self.reports)\n\n        # Check compatibility between query embedding and document embeddings\n        if not self.check_query_doc_encodings(\n            query_embedding, report_df[\"full_content_embedding\"].iloc[0]\n        ):\n            error_message = (\n                \"Query and document embeddings are not compatible. \"","sourceCodeStart":175,"sourceCodeEnd":211,"githubUrl":"https://github.com/microsoft/graphrag/blob/f40e9a26ce62ba0b3fef8837d24aafdcc6e6c704/packages/graphrag/graphrag/query/structured_search/drift_search/drift_context.py#L175-L211","documentation":"DRIFT search requires a set of community reports to prime its query decomposition. When DriftContext.build_context is called with self.reports set to None (no community reports loaded or passed), it raises this ValueError before doing any work. The reports come from the communities output of an indexing run, so their absence means the search was configured without them or the index is incomplete.","triggerScenarios":"Calling DriftSearch.search (which invokes DriftContext.build_context) after constructing the context with reports=None, e.g. loading a DRIFT search object from an index directory that lacks a create_final_community_reports.parquet (or .csv), or manually building DriftContext without passing community_reports.","commonSituations":"Running local DRIFT query against an index produced with community reporting disabled (--skip-community-reporting or community level settings that yield no reports), pointing --root at the wrong/wrongly-completed output folder, or a partially failed indexing run that never wrote the community report artifacts.","solutions":["Check that your indexing run produced communities output (output/create_final_community_reports.parquet) and that it is non-empty","Verify the index directory you pass to the DRIFT query loader actually contains community report files and that you use the correct --root path","Re-run the indexing pipeline with community generation enabled if reports were skipped or empty","If constructing DriftContext manually, pass a valid community_reports DataFrame instead of None"],"exampleFix":"# before\ncontext = DriftContext(reports=None, ...)  # or index missing community reports\n\n# after\ncommunity_reports = pd.read_parquet(\"output/create_final_community_reports.parquet\")\ncontext = DriftContext(reports=community_reports, ...)","handlingStrategy":"validation","validationCode":"import pandas as pd\nfrom pathlib import Path\n\nreport_path = Path(\"output/create_final_community_reports.parquet\")\nassert report_path.exists(), f\"Missing {report_path}; re-run indexing with community reports enabled\"\nreports = pd.read_parquet(report_path)\nassert len(reports) > 0 and \"full_content\" in reports.columns, \"Community reports are empty or malformed\"","typeGuard":null,"tryCatchPattern":null,"preventionTips":["Always verify the index output directory contains community report artifacts before running DRIFT query","Keep community generation enabled in your indexing settings when you plan to use DRIFT search","Fail fast in your pipeline setup by loading and validating the reports DataFrame explicitly"],"tags":["graphrag","drift-search","community-reports","missing-data"],"backgroundTag":"missing-required-input","analyzedSha":"f40e9a26ce62ba0b3fef8837d24aafdcc6e6c704","analyzedAt":"2026-08-27T11:16:29.677Z","schemaVersion":2},"datasetVersion":"2026-08-27T13:17:12.746Z"}