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name: vector-corpus description: "Ground STORM article runs on a user CSV or local corpus with VectorRM and Qdrant, including schema validation, offline/online vector stores, device choices, and STORMWikiRunner integration." disable-model-invocation: true metadata: disco-role: operating license: MIT

vector-corpus

Use this sub-skill when the task asks to run or prepare STORM over a user-owned CSV/local corpus rather than Internet search. It covers VectorRM, Qdrant offline/online stores, CSV validation, corpus chunking, embedding device choices, and the handoff into STORMWikiRunner.

Route here when

• The user has a CSV corpus with content and url columns and wants STORM grounded on those rows.
• The user needs to create or update a Qdrant collection for VectorRM from CSV documents.
• The user already has a local Qdrant directory or Qdrant Cloud URL and needs VectorRM to retrieve from it.
• The user asks about VectorRM.__init__, init_offline_vector_db, init_online_vector_db, get_vector_count, forward, or QdrantVectorStoreManager.create_or_update_vector_store.

Route elsewhere

• Internet-search STORM workflows, search retriever selection, stage resume, and article output inspection belong in ../storm-wiki/.
• Co-STORM collaborative discourse, warm start, turn-taking, mind maps, and report generation belong in ../co-storm/.

Bundled references

• references/workflows.md: end-to-end commands for validating CSVs, creating offline/online Qdrant stores, and plugging VectorRM into STORM.
• references/data-formats.md: exact CSV schema, chunking arguments, and validation symptoms.
• references/api-reference.md: API signatures and behavior for VectorRM and QdrantVectorStoreManager.
• references/troubleshooting.md: symptoms, causes, and fixes for CSV, Qdrant, embedding, device, and STORM runner issues.

Bundled scripts

• scripts/validate_vector_corpus_csv.py: standard-library CSV schema checker. Use --strict-unique-url before indexing.
• scripts/process_kaggle_arxiv_abstract_dataset.py: converts Kaggle arXiv abstracts CSVs into the VectorRM CSV schema.
• scripts/run_storm_wiki_with_vector_rm.py: safe helper for corpus-grounded STORM with current LitellmModel; supports --dry-run and --validate-only without embedding, Qdrant, LLM, or network calls.

Minimum safe workflow

1. Validate the corpus with python scripts/validate_vector_corpus_csv.py --input-path corpus.csv --strict-unique-url.
2. Choose Qdrant mode:
   • offline: local filesystem directory with --vector-db-mode offline --offline-vector-db-dir ./vector_store;
   • online: Qdrant URL plus QDRANT_API_KEY with --vector-db-mode online --online-vector-db-url https://....
3. Start with --device cpu; use cuda or mps only for embedding acceleration when available.
4. Use --dry-run or --validate-only first, then run the full helper with explicit STORM stage flags.

The runtime scripts assume the public knowledge-storm package is installed for full runs. Help, dry-run, and validate-only paths avoid package imports where possible.