π¦ ClawHub
2026-3-22dataset
by @redredrrred
Use for RAGFlow dataset tasks: create, list, inspect, update, or delete datasets; upload, list, update, or delete documents; start or stop parsing; check par...
TERMINAL
clawhub install 2026-3-22datasetπ About This Skill
name: ragflow-dataset-ingest description: "Use for RAGFlow dataset tasks: create, list, inspect, update, or delete datasets; upload, list, update, or delete documents; start or stop parsing; check parse status; retrieve chunks with
search.py; and list configured models."
metadata:
openclaw:
requires:
env:
- RAGFLOW_API_URL
- RAGFLOW_API_KEY
bins:
- python3
primaryEnv: RAGFLOW_API_KEY
RAGFlow Dataset And Retrieval
Use only the bundled scripts in scripts/.
Prefer --json so returned fields can be relayed exactly.
Follow reference.md for all user-facing output.
Use This Skill When
Core Workflow
1. Resolve the target dataset or document IDs first.
2. Run the matching script from scripts/.
3. Use --json unless a script only needs a simple text response.
4. Return API fields exactly; do not guess missing details.
Common commands:
python3 scripts/datasets.py list --json
python3 scripts/datasets.py info DATASET_ID --json
python3 scripts/datasets.py create "Example Dataset" --description "Quarterly reports" --json
python3 scripts/update_dataset.py DATASET_ID --name "Updated Dataset" --json
python3 scripts/upload.py DATASET_ID /path/to/file.pdf --json
python3 scripts/upload.py list DATASET_ID --json
python3 scripts/update_document.py DATASET_ID DOC_ID --name "Updated Document" --json
python3 scripts/parse.py DATASET_ID DOC_ID1 [DOC_ID2 ...] --json
python3 scripts/stop_parse_documents.py DATASET_ID DOC_ID1 [DOC_ID2 ...] --json
python3 scripts/parse_status.py DATASET_ID --json
python3 scripts/search.py "query" --json
python3 scripts/search.py "query" DATASET_ID --json
python3 scripts/search.py --dataset-ids DATASET_ID1,DATASET_ID2 --doc-ids DOC_ID1,DOC_ID2 "query" --json
python3 scripts/search.py --retrieval-test --kb-id DATASET_ID "query" --json
python3 scripts/list_models.py --json
Guardrails
parse.py returns immediately after the start request; use parse_status.py for progress.parse_status.py on the most specific scope available:--doc-ids
- no dataset specified: list datasets first, then aggregate status across datasets
progress_msg, surface it directly. For FAIL, treat it as the primary error detail.--retrieval-test only for single-dataset debugging or when the user explicitly asks for that endpoint.Output Rules
reference.md.api_error, error, message, and related fields exactly as returned.