ragflow-skill-pythonUse for RAGFlow dataset tasks: create, list, inspect, update, or delete datasets; upload, list, update, or delete documents; start or stop parsing; check par...
Install via ClawdBot CLI:
clawdbot install liberalchang/ragflow-skill-pythonGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Calls external URL not in known-safe list
http://www.apache.org/licenses/LICENSE-2.0Audited Apr 19, 2026 · audit v1.0
Generated Sep 29, 2026
A company uploads internal policy documents, onboarding guides, and meeting notes into RAGFlow datasets, parses them, and lets employees query across all sources with chunk-level retrieval. This replaces manual document hunting and delivers cited answers from a unified knowledge repository.
A law firm ingests client contracts and regulatory filings into RAGFlow, parses them for semantic indexing, and uses search.py to retrieve relevant clauses and precedents. Paralegals and attorneys query specific clauses across datasets to accelerate due diligence and research.
A SaaS company uploads product documentation, troubleshooting guides, and historical support tickets to RAGFlow, then connects an AI assistant to search.py for grounded answers. Support agents retrieve exact chunks to resolve tickets faster without fabricating details.
A research team batch-uploads PDF papers into RAGFlow datasets, starts parsing to extract structured chunks, and queries between multiple datasets using --dataset-ids. Researchers compare findings accross collections and retrieve passages for literature reviews and grant writing.
An analyst uploads quarterly earnings reports and SEC filings into RAGFlow, parses them, and searches across document IDs to extract specific figures and management commentary. This enables fast trend analysis and fact-checking without manually skimming hundreds of pages.
A subscription platform built on RAGFlow scripts that lets businesses upload, parse, and semantically search their document collections through a web interface and API. Tiered pricing based on document volume, storage, and query limits.
A consultancy that deploys RAGFlow-based retrieval systems for clients, handling dataset design, document migration, parsing pipelines, and custom search integrations. Sells packaged implementation projects and ongoing support retainers.
A domain-specific application for legal, healthcare, or finance that wraps RAGFlow into a tailored workflow with pre-configured datasets, connectors, and compliance controls. Customers pay per seat or per workspace for industry-specific retrieval.
💬 Integration Tip
Ensure RAGFLOW_API_URL and RAGFLOW_API_KEY are set as environment variables before running any script, and always validate dataset or document IDs via list/info commands before performing destructive operations. Use `--json` output consistently and follow reference.md for exact field relay, especially for parse status error messages like progress_msg or FAIL.
Scored Aug 30, 2026
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