How to Set Up OpenClaw RAG Storage

What Is OpenClaw RAG Storage?

OpenClaw RAG storage indexes documents so agents can pull relevant sections for responses. Fast.io workspaces handle indexing when you enable Intelligence Mode. Just upload files. They process and become searchable.

No need for a separate vector database. Install the ClawHub skill (npx clawhub@latest install fast-io) to connect. Queries include citations to pages or sections.

Set up RAG pipelines that fetch context from workspaces. Good for knowledge bases, report analysis, and code reviews.

Practical example: Summarize key risks from multiple compliance docs with page citations. Constraint: Enable intelligence mode first. Outcome: Audit time drops .

Practical example: Query sales reports across multiple PDFs; gets cited summaries in seconds. Constraint: Limit to one workspace per query. Outcome: Cuts research from hours to minutes.

Why Fast.io for OpenClaw RAG Pipelines?

Fast.io workspaces support semantic search across files. Upload PDFs, docs, or code. Files index automatically.

Key benefits:

• No vector DB: Indexing runs automatically, no DevOps work needed. Agents storage.
• Citations: Links to pages, sections, or timestamps.
• Free tier: 50 GB, 5k credits/mo, 3 workspaces. Pricing.
• 14 tools: Orgs, workspaces, uploads, AI chat, shares. Docs.
• URL import: Drive/Dropbox without local files.
• Locks/webhooks: Safe for multiple agents.

Other storage services handle basic files. Fast.io adds RAG too.

Practical example: Summarize key risks from multiple compliance docs with page citations. Constraint: Enable intelligence mode first. Outcome: Audit time drops .

Practical example: Query sales reports across multiple PDFs; gets cited summaries in seconds. Constraint: Limit to one workspace per query. Outcome: Cuts research from hours to minutes.

Install Fast.io ClawHub Skill

Run npx clawhub@latest install fast-io in your terminal. This adds 14 tools to OpenClaw.

The first use opens a browser for authentication. Create a free agent account or use your API key.

Tools manage workspaces, uploads, AI chat, shares. No more setup after that.

Example installation output:

      $ npx clawhub@latest install fast-io
      Installed 14 tools: org.create, workspace.create, upload.web-import, ai.chat-create, etc.
      ```

First tool use opens browser for auth. Sign up for free agent account (no CC) or use existing API key.

Practical example: Run install command; agents manage files via natural language. Constraint: Initial browser auth required. Outcome: Eliminates manual file handling.

Create RAG-Enabled Workspace

Have agents run org create for an org, then org create-workspace for the workspace.

Enable intelligence mode. Upload files using upload web-import (for URLs) or directly.

Look for ai_state: ready on files to confirm indexing.

Example workflow:

1. Create workspace "ProjectRAG"
2. Enable intelligence
3. Import docs from Drive/Dropbox
4. Query: "Summarize contracts"

Practical example: Summarize key risks from multiple compliance docs with page citations. Constraint: Enable intelligence mode first. Outcome: Audit time drops .

Log workspace IDs and tool calls for easy replication and debugging.

Practical example: Query sales reports across multiple PDFs; gets cited summaries in seconds. Constraint: Limit to one workspace per query. Outcome: Cuts research from hours to minutes.

Query Documents in OpenClaw

Use ai chat-create with chat_with_files and folders_scope for RAG.

Scope to a workspace or folder. Answers cite sources.

Add follow-ups with ai message-send. Check with ai message-read.

Example: Scope root, ask "Key risks in reports?"

Practical example: Summarize key risks from multiple compliance docs with page citations. Constraint: Enable intelligence mode first. Outcome: Audit time drops .

Log workspace IDs and tool calls for easy replication and debugging.

Validate with test documents before scaling to production data.

Practical example: Query sales reports across multiple PDFs; gets cited summaries in seconds. Constraint: Limit to one workspace per query. Outcome: Cuts research from hours to minutes.

Teams should validate this approach in a small test path first, then standardize it across environments once metrics and outcomes are stable.

Advanced RAG Pipelines

Chain queries: summarize a folder, extract entities, generate a report.

Multi-agent setups: one indexes, another queries.

Webhooks for change notifications. Locks avoid conflicts.

Ownership transfer hands workspaces to humans.

Practical example: Summarize key risks from multiple compliance docs with page citations. Constraint: Enable intelligence mode first. Outcome: Audit time drops .

Log workspace IDs and tool calls for easy replication and debugging.

Validate with test documents before scaling to production data.

Practical example: Query sales reports across multiple PDFs; gets cited summaries in seconds. Constraint: Limit to one workspace per query. Outcome: Cuts research from hours to minutes.

Teams should validate this approach in a small test path first, then standardize it across environments once metrics and outcomes are stable.

Best Practices

• Limit scopes for faster results
• Track credit usage
• Use notes to ground responses
• Version files to track history

Practical example: Summarize key risks from multiple compliance docs with page citations. Constraint: Enable intelligence mode first. Outcome: Audit time drops .

Log workspace IDs and tool calls for easy replication and debugging.

Validate with test documents before scaling to production data.

Log workspace IDs and tool calls for easy replication and debugging.

Practical example: Query sales reports across multiple PDFs; gets cited summaries in seconds. Constraint: Limit to one workspace per query. Outcome: Cuts research from hours to minutes.

Teams should validate this approach in a small test path first, then standardize it across environments once metrics and outcomes are stable.