Overview
RAG (Retrieval-Augmented Generation) allows your AI agents to access custom knowledge bases. Upload documents and let agents search through your organization’s proprietary information.RAG Knowledge requires Admin access. Contact your organization admin to upload documents.
Supported File Types
| Format | Extension | Max Size |
|---|---|---|
| Plain Text | .txt | 10MB |
| 50MB | ||
| HTML | .html, .htm | 10MB |
| JSON | .json | 10MB |
| JSONL | .jsonl, .ndjson | 10MB |
| Markdown | .md, .markdown | 10MB |
| Word | .docx | 50MB |
| PowerPoint | .pptx | 10MB |
Uploading Documents
Step 1: Access RAG Knowledge
- Navigate to Team > RAG Knowledge
- You must have Admin access to upload documents
Step 2: Create a DataStore
- Click Create DataStore
- Enter a name for your knowledge base
- Select files to upload
Step 3: Wait for Indexing
After upload, documents are processed and indexed:| Status | Description |
|---|---|
pending | Waiting to start processing |
uploading | Files being uploaded to cloud storage |
indexing | Documents being processed and indexed |
processing | Processing in progress |
completed | Knowledge base ready to use |
failed | Processing error (can be retried) |
Indexing typically takes 1-5 minutes depending on document size and quantity.
Using RAG with Agents
Once documents are indexed, they can be assigned to AI agents.Admin Configuration
- Go to Admin > Agents
- Edit an agent
- In the RAG Tools section, select the DataStore
- Save changes
How It Works
When a user asks a question:- The agent searches the knowledge base
- Relevant document sections are retrieved
- The agent uses this context to provide accurate answers
Best Practices
Organize content logically
Organize content logically
- Group related documents together
- Use clear, descriptive filenames
- Remove duplicate content
Format documents well
Format documents well
- Use clear headings and structure
- Break long documents into sections
- Include context in document titles
Keep content current
Keep content current
- Update documents when information changes
- Remove outdated content
- Re-index after major updates
Troubleshooting
Upload failed
Upload failed
Possible causes:
- File type not supported
- File exceeds size limit
- Network connection issue
- Check file format and size
- Try uploading again
- Contact support if issue persists
Agent not finding information
Agent not finding information
Possible causes:
- DataStore not assigned to agent
- Documents not fully indexed
- Query doesn’t match document content
- Verify DataStore is linked to the agent
- Check indexing status is “ready”
- Try rephrasing your question
