Welcome to the Admin Panel
The Junis Admin Panel is your central command center for managing AI agents, workflows, knowledge bases, and team settings. This no-code interface allows you to build sophisticated multi-agent systems without writing a single line of code. What You’ll Learn:- Navigate the Admin interface
- Manage agents and workflows
- Configure RAG knowledge bases
- Connect MCP integrations
- Monitor usage and performance
📍 Accessing the Admin Panel
Navigation
Sign In
Navigate to https://junis.ai and sign in with your account
Select Organization
From the top navigation bar, ensure you’ve selected the correct organization (if you’re a member of multiple organizations)
Permission Levels
Different features are available based on your role:| Feature | Member | Admin |
|---|---|---|
| View Dashboard | ✅ | ✅ |
| Manage API Keys | ✅ | ✅ |
| View Agents | ❌ | ✅ |
| Create/Edit Agents | ❌ | ✅ |
| Organization Settings | ❌ | ✅ |
| System Management | ❌ | ❌ |
Role Hierarchy: Admin > Member. Higher roles inherit all permissions from lower roles.
📊 Dashboard Overview
The Dashboard is the first page you see when entering the Admin panel. It provides real-time insights into your organization’s AI usage.Quick Stats
The top section displays four key metrics:Active Users Today
Number of unique users in the last 24 hours
Active Chats Today
Total chat sessions created today
Live Now
Currently connected WebSocket sessions (real-time)
Avg Speed
Average response time in milliseconds (last 24 hours)
Real-Time Metrics
The metrics section shows live updates via WebSocket:- Active Sessions: Users currently chatting with agents
- Recent Messages: Message rate per minute
- Agent Performance: Response times by agent
- Error Rate: System health monitoring
Recent Activity (Admin Only)
Admins and Super Admins can see:- Latest chat sessions
- Which agents were used
- Session duration and message count
- User information
🤖 Agent Management
The heart of Junis - where you create, configure, and visualize your AI agent workflows.Two Views: List and Orchestration
- Agent List
- Orchestration
Table View - See all agents in a sortable, hierarchical listColumns:
- Name: Agent identifier (Orchestrator shown first)
- Type: LLM, Sequential, Parallel, or Loop (color-coded badges)
- SubAgents: Visual chips showing connected agents with order numbers
- Description: Agent purpose and function
- Actions: Edit, Relationships, Delete buttons
Creating a New Agent
Choose Method
Select how to create the agent:
- Create New: Build from scratch
- Use Global Agent: Import a public template from the Junis marketplace
Add Tools (Optional)
- Regular Tools: Select Python functions (search_database, send_email, etc.)
- RAG Tools: Select knowledge bases (rag_product_docs, rag_support_kb)
- MCP Platforms: Select integrations (GitHub, Firecrawl)
Configure Advanced Settings
- Output Key: Variable name for Sequential Agent data passing
- Payment Settings: Enable paid usage (wallet address, price per use)
- Web Search: Enable real-time web search (Gemini 2.0, Claude 3.5+)
- Extended Thinking: Enable reasoning tokens (Claude 3.5+, o1 models)
Auto-Refresh: The cache is automatically refreshed when you create or update agents. No manual reload needed!
Editing an Agent
- From List View
- Quick Actions
- Click the Edit (pencil) icon next to the agent name
- Modify settings in the dialog
- Click “Save” to apply changes
Managing Agent Relationships
Agent Relationships define which sub-agents a parent agent can call.View Current Relationships
See two sections:
- Sub-Agents: Agents this one calls (with order index)
- Parent Agents: Agents that call this one
Add a Sub-Agent
- Click ”+ Add Sub-Agent”
- Select an agent from the dropdown
- Set the order index (1 = first, 2 = second, etc.)
- Click “Add”
Reorder Sub-Agents
For Sequential Agents, order matters!
- Click the up/down arrows to change execution order
- Changes save immediately
For Sequential Agents: Sub-agents execute in order (1, 2, 3…). Each agent passes its output to the next via the
output_key variable.For Parallel Agents: Order doesn’t matter. All sub-agents run simultaneously, and results are combined.
Visual Workflow Builder
The Orchestration tab provides an interactive graph view of your agent system. Node Colors:- Blue Gradient: LLM Agent (performs tasks)
- Purple Gradient: Sequential Agent (runs agents in order)
- Green Gradient: Parallel Agent (runs agents simultaneously)
- Orange Gradient: Loop Agent (repeats until condition met)
- Solid: Direct parent-child relationship
- Dotted (Purple): Sequential execution flow (left to right)
- Dotted (Green): Parallel execution flow (top to bottom)
- Shows agent type meanings
- Indicates execution flow patterns
- Lists agents not connected to the Orchestrator
- Displays active/inactive status
- Tool Agents are automatically hidden
Deleting an Agent
Check Relationships
Before deleting, open the Relationships dialog to see if other agents use this one
Orchestrator Protection: You cannot delete the Orchestrator agent. It’s the root of your organization’s agent system.
📚 RAG Knowledge Base
RAG (Retrieval-Augmented Generation) allows your agents to query uploaded documents for accurate, context-aware responses.How It Works
Uploading Documents
Prepare Your Files
Supported Formats:
- ✅ PDF (.pdf) - Max 50MB
- ✅ Microsoft Word (.docx) - Max 50MB
- ✅ PowerPoint (.pptx) - Max 10MB
- ✅ Plain Text (.txt) - Max 10MB
- ✅ Markdown (.md, .markdown) - Max 10MB
- ✅ HTML (.html, .htm) - Max 10MB
- ✅ JSON (.json, .jsonl) - Max 10MB
Documents are uploaded to Google Cloud Storage and indexed by Vertex AI Search. Indexing typically takes 5-60 minutes depending on file count.
Upload
Click “Upload Document” and select your fileThe system will:
- Upload to Google Cloud Storage
- Create a Vertex AI Search DataStore
- Index the document (JSONL conversion)
- Generate a RAG tool ID (format:
rag_{datastore_id})
Assigning RAG Tools to Agents
Select DataStores
Check the boxes for the knowledge bases this agent should accessExample:
- ✅
rag_product_documentation - ✅
rag_support_tickets_history - ☐
rag_marketing_materials
RAG Best Practices
Document Preparation
Document Preparation
- Clean formatting: Remove unnecessary headers, footers
- Consistent structure: Use headings, bullet points
- Clear language: Avoid jargon unless necessary
- Chunk size: Keep documents under 10MB for faster indexing
Multiple DataStores
Multiple DataStores
- Separate by topic (product docs, support tickets, policies)
- Separate by audience (internal vs customer-facing)
- Agents can use multiple DataStores simultaneously
Query Optimization
Query Optimization
- Include keywords in your documents
- Use semantic search (Vertex AI Search handles this automatically)
- Test queries with the agent to verify retrieval accuracy
🔌 MCP Integrations
MCP (Model Context Protocol) connects your agents to external platforms like GitHub, Firecrawl, and custom services.Available Platforms
GitHub
Manage repos, issues, and PRs
Firecrawl
Web scraping and crawling
Supported platforms: GitHub, Firecrawl, and custom MCP servers. Easily extensible for any service with MCP implementation. See the MCP Integration Guide for details.
Setting Up MCP Credentials
- Organization-Level (Admin)
- User-Level (Personal)
Shared credentials for all team members
Shared Access: All agents in your organization can now use this platform (if granted permission).
Enabling MCP for an Agent
Select Platforms
Check the boxes for platforms this agent should access:
- ✅ GitHub
- ✅ Firecrawl
- ☐ Custom MCP (if configured)
🔑 API Keys
Generate API keys to integrate Junis agents into external applications.Creating an API Key
Using an API Key
Authentication Header:OpenAI SDK Compatible: Use the OpenAI Python SDK with
base_url="https://api.junis.ai/api/external/v1" for seamless integration.Managing API Keys
- View Keys
- Revoke Key
- Rotate Keys
- See all API keys for your organization
- Check last used timestamp
- View permissions and expiration
⚙️ Organization Settings
Navigate to Admin > Dashboard > Settings tab to configure organization-wide options.Team Settings
Organization Profile
Organization Profile
- Name: Your organization’s display name
- Slug: URL-friendly identifier (e.g.,
acme-corp) - Logo: Upload a logo image (PNG, JPG, max 2MB)
- Description: Public description (shown on showcase page)
Public Showcase
Public Showcase
- Enable Public Profile: Make your organization discoverable on junis.ai/showcase
- Welcome Suggestions: Customize suggested prompts for visitors
- Featured Agents: Select which agents to showcase publicly
Payment Settings
Payment Settings
- Company Wallet: Ethereum wallet address for receiving agent usage payments
- Default Agent Pricing: Set default price per use (USDC micro)
Usage Limits
Usage Limits
- View current usage statistics
- Set monthly limits (Pro/Enterprise plans)
- Configure billing alerts
User Management
Invite Team Members:Assign Role
- Member: Can use agents, view dashboard
- Support: + Can view agent configurations
- Admin: + Can create/edit agents, manage settings
- Find the user in the list
- Click the role dropdown
- Select the new role
- Click the trash icon next to a user
- Confirm removal
🔍 Advanced Features
Scheduled Tasks
Automate agent execution with schedules (cron jobs).- Create Schedule
- Schedule Types
Workflow Builder (Coming Soon)
Visual drag-and-drop interface for building complex agent workflows. Features (planned):- Drag agents from a palette
- Draw connections between agents
- Set conditional logic (if/else branches)
- Test workflows in real-time
- Export/import workflow templates
💡 Tips for Effective Admin Management
Start Simple, Scale Gradually
Start Simple, Scale Gradually
- Begin with a single LLM Agent to handle basic tasks
- Test thoroughly before adding complexity
- Add Sequential/Parallel agents only when you need multi-step workflows
- Monitor performance before scaling up
Organize Agents by Function
Organize Agents by Function
Naming Convention:
orchestrator- Main routercustomer_support_agent- Customer-facingresearch_analyst- Data analysisemail_sender- Action agents
- Front-line: Customer support, sales
- Back-office: Data processing, reporting
- Specialized: Legal, technical documentation
Use Descriptive Instructions
Use Descriptive Instructions
Good:Bad:
Monitor and Iterate
Monitor and Iterate
- Check Dashboard metrics weekly
- Review Recent Activity to see how agents are being used
- Update agent instructions based on user feedback
- Test edge cases regularly
Security Best Practices
Security Best Practices
- Rotate API keys every 90 days
- Use user-level MCP credentials for personal platforms (e.g., personal GitHub)
- Set payment thresholds for paid agents
- Review user permissions quarterly
- Enable 2FA for all admin users (if available)
🆘 Common Issues and Solutions
Agent not responding
Agent not responding
Possible Causes:
- Agent is inactive (check the toggle)
- Agent is not connected to Orchestrator (check relationships)
- Model API key is missing (verify in SQLAdmin)
- Check agent status (green toggle)
- Verify Orchestrator relationships
- Test with a simple message
- Check Dashboard > Recent Activity for errors
RAG tool not finding documents
RAG tool not finding documents
Possible Causes:
- Document still indexing (wait 1-2 minutes)
- RAG tool not assigned to agent
- Query doesn’t match document content
- Check DataStore status (should be “Completed”)
- Verify agent has the RAG tool enabled
- Test with a query that matches document keywords
- Check Vertex AI Search console for indexing errors
MCP integration failing
MCP integration failing
Possible Causes:
- Credentials expired or invalid
- Platform not enabled for agent
- Rate limiting from external platform
- Re-authenticate the MCP platform
- Check agent MCP platforms list
- Verify API key permissions on the external platform
- Check error logs in Dashboard > Recent Activity
Visual workflow not updating
Visual workflow not updating
Possible Causes:
- Browser cache issue
- Relationships not saved correctly
- Hard refresh the page (Ctrl+Shift+R or Cmd+Shift+R)
- Switch to List view to verify relationships
- Re-save the relationships if needed
📖 Next Steps
MCP Integration Guide
Connect external platforms via Model Context Protocol
Custom Tools
Register Python functions as agent tools
API Reference
Integrate Junis into your applications
🎓 Admin Interface Certification
Congratulations! You now know how to:✅ Navigate the Admin dashboard and interpret metrics
✅ Create, edit, and delete agents with confidence
✅ Manage agent relationships and build workflows
✅ Upload RAG documents and assign to agents
✅ Configure MCP integrations (org-level and user-level)
✅ Generate and manage API keys securely
✅ Configure organization settings and team permissions
✅ Troubleshoot common issues independently
Need More Help? Check the API Reference for programmatic management or contact us at contact@junis.ai.
