Files
AutoGPT/autogpt_platform
Zamil Majdy a78b08f5e7 feat(platform): implement admin user impersonation with header-based authentication (#11298)
## Summary

Implement comprehensive admin user impersonation functionality to enable
admins to act on behalf of any user for debugging and support purposes.

## 🔐 Security Features

- **Admin Role Validation**: Only users with 'admin' role can
impersonate others
- **Header-Based Authentication**: Uses `X-Act-As-User-Id` header for
impersonation requests
- **Comprehensive Audit Logging**: All impersonation attempts logged
with admin details
- **Secure Error Handling**: Proper HTTP 403/401 responses for
unauthorized access
- **SSR Safety**: Client-side environment checks prevent server-side
rendering issues

## 🏗️ Architecture

### Backend Implementation (`autogpt_libs/auth/dependencies.py`)
- Enhanced `get_user_id` FastAPI dependency to process impersonation
headers
- Admin role verification using existing `verify_user()` function
- Audit trail logging with admin email, user ID, and target user
- Seamless integration with all existing routes using `get_user_id`
dependency

### Frontend Implementation
- **React Hook**: `useAdminImpersonation` for state management and API
calls
- **Security Banner**: Prominent warning when impersonation is active
- **Admin Panel**: Control interface for starting/stopping impersonation
- **Session Persistence**: Maintains impersonation state across page
refreshes
- **Full Page Refresh**: Ensures all data updates correctly on state
changes

### API Integration
- **Header Forwarding**: All API requests include impersonation header
when active
- **Proxy Support**: Next.js API proxy forwards headers to backend
- **Generated Hooks**: Compatible with existing React Query API hooks
- **Error Handling**: Graceful fallback for storage/authentication
failures

## 🎯 User Experience

### For Admins
1. Navigate to `/admin/impersonation` 
2. Enter target user ID (UUID format with validation)
3. System displays security banner during active impersonation
4. All API calls automatically use impersonated user context
5. Click "Stop Impersonation" to return to admin context

### Security Notice
- **Audit Trail**: All impersonation logged with `logger.info()`
including admin email
- **Session Isolation**: Impersonation state stored in sessionStorage
(not persistent)
- **No Token Manipulation**: Uses header-based approach, preserving
admin's JWT
- **Role Enforcement**: Backend validates admin role on every
impersonated request

## 🔧 Technical Details

### Constants & Configuration
- `IMPERSONATION_HEADER_NAME = "X-Act-As-User-Id"`
- `IMPERSONATION_STORAGE_KEY = "admin-impersonate-user-id"`
- Centralized in `frontend/src/lib/constants.ts` and
`autogpt_libs/auth/dependencies.py`

### Code Quality Improvements
- **DRY Principle**: Eliminated duplicate header forwarding logic
- **Icon Compliance**: Uses Phosphor Icons per coding guidelines  
- **Type Safety**: Proper TypeScript interfaces and error handling
- **SSR Compatibility**: Environment checks for client-side only
operations
- **Error Consistency**: Uniform silent failure with logging approach

### Testing
- Updated backend auth dependency tests for new function signatures
- Added Mock Request objects for comprehensive test coverage
- Maintained existing test functionality while extending capabilities

## 🚀 CodeRabbit Review Responses

All CodeRabbit feedback has been addressed:

1.  **DRY Principle**: Refactored duplicate header forwarding logic
2.  **Icon Library**: Replaced lucide-react with Phosphor Icons  
3.  **SSR Safety**: Added environment checks for sessionStorage
4.  **UI Improvements**: Synchronous initialization prevents flicker
5.  **Error Handling**: Consistent silent failure with logging
6.  **Backend Validation**: Confirmed comprehensive security
implementation
7.  **Type Safety**: Addressed TypeScript concerns
8.  **Code Standards**: Followed all coding guidelines and best
practices

## 🧪 Testing Instructions

1. **Login as Admin**: Ensure user has admin role
2. **Navigate to Panel**: Go to `/admin/impersonation`
3. **Test Impersonation**: Enter valid user UUID and start impersonation
4. **Verify Banner**: Security banner should appear at top of all pages
5. **Test API Calls**: Verify credits/graphs/etc show impersonated
user's data
6. **Check Logging**: Backend logs should show impersonation audit trail
7. **Stop Impersonation**: Verify return to admin context works
correctly

## 📝 Files Modified

### Backend
- `autogpt_libs/auth/dependencies.py` - Core impersonation logic
- `autogpt_libs/auth/dependencies_test.py` - Updated test signatures

### Frontend
- `src/hooks/useAdminImpersonation.ts` - State management hook
- `src/components/admin/AdminImpersonationBanner.tsx` - Security warning
banner
- `src/components/admin/AdminImpersonationPanel.tsx` - Admin control
interface
- `src/app/(platform)/admin/impersonation/page.tsx` - Admin page
- `src/app/(platform)/admin/layout.tsx` - Navigation integration
- `src/app/(platform)/layout.tsx` - Banner integration
- `src/lib/autogpt-server-api/client.ts` - Header injection for API
calls
- `src/lib/autogpt-server-api/helpers.ts` - Header forwarding logic
- `src/app/api/proxy/[...path]/route.ts` - Proxy header forwarding
- `src/app/api/mutators/custom-mutator.ts` - Enhanced error handling
- `src/lib/constants.ts` - Shared constants

## 🔒 Security Compliance

- **Authorization**: Admin role required for impersonation access
- **Authentication**: Uses existing JWT validation with additional role
checks
- **Audit Logging**: Comprehensive logging of all impersonation
activities
- **Error Handling**: Secure error responses without information leakage
- **Session Management**: Temporary sessionStorage without persistent
data
- **Header Validation**: Proper sanitization and validation of
impersonation headers

This implementation provides a secure, auditable, and user-friendly
admin impersonation system that integrates seamlessly with the existing
AutoGPT Platform architecture.

<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->

## Summary by CodeRabbit

* **New Features**
  * Admin user impersonation to view the app as another user.
* New "User Impersonation" admin page for entering target user IDs and
managing sessions.
  * Sidebar link for quick access to the impersonation page.
* Persistent impersonation state that updates app data (e.g., credits)
and survives page reloads.
* Top warning banner when impersonation is active with a Stop
Impersonation control.

<!-- end of auto-generated comment: release notes by coderabbit.ai -->

---------

Co-authored-by: Claude <noreply@anthropic.com>
2025-11-04 03:51:28 +00:00
..
2025-11-01 10:19:55 +01:00

AutoGPT Platform

Welcome to the AutoGPT Platform - a powerful system for creating and running AI agents to solve business problems. This platform enables you to harness the power of artificial intelligence to automate tasks, analyze data, and generate insights for your organization.

Getting Started

Prerequisites

  • Docker
  • Docker Compose V2 (comes with Docker Desktop, or can be installed separately)

Running the System

To run the AutoGPT Platform, follow these steps:

  1. Clone this repository to your local machine and navigate to the autogpt_platform directory within the repository:

    git clone <https://github.com/Significant-Gravitas/AutoGPT.git | git@github.com:Significant-Gravitas/AutoGPT.git>
    cd AutoGPT/autogpt_platform
    
  2. Run the following command:

    cp .env.default .env
    

    This command will copy the .env.default file to .env. You can modify the .env file to add your own environment variables.

  3. Run the following command:

    docker compose up -d
    

    This command will start all the necessary backend services defined in the docker-compose.yml file in detached mode.

  4. After all the services are in ready state, open your browser and navigate to http://localhost:3000 to access the AutoGPT Platform frontend.

Running Just Core services

You can now run the following to enable just the core services.

# For help
make help

# Run just Supabase + Redis + RabbitMQ
make start-core

# Stop core services
make stop-core

# View logs from core services 
make logs-core

# Run formatting and linting for backend and frontend
make format

# Run migrations for backend database
make migrate

# Run backend server
make run-backend

# Run frontend development server
make run-frontend

Docker Compose Commands

Here are some useful Docker Compose commands for managing your AutoGPT Platform:

  • docker compose up -d: Start the services in detached mode.
  • docker compose stop: Stop the running services without removing them.
  • docker compose rm: Remove stopped service containers.
  • docker compose build: Build or rebuild services.
  • docker compose down: Stop and remove containers, networks, and volumes.
  • docker compose watch: Watch for changes in your services and automatically update them.

Sample Scenarios

Here are some common scenarios where you might use multiple Docker Compose commands:

  1. Updating and restarting a specific service:

    docker compose build api_srv
    docker compose up -d --no-deps api_srv
    

    This rebuilds the api_srv service and restarts it without affecting other services.

  2. Viewing logs for troubleshooting:

    docker compose logs -f api_srv ws_srv
    

    This shows and follows the logs for both api_srv and ws_srv services.

  3. Scaling a service for increased load:

    docker compose up -d --scale executor=3
    

    This scales the executor service to 3 instances to handle increased load.

  4. Stopping the entire system for maintenance:

    docker compose stop
    docker compose rm -f
    docker compose pull
    docker compose up -d
    

    This stops all services, removes containers, pulls the latest images, and restarts the system.

  5. Developing with live updates:

    docker compose watch
    

    This watches for changes in your code and automatically updates the relevant services.

  6. Checking the status of services:

    docker compose ps
    

    This shows the current status of all services defined in your docker-compose.yml file.

These scenarios demonstrate how to use Docker Compose commands in combination to manage your AutoGPT Platform effectively.

Persisting Data

To persist data for PostgreSQL and Redis, you can modify the docker-compose.yml file to add volumes. Here's how:

  1. Open the docker-compose.yml file in a text editor.

  2. Add volume configurations for PostgreSQL and Redis services:

    services:
      postgres:
        # ... other configurations ...
        volumes:
          - postgres_data:/var/lib/postgresql/data
    
      redis:
        # ... other configurations ...
        volumes:
          - redis_data:/data
    
    volumes:
      postgres_data:
      redis_data:
    
  3. Save the file and run docker compose up -d to apply the changes.

This configuration will create named volumes for PostgreSQL and Redis, ensuring that your data persists across container restarts.

API Client Generation

The platform includes scripts for generating and managing the API client:

  • pnpm fetch:openapi: Fetches the OpenAPI specification from the backend service (requires backend to be running on port 8006)
  • pnpm generate:api-client: Generates the TypeScript API client from the OpenAPI specification using Orval
  • pnpm generate:api: Runs both fetch and generate commands in sequence

Manual API Client Updates

If you need to update the API client after making changes to the backend API:

  1. Ensure the backend services are running:

    docker compose up -d
    
  2. Generate the updated API client:

    pnpm generate:api
    

This will fetch the latest OpenAPI specification and regenerate the TypeScript client code.