LoRa Manager E2E Testing

This skill provides workflows and utilities for end-to-end testing of LoRa Manager using Chrome DevTools MCP.

Prerequisites

•LoRa Manager project cloned and dependencies installed (pip install -r requirements.txt)
•Chrome browser available for debugging
•Chrome DevTools MCP connected

Quick Start Workflow

1. Start LoRa Manager Standalone

python

# Use the provided script to start the server
python .agents/skills/lora-manager-e2e/scripts/start_server.py --port 8188

Or manually:

bash

cd /home/miao/workspace/ComfyUI/custom_nodes/ComfyUI-Lora-Manager
python standalone.py --port 8188

Wait for server ready message before proceeding.

2. Open Chrome Debug Mode

bash

# Chrome with remote debugging on port 9222
google-chrome --remote-debugging-port=9222 --user-data-dir=/tmp/chrome-lora-manager http://127.0.0.1:8188/loras

3. Connect Chrome DevTools MCP

Ensure the MCP server is connected to Chrome at http://localhost:9222.

4. Navigate and Interact

Use Chrome DevTools MCP tools to:

•Take snapshots: take_snapshot
•Click elements: click
•Fill forms: fill or fill_form
•Evaluate scripts: evaluate_script
•Wait for elements: wait_for

Common E2E Test Patterns

Pattern: Full Page Load Verification

python

# Navigate to LoRA list page
navigate_page(type="url", url="http://127.0.0.1:8188/loras")

# Wait for page to load
wait_for(text="LoRAs", timeout=10000)

# Take snapshot to verify UI state
snapshot = take_snapshot()

Pattern: Restart Server for Configuration Changes

python

# Stop current server (if running)
# Start with new configuration
python .agents/skills/lora-manager-e2e/scripts/start_server.py --port 8188 --restart

# Wait and refresh browser
navigate_page(type="reload", ignoreCache=True)
wait_for(text="LoRAs", timeout=15000)

Pattern: Verify Backend API via Frontend

python

# Execute script in browser to call backend API
result = evaluate_script(function="""
async () => {
  const response = await fetch('/loras/api/list');
  const data = await response.json();
  return { count: data.length, firstItem: data[0]?.name };
}
""")

Pattern: Form Submission Flow

python

# Fill a form (e.g., search or filter)
fill_form(elements=[
    {"uid": "search-input", "value": "character"},
])

# Click submit button
click(uid="search-button")

# Wait for results
wait_for(text="Results", timeout=5000)

# Verify results via snapshot
snapshot = take_snapshot()

Pattern: Modal Dialog Interaction

python

# Open modal (e.g., add LoRA)
click(uid="add-lora-button")

# Wait for modal to appear
wait_for(text="Add LoRA", timeout=3000)

# Fill modal form
fill_form(elements=[
    {"uid": "lora-name", "value": "Test LoRA"},
    {"uid": "lora-path", "value": "/path/to/lora.safetensors"},
])

# Submit
click(uid="modal-submit-button")

# Wait for success message or close
wait_for(text="Success", timeout=5000)

Available Scripts

scripts/start_server.py

Starts or restarts the LoRa Manager standalone server.

bash

python scripts/start_server.py [--port PORT] [--restart] [--wait]

Options:

•--port: Server port (default: 8188)
•--restart: Kill existing server before starting
•--wait: Wait for server to be ready before exiting

scripts/wait_for_server.py

Polls server until ready or timeout.

bash

python scripts/wait_for_server.py [--port PORT] [--timeout SECONDS]

Test Scenarios Reference

See references/test-scenarios.md for detailed test scenarios including:

•LoRA list display and filtering
•Model metadata editing
•Recipe creation and management
•Settings configuration
•Import/export functionality

Network Request Verification

Use list_network_requests and get_network_request to verify API calls:

python

# List recent XHR/fetch requests
requests = list_network_requests(resourceTypes=["xhr", "fetch"])

# Get details of specific request
details = get_network_request(reqid=123)

Console Message Monitoring

python

# Check for errors or warnings
messages = list_console_messages(types=["error", "warn"])

Performance Testing

python

# Start performance trace
performance_start_trace(reload=True, autoStop=False)

# Perform actions...

# Stop and analyze
results = performance_stop_trace()

Cleanup

Always ensure proper cleanup after tests:

•Stop the standalone server
•Close browser pages (keep at least one open)
•Clear temporary data if needed