Opencode

```python
from prometheus_client import start_http_server, Counter, Gauge
import time
import random

# Custom metrics for API monitoring
API_RESPONSE_TIME = Gauge('api_response_time_seconds', 'Time spent processing API requests')
API_ERROR_COUNT = Counter('api_errors_total', 'Total number of API errors', ['endpoint', 'error_type'])
API_REQUEST_COUNT = Counter('api_requests_total', 'Total number of API requests', ['endpoint'])

def simulate_api_call(endpoint):
    """Simulate an API call with variable response time and potential errors"""
    API_REQUEST_COUNT.labels(endpoint=endpoint).inc()
    
    # Simulate processing time between 0.1 and 2 seconds
    start_time = time.time()
    time.sleep(random.uniform(0.1, 2))
    
    # Randomly introduce errors (20% chance)
    if random.random() < 0.2:
        error_type = random.choice(['timeout', 'validation_error', 'server_error'])
        API_ERROR_COUNT.labels(endpoint=endpoint, error_type=error_type).inc()
        raise Exception(f"API error: {error_type}")
    
    API_RESPONSE_TIME.set(time.time() - start_time)
    return {"status": "success", "data": f"Sample response for {endpoint}"}

if __name__ == '__main__':
    # Start Prometheus metrics server on port 8000
    start_http_server(8000)
    print("Prometheus metrics server started on port 8000")
    
    # Simulate API calls
    endpoints = ['/users', '/products', '/orders']
    while True:
        endpoint = random.choice(endpoints)
        try:
            result = simulate_api_call(endpoint)
            print(f"Success: {result}")
        except Exception as e:
            print(f"Error: {str(e)}")
        time.sleep(1)
```

**Prometheus Query to Test Metrics:**
- `rate(api_requests_total[5m])` - Request rate over last 5 minutes
- `sum(api_response_time_seconds) by (endpoint)` - Total response time by endpoint
- `rate(api_errors_total[5m])` - Error rate over last 5 minutes

This snippet demonstrates how to instrument a Python application with Prometheus metrics, including custom gauges and counters for API monitoring. The metrics can be scraped by Prometheus and visualized in Grafana dashboards.