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ai_intelligence_layer/test_webhook_push.py

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+#!/usr/bin/env python3
+"""
+Test script to simulate the enrichment service POSTing enriched telemetry
+to the AI Intelligence Layer webhook endpoint.
+
+This mimics the behavior when NEXT_STAGE_CALLBACK_URL is configured in the
+enrichment service to push data to http://localhost:9000/api/ingest/enriched
+
+Usage:
+    python3 test_webhook_push.py           # Post sample telemetry
+    python3 test_webhook_push.py --loop 5  # Post 5 times with delays
+"""
+import sys
+import json
+import time
+from urllib.request import urlopen, Request
+from urllib.error import URLError, HTTPError
+
+WEBHOOK_URL = "http://localhost:9000/api/ingest/enriched"
+
+# Sample enriched telemetry (lap 27 from Monaco)
+# Matches EnrichedTelemetryWebhook model exactly
+SAMPLE_TELEMETRY = {
+    "lap": 27,
+    "aero_efficiency": 0.85,
+    "tire_degradation_index": 0.72,
+    "ers_charge": 0.78,
+    "fuel_optimization_score": 0.82,
+    "driver_consistency": 0.88,
+    "weather_impact": "low"
+}
+
+def post_telemetry(telemetry_data):
+    """POST telemetry to the webhook endpoint."""
+    body = json.dumps(telemetry_data).encode('utf-8')
+    req = Request(
+        WEBHOOK_URL,
+        data=body,
+        headers={
+            'Content-Type': 'application/json',
+            'Accept': 'application/json'
+        },
+        method='POST'
+    )
+    
+    try:
+        with urlopen(req, timeout=10) as resp:
+            response_body = resp.read().decode('utf-8')
+            result = json.loads(response_body)
+            print(f"✓ Posted lap {telemetry_data['lap']}")
+            print(f"  Status: {result.get('status')}")
+            print(f"  Buffer size: {result.get('buffer_size')} records")
+            return True
+    except HTTPError as e:
+        print(f"✗ HTTP Error {e.code}: {e.reason}")
+        try:
+            error_body = e.read().decode('utf-8')
+            print(f"  Details: {error_body}")
+        except:
+            pass
+        return False
+    except URLError as e:
+        print(f"✗ Connection Error: {e.reason}")
+        print(f"  Is the AI service running on port 9000?")
+        return False
+    except Exception as e:
+        print(f"✗ Unexpected error: {e}")
+        return False
+
+def main():
+    import argparse
+    parser = argparse.ArgumentParser(description='Test webhook push to AI layer')
+    parser.add_argument('--loop', type=int, default=1, help='Number of telemetry records to post')
+    parser.add_argument('--delay', type=int, default=2, help='Delay between posts (seconds)')
+    args = parser.parse_args()
+    
+    print(f"Testing webhook push to {WEBHOOK_URL}")
+    print(f"Will post {args.loop} telemetry record(s)\n")
+    
+    success_count = 0
+    for i in range(args.loop):
+        # Increment lap number for each post
+        telemetry = SAMPLE_TELEMETRY.copy()
+        telemetry['lap'] = SAMPLE_TELEMETRY['lap'] + i
+        
+        # Slight variations in metrics (simulate degradation)
+        telemetry['tire_degradation_index'] = min(1.0, round(SAMPLE_TELEMETRY['tire_degradation_index'] + (i * 0.02), 3))
+        telemetry['aero_efficiency'] = max(0.0, round(SAMPLE_TELEMETRY['aero_efficiency'] - (i * 0.01), 3))
+        telemetry['ers_charge'] = round(0.5 + (i % 5) * 0.1, 2)  # Varies between 0.5-0.9
+        telemetry['weather_impact'] = ["low", "low", "medium", "medium", "high"][i % 5]
+        
+        if post_telemetry(telemetry):
+            success_count += 1
+        
+        if i < args.loop - 1:
+            time.sleep(args.delay)
+    
+    print(f"\n{'='*50}")
+    print(f"Posted {success_count}/{args.loop} records successfully")
+    
+    if success_count > 0:
+        print(f"\n✓ Telemetry is now in the AI layer's buffer")
+        print(f"  Next: Call /api/strategy/brainstorm (without enriched_telemetry)")
+        print(f"  The service will use buffered data automatically\n")
+    
+    return 0 if success_count == args.loop else 1
+
+if __name__ == '__main__':
+    sys.exit(main())