Add complete anomaly detection workflow with proper error handling

.github/scripts/anomaly_detector.py

@@ -2,6 +2,7 @@ import os
 import requests
 import sys
 import json
+from urllib.parse import urljoin
 
 def download_workflow_logs(run_id, token):
     """Download logs from a specific workflow run"""
@@ -21,13 +22,29 @@ def download_workflow_logs(run_id, token):
         return response.text
     else:
         print(f"Failed to download logs: {response.status_code}")
+        print(f"Response: {response.text}")
         return None
 
 def analyze_logs_with_model(log_content, model_url):
     """Send logs to the model API for analysis"""
     try:
+        # Validate and construct the full URL
+        if not model_url:
+            print("❌ MODEL_API_URL is empty")
+            return None
+            
+        # Ensure the URL has a scheme
+        if not model_url.startswith(('http://', 'https://')):
+            print(f"❌ MODEL_API_URL is missing scheme: {model_url}")
+            print("💡 Please set MODEL_API_URL to a valid URL starting with http:// or https://")
+            return None
+        
+        # Construct the full prediction endpoint URL
+        prediction_url = urljoin(model_url.rstrip('/') + '/', 'predict')
+        print(f"🔗 Calling model API: {prediction_url}")
+        
         response = requests.post(
-            f"{model_url}/predict",
+            prediction_url,
             json={
                 "log_content": log_content,
                 "include_explanation": True
@@ -38,11 +55,21 @@ def analyze_logs_with_model(log_content, model_url):
         if response.status_code == 200:
             return response.json()
         else:
-            print(f"Model API error: {response.status_code}")
+            print(f"❌ Model API error: {response.status_code}")
+            print(f"Response: {response.text}")
             return None
     
-    except requests.RequestException as e:
-        print(f"Failed to call model API: {e}")
+    except requests.exceptions.Timeout:
+        print("❌ Model API request timed out (30 seconds)")
+        return None
+    except requests.exceptions.ConnectionError:
+        print("❌ Failed to connect to Model API - check the URL")
+        return None
+    except requests.exceptions.RequestException as e:
+        print(f"❌ Failed to call model API: {e}")
+        return None
+    except Exception as e:
+        print(f"❌ Unexpected error: {e}")
         return None
 
 def main():
@@ -51,34 +78,43 @@ def main():
     workflow_run_id = os.environ.get('WORKFLOW_RUN_ID')
     model_api_url = os.environ.get('MODEL_API_URL')
     
+    print("🔍 Environment variables check:")
+    print(f"   GITHUB_TOKEN: {'✅' if github_token else '❌'}")
+    print(f"   WORKFLOW_RUN_ID: {'✅' if workflow_run_id else '❌'} -> {workflow_run_id}")
+    print(f"   MODEL_API_URL: {'✅' if model_api_url else '❌'} -> {model_api_url}")
+    
     if not all([github_token, workflow_run_id, model_api_url]):
-        print("Missing required environment variables")
+        print("❌ Missing required environment variables")
         sys.exit(1)
     
-    print(f"Analyzing workflow run: {workflow_run_id}")
+    print(f"📊 Analyzing workflow run: {workflow_run_id}")
     
     # Download logs
+    print("⬇️ Downloading workflow logs...")
     logs = download_workflow_logs(workflow_run_id, github_token)
     if not logs:
-        print("Failed to download logs")
+        print("❌ Failed to download logs")
         sys.exit(1)
     
+    print(f"📄 Logs downloaded ({len(logs)} characters)")
+    
     # Analyze with model
+    print("🤖 Sending logs to model API...")
     result = analyze_logs_with_model(logs, model_api_url)
     if not result:
-        print("Failed to analyze logs with model")
+        print("❌ Failed to analyze logs with model")
         sys.exit(1)
     
-    print(f"Analysis result: {json.dumps(result, indent=2)}")
+    print(f"📋 Analysis result: {json.dumps(result, indent=2)}")
     
     # Check if anomaly detected
     if result.get('is_anomaly', False):
         print("🚨 ANOMALY DETECTED!")
-        print(f"Confidence: {result.get('confidence', 0):.2%}")
-        print(f"Anomaly Probability: {result.get('anomaly_probability', 0):.2%}")
+        print(f"   Confidence: {result.get('confidence', 0):.2%}")
+        print(f"   Anomaly Probability: {result.get('anomaly_probability', 0):.2%}")
         
         if result.get('explanation'):
-            print("Explanation:", result['explanation'])
+            print("   Explanation:", json.dumps(result['explanation'], indent=2))
         
         # Exit with error code to mark step as failed
         sys.exit(1)

.github/workflows/anomaly-check.yml

@@ -1,6 +1,5 @@
 name: Anomaly Detection Check
 
-
 permissions:
   issues: write
   contents: read
@@ -16,7 +15,6 @@ jobs:
     runs-on: ubuntu-latest
     if: ${{ github.event.workflow_run.conclusion != 'cancelled' }}
     
-
     env:
       GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
       WORKFLOW_RUN_ID: ${{ github.event.workflow_run.id }}