Update app.py

app.py

@@ -71,7 +71,6 @@ def background_processing(session_data: dict):
     session_id = session_data.get('sessionId')
     video_url = session_data.get('originalVideoUrl')
     callback_url = session_data.get('callbackBaseUrl')
-    
 
     session_dir = os.path.join(RESULT_DIR, session_id)
     os.makedirs(session_dir, exist_ok=True)
@@ -80,18 +79,19 @@ def background_processing(session_data: dict):
     
     local_input_path = os.path.join(UPLOAD_DIR, f"{session_id}_input.mp4")
 
-
+    # 1. Download the original video from Cloudinary/URL
     try:
-        response = http.get(video_url, stream=True, timeout=300)
+        response = http.get(str(video_url), stream=True, timeout=300)
         response.raise_for_status()
         with open(local_input_path, 'wb') as f:
             for chunk in response.iter_content(chunk_size=1024*1024):
                 f.write(chunk)
+        print(f"[LOG] Download complete: {local_input_path}")
     except Exception as e:
         print(f"[DOWNLOAD ERROR]: {e}")
         return
 
-
+    # 2. Prepare questions for the pipeline
     final_questions = []
     skipped_failed_reports = []
     
@@ -110,40 +110,47 @@ def background_processing(session_data: dict):
                 "userAnswerText": "N/A",
                 "score": 0.0, "relevance": 0.0, "confidence": 0.0,
                 "stress": 0.0, "clarity": 0.0, "pauses": 0.0,
-                "toneOfVoice": 3, # Natural/NA
+                "toneOfVoice": 3,
                 "status": "skipped" if q.get('isSkipped') else "failed"
             })
 
     ai_results = []
-    final_video_path = None
+    final_video_url = None
     
+    # 3. Run the AI Pipeline
     if final_questions:
+        print(f"[LOG] Running pipeline for {len(final_questions)} questions...")
+        # Capture the return message to ensure the pipeline finished
+        pipeline_status = run_intervision_pipeline(local_input_path, final_questions, session_dir)
+        print(f"[LOG] Pipeline Status: {pipeline_status}")
 
-        run_intervision_pipeline(local_input_path, final_questions, session_dir)
-        
         report_path = os.path.join(session_dir, "report.json")
-
+        # Ensure this filename exactly matches the one inside run_intervision_pipeline
         final_video_path = os.path.join(session_dir, "Intervision_Final_Report.mp4")
         
+        # Parse JSON results
         if os.path.exists(report_path):
             with open(report_path, "r") as f:
                 ai_results = json.load(f).get("listOfAnswerReport", [])
 
+        # 4. Upload the generated video to Cloudinary
+        if os.path.exists(final_video_path):
+            print(f"[LOG] Uploading final video to Cloudinary...")
+            try:
+                upload_res = cloudinary.uploader.upload(
+                    final_video_path, 
+                    public_id=f"res_{session_id}", 
+                    folder="intervision_results",
+                    resource_type="video"
+                )
+                final_video_url = upload_res.get("secure_url")
+                print(f"[LOG] Upload successful: {final_video_url}")
+            except Exception as e:
+                print(f"[UPLOAD ERROR]: {e}")
+        else:
+            print(f"[ERROR] Final video file not found at {final_video_path}")
 
-    final_video_url = None
-    if final_video_path and os.path.exists(final_video_path):
-        try:
-            upload_res = cloudinary.uploader.upload(
-                final_video_path, 
-                public_id=f"res_{session_id}", 
-                folder="intervision_results",
-                resource_type="video"
-            )
-            final_video_url = upload_res.get("secure_url")
-        except Exception as e:
-            print(f"[UPLOAD ERROR]: {e}")
-
-
+    # 5. Send results back via Callback
     final_payload = {
         "sessionId": session_id,
         "finalVideoUrl": final_video_url,
@@ -151,9 +158,11 @@ def background_processing(session_data: dict):
     }
     
     try:
-        requests.post(f"{callback_url}/api/ai-callback", json=final_payload, timeout=30)
-        
+        callback_endpoint = f"{str(callback_url).rstrip('/')}/api/ai-callback"
+        callback_resp = requests.post(callback_endpoint, json=final_payload, timeout=30)
+        print(f"[LOG] Callback sent. Status: {callback_resp.status_code}")
 
+        # 6. Cleanup local storage
         print(f"[LOG] Cleaning up session {session_id}...")
         if os.path.exists(local_input_path): 
             os.remove(local_input_path)