Update app.py

app.py

@@ -74,27 +74,21 @@ def background_processing(session_data: dict):
 
     session_dir = os.path.join(RESULT_DIR, session_id)
     os.makedirs(session_dir, exist_ok=True)
-    
-    print(f"[LOG] Processing started for session: {session_id}")
-    
     local_input_path = os.path.join(UPLOAD_DIR, f"{session_id}_input.mp4")
 
-    # 1. Download the original video from Cloudinary/URL
+    # 1. Download
     try:
         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 = []
-    
+    # 2. Prepare Data
+    final_questions, skipped_failed_reports = [], []
     for q in session_data.get('answers', []):
         if q.get('isAnswered'):
             final_questions.append({
@@ -106,51 +100,36 @@ def background_processing(session_data: dict):
             })
         else:
             skipped_failed_reports.append({
-                "questionId": q['aiQuestionId'],
-                "userAnswerText": "N/A",
+                "questionId": q['aiQuestionId'], "userAnswerText": "N/A",
                 "score": 0.0, "relevance": 0.0, "confidence": 0.0,
-                "stress": 0.0, "clarity": 0.0, "pauses": 0.0,
-                "toneOfVoice": 3,
+                "stress": 0.0, "clarity": 0.0, "pauses": 0.0, "toneOfVoice": 3,
                 "status": "skipped" if q.get('isSkipped') else "failed"
             })
 
-    ai_results = []
-    final_video_url = None
+    ai_results, final_video_url = [], None
     
-    # 3. Run the AI Pipeline
+    # 3. Run 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}")
-
-        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
+        print(f"[LOG] Running pipeline...")
+        # Synchronized return: receive both paths
+        final_video_path, report_path = run_intervision_pipeline(local_input_path, final_questions, session_dir)
+
         if os.path.exists(report_path):
             with open(report_path, "r") as f:
+                # This now finds the key 'listOfAnswerReport'
                 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_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}")
 
-    # 5. Send results back via Callback
+    # 4. Callback
     final_payload = {
         "sessionId": session_id,
         "finalVideoUrl": final_video_url,
@@ -159,18 +138,14 @@ def background_processing(session_data: dict):
     
     try:
         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)
-        if os.path.exists(session_dir): 
-            shutil.rmtree(session_dir)
-            
+        requests.post(callback_endpoint, json=final_payload, timeout=30)
+        
+        # Cleanup
+        if os.path.exists(local_input_path): os.remove(local_input_path)
+        if os.path.exists(session_dir): shutil.rmtree(session_dir)
     except Exception as e:
-        print(f"[CALLBACK/CLEANUP ERROR]: {e}")
+        print(f"[CALLBACK ERROR]: {e}")
+        
 
 @app.get("/")
 async def root():