Update app.py

app.py

@@ -6,7 +6,10 @@ from PIL import Image
 import io
 import json
 import hashlib
+from google.api_core import exceptions as google_exceptions
+
 app = FastAPI()
+
 app.add_middleware(
     CORSMiddleware,
     allow_origins=["*"], 
@@ -14,9 +17,12 @@ app.add_middleware(
     allow_methods=["*"],
     allow_headers=["*"],
 )
+
 print("Initializing backend...")
+
 GEMINI_API_KEY = os.environ.get("GEMINI_API_KEY")
 MODEL_LOADED = False
+
 if GEMINI_API_KEY:
     try:
         genai.configure(api_key=GEMINI_API_KEY)
@@ -46,9 +52,11 @@ if GEMINI_API_KEY:
         print(f"General configuration error: {e}")
 else:
     print("Warning: GEMINI_API_KEY environment variable not set. Running in simulation mode.")
+
 @app.get("/")
 def read_root():
     return {"status": "online", "engine": "Creative Intelligence Engine", "active": True}
+
 @app.get("/api/health")
 def health_check():
     return {
@@ -57,16 +65,19 @@ def health_check():
         "api_key_configured": bool(GEMINI_API_KEY),
         "message": "Neural Engine analysis is operational."
     }
+
 prompt_template = """
 You are a neuromarketing expert AI analyzing an ad creative image critically with emphasis on copy, CTA, best time and platform etc..
 Evaluate this image strictly on these 5 cognitive parameters. Give a score between 0.10 and 0.98.
 Also provide a VERY brief 1-sentence analytical reason based exactly on what is visibly in the image.
+
 The parameters are:
 - visual_saliency (How effectively it draws the eye with contrast, colors, shapes)
 - cognitive_ease (Clean layout vs clutter. Higher score = easier to process)
 - emotional_arousal (Does it trigger a mood via faces, colors, or atmosphere)
 - value_recognition (Speed of identifying the core reward/benefit/CTA)
 - memory_encoding (Distinctiveness of brand motifs, logos, or striking imagery)
+
 Return strictly valid JSON containing a single "scores" object, a "reasons" object, and an "insights" array.
 Format:
 {
@@ -89,6 +100,7 @@ Format:
   ]
 }
 """
+
 @app.post("/api/analyze")
 async def analyze_creative(
     creative: UploadFile = File(None),
@@ -119,14 +131,25 @@ async def analyze_creative(
             scores = data.get("scores", {})
             reasons = data.get("reasons", {})
             insights = data.get("insights", ["Analysis completed successfully."])
+
+        except google_exceptions.ResourceExhausted as e:
+            print(f"Quota Exceeded (429): {e}")
+            scores = {
+                "visual_saliency": 0.40, "cognitive_ease": 0.35, 
+                "emotional_arousal": 0.30, "value_recognition": 0.40, "memory_encoding": 0.35
+            }
+            reasons = {k: "Analysis paused due to capacity constraints." for k in scores}
+            insights = ["Neural Engine is currently at peak capacity. Analysis is temporarily paused to ensure data fidelity. Please try again in a few moments."]
+            source = "Cloud VLM (Quota Reached)"
         except Exception as e:
+            print(f"API Error during analysis: {e}")
             scores = {
                 "visual_saliency": 0.32, "cognitive_ease": 0.28, 
                 "emotional_arousal": 0.10, "value_recognition": 0.45, "memory_encoding": 0.24
             }
-            reasons = {k: f"Error: {str(e)[:50]}..." for k in scores}
-            insights = [f"API Error: {str(e)}"]
-            source = f"HF Space (Error)"
+            reasons = {k: "Neural processing temporarily restricted." for k in scores}
+            insights = ["The Neural Engine encountered an unexpected synchronization error. Please retry the analysis."]
+            source = f"HF Space (Sync Error)"
     else:
         # Deterministic fallback based on file name
         seed = name + description
@@ -148,6 +171,7 @@ async def analyze_creative(
         }
         insights = ["Running in simulation mode. No valid GEMINI_API_KEY provided."]
         source = "HF Space (Simulation Fallback)"
+
     # Calculate timeline metrics from current scores (averaging for consistency)
     avg_score = sum(scores.values()) / len(scores) if scores else 0.5
     timeline = {
@@ -157,6 +181,7 @@ async def analyze_creative(
     }
     # Clamp timeline scores to 100
     timeline = {k: min(v, 99.0) for k, v in timeline.items()}
+
     return {
         "id": id,
         "name": name,