Update main.py

main.py

@@ -80,37 +80,42 @@ def auto_fill(value: Optional[str], fallback: str) -> str:
 async def analyze(data: ReviewInput, x_api_key: str = Header(None)):
     if x_api_key and x_api_key != VALID_API_KEY:
         raise HTTPException(status_code=401, detail="❌ Invalid API key")
+    
     if len(data.text.split()) < 20:
         raise HTTPException(status_code=400, detail="⚠️ Review too short for analysis (min. 20 words).")
 
     try:
-        # Smart summary logic based on verbosity and intelligence
-        if data.verbosity.lower() == "brief":
-            summary = summarize_review(data.text, max_len=40, min_len=8)
-        else:
-            summary = smart_summarize(data.text, n_clusters=2 if data.intelligence else 1)
+        response = {}
+
+        # Only perform core analysis if follow-up not present (or first-time analysis)
+        if not data.follow_up:
+            if data.verbosity.lower() == "brief":
+                summary = summarize_review(data.text, max_len=40, min_len=8)
+            else:
+                summary = smart_summarize(data.text, n_clusters=2 if data.intelligence else 1)
+
+            sentiment = sentiment_pipeline(data.text)[0]
+            emotion = "joy"
 
-        sentiment = sentiment_pipeline(data.text)[0]
-        emotion = "joy" 
+            industry = detect_industry(data.text) if not data.industry or "auto" in data.industry.lower() else data.industry
+            product_category = detect_product_category(data.text) if not data.product_category or "auto" in data.product_category.lower() else data.product_category
+            device = "Web"
 
-        # Auto-detection logic
-        industry = detect_industry(data.text) if not data.industry or "auto" in data.industry.lower() else data.industry
-        product_category = detect_product_category(data.text) if not data.product_category or "auto" in data.product_category.lower() else data.product_category
-        device = "Web"
+            response = {
+                "summary": summary,
+                "sentiment": sentiment,
+                "emotion": emotion,
+                "product_category": product_category,
+                "device": device,
+                "industry": industry
+            }
 
-        follow_up_response = None
+        # If follow-up question is asked, generate answer
         if data.follow_up:
             follow_up_response = answer_followup(data.text, data.follow_up, verbosity=data.verbosity)
+            response["follow_up"] = follow_up_response
 
-        return {
-            "summary": summary,
-            "sentiment": sentiment,
-            "emotion": emotion,
-            "product_category": product_category,
-            "device": device,
-            "industry": industry,
-            "follow_up": follow_up_response
-        }
+        return response
 
     except Exception as e:
         logging.error(f"🔥 Unexpected analysis failure: {traceback.format_exc()}")