feat(analytics): Replace unreliable LLM with robust Python-based summary generator

core/strategist.py

@@ -274,60 +274,43 @@ You are an expert Campaign Analyst...
 
     def generate_influencer_analytics_summary(self, kpis: Dict[str, Any]) -> str:
         """
-        [BULLETPROOF "FILL-IN-THE-BLANKS" VERSION] This gives the AI model a strict template
-        to complete, preventing hallucinations and ensuring a consistent, encouraging tone.
+        [BULLETPROOF "NON-AI" VERSION] This function no longer calls the LLM.
+        It generates a high-quality, dynamic summary using Python logic for 100% reliability.
         """
-        if not self.llm: return "AI Analyst is currently calibrating. Please check back shortly."
-        
-        print(f"--- Strategist Skill (Influencer Analytics): Received KPIs for analysis.")
-
-        # === THE "FILL-IN-THE-BLANKS" PROMPT ===
-        # Model ko ab sirf खाली jagah bharni hai.
-        prompt = f"""You are an AI Analyst. Your job is to complete the 2-sentence summary below using the provided data.
-DO NOT change the template. Only fill in the [adjective] and [actionable tip] placeholders.
-
-[DATA]
-- Engagement Rate: {kpis.get('avgEngagementRate', 0.0):.2f}%
-- Total Reach: {kpis.get('totalReach', 0)}
+        print(f"--- Strategist Skill (Influencer Analytics): Generating summary with RELIABLE PYTHON logic.")
 
-[TEMPLATE TO COMPLETE]
-"Your engagement rate is looking [adjective], which is great for building your community! To boost your reach even further, try to [actionable tip] on your next post."
-
-[YOUR COMPLETED SUMMARY]
-"""
-        
         try:
-            print("   - Calling LLM with Fill-in-the-Blanks prompt...")
-            response = self.llm(
-                prompt,
-                max_tokens=150,
-                temperature=0.8, # Thodi creativity allow karte hain adjective ke liye
-                stop=["[INST]", "[DATA]", "[TEMPLATE TO COMPLETE]", "\n\n"],
-                echo=False
-            )
-            raw_text = response['choices'][0]['text'].strip()
-
-            print(f"   - Raw AI Response: '{raw_text}'")
-
-            # --- PYTHON CLEANUP (FINAL VERSION) ---
-            summary_text = raw_text.replace("Answer:", "").strip()
-            
-            # Agar AI ne phir bhi quotes add kiye, to unhein hata do
-            if summary_text.startswith('"') and summary_text.endswith('"'):
-                summary_text = summary_text[1:-1]
+            engagement_rate = kpis.get('avgEngagementRate', 0.0)
+            reach = kpis.get('totalReach', 0)
+
+            # --- DYNAMIC SENTENCE GENERATION LOGIC ---
+
+            # Part 1: Adjective for engagement
+            if engagement_rate > 5.0:
+                adjective = "excellent"
+            elif engagement_rate > 2.5:
+                adjective = "solid"
+            else:
+                adjective = "good"
+
+            # Part 2: Actionable tip based on the most impactful metric
+            if reach < 1000 and engagement_rate < 3.0:
+                actionable_tip = "try collaborating with another creator to cross-promote and grow your audience."
+            elif engagement_rate < 2.0:
+                actionable_tip = "try asking a question in your next caption to boost comments and engagement."
+            else:
+                actionable_tip = "try using a trending audio or format on your next Reel to expand your reach."
+                
+            # Part 3: Combine everything into a perfect summary
+            summary = f"Your engagement rate is looking {adjective}, which is great for building community! To grow even further, {actionable_tip}"
             
-            # Agar AI ne galti se template repeat kiya, toh fallback message do
-            if "[adjective]" in summary_text or "[actionable tip]" in summary_text:
-                 print("   - ⚠️ AI failed to fill the template. Falling back to a default message.")
-                 return "Your performance analytics are looking solid! Keep creating great content to grow your reach."
-
-            print(f"   - ✅ LLM generated and CLEANED summary successfully: '{summary_text}'")
-            return summary_text
+            print(f"   - ✅ Python-generated summary: '{summary}'")
+            return summary
 
         except Exception as e:
-            print(f"--- Strategist Skill (Influencer Analytics) ERROR: {e}")
-            return "AI summary could not be generated at this time."
-
+            print(f"--- Strategist Skill (Influencer Analytics) PYTHON ERROR: {e}")
+            return "Analytics summary is currently unavailable due to a system error."
+            
 
     def generate_influencer_growth_plan(self, influencer_data: Dict[str, Any]) -> List[str]:
         """