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

core/strategist.py

@@ -173,49 +173,49 @@ Your Answer:
 
     def generate_analytics_insights(self, analytics_data: dict) -> str:
         """
-        [BULLETPROOF VERSION] Takes campaign analytics data and generates 3 actionable insights
-        using a very simple, direct prompt for small LLMs.
+        [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 unavailable."
-            
-        print(f"--- Strategist Skill (Analytics Insights): Received analytics data.")
+        print(f"--- Strategist Skill (Analytics Insights): Generating summary with RELIABLE PYTHON logic.")
+        
+        try:
+            reach = analytics_data.get('totalReach', 0)
+            engagement_rate = analytics_data.get('averageEngagementRate', 0.0)
+            top_influencer = analytics_data.get('topPerformingInfluencer', 'N/A')
 
-        # === THE "IDIOT-PROOF" SIMPLIFIED PROMPT ===
-        # Hum AI ko sirf 3 bullet points poora karne ko bol rahe hain.
-        prompt = f"""You are an expert campaign analyst.
-Analyze the data below and provide ONLY 3 short, actionable bullet points about the campaign's performance.
+            insights = []
 
-[CAMPAIGN DATA]
-- Total Reach: {analytics_data.get('totalReach', 0)}
-- Average Engagement Rate: {analytics_data.get('averageEngagementRate', 0.0):.2f}%
-- Top Performing Influencer: {analytics_data.get('topPerformingInfluencer', 'N/A')}
+            # Insight 1: Analyze Reach
+            if reach > 50000:
+                insights.append(f"- The campaign reached an impressive {reach:,} people, indicating strong initial visibility.")
+            elif reach > 0:
+                insights.append(f"- With a total reach of {reach:,}, the campaign is building a good foundation. Let's focus on amplifying this.")
+            else:
+                insights.append("- Campaign data is still being gathered. Initial reach numbers will appear here soon.")
 
-[YOUR 3 BULLET POINTS]
-- The total reach of {analytics_data.get('totalReach', 0)} is a good start.
-- """ # Hum pehla point khud shuru kar denge taaki AI ko hint mil jaaye.
-        
-        print("--- Strategist Skill (Analytics Insights): Sending simplified prompt to LLM...")
-        try:
-            response = self.llm(
-                prompt,
-                max_tokens=250,
-                temperature=0.7,
-                stop=["[SYSTEM]", "[CAMPAIGN DATA]", "User:", "\n\n-"], # Stop at new bullet points
-                echo=False
-            )
-            raw_text = response['choices'][0]['text'].strip()
+            # Insight 2: Analyze Engagement
+            if engagement_rate > 3.5:
+                insights.append(f"- The engagement rate is excellent at {engagement_rate:.2f}%. The content is clearly resonating with the audience.")
+            elif engagement_rate > 1.5:
+                insights.append(f"- The engagement rate of {engagement_rate:.2f}% is solid. A great next step is to encourage more comments and shares.")
+            else:
+                insights.append("- To boost the engagement rate, try creating more interactive content like polls or Q&A sessions.")
 
-            # Final response ko format karein
-            final_insights = "- The total reach of {:,} is a good start.\n- {}".format(analytics_data.get('totalReach', 0), raw_text)
+            # Insight 3: Analyze Top Performer
+            if top_influencer and top_influencer != "N/A":
+                insights.append(f"- Analyze the content from '{top_influencer}'. Their successful strategy should be replicated with other creators.")
+            else:
+                insights.append("- It is crucial to identify top-performing influencers early. This helps in doubling down on successful strategies.")
             
-            print("--- Strategist Skill (Analytics Insights): Successfully received and processed response.")
-            return final_insights
+            final_summary = "\n".join(insights)
+            print(f"   - ✅ Python-generated insights:\n{final_summary}")
             
+            return final_summary
+
         except Exception as e:
-            print(f"--- Strategist Skill (Analytics Insights) FATAL ERROR: {e}")
+            print(f"--- Strategist Skill (Analytics Insights) PYTHON ERROR: {e}")
             traceback.print_exc()
-            return "- AI insights could not be generated due to an internal model error."
+            return "- Analytics summary is currently unavailable due to a system error."
 
 
     def get_caption_assistance(self, caption: str, action: str, guidelines: str = None) -> str: