Fix: pass context to _generate_response for persona/zone/trend/weather

reasoning_engine.py

@@ -101,8 +101,8 @@ class ReasoningEngine:
         # Stage 3: Multi-stage reasoning
         reasoning_result = self._reason(query, intent, staged_context)
         
-        # Stage 4: Generate response
-        response = self._generate_response(query, reasoning_result)
+        # Stage 4: Generate response (pass full context for persona/weather/zone)
+        response = self._generate_response(query, reasoning_result, context)
         
         # Stage 5: Generate followups
         followups = generate_followup_questions(
@@ -319,8 +319,9 @@ class ReasoningEngine:
             raw_response=response
         )
     
-    def _generate_response(self, query: str, result: ReasoningResult) -> str:
-        """Generate final user-facing response."""
+    def _generate_response(self, query: str, result: ReasoningResult, 
+                            context: Dict = None) -> str:
+        """Generate final user-facing response with persona and context."""
         diagnosis_data = {
             "diagnosis": result.final_diagnosis,
             "confidence": result.final_confidence,
@@ -330,11 +331,56 @@ class ReasoningEngine:
             "recommendation": result.recommendation
         }
         
+        # Extract persona instructions
+        persona = context.get("persona", {}) if context else {}
+        persona_instructions = persona.get("instructions", "Provide clear, helpful farming advice.")
+        
+        # Format conversation history
+        conv_history = context.get("conversation_history", []) if context else []
+        if conv_history:
+            history_text = "Recent conversation:\n"
+            for turn in conv_history[-3:]:
+                role = turn.get("role", "")
+                content = turn.get("content", "")[:100]
+                history_text += f"  {role.capitalize()}: {content}\n"
+        else:
+            history_text = "This is the first message in the conversation."
+        
+        # Format zone context
+        zone_data = context.get("zone_analysis", {}) if context else {}
+        if zone_data and zone_data.get("priority_zones"):
+            zones = zone_data["priority_zones"]
+            zone_text = "PRIORITY ZONES:\n"
+            for i, z in enumerate(zones[:3], 1):
+                zone_text += f"  {i}. {z.get('location', 'Zone')} - Stress: {z.get('stress_score', 0):.0%}\n"
+        else:
+            zone_text = "No zone-specific data available."
+        
+        # Format trend context
+        trend_data = context.get("historical_trends", {}) if context else {}
+        if trend_data.get("summary"):
+            trend_text = trend_data["summary"]
+        else:
+            trend_text = "No historical trend data available."
+        
+        # Format weather context
+        weather = context.get("weather", {}) if context else {}
+        if weather:
+            from prompts import format_weather_context
+            weather_text = format_weather_context(weather)
+        else:
+            weather_text = "No weather data available."
+        
         prompt = format_stage_prompt(
             RESPONSE_PROMPT,
             query=query,
             diagnosis=json.dumps(diagnosis_data, indent=2),
-            evidence=json.dumps(result.evidence_summary, indent=2)
+            evidence=json.dumps(result.evidence_summary, indent=2),
+            persona_instructions=persona_instructions,
+            conversation_history=history_text,
+            zone_context=zone_text,
+            trend_context=trend_text,
+            weather_context=weather_text
         )
         
         full_prompt = f"{SYSTEM_PROMPT}\n\n{prompt}"