Remove conversation history from LLM context to reduce tokens

prompts.py

@@ -908,16 +908,6 @@ def build_compact_context(context: Dict) -> str:
         if concerns and isinstance(concerns, list):
             lines.append(f"[CONCERNS] " + ", ".join(str(c)[:30] for c in concerns[:3]))
     
-    # --- Conversation History (for follow-ups) ---
-    conv = context.get("conversation_history", [])
-    if conv:
-        lines.append(f"[CONV] {len(conv)} prior turns")
-        if len(conv) > 0:
-            last = conv[-1]
-            role = last.get("role", "")
-            content = last.get("content", "")[:50]
-            lines.append(f"  Last: {role}: {content}...")
-    
     return "\n".join(lines) if lines else "No data"
 
 

reasoning_engine.py

@@ -372,16 +372,8 @@ class ReasoningEngine:
         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."
+        # Conversation history disabled to reduce token usage
+        history_text = ""
         
         # Format zone context
         zone_data = context.get("zone_analysis", {}) if context else {}