fix: smart extraction of action from verbose LLM thinking output

GramAddict/core/navigation/brain.py

@@ -55,12 +55,32 @@ def ask_brain_for_action(
             result = response if isinstance(response, str) else response.get("response", "")
             result = result.strip().strip("'\"")
 
-            # Fuzzy match to available actions just in case
+            # 1. Exact match check (ideal case)
             for act in available_actions:
-                if act.lower() in result.lower():
+                if act.lower() == result.lower():
                     return act
+                    
+            # 2. Strict line-by-line check (often the model outputs the action on the last line)
+            for line in reversed(result.splitlines()):
+                line = line.strip().strip("'\"")
+                for act in available_actions:
+                    if act.lower() == line.lower():
+                        return act
 
-            logger.warning(f"🧠 [Brain] LLM returned an invalid action: '{result}'. Falling back.")
+            # 3. Fuzzy match (find the LAST mentioned action in the text, assuming it's the conclusion)
+            best_act = None
+            best_idx = -1
+            for act in available_actions:
+                idx = result.lower().rfind(act.lower())
+                if idx > best_idx:
+                    best_idx = idx
+                    best_act = act
+            
+            if best_act:
+                logger.warning(f"🧠 [Brain] Extracted action '{best_act}' from verbose LLM output.")
+                return best_act
+
+            logger.warning(f"🧠 [Brain] LLM returned an invalid action or no action found: '{result[:100]}...'. Falling back.")
     except Exception as e:
         logger.debug(f"🧠 [Brain] Error querying LLM: {e}")