Update tools_engine.py

tools_engine.py

@@ -1,27 +1,36 @@
 """
-Nexari Tools Engine (Dynamic Classifier)
+Nexari Tools Engine (Smart Override Edition)
 Author: Piyush
-Description: Provides the Neural Network for Intent Detection and Web Search capability.
+Description: Prevents silly mistakes on short messages by using a 'Hardcoded Logic Layer' before the Neural Network.
 """
 
 from duckduckgo_search import DDGS
 from transformers import pipeline
 
 print(">>> Tools: Loading Intent Classification Model...")
-# Loading the Brain
 intent_classifier = pipeline("zero-shot-classification", model="typeform/distilbert-base-uncased-mnli")
 
 def analyze_intent(user_text):
     """
-    Decides the specific intent of the user to route the request dynamically.
+    Decides intent with a Safety Layer for short greetings to prevent hallucination.
     """
-    # Updated Labels for Granular Control
+    text_lower = user_text.lower().strip()
+    
+    # === LAYER 1: HARDCODED SAFETY (The Fix for 'Hi' -> Searching) ===
+    # Agar user bas hello bol raha hai, to AI brain mat lagao. Direct chat karo.
+    direct_chat_triggers = ["hi", "hello", "hey", "hlo", "hola", "namaste", "what is your name", "who are you"]
+    
+    # Agar input EXACTLY inme se ek hai, ya start hota hai
+    if text_lower in direct_chat_triggers or any(text_lower.startswith(t + " ") for t in direct_chat_triggers):
+        print(f">>> Brain Override: Detected Greeting/Identity -> Force 'general conversation'")
+        return "general conversation"
+
+    # === LAYER 2: NEURAL NETWORK DECISION ===
     candidate_labels = [
         "internet search", 
         "general conversation", 
-        "coding or technical request", 
-        "checking time or date",  # <--- NEW: Time specific intent
-        "mathematical calculation"
+        "coding request", 
+        "checking time"
     ]
     
     try:
@@ -31,8 +40,8 @@ def analyze_intent(user_text):
         
         print(f">>> Brain: Detected '{top_intent}' ({confidence:.2f})")
         
-        # High confidence filter
-        if confidence > 0.4:
+        # Confidence Threshold badha diya (0.4 -> 0.5) taaki ghalat search na kare
+        if confidence > 0.5:
             return top_intent
     except Exception as e:
         print(f"Intent Error: {e}")
@@ -41,7 +50,7 @@ def analyze_intent(user_text):
 
 def perform_web_search(user_text):
     """
-    Executes search only when triggered by the Brain.
+    Executes search only when triggered.
     """
     try:
         clean_query = user_text.lower()