Update tools_engine.py

tools_engine.py

@@ -1,76 +1,70 @@
 """
-Nexari Tools Engine (Neural Network Edition)
+Nexari Tools Engine (Optimized)
 Author: Piyush
-Description: Uses a Zero-Shot Classification Model to detect intent intelligently.
+Description: Efficient Neural Intent Detection & Direct Search Execution.
 """
 
 from duckduckgo_search import DDGS
 import wikipedia
 from transformers import pipeline
 
-print(">>> Tools: Loading Intent Classification Model (Neural Network)...")
-# Hum ek lightweight model use kar rahe hain jo CPU par fast chale
-# "typeform/distilbert-base-uncased-mnli" is fast and accurate for intents
+print(">>> Tools: Loading Intent Classification Model...")
+# Load model once into memory
 intent_classifier = pipeline("zero-shot-classification", model="typeform/distilbert-base-uncased-mnli")
 
 def analyze_intent(user_text):
     """
-    Uses Neural Network to decide if the user wants to Search, Chat, or Calculate.
-    Returns: 'internet_search' or 'general_chat'
+    Decides the intent: 'internet search', 'coding request', or 'general conversation'.
     """
-    # Candidates labels defines what the AI looks for
     candidate_labels = ["internet search", "general conversation", "coding request", "mathematical calculation"]
     
-    # Run Classification
-    result = intent_classifier(user_text, candidate_labels)
-    
-    # Top prediction nikalo
-    top_intent = result['labels'][0]
-    confidence = result['scores'][0]
-    
-    print(f">>> Intent Detected: {top_intent} (Confidence: {confidence:.2f})")
-    
-    # Agar confidence 40% se zyada hai tabhi action lo
-    if confidence > 0.4:
-        return top_intent
+    try:
+        result = intent_classifier(user_text, candidate_labels)
+        top_intent = result['labels'][0]
+        confidence = result['scores'][0]
+        
+        print(f">>> Intent: {top_intent} ({confidence:.2f})")
+        
+        if confidence > 0.4:
+            return top_intent
+    except Exception as e:
+        print(f"Intent Error: {e}")
+        
     return "general_chat"
 
-def get_internet_context(user_text):
+def perform_web_search(user_text):
     """
-    Fetches data only if the Neural Network detects 'internet search' intent.
+    Directly executes search without re-analyzing intent.
+    Called specifically when app.py decides to search.
     """
-    
-    # === STEP 1: NEURAL INTENT CHECK ===
-    intent = analyze_intent(user_text)
-    
-    # Agar AI ko lagta hai ki ye search nahi hai, to khali laut jao
-    if intent != "internet search":
-        return ""
-
-    # === STEP 2: PERFORM SEARCH ===
     try:
-        # Query Cleaning: Common phrases hatao taaki search accurate ho
-        clean_query = user_text
-        remove_phrases = ["search for", "google", "find", "tell me about", "what is", "do you know", "latest info on"]
+        # Query Cleaning
+        clean_query = user_text.lower()
+        remove_phrases = ["search for", "google", "find", "tell me about", "what is", "do you know", "latest info on", "news about"]
         for phrase in remove_phrases:
-            clean_query = clean_query.lower().replace(phrase, "")
+            clean_query = clean_query.replace(phrase, "")
         
         clean_query = clean_query.strip()
-        if len(clean_query) < 2: return "" # Bahut choti query ignore karo
+        
+        # Fallback if query is empty
+        if len(clean_query) < 2: 
+            clean_query = user_text 
 
-        print(f">>> Tool: Searching for '{clean_query}'...")
+        print(f">>> Tool: Searching DuckDuckGo for '{clean_query}'...")
         results = DDGS().text(clean_query, max_results=3)
         
         if results:
             search_summary = "\n".join([f"- {r['title']}: {r['body']}" for r in results])
             return (
                 f"### REAL-TIME INTERNET DATA ###\n"
-                f"Intent Detected: Web Search\n"
+                f"Source: DuckDuckGo Web Search\n"
+                f"Topic: {clean_query}\n"
                 f"Results:\n{search_summary}\n\n"
-                f"INSTRUCTION: Use the above search results to answer the user's question."
+                f"INSTRUCTION: Use the above results to answer. If results are irrelevant, rely on your memory."
             )
+        else:
+            return "" # No results found
             
     except Exception as e:
-        print(f"Tool Error: {e}")
-    
-    return ""
+        print(f"Search Tool Error: {e}")
+        return ""