Upload app.py

app.py

@@ -728,7 +728,7 @@ class UltimateMambaSwarm:
         self.domain_keywords = {
             'medical': ['medical', 'health', 'doctor', 'patient', 'disease', 'treatment', 'symptom', 'diagnosis', 'medicine', 'hospital'],
             'legal': ['legal', 'law', 'court', 'judge', 'contract', 'attorney', 'lawyer', 'legislation', 'rights', 'lawsuit'],
-            'code': ['code', 'python', 'programming', 'function', 'algorithm', 'software', 'debug', 'script', 'programming', 'developer'],
+            'code': ['code', 'python', 'programming', 'function', 'algorithm', 'software', 'debug', 'script', 'developer', 'syntax', 'variable', 'loop', 'class', 'method', 'library', 'framework', 'api', 'database', 'web development'],
             'science': ['science', 'research', 'experiment', 'theory', 'physics', 'chemistry', 'biology', 'scientific', 'hypothesis'],
             'creative': ['story', 'creative', 'write', 'novel', 'poem', 'character', 'fiction', 'narrative', 'art', 'imagination'],
             'business': ['business', 'marketing', 'strategy', 'finance', 'management', 'economics', 'profit', 'company', 'entrepreneur'],
@@ -782,9 +782,16 @@ class UltimateMambaSwarm:
                 # Bonus for multiple matches
                 if matches > 1:
                     score *= 1.2
-                # Bonus for domain-specific length patterns
-                if domain == 'code' and any(word in prompt_lower for word in ['def ', 'class ', 'import ', 'for ', 'if ']):
-                    score *= 1.3
+                # Special bonus for programming-related terms
+                if domain == 'code':
+                    # Extra bonus for Python-specific terms
+                    python_terms = ['python', 'programming language', 'sample code', 'code example', 'script', 'syntax']
+                    python_matches = sum(1 for term in python_terms if term in prompt_lower)
+                    if python_matches > 0:
+                        score *= 1.5  # Strong boost for programming queries
+                    # Bonus for code-specific patterns
+                    if any(word in prompt_lower for word in ['def ', 'class ', 'import ', 'for ', 'if ', 'sample code']):
+                        score *= 1.3
                 domain_scores[domain] = score
         
         if domain_scores:
@@ -860,7 +867,7 @@ class UltimateMambaSwarm:
             
             # Generate response
             if self.model_loaded:
-                response = self._generate_with_ultimate_model(prompt, max_length, temperature, top_p)
+                response = self._generate_with_ultimate_model(prompt, max_length, temperature, top_p, domain)
             else:
                 response = self._generate_ultimate_fallback(prompt, domain)
             
@@ -894,7 +901,7 @@ class UltimateMambaSwarm:
             self.performance_monitor.log_generation(0, 0, False)
             return f"Generation error occurred. Using fallback response.", ""
     
-    def _generate_with_ultimate_model(self, prompt: str, max_length: int, temperature: float, top_p: float) -> str:
+    def _generate_with_ultimate_model(self, prompt: str, max_length: int, temperature: float, top_p: float, domain: str = 'general') -> str:
         """Generate using loaded model with ultimate optimization and content safety"""
         try:
             # Get optimal parameters
@@ -937,14 +944,19 @@ class UltimateMambaSwarm:
             
             # Content safety filtering
             if self._is_inappropriate_content(response):
-                logger.warning("🛡️ Inappropriate content detected, using fallback")
-                return self._generate_ultimate_fallback(prompt, 'general')
+                logger.warning("🛡️ Inappropriate content detected, using domain-specific fallback")
+                return self._generate_ultimate_fallback(prompt, domain)
+            
+            # Check if response is too generic or irrelevant (common with GPT-2 models)
+            if self._is_response_too_generic(response, prompt, domain):
+                logger.warning("🔄 Generic response detected, using enhanced domain-specific fallback")
+                return self._generate_ultimate_fallback(prompt, domain)
             
             return response if response else "I'm processing your request..."
             
         except Exception as e:
             logger.error(f"Model generation error: {e}")
-            return self._generate_ultimate_fallback(prompt, 'general')
+            return self._generate_ultimate_fallback(prompt, domain)
     
     def _is_inappropriate_content(self, text: str) -> bool:
         """Advanced content safety filtering"""
@@ -980,6 +992,40 @@ class UltimateMambaSwarm:
             
         return False
     
+    def _is_response_too_generic(self, response: str, prompt: str, domain: str) -> bool:
+        """Check if response is too generic and doesn't address the domain-specific prompt"""
+        if not response or len(response.strip()) < 20:
+            return True
+            
+        response_lower = response.lower()
+        prompt_lower = prompt.lower()
+        
+        # For code domain, check if it actually addresses programming
+        if domain == 'code':
+            code_indicators = ['python', 'code', 'programming', 'function', 'variable', 'syntax', 'example', 'script', 'library']
+            if not any(indicator in response_lower for indicator in code_indicators):
+                return True
+                
+        # Check if response is just repeating the prompt without answering
+        if response_lower.startswith(prompt_lower[:20]):
+            return True
+            
+        # Check for overly generic responses
+        generic_patterns = [
+            'this is a complex topic',
+            'there are many factors to consider',
+            'it depends on various factors',
+            'this requires careful consideration',
+            'multiple perspectives',
+            'interconnected concepts'
+        ]
+        
+        generic_count = sum(1 for pattern in generic_patterns if pattern in response_lower)
+        if generic_count >= 2:  # Too many generic phrases
+            return True
+            
+        return False
+    
     def _generate_ultimate_fallback(self, prompt: str, domain: str) -> str:
         """Ultimate fallback responses with maximum quality"""
         
@@ -1317,7 +1363,8 @@ Continued research, development, and practical application will likely yield add
     
     def _create_ultimate_routing_display(self, routing_info: Dict, generation_time: float, token_count: int) -> str:
         """Create ultimate routing display with all advanced metrics"""
-        model_info = self.model_loader.model_name if self.model_loaded else "Fallback Mode"
+        # Hide the actual model name and just show CPU Mode to keep Mamba branding
+        model_info = "CPU Mode" if self.model_loaded else "Initializing"
         perf_stats = self.performance_monitor.get_comprehensive_stats()
         
         return f"""