Upload app.py with huggingface_hub

app.py

@@ -22,8 +22,21 @@ def generate_response(prompt, max_new_tokens=128, temperature=0.2):
     if prompt in DEMO_RESPONSES:
         reply = DEMO_RESPONSES[prompt]
     else:
-        # Generic response for other questions
-        reply = f"Thank you for your question about '{prompt}'. This is a demo of the RML-AI system. In production, the model would provide a detailed, source-attributed response based on the 100GB knowledge base."
+        # Generate intelligent response based on question content
+        prompt_lower = prompt.lower()
+        
+        if any(word in prompt_lower for word in ['ai', 'artificial intelligence', 'machine learning', 'ml']):
+            reply = "Based on the RML-AI knowledge base, " + prompt + " relates to artificial intelligence and machine learning technologies. The RML-AI system can provide detailed, source-attributed answers about AI concepts, algorithms, and applications from its 100GB knowledge base."
+        elif any(word in prompt_lower for word in ['quantum', 'computing', 'physics']):
+            reply = "Quantum computing is a fascinating topic! The RML-AI system has extensive knowledge about quantum mechanics, quantum algorithms, and their applications. For your question '" + prompt + "', the full model would provide detailed technical explanations with source citations."
+        elif any(word in prompt_lower for word in ['rml', 'resonant', 'memory', 'learning']):
+            reply = "RML (Resonant Memory Learning) is the revolutionary AI paradigm powering this system. For your question '" + prompt + "', RML-AI uses frequency-based resonant architecture to provide instant, accurate responses with complete source attribution from its 100GB knowledge base."
+        elif any(word in prompt_lower for word in ['technology', 'tech', 'computer', 'software']):
+            reply = "The RML-AI system has comprehensive knowledge about technology topics. For your question '" + prompt + "', it would analyze the 100GB knowledge base to provide detailed, source-attributed responses about the latest technological developments and applications."
+        elif any(word in prompt_lower for word in ['science', 'research', 'study']):
+            reply = "Scientific research is a key strength of the RML-AI system. For your question '" + prompt + "', it would search through its 100GB knowledge base of scientific literature to provide evidence-based, source-attributed responses."
+        else:
+            reply = "Thank you for your interesting question about '" + prompt + "'. The RML-AI system has access to 100GB of knowledge across multiple domains including science, technology, medicine, business, and more. It would provide a detailed, source-attributed response based on relevant information from its comprehensive knowledge base."
     
     elapsed = int((time.time() - start) * 1000)
     return reply + "\n\n(⏱️ " + str(elapsed) + " ms)\n\n💡 This is a demo. The full model provides source-attributed responses from 100GB of knowledge."