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model_options.py

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+#!/usr/bin/env python3
+"""
+Model Options - Brello EI 0
+Created by Epic Systems | Engineered by Rehan Temkar
+
+Demonstrates different model options for Brello EI 0.
+"""
+
+from brello_ei_0 import BrelloEI0
+
+def test_model_option(model_path, description):
+    """Test a specific model option"""
+    print(f"\n🤖 Testing: {description}")
+    print(f"Model: {model_path}")
+    print("-" * 50)
+    
+    try:
+        # Load the model
+        model = BrelloEI0(
+            model_path=model_path,
+            load_in_4bit=False
+        )
+        
+        # Test emotional intelligence
+        test_message = "I'm feeling really stressed about my presentation tomorrow."
+        response = model.generate_response(test_message)
+        
+        print(f"Input: {test_message}")
+        print(f"Response: {response}")
+        print("✅ Model working!")
+        
+        return True
+    except Exception as e:
+        print(f"❌ Model failed: {e}")
+        return False
+
+def main():
+    """Test different model options"""
+    print("🤖 Brello EI 0 - Model Options")
+    print("Created by Epic Systems | Engineered by Rehan Temkar")
+    print("=" * 60)
+    
+    # Available model options
+    model_options = [
+        {
+            "path": "microsoft/DialoGPT-medium",
+            "description": "Public Model (Recommended for quick start)"
+        },
+        {
+            "path": "microsoft/DialoGPT-large", 
+            "description": "Larger Public Model (Better responses)"
+        },
+        {
+            "path": "microsoft/DialoGPT-small",
+            "description": "Smaller Public Model (Faster)"
+        }
+    ]
+    
+    # Test each model option
+    working_models = []
+    for option in model_options:
+        if test_model_option(option["path"], option["description"]):
+            working_models.append(option)
+    
+    print(f"\n📊 Results:")
+    print(f"✅ Working models: {len(working_models)}/{len(model_options)}")
+    
+    if working_models:
+        print("\n🎯 Recommended models:")
+        for model in working_models:
+            print(f"  • {model['path']} - {model['description']}")
+    
+    print("\n💡 To use Llama 3.2 3B:")
+    print("1. Create Hugging Face account")
+    print("2. Accept license at: https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct")
+    print("3. Login with: huggingface-cli login")
+    print("4. Update model_path to: 'meta-llama/Llama-3.2-3B-Instruct'")
+
+if __name__ == "__main__":
+    main()