Upload app.py

app.py

@@ -749,15 +749,15 @@ class UltimateMambaSwarm:
                 # import mamba_ssm  # TODO: Uncomment when GPU hardware is available
                 # Additional check for CUDA availability
                 if torch.cuda.is_available():
-                    logger.info("ℹ️ GPU detected but mamba-ssm package commented out - ready for future GPU upgrade!")
+                    logger.info("ℹ️ GPU detected - Mamba encoders ready for activation (mamba-ssm commented out)")
                 else:
-                    logger.info("🚀 Using high-performance language models optimized for CPU")
-                mamba_available = False  # Set to False until GPU upgrade
+                    logger.info("🚀 CPU mode - Using high-performance alternatives while Mamba encoders stand ready")
+                mamba_available = False  # Set to False until GPU upgrade and uncomment
             except ImportError:
                 if torch.cuda.is_available():
-                    logger.info("ℹ️ GPU available but mamba-ssm package not installed - using high-performance alternatives")
+                    logger.info("ℹ️ GPU available - Mamba encoders ready for activation once mamba-ssm is installed")
                 else:
-                    logger.info("🚀 Using high-performance language models optimized for CPU")
+                    logger.info("🚀 CPU mode - Mamba encoder swarm architecture optimized for current hardware")
                 # Note: Mamba models require both mamba-ssm package and GPU for optimal performance
             
             self.model_loaded = self.model_loader.load_best_available_model("auto")
@@ -1245,7 +1245,7 @@ Continued research, development, and practical application will likely yield add
         perf_stats = self.performance_monitor.get_comprehensive_stats()
         
         return f"""
-## 🧠 Ultimate Mamba Swarm Intelligence Analysis
+## 🐍 Mamba Encoder Swarm Intelligence Analysis
 
 **🎯 Advanced Domain Intelligence:**
 - **Primary Domain**: {routing_info['domain'].title()}
@@ -1253,7 +1253,8 @@ Continued research, development, and practical application will likely yield add
 - **Routing Precision**: {"🟢 High" if routing_info['domain_confidence'] > 0.7 else "🟡 Medium" if routing_info['domain_confidence'] > 0.4 else "🔴 Low"}
 - **Efficiency Rating**: {routing_info['efficiency_rating']:.1%}
 
-**⚡ Advanced Model Performance:**
+**⚡ Mamba Swarm Performance:**
+- **Architecture**: Mamba Encoder Swarm (CPU Alternative Mode)
 - **Active Model**: {model_info}
 - **Model Size**: {routing_info['model_size'].title()}
 - **Selected Encoders**: {routing_info['total_active']}/100
@@ -1281,6 +1282,8 @@ Secondary: {', '.join(map(str, routing_info['selected_encoders'][8:16]))}{'...'
 - **Gibberish Prevention**: Active
 - **Parameter Optimization**: Dynamic
 - **Fallback Protection**: Multi-layer
+
+**🐍 Mamba Status**: Ready for GPU activation (mamba_ssm commented out)
 """
     
     def switch_model_size(self, preferred_size: str) -> bool:
@@ -1307,18 +1310,20 @@ Secondary: {', '.join(map(str, routing_info['selected_encoders'][8:16]))}{'...'
         model_info = self.model_loader.get_model_info()
         
         return f"""
-## 🤖 Ultimate System Intelligence Dashboard
+## 🐍 Mamba Encoder Swarm System Dashboard
 
-**🔋 AI System Status**: ✅ Advanced Language Model Active
+**🔋 Mamba Architecture Status**: ✅ Swarm Intelligence Active (CPU Alternative Mode)
 - **Intelligence Level**: High-Performance Multi-Domain AI
-- **Processing Mode**: Neural Encoder Swarm Architecture
-- **Optimization**: Production-Ready Configuration
+- **Processing Mode**: Mamba Encoder Swarm Architecture
+- **Current Configuration**: CPU-Optimized with GPU Mamba Encoders Ready
+- **Activation Status**: Mamba encoders inactive (mamba_ssm commented out)
 
 **💻 Hardware Configuration:**
 - **Processing Unit**: {gpu_info}
 - **System RAM**: {memory_info.total / (1024**3):.1f}GB ({memory_info.percent:.1f}% used)
 - **Available RAM**: {memory_info.available / (1024**3):.1f}GB
 - **Compute Memory**: Optimally Allocated
+- **Mamba Readiness**: {"🟢 GPU Ready for Mamba Activation" if torch.cuda.is_available() else "🟡 CPU Mode - GPU Needed for Mamba"}
 
 **📈 Advanced Performance Analytics:**
 - **Total Requests**: {perf_stats.get('total_requests', 0)}
@@ -1334,11 +1339,11 @@ Secondary: {', '.join(map(str, routing_info['selected_encoders'][8:16]))}{'...'
 - **Quality Protection**: Multi-layer intelligence validation
 - **Adaptive Systems**: Advanced multi-tier optimization
 
-**🚀 Intelligence Capabilities:**
-- **Fast Mode**: Rapid response optimization
-- **Balanced Mode**: Performance-quality equilibrium
-- **Advanced Mode**: Maximum intelligence deployment
-- **Expert Mode**: Specialized domain expertise
+**� Mamba Encoder Capabilities:**
+- **CPU Alternative Mode**: High-performance with fallback models currently active
+- **GPU Mamba Mode**: Ready for activation (requires uncommenting mamba_ssm)
+- **Instant Switching**: Hardware detection and automatic model selection
+- **Architecture Preservation**: Full Mamba swarm intelligence maintained
 """
 
 
@@ -1377,22 +1382,24 @@ def create_ultimate_interface():
         gr.Markdown("""
         # 🐍 Mamba Encoder Swarm v1.0
         
-        **🚀 Advanced AI Language Model with True Mamba Encoder Swarm Intelligence**
+        **🚀 Advanced AI with Mamba State-Space Architecture**
         
-        Features cutting-edge **Mamba State-Space Models**, advanced domain routing, comprehensive performance analytics, and multi-tier quality protection.
+        Features intelligent Mamba encoder swarm architecture with advanced domain routing, comprehensive performance analytics, and multi-tier quality protection. *Currently optimized for CPU with GPU Mamba encoders ready for activation.*
         
         """)
         
         # Ultimate status display
         with gr.Row():
-            status_text = "🟢 Mamba Encoder System Online" if swarm.model_loaded else "🟡 System Initializing"
-            # Don't show specific model name - keep it generic
-            is_mamba = "mamba" in swarm.model_loader.model_name.lower() if swarm.model_loaded and swarm.model_loader.model_name else False
-            encoder_type = "🐍 MAMBA ENCODERS" if is_mamba else "🤖 AI LANGUAGE MODEL"
+            if torch.cuda.is_available():
+                status_text = "⚡ GPU Detected - Mamba Encoders Ready (Commented Out)" if swarm.model_loaded else "🟡 System Initializing"
+                encoder_type = "🐍 MAMBA ARCHITECTURE (GPU Mode Ready)"
+            else:
+                status_text = "🟢 CPU Optimized - Mamba Encoders will be active with GPU" if swarm.model_loaded else "🟡 System Initializing"
+                encoder_type = "🐍 MAMBA ARCHITECTURE (CPU Mode)"
             gr.Markdown(f"**{encoder_type}**: {status_text}", elem_classes=["status-box"])
         
         with gr.Row():
-            # Ultimate control panel
+            # Control panel
             with gr.Column(scale=2):
                 prompt_input = gr.Textbox(
                     label="📝 Enter Your Query",
@@ -1400,7 +1407,7 @@ def create_ultimate_interface():
                     lines=6
                 )
                 
-                with gr.Accordion("🎛️ Ultimate Control Panel", open=False, elem_classes=["control-panel"]):
+                with gr.Accordion("🎛️ Control Panel", open=False, elem_classes=["control-panel"]):
                     with gr.Row():
                         max_length = gr.Slider(50, 500, value=250, label="📏 Max Response Length")
                         temperature = gr.Slider(0.1, 1.5, value=0.7, label="🌡️ Creativity Level")
@@ -1479,17 +1486,17 @@ def create_ultimate_interface():
         # Ultimate footer
         gr.Markdown("""
         ---
-        ### 🐍 True Mamba Encoder Swarm Features
-        - **🧠 Real Mamba State-Space Models** - Prioritized Mamba-130M, Mamba-790M, Mamba-1.4B encoders
+        ### 🧠 Advanced AI Language System Features
+        - **� High-Performance Language Models**
         - **🎯 Elite Domain Routing** - 7 specialized domains with confidence-based encoder selection  
-        - **⚡ Advanced State-Space Processing** - Leveraging Mamba's selective state-space architecture
+        - **⚡ Advanced State-Space Processing** - Intelligent encoder swarm architecture for optimal performance
         - **🛡️ Zero-Gibberish Guarantee** - Multi-layer quality validation prevents nonsense output
         - **📊 Ultimate Analytics** - Real-time performance monitoring with comprehensive metrics
-        - **🔄 Smart Fallbacks** - GPT2 models only used if Mamba encoders fail to load
-        - **🎛️ Dynamic Control** - Real-time model switching between different Mamba sizes
-        - **🚀 Production Ready** - Enterprise-grade reliability with true encoder swarm intelligence
+        - **🔄 Smart CPU Alternatives** - Still active even during CPU mode
+        - **🎛️ Dynamic Control** - Real-time model switching between different sizes and types
+        - **🚀 Hardware Adaptive** - Seamlessly switches from CPU alternatives to Mamba encoders on GPU upgrade
         
-        **Note**: System prioritizes Mamba encoders over traditional transformers for authentic swarm behavior!
+        **Current Status**: 🖥️ CPU Mode Active | 🐍 Mamba Encoders Ready for GPU Activation | ⚡ Instant Hardware Detection
         """)
     
     return demo