Frontend Fixed

Backend/api/routes.py

@@ -0,0 +1,74 @@
+import os
+import torch
+import psutil
+from flask import send_from_directory, jsonify, request
+
+def register_routes(app):
+    """Register HTTP routes for the application"""
+    
+    @app.route('/')
+    def index():
+        """Serve the main application page"""
+        return send_from_directory(app.static_folder, 'index.html')
+
+    @app.route('/voice-chat.js')
+    def serve_js():
+        """Serve the JavaScript file"""
+        return send_from_directory(app.static_folder, 'voice-chat.js')
+
+    @app.route('/api/status')
+    def system_status():
+        """Return the system status"""
+        # Import here to avoid circular imports
+        from api.app import models, DEVICE
+        
+        return jsonify({
+            "status": "ok",
+            "cuda_available": torch.cuda.is_available(),
+            "device": DEVICE,
+            "models": {
+                "generator": models.generator is not None,
+                "asr": models.whisperx_model is not None,
+                "llm": models.llm is not None
+            },
+            "versions": {
+                "transformers": "4.49.0",  # Replace with actual version
+                "torch": torch.__version__
+            }
+        })
+
+    @app.route('/api/system_resources')
+    def system_resources():
+        """Return system resource usage"""
+        # Import here to avoid circular imports
+        from api.app import active_conversations, DEVICE
+        
+        # Get CPU usage
+        cpu_percent = psutil.cpu_percent(interval=0.1)
+        
+        # Get memory usage
+        memory = psutil.virtual_memory()
+        memory_used_gb = memory.used / (1024 ** 3)
+        memory_total_gb = memory.total / (1024 ** 3)
+        memory_percent = memory.percent
+        
+        # Get GPU memory if available
+        gpu_memory = {}
+        if torch.cuda.is_available():
+            for i in range(torch.cuda.device_count()):
+                gpu_memory[f"gpu_{i}"] = {
+                    "allocated": torch.cuda.memory_allocated(i) / (1024 ** 3),
+                    "reserved": torch.cuda.memory_reserved(i) / (1024 ** 3),
+                    "max_allocated": torch.cuda.max_memory_allocated(i) / (1024 ** 3)
+                }
+        
+        return jsonify({
+            "cpu_percent": cpu_percent,
+            "memory": {
+                "used_gb": memory_used_gb,
+                "total_gb": memory_total_gb,
+                "percent": memory_percent
+            },
+            "gpu_memory": gpu_memory,
+            "active_sessions": len(active_conversations)
+        })