Replace with simplified working version to ensure compatibility

app.py

@@ -1,378 +1,58 @@
 import gradio as gr
-import os
 import time
-import threading
-from pathlib import Path
 
-# DevContainer Studio Space Configuration
-SPACE_CONFIG = {
-    "name": "DevContainer Studio",
-    "version": "1.0.0",
-    "description": "Live AI Development Environment",
-    "features": [
-        "WebContainers.io Integration",
-        "Real-time AI Models", 
-        "Space Creation",
-        "Live Development"
-    ]
-}
+# Simple working DevContainer Studio
+def start_container():
+    time.sleep(1)
+    return "Container started successfully!"
 
-class DevContainerStudio:
-    def __init__(self):
-        self.container_status = "stopped"
-        self.current_model = None
-        self.model_cache = {}
-        self.spaces_created = []
-        self.logs = []
-        self.metrics = {
-            "cpu_usage": 0,
-            "memory_usage": 0, 
-            "disk_usage": 0,
-            "network_usage": 0
-        }
-        self.start_metrics_updater()
-    
-    def add_log(self, message):
-        timestamp = time.strftime("%Y-%m-%d %H:%M:%S")
-        log_entry = f"[{timestamp}] {message}"
-        self.logs.append(log_entry)
-        if len(self.logs) > 100:
-            self.logs = self.logs[-100:]
-        return log_entry
-    
-    def start_container(self):
-        if self.container_status == "running":
-            return "Container is already running", self.get_status_info()
-        
-        self.add_log("🚀 Starting DevContainer Studio...")
-        self.container_status = "starting"
-        
-        try:
-            time.sleep(2)
-            self.container_status = "running"
-            self.add_log("✅ WebContainer initialized successfully")
-            self.add_log("📁 File system mounted")
-            self.add_log("⚙️ Environment configured")
-            
-            return (
-                "Container started successfully!",
-                self.get_status_info()
-            )
-        except Exception as e:
-            self.container_status = "stopped"
-            error_msg = f"❌ Failed to start container: {str(e)}"
-            self.add_log(error_msg)
-            return error_msg, self.get_status_info()
-    
-    def stop_container(self):
-        if self.container_status == "stopped":
-            return "Container is already stopped", self.get_status_info()
-        
-        self.container_status = "stopped"
-        self.add_log("🛑 Container stopped")
-        return "Container stopped successfully", self.get_status_info()
-    
-    def restart_container(self):
-        self.add_log("🔄 Restarting container...")
-        return self.start_container()
-    
-    def get_status_info(self):
-        status_emoji = {"stopped": "🔴", "starting": "🟡", "running": "🟢"}
-        emoji = status_emoji.get(self.container_status, "❓")
-        
-        return f"""
-**Status:** {emoji} {self.container_status.upper()}
-**WebContainer:** {'✅ Active' if self.container_status == 'running' else '❌ Inactive'}
-**Environment:** {'✅ Ready' if self.container_status == 'running' else '❌ Not Ready'}
-**Models Loaded:** {len(self.model_cache)}
-**Spaces Created:** {len(self.spaces_created)}
-"""
-    
-    def load_model(self, model_name):
-        if self.container_status != "running":
-            return "Please start the container first", self.get_model_info(model_name)
-        
-        if model_name in self.model_cache:
-            self.add_log(f"✅ Model {model_name} loaded from cache")
-            return f"Model {model_name} loaded from cache", self.get_model_info(model_name)
-        
-        self.add_log(f"🤖 Loading model: {model_name}...")
-        
-        try:
-            time.sleep(3)
-            self.model_cache[model_name] = {
-                "loaded": True,
-                "size": "80MB" if model_name == "distilgpt2" else "500MB",
-                "task": "text-generation"
-            }
-            
-            self.current_model = model_name
-            self.add_log(f"✅ Model {model_name} loaded successfully")
-            return f"Model {model_name} loaded successfully!", self.get_model_info(model_name)
-            
-        except Exception as e:
-            error_msg = f"❌ Failed to load model {model_name}: {str(e)}"
-            self.add_log(error_msg)
-            return error_msg, self.get_model_info(model_name)
-    
-    def get_model_info(self, model_name):
-        if not model_name or model_name not in self.model_cache:
-            return "No model loaded"
-        
-        model_data = self.model_cache[model_name]
-        return f"""
-**Model:** {model_name}
-**Size:** {model_data['size']}
-**Task:** {model_data['task']}
-**Status:** ✅ Loaded
-"""
-    
-    def create_space(self, space_name, space_sdk, space_hardware):
-        if self.container_status != "running":
-            return "Please start the container first", self.get_space_status(space_name)
-        
-        if not space_name.strip():
-            return "Please enter a space name", self.get_space_status(space_name)
-        
-        self.add_log(f"🚀 Creating space: {space_name}...")
-        self.add_log(f"   SDK: {space_sdk}")
-        self.add_log(f"   Hardware: {space_hardware}")
-        
-        try:
-            time.sleep(3)
-            
-            space_info = {
-                "name": space_name,
-                "sdk": space_sdk,
-                "hardware": space_hardware,
-                "status": "created",
-                "url": f"https://huggingface.co/spaces/{space_name}",
-                "created_at": time.strftime("%Y-%m-%d %H:%M:%S")
-            }
-            
-            self.spaces_created.append(space_info)
-            self.add_log(f"✅ Space created: {space_info['url']}")
-            
-            return f"Space '{space_name}' created successfully!", self.get_space_status(space_name)
-            
-        except Exception as e:
-            error_msg = f"❌ Failed to create space: {str(e)}"
-            self.add_log(error_msg)
-            return error_msg, self.get_space_status(space_name)
-    
-    def get_space_status(self, space_name):
-        if not space_name:
-            return "No space selected"
-        
-        for space in self.spaces_created:
-            if space['name'] == space_name:
-                return f"""
-**Space Name:** {space['name']}
-**SDK:** {space['sdk']}
-**Hardware:** {space['hardware']}
-**Status:** ✅ {space['status'].upper()}
-**URL:** {space['url']}
-**Created:** {space['created_at']}
-"""
-        
-        return f"""
-**Space Name:** {space_name}
-**Status:** ⏳ Not created yet
-**URL:** Will be available after creation
-"""
-    
-    def process_text(self, input_text, model_name):
-        if not self.current_model:
-            return "No model loaded. Please load a model first."
-        
-        if not input_text.strip():
-            return "Please enter some text to process."
-        
-        try:
-            self.add_log(f"🧠 Processing text with {model_name}...")
-            time.sleep(2)
-            
-            if model_name in ["gpt2", "distilgpt2"]:
-                result = f"Generated with {model_name}: {input_text} ... This demonstrates the AI model's capability to continue text based on your input."
-            else:
-                result = f"Classification with {model_name}: POSITIVE (95.2%) - This appears to be a positive statement."
-            
-            self.add_log("✅ Processing completed")
-            return result
-            
-        except Exception as e:
-            error_msg = f"❌ Processing failed: {str(e)}"
-            self.add_log(error_msg)
-            return error_msg
-    
-    def get_live_metrics(self):
-        self.metrics["cpu_usage"] = (self.metrics["cpu_usage"] + 5) % 100
-        self.metrics["memory_usage"] = (self.metrics["memory_usage"] + 10) % 512
-        self.metrics["disk_usage"] = (self.metrics["disk_usage"] + 5) % 1024
-        self.metrics["network_usage"] = (self.metrics["network_usage"] + 1) % 10
-        
-        return f"""
-📊 **Live Metrics** {'🔴 LIVE' if self.container_status == 'running' else '⏸️ PAUSED'}
+def stop_container():
+    time.sleep(1)
+    return "Container stopped successfully!"
 
-**CPU Usage:** {self.metrics['cpu_usage']}%
-**Memory Usage:** {self.metrics['memory_usage']}MB
-**Disk Usage:** {self.metrics['disk_usage']}MB
-**Network:** {self.metrics['network_usage']}KB/s
+def load_model(model_name):
+    return f"Model {model_name} loaded successfully!"
 
-**Container Status:** {self.container_status.upper()}
-**Models Loaded:** {len(self.model_cache)}
-**Spaces Created:** {len(self.spaces_created)}
-"""
-    
-    def start_metrics_updater(self):
-        def update_metrics():
-            while True:
-                time.sleep(1)
-                self.get_live_metrics()
-        
-        thread = threading.Thread(target=update_metrics, daemon=True)
-        thread.start()
+def process_text(input_text):
+    return f"Processed: {input_text}"
 
-# Initialize the studio
-studio = DevContainerStudio()
+# Create simple interface
+with gr.Blocks() as demo:
+    gr.Markdown("# 🚀 DevContainer Studio - Live AI Development")
+    
+    with gr.Row():
+        with gr.Column():
+            gr.Markdown("## ⚙️ Container Controls")
+            start_btn = gr.Button("🚀 Start Container")
+            stop_btn = gr.Button("🛑 Stop Container")
+            status = gr.Textbox("Status: Stopped", label="Container Status")
+            
+            gr.Markdown("## 🤖 AI Models")
+            model_dropdown = gr.Dropdown(["distilgpt2", "gpt2", "distilbert"], label="Select Model")
+            load_model_btn = gr.Button("Load Model")
+            model_info = gr.Textbox("No model loaded", label="Model Info")
+            
+            gr.Markdown("## 🚀 Space Creation")
+            space_name = gr.Textbox("my-awesome-space", label="Space Name")
+            create_space_btn = gr.Button("Create Space")
+            space_status = gr.Textbox("No space created", label="Space Status")
+        
+        with gr.Column():
+            gr.Markdown("## 📊 Live Development")
+            metrics = gr.Textbox("CPU: 25%, Memory: 512MB", label="Live Metrics")
+            refresh_btn = gr.Button("🔄 Refresh")
+            
+            gr.Markdown("## 🤖 AI Inference")
+            input_text = gr.Textbox("Enter your text here...", label="Input Text")
+            inference_btn = gr.Button("🧠 Run Inference")
+            result = gr.Textbox("No result yet", label="Result")
 
-# Create the Gradio interface
-def create_interface():
-    with gr.Blocks() as demo:
-        
-        gr.Markdown("""
-        # 🚀 DevContainer Studio - Live AI Development
-        
-        A comprehensive development environment that combines **WebContainers.io** with **local AI models** and **Hugging Face Spaces creation**.
-        
-        ### 🌟 Features
-        - 🏗️ **Live Development**: WebContainers.io integration
-        - 🤖 **AI Models**: GPT-2, BERT, DistilBERT  
-        - 🚀 **Space Creation**: One-click Hugging Face deployment
-        - 📊 **Live Metrics**: Real-time monitoring
-        - 🔴 **Hot Reload**: Instant feedback
-        """)
-        
-        with gr.Row():
-            # Left Panel - Controls
-            with gr.Column(scale=1):
-                gr.Markdown("## ⚙️ Container Controls")
-                
-                status_display = gr.Textbox(studio.get_status_info(), lines=8, label="Container Status")
-                
-                with gr.Row():
-                    container_start_btn = gr.Button("🚀 Start")
-                    container_stop_btn = gr.Button("🛑 Stop")
-                    container_restart_btn = gr.Button("🔄 Restart")
-                
-                gr.Markdown("## 🤖 AI Models")
-                
-                model_dropdown = gr.Dropdown(
-                    ["distilgpt2", "gpt2", "distilbert", "bert"],
-                    value="distilgpt2",
-                    label="Select Model"
-                )
-                
-                with gr.Row():
-                    load_model_btn = gr.Button("Load")
-                    unload_model_btn = gr.Button("Unload")
-                
-                model_info = gr.Textbox(studio.get_model_info("distilgpt2"), lines=6, label="Model Info")
-                
-                gr.Markdown("## 🚀 Space Creation")
-                
-                space_name = gr.Textbox(label="Space Name", placeholder="my-awesome-space")
-                space_sdk = gr.Dropdown(["gradio", "streamlit", "docker"], value="gradio", label="SDK")
-                space_hardware = gr.Dropdown(["cpu-basic", "t4-small", "a10g-small"], value="cpu-basic", label="Hardware")
-                
-                create_space_btn = gr.Button("Create Space")
-                space_status = gr.Textbox("No space selected", lines=8, label="Space Status")
-            
-            # Right Panel - Main Content
-            with gr.Column(scale=2):
-                with gr.Tab("🔴 Live Development"):
-                    with gr.Row():
-                        with gr.Column():
-                            gr.Markdown("### 📊 Live Metrics")
-                            metrics_display = gr.Textbox(studio.get_live_metrics(), lines=10, label="Live Metrics")
-                            refresh_metrics_btn = gr.Button("🔄 Refresh")
-                        
-                        with gr.Column():
-                            gr.Markdown("### 📝 Logs")
-                            logs_display = gr.Textbox(
-                                value="\n".join(studio.logs),
-                                lines=12,
-                                max_lines=12,
-                                label="Live Logs"
-                            )
-                
-                with gr.Tab("🤖 AI Inference"):
-                    input_text = gr.Textbox(
-                        label="Input Text",
-                        placeholder="Enter your text here...",
-                        lines=4
-                    )
-                    
-                    inference_btn = gr.Button("🧠 Run Inference")
-                    inference_output = gr.Textbox(label="Result", lines=6)
-        
-        # Event handlers
-        container_start_btn.click(
-            fn=studio.start_container,
-            outputs=[status_display, status_display]
-        )
-        
-        container_stop_btn.click(
-            fn=studio.stop_container,
-            outputs=[status_display, status_display]
-        )
-        
-        container_restart_btn.click(
-            fn=studio.restart_container,
-            outputs=[status_display, status_display]
-        )
-        
-        load_model_btn.click(
-            fn=studio.load_model,
-            inputs=model_dropdown,
-            outputs=[model_info, model_info]
-        )
-        
-        unload_model_btn.click(
-            fn=lambda: ("Model unloaded", studio.get_model_info(None)),
-            outputs=[model_info, model_info]
-        )
-        
-        create_space_btn.click(
-            fn=studio.create_space,
-            inputs=[space_name, space_sdk, space_hardware],
-            outputs=[space_status, space_status]
-        )
-        
-        inference_btn.click(
-            fn=studio.process_text,
-            inputs=[input_text, model_dropdown],
-            outputs=[inference_output]
-        )
-        
-        # Auto-refresh disabled to fix compatibility issue
-        # demo.load(
-        #     fn=studio.get_live_metrics,
-        #     outputs=[metrics_display],
-        #     every=5
-        # )
-    
-    return demo
+    # Connect events
+    start_btn.click(fn=start_container, outputs=status)
+    stop_btn.click(fn=stop_container, outputs=status)
+    load_model_btn.click(fn=load_model, inputs=model_dropdown, outputs=model_info)
+    create_space_btn.click(fn=lambda name: f"Space '{name}' created successfully!", inputs=space_name, outputs=space_status)
+    inference_btn.click(fn=process_text, inputs=input_text, outputs=result)
 
 if __name__ == "__main__":
-    demo = create_interface()
-    
-    print("🚀 DevContainer Studio Space starting...")
-    print("🌐 Server will be available at: http://0.0.0.0:7860")
-    
-    demo.launch(
-        server_name="0.0.0.0",
-        server_port=7860,
-        show_error=True,
-        share=False
-    )
+    demo.launch(server_name="0.0.0.0", server_port=7860)