Update app.py

app.py

@@ -2,31 +2,30 @@ import gradio as gr
 import torch
 from transformers import pipeline
 import re
-import time
 
-# Initialize the model pipeline
-model_id = "openai/gpt-oss-120b"
-pipe = None
+# Choose a CPU-friendly fallback model
+# Change this to a GPU-optimized model if running with GPU
+DEFAULT_MODEL_ID = "tiiuae/falcon-7b-instruct"  # Much smaller & CPU-compatible
 
-def initialize_model():
-    global pipe
-    try:
-        pipe = pipeline(
-            "text-generation",
-            model=model_id,
-            torch_dtype="auto",
-            device_map="auto",
-        )
-        return "✅ Model loaded successfully!"
-    except Exception as e:
-        return f"❌ Error loading model: {str(e)}"
+# Automatically initialize the model pipeline
+try:
+    device = 0 if torch.cuda.is_available() else -1
+    pipe = pipeline(
+        "text-generation",
+        model=DEFAULT_MODEL_ID,
+        torch_dtype=torch.float32 if device == -1 else torch.float16,
+        device_map="auto" if device != -1 else None
+    )
+    model_status = f"✅ Model '{DEFAULT_MODEL_ID}' loaded successfully on {'GPU' if device != -1 else 'CPU'}!"
+except Exception as e:
+    pipe = None
+    model_status = f"❌ Error loading model: {str(e)}"
 
 def generate_code(prompt, task_type, language, max_tokens, temperature):
     if pipe is None:
-        return "❌ Model not initialized. Please load the model first.", ""
+        return "❌ Model not initialized. Please check logs.", ""
     
     try:
-        # Customize prompt based on task type
         if task_type == "Generate Code":
             system_prompt = f"You are an expert {language} programmer. Generate clean, optimized, and well-commented code for the following request:"
             full_prompt = f"{system_prompt}\n\n{prompt}\n\nCode:"
@@ -36,7 +35,7 @@ def generate_code(prompt, task_type, language, max_tokens, temperature):
         elif task_type == "Optimize Code":
             system_prompt = f"You are an expert {language} optimizer. Analyze and optimize the following code for better performance and readability:"
             full_prompt = f"{system_prompt}\n\n{prompt}\n\nOptimized Code:"
-        else:  # Explain Code
+        else:
             system_prompt = f"You are an expert {language} teacher. Explain the following code step by step:"
             full_prompt = f"{system_prompt}\n\n{prompt}\n\nExplanation:"
 
@@ -49,152 +48,44 @@ def generate_code(prompt, task_type, language, max_tokens, temperature):
         )
         
         generated_text = outputs[0]["generated_text"]
-        
-        # Extract code if it's wrapped in code blocks
         code_match = re.search(r'```(?:\w+\n)?(.*?)```', generated_text, re.DOTALL)
         if code_match:
             code_output = code_match.group(1).strip()
         else:
-            # For "Explain Code" task, code_output should hold explanation text instead
             code_output = generated_text.strip()
         
-        # Generate explanation based on the output
-        explanation = f"Task completed successfully! Generated {len(code_output)} characters of {language} code."
-        if task_type == "Fix Bugs":
-            explanation = "Bugs have been identified and fixed. Please review the corrected code."
-        elif task_type == "Optimize Code":
-            explanation = "Code has been optimized for better performance and readability."
-        elif task_type == "Explain Code":
-            explanation = "Code explanation provided below."
+        explanation = {
+            "Generate Code": f"Task completed successfully! Generated {len(code_output)} characters of {language} code.",
+            "Fix Bugs": "Bugs have been identified and fixed. Please review the corrected code.",
+            "Optimize Code": "Code has been optimized for better performance and readability.",
+            "Explain Code": "Code explanation provided below."
+        }[task_type]
         
         return code_output, explanation
         
     except Exception as e:
         return f"❌ Error generating code: {str(e)}", "Please try again with different parameters."
 
-# Custom CSS for modern UI
 css = """
-.gradio-container {
-    font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
-}
-.header {
-    text-align: center;
-    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
-    color: white;
-    padding: 2rem;
-    border-radius: 15px;
-    margin-bottom: 2rem;
-    box-shadow: 0 10px 30px rgba(0,0,0,0.2);
-}
-.header h1 {
-    font-size: 2.5rem;
-    font-weight: 700;
-    margin: 0;
-    text-shadow: 2px 2px 4px rgba(0,0,0,0.3);
-}
-.header p {
-    font-size: 1.2rem;
-    margin: 0.5rem 0 0 0;
-    opacity: 0.9;
-}
-.custom-button {
-    background: linear-gradient(135deg, #4facfe 0%, #00f2fe 100%);
-    border: none;
-    color: white;
-    font-weight: 600;
-    border-radius: 8px;
-    transition: all 0.3s ease;
-}
-.custom-button:hover {
-    transform: translateY(-2px);
-    box-shadow: 0 5px 15px rgba(79, 172, 254, 0.4);
-}
-.footer {
-    text-align: center;
-    margin-top: 3rem;
-    padding: 2rem;
-    background: linear-gradient(135deg, #2d3436 0%, #636e72 100%);
-    color: white;
-    border-radius: 15px;
-    box-shadow: 0 5px 15px rgba(0,0,0,0.1);
-}
-.footer h3 {
-    margin: 0 0 1rem 0;
-    font-size: 1.3rem;
-}
-.footer a {
-    color: #74b9ff;
-    text-decoration: none;
-    margin: 0 1rem;
-    font-weight: 500;
-    transition: color 0.3s ease;
-}
-.footer a:hover {
-    color: #0984e3;
-}
-.status-box {
-    padding: 1rem;
-    border-radius: 8px;
-    margin: 1rem 0;
-    font-weight: 500;
-}
-.code-output {
-    background: #1e1e1e;
-    border-radius: 8px;
-    border: 1px solid #333;
-}
-.explanation-output {
-    background: linear-gradient(135deg, #a8edea 0%, #fed6e3 100%);
-    border-radius: 8px;
-    padding: 1rem;
-}
+.gradio-container { font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; }
 """
 
-# Create the Gradio interface
 with gr.Blocks(css=css, title="AI Code Generator & Bug Fixer", theme=gr.themes.Soft()) as demo:
     
-    # Header
-    gr.HTML("""
-    <div class="header">
-        <h1>🚀 AI Code Generator & Bug Fixer</h1>
-        <p>Powered by Advanced AI • Generate, Fix, Optimize & Explain Code</p>
-    </div>
-    """)
-    
-    # Model initialization section
-    with gr.Row():
-        with gr.Column(scale=3):
-            model_status = gr.Textbox(
-                label="🤖 Model Status", 
-                value="Click 'Initialize Model' to load the AI model",
-                interactive=False
-            )
-        with gr.Column(scale=1):
-            init_btn = gr.Button(
-                "Initialize Model", 
-                variant="primary",
-                elem_classes=["custom-button"]
-            )
-    
-    gr.Markdown("---")
+    gr.HTML(f"<div class='header'><h1>🚀 AI Code Generator & Bug Fixer</h1><p>{model_status}</p></div>")
     
-    # Main interface
     with gr.Row():
         with gr.Column(scale=1):
-            gr.Markdown("### ⚙️ Configuration")
-            
             task_type = gr.Dropdown(
                 choices=["Generate Code", "Fix Bugs", "Optimize Code", "Explain Code"],
                 value="Generate Code",
                 label="🎯 Task Type"
             )
-            
             language = gr.Dropdown(
                 choices=["Python", "JavaScript", "Java", "C++", "C#", "Go", "Rust", "TypeScript", "PHP", "Ruby"],
                 value="Python",
                 label="💻 Programming Language"
             )
-            
             max_tokens = gr.Slider(
                 minimum=50,
                 maximum=1000,
@@ -202,7 +93,6 @@ with gr.Blocks(css=css, title="AI Code Generator & Bug Fixer", theme=gr.themes.S
                 step=50,
                 label="📏 Max Tokens"
             )
-            
             temperature = gr.Slider(
                 minimum=0.1,
                 maximum=1.0,
@@ -210,94 +100,23 @@ with gr.Blocks(css=css, title="AI Code Generator & Bug Fixer", theme=gr.themes.S
                 step=0.1,
                 label="🌡️ Temperature (Creativity)"
             )
-            
-            generate_btn = gr.Button(
-                "🚀 Generate/Fix Code",
-                variant="primary",
-                size="lg",
-                elem_classes=["custom-button"]
-            )
-            
         with gr.Column(scale=2):
-            gr.Markdown("### 📝 Input")
-            
             prompt = gr.Textbox(
                 label="Your Code Request or Buggy Code",
                 placeholder="Example: Create a function to sort a list of dictionaries by a specific key...",
                 lines=8
             )
-            
-            gr.Markdown("### 💡 Examples")
-            examples = gr.Examples(
-                examples=[
-                    ["Generate Code", "Python", "Create a REST API with FastAPI for user management with CRUD operations"],
-                    ["Fix Bugs", "JavaScript", "function calculateSum(arr) {\n  let sum = 0;\n  for (let i = 0; i <= arr.length; i++) {\n    sum += arr[i];\n  }\n  return sum;\n}"],
-                    ["Optimize Code", "Python", "def fibonacci(n):\n  if n <= 1:\n    return n\n  return fibonacci(n-1) + fibonacci(n-2)"],
-                    ["Explain Code", "Python", "class decorator(func):\n  def wrapper(*args, **kwargs):\n    print('Before')\n    result = func(*args, **kwargs)\n    print('After')\n    return result\n  return wrapper"]
-                ],
-                inputs=[task_type, language, prompt]
-            )
-    
-    gr.Markdown("---")
     
-    # Output section
     with gr.Row():
-        with gr.Column():
-            gr.Markdown("### 📤 Generated Code")
-            code_output = gr.Code(
-                label="Result",
-                language="python",
-                elem_classes=["code-output"]
-            )
-            
-            gr.Markdown("### 💬 AI Explanation")
-            explanation_output = gr.Textbox(
-                label="Analysis & Explanation",
-                lines=3,
-                elem_classes=["explanation-output"]
-            )
-    
-    # Footer
-    gr.HTML("""
-    <div class="footer">
-        <h3>🛠️ Built by Hariom Kumar Pandit</h3>
-        <p>
-            <a href="https://github.com/hari7261" target="_blank">🐙 GitHub: hari7261</a>
-            <a href="https://huggingface.co/hari7261" target="_blank">🤗 HuggingFace: hari7261</a>
-        </p>
-        <p style="margin-top: 1rem; font-size: 0.9rem; opacity: 0.8;">
-            Empowering developers with AI-assisted coding • Made with ❤️
-        </p>
-    </div>
-    """)
-    
-    # Event handlers
-    init_btn.click(
-        fn=initialize_model,
-        outputs=model_status
-    )
-    
+        code_output = gr.Code(label="Result", language="python")
+        explanation_output = gr.Textbox(label="Analysis & Explanation", lines=3)
+
+    generate_btn = gr.Button("🚀 Generate/Fix Code")
     generate_btn.click(
         fn=generate_code,
         inputs=[prompt, task_type, language, max_tokens, temperature],
         outputs=[code_output, explanation_output]
     )
-    
-    # Note: Dynamic update of the code block's language is tricky in Gradio.
-    # This is commented out as it won't update the existing gr.Code component properly.
-    # def update_code_language(lang):
-    #     return lang.lower()
-    # language.change(
-    #     fn=update_code_language,
-    #     inputs=language,
-    #     outputs=code_output.language
-    # )
 
-# Launch the app
 if __name__ == "__main__":
-    demo.launch(
-        server_name="0.0.0.0",
-        server_port=7860,
-        share=True,
-        debug=True
-    )
+    demo.launch(server_name="0.0.0.0", server_port=7860, share=True, debug=True)