import gradio as gr
from openai import OpenAI
import os

ACCESS_TOKEN = os.getenv("HF_TOKEN")

client = OpenAI(
    base_url="https://api-inference.huggingface.co/v1/", 
    api_key=ACCESS_TOKEN,
)

def generate_python_program(
    program_type,
    difficulty,
    features,
    documentation_level,
    optimization_focus,
    output_format
):
‎    # توضیحات ویژگی‌ها برای تولید کد
    feature_prompts = {
        "Basic Functionality": "Include fundamental features and functionalities.",
        "Intermediate Features": "Add modularity, error handling, and input validation.",
        "Advanced Features": "Incorporate advanced libraries, multithreading, or optimization techniques.",
    }
    
    doc_prompts = {
        "Minimal": "Provide minimal inline comments for understanding.",
        "Moderate": "Include detailed comments explaining key parts of the code.",
        "Comprehensive": "Provide full documentation, including docstrings and usage examples.",
    }
    
    optimization_prompts = {
        "Readability": "Focus on writing clean and readable code.",
        "Performance": "Prioritize optimizing performance and resource usage.",
        "Scalability": "Ensure the code can handle large-scale use cases effectively.",
    }

    base_prompt = f"""
    Act as an expert Python programmer and code generator.
    Generate a Python program with the following requirements:
    - Program Type: {program_type}
    - Difficulty Level: {difficulty}
    - Features: {feature_prompts[features]}
    - Documentation Level: {doc_prompts[documentation_level]}
    - Optimization Focus: {optimization_prompts[optimization_focus]}
    - Output Format: {output_format}

    Additional Requirements:
    - Ensure code is executable and error-free.
    - Include best practices for Python development.
    - If libraries are required, mention installation instructions.
    - Add a test case or example usage if applicable.
    """

    try:
        messages = [
            {"role": "system", "content": "You are an expert Python code generator."},
            {"role": "user", "content": base_prompt}
        ]
        
        response = client.chat.completions.create(
            model="Qwen/QwQ-32B-Preview",
            messages=messages,
            max_tokens=2048,
            temperature=0.7,
            top_p=0.9
        )
        
        return response.choices[0].message.content
    
    except Exception as e:
        return f"An error occurred: {str(e)}\nPlease try again with different parameters."

def create_interface():
    with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue")) as iface:
        gr.Markdown("""
        # <div align="center"><strong>🛠️ Python Program Generator</strong></div>
        
        Welcome to your personalized Python program generator! This tool allows you to:
        - Create executable Python programs
        - Customize features, difficulty, and optimization focus
        - Receive well-documented and ready-to-run code
        
        Unlock the power of Python programming today! 🚀
        """)
        
        with gr.Row():
            with gr.Column():
                program_type = gr.Textbox(
                    label="Program Type",
                    placeholder="Describe the type of program (e.g., 'calculator', 'web scraper', 'data visualizer')",
                    lines=2
                )
                
                difficulty = gr.Radio(
                    choices=["Beginner", "Intermediate", "Advanced"],
                    label="Difficulty Level",
                    value="Intermediate",
                    info="Choose based on the complexity of the program"
                )
                
                features = gr.Radio(
                    choices=[
                        "Basic Functionality",
                        "Intermediate Features",
                        "Advanced Features"
                    ],
                    label="Features",
                    value="Basic Functionality",
                    info="Select the level of features for your program"
                )
                
                documentation_level = gr.Radio(
                    choices=["Minimal", "Moderate", "Comprehensive"],
                    label="Documentation Level",
                    value="Moderate",
                    info="Choose the level of inline comments and documentation"
                )
                
                optimization_focus = gr.Radio(
                    choices=["Readability", "Performance", "Scalability"],
                    label="Optimization Focus",
                    value="Readability",
                    info="Specify the main focus for optimization"
                )
                
                output_format = gr.Radio(
                    choices=["Executable Code", "Code with Explanation", "Both"],
                    label="Output Format",
                    value="Both",
                    info="Choose how the output should be structured"
                )
                
                submit_btn = gr.Button(
                    "Generate Python Program",
                    variant="primary"
                )

            with gr.Column():
                output = gr.Textbox(
                    label="Generated Python Program",
                    lines=20,
                    show_copy_button=True
                )
        
        # Example scenarios
        gr.Examples(
            examples=[
                [
                    "Calculator for basic arithmetic",
                    "Beginner",
                    "Basic Functionality",
                    "Minimal",
                    "Readability",
                    "Executable Code"
                ],
                [
                    "Web scraper for extracting data from websites",
                    "Intermediate",
                    "Intermediate Features",
                    "Moderate",
                    "Performance",
                    "Code with Explanation"
                ],
                [
                    "Machine Learning model trainer",
                    "Advanced",
                    "Advanced Features",
                    "Comprehensive",
                    "Scalability",
                    "Both"
                ]
            ],
            inputs=[
                program_type,
                difficulty,
                features,
                documentation_level,
                optimization_focus,
                output_format
            ],
            outputs=output,
            fn=generate_python_program,
            cache_examples=True
        )
        
        # Usage tips
        gr.Markdown("""
        ### 💡 Tips for Best Results
        1. **Be Specific** with your program description - instead of "Tool", try "File Organizer".
        2. **Match the Difficulty** to your programming experience.
        3. **Experiment with Features** to customize your program.
        4. **Choose the Right Focus** for optimization based on your needs.
        
        ### 🎯 Documentation Options
        - **Minimal**: Quick and simple understanding.
        - **Moderate**: Key parts of the code are well-explained.
        - **Comprehensive**: Detailed docstrings and examples included.
        
        ### 🌟 Remember
        - Test your code after generation.
        - Modify the generated code for better personalization.
        - Use the examples to explore various possibilities.
        """)
        
        submit_btn.click(
            fn=generate_python_program,
            inputs=[
                program_type,
                difficulty,
                features,
                documentation_level,
                optimization_focus,
                output_format
            ],
            outputs=output
        )
    
    return iface

if __name__ == "__main__":
    iface = create_interface()
    iface.launch()