"""
Email Assistant Agent - Gradio Interface

This is the main application file that provides a Gradio web interface
for the AI-powered Email Assistant using OpenAI Agents SDK.
"""

import gradio as gr
import os
from agent import process_email


def load_email_examples() -> list:
    """
    Loads email examples from the external text file.
    
    Returns:
        list: List of email examples for the Gradio interface
    """
    examples_file = os.path.join(os.path.dirname(__file__), "email_examples.txt")
    
    try:
        with open(examples_file, 'r', encoding='utf-8') as f:
            content = f.read()
        
        # Split examples by the separator "---"
        examples = [example.strip() for example in content.split('---') if example.strip()]
        
        return examples
    except FileNotFoundError:
        print(f"Warning: Examples file not found at {examples_file}")
        return []
    except Exception as e:
        print(f"Error loading examples: {e}")
        return []


def flag_inappropriate_content(output_text: str) -> str:
    """
    Flags inappropriate content and saves it for review.
    
    Args:
        output_text (str): The output content to flag
        
    Returns:
        str: Confirmation message
    """
    import datetime
    
    # Create flagged content directory if it doesn't exist
    import os
    flagged_dir = "flagged_content"
    if not os.path.exists(flagged_dir):
        os.makedirs(flagged_dir)
    
    # Save flagged content with timestamp
    timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
    filename = f"{flagged_dir}/flagged_{timestamp}.txt"
    
    try:
        with open(filename, 'w', encoding='utf-8') as f:
            f.write(f"Flagged at: {datetime.datetime.now()}\n")
            f.write("=" * 50 + "\n")
            f.write(output_text)
        
        return f"✅ Content flagged and saved to {filename}"
    except Exception as e:
        return f"❌ Error saving flagged content: {str(e)}"


def process_email_interface(api_key: str, email_text: str) -> str:
    """
    Gradio interface function to process emails through the AI agent.
    
    Args:
        api_key (str): OpenAI API key
        email_text (str): Email content to process
        
    Returns:
        str: Formatted response with category, summary, and suggested reply
    """
    print("Starting email processing...")
    
    # Validate inputs first
    if not api_key or not api_key.strip():
        return "**Error:** OpenAI API key is required. Please enter your API key."
    
    if not email_text or not email_text.strip():
        return "**Error:** Email content is required. Please enter the email text to process."
    
    print("Inputs validated, calling process_email...")
    
    # Process the email through the agent
    result = process_email(email_text, api_key)
    
    print(f"Process email result: {result}")
    
    if not result['success']:
        return f"**Error:** {result['error']}"
    
    # Format the reply text for HTML display
    formatted_reply = result['reply']
    
    print("=" * 80)
    print("DEBUG: HTML FORMATTING IN APP.PY")
    print("=" * 80)
    print(f"Original reply from result: '{result['reply']}'")
    print(f"Reply length: {len(result['reply'])} characters")
    
    if formatted_reply:
        # Convert \n to HTML line breaks for proper rendering in Gradio
        formatted_reply = formatted_reply.replace('\n', '<br>')
        print(f"After HTML formatting: '{formatted_reply}'")
        print(f"Formatted reply length: {len(formatted_reply)} characters")
    else:
        print("WARNING: Reply is empty or None!")
    
    print("=" * 80)
    
    # Format the successful response
    response = f"""
## Email Analysis Results

### **Detected Category:** {result['category']}

### **Summary:**
{result['summary']}

### **Suggested Reply:**
{formatted_reply}

---
*Generated by Email Assistant Agent using OpenAI Agents SDK*
"""
    
    print("DEBUG: FINAL RESPONSE FOR GRADIO")
    print("=" * 80)
    print(f"Final response length: {len(response)} characters")
    print(f"Final response content:\n{response}")
    print("=" * 80)
    
    return response


def create_gradio_interface() -> gr.Blocks:
    """
    Creates and configures the Gradio interface for the Email Assistant.
    
    Returns:
        gr.Blocks: Configured Gradio interface with separate API key field
    """
    # Load email examples from external file
    email_examples = load_email_examples()
    
    with gr.Blocks(
        title="Email Assistant Agent",
        theme=gr.themes.Soft(),
        css="""
        .gradio-container {
            max-width: 1000px !important;
        }
        .main-header {
            text-align: center;
            margin-bottom: 2rem;
        }
        """
    ) as interface:
        
        gr.Markdown("""
        # Email Assistant Agent
        
        **Automatically classify, summarize, and respond to business emails using OpenAI Agents SDK.**
        
        This AI agent will:
        - **Classify** your email into categories (Inquiry, Complaint, Feedback, Other)
        - **Summarize** the content in two concise sentences  
        - **Generate** a professional reply suggestion
        
        **Note:** You need a valid OpenAI API key to use this service. The key is not stored and is only used for processing your request.
        
        **Flag Button:** Use the flag button to report inappropriate, offensive, or incorrect responses. This helps improve the AI's performance and ensures a better experience for all users.
        """)
        
        # Two-column layout
        with gr.Row():
            # Left column: API Key, Email input and controls
            with gr.Column(scale=1):
                api_key_input = gr.Textbox(
                    label="OpenAI API Key",
                    placeholder="Enter your OpenAI API key here...",
                    type="password",
                    info="Your API key is not stored and is only used for this session"
                )
                
                email_input = gr.Textbox(
                    label="Email Content",
                    placeholder="Paste your business email here...",
                    lines=10,
                    max_lines=20,
                    info="Enter the full email content you want to analyze"
                )
                
                # Examples for email content only
                gr.Examples(
                    examples=email_examples,
                    inputs=email_input,
                    label="Email Examples (click to load)"
                )
                
                with gr.Row():
                    submit_btn = gr.Button("Submit", variant="primary")
                    clear_btn = gr.Button("Clear", variant="secondary")
            
            # Right column: Output results
            with gr.Column(scale=1):
                output = gr.Markdown(
                    label="Analysis Results",
                    show_copy_button=True
                )
                
                # Manual flag button for inappropriate content
                with gr.Row():
                    flag_btn = gr.Button("🚩 Flag Inappropriate Content", variant="stop", size="sm")
                    flag_status = gr.Textbox(label="Flag Status", visible=False)
        
        # Connect the function with flagging
        submit_btn.click(
            fn=process_email_interface,
            inputs=[api_key_input, email_input],
            outputs=output,
            api_name="process_email"
        )
        
        clear_btn.click(
            fn=lambda: ("", ""),
            outputs=[api_key_input, email_input]
        )
        
        # Connect flag button
        flag_btn.click(
            fn=flag_inappropriate_content,
            inputs=output,
            outputs=flag_status
        )
    
    return interface


def main():
    """
    Main function to launch the Gradio interface.
    """
    # Create and launch the interface
    interface = create_gradio_interface()
    
    # Launch the interface
    interface.launch(
        server_name="0.0.0.0",  # Allow external connections for Hugging Face Spaces
        server_port=7860,       # Default Gradio port
        share=False,            # Don't create public link (for Hugging Face Spaces)
        show_error=True,        # Show errors in the interface
        quiet=False            # Show startup messages
    )


if __name__ == "__main__":
    main()