import gradio as gr
import pandas as pd
import logging
import sys
import os

from database import initialize_database, add_participant, get_participants_dataframe

# --- Logging Setup ---
logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
    handlers=[logging.StreamHandler(sys.stdout)]
)
logger = logging.getLogger('app_simple')

# --- Initial Setup ---
logger.info("Initializing database...")
initialize_database()

# --- Gradio UI Functions ---

def register_participant(name, email, linkedin, background, goals):
    """Callback function to register a new participant."""
    if not all([name, email]):
        return "Please provide at least a name and email.", get_participants_dataframe()
    
    participant_data = {
        "name": name,
        "email": email,
        "linkedin_profile": linkedin,
        "background": background,
        "goals": goals
    }
    try:
        add_participant(participant_data)
        feedback = f"✅ Success! Participant '{name}' registered."
        logger.info(f"Registered new participant: {email}")
    except Exception as e:
        feedback = f"❌ Error! Could not register participant. Reason: {e}"
        logger.error(f"Failed to register participant {email}: {e}")
        
    return feedback, get_participants_dataframe()

def refresh_participants_list():
    """Callback to reload the participant data from the database."""
    return get_participants_dataframe()

def mock_matching_process(organizer_criteria):
    """Mock function for the matching process (without using TinyCodeAgent)."""
    participants_df = get_participants_dataframe()
    if len(participants_df) < 2:
        logger.warning("Matching process aborted: not enough participants.")
        return "Cannot run matching with fewer than 2 participants."

    # Create a simple mock output
    result = f"""
## Team Matching Results

**Criteria used**: {organizer_criteria}

### Team 1
* **{participants_df['name'].iloc[0] if len(participants_df) > 0 else 'No participants'}**
* **{participants_df['name'].iloc[1] if len(participants_df) > 1 else 'No participants'}**

**Justification**: This is a mock team created for demonstration purposes.

### Team 2
* **{participants_df['name'].iloc[2] if len(participants_df) > 2 else 'No participants'}**
* **{participants_df['name'].iloc[3] if len(participants_df) > 3 else 'No participants'}**

**Justification**: This is another mock team created for demonstration purposes.

*Note: This is a simplified version without the AI matching. The full version would use TinyCodeAgent to create optimized teams.*
"""
    return result

# --- Gradio App Definition ---

with gr.Blocks(theme=gr.themes.Soft(), title="HackBuddyAI (Simple)") as app:
    gr.Markdown("# 🤖 HackBuddyAI (Simple Version)")
    gr.Markdown("*This is a simplified version without the AI matching component.*")
    
    with gr.Tabs():
        with gr.TabItem("👤 Participant Registration"):
            gr.Markdown("## Welcome, Participant!")
            gr.Markdown("Fill out the form below to register for the hackathon.")
            with gr.Row():
                with gr.Column():
                    name_in = gr.Textbox(label="Full Name")
                    email_in = gr.Textbox(label="Email Address")
                    linkedin_in = gr.Textbox(label="LinkedIn Profile URL", placeholder="Optional")
                with gr.Column():
                    background_in = gr.Textbox(label="Your Background & Skills", lines=5, placeholder="e.g., Python developer with 3 years of experience, specializing in Django and REST APIs...")
                    goals_in = gr.Textbox(label="Your Goals for this Hackathon", lines=5, placeholder="e.g., I want to learn about machine learning and work on a cool data visualization project...")
            
            submit_button = gr.Button("Register", variant="primary")
            registration_feedback = gr.Markdown()

        with gr.TabItem("👑 Organizer Dashboard"):
            gr.Markdown("## Welcome, Organizer!")
            gr.Markdown("Here you can view registered participants and run the team matching process.")
            
            with gr.Accordion("View Registered Participants", open=False):
                refresh_button = gr.Button("🔄 Refresh List")
                participants_df_out = gr.DataFrame(value=get_participants_dataframe, interactive=False)

            gr.Markdown("### Run Matching")
            organizer_criteria_in = gr.Textbox(
                label="Matching Criteria", 
                lines=4,
                value="Create teams of 3. Try to balance skills in each team (e.g., frontend, backend, data).",
                placeholder="Describe your ideal team composition..."
            )
            run_button = gr.Button("🚀 Run Matching", variant="primary")
            
            gr.Markdown("### 🤝 Matched Teams")
            matching_results_out = gr.Markdown("Matching has not been run yet.")

    # --- Event Handlers ---
    submit_button.click(
        fn=register_participant,
        inputs=[name_in, email_in, linkedin_in, background_in, goals_in],
        outputs=[registration_feedback, participants_df_out]
    )
    
    refresh_button.click(
        fn=refresh_participants_list,
        inputs=[],
        outputs=[participants_df_out]
    )

    run_button.click(
        fn=mock_matching_process,
        inputs=[organizer_criteria_in],
        outputs=[matching_results_out]
    )

# --- Launching the App ---
if __name__ == "__main__":
    try:
        logger.info("Launching Gradio app (simple version)...")
        # queue() is important for handling multiple users
        app.queue().launch(share=False)
    except KeyboardInterrupt:
        logger.info("Gradio app shutting down.")