app.py

import discord
import os
import threading
from discord.ext import commands
import gradio_client
import gradio as gr
from gradio_client import Client
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
import asyncio
from collections import deque
import re
import random

DISCORD_TOKEN = os.environ.get("DISCORD_TOKEN", None)
intents = discord.Intents.all() 
bot = commands.Bot(command_prefix='!', intents=intents)

# Enhanced welcome system with AI
welcome_list = []
recent_introductions = deque(maxlen=15)  # Store last 15 full introductions for rich context
model = None
tokenizer = None

# Initialize the AI model
def initialize_ai_model():
    global model, tokenizer
    try:
        print("🤖 Loading BitNet AI model for personalized welcomes...")
        model_id = "microsoft/bitnet-b1.58-2B-4T"
        tokenizer = AutoTokenizer.from_pretrained(model_id)
        model = AutoModelForCausalLM.from_pretrained(
            model_id,
            torch_dtype=torch.bfloat16
        )
        print("✅ AI model loaded successfully!")
    except Exception as e:
        print(f"❌ Failed to load AI model: {e}")
        print("🔄 Falling back to traditional welcome messages...")

# Fallback welcome messages (original ones)
fallback_welcome_messages = [
    "Welcome to the community <:hugging_croissant:1103375763207622656>  \n",
    "Good to have you with us! :hugging: Got any cool projects you feel like sharing? :eyes:  \n",
    "Welcome aboard 🦜 ⛵  \n",
    "Hello friends! :wave: Where are you folks from? :globe_with_meridians: <:hugging_earth:968126923408564306>  \n",
    "Glad you're here! Welcome! 🎊  \n",
    "Happy to have you with us! <:blobcatlove:1103376097841790986> How much have you played around with ML/AI? :computer:  \n",    
    "New faces, new friends! Welcome! 😄👋  \n"
]

welcome_messages_counter = 0
wait_messages_counter = 0
channel_id = 900017973547388988 # 900017973547388988 = #introduce-yourself

def store_full_introduction(message_content, author_name):
    """Store the complete introduction message for rich AI context"""
    return {
        'author': author_name,
        'content': message_content,
        'timestamp': discord.utils.utcnow().isoformat()
    }

async def generate_ai_welcome_message(new_members, recent_context):
    """Generate a personalized welcome message using BitNet AI with full introduction context"""
    if not model or not tokenizer:
        return None
    
    try:
        # Build rich context from recent full introductions
        if recent_context:
            context_intros = "\n".join([
                f"- {intro['author']}: {intro['content'][:300]}..." if len(intro['content']) > 300 
                else f"- {intro['author']}: {intro['content']}"
                for intro in list(recent_context)[-8:]  # Use last 8 intros for context
            ])
        else:
            context_intros = "No recent introductions available."
        
        # Create the AI prompt with full context
        system_prompt = """You are a friendly, encouraging Discord community welcomer for a tech/AI community. 
        You'll be given recent introductions from community members to understand the vibe and interests.
        
        Generate a warm, personalized welcome message that:
        - Is enthusiastic and welcoming but not overwhelming
        - References themes or interests you notice from recent introductions
        - Asks an engaging question that connects to what people are discussing
        - Uses 1-2 relevant emojis
        - Keeps it concise (2-3 sentences max)
        - Feels natural and conversational
        
        DO NOT mention the new members' @ tags in your message - they will be added separately."""
        
        user_prompt = f"""Here are recent introductions from the community:

{context_intros}

Based on these introductions, generate a welcoming message for new members joining the community. Make it feel connected to what current members are sharing and interested in."""
        
        messages = [
            {"role": "system", "content": system_prompt},
            {"role": "user", "content": user_prompt},
        ]
        
        prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
        chat_input = tokenizer(prompt, return_tensors="pt").to(model.device)
        
        # Generate with controlled parameters
        with torch.no_grad():
            chat_outputs = model.generate(
                **chat_input, 
                max_new_tokens=100,
                do_sample=True,
                temperature=0.8,
                top_p=0.9,
                pad_token_id=tokenizer.eos_token_id
            )
        
        response = tokenizer.decode(
            chat_outputs[0][chat_input['input_ids'].shape[-1]:], 
            skip_special_tokens=True
        ).strip()
        
        # Clean up the response
        response = re.sub(r'\n+', ' ', response)
        response = response[:400]  # Limit length but allow more room
        
        return response
        
    except Exception as e:
        print(f"❌ AI generation failed: {e}")
        return None

@bot.event
async def on_ready():
    print(f'🤖 {bot.user} has landed! Ready to create amazing welcomes!')
    # Initialize AI model in background
    loop = asyncio.get_event_loop()
    await loop.run_in_executor(None, initialize_ai_model)

@bot.event
async def on_member_join(member):
    global welcome_list
    global welcome_messages_counter
    welcome_list.append(member.mention)
    
    if len(welcome_list) >= 8:
        channel = bot.get_channel(channel_id)
        print(f"channel: {channel}")
        
        # Check if the channel has received at least 3 messages from other users since the last bot message
        count = 0
        print(f"count: {count}")
        async for message in channel.history(limit=3):
            if message.author.bot:
                print(f"This is a bot message! -> {message.content}")
            else:
                count = count + 1
                print(f"count: {count}")
        
        if count == 3:
            print(f"count: {count}")
            
            # Try to generate AI welcome message
            ai_message = await generate_ai_welcome_message(welcome_list[:8], list(recent_introductions))
            
            if ai_message:
                # Use AI-generated message
                message = f'{ai_message} {" ".join(welcome_list[:8])}'
                print(f"🤖 Generated AI welcome: {message}")
            else:
                # Fallback to traditional messages
                message = f'{fallback_welcome_messages[welcome_messages_counter]} {welcome_list[0]} {welcome_list[1]} {welcome_list[2]} {welcome_list[3]} {welcome_list[4]} {welcome_list[5]} {welcome_list[6]} {welcome_list[7]}'
                if welcome_messages_counter == 6:
                    welcome_messages_counter = -1
                welcome_messages_counter = welcome_messages_counter + 1
                print(f"📝 Using fallback welcome message")
            
            await channel.send(message)
            welcome_list = []
    else:
        print(f"welcome_list: {welcome_list}")

@bot.event
async def on_message(message):
    # React to introductions
    if message.channel.id == 900017973547388988:
        await message.add_reaction('🤗')
        
        # Store full introduction for rich context (if it's not from a bot and has substantial content)
        if not message.author.bot and len(message.content) > 20:
            full_intro = store_full_introduction(message.content, message.author.display_name)
            recent_introductions.append(full_intro)
            print(f"📝 Stored full introduction from {message.author.display_name}: {message.content[:100]}...")
    
    await bot.process_commands(message)

# New command to test AI welcome generation
@bot.command(name='testwelcome')
async def test_welcome(ctx):
    """Test the AI welcome message generation (admin only)"""
    if not ctx.author.guild_permissions.administrator:
        await ctx.send("❌ Only admins can test this feature!")
        return
    
    # Generate a test welcome
    test_members = [ctx.author.mention]
    ai_message = await generate_ai_welcome_message(test_members, list(recent_introductions))
    
    if ai_message:
        await ctx.send(f"🤖 **AI Test Welcome:**\n{ai_message}")
    else:
        await ctx.send("❌ AI generation failed, check console for errors.")

@bot.command(name='recentintros')
async def recent_intros(ctx):
    """Show recent introductions stored for AI context (admin only)"""
    if not ctx.author.guild_permissions.administrator:
        await ctx.send("❌ Only admins can view stored introductions!")
        return
    
    if not recent_introductions:
        await ctx.send("📝 No recent introductions stored yet.")
        return
    
    intro_list = []
    for i, intro in enumerate(list(recent_introductions)[-5:], 1):  # Show last 5
        preview = intro['content'][:150] + "..." if len(intro['content']) > 150 else intro['content']
        intro_list.append(f"**{i}. {intro['author']}:** {preview}")
    
    intros_text = "\n\n".join(intro_list)
    await ctx.send(f"📝 **Recent Introductions (Last 5):**\n\n{intros_text}")

@bot.command(name='welcomestats')
async def welcome_stats(ctx):
    """Show welcome system statistics"""
    if not ctx.author.guild_permissions.administrator:
        await ctx.send("❌ Only admins can view stats!")
        return
    
    ai_status = "✅ Loaded" if model and tokenizer else "❌ Not loaded"
    intro_count = len(recent_introductions)
    waiting_count = len(welcome_list)
    
    stats_message = f"""📊 **Welcome System Stats**
🤖 AI Model: {ai_status}
📝 Full Intros Stored: {intro_count}/15
⏳ Members Waiting: {waiting_count}/8
🎯 Channel ID: {channel_id}"""
    
    await ctx.send(stats_message)

# Fun gradio interface
def greet(name):
    return f"Hello {name}! 🎉 The AI-powered Discord bot is running!"

DISCORD_TOKEN = os.environ.get("DISCORD_TOKEN", None)

def run_bot():
    bot.run(DISCORD_TOKEN)

# Start bot in separate thread
threading.Thread(target=run_bot).start()

# Launch Gradio interface
demo = gr.Interface(
    fn=greet, 
    inputs="text", 
    outputs="text",
    title="🤖 AI-Powered Discord Welcome Bot",
    description="Enhanced with BitNet b1.58 for personalized community welcomes!"
)
demo.launch()