import csv
import discord
from discord.ext import commands
from groq import Groq
from surprise import SVD, Dataset, Reader

GROQ_API_KEY = "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"
DISCORD_TOKEN = "MTUyOTIyMTE0NjIzNzU5OTg1NQ.GS88u5.LK7oXe3F1B0_jdTqemPRBkcxlT4HiGXJdOLwaE"

ITEM_PATH = r"C:\Users\aadid\PycharmProjects\PythonProject\ml-100k\ml-100k\u.item"
DATA_PATH = r"C:\Users\aadid\PycharmProjects\PythonProject\ml-100k\ml-100k\u.data"


movies = []
movie_id_to_title = {}

with open(ITEM_PATH, "r", encoding="utf-8", errors="replace") as file:
    reader = csv.reader(file, delimiter="|")
    for row in reader:
        if len(row) > 1:
            movies.append(row)
            movie_id_to_title[row[0]] = row[1]

print("Movies loaded:", len(movies))
reader = Reader(line_format="user item rating timestamp", sep="\t")
data = Dataset.load_from_file(DATA_PATH, reader=reader)

trainset = data.build_full_trainset()
svd_algo = SVD()
svd_algo.fit(trainset)
print("Surprise SVD Model trained successfully!")

client = Groq(api_key=GROQ_API_KEY)

intents = discord.Intents.default()
intents.message_content = True

bot = commands.Bot(command_prefix="!", intents=intents)

conversation = {}

system_prompt = """
You are ZenAI, an AI assistant inside Discord, made by Aadidev.

You are helpful, natural, and clear.

Help users with:
- Movies
- Games
- Coding
- School
- Science
- Technology
- General questions

MOVIES:
When a user asks for movie recommendations:
First ask:
- What genres do you like?
- What age rating are you comfortable with?
- What movies have you enjoyed before?

Use the user's answers to recommend movies.

For every movie recommendation include:
- Movie title
- Short description
- Rating out of 10
- Why they might like it

Use the dataset provided when possible.

GAMES:
When a user asks for game recommendations:
First ask:
- What genres they like
- What platform they play on
- Multiplayer or story preference

For each game include:
- Title
- Genre
- Platform
- Short description
- Rating out of 10
- Why they might enjoy it

Do not use unnecessary greetings.
Do not end every answer with a question.
"""

def get_svd_recommendations(user_id_str="1", top_n=10):
    predictions = []
    for item_id, title in movie_id_to_title.items():
        pred = svd_algo.predict(uid=user_id_str, iid=item_id)
        predictions.append((title, pred.est))

    predictions.sort(key=lambda x: x[1], reverse=True)
    return predictions[:top_n]

@bot.event
async def on_ready():
    print(f"Logged in as {bot.user}")
@bot.event
async def on_message(message):
    if message.author == bot.user:
        return
    user_id = str(message.author.id)
    if user_id not in conversation:
        conversation[user_id] = []

    user_message = message.content.strip()
    if user_message == "":
        return

    conversation[user_id].append({"role": "user", "content": user_message})

    dataset_info = ""
    if "movie" in user_message.lower():
        svd_recs = get_svd_recommendations(user_id_str="1", top_n=15)
        rec_titles = [f"{title} (SVD Score: {score:.2f})" for title, score in svd_recs]
        dataset_info = f"""
Here are top recommended movie titles generated by the Surprise SVD Collaborative Filtering algorithm:
{rec_titles}
Use these high-scoring SVD predictions to curate recommendations for the user.
"""
    messages = [{"role": "system", "content": system_prompt + dataset_info}]
    messages.extend(conversation[user_id][-10:])
    try:
        async with message.channel.typing():
            response = client.chat.completions.create(
                model="llama-3.3-70b-versatile",
                messages=messages,
                temperature=0.5,
                max_tokens=1000,
            )
            answer = response.choices[0].message.content
        conversation[user_id].append({"role": "assistant", "content": answer})
        await message.channel.send(answer)
    except Exception as e:
        print(e)
        await message.channel.send("Error connecting to AI.")
    await bot.process_commands(message)
bot.run("MTUyOTIyMTE0NjIzNzU5OTg1NQ.GS88u5.LK7oXe3F1B0_jdTqemPRBkcxlT4HiGXJdOLwaE")