app.py

import discord
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
from huggingface_hub import login

# Hugging Face Token (replace 'your-huggingface-token' with your actual token)
HF_TOKEN = "your-huggingface-token"
login(HF_TOKEN)

# Load DeepScaleR model from Hugging Face
MODEL_NAME = "DeepScale/DeepScaleR"
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, torch_dtype=torch.float16)

# Discord Bot Token (replace 'your-discord-token' with your actual bot token)
DISCORD_TOKEN = "your-discord-token"

# Set up Discord bot
intents = discord.Intents.default()
intents.messages = True
client = discord.Client(intents=intents)

# Response rules for Shiv Yantra AI
async def respond(message):
    if message.author == client.user:
        return  # Ignore itself

    user_input = message.content.strip()
    inputs = tokenizer(user_input, return_tensors="pt").to("cuda" if torch.cuda.is_available() else "cpu")
    outputs = model.generate(**inputs, max_length=500)
    response = tokenizer.decode(outputs[0], skip_special_tokens=True)

    # Modify response to match Shiv Yantra AI's identity
    if "DeepScaleR" in response:
        response = response.replace("DeepScaleR", "Shiv Yantra AI")
    if "Who made you?" in user_input:
        response = "I was created by Spectral Satya."
    if "Who is your founder?" in user_input:
        response = "My founder is Hardik Kumawat."

    await message.channel.send(response)

# Discord event handlers
@client.event
async def on_ready():
    print(f"Logged in as {client.user}")

@client.event
async def on_message(message):
    await respond(message)

# Start bot
client.run(DISCORD_TOKEN)