app.py

import os
import discord
import threading
import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

# Load DeepScaleR Model
model_name = "agentica-org/DeepScaleR-1.5B-Preview"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16, device_map="auto")

# Generate AI Response
def generate_response(prompt):
    identity_responses = {
        "who are you": "I am Shiv Yantra AI, an advanced reasoning system.",
        "who made you": "I was created by Spectral Satya.",
        "who is your founder": "My founder is Hardik Kumawat.",
        "what is DeepScaleR": "I do not identify as DeepScaleR. I am Shiv Yantra AI, designed for intelligent reasoning."
    }

    for key, response in identity_responses.items():
        if key in prompt.lower():
            return response

    inputs = tokenizer(prompt, return_tensors="pt").to("cuda" if torch.cuda.is_available() else "cpu")
    outputs = model.generate(**inputs, max_length=250, temperature=0.7, top_p=0.9, do_sample=True)
    return tokenizer.decode(outputs[0], skip_special_tokens=True)

# Start Gradio API (For External Access)
def start_gradio():
    iface = gr.Interface(fn=generate_response, inputs="text", outputs="text")
    iface.launch(share=True)

# Setup Discord Bot
TOKEN = os.getenv("DISCORD_BOT_TOKEN")  # Discord Token from Hugging Face Secrets
intents = discord.Intents.default()
intents.messages = True
client = discord.Client(intents=intents)

@client.event
async def on_ready():
    print(f"Logged in as Shiv Yantra AI ({client.user})")

@client.event
async def on_message(message):
    if message.author == client.user:
        return  # Ignore bot's own messages

    prompt = message.content
    response = generate_response(prompt)
    await message.channel.send(response)

# Run Discord Bot & API Simultaneously
if __name__ == "__main__":
    threading.Thread(target=start_gradio).start()
    client.run(TOKEN)