Update app.py

app.py

@@ -1,65 +1,18 @@
-import discord
-import os
-import torch
+import gradio as gr
 from transformers import AutoModelForCausalLM, AutoTokenizer
-from flask import Flask
-
-# Load environment variables (Hugging Face & Discord tokens)
-HF_TOKEN = os.getenv("HF_TOKEN")
-DISCORD_TOKEN = os.getenv("DISCORD_TOKEN")
-
-# Define model name (Make sure this matches your uploaded model in Hugging Face)
-MODEL_NAME = "Hardik5456/DeepScaleR"
-
-# Load Model & Tokenizer
-device = "cuda" if torch.cuda.is_available() else "cpu"
-tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, token=HF_TOKEN)
-model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, token=HF_TOKEN).to(device)
-
-# Initialize Flask for Hugging Face Space (Prevents Space from Sleeping)
-app = Flask(__name__)
-
-@app.route("/")
-def home():
-    return "Shiv Yantra AI is running!"
-
-# Discord Bot Setup
-intents = discord.Intents.default()
-intents.messages = True
-client = discord.Client(intents=intents)
-
-@client.event
-async def on_ready():
-    print(f'Logged in as {client.user}')
-
-@client.event
-async def on_message(message):
-    if message.author == client.user:
-        return
-
-    # Shiv Yantra AI's Special Responses
-    if message.content.lower() == "who are you?":
-        await message.channel.send("I am Shiv Yantra AI, an advanced intelligence created for cinematic AI filmmaking.")
-    elif message.content.lower() == "who made you?":
-        await message.channel.send("I was created by Spectral Satya.")
-    elif message.content.lower() == "who is the founder?":
-        await message.channel.send("Hardik Kumawat is the visionary behind this AI.")
-    else:
-        # Generate AI Response
-        input_text = message.content
-        input_ids = tokenizer.encode(input_text, return_tensors="pt").to(device)
-        output = model.generate(input_ids, max_length=200)
-        response = tokenizer.decode(output[0], skip_special_tokens=True)
-        
-        await message.channel.send(response)
+import torch
 
-# Run Flask & Discord Bot
-if __name__ == "__main__":
-    import threading
+# Load DeepScaleR model
+MODEL_NAME = "agentica-org/DeepScaleR-1.5B-Preview"
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForCausalLM.from_pretrained(MODEL_NAME)
 
-    # Start Discord Bot in a separate thread
-    discord_thread = threading.Thread(target=lambda: client.run(DISCORD_TOKEN))
-    discord_thread.start()
+# Function to generate AI responses
+def generate_response(prompt):
+    inputs = tokenizer(prompt, return_tensors="pt", truncation=True, max_length=2048)
+    output = model.generate(**inputs, max_new_tokens=200)
+    return tokenizer.decode(output[0], skip_special_tokens=True)
 
-    # Run Flask App for Hugging Face Space
-    app.run(host="0.0.0.0", port=7860)
+# Launch API for Discord bot
+iface = gr.Interface(fn=generate_response, inputs="text", outputs="text")
+iface.launch(server_name="0.0.0.0", server_port=7860, share=False)