convert to original

app.py

@@ -1,59 +1,7 @@
-import os
-import threading
 import gradio as gr
-import torch
-from transformers import AutoModelForCausalLM, AutoTokenizer
-import subprocess
-import sys
 
-def install_requirements():
-    print('Installing Requirements')
-    subprocess.check_call([sys.executable, '-m', 'pip', 'install', '-r', 'requirements.txt'])
+def greet(name):
+    return "Hello " + name + "!!"
 
-# Check if CUDA is available
-if not torch.cuda.is_available():
-    raise EnvironmentError("CUDA is not available. This script requires a GPU.")
-
-# Model Configuration
-MODEL_ID = "meta-llama/Llama-2-7b-chat"
-MAX_INPUT_TOKEN_LENGTH = 4096
-MAX_NEW_TOKENS = 1024
-TEMPERATURE = 0.6
-TOP_P = 0.9
-TOP_K = 50
-REPETITION_PENALTY = 1.2
-
-# Load the model and tokenizer
-model = AutoModelForCausalLM.from_pretrained(MODEL_ID, torch_dtype=torch.float16, device_map="auto")
-tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
-
-def generate_response(user_input):
-    """
-    Generate a response to the user input using the Llama-2 7B model.
-    """
-    input_ids = tokenizer.encode(user_input, return_tensors="pt")
-    input_ids = input_ids.to(model.device)
-
-    # Generate a response
-    output = model.generate(input_ids, max_length=MAX_INPUT_TOKEN_LENGTH + len(input_ids[0]), 
-                            max_new_tokens=MAX_NEW_TOKENS, temperature=TEMPERATURE, 
-                            top_k=TOP_K, top_p=TOP_P, repetition_penalty=REPETITION_PENALTY)
-
-    response = tokenizer.decode(output[0], skip_special_tokens=True)
-    return response
-
-def chatbot_interface(user_input):
-    return generate_response(user_input)
-
-# Create the Gradio interface
-iface = gr.Interface(
-    fn=chatbot_interface,
-    inputs=gr.inputs.Textbox(lines=2, placeholder="Type your message here..."),
-    outputs="text",
-    title="Llama-2 7B Chatbot",
-    description="This is a chatbot powered by the Llama-2 7B model. Try asking it something!",
-)
-
-if __name__ == "__main__":
-    install_requirements()
-    iface.launch()
+iface = gr.Interface(fn=greet, inputs="text", outputs="text")
+iface.launch()