app/main.py

import argparse
import gradio as gr
from ui import chat
import os
from dotenv import load_dotenv

load_dotenv()

USERNAME = os.getenv("USERNAME")
PWD = os.getenv("USER_PWD")

def main(args):
    demo = gr.ChatInterface(
        fn=chat, 
        examples=["Explain the AI adoption challenges for enterprises.", "How can we identify a fraud transaction?", "Por que os grandes modelos de linguagem de AI halucinam?"], 
        title="Chat and LLM server in the same application",
        description="This space is a template that we can duplicate for your own usage. "
                    "This space let you build LLM powered idea on top of [Gradio](https://www.gradio.app/) " 
                    "and open LLM served locally by [TGI(Text Generation Inference)](https://huggingface.co/docs/text-generation-inference/en/index). "
                    "Below is a placeholder Gradio ChatInterface for you to try out Mistral-7B backed by the power of TGI's efficiency. \n\n"
                    "To use this space for your own usecase, follow the simple steps below:\n"
                    "1. Duplicate this space. \n"
                    "2. Set which LLM you wish to use (i.e. mistralai/Mistral-7B-Instruct-v0.2). \n"
                    "3. Inside app/main.py write Gradio application. \n",
        multimodal=False,
        theme='sudeepshouche/minimalist',
    )
    
    demo.queue(
        default_concurrency_limit=20,
        max_size=256        
    ).launch(auth=(USERNAME, PWD), server_name="0.0.0.0", server_port=args.port)

if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="A MAGIC example by ConceptaTech")
    parser.add_argument("--port", type=int, default=7860, help="Port to expose Gradio app")
    
    args = parser.parse_args()    
    main(args)