app.py

import gradio as gr
import asyncio
from openai import AsyncOpenAI
from RAGModule import RAGModule

# Instantiate the RAG module
RAG_Trwira = RAGModule()

# Configure the async OpenAI client
client = AsyncOpenAI(api_key="34.69.9.203", base_url="http://34.69.9.203:11434/v1")

settings = {
    "model": "MarcoAland/llama3.1-rag-indo",
    "temperature": 0.3,
    "max_tokens": 2048,
}

async def generate_response(user_input: str) -> str:
    message = "Namamu adalah Mitrakara.\n\n" + user_input
    # Call documents options or not
    if "dokumen" in message.lower() or "document" in message.lower() or "documents" in message.lower():
        prompt = RAG_Trwira.main(message[10:])
    else:
        prompt = message
        
    # Format the messages as a list of message dictionaries
    message_formated = [
        {"role": "user", "content": prompt}
    ]

    # Use streaming to handle partial responses
    stream = await client.chat.completions.create(messages=message_formated, stream=True, **settings)
    
    response = ""
    async for part in stream:
        if token := part.choices[0].delta.content or "":
            response += token

    return response

def chat(user_input: str):
    # Call the asynchronous response generation function
    response = asyncio.run(generate_response(user_input))
    return response

# Define the Gradio interface
iface = gr.Interface(
    fn=chat,
    inputs=gr.Textbox(label="Masukkan pertanyaan anda", placeholder="Tanyakan saja padaku🌟"),
    outputs=gr.Textbox(label="Respons Mitrakara"),
    title="Hai, namaku Mitrakara. Selamat datang!👋",
    description="Berikut adalah beberapa tips untuk bertanya denganku✨✨✨\n1. Gunakan kata 'document:' jika ingin bertanya mengenai dokumen/administrasi perusahaan.\n2. Gunakan kalimat tanya yang baik.\n3. Enjoy the conversation.😊"
)

# Launch the Gradio interface
if __name__ == "__main__":
    iface.launch(share=False)