app.py

import os
import gradio as gr
from rag_utility import process_document_to_chromadb, answer_question

def process_and_store_file(file):
    if file is not None:
        working_dir = os.getcwd()
        save_path = os.path.join(working_dir, os.path.basename(file))
        with open(save_path, "wb") as f:
            f.write(file.read())
        process_document_to_chromadb(save_path)
        return "Document Processed Successfully"
    return "No file uploaded."

def get_answers(question):
    if not question.strip():
        return "Please enter a question.", "Please enter a question."
    answer = answer_question(question)
    return answer["answer_deepseek"], answer["answer_llama3"]

with gr.Blocks() as demo:
    gr.Markdown("# 🐋 DeepSeek-R1 vs 🦙 Llama-3")
    with gr.Row():
        file_input = gr.File(label="Upload a PDF file", file_types=[".pdf"], type="filepath")
        process_button = gr.Button("Process Document")
    status_output = gr.Textbox(label="Status", interactive=False)
    process_button.click(process_and_store_file, inputs=file_input, outputs=status_output)
    
    question_input = gr.Textbox(label="Ask your question from the document")
    answer_button = gr.Button("Answer")
    with gr.Row():
        deepseek_output = gr.Markdown("### DeepSeek-r1 Response")
        llama3_output = gr.Markdown("### Llama-3 Response")
    
    answer_button.click(get_answers, inputs=question_input, outputs=[deepseek_output, llama3_output])

demo.launch()