app.py

import gradio as gr
from transformers import pipeline

# Load the Hugging Face model
model = "deepset/bert-base-cased-squad2"
qa_pipeline = pipeline("question-answering", model=model, tokenizer=model)

# Define the function to answer questions
def get_answer(text):
    result = qa_pipeline({
        "question": text,
        "context": knowledge_base_text
    })
    return result["answer"]

# Define the Gradio interface
def chatbot_interface(text):
    answer = get_answer(text)
    return answer

knowledge_base_file = "knowledge_base.txt"  # Path to the knowledge base text file

# Load the knowledge base from a text file
with open(knowledge_base_file, "r") as f:
    knowledge_base_text = f.read()

# Create the Gradio interface
iface = gr.Interface(
    fn=chatbot_interface,
    inputs="Ask any questions about BATB",
    outputs="Result",
    title="British American Tobacco Bangladesh",
    description="- powered by IDT",
    theme="default"
)

# Run the Gradio interface
iface.launch()