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import streamlit as st
from transformers import pipeline, AutoModelForSeq2SeqLM, AutoTokenizer
# Load model and tokenizer
model_name = "t5_qa_model.pt"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
qa_pipeline = pipeline("text2text-generation", model=model, tokenizer=tokenizer)
# Streamlit app
st.title("History QA with T5 Model")
st.write("Enter the historical context and your question below:")
context = st.text_area("Context", height=200)
question = st.text_input("Question")
if st.button("Get Answer"):
input_text = f"question: {question} context: {context}"
result = qa_pipeline(input_text)
answer = result[0]['generated_text']
st.write("**Answer:**")
st.write(answer)
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