app.py

import streamlit as st
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline

# Load the fine-tuned model and tokenizer
model_name = "ibrahimgiki/qa_facebook_bart_base_new"  
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)

# Define a custom question-answering pipeline
qa_pipeline = pipeline("text2text-generation", model=model, tokenizer=tokenizer)

# Streamlit app layout
st.title("Ask anything about crop production, animal husbandry, soil management, and farming practices")

# Text area for the user to input a question
question = st.text_area("Enter your question:")

# Submit button
if st.button("Submit"):
    if question:
        # Perform inference using the pipeline
        result = qa_pipeline(question)
        answer = result[0]['generated_text']
        
        # Display the answer
        st.write("**Answer:**", answer)
    else:
        st.write("Please enter a question.")