generate_answer.py

from transformers import BartTokenizer, BartModel
from langchain.prompts import PromptTemplate

tokenizer = BartTokenizer.from_pretrained('facebook/bart-base')
model = BartModel.from_pretrained('facebook/bart-base')

def generate_answer(context):
    prompt_template = PromptTemplate(template="Summarise the following context: {context}",
                                     input_variables=["context"], output_variables=["answer"])
    # Model loading
    format_prompt = prompt_template.format(question=question)
    encoded_input = tokenizer(format_prompt, return_tensors='pt')
    # Run the model
    output = model.generate(**encoded_input)  # Use generate method for text generation
    # Decode the model output to text
    decoded_output = tokenizer.decode(output[0])
    return decoded_output