| import streamlit as st | |
| from haystack.generator.transformers import RAGenerator | |
| generator = RAGenerator(model_name_or_path="facebook/rag-token-nq", | |
| embed_title=False, num_beams=5) | |
| from haystack.pipeline import GenerativeQAPipeline | |
| pipe = GenerativeQAPipeline(generator=generator, retriever=dpr_retriever) | |
| def generate_answers(query, top_k_generator=3): | |
| preds = pipe.run(query=query, top_k_generator=top_k_generator, | |
| top_k_retriever=5, filters={"item_id":["B0074BW614"]}) | |
| st.write(f"Question: {preds['query']} \n") | |
| for idx in range(top_k_generator): | |
| st.write(f"Answer {idx+1}: {preds['answers'][idx]['answer']}") | |
| query = st.textarea("Enter the Query:") | |
| generate_answers(query) |