| import os |
| import streamlit as st |
| from tempfile import NamedTemporaryFile |
| from retriever import get_retrieval_chain |
| from preprocess import create_vectorstore |
| from preprocess import load_vectorstore |
|
|
| def rag_with_new_data(file_name): |
| cwd = os.getcwd() |
| temp_dir = os.path.join(cwd, "temp") |
| os.makedirs(temp_dir, exist_ok=True) |
| file_path = os.path.join(temp_dir, file_name.name) |
| |
| st.write("Creating a temporary file..") |
| with open(file_path, "wb") as f: |
| f.write(file_name.getbuffer()) |
| |
| st.write("Temp file created...") |
| |
| st.write("Wait while I create the embeddings..") |
| vectorstore = create_vectorstore(f.name) |
| st.write("OK the embeddings are ready.") |
|
|
| retriever = "google/flan-t5-large" |
| qa_chain = get_retrieval_chain(retriever, vectorstore) |
| |
| return qa_chain |
|
|
| def rag_with_saved_data(saved_db_name): |
|
|
| vectorstore = load_vectorstore(saved_db_name) |
| |
| retriever = "google/flan-t5-large" |
| qa_chain = get_retrieval_chain(retriever, vectorstore) |
| |
| return qa_chain |
| |
| st.title("Ask me anything about the PDF!") |
|
|
| file_name =None |
| qa_chain = None |
|
|
| choice = st.sidebar.radio("select" , |
| ["Existing Knowledge Base", "New Knowledge Base"]) |
|
|
| if choice == "Existing Knowledge Base": |
| |
| selected_option= st.sidebar.selectbox("choose an existing knowledgebase", |
| ("choose an option", "underwriting"), |
| index = 0, |
| placeholder = "choose an option" |
| ) |
| if selected_option == "underwriting": |
| qa_chain = rag_with_saved_data(selected_option) |
| elif choice == "New Knowledge Base": |
| file_name = st.sidebar.file_uploader("Upload a PDF file", type=['pdf']) |
| if file_name: |
| qa_chain = rag_with_new_data(file_name) |
| |
|
|
| user_prompt = st.text_input('Ask your question here e.g. \"what is the total purchase price\"') |
|
|
| if user_prompt != '' and qa_chain: |
| |
| |
| |
| |
| response = qa_chain(user_prompt) |
| st.write(response) |
