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Sleeping
| import streamlit as st | |
| from utils import * | |
| import constants | |
| # Creating Seesion state variable | |
| if 'HuggingFace_API_Key' not in st.session_state: | |
| st.session_state['HuggingFace_API_Key'] = '' | |
| if 'Pinecone_API_Key' not in st.session_state: | |
| st.session_state['Pinecone_API_Key'] = '' | |
| st.title('🦾 AI assistance for website') | |
| # SIDE BAR Functionality started | |
| # Sidebar to capture the API keys | |
| st.sidebar.title("🤓 🆒") | |
| st.session_state['HuggingFace_API_Key'] = st.sidebar.text_input("What's ur HuggingFace API key?", | |
| type="password") | |
| st.session_state['Pinecone_API_Key'] = st.sidebar.text_input("What's ur Pinecone API key?", | |
| type="password") | |
| load_button = st.sidebar.button("Load data to Pinecone", key="load_button") | |
| # If the above button is clicked, pushing the dat to Pinecone | |
| if load_button: | |
| # Proceed only if API keys are provided | |
| if st.session_state['HuggingFace_API_Key'] != "" and st.session_state['Pinecone_API_Key'] != "": | |
| # Fetch data from site | |
| site_data = get_website_data(constants.WEBSITE_URL) | |
| st.write("Data pull done...") | |
| # Split data into chunks | |
| chunks_data = split_data(site_data) | |
| st.write("Splitting data done...") | |
| # Creating embedding instance | |
| embeddings = create_embeddings() | |
| st.write("Embeddings instance creation done...") | |
| # Push data to Pinecone | |
| push_to_pinecone(st.session_state['Pinecone_API_Key'], constants.PINECONE_ENVIRONMENT, | |
| constants.PINECONE_INDEX, embeddings, chunks_data) | |
| st.write("Pushing data to Pinecone done...") | |
| st.sidebar.success("Data pushed to Piencone successfully!!!") | |
| else: | |
| st.sidebar.error("Nope!!!! Please provide ur API Keys....") | |
| # SIDE BAR Functionality ended | |
| # Captures User Inputs | |
| # The box for text prompt | |
| prompt = st.text_input('How can I help you bro ?', key="prompt") | |
| document_count = st.slider("No of links to return 🌐 - (0 Low || 5 High)", 0, 5, 2, step=1) | |
| submit = st.button("Search") | |
| if submit: | |
| # Proceed only if API keys are provided. | |
| if st.session_state['HuggingFace_API_Key'] != "" and st.session_state['Pinecone_API_Key'] !="": | |
| # Creating embedded instance | |
| embeddings = create_embeddings() | |
| st.write("Embeddings instance creation done...") | |
| # Pull index data from Pinecone | |
| index = pull_from_pinecone(st.session_state['Pinecone_API_Key'], constants.PINECONE_ENVIRONMENT, | |
| constants.PINECONE_INDEX, embeddings) | |
| st.write("Pinecone index retrieval done...") | |
| # Fetch relevant documents from Pinecone index | |
| relevant_docs = get_similiar_docs(index, prompt, document_count) | |
| st.write(relevant_docs) | |
| # Displaying search results | |
| st.success("Please find the search results: ") | |
| # Display search results | |
| st.write("search results list....") | |
| for document in relevant_docs: | |
| st.write("👉**Result : " + str(relevant_docs.index(document)+1)+"***") | |
| st.write("**Infor**" + document.page_content) | |
| #st.write("**Link**" + document.metadata['source']) | |
| else: | |
| st.sidebar.error("Nope!!! Please provide API Keys.....") |