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| import streamlit as st | |
| from utils import * | |
| import constants | |
| # Creating Session 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 Funtionality started******* | |
| # Sidebar to capture the API keys | |
| st.sidebar.title("😎🗝️") | |
| st.session_state['HuggingFace_API_Key']= st.sidebar.text_input("What's your HuggingFace API key?",type="password") | |
| st.session_state['Pinecone_API_Key']= st.sidebar.text_input("What's your Pinecone API key?",type="password") | |
| load_button = st.sidebar.button("Load data to Pinecone", key="load_button") | |
| #If the bove button is clicked, pushing the data 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("Spliting data done...") | |
| #Creating embeddings 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 Pinecone successfully!") | |
| else: | |
| st.sidebar.error("Ooopssss!!! Please provide API keys.....") | |
| #********SIDE BAR Funtionality ended******* | |
| #Captures User Inputs | |
| prompt = st.text_input('How can I help you my friend ❓',key="prompt") # The box for the text 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 embeddings 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 relavant documents from Pinecone index | |
| relavant_docs=get_similar_docs(index,prompt,document_count) | |
| #st.write(relavant_docs) | |
| #Displaying search results | |
| st.success("Please find the search results :") | |
| #Displaying search results | |
| st.write("search results list....") | |
| for document in relavant_docs: | |
| st.write("👉**Result : "+ str(relavant_docs.index(document)+1)+"**") | |
| st.write("**Info**: "+document.page_content) | |
| st.write("**Link**: "+ document.metadata['source']) | |
| else: | |
| st.sidebar.error("Ooopssss!!! Please provide API keys.....") |