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import streamlit as st
from streamlit_lottie import st_lottie
def faq():
st.markdown(
"""
# FAQ
## How does Document Q&A Bot work?
When you upload a document (in Pdf, word, csv or txt format), it will be divided into smaller chunks
and stored in a special type of database called a vector index
that allows for semantic search and retrieval.
When you ask a question, our Q&A bot will first look through the document chunks and find the
most relevant ones using the vector index. Then, it will use open-source LLM model named Google Palm
and will provide the final answer.
## Is my data safe?
Yes, your data is safe. Our bot does not store your documents or
questions. All uploaded data is deleted after you close the browser tab.
## Why does it take so long to index my document?
Since, this is a sample QA bot project that uses open-source model
and doesn't have much resource capabilities like GPU, it may take time
to index your document based on the size of the document.
## Are the answers 100% accurate?
No, the answers are not 100% accurate.
But for most use cases, our QA bot is very accurate and can answer
most questions. Always check with the sources to make sure that the answers
are correct.
"""
)
def sidebar():
with st.sidebar:
st.markdown("## Google Palm")
st.success('API key already provided!', icon='✅')
st.markdown(
"## How to use QA bot\n"
"1. Upload a pdf, docx, or a txt file📄\n"
"2. Ask questions about the document💬\n"
)
# st.session_state["OPENAI_API_KEY"] = api_key_input
st.markdown("---")
st.markdown("# About")
st.markdown(
"🤖 QA bot allows you to ask questions about your "
"documents and get accurate answers with citations. "
)
st.markdown("Created by [Krishna Kumar](https://www.linkedin.com/in/krishna-kumar-yadav-726831105/)")
st.markdown("---")
faq()
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