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import streamlit as st
import os
import pickle
from streamlit_extras.add_vertical_space import add_vertical_space
from huggingface_hub import Repository
from PyPDF2 import PdfReader
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.vectorstores import FAISS
from langchain.llms import OpenAI
from langchain.chains.question_answering import load_qa_chain
from langchain.callbacks import get_openai_callback
# Step 1: Clone the Dataset Repository
repo = Repository(
local_dir="Private_Book", # Local directory to clone the repository
repo_type="dataset", # Specify that this is a dataset repository
clone_from="Anne31415/Private_Book", # Replace with your repository URL
token=os.getenv("HUB_TOKEN") # Use the secret token to authenticate
)
repo.git_pull() # Pull the latest changes (if any)
# Step 2: Load the PDF File
pdf_file_path = "Private_Book/KOMBI_all2.pdf" # Replace with your PDF file path
def cloud_button(label, key=None, color=None):
button_id = f"cloud-button-{key or label}"
color_class = f"color-{color}" if color else ""
cloud_button_html = f"""
<div class="cloud {color_class}" id="{button_id}" style="margin-bottom: 20px;">
<div class="circle small"></div>
<div class="circle medium"></div>
<div class="circle large"></div>
<div class="rectangle">{label}</div>
<div class="circle medium right"></div>
<div class="circle small right"></div>
</div>
<style>
.cloud {{
position: relative;
display: inline-block;
cursor: pointer;
user-select: none;
font-size: 16px;
background-color: #f8f9fa;
}}
.rectangle {{
min-width: 120px;
height: auto;
border-radius: 30px;
position: relative;
display: flex;
align-items: center;
justify-content: center;
font-weight: bold;
padding: 10px 20px;
z-index: 2;
transition: background-color 0.4s;
}}
.circle {{
position: absolute;
background-color: #f8f9fa;
z-index: 1;
}}
.circle.small {{
width: 40px;
height: 40px;
border-radius: 20px;
top: 50%;
left: -20px;
transform: translateY(-50%);
}}
.circle.medium {{
width: 60px;
height: 60px;
border-radius: 30px;
top: 50%;
left: -30px;
transform: translateY(-50%);
}}
.circle.large {{
width: 80px;
height: 80px;
border-radius: 40px;
top: 50%;
left: -40px;
transform: translateY(-50%);
}}
.circle.right.small {{
left: auto;
right: -20px;
}}
.circle.right.medium {{
left: auto;
right: -30px;
}}
.cloud:hover .rectangle {{
background-color: #008CBA;
color: white;
}}
.color-1 .rectangle {{ background-color: #FFA07A; }}
.color-2 .rectangle {{ background-color: #FF7F50; }}
.color-3 .rectangle {{ background-color: #FF6347; }}
.color-4 .rectangle {{ background-color: #FF4500; }}
.color-5 .rectangle {{ background-color: #FF8C00; }}
.color-6 .rectangle {{ background-color: #FFD700; }}
</style>
<script>
document.getElementById("{button_id}").onclick = function() {{
// Your existing JavaScript code for handling button click
}};
</script>
"""
st.markdown(cloud_button_html, unsafe_allow_html=True)
def load_pdf(file_path):
pdf_reader = PdfReader(file_path)
text = ""
for page in pdf_reader.pages:
text += page.extract_text()
text_splitter = RecursiveCharacterTextSplitter(
chunk_size=1000,
chunk_overlap=200,
length_function=len
)
chunks = text_splitter.split_text(text=text)
store_name, _ = os.path.splitext(os.path.basename(file_path))
if os.path.exists(f"{store_name}.pkl"):
with open(f"{store_name}.pkl", "rb") as f:
VectorStore = pickle.load(f)
else:
embeddings = OpenAIEmbeddings()
VectorStore = FAISS.from_texts(chunks, embedding=embeddings)
with open(f"{store_name}.pkl", "wb") as f:
pickle.dump(VectorStore, f)
return VectorStore
def load_chatbot():
return load_qa_chain(llm=OpenAI(), chain_type="stuff")
def display_chat_history(chat_history):
for chat in chat_history:
background_color = "#FFA07A" if chat[2] == "new" else "#acf" if chat[0] == "User" else "#caf"
st.markdown(f"<div style='background-color: {background_color}; padding: 10px; border-radius: 10px; margin: 10px;'>{chat[0]}: {chat[1]}</div>", unsafe_allow_html=True)
def main():
with st.sidebar:
st.title('BinDoc GmbH')
st.markdown("Experience revolutionary interaction with BinDocs Chat App, leveraging state-of-the-art AI technology.")
add_vertical_space(1) # Adjust as per the desired spacing
st.markdown("""
Hello! I’m here to assist you with:<br><br>
📘 **Glossary Inquiries:**<br>
I can clarify terms like "DiGA", "AOP", or "BfArM", providing clear and concise explanations to help you understand our content better.<br><br>
🆘 **Help Page Navigation:**<br>
Ask me if you forgot your password or want to know more about topics related to the platform.<br><br>
📰 **Latest Whitepapers Insights:**<br>
Curious about our recent publications? Feel free to ask about our latest whitepapers!<br><br>
""", unsafe_allow_html=True)
add_vertical_space(1) # Adjust as per the desired spacing
st.write('Made with ❤️ by BinDoc GmbH')
api_key = os.getenv("OPENAI_API_KEY")
hide_streamlit_style = """
<style>
#MainMenu {visibility: hidden;}
footer {visibility: hidden;}
</style>
"""
st.markdown(hide_streamlit_style, unsafe_allow_html=True)
# Main content
st.title("Welcome to BinDocs ChatBot! 🤖")
# Cloud Buttons as Example Questions
st.markdown("**Example Questions:**")
cloud_button("Was genau ist ein Belegarzt?", color="1")
st.markdown("<div style='margin-bottom: 20px;'></div>", unsafe_allow_html=True) # Space after the cloud button
cloud_button("Wofür wird die Alpha-ID verwendet?", color="2")
st.markdown("<div style='margin-bottom: 20px;'></div>", unsafe_allow_html=True) # Space after the cloud button
cloud_button("Was sind die Vorteile des ambulanten operierens?", color="3")
st.markdown("<div style='margin-bottom: 20px;'></div>", unsafe_allow_html=True) # Space after the cloud button
cloud_button("Was kann ich mit dem Prognose-Analyse Toll machen?", color="4")
st.markdown("<div style='margin-bottom: 20px;'></div>", unsafe_allow_html=True) # Space after the cloud button
cloud_button("Was sagt mir die Farbe der Balken der Bevölkerungsentwicklung?", color="5")
st.markdown("<div style='margin-bottom: 20px;'></div>", unsafe_allow_html=True) # Space after the cloud button
cloud_button("Ich habe mein Meta Password vergessen, wie kann ich es zurücksetzen?", color="6")
st.markdown("<div style='margin-bottom: 20px;'></div>", unsafe_allow_html=True) # Space after the cloud button
pdf_path = "path_to_your_pdf_file.pdf" # Update this to the path of your PDF file
if not os.path.exists(pdf_path):
st.error("File not found. Please check the file path.")
return
if "chat_history" not in st.session_state:
st.session_state['chat_history'] = []
display_chat_history(st.session_state['chat_history'])
st.write("<!-- Start Spacer -->", unsafe_allow_html=True)
st.write("<div style='flex: 1;'></div>", unsafe_allow_html=True)
st.write("<!-- End Spacer -->", unsafe_allow_html=True)
new_messages_placeholder = st.empty()
if pdf_path is not None:
query = st.text_input("Ask questions about your PDF file (in any preferred language):")
if st.button("Ask") or (not st.session_state['chat_history'] and query) or (st.session_state['chat_history'] and query != st.session_state['chat_history'][-1][1]):
st.session_state['chat_history'].append(("User", query, "new"))
loading_message = st.empty()
loading_message.text('Bot is thinking...')
VectorStore = load_pdf(pdf_path)
chain = load_chatbot()
docs = VectorStore.similarity_search(query=query, k=3)
response = chain.run(input_documents=docs, question=query)
st.session_state['chat_history'].append(("Bot", response, "new"))
new_messages = st.session_state['chat_history'][-2:]
for chat in new_messages:
background_color = "#FFA07A" if chat[2] == "new" else "#acf" if chat[0] == "User" else "#caf"
new_messages_placeholder.markdown(f"<div style='background-color: {background_color}; padding: 10px; border-radius: 10px; margin: 10px;'>{chat[0]}: {chat[1]}</div>", unsafe_allow_html=True)
st.write("<script>document.getElementById('response').scrollIntoView();</script>", unsafe_allow_html=True)
loading_message.empty()
query = ""
st.session_state['chat_history'] = [(sender, msg, "old") for sender, msg, _ in st.session_state['chat_history']]
if __name__ == "__main__":
main() |