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import requests
import streamlit as st
from layouts.mainlayout import mainlayout
@mainlayout
def upload_data():
# upload pdf
upload_pdf = st.file_uploader("Upload PDF", type="pdf")
if upload_pdf is not None:
files = {"file": upload_pdf}
with st.spinner("Uploading PDF..."):
response = requests.post(
"https://hemanthsai7-studybotapi.hf.space/api/upload", files=files
)
if response.status_code == 200:
st.success(
f'{response.json()["message"][0]}. Vector Store created successfully!'
)
st.session_state.uploaded_pdf=True
else:
st.error("Failed to upload PDF!")
upload_data()
with st.expander("What happens when I upload a PDF? 📑", expanded=True):
st.info(
"""
- The PDF is uploaded to the backend server. ⚙️
- The PDF is converted into small chunks for faster processing. 🚀
- The chunks are broken down into tokens. A token is a single word or a group of words. 📝
- The tokens are converted into embedding vectors. 📊
- The embedding vectors are stored in a vector store. 🗄️
""",
icon="ℹ️",
)
st.divider()
if "uploaded_pdf" in st.session_state.keys():
# chatbot
st.subheader("Ask Studybot a question! 🤖")
if "messages" not in st.session_state.keys():
st.session_state.messages = [
{
"role": "assistant",
"content": "What's troubling you? Ask me a question right away!",
}
]
# Display or clear chat messages
for message in st.session_state.messages:
with st.chat_message(message["role"]):
st.write(message["content"])
def clear_chat_history():
st.session_state.messages = [
{
"role": "assistant",
"content": "What's troubling you? Ask me a question right away!",
}
]
st.sidebar.button("Clear Chat History", on_click=clear_chat_history)
def generate_mistral_response(question: str):
for dict_message in st.session_state.messages:
if dict_message["role"] == "user":
question = dict_message["content"]
answer = requests.post(
"https://hemanthsai7-studybotapi.hf.space/api/inference",
json={"promptMessage": question},
).json()
return answer
# User-provided prompt
if prompt := st.chat_input(
disabled=not st.session_state.messages[-1]["role"] == "assistant",
placeholder="Hello, please ask me a question! 🤖"):
st.session_state.messages.append({"role": "user", "content": prompt})
with st.chat_message("user"):
st.write(prompt)
# ask question
st.write(st.session_state)
# Generate a new response if last message is not from assistant
if st.session_state.messages[-1]["role"] != "assistant":
with st.chat_message("assistant"):
with st.spinner("Thinking..."):
response = generate_mistral_response(prompt)
placeholder = st.empty()
full_response = ""
for item in response:
full_response += item
placeholder.markdown(full_response)
placeholder.markdown(full_response)
message = {"role": "assistant", "content": full_response}
st.session_state.messages.append(message)
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