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| import requests | |
| import streamlit as st | |
| from components.display import * | |
| from layouts.mainlayout import mainlayout | |
| from components.file_streaming import upload_data | |
| def display(): | |
| 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() | |
| display() | |
| BASE_URL = "https://hemanthsai7-studybotapi.hf.space" | |
| uploaded_files = st.sidebar.file_uploader(label="Upload PDF files", type=["pdf"]) | |
| if not uploaded_files: | |
| st.info("Please upload PDF documents to continue.") | |
| st.stop() | |
| upload_data(uploaded_files, BASE_URL) | |
| 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"] | |
| try: | |
| response = requests.post( | |
| f"{BASE_URL}/api/inference", | |
| json={"promptMessage": question}).json() | |
| if response["status"]=="error": | |
| st.error("Please refresh the page and try uploading the file again.") | |
| st.stop() | |
| answer = response["result"]["answer"] | |
| with st.expander("Source documents 🧐"): | |
| source_documents = response["result"]["source_documents"] | |
| display_source_document(source_documents) | |
| except Exception as e: | |
| if response.json()=='exception.ModelDeployingException()': | |
| st.error("Model is deploying in the backend servers. Please try again after some time") | |
| st.stop() | |
| 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) | |