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| import os | |
| import pandas as pd | |
| import streamlit as st | |
| import pdfplumber | |
| from modules.chatbot import Chatbot | |
| from modules.embedder import Embedder | |
| class Utilities: | |
| def load_api_key(): | |
| """ | |
| Loads the OpenAI API key from the .env file or | |
| from the user's input and returns it | |
| """ | |
| if not hasattr(st.session_state, "api_key"): | |
| st.session_state.api_key = None | |
| #you can define your API key in .env directly | |
| if os.path.exists(".env") and os.environ.get("OPENAI_API_KEY") is not None: | |
| user_api_key = os.environ["OPENAI_API_KEY"] | |
| st.sidebar.success("API key loaded from .env", icon="🚀") | |
| else: | |
| if st.session_state.api_key is not None: | |
| user_api_key = st.session_state.api_key | |
| st.sidebar.success("API key loaded from previous input", icon="🚀") | |
| else: | |
| user_api_key = st.sidebar.text_input( | |
| label="#### Your OpenAI API key 👇", placeholder="sk-...", type="password" | |
| ) | |
| if user_api_key: | |
| st.session_state.api_key = user_api_key | |
| return user_api_key | |
| def handle_upload(file_types): | |
| """ | |
| Handles and display uploaded_file | |
| :param file_types: List of accepted file types, e.g., ["csv", "pdf", "txt"] | |
| """ | |
| uploaded_file = st.sidebar.file_uploader("upload", type=file_types, label_visibility="collapsed") | |
| if uploaded_file is not None: | |
| def show_csv_file(uploaded_file): | |
| file_container = st.expander("Your CSV file :") | |
| uploaded_file.seek(0) | |
| shows = pd.read_csv(uploaded_file) | |
| file_container.write(shows) | |
| def show_pdf_file(uploaded_file): | |
| file_container = st.expander("Your PDF file :") | |
| with pdfplumber.open(uploaded_file) as pdf: | |
| pdf_text = "" | |
| for page in pdf.pages: | |
| pdf_text += page.extract_text() + "\n\n" | |
| file_container.write(pdf_text) | |
| def show_txt_file(uploaded_file): | |
| file_container = st.expander("Your TXT file:") | |
| uploaded_file.seek(0) | |
| content = uploaded_file.read().decode("utf-8") | |
| file_container.write(content) | |
| def get_file_extension(uploaded_file): | |
| return os.path.splitext(uploaded_file)[1].lower() | |
| file_extension = get_file_extension(uploaded_file.name) | |
| # Show the contents of the file based on its extension | |
| #if file_extension == ".csv" : | |
| # show_csv_file(uploaded_file) | |
| if file_extension== ".pdf" : | |
| show_pdf_file(uploaded_file) | |
| elif file_extension== ".txt" : | |
| show_txt_file(uploaded_file) | |
| else: | |
| st.session_state["reset_chat"] = True | |
| #print(uploaded_file) | |
| return uploaded_file | |
| def setup_chatbot(uploaded_file, model, temperature): | |
| """ | |
| Sets up the chatbot with the uploaded file, model, and temperature | |
| """ | |
| embeds = Embedder() | |
| with st.spinner("Processing..."): | |
| uploaded_file.seek(0) | |
| file = uploaded_file.read() | |
| # Get the document embeddings for the uploaded file | |
| vectors = embeds.getDocEmbeds(file, uploaded_file.name) | |
| # Create a Chatbot instance with the specified model and temperature | |
| chatbot = Chatbot(model, temperature,vectors) | |
| st.session_state["ready"] = True | |
| return chatbot | |