app.py

from dotenv import load_dotenv
import pandas as pd
import streamlit as st
import streamlit_authenticator as stauth
from streamlit_modal import Modal

from utils import new_file, clear_memory, append_documentation_to_sidebar, load_authenticator_config, init_qa, \
    append_header
from haystack.document_stores.in_memory import InMemoryDocumentStore
from haystack import Document

load_dotenv()

OPENAI_MODELS = ['gpt-3.5-turbo',
                 "gpt-4",
                 "gpt-4-1106-preview"]

OPEN_MODELS = [
    'mistralai/Mistral-7B-Instruct-v0.1',
    'HuggingFaceH4/zephyr-7b-beta'
]


def reset_chat_memory():
    st.button(
        'Reset chat memory',
        key="reset-memory-button",
        on_click=clear_memory,
        help="Clear the conversational memory. Currently implemented to retain the 4 most recent messages.",
        disabled=False)


def manage_files(modal, document_store):
    open_modal = st.sidebar.button("Manage Files", use_container_width=True)
    if open_modal:
        modal.open()

    if modal.is_open():
        with modal.container():
            uploaded_file = st.file_uploader(
                "Upload a CV in PDF format",
                type=("pdf",),
                on_change=new_file(),
                disabled=st.session_state['document_qa_model'] is None,
                label_visibility="collapsed",
                help="The document is used to answer your questions. The system will process the document and store it in a RAG to answer your questions.",
            )
            edited_df = st.data_editor(use_container_width=True, data=st.session_state['files'],
                                       num_rows='dynamic',
                                       column_order=['name', 'size', 'is_active'],
                                       column_config={'name': {'editable': False}, 'size': {'editable': False},
                                                      'is_active': {'editable': True, 'type': 'checkbox',
                                                                    'width': 100}}
                                       )
            st.session_state['files'] = pd.DataFrame(columns=['name', 'content', 'size', 'is_active'])

            if uploaded_file:
                st.session_state['file_uploaded'] = True
                st.session_state['files'] = pd.concat([st.session_state['files'], edited_df])
                with st.spinner('Processing the CV content...'):
                    store_file_in_table(document_store, uploaded_file)
                    ingest_document(uploaded_file)


def ingest_document(uploaded_file):
    if not st.session_state['document_qa_model']:
        st.warning('Please select a model to start asking questions')
    else:
        try:
            st.session_state['document_qa_model'].ingest_pdf(uploaded_file)
            st.success('Document processed successfully')
        except Exception as e:
            st.error(f"Error processing the document: {e}")
            st.session_state['file_uploaded'] = False


def store_file_in_table(document_store, uploaded_file):
    pdf_content = uploaded_file.getvalue()
    st.session_state['pdf_content'] = pdf_content
    st.session_state.messages = []
    document = Document(content=pdf_content, meta={"name": uploaded_file.name})
    df = pd.DataFrame(st.session_state['files'])
    df['is_active'] = False
    st.session_state['files'] = pd.concat([df, pd.DataFrame(
        [{"name": uploaded_file.name, "content": pdf_content, "size": len(pdf_content),
          "is_active": True}])])
    document_store.write_documents([document])


def init_session_state():
    st.session_state.setdefault('files', pd.DataFrame(columns=['name', 'content', 'size', 'is_active']))
    st.session_state.setdefault('models', [])
    st.session_state.setdefault('api_keys', {})
    st.session_state.setdefault('current_selected_model', 'gpt-3.5-turbo')
    st.session_state.setdefault('current_api_key', '')
    st.session_state.setdefault('messages', [])
    st.session_state.setdefault('pdf_content', None)
    st.session_state.setdefault('memory', None)
    st.session_state.setdefault('pdf', None)
    st.session_state.setdefault('document_qa_model', None)
    st.session_state.setdefault('file_uploaded', False)


def set_page_config():
    st.set_page_config(
        page_title="CV Insights AI Assistant",
        page_icon=":shark:",
        initial_sidebar_state="expanded",
        layout="wide",
        menu_items={
            'Get Help': 'https://www.extremelycoolapp.com/help',
            'Report a bug': "https://www.extremelycoolapp.com/bug",
            'About': "# This is a header. This is an *extremely* cool app!"
        }
    )


def update_running_model(api_key, model):
    st.session_state['api_keys'][model] = api_key
    st.session_state['document_qa_model'] = init_qa(model, api_key)


def init_api_key_dict():
    st.session_state['models'] = OPENAI_MODELS + list(OPEN_MODELS) + ['local LLM']
    for model_name in OPENAI_MODELS:
        st.session_state['api_keys'][model_name] = None


def display_chat_messages(chat_box, chat_input):
    with chat_box:
        if chat_input:
            for message in st.session_state.messages:
                with st.chat_message(message["role"]):
                    st.markdown(message["content"], unsafe_allow_html=True)

            st.chat_message("user").markdown(chat_input)
            with st.chat_message("assistant"):
                # process user input and generate response
                response = st.session_state['document_qa_model'].inference(chat_input, st.session_state.messages)

                st.markdown(response)
                st.session_state.messages.append({"role": "user", "content": chat_input})
                st.session_state.messages.append({"role": "assistant", "content": response})


def setup_model_selection():
    model = st.selectbox(
        "Model:",
        options=st.session_state['models'],
        index=0,  # default to the first model in the list gpt-3.5-turbo
        placeholder="Select model",
        help="Select an LLM:"
    )

    if model:
        if model != st.session_state['current_selected_model']:
            st.session_state['current_selected_model'] = model
            if model == 'local LLM':
                st.session_state['document_qa_model'] = init_qa(model)

    api_key = st.sidebar.text_input("Enter LLM-authorization Key:", type="password",
                                    disabled=st.session_state['current_selected_model'] == 'local LLM')
    if api_key and api_key != st.session_state['current_api_key']:
        update_running_model(api_key, model)
        st.session_state['current_api_key'] = api_key

    return model


def setup_task_selection(model):
    # enable extractive and generative tasks if we're using a local LLM or an OpenAI model with an API key
    if model == 'local LLM' or st.session_state['api_keys'].get(model):
        task_options = ['Extractive', 'Generative']
    else:
        task_options = ['Extractive']

    task_selection = st.sidebar.radio('Select the task:', task_options)

    # TODO: Add the task selection logic here (initializing the model based on the task)


def setup_page_body():
    chat_box = st.container(height=350, border=False)
    chat_input = st.chat_input(
        placeholder="Upload a document to start asking questions...",
        disabled=not st.session_state['file_uploaded'],
    )
    if st.session_state['file_uploaded']:
        display_chat_messages(chat_box, chat_input)


class StreamlitApp:
    def __init__(self):
        self.authenticator_config = load_authenticator_config()
        self.document_store = InMemoryDocumentStore()
        set_page_config()
        self.authenticator = self.init_authenticator()
        init_session_state()
        init_api_key_dict()

    def init_authenticator(self):
        return stauth.Authenticate(
            self.authenticator_config['credentials'],
            self.authenticator_config['cookie']['name'],
            self.authenticator_config['cookie']['key'],
            self.authenticator_config['cookie']['expiry_days']
        )

    def setup_sidebar(self):
        with st.sidebar:
            st.sidebar.image("resources/puma.png", use_column_width=True)

            # Sidebar for Task Selection
            st.sidebar.header('Options:')
            model = setup_model_selection()
            setup_task_selection(model)
            st.divider()
            self.authenticator.logout()
            reset_chat_memory()
            modal = Modal("Manage Files", key="demo-modal")
            manage_files(modal, self.document_store)
            st.divider()
            append_documentation_to_sidebar()

    def run(self):
        name, authentication_status, username = self.authenticator.login()
        if authentication_status:
            self.run_authenticated_app()
        elif st.session_state["authentication_status"] is False:
            st.error('Username/password is incorrect')
        elif st.session_state["authentication_status"] is None:
            st.warning('Please enter your username and password')

    def run_authenticated_app(self):
        self.setup_sidebar()
        append_header()
        setup_page_body()


app = StreamlitApp()
app.run()