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import streamlit as st
import streamlit.components.v1 as components
import pandas as pd
from my_model.tabs.run_inference import InferenceRunner
from my_model.tabs.results import run_demo
from my_model.tabs.home import run_home
from my_model.state_manager import StateManager
from my_model.tabs.dataset_analysis import run_dataset_analyzer

class UIManager():
    """Manages the user interface for the Streamlit application."""

    def __init__(self):
        """Initializes the UIManager with predefined tabs."""
        
        self.tabs = {
            "Home": self.display_home,
            "Dataset Analysis": self.display_dataset_analysis,
            "Results": self.display_results,
            "Run Inference": self.display_run_inference,
            "Dissertation Report": self.display_dissertation_report,
            "Code": self.display_code
        }

        state_manager = StateManager()
        state_manager.initialize_state()

    
    def add_tab(self, tab_name, display_function):
        """Adds a new tab to the UI."""
        self.tabs[tab_name] = display_function

    
    def display_sidebar(self):
        """Displays the sidebar for navigation."""
        
        st.sidebar.title("Navigation")
        selection = st.sidebar.radio("Go to", list(self.tabs.keys()), disabled=st.session_state['loading_in_progress'])
        st.sidebar.image("Files/mm.jpeg", use_column_width=True)
        st.sidebar.markdown("**[Mohammed H AlHaj](https://www.linkedin.com/in/m7mdal7aj)**")

        return selection
        

    def display_selected_page(self, selection):
        """Displays the selected page based on user's choice."""
        
        if selection in self.tabs:
            self.tabs[selection]()

    
    def display_home(self):
        """Displays the Home page of the application."""
        
        run_home()
    
    def display_dataset_analysis(self):
        """Displays the Dataset Analysis page."""
        
        st.title("OK-VQA Dataset Analysis")
        st.write("This is a Place Holder until the contents are uploaded.")
        run_dataset_analyzer()

    
    def display_results(self):
        """Displays Evaluation Results page."""
        
        st.title("Evaluation Results & Analyses")
        st.write("This page demonstrates the model evaluation results and analyses in an interactive way.")
        st.write("\n")
        
        run_demo()

    
    def display_run_inference(self):
        """Displays the Run Inference page."""
        
        st.title("Run Inference")
        st.write("""Please note that this is not a general purpose model, it is specifically trained on 
        [OK-VQA Dataset](https://okvqa.allenai.org/) and desgined to give short and direct answers to the 
        given questions about the given image.\n""")

        inference_runner = InferenceRunner()
        inference_runner.run_inference()

    
    def display_dissertation_report(self):
        """Displays the Dissertation Report page."""
        
        st.title("Dissertation Report")
        st.write("Click the link below to view the PDF.")
        # Error handling for file access should be considered here
        st.download_button(
            label="Download PDF",
            data=open("Files/Dissertation Report.pdf", "rb"),
            file_name="example.pdf",
            mime="application/octet-stream"
        )

    
    def display_code(self):
        """Displays the Code page with a link to the project's code repository."""
        
        st.title("Code")
        st.markdown("You can view the code for this project on HuggingFace Space files page.")
        st.markdown("[View Code](https://huggingface.co/spaces/m7mdal7aj/Mohammed_Alhaj_KB-VQA/tree/main)", unsafe_allow_html=True)

    
    def display_placeholder(self):
        """Displays a placeholder for future content."""
        
        st.title("Stay Tuned")
        st.write("This is a Place Holder until the contents are uploaded.")