app_main_hf.py

import os
import sys
import time
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), )))

# from streamlit_extras.bottom_container import bottom
# from streamlit_extras.app_logo import add_logo
# from streamlit_extras.add_vertical_space import add_vertical_space
# from streamlit_extras.stylable_container import stylable_container
import torch
from imports import *
import streamlit as st
from streamlit_option_menu import option_menu
import asyncio
import shutil
import gc
from transformers.utils.hub import TRANSFORMERS_CACHE

torch.classes.__path__ = [] 


try:
    asyncio.get_running_loop()
except RuntimeError:
    asyncio.run(asyncio.sleep(0))

if sys.platform == "win32":
    asyncio.set_event_loop_policy(asyncio.WindowsSelectorEventLoopPolicy())
else:
    try:
        asyncio.get_running_loop()
    except RuntimeError:
        asyncio.set_event_loop(asyncio.new_event_loop())

st.set_page_config(
    page_title="Tachygraphy Microtext Analysis & Normalization",
    layout="wide"
)



import joblib
import importlib
import importlib.util

# sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), )))


from emotionMoodtag_analysis.emotion_analysis_main import show_emotion_analysis
from sentimentPolarity_analysis.sentiment_analysis_main import show_sentiment_analysis
from transformation_and_Normalization.transformationNormalization_main import transform_and_normalize
from dashboard import show_dashboard
from stacked_stacking_stages.stacking_stages import show_stacking_stages
from data_collection_form.data_collector import show_data_collector


# from text_transformation import show_text_transformation



def free_memory():
    #  """Free up CPU & GPU memory before loading a new model."""
    # global current_model, current_tokenizer

    # if current_model is not None:
    #     del current_model  # Delete the existing model
    #     current_model = None  # Reset reference

    # if current_tokenizer is not None:
    #     del current_tokenizer  # Delete the tokenizer
    #     current_tokenizer = None

    gc.collect()  # Force garbage collection for CPU memory

    if torch.cuda.is_available():
        torch.cuda.empty_cache()  # Free GPU memory
        torch.cuda.ipc_collect()  # Clean up PyTorch GPU cache

    # If running on CPU, reclaim memory using OS-level commands
    try:
        if torch.cuda.is_available() is False:
            psutil.virtual_memory()  # Refresh memory stats
    except Exception as e:
        print(f"Memory cleanup error: {e}")

    # Delete cached Hugging Face models
    try:
        cache_dir = TRANSFORMERS_CACHE
        if os.path.exists(cache_dir):
            shutil.rmtree(cache_dir)
            print("Cache cleared!")
    except Exception as e:
        print(f"❌ Cache cleanup error: {e}")



if "last_run" not in st.session_state:
    st.session_state.last_run = time.time()

def main():

    if "last_run" not in st.session_state:
        st.session_state.last_run = time.time()

    if time.time() - st.session_state.last_run > 3600:
        st.session_state.clear()
        st.rerun()

    if "current_page" not in st.session_state:
        st.session_state.current_page = None

    # selection = option_menu(
    #     menu_title="Navigation",
    #     options=[
    #         "Dashboard",
    #         "Stage 1: Sentiment Polarity Analysis",
    #         "Stage 2: Emotion Mood-tag Analysis",
    #         "Stage 3: Text Transformation & Normalization"
    #     ],
    #     icons=["joystick", "bar-chart", "emoji-laughing", "pencil"],
    #     styles={
    #         "container": {}},
    #     menu_icon="menu-button-wide-fill",
    #     default_index=0,
    #     orientation="horizontal"
    # )

    st.sidebar.title("Navigation")
    with st.sidebar:

        # selected = option_menu("Main Menu", ["Home", 'Settings'], 
        #         icons=['house', 'gear'], menu_icon="cast", default_index=1)
        # selected

        # # 2. horizontal menu
        # selected2 = option_menu(None, ["Home", "Upload", "Tasks", 'Settings'], 
        #     icons=['house', 'cloud-upload', "list-task", 'gear'], 
        #     menu_icon="cast", default_index=0, orientation="horizontal")
        # selected2

        selection = option_menu(
            menu_title=None,          # No title for a sleek look
            options=["Dashboard", "Stage 1: Sentiment Polarity Analysis", "Stage 2: Emotion Mood-tag Analysis", "Stage 3: Text Transformation & Normalization", "Stacked Stages", "Data Correction & Collection"],
            icons=['house', 'diagram-3', "snow", 'activity', 'collection', 'database-up'],
            menu_icon="cast",          # Main menu icon
            default_index=0,           # Highlight the first option
            orientation="vertical",
            styles={
                "container": {"padding": "0!important", "background-color": "#f8f9fa"},
                "icon": {"color": "#6c757d", "font-size": "18px"},
                "nav-link": {
                    "font-size": "16px",
                    "text-align": "left",
                    "margin": "0px",
                    "color": "#000000",
                    "transition": "0.3s",
                },
                "nav-link-selected": {
                    "background-color": "#020045",
                    "color": "white",
                    "font-weight": "bold",
                    "border-radius": "8px",
                },
            }
        )

    # st.sidebar.title("Navigation")
    # selection = st.sidebar.radio("Go to", ["Dashboard", "Stage 1: Sentiment Polarity Analysis", "Stage 2: Emotion Mood-tag Analysis", "Stage 3: Text Transformation & Normalization"])

    # if selection == "Dashboard":
    #     show_dashboard()
    # elif selection == "Stage 1: Sentiment Polarity Analysis":
    #     show_sentiment_analysis()
    # elif selection == "Stage 2: Emotion Mood-tag Analysis":
    #     # show_emotion_analysis()
    #     st.write("This section is under development.")
    # elif selection == "Stage 3: Text Transformation & Normalization":
    #     # show_text_transformation()
    #     st.write("This section is under development.")



    if st.session_state.current_page != selection:
        st.cache_data.clear()
        st.cache_resource.clear()
        free_memory()
        st.session_state.current_page = selection

    if selection == "Dashboard":
        # st.title("Tachygraphy Micro-text Analysis & Normalization")
        # st.cache_resource.clear()
        # free_memory()
        show_dashboard()

    elif selection == "Stage 1: Sentiment Polarity Analysis":
        # st.title("Sentiment Polarity Analysis")
        # st.cache_resource.clear()
        # free_memory()
        show_sentiment_analysis()

    elif selection == "Stage 2: Emotion Mood-tag Analysis":
        # st.title("Emotion Mood-tag Analysis")
        # st.cache_resource.clear()
        # free_memory()
        show_emotion_analysis()
        # st.write("This section is under development.")

    elif selection == "Stage 3: Text Transformation & Normalization":
        # st.title("Text Transformation & Normalization")
        # st.cache_resource.clear()
        # free_memory()
        transform_and_normalize()
        # st.write("This section is under development.")

    elif selection == "Stacked Stages":
        # st.title("Stacked Stages")
        # st.cache_resource.clear()
        # free_memory()
        show_stacking_stages()
    
    elif selection == "Data Correction & Collection":
        # st.title("Data Correction & Collection")
        # st.cache_resource.clear()
        # free_memory()
        show_data_collector()



    # st.sidebar.title("Navigation")
    # selection = st.sidebar.radio("Go to", ["Dashboard", "Stage 1: Sentiment Polarity Analysis", "Stage 2: Emotion Mood-tag Analysis", "Stage 3: Text Transformation & Normalization"])

    # if selection == "Dashboard":
    #     show_dashboard()
    # elif selection == "Stage 1: Sentiment Polarity Analysis":
    #     show_sentiment_analysis()
    # elif selection == "Stage 2: Emotion Mood-tag Analysis":
    #     # show_emotion_analysis()
    #     st.write("This section is under development.")
    # elif selection == "Stage 3: Text Transformation & Normalization":
    #     # show_text_transformation()
    #     st.write("This section is under development.")

    st.sidebar.title("About")
    st.sidebar.info("""
        **Contributors:**
        - Archisman Karmakar
            - [LinkedIn](https://www.linkedin.com/in/archismankarmakar/)
            - [GitHub](https://www.github.com/ArchismanKarmakar)
            - [Kaggle](https://www.kaggle.com/archismancoder)
        - Sumon Chatterjee
            - [LinkedIn](https://www.linkedin.com/in/sumon-chatterjee-3b3b43227)
            - [GitHub](https://github.com/Sumon670)
            - [Kaggle](https://www.kaggle.com/sumonchatterjee)

        **Mentors:**
        - Prof. Anupam Mondal
            - [LinkedIn](https://www.linkedin.com/in/anupam-mondal-ph-d-8a7a1a39/)
            - [Google Scholar](https://scholar.google.com/citations?user=ESRR9o4AAAAJ&hl=en)
            - [Website](https://sites.google.com/view/anupammondal/home)
        - Prof. Sainik Kumar Mahata
            - [LinkedIn](https://www.linkedin.com/in/mahatasainikk)
            - [Google Scholar](https://scholar.google.co.in/citations?user=OcJDM50AAAAJ&hl=en)
            - [Website](https://sites.google.com/view/sainik-kumar-mahata/home)

        This is our research project for our B.Tech final year and a journal which is yet to be published.
    """)

if __name__ == "__main__":
    main()