pages/2_📝_Model_Panel.py

import streamlit as st
import sys,os


sys.path.append(f'{os.getcwd()}/utils')
from utils.model_users import get_product_dev_page_layout,get_product_manager_page_layout,get_product_practitioner_page_layout

# st.write(st.session_state.user_group)
USER_GROUPS = ["Developer", "Manager", "Practitioner"]

st.set_page_config(layout="wide")

if 'user_group' not in st.session_state:
    index_tmp = 0
else: 
    index_tmp = USER_GROUPS.index(st.session_state['user_group'])

#Sidebar for USER GROUPS
st.sidebar.title("USER GROUPS")
backend = st.sidebar.selectbox(
            "Select User-Group ", USER_GROUPS, index=index_tmp
        )

st.session_state['user_group'] = backend



st.title("Model Panel for OCT Image Analysis")
st.write(
        """
       The users can find following information regarding the AI model developed for the task: what is the purpose of the model, how it was developed and how it is used. Thus,answers 
       to these questions areprovided via the tabs described below.
        """)

list_test = """<ul>
                <li>Model Generic information contains a summary of the model’s details, including its main features, capabilities, and intended use. 
                    It also highlights the model’s behaviour, such as the type of data inputs(image, feature etc) it can handle and the types of outputs it produces.</li>
                <li>Model Development Information includes information on the hyperparameters, model development framework/library such as Tensorflow or PyTorch, and other technical details. It also includes a complete analysis of the model’s inference performance, such as the model size, 
                        hardware-specific (GPU and CPU) inference time,and speed, as well as reproducibility check list.</li>
                <li>Model Deployment Information provides information on how the model is used in production, including details on the inference speed and latency,  
                        and how users can access and interact with the model in production.</li>
                </ul>"""
st.markdown(list_test, unsafe_allow_html=True)

if backend == "Developer":
    get_product_dev_page_layout()

if backend == "Manager":
    get_product_manager_page_layout()

if backend == "Practitioner":
    get_product_practitioner_page_layout()