app.py

from dotenv import load_dotenv
import os
import streamlit as st
from streamlit_option_menu import option_menu
import pandas as pd
import base64
from Functions import RFPProcessor
# from localStoragePy import localStoragePy
from Utils import (
    export,
    clear_rfp_data,
    get_binary_file_downloader_html,
    generate_roadmap_image,
)
# from Login_and_email import *
from Proposal import prop
#localStorage = localStoragePy("RFP", "json")

# Initialize session states
if "generated" not in st.session_state:
    st.session_state["generated"] = []
if "past" not in st.session_state:
    st.session_state["past"] = []
if "input" not in st.session_state:
    st.session_state["input"] = ""
if "vectorstore" not in st.session_state:
    st.session_state["vectorstore"] = None
if "rfp_details" not in st.session_state:
    st.session_state["rfp_details"] = ""
if "is_data_processed" not in st.session_state:
    st.session_state["is_data_processed"] = False
if "user_stories" not in st.session_state:
    st.session_state["user_stories"] = ""
if "user_stories_data" not in st.session_state:
    st.session_state["user_stories_data"] = []
if "user_stories_json" not in st.session_state:
    st.session_state["user_stories_json"] = {}
if "is_user_stories_created" not in st.session_state:
    st.session_state["is_user_stories_created"] = False
if "rfp_summary" not in st.session_state:
    st.session_state["rfp_summary"] = ""
if "estimation_data" not in st.session_state:
    st.session_state["estimation_data"] = []
if "estimation_data_json" not in st.session_state:
    st.session_state["estimation_data_json"] = {}
if "is_estimation_data_created" not in st.session_state:
    st.session_state["is_estimation_data_created"] = False
if "roadmap_data" not in st.session_state:
    st.session_state["roadmap_data"] = []
if "roadmap_data_json" not in st.session_state:
    st.session_state["roadmap_data_json"] = []
if "is_roadmap_data_created" not in st.session_state:
    st.session_state["is_roadmap_data_created"] = False
if "is_presentation_created" not in st.session_state:
    st.session_state["is_presentation_created"] = False


def main():
    function = RFPProcessor()

    if "input" not in st.session_state:
        st.session_state["input"] = ""

    with st.sidebar:
        menu_choice = option_menu(
            menu_title="RFPStoryCraft",
            options=[
                "Home",
                "RFP Bot",
                "User Stories",
                "Summary",
                "Estimations",
                "RoadMap",
            ],
            icons=["house", "list-task", "book", "book", "list-task"],
        )

        if st.session_state["is_data_processed"] == True:
            st.button("Clear RFP Data", on_click=clear_rfp_data)

        # if localStorage.getItem("email"):
        #     st.button("Log out", on_click=lambda: log_out_user(localStorage))

    if menu_choice == "Home":
        with st.form("my_form"):
            project_name = st.text_input(
                "Project Name",
                key="Project Name",
                type="default",
                placeholder="Project Name",
            )
            files = st.file_uploader(
                "Document", type=["pdf", "txt", "docx"], accept_multiple_files=True
            )

            submitted = st.form_submit_button("Process Data")

            if submitted:
                if project_name and files:
                    function.process_rfp_data(project_name, files)
                else:
                    st.warning(
                        "project_name and file are required to create create stories",
                        icon="⚠️",
                    )

    if menu_choice == "RFP Bot":
        if st.session_state["is_data_processed"] == True:
            st.title(" RFP Chatbot ")
            st.subheader(" Powered by Coffeebeans")
            st.text_input(
                "You: ",
                st.session_state["input"],
                key="input",
                placeholder="Your AI assistant here! Ask me Queries related to RFP",
                on_change=function.genrate_bot_result(),
                label_visibility="hidden",
            )
            with st.container():
                for i in range(len(st.session_state["generated"]) - 1, -1, -1):
                    st.success(st.session_state["generated"][i], icon="🤖")
                    st.info(st.session_state["past"][i], icon="🧐")
        else:
            st.warning("Plesase Process RFP Details to access this feature", icon="⚠️")

    if menu_choice == "User Stories":
        if st.session_state["is_data_processed"] == True:
            st.title("User Stories")
            st.button(
                "Genrate User Stories",
                type="primary",
                on_click=function.genrate_user_stories,
            )
            if st.session_state["is_user_stories_created"] == True:
                st.button(
                    "Export Stories",
                    on_click=lambda: export(st.session_state["user_stories_data"]),
                )
                with st.container():
                    df = pd.DataFrame(st.session_state["user_stories_data"])
                    st.table(df)
        else:
            st.warning("Plesase Process RFP Details to access this feature", icon="⚠️")

    if menu_choice == "Summary":
        if st.session_state["is_data_processed"] == True:
            st.title("Summary")
            with st.container():
                st.markdown(st.session_state["rfp_summary"])
        else:
            st.warning("Plesase Process RFP Details to access this feature", icon="⚠️")

    if menu_choice == "Estimations":
        if st.session_state["is_data_processed"] == True:
            if st.session_state["is_user_stories_created"] == True:
                st.title("Estimations")
                senior_developers = st.text_input(
                    label="Number of Senior Developers",
                    placeholder="Enter here....",
                )
                junior_developers = st.text_input(
                    label="Number of Junior Developers",
                    placeholder="Enter here...",
                )
                tech_leads = st.text_input(
                    label="Number of Tech Leads",
                    placeholder="Enter here....",
                )

                if (
                    senior_developers
                    and junior_developers
                    and tech_leads
                    and st.session_state["is_user_stories_created"] == True
                ):
                    st.button(
                        "Generate Estimations",
                        on_click=lambda: function.generate_estimations(
                            tech_leads, senior_developers, junior_developers
                        ),
                    )

                    if st.session_state["is_estimation_data_created"] == True:
                        st.button(
                            "Export Stories",
                            on_click=lambda: export(
                                st.session_state["estimation_data"]
                            ),
                        )

                        with st.container():
                            df = pd.DataFrame(st.session_state["estimation_data"])
                            st.table(df)
            else:
                st.warning(
                    "Plesase Process User Stories to access this feature", icon="⚠️"
                )
        else:
            st.warning("Plesase Process RFP Details to access this feature", icon="⚠️")

    if menu_choice == "RoadMap":
        if st.session_state["is_data_processed"] == True:
            if st.session_state["is_estimation_data_created"] == True:
                st.title("RoadMap")
                st.button(
                    "Generate RoadMap", on_click=lambda: function.generate_roadmap()
                )

                if st.session_state["is_roadmap_data_created"] == True:
                    st.button(
                        "Export RoadMap",
                        on_click=lambda: export(st.session_state["roadmap_data"]),
                    )
                    if st.button("Generate Roadmap and Download"):
                        st.info("Generating roadmap... Please wait.")
                        # Generate the roadmap image
                        generate_roadmap_image()

                    with st.container():
                        df = pd.DataFrame(st.session_state["roadmap_data"])
                        st.table(df)

            else:
                st.warning(
                    "Please Process the Estimations Data to access this feature",
                    icon="⚠️",
                )
        else:
            st.warning("Plesase Process RFP Details to access this feature", icon="⚠️")

    # if menu_choice == "Proposal":
    #     if st.session_state["is_data_processed"] == True:
    #         if st.session_state["is_user_stories_created"] == True:
    #             st.title("Proposal")
    #             num_slides = st.number_input(
    #                 "Enter the number of slides", min_value=1, max_value=20, value=None
    #             )
    #             if num_slides:
    #                 st.button(
    #                     "Generate Presentation", on_click=lambda: prop(num_slides)
    #                 )

    #                 if st.session_state["is_presentation_created"] == True:
    #                     st.success("Presentation Created!", icon="✅")
    #                     with open("Generated_Presentation.pptx", "rb") as pptx_file:
    #                         pptx_bytes = pptx_file.read()
    #                         st.download_button(
    #                             label="Download Presentation",
    #                             data=pptx_bytes,
    #                             file_name="Generated_Presentation_from_code.pptx",
    #                             mime="application/vnd.openxmlformats-officedocument.presentationml.presentation",
    #                         )

    #         else:
    #             st.warning(
    #                 "Please Process the User Stories Data to access this feature",
    #                 icon="⚠️",
    #             )
    #     else:
    #         st.warning("Plesase Process RFP Details to access this feature", icon="⚠️")


if __name__ == "__main__":
        main()