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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()
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