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import streamlit as st
from streamlit_option_menu import option_menu
from memory import memory_storage
from agent_chain import get_agent_chain
from default_text import default_text4
from generate_plot import generate_plot, retry_generate_plot
from markup import app_intro, how_use_intro
from modules import replace_default_dataset, save_uploaded_dataset
import pandas as pd
import os
if 'error' not in st.session_state:
st.session_state['error'] = []
def tab1():
col1, col2 = st.columns([1, 2])
with col1:
st.image("image.jpg", use_column_width=True)
with col2:
st.markdown(app_intro(), unsafe_allow_html=True)
st.markdown(how_use_intro(),unsafe_allow_html=True)
#st.markdown("<p style='font-size: 14px; color: #777;'>Disclaimer: This app is a proof-of-concept and may not be suitable for real-world decisions. During the Hackthon period usage information are being recorded using Langsmith</p>", unsafe_allow_html=True)
def tab2():
dataset_option = st.radio("Select Dataset Option", ("Default", "Upload"))
if dataset_option == "Default":
if st.button("Use Default Dataset"):
replace_default_dataset()
else:
uploaded_file = st.file_uploader("Upload a CSV file", type=["csv"])
if uploaded_file:
save_uploaded_dataset(uploaded_file)
st.header("🗣️ Chat")
for i, msg in enumerate(memory_storage.messages):
name = "user" if i % 2 == 0 else "assistant"
st.chat_message(name).markdown(msg.content)
if user_input := st.chat_input("User Input"):
with st.chat_message("user"):
st.markdown(user_input)
with st.spinner("Generating Response..."):
with st.chat_message("assistant"):
zeroshot_agent_chain = get_agent_chain()
response = zeroshot_agent_chain({"input": user_input})
answer = response['output']
st.markdown(answer)
if st.sidebar.button("Clear Chat History"):
memory_storage.clear()
def tab4():
try:
df = pd.read_csv("dataset.csv")
st.header("Dataset Content")
st.dataframe(df)
except FileNotFoundError:
st.error("File 'dataset.csv' not found in the current directory.")
except pd.errors.EmptyDataError:
st.error("File 'dataset.csv' is empty.")
except pd.errors.ParserError:
st.error("File 'dataset.csv' could not be parsed as a CSV file.")
def main():
st.set_page_config(page_title="NaturalViz", page_icon=":memo:", layout="wide")
#os.environ['LANGCHAIN_TRACING_V2'] = "true"
#os.environ['LANGCHAIN_API_KEY'] == st.secrets['LANGCHAIN_API_KEY']
tabs = ["Intro","Chat", "View Dataset"]
with st.sidebar:
current_tab = option_menu("Select a Tab", tabs, menu_icon="cast")
tab_functions = {
"Intro": tab1,
"Chat": tab2,
"View Dataset": tab4,
}
if current_tab in tab_functions:
tab_functions[current_tab]()
if __name__ == "__main__":
main() |