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import pandas as pd
from ydata_profiling import ProfileReport
import streamlit as st
from streamlit_pandas_profiling import st_profile_report
from langchain.llms.openai import OpenAI
from langchain.agents.agent_types import AgentType
import time
def main():
st.sidebar.title("App Options")
option = st.sidebar.selectbox("Choose an option", ["Data Profiling", "Personal Assistant"])
if option == "Data Profiling":
data_profiling()
elif option == "Personal Assistant":
personal_assistant()
def data_profiling():
st.title("Data Profiling App")
# Load the data
df = pd.read_csv('data.csv')
# Display the dataframe
st.dataframe(df)
# Generate and display the data profile report
pr = ProfileReport(df, title="Report")
st_profile_report(pr)
def personal_assistant():
st.sidebar.title("OpenAI Settings")
openai_api_key = st.sidebar.text_input("Enter your OpenAI API Key", type="password")
os.environ['OPENAI_API_KEY'] = openai_api_key
st.title("Personal Assistant")
st.text("A BR CREATION")
st.image("chatbot.jpg", caption="Chatbot", width=178)
uploaded_file = st.file_uploader("Upload CSV file", type=["csv"])
if uploaded_file is None:
st.warning("Please upload a CSV file.")
st.stop() # Stop execution if no file uploaded
llm = OpenAI(temperature=0)
agent = create_csv_agent(
llm,
uploaded_file,
verbose=False,
agent_type=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
)
query = st.text_input("What would you like to know?")
if st.button("Ask"):
if query.strip() == "":
st.warning("Please enter a query.")
else:
start = time.time()
answer = agent.run(query)
end = time.time()
st.write(answer)
st.write(f"Answer (took {round(end - start, 2)} s.)")
if __name__ == "__main__":
main()
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