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"""
This is a streamlit application that allows user to query multiple csv
files and return the answer based on the text in the csv files.
It uses streamlit to create a web application to load the csv files and
query them.
Langchain and OpenAI API are used to generate the answer based on the
text in the csv files.
Credit: https://www.youtube.com/@alejandro_ao 👊🏿
"""
from langchain.agents import create_csv_agent
from langchain.chat_models import ChatOpenAI
from langchain.agents.agent_types import AgentType
#from dotenv import load_dotenv
import os
import pandas as pd
import streamlit as st
def main():
# set the page title
st.set_page_config("Data Analysis Helper \U0001F4CA")
st.markdown("# Data Analysis Helper")
st.markdown("This tool helps you analyze your CSV files. Please remember to **remove personal information** first, such as names, addresses, phone numbers, emails, etc.")
st.markdown("## How to use this tool")
st.markdown("1. Upload your CSV file")
st.markdown("2. Ask a question about your CSV file")
st.markdown("3. Wait for the answer to appear")
st.markdown("## Example questions")
st.markdown("1. What is the average age?")
st.markdown("2. What is the average income?")
st.markdown("3. What is the average age of people who live in London?")
st.markdown("Go to [this page](https://openai.com/pricing) to get an OpenAI API key.")
# text input to ask for openai api key
# then hide the input
openai_api_key = st.text_input("Enter your OpenAI API key", type="password")
# set this key as an environment variable
os.environ["OPENAI_API_KEY"] = openai_api_key
# load the api key from the .env file
#load_dotenv()
# inform the user that the api key is loaded
if os.getenv("OPENAI_API_KEY") is None or os.getenv("OPENAI_API_KEY") == "":
print("OPENAI_API_KEY is not set")
exit(1)
else:
print("OPENAI_API_KEY is set")
# inform user that the model being used is the turbo model
st.write("Using the gpt-3.5-turbo-0613 model from OpenAI")
# Upload the CSV file
csv_file = st.file_uploader("Upload a CSV file", type="csv")
# if the user has uploaded a csv file then save it to the current directory
if csv_file is not None:
with open(os.path.join(os.getcwd(), csv_file.name), "wb") as f:
f.write(csv_file.getbuffer())
st.write("CSV file uploaded to: ", os.path.join(os.getcwd(), csv_file.name))
# see a preview of the csv file
st.write("Preview of the CSV file:")
# see a preview of the csv file
df = pd.read_csv(os.path.join(os.getcwd(), csv_file.name))
st.dataframe(df.head()) # Display the first few rows of the DataFrame
# create the agent
agent = create_csv_agent(
ChatOpenAI(temperature=0, model="gpt-3.5-turbo-0613"),
os.path.join(os.getcwd(), csv_file.name),
verbose=True,
agent_type=AgentType.OPENAI_FUNCTIONS,
)
# ask the user for a question
user_question = st.text_input("Ask a question \U0001F914 about your CSV: ")
# if the user has asked a question then run the agent
if user_question is not None and user_question != "":
with st.spinner(text="In progress..."):
st.write(agent.run(user_question))
if __name__ == "__main__":
main()
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