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import openai
import os
import streamlit as st
import pandas as pd
from streamlit_chat import message as st_message # Ensure streamlit_chat is installed
# Load data function remains the same
def load_data(path):
return pd.read_csv(path)
# Assuming you've set your OpenAI API key in the environment variables
openai.api_key = os.getenv("OPENAI_API_KEY")
# File uploader and data loading logic can remain the same
uploaded_file = st.sidebar.file_uploader("Choose a CSV file", type="csv")
if uploaded_file is not None:
st.session_state["df"] = pd.read_csv(uploaded_file)
# Example function to generate a response from OpenAI's chat model
def ask_openai(prompt):
try:
response = openai.ChatCompletion.create(
model="gpt-3.5-turbo", # Adjust model as needed
messages=[{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": prompt}],
)
return response.choices[0].message["content"]
except Exception as e:
print(f"Error in generating response: {e}")
return "Sorry, I couldn't generate a response. Please try again."
# Example chat interaction in Streamlit
if "chat_history" not in st.session_state:
st.session_state["chat_history"] = []
if prompt := st.text_input("Ask me anything about the data:"):
st.session_state["chat_history"].append({"role": "user", "content": prompt})
response = ask_openai(prompt)
st.session_state["chat_history"].append({"role": "assistant", "content": response})
for chat in st.session_state["chat_history"]:
st_message(chat["content"], is_user=True if chat["role"] == "user" else False)
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