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