Create app.py

app.py

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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)