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health_assist.py

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+import os
+import streamlit as st
+import pandas as pd
+import google.generativeai as genai
+
+# Set the background image
+st.set_page_config(page_title="Quantified Self Chat", page_icon=":bar_chart:", layout="wide", initial_sidebar_state="expanded", menu_items=None)
+st.markdown(
+    """
+    <style>
+    body {
+        background-image: url("quantified_image.jpg");
+        background-size: cover;
+    }
+    </style>
+    """,
+    unsafe_allow_html=True,
+)
+
+# Set the environment variable
+os.environ['GOOGLE_API_KEY'] = st.secrets["GOOGLE_API_KEY"]
+
+def configure_model():
+    """Configure the generative model."""
+    genai.configure(api_key=os.getenv('GOOGLE_API_KEY'))
+    return genai.GenerativeModel('gemini-pro')
+
+def load_data():
+    """Load and preprocess the data."""
+    uploaded_file = st.file_uploader("Choose a CSV file", type='csv')
+    if uploaded_file is not None:
+        df = pd.read_csv(uploaded_file, delimiter=',')
+        df.drop(columns=['Person ID', 'Gender', 'Age', 'Occupation', 'Nurse ID'], inplace=True)
+        return df.to_dict(orient='list')
+
+def get_response(model, user_input, sleep_data):
+    """Generate a response from the model."""
+    input_prompt = f"This is user asking : {user_input}\n\n based on what user asked, this is the sleep data: {str(sleep_data)}\n\n Give me short quantified answer in 1 to 5 lines only based on the sleep data: "
+    return model.generate_content(input_prompt).text
+
+def main():
+    """Main function to run the app."""
+    st.title('The Quantified Self Chat')
+    model = configure_model()
+    sleep_data = load_data()
+
+    if sleep_data is not None:
+
+        st.subheader('Sleep dataset')
+        st.write(pd.DataFrame.from_dict(sleep_data))
+
+        # Initialize session state for chat history
+        if 'chat_history' not in st.session_state:
+            st.session_state['chat_history'] = []
+
+        user_input = st.text_input("Ask Questions", "")
+
+        if st.button("Submit"):  # Check if user input is not empty
+            response = get_response(model, user_input, sleep_data)
+            # Update chat history
+            st.session_state['chat_history'].append({"User": user_input, "Gemini Pro": response})
+
+        # Display chat history
+        for chat in st.session_state['chat_history']:
+            st.write(f"User: {chat['User']}")
+            st.write(f"AI Assistant: {chat['Gemini Pro']}")
+
+    else:
+        st.write("Please upload a CSV file to load the sleep data.")
+
+if __name__ == "__main__":
+    main()