app.py

from dotenv import load_dotenv
import streamlit as st
import os
import google.generativeai as genai

# Load environment variables 
load_dotenv()

# Configure Gemini Pro model
genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
model = genai.GenerativeModel("gemini-1.5-pro")

# Initialize Streamlit app
st.set_page_config(page_title="Gemmy")

# Custom header with centered text
header_html = """
    <style>
        .header {
            text-align: center;
            font-family: Arial, sans-serif;
            font-size: 2em;
            color: #F8F9F9;
            margin-top: 50px;
            margin-bottom: 20px;
        }
    </style>
    <div class="header">
        Gemmy
    </div>
"""
st.markdown(header_html, unsafe_allow_html=True)

# Initialize session state for chat history
if "chat_history" not in st.session_state:
    st.session_state.chat_history = []
if 'chat_session' not in st.session_state:
    st.session_state['chat_session'] = model.start_chat(history=[])

# Function to get response from Gemini model
def get_gemini_response():
    question = st.session_state.input
    chat = st.session_state['chat_session']
    response = chat.send_message(question, stream=True)
    response_text = "".join(chunk.text for chunk in response)
    
    # Save question and response to chat history
    st.session_state.chat_history.append({"question": question, "response": response_text})
    
    # Clear the input box after submission
    st.session_state.input = ""

# Display chat history
for entry in st.session_state.chat_history:
    st.write(f"***You :*** {entry['question']}")
    st.write(f"***Gemmy :*** {entry['response']}")
    st.markdown("<hr>", unsafe_allow_html=True)  # Add a line below each response


# Input box 
st.text_input(" ", key="input", on_change=get_gemini_response, placeholder="Ask Gemmy")