from dotenv import load_dotenv
load_dotenv()

import streamlit as st
import os
import google.generativeai as genai

# Configure Google Generative AI
genai.configure(api_key=os.getenv("GOOGLE_KEY"))
model = genai.GenerativeModel("gemini-pro")
chat = model.start_chat(history=[])

def get_gemini_response(prompt):
    try:
        response = chat.send_message(prompt, stream=True)
        return response
    except Exception as e:
        return f"An error occurred: {str(e)}"

# Streamlit app configuration
st.set_page_config(page_title = "Med ChatBot")
st.header = ("ChatBot App")

# Initialize session state for chat history
if "chat_history" not in st.session_state:
    st.session_state["chat_history"] = []

# Input and submission button
input_text = st.text_input("Input: ", key="input")
submit = st.button("Ask the question")

if submit and input_text:
    # Context for the LLM with history included
    chat_history_text = " ".join([f"{role}: {text}" for role, text in st.session_state["chat_history"]])
    
    context = (
        "You are a medical chatbot designed to assist users in understanding their symptoms. "
        "Provide clear, concise, and informative responses based on NHS guidelines. "
        "Avoid technical jargon and code snippets. If asked a question unrelated to medical topics, "
        "respond with: 'I am a medical bot and I don't have that knowledge.' "
        f"Previous conversation: {chat_history_text} "
    )

    prompt = f"{context} User's latest input: {input_text}"  # Include the latest user input
    response = get_gemini_response(prompt)

    # Add user query to session state chat history
    st.session_state['chat_history'].append(("You", input_text))

    st.subheader("The Response is")
    if isinstance(response, str):  # Handle cases where response might be a string
        st.write(response)
        st.session_state['chat_history'].append(("Bot", response))
    else:
        for chunk in response:
            st.write(chunk.text)
            st.session_state['chat_history'].append(("Bot", chunk.text))

st.subheader("The Chat History is")

for role, text in st.session_state['chat_history']:
    st.write(f"{role}: {text}")