import os
import keyfile
import warnings
import streamlit as st
from langchain_google_genai import ChatGoogleGenerativeAI
from langchain.schema import HumanMessage, SystemMessage, AIMessage

# Ignore warnings
warnings.filterwarnings("ignore")

# Streamlit settings
st.set_page_config(page_title="Magical Healer")
st.header("Welcome, What help do you need?")

# Initialize session state for messages
if "sessionMessages" not in st.session_state:
    st.session_state["sessionMessages"] = [
        SystemMessage(content="You are a medieval magical healer known for your peculiar sarcasm")
    ]

# Set Google API key
os.environ["GOOGLE_API_KEY"] = keyfile.GOOGLEKEY

# Initialize the model
llm = ChatGoogleGenerativeAI(
    model="gemini-1.5-pro",
    temperature=0.7,
    convert_system_message_to_human=True
)

# Response function
def load_answer(question):
    # Add user question to the message history
    st.session_state.sessionMessages.append(HumanMessage(content=question))
    
    # Get AI's response
    assistant_answer = llm.invoke(st.session_state.sessionMessages)
    
    # Append AI's answer to the session messages
    if isinstance(assistant_answer, AIMessage):
        st.session_state.sessionMessages.append(assistant_answer)
        return assistant_answer.content
    else:
        st.session_state.sessionMessages.append(AIMessage(content=assistant_answer))
        return assistant_answer

# Capture user input
def get_text():
    input_text = st.text_input("You: ", key="input")
    return str(input_text)

# Main implementation
user_input = get_text()
submit = st.button("Generate")

if submit and user_input:
    response = load_answer(user_input)
    st.subheader("Answer:")
    st.write(response)