import streamlit as st
import os
import pickle
import time
import g4f

st.set_page_config(page_title="MEDICAL ASSISTANT")

st.markdown(
    """
    <style>
        .title {
            text-align: center;
            font-size: 2em;
            font-weight: bold;
        }
    </style>
    <div class="title">🧠 MEDICAL ASSISTANT</div>
    """,
    unsafe_allow_html=True
)
# Load and Save Conversations
conversations_file = "conversations.pkl"


@st.cache_data
def load_conversations():
    try:
        with open(conversations_file, "rb") as f:
            return pickle.load(f)
    except (FileNotFoundError, EOFError):
        return []


def save_conversations(conversations):
    temp_conversations_file = conversations_file
    with open(temp_conversations_file, "wb") as f:
        pickle.dump(conversations, f)
    os.replace(temp_conversations_file, conversations_file)


if 'conversations' not in st.session_state:
    st.session_state.conversations = load_conversations()

if 'current_conversation' not in st.session_state:
    st.session_state.current_conversation = [{"role": "assistant", "content": "How may I assist you today?"}]


def truncate_string(s, length=30):
    return s[:length].rstrip() + "..." if len(s) > length else s


def display_chats_sidebar():
    with st.sidebar.container():
        st.header('Settings')
        col1, col2 = st.columns([1, 1])

        with col1:
            if col1.button('Start New Chat', key="new_chat"):
                st.session_state.current_conversation = []
                st.session_state.conversations.append(st.session_state.current_conversation)

        with col2:
            if col2.button('Clear All Chats', key="clear_all"):
                st.session_state.conversations = []
                st.session_state.current_conversation = []

    with st.sidebar.container():
        st.header('Conversations')
        for idx, conversation in enumerate(st.session_state.conversations):
            if conversation:
                chat_title_raw = next((msg["content"] for msg in conversation if msg["role"] == "user"), "New Chat")
                chat_title = truncate_string(chat_title_raw)
                if st.sidebar.button(f"{chat_title}", key=f"chat_button_{idx}"):
                    st.session_state.current_conversation = st.session_state.conversations[idx]


def main_app():
    for message in st.session_state.current_conversation:
        with st.chat_message(message["role"]):
            st.write(message["content"])

    def generate_response(prompt_input):
        string_dialogue = "You are a helpful Medical Assistant. You will Only respond to Medical related Queries. Say Sorry to any other Type of Queries."
        for dict_message in st.session_state.current_conversation:
            string_dialogue += dict_message["role"].capitalize() + ": " + dict_message["content"] + "\\n\\n"

        prompt = f"{string_dialogue}\n  {prompt_input} Assistant: "
        response_generator = g4f.ChatCompletion.create(
            model="gpt-3.5-turbo",
            messages=[{"role": "user", "content": prompt}],
            stream=True,
        )
        return response_generator

    if prompt := st.chat_input('Send a Message'):
        st.session_state.current_conversation.append({"role": "user", "content": prompt})
        with st.chat_message("user"):
            st.write(prompt)

        with st.chat_message("assistant"):
            with st.spinner("Thinking..."):
                response = generate_response(prompt)
                placeholder = st.empty()
                full_response = ''
                for item in response:
                    full_response += item
                    time.sleep(0.003)
                    placeholder.markdown(full_response)
                placeholder.markdown(full_response)
                st.session_state.current_conversation.append({"role": "assistant", "content": full_response})
                save_conversations(st.session_state.conversations)


display_chats_sidebar()
main_app()