import os
import streamlit as st
import json
from streamlit_option_menu import option_menu
from gemini_utility import (load_gemini_pro, gemini_pro_vision_responce)
from PIL import Image

# Configuración de la página
st.set_page_config(
    page_title="GnosticDev AI",
    page_icon="🤖",
    layout="centered",
    initial_sidebar_state="expanded",
)

# Función para guardar el historial en cookies
def save_chat_history(history):
    serializable_history = []
    for message in history:
        serializable_history.append({
            "role": message.role,
            "text": message.parts[0].text
        })
    st.session_state.cookie_chat_history = json.dumps(serializable_history)

# Función para cargar el historial desde cookies
def load_chat_history():
    if 'cookie_chat_history' in st.session_state:
        try:
            history = json.loads(st.session_state.cookie_chat_history)
            model = load_gemini_pro()
            chat = model.start_chat(history=[])
            if st.session_state.system_prompt:
                chat.send_message(st.session_state.system_prompt)
            for message in history:
                if message["role"] != "model" or not message["text"].startswith(st.session_state.system_prompt):
                    chat.send_message(message["text"])
            return chat
        except Exception as e:
            st.error(f"Error cargando el historial: {e}")
    return None

# Inicializar estados
if "system_prompt" not in st.session_state:
    st.session_state.system_prompt = st.session_state.get('cookie_system_prompt', "")

with st.sidebar:
    selected = option_menu(
        "GD AI",
        ["System Prompt", "Chatbot", "Image Captioning"],
        menu_icon="robot",
        icons=['gear', 'chat-dots-fill', 'image-fill'],
        default_index=0
    )
    
    # Botón para borrar historial
    if st.button("Borrar Historial"):
        if 'cookie_chat_history' in st.session_state:
            del st.session_state.cookie_chat_history
        if 'chat_session' in st.session_state:
            del st.session_state.chat_session
        st.success("Historial borrado!")

def translate_role_to_streamlit(user_role):
    return "assistant" if user_role == "model" else user_role

if selected == "System Prompt":
    st.title("Configuración del System Prompt")
    
    new_system_prompt = st.text_area(
        "Ingresa las instrucciones para el AI (System Prompt)",
        value=st.session_state.system_prompt,
        height=300,
        help="Escribe aquí las instrucciones que definirán el comportamiento del AI"
    )
    
    if st.button("Guardar System Prompt"):
        st.session_state.system_prompt = new_system_prompt
        st.session_state.cookie_system_prompt = new_system_prompt
        if "chat_session" in st.session_state:
            del st.session_state.chat_session
        st.success("System Prompt actualizado con éxito!")
        
    if st.session_state.system_prompt:
        st.markdown("### System Prompt Actual:")
        st.info(st.session_state.system_prompt)

elif selected == "Chatbot":
    model = load_gemini_pro()
    
    # Inicializar o cargar sesión de chat
    if "chat_session" not in st.session_state:
        loaded_chat = load_chat_history()
        if loaded_chat:
            st.session_state.chat_session = loaded_chat
        else:
            st.session_state.chat_session = model.start_chat(history=[])
            if st.session_state.system_prompt:
                st.session_state.chat_session.send_message(st.session_state.system_prompt)

    st.title("Gnosticdev Chatbot")
    
    if st.session_state.system_prompt:
        with st.expander("Ver System Prompt actual"):
            st.info(st.session_state.system_prompt)
    
    # Mostrar historial
    for message in st.session_state.chat_session.history:
        with st.chat_message(translate_role_to_streamlit(message.role)):
            st.markdown(message.parts[0].text)

    # Campo de entrada
    user_prompt = st.chat_input("Preguntame algo...")
    if user_prompt:
        st.chat_message("user").markdown(user_prompt)
        gemini_response = st.session_state.chat_session.send_message(user_prompt)
        with st.chat_message("assistant"):
            st.markdown(gemini_response.text)
        
        # Guardar historial actualizado
        save_chat_history(st.session_state.chat_session.history)

elif selected == "Image Captioning":
    st.title("Image Caption Generation📸")
    upload_image = st.file_uploader("Upload an image...", type=["jpg", "jpeg", "