import streamlit as st
import google.generativeai as genai
import os
from dotenv import load_dotenv
from PIL import Image
import tempfile
import time
import ssl

# Charger les variables d'environnement
load_dotenv()

# Configurer la clé API
genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))

# Paramètres de sécurité
safety_settings = [
    {"category": "HARM_CATEGORY_HARASSMENT", "threshold": "BLOCK_NONE"},
    {"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "BLOCK_NONE"},
    {"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", "threshold": "BLOCK_NONE"},
    {"category": "HARM_CATEGORY_DANGEROUS_CONTENT", "threshold": "BLOCK_NONE"},
]

def role_to_streamlit(role):
    return "assistant" if role == "model" else role

def upload_and_process_file(file_path):
    max_retries = 3
    retry_delay = 2
    
    for attempt in range(max_retries):
        try:
            if not os.path.exists(file_path):
                raise FileNotFoundError(f"Le fichier {file_path} n'existe pas")
                
            file_size = os.path.getsize(file_path)
            if file_size == 0:
                raise ValueError(f"Le fichier {file_path} est vide")
                
            uploaded_file = genai.upload_file(path=file_path)
            
            timeout = 300
            start_time = time.time()
            
            while uploaded_file.state.name == "PROCESSING":
                if time.time() - start_time > timeout:
                    raise TimeoutError("Timeout pendant le traitement du fichier")
                time.sleep(10)
                uploaded_file = genai.get_file(uploaded_file.name)

            if uploaded_file.state.name == "FAILED":
                raise ValueError(f"Échec du traitement: {uploaded_file.state.name}")
                
            return uploaded_file

        except Exception as e:
            if attempt < max_retries - 1:
                time.sleep(retry_delay * (attempt + 1))
            else:
                raise

def allowed_file(filename):
    ALLOWED_EXTENSIONS = {'txt','mp4','mp3','pdf', 'png', 'jpg', 'jpeg', 'gif'}
    return '.' in filename and filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS

# Initialiser le modèle
model = genai.GenerativeModel('gemini-1.5-flash', 
                            safety_settings=safety_settings,
                            system_instruction="Tu es un assistant intelligent. ton but est d'assister au mieux que tu peux. tu as été créé par Aenir et tu t'appelles Mariam")

# Configuration de la page Streamlit
st.set_page_config(page_title="Mariam - Assistant IA", page_icon="🤖")
st.title("Mariam AI - Chat Intelligent")

# CSS personnalisé 
st.markdown("""
    <style>
    .stFileUploader {
        margin-bottom: 10px;
    }
    .upload-container {
        display: flex;
        align-items: center;
        gap: 10px;
    }
    .fixed-input {
        position: fixed;
        bottom: 0;
        left: 0;
        right: 0;
        z-index: 1000;
        background-color: white;
        padding: 10px;
        box-shadow: 0 -2px 5px rgba(0,0,0,0.1);
    }
    .main-content {
        margin-bottom: 80px;  /* Pour laisser de l'espace pour l'input fixe */
    }
    </style>
""", unsafe_allow_html=True)

# Initialiser l'historique de chat
if "chat" not in st.session_state:
    st.session_state.chat = model.start_chat(history=[])

# Conteneur principal avec marge en bas
main_container = st.container()
main_container.markdown('<div class="main-content">', unsafe_allow_html=True)

# Zone d'upload en haut
upload_container = st.container()
with upload_container:
    uploaded_files = st.file_uploader("📁", 
                                      type=["txt","mp4","mp3","pdf", "jpg", "jpeg", "png", "gif"], 
                                      accept_multiple_files=True)

# Afficher l'historique des messages
for message in st.session_state.chat.history:
    with main_container.chat_message(role_to_streamlit(message.role)):
        st.markdown(message.parts[0].text)
        if len(message.parts) > 1:
            for part in message.parts[1:]:
                if hasattr(part, 'image'):
                    st.image(part.image)

# Fermer le div de marge
main_container.markdown('</div>', unsafe_allow_html=True)

# Input fixé en bas
st.markdown('<div class="fixed-input">', unsafe_allow_html=True)
prompt = st.chat_input("Que puis-je faire pour vous ?")
st.markdown('</div>', unsafe_allow_html=True)

if prompt:
    content = [prompt]
    temp_files = []
    
    try:
        # Traitement des fichiers
        if uploaded_files:
            for file in uploaded_files:
                if allowed_file(file.name):
                    # Si c'est une image
                    if file.type.startswith('image/'):
                        image = Image.open(file)
                        content.append(image)
                        st.chat_message("user").image(image)
                    else:
                        # Pour les autres types de fichiers
                        with tempfile.NamedTemporaryFile(delete=False, suffix=os.path.splitext(file.name)[1]) as temp_file:
                            temp_file.write(file.getvalue())
                            temp_files.append(temp_file.name)
                            uploaded_file = upload_and_process_file(temp_file.name)
                            content.append(uploaded_file)

        # Afficher le message utilisateur
        st.chat_message("user").markdown(prompt)
        
        # Envoyer le message et afficher la réponse
        response = st.session_state.chat.send_message(content)
        with st.chat_message("assistant"):
            st.markdown(response.text)

    except Exception as e:
        st.error(f"Une erreur est survenue : {str(e)}")
    
    finally:
        # Nettoyage des fichiers temporaires
        for temp_file in temp_files:
            try:
                os.unlink(temp_file)
            except Exception as e:
                print(f"Erreur lors de la suppression du fichier temporaire {temp_file}: {e}")