import gradio as gr
from openai import OpenAI
import os
from datetime import datetime
import uuid

api_key = os.environ.get("KEY_SECRET")
if not api_key:
    raise ValueError("Variable d'environnement KEY_SECRET introuvable.")

client = OpenAI(
    api_key=api_key,
    base_url="https://api.together.xyz/v1",
)

conversation_history = {}
current_conversation_id = None

def generate_conversation_title(message):
    return message[:50] + "..." if len(message) > 50 else message

def create_new_conversation():
    global current_conversation_id
    current_conversation_id = str(uuid.uuid4())
    timestamp = datetime.now().strftime("%Y-%m-%d %H:%M")
    conversation_history[current_conversation_id] = {
        "title": "Nouvelle conversation",
        "timestamp": timestamp,
        "messages": [],
        "system_prompt": "Tu es un assistant IA utile, honnête et inoffensif."
    }
    return current_conversation_id

# --- AJOUT DU PARAMÈTRE TEMPERATURE ICI ---
def chat(message, history, system_prompt, temperature):
    api_messages = [{"role": "system", "content": system_prompt}]
    for entry in history:
        api_messages.append({"role": entry["role"], "content": entry["content"]})
    api_messages.append({"role": "user", "content": message})

    try:
        stream = client.chat.completions.create(
            model="meta-llama/Llama-3.3-70B-Instruct-Turbo",
            messages=api_messages,
            stream=True,
            temperature=temperature, # Utilise maintenant la valeur du slider
            max_tokens=1024
        )
        partial_text = ""
        for chunk in stream:
            if chunk.choices[0].delta.content:
                partial_text += chunk.choices[0].delta.content
                yield partial_text
    except Exception as e:
        yield f"❌ Erreur: {str(e)}"

# --- AJOUT DU PARAMÈTRE TEMPERATURE ICI ---
def respond(message, history, system_prompt, temperature):
    global current_conversation_id

    if not current_conversation_id:
        current_conversation_id = create_new_conversation()

    if not conversation_history[current_conversation_id]["messages"]:
        conversation_history[current_conversation_id]["title"] = generate_conversation_title(message)

    history.append({"role": "user", "content": message})
    history.append({"role": "assistant", "content": ""})

    # On passe la température à la fonction chat
    for partial_response in chat(message, history[:-2], system_prompt, temperature):
        history[-1]["content"] = partial_response
        yield "", history

    conversation_history[current_conversation_id]["messages"] = history
    conversation_history[current_conversation_id]["system_prompt"] = system_prompt

def get_conversation_list():
    if not conversation_history:
        return "Aucune conversation"
    items = []
    for conv_id, conv_data in sorted(
        conversation_history.items(),
        key=lambda x: x[1]["timestamp"],
        reverse=True
    ):
        items.append(f"{conv_data['title']}\n{conv_data['timestamp']}")
    return "\n\n".join(items)

def new_conversation():
    create_new_conversation()
    return (
        [],
        "Tu es un assistant IA utile et honnête. Réponds de manière claire et concise.",
        get_conversation_list()
    )

def delete_conv():
    global current_conversation_id
    if current_conversation_id and current_conversation_id in conversation_history:
        del conversation_history[current_conversation_id]
        current_conversation_id = None
    return [], "Tu es un assistant IA utile.", get_conversation_list()

with gr.Blocks(title="Chatbot Mentorat") as demo:
    gr.Markdown("# 🤖 Chatbot Mentorat")
    gr.Markdown("Votre assistant IA personnel avec historique et personnalisation")

    with gr.Row():
        with gr.Column(scale=1, min_width=280):
            gr.Markdown("### Historique")
            history_display = gr.Textbox(
                label="Conversations",
                interactive=False,
                lines=15,
                placeholder="Aucune conversation"
            )

            with gr.Row():
                btn_new = gr.Button("Nouvelle Conversation", size="sm")
                btn_delete = gr.Button("Supprimer", size="sm")

            gr.Markdown("### Configuration")
            system_prompt = gr.Textbox(
                value="Tu es un assistant IA utile et honnête. Répondsmanière claire et concise.",
                label="Prompt système",
                lines=4
            )

            # --- ON ASSIGNE LE SLIDER À UNE VARIABLE ---
            temp_slider = gr.Slider(
                minimum=0.0, maximum=1.0, value=0.6, step=0.1,
                label="Température (créativité)",
                info="Plus bas = plus précis, plus haut = plus créatif"
            )

        with gr.Column(scale=3):
            gr.Markdown("### Conversation")
            chatbot = gr.Chatbot(height=600, show_label=False, avatar_images=("👤", "🤖"))

            with gr.Row():
                msg = gr.Textbox(label="Votre message", scale=5)
                btn_send = gr.Button("Envoyer", scale=1)


    # --- MISE À JOUR DES INPUTS POUR INCLURE LE SLIDER ---
    btn_new.click(new_conversation, outputs=[chatbot, system_prompt, history_display])
    btn_delete.click(delete_conv, outputs=[chatbot, system_prompt, history_display])

    msg.submit(
        respond, 
        [msg, chatbot, system_prompt, temp_slider], # Slider ajouté ici
        [msg, chatbot]
    ).then(lambda: get_conversation_list(), outputs=[history_display])

    btn_send.click(
        respond, 
        [msg, chatbot, system_prompt, temp_slider], # Slider ajouté ici
        [msg, chatbot]
    ).then(lambda: get_conversation_list(), outputs=[history_display])

    demo.load(lambda: get_conversation_list(), outputs=[history_display])

if __name__ == "__main__":
    demo.launch(share=False, theme=gr.themes.Soft())