import gradio as gr
import requests, secrets, sqlite3, os
from fastapi import FastAPI
from pydantic import BaseModel

# --- Config ---
API_URL = "https://Mauricio-100-agent-ai.hf.space/infer"
DB_PATH = "tokens.db"

# --- SQLite init ---
def init_db():
    conn = sqlite3.connect(DB_PATH)
    c = conn.cursor()
    c.execute("""
        CREATE TABLE IF NOT EXISTS api_tokens (
            id INTEGER PRIMARY KEY AUTOINCREMENT,
            token TEXT UNIQUE,
            description TEXT
        )
    """)
    conn.commit()
    conn.close()

init_db()

# --- FastAPI (optionnel si tu veux exposer aussi côté backend) ---
app = FastAPI()

class Input(BaseModel):
    input: str
    system_prompt: str | None = None
    temperature: float = 0.7
    max_new_tokens: int = 200
    top_p: float = 0.9
    api_token: str | None = None

@app.post("/validate_token")
def validate_token(data: Input):
    conn = sqlite3.connect(DB_PATH)
    c = conn.cursor()
    c.execute("SELECT token FROM api_tokens WHERE token=?", (data.api_token,))
    row = c.fetchone()
    conn.close()
    return {"valid": row is not None}

# --- Fonctions pour Gradio ---
def generate_token(description):
    token = "sk-" + secrets.token_hex(16)  # style OpenAI
    conn = sqlite3.connect(DB_PATH)
    c = conn.cursor()
    c.execute("INSERT INTO api_tokens (token, description) VALUES (?, ?)", (token, description))
    conn.commit()
    conn.close()
    return token

def list_tokens():
    conn = sqlite3.connect(DB_PATH)
    c = conn.cursor()
    c.execute("SELECT id, token, description FROM api_tokens")
    rows = c.fetchall()
    conn.close()
    return "\n".join([f"{r[0]} | {r[1]} | {r[2]}" for r in rows])

def call_gopu(system_prompt, user_prompt, temperature, max_new_tokens, top_p, api_token):
    # Vérifier le token
    conn = sqlite3.connect(DB_PATH)
    c = conn.cursor()
    c.execute("SELECT token FROM api_tokens WHERE token=?", (api_token,))
    row = c.fetchone()
    conn.close()
    if not row:
        return "[Erreur] Token invalide"

    payload = {
        "input": user_prompt,
        "system_prompt": system_prompt,
        "temperature": temperature,
        "max_new_tokens": int(max_new_tokens),
        "top_p": top_p
    }
    try:
        response = requests.post(API_URL, json=payload)
        if response.status_code == 200:
            return response.json().get("generated_text", "")
        else:
            return f"[Erreur {response.status_code}] {response.text}"
    except Exception as e:
        return f"[Exception] {str(e)}"

# --- Interface Gradio ---
with gr.Blocks(title="⚡ GopuOS API Manager") as demo:
    gr.Markdown("## ⚡ GopuOS Client + Gestion des Tokens")

    with gr.Tab("Générer un Token"):
        desc = gr.Textbox(label="Description du token")
        out_token = gr.Textbox(label="Nouveau Token")
        btn_gen = gr.Button("Générer")
        btn_gen.click(fn=generate_token, inputs=desc, outputs=out_token)

    with gr.Tab("Lister les Tokens"):
        out_list = gr.Textbox(label="Tokens existants", lines=10)
        btn_list = gr.Button("Afficher")
        btn_list.click(fn=list_tokens, outputs=out_list)

    with gr.Tab("Appeler le modèle"):
        sys_prompt = gr.Textbox(label="Prompt système")
        user_prompt = gr.Textbox(label="Texte utilisateur")
        temp = gr.Slider(0.1, 1.5, value=0.7, step=0.1, label="Température")
        max_tok = gr.Slider(50, 500, value=200, step=10, label="Max new tokens")
        top_p = gr.Slider(0.1, 1.0, value=0.9, step=0.05, label="Top-p")
        api_token = gr.Textbox(label="API Token")
        output = gr.Textbox(label="Réponse du modèle")
        btn_call = gr.Button("Envoyer")
        btn_call.click(
            fn=call_gopu,
            inputs=[sys_prompt, user_prompt, temp, max_tok, top_p, api_token],
            outputs=output
        )

# Monter Gradio dans FastAPI
app = gr.mount_gradio_app(app, demo, path="/gradio")