import gradio as gr
import requests
import os
import json

API_KEY = os.getenv('API_KEY')
INVOKE_URL = "https://api.nvcf.nvidia.com/v2/nvcf/pexec/functions/0e349b44-440a-44e1-93e9-abe8dcb27158"
FETCH_URL_FORMAT = "https://api.nvcf.nvidia.com/v2/nvcf/pexec/status/"

headers = {
    "Authorization": f"Bearer {API_KEY}",
    "Accept": "application/json",
    "Content-Type": "application/json",
}

BASE_SYSTEM_MESSAGE = "I carefully provide accurate, factual, thoughtful, nuanced answers and am brilliant at reasoning."

def call_nvidia_api(history_api, system_message, max_tokens, temperature, top_p):
    messages = [{"role": "system", "content": system_message}] if system_message else []
    for msg in history_api:
        if msg[1]:  # Se existe uma resposta do assistente
            messages.append({"role": "user", "content": msg[0]})
            messages.append({"role": "assistant", "content": msg[1]})

    payload = {
        "messages": messages,
        "temperature": temperature,
        "top_p": top_p,
        "max_tokens": max_tokens,
        "stream": False
    }

    session = requests.Session()
    response = session.post(INVOKE_URL, headers=headers, json=payload)
    while response.status_code == 202:
        request_id = response.headers.get("NVCF-REQID")
        fetch_url = FETCH_URL_FORMAT + request_id
        response = session.get(fetch_url, headers=headers)
    response.raise_for_status()
    response_body = response.json()

    if response_body.get("choices"):
        assistant_message = response_body["choices"][0]["message"]["content"]
        return assistant_message, response_body["choices"][0]
    else:
        return "Desculpe, ocorreu um erro ao gerar a resposta.", None

def chatbot_submit(message, chat_history_ui, chat_history_api, system_message, max_tokens_val, temperature_val, top_p_val):
    assistant_message, api_response = call_nvidia_api(chat_history_api, system_message, max_tokens_val, temperature_val, top_p_val)

    chat_history_ui.append([message, assistant_message])

    if api_response:
        chat_history_api.append([message, assistant_message])

    return assistant_message, chat_history_ui, chat_history_api

system_msg = gr.Textbox(BASE_SYSTEM_MESSAGE, label="System Message", placeholder="System prompt.", lines=5)
max_tokens = gr.Slider(20, 1024, label="Max Tokens", step=20, value=1024)
temperature = gr.Slider(0.0, 1.0, label="Temperature", step=0.1, value=0.2)
top_p = gr.Slider(0.0, 1.0, label="Top P", step=0.05, value=0.7)
# Gradio interface setup
with gr.Blocks() as demo:
    chat_history_state_ui = gr.State([])
    chat_history_state_api = gr.State([])
    system_msg = gr.Textbox(BASE_SYSTEM_MESSAGE, label="System Message", placeholder="System prompt.", lines=5)
    max_tokens = gr.Slider(20, 1024, label="Max Tokens", step=20, value=1024)
    temperature = gr.Slider(0.0, 1.0, label="Temperature", step=0.1, value=0.2)
    top_p = gr.Slider(0.0, 1.0, label="Top P", step=0.05, value=0.7)
    chatbot = gr.ChatInterface(
        fn=chatbot_submit,
        inputs=[gr.Textbox(label="Your Message"), chat_history_state_ui, chat_history_state_api, system_msg, max_tokens, temperature, top_p],
        outputs=[gr.Text(label="Assistant Response"), chat_history_state_ui, chat_history_state_api],
        title="Chatbot Interface"
    )

demo.launch()