import gradio as gr
import requests
import os
import random
import base64
from PIL import Image
import io


def resize_image(image_path, max_size=(800, 800), quality=85):
    with Image.open(image_path) as img:
        img.thumbnail(max_size, Image.ANTIALIAS)
        buffer = io.BytesIO()
        img.save(buffer, format="JPEG", quality=quality)
        return buffer.getvalue()
        
def filepath_to_base64(image_path):
    img_bytes = resize_image(image_path)
    img_base64 = base64.b64encode(img_bytes)
    return f"data:image/jpeg;base64,{img_base64.decode('utf-8')}"

# A chave da API é lida de uma variável de ambiente para maior segurança.
api_key = os.getenv('API_KEY')

def call_fuyu_8b_api(image_path, content, temperature=0.2, top_p=0.7, max_tokens=1024, seed=None):
    print(f"Caminho da imagem recebida: {image_path}")
    print(f"Conteúdo: {content}")
    print(f"Temperatura: {temperature}")
    print(f"Top P: {top_p}")
    print(f"Max Tokens: {max_tokens}")
    print(f"Seed: {seed}")
    image_base64 = filepath_to_base64(image_path)
    invoke_url = "https://api.nvcf.nvidia.com/v2/nvcf/pexec/functions/9f757064-657f-4c85-abd7-37a7a9b6ee11"
    headers = {
        "Authorization": f"Bearer {api_key}",
        "accept": "text/event-stream",
        "content-type": "application/json",
    }
    if seed is None or seed == "":
        seed = random.randint(0, 18446744073709552000)
    else:
        try:
            seed = int(seed)
        except ValueError:
            return "Seed must be an integer."

    payload = {
        "messages": [
            {
                "content": f"{content} <img src=\"{image_base64}\" />",
                "role": "user"
            }
        ],
        "temperature": temperature,
        "top_p": top_p,
        "max_tokens": max_tokens,
        "stream": True,
        "seed": seed
    }
    print(payload)
    response = requests.post(invoke_url, headers=headers, json=payload, stream=True)
    if response.status_code != 200:
        print(f"Erro na requisição: {response.status_code}")
        try:
            error_details = response.json()
            print(error_details)
        except ValueError:
            print(response.text)
    else:
        print(response)
        response_text = ""
        for line in response.iter_lines():
            if line:
                decoded_line = line.decode("utf-8")
                if "content" in decoded_line:
                    response_text += decoded_line.split('"content":"')[1].split('","finish_reason')[0]
        return response_text

# Definindo os componentes da interface
content_input = gr.Textbox(lines=2, placeholder="Enter your content here...", label="Content")
image_input = gr.Image(type="filepath", label="Upload Image")
temperature_input = gr.Slider(minimum=0, maximum=1, step=0.01, value=0.2, label="Temperature")
top_p_input = gr.Slider(minimum=0, maximum=1, step=0.01, value=0.7, label="Top P")
max_tokens_input = gr.Slider(minimum=1, maximum=1024, step=1, value=1024, label="Max Tokens")
seed_input = gr.Textbox(label="Seed (optional)")

# Criando a interface Gradio
iface = gr.Interface(fn=call_fuyu_8b_api,
                     inputs=[image_input, content_input, temperature_input, top_p_input, max_tokens_input, seed_input],
                     outputs="text",
                     title="Fuyu-8B API Explorer",
                     description="Explore the capabilities of Fuyu-8B multi-modal transformer.")

# Executando a interface
iface.launch()