import os
from dotenv import load_dotenv
from langchain_openai import ChatOpenAI
import gradio as gr
import pybase64

# Carrega a chave do .env
load_dotenv()
api_key = os.getenv("OPENROUTER_API_KEY")
# Verifica se a chave está disponível
if not api_key:
    raise ValueError("❌ Variável OPENROUTER_API_KEY não encontrada.")

# Define as variáveis que o LangChain espera
os.environ["OPENAI_API_KEY"] = api_key
os.environ["OPENAI_API_BASE"] = "https://openrouter.ai/api/v1"

# Instancia o modelo
llm = ChatOpenAI(
    model="deepseek/deepseek-r1:free",
    temperature=0.5
)

# 1. Função de resposta (mantida igual à original)
def responder(mensagem):
    try:
        instrucao = 'Responder em Portugues. '
        resposta = llm.invoke(instrucao+mensagem)
        return resposta.content
    except Exception as e:
        import traceback
        return f"❌ Erro:\n{traceback.format_exc()}"

        
# Leitura da imagem
try:
    with open("./robo.png", "rb") as img_file:
        logo_base64 = pybase64.b64encode(img_file.read()).decode('utf-8')
    # Imagen no canto superior esquerdo     
    #img_html = f"""
    #<div style="text-align: center; margin: 20px 0;">
    #    <img src="data:image/png;base64,{logo_base64}" 
    #         style="height: 200px; max-width: 100%; border-radius: 8px;">
    #</div>
    #"""

    # Imagem centraliza
    img_html = f"""
    <div style="display: flex; justify-content: center; margin: 20px 0;">
        <img src="data:image/png;base64,{logo_base64}" 
             style="height: 200px; max-width: 100%; 
                    border-radius: 8px; object-fit: contain;">
    </div>
    """
except:
    with open("./aprender.png", "rb") as img_file:
        error_base64 = pybase64.b64encode(img_file.read()).decode('utf-8')
    img_html = """
    <div style="text-align: center; margin: 20px 0;">
        <img src="data:image/png;base64,{error_base64}" 
             style="height: 200px; max-width: 100%; border-radius: 8px;">
    </div>
    """

# 3. CSS customizado para o layout
#custom_css = """
#logo-container {
#    display: flex;
#    align-items: center;
#    margin-bottom: 15px;
#}
#.title {
#    flex-grow: 1;
#    text-align: center;
#}
#"""

# 4. Criar a interface com Blocks
#with gr.Blocks(css=custom_css) as app:
with gr.Blocks() as app:
    # Container para logo e título
    with gr.Column():#elem_id="logo-container"):
        gr.HTML(img_html)
        gr.Markdown("""
        <div class="title">
            <h1>Chatbot com IA Generativa</h1>
            <p>Modelo DeepSeek via OpenRouter com retorno direto.</p>
        </div>
        """)
    
    # Área de chat (simulando a Interface original)
    with gr.Row():
        message = gr.Textbox(placeholder="Digite sua pergunta aqui", label="Mensagem")
        output = gr.Textbox(label="Resposta do Chatbot", interactive=False)
    
    message.submit(
        responder,
        inputs=message,
        outputs=output
    )

# 5. Lançar o aplicativo
app.launch(share=True)