import os
import google.generativeai as genai
import gradio as gr
from dotenv import load_dotenv

# Carrega variáveis de ambiente
load_dotenv()

# Configura a API do Gemini
GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
genai.configure(api_key=GOOGLE_API_KEY)

# Configurações do modelo
generation_config = {
    "temperature": 0.7,
    "top_p": 0.95,
    "top_k": 40,
    "max_output_tokens": 2048,
}

# Inicializa o modelo
model = genai.GenerativeModel(
    model_name="gemini-1.5-pro",  # ou "gemini-1.5-flash" para mais rápido
    generation_config=generation_config,
)

def chat_with_gemini(message, history):
    """
    Função para interagir com o Gemini
    """
    try:
        # Inicia uma conversa
        chat = model.start_chat(history=[])
        
        # Envia a mensagem e obtém resposta
        response = chat.send_message(message)
        
        return response.text
    except Exception as e:
        return f"Erro: {str(e)}"

# Cria a interface com Gradio
def create_interface():
    with gr.Blocks(theme=gr.themes.Soft(), title="Chat com Gemini") as demo:
        gr.Markdown("""
        # 🤖 Chat com Google Gemini
        ### Converse com o modelo Gemini do Google AI
        """)
        
        chatbot = gr.Chatbot(label="Conversa", height=500)
        
        with gr.Row():
            msg = gr.Textbox(
                label="Sua mensagem",
                placeholder="Digite sua pergunta aqui...",
                scale=9
            )
            send_btn = gr.Button("Enviar", variant="primary", scale=1)
        
        clear_btn = gr.Button("Limpar conversa", variant="secondary")
        
        def respond(message, chat_history):
            if not message:
                return "", chat_history
            
            # Obtém resposta do Gemini
            response = chat_with_gemini(message, chat_history)
            
            # Adiciona à conversa
            chat_history.append((message, response))
            
            return "", chat_history
        
        def clear_chat():
            return []
        
        # Conecta os eventos
        send_btn.click(
            respond,
            inputs=[msg, chatbot],
            outputs=[msg, chatbot]
        )
        
        msg.submit(
            respond,
            inputs=[msg, chatbot],
            outputs=[msg, chatbot]
        )
        
        clear_btn.click(
            clear_chat,
            outputs=[chatbot]
        )
    
    return demo

# Executa a aplicação
if __name__ == "__main__":
    demo = create_interface()
    demo.launch(server_name="0.0.0.0", server_port=7860)