app.py

import os
import time
import gradio as gr
import google.generativeai as genai
from typing import Optional, List

# Cargar la clave API desde el entorno
GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set.")

# Configurar la API de Gemini
genai.configure(api_key=GOOGLE_API_KEY)

def transform_history(history):
    """Transforma el historial en el formato esperado por Gemini."""
    new_history = []
    for chat in history:
        new_history.append({"role": "user", "content": chat[0]})
        new_history.append({"role": "assistant", "content": chat[1]})
    return new_history

def bot(files: Optional[List[str]], model_choice: str, system_instruction: Optional[str], history):
    """Procesa la interacción del chatbot."""
    chat_history = transform_history(history)
    
    if system_instruction:
        chat_history.insert(0, {"role": "system", "content": system_instruction})
    
    # Configuración del modelo Flash 1.5
    generation_config = genai.types.GenerationConfig(
        temperature=0.7,
        max_output_tokens=8192,
        top_k=10,
        top_p=0.9
    )
    
    response = genai.ChatCompletion.create(
        model=model_choice,
        messages=chat_history + [{"role": "user", "content": history[-1][0]}],
        generation_config=generation_config
    )

    reply = response['candidates'][0]['content']
    for i in range(len(reply)):
        time.sleep(0.05)
        yield history + [{"role": "assistant", "content": reply[:i + 1]}]

# Interfaz con Gradio
with gr.Blocks() as demo:
    chatbot = gr.Chatbot(elem_id="chatbot", bubble_full_width=False, type="messages")
    
    chat_input = gr.Textbox(
        placeholder="Escribe un mensaje...",
        show_label=False
    )
    
    submit_btn = gr.Button("Enviar")
    system_input = gr.Textbox(placeholder="Instrucción del sistema (opcional)", show_label=True, lines=2)
    model_choice = gr.Dropdown(choices=["gemini-1.5-flash"], value="gemini-1.5-flash", label="Modelo")
    
    submit_btn.click(
        bot,  # Función que manejará la acción del botón
        inputs=[chat_input, model_choice, system_input, chatbot],  # Asegúrate de que las entradas sean válidas
        outputs=chatbot  # El chatbot será actualizado con la respuesta
    )
    
demo.launch()